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  <rdf:Description>
        <dcterms:issued>1995</dcterms:issued>
        <dc:language>es</dc:language>
        <dc:creator>Corden, W. Max</dc:creator>
        <dc:contributor>Corden, W. Max</dc:contributor>
        <dcterms:title>Una zona de libre comercio en el Hemisferio Occidental: posibles implicancias para América Latina</dcterms:title>
        <dcterms:isPartOf>En: La liberalización del comercio en el Hemisferio Occidental - Washington, DC : BID/CEPAL, 1995 - p. 13-40</dcterms:isPartOf>
        <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-01-02T14:51:16Z</dcterms:available>
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2007

Social Panorama
of latin

America

The Social Panorama of Latin America is prepared each year by the Social Development Division and the Statistics and Economic
Projections Division of ECLAC, under the supervision of Andras Uthoff and Luis Beccaria, respectively.
Work on the 2007 edition was coordinated by Andras Uthoff, Martín Hopenhayn and Juan Carlos Feres, who, together with Irma
Arriagada, Simone Cecchini, Ernesto Espíndola, Fabiana Del Popolo, Xavier Mancero, Rubén Katzman, Ana María Oyarce,
Jorge Rodríguez and Pablo Villatoro, were also responsible for preparing the individual chapters. Substantive inputs, statistical
information and cartographic material were prepared and processed by Mario Acuña, María de la Luz Avendaño, Carlos Daroch,
Fabiana Del Popolo, Andrés Espejo, Ernesto Espíndola, Marco Galván, Daniela González, Sandra Huenchuan, Miguel Ojeda, Ana
María Oyarce, Felipe Rivera, Elisa Heynig, Carlos Howes, Sandra Lafosse, Ximena Rodríguez and Nora Ruedi.
The section entitled “Internal migration and development in Latin America and the Caribbean: policy challenges, changes and
continuity” was produced by the Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC,
with contributions from the IDB/ECLAC project “Migration and development: the case of Latin America” (internal migration
component) and support from the United Nations Population Fund (UNFPA), under the ECLAC/UNFPA Regional Programme on
Population and Development in Latin America and the Caribbean, 2005-2007.
The subsection of the chapter on the social agenda entitled “Health programmes and policies for indigenous peoples of Latin
America” was prepared jointly by the Social Development Division and CELADE - Population Division of ECLAC, with support
from the Project on Advances in Policies and Programmes for Indigenous Peoples of Latin America since the Implementation of
the International Decade for Indigenous Peoples, financed by the Government of France.

Explanatory notes
The following symbols are used in tables in this edition of the Social Panorama of Latin America:
Three dots (…) indicate that data are not available or are not separately reported.
A dash (–) indicates that the amount is nil or negligible.
A point (.) is used to indicate decimals.
Use of a hyphen (-) between years (e.g., 2001-2006) indicates reference to the complete period considered, including the beginning and end years.
The word “tons” means metric tons and the word “dollars” means United States dollars, unless otherwise specified.
References to annual rates of growth or variation signify compound annual rates, unless otherwise specified.
Individual figures and percentages in tables do not necessarily add up to the corresponding totals because of rounding.

United Nations publication
ISBN 978-92-1-323118-0
ISSN printed version: 1014-7810 ISSN online version: 1684-1387
LC/G.2351-P
Número de venta: S.07.II.G.124
Copyright © United Nations, May 2008. All rights reserved
Printed in Santiago, Chile
Request for authorization to reproduce this work in whole or in part should be sent to the Secretary of the Publication Board, United Nations
Headquarters, New York, N.Y. 10017, United States of America. Member States and their governmental institutions may reproduce this work without
prior authorization, but are requested to mention the source and to inform the United Nations of such reproduction.

Social Panorama of Latin America • 2007

3

Contents

Abstract ............................................................................................................................................................................. 
Summary ............................................................................................................................................................................. 

13
17

Chapter I
Advances in poverty reduction and challenges in attaining social cohesion................................

49

 A. Poverty trends................................................................................................................................................................... 
 1. The Economic Situation.............................................................................................................................................. 
.
 2. Poverty in the region.................................................................................................................................................... 
 3. Poverty and indigence in the different countries......................................................................................................... 
 B.  Progress towards meeting the first target of the millennium development goals............................................................. 
 C. Factors linked with poverty reduction.............................................................................................................................. 
 1. Preliminary considerations.......................................................................................................................................... 
 2. The factors linked to poverty reduction, 1990 - 2005................................................................................................. 
.
 3. Public policy challenges.............................................................................................................................................. 
 D.  Poverty and residential segregation in urban areas. ......................................................................................................... 
.
 1. Employment................................................................................................................................................................. 
 2. Education..................................................................................................................................................................... 
 3. The institutional alienation of adolescents.................................................................................................................. 
.
 4. The reproductive behaviour of adolescents ................................................................................................................ 
 5. Conclusions................................................................................................................................................................. 
.
 E.  Poverty, exclusion and social cohesion: psycho-social divides........................................................................................ 
 1. Expectations of inter-generational social mobility...................................................................................................... 
 2. Confidence in state institutions and participation in politics....................................................................................... 
 3. Discrimination............................................................................................................................................................. 

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Economic Commission for Latin America and the Caribbean (ECLAC)

Chapter II
Public social expenditure and the need for a social contract in Latin America.............................

99

 A.
 B.


 C.
 D.

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115
119

Level and composition of public social expenditure ....................................................................................................... 
Orientation and redistributive impact of public social expenditure. ................................................................................ 
.
1. Orientation of public social spending.......................................................................................................................... 
2. Orientation of sectoral spending.................................................................................................................................. 
3. Redistributive impact of public social spending.......................................................................................................... 
4. Social welfare spending and anti-poverty programmes. ............................................................................................. 
.
Public social spending by groups of countries: towards a composite typology............................................................... 
Public spending and the social contract............................................................................................................................ 

Chapter III
The quality of education: inequalities that go beyond access and educational progression. ..... 151
.
 A.


 B.


 C.


 D.

Advances in the right to education: access, progression and completion. ....................................................................... 
.
1. Access to education..................................................................................................................................................... 
2. Educational progression.............................................................................................................................................. 
.
3. Completing levels of education................................................................................................................................... 
Inequality in educational opportunities: more than differences in income....................................................................... 
1. Gender differences ..................................................................................................................................................... 
2. Inequities between urban and rural areas and ethnic groups ...................................................................................... 
3. Transmission of educational opportunities ................................................................................................................. 
Quality of education: another manifestation of inequality............................................................................................... 
1. Quality of education: a variety of approaches............................................................................................................. 
2. Measuring the quality of education............................................................................................................................. 
3. Factors associated with differences in educational results.......................................................................................... 
Conclusion........................................................................................................................................................................ 

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Chapter IV

Internal migration and development in Latin America and the Caribbean:
continuity, changes and policy challenges........................................................................................ 195
 A.
 B.


 C.
 D.


 E.


Introduction . .................................................................................................................................................................... 
Theoretical framework. .................................................................................................................................................... 
.
1. Internal migration and social and economic development ......................................................................................... 
2. Relationship between internal migration and development. ....................................................................................... 
.
3. Contribution of migration to the convergence or divergence of the human resource base at the national level......... 
4. Changes in the patterns and characteristics of internal migration caused by urbanization......................................... 
5. Emigrants as a representative sample of the population.............................................................................................. 
6. Integration of migrants in places of destination.......................................................................................................... 
.
7. Relevant definitions and clarifications........................................................................................................................ 
Internal migration and development in countries............................................................................................................. 
Internal migration and countries’ development................................................................................................................ 
1. Expulsive major administrative divisions.................................................................................................................... 
2. Attractive major administrative divisions.................................................................................................................... 
3. “Changing” major administrative divisions................................................................................................................ 
.
4. Conclusion................................................................................................................................................................... 
Effect of internal migration on the areas of origin and destination.................................................................................. 
1. Migration and territorial poverty traps........................................................................................................................ 
.

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Social Panorama of Latin America • 2007

5


 F.


 G.
 H.


 I.


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2. Migration and sociodemographic disparities between territories................................................................................ 
Urbanization and migration.............................................................................................................................................. 
1. Direct estimates of migration between countryside and city....................................................................................... 
2. Indirect estimates......................................................................................................................................................... 
Internal migration, deconcentration of the city system and metropolitan reconfiguration. ............................................. 
.
Migration and individual characteristics.......................................................................................................................... 
.
1. Selectivity.................................................................................................................................................................... 
2. Integration in place of destination............................................................................................................................... 
3. Migration histories....................................................................................................................................................... 
Policy orientations............................................................................................................................................................ 
1. Principles..................................................................................................................................................................... 
2. History......................................................................................................................................................................... 
3. Contemporary situation, strategies and challenges...................................................................................................... 

Chapter V
S
 ocial agenda
Public policies and health programmes for indigenous peoples in Latin America....................... 235
Introduction ............................................................................................................................................................................. 
 A. Indigenous peoples and the right to health: juridical advances and public policy implications. ..................................... 
.
 1. Health rights of indigenous peoples: minimum standards and main dimensions........................................................ 
 2. Constitutional framework and legislation concerning the health of indigenous peoples ........................................... 
 3. Public institutions relating to indigenous peoples and health..................................................................................... 
 B. Health programmes and policies for indigenous peoples: how much and in what way has progress been made? ......... 
 1. Health sector reforms: is the outlook more favourable?.............................................................................................. 
 2. Public health policies and indigenous peoples: concepts and regional situation. ...................................................... 
.
 3. Programmes of, for and with indigenous peoples: passive recipients or rights-holders? . ........................................ 
 4. Main achievements and difficulties ............................................................................................................................ 
 5. Indigenous management and participation.................................................................................................................. 
 6. Health information: how to measure the advances?.................................................................................................... 
 C. Closing remarks and policy recommendations . .............................................................................................................. 
 D. International agenda. Tenth session of the Regional Conference on Women in Latin America and the Caribbean........ 
.

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Bibliography. ........................................................................................................................................ 273
.
Statistical Appendix............................................................................................................................. 281
CEPAL Publications............................................................................................................................. 465
Tables
Table I.1

Latin America (20 countries): selected socio-economic indicators, 1990-2006................................................. 

50

Table I.2 

Latin America: poverty and indigence rates, 1980-2006.................................................................................... 

52

Table I.3 

Latin America: poor and indigent population, 1980-2006.................................................................................. 

52

Table I.4 

Latin America (18 countries): poverty and indigence indicators, 1990-2006..................................................... 

54

Table I.5 

Latin America (6 countries): total fertility rate, by socio-economic strata......................................................... 

66

Table I.6


Latin America (16 countries): per capita family income and breakdown of its variation by changes
in labour income per employed person, the overall employment rate and per capita non-labour income
(in multiples of the poverty line), by deciles of income distribution, 1989-1995 and 2001-2005...................... 

71

6

Table I.7


Table I.8

Table I.9

Table I.10


Table II.1

Table II.2
Table II.3
Table II.4

Table II.5
Table II.6

Table II.7

Table II.8

Table II.9

Table II.10

Table II.11

Table II.12

Table II.13
Table II.14

Table II.15

Table II.16
Table II.17
Table II.18
Table II.19
Table II.20
Table III.1

Table III.2


Table III.3


Economic Commission for Latin America and the Caribbean (ECLAC)

Latin America (16 countries): country typology based on trends in the overall employment rate,
labour income per employed person and non-labour income in population deciles that include
poor households, 1990-2005............................................................................................................................... 
Brazil (metropolitan region of São Paulo): average wages of workers by educational level,
economic sector and the social composition of the district in which the company is located, 2000.................. 
Brazil (three cities): percentage of the population aged 15 to 24 that does not study, work or seek work,
by social composition of the area of residence, 2004......................................................................................... 
.
Uruguay (Montevideo): percentage of unemancipated boys aged 15 to 19 who do not study,
work or seek work, by educational context of the segment and the educational background
of the home, 1996................................................................................................................................................ 
Latin America (18 countries): incidence of public social spending by income quintile and
concentration coefficient..................................................................................................................................... 
Conditional transfer programmes in Latin America and the Caribbean. ............................................................ 
.
Typology of countries, by challenges to social contracts.................................................................................... 
Latin America and the Caribbean: estimated spending by target population on education,
social security and welfare and health, by groups of countries, 2004-2005....................................................... 
Latin America and the Caribbean (21 countries): per capita public social spending.......................................... 
Latin America and the Caribbean (21 countries): public social spending as a percentage of gross
national product................................................................................................................................................... 
Latin America and the Caribbean (21 countries): public social spending
as a percentage of total public spending. ............................................................................................................ 
.
Latin America and the Caribbean (21 countries): public social spending on
education as a percentage of gross national product........................................................................................... 
Latin America and the Caribbean (21 countries): public social spending on
health as a percentage of gross national product................................................................................................. 
Latin America and the Caribbean (20 countries): public social spending on
social security and welfare as a percentage of gross national product................................................................ 
Latin America and the Caribbean (21 countries): public social spending on
housing and others as a percentage of gross national product............................................................................ 
Latin America and the Caribbean (21 countries): per capita public
social spending on education. ............................................................................................................................. 
.
Latin America and the Caribbean (21 countries): public social spending on health, per capita......................... 
Latin America and the Caribbean (20 countries): public social spending on
social security and welfare, per capita................................................................................................................ 
.
Latin America and the Caribbean (21 countries): public social spending
per capita on housing and others......................................................................................................................... 
Latin America (18 countries): orientation of education spending by primary income quintile.......................... 
Latin America (16 countries): orientation of health spending by primary income quintile................................ 
Latin America (18 countries): orientation of social security spending by primary income quintile................... 
Latin America (11 countries): orientation of welfare spending by primary income quintile.............................. 
Latin America (18 countries): redistributive effect of the various social spending items................................... 
Latin America (18 countries): attendance rates in different cycles of education among
school-age children and young people, nationwide totals, around 1990 and 2005............................................. 
Latin America (18 countries): timely school progression among students aged
10 to 14 and students and graduates aged 15 to 19, by selected quintiles
of per capita income, nationwide totals, around 1990 and 2005......................................................................... 
Latin America (18 countries): young people of different age groups who have completed
primary education, early secondary and upper secondary and at least five years of tertiary
education, by selected quintiles of per capita income, around 1990 and 2005................................................... 

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Social Panorama of Latin America • 2007

Table III.4

Table III.5

Table III.6

Table III.7

Table III.8


Table III.9

Table III.10

Table IV.1

Table IV.2

Table IV.3


Table IV.4

Table IV.5


Table IV.6


Table IV.7

Table IV.8
Table IV.9
Table IV.10

Table IV.11

Table IV.12

Table IV.13

Table IV.14

Table V.1

Table V.2
Table V.3

Latin America (18 countries): selected educational indicators for children
and young people of different age groups, by sex, nationwide totals................................................................. 
Latin America (18 countries): selected educational indicators for children and young people
of different age groups, by geographical area, nationwide totals........................................................................ 
Latin America (18 countries): completion of the various education cycles,
by poverty status, nationwide totals.................................................................................................................... 
Latin America (18 countries): completion of the various education cycles, by household
educational background, nationwide totals......................................................................................................... 
Latin America (5 countries), selected OECD countries (7 countries) and others (5 countries):
scores and correlations of reading test according to various characteristics of the teaching
staff and school community................................................................................................................................ 
Latin America (5 countries), selected OECD countries (7 countries) and others (5 countries):
scores and correlations of reading test according to main extra-scholastic factors............................................ 
.
Latin America (5 countries), selected OECD countries (7 countries) and others (5 countries):
reading test scores and student distribution by school characteristics................................................................ 
Latin America and the Caribbean: percentage of migrants between major and minor administrative
divisions by migration type (absolute or recent), countries and years available. ............................................... 
.
Simple correlation between percentage of migrants (four types) and the human development index
(HDI), 2000 and 1990 census rounds, selected countries................................................................................... 
Latin America and the Caribbean: simple linear correlation between the human development index
(HDI) and the net internal migration rate at the level of major administrative divisions (MAD),
selected countries, censuses from the 2000 round.............................................................................................. 
Latin America and the Caribbean (selected countries): classification of major administrative divisions
by internal migration status in 1990 and 2000 census rounds. ........................................................................... 
.
Latin America and the Caribbean (selected countries): major administrative divisions (MAD)
belonging to historically depressed subnational regions with net emigration, by effect of internal
migration on the age structure and education level of the population................................................................ 
.
Latin America and the Caribbean (selected countries): correlations between selected
sociodemographic variables and their variation due to the effect of recent internal migration,
censuses from the 2000 round............................................................................................................................. 
Population aged 5 and above: direct estimates of recent migration between urban and rural areas:
countries whose census includes relevant questions, 2000 round of censuses................................................... 
Population aged 10 and above: net rural-to-urban migration and urban population growth.............................. 
Bolivia: population aged five and above (indigenous and non-indigenous)....................................................... 
Latin America (selected countries): internal migration indicators for three main metropolitan areas,
1990 and 2000 census rounds............................................................................................................................. 
.
Migrants between major administrative divisions (MAD) and minor administrative divisions (MIAD),
selected characteristics according to ethnicity, 2000 census round.................................................................... 
.
Latin America: standardization of workforce participation rate among recent migrants between major
administrative divisions (MAD), selected countries, 1990 and 2000 census rounds.......................................... 
Latin America: standardization of migrant unemployment rate, selected countries,
1990 and 2000 census rounds............................................................................................................................. 
.
Migration typology combining lifetime and recent migration at the level of minor administrative
division (MIAD), according to ethnicity............................................................................................................. 
Specific rights in the area of health related to each of the five dimensions of the minimum standard
for indigenous peoples’ rights............................................................................................................................. 
Latin America (16 countries): special legislation on the health of indigenous peoples...................................... 
Latin America (16 countries): health policies and indigenous peoples............................................................... 

7

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Figures
Figure I.1
Figure I.2

Figure I.3

Figure I.4

Figure I.5

Figure I.6

Figure I.7

Figure I.8

Figure I.9
Figure I.10

Figure I.11

Figure I.12

Figure I.13


Figure I.14

Figure I.15

Figure I.16

Figure I.17

Figure I.18

Figure I.19

Figure I.20

Figure I.21

Figure I.22

Figure I.23

Figure I.24

Figure I.25


Latin America: poverty and indigence rates, 1980-2007.................................................................................... 
Latin America (16 countries): poverty and indigence rates, around 2002-2005
and around 2002-2006......................................................................................................................................... 
Latin America (17 countries): progress in reducing extreme poverty and total poverty
between 1990 and 2007....................................................................................................................................... 
Latin America (16 countries): per capita GDP growth rates needed to halve the 1990
extreme poverty rate by 2015.............................................................................................................................. 
Latin America (18 countries): percentage distribution of households and families in different stages
of the family life cycle, by income quintile, urban areas, around 2005.............................................................. 
Latin America (18 countries): working-age population and participation in economic activity,
by income deciles, national totals, around 2005................................................................................................. 
Latin America (18 countries): unemployment rate, employment rate and proportion of total workers
employed in the formal sector of the economy, by income decile, national totals, around 2005....................... 
Latin America (18 countries): participation in economic activity of men and women,
by income deciles, national total, around 2005................................................................................................... 
Determinants of changes in poverty levels, deciles I-IX.................................................................................... 
.
Uruguay (Montevideo): open unemployment rate, by average educational level of the
corresponding census district, by age and years of schooling, 1996. ................................................................. 
.
Uruguay (Montevideo): own-account workers, by average educational level of the
corresponding census district and years of schooling, 1996............................................................................... 
Uruguay (Montevideo): private-sector employees without health coverage or access to the
public health service, by years of schooling and educational context of the census district, 1996.................... 
.
Uruguay (Montevideo): neighbourhoods ordered by the percentage of high-status jobs and males
aged 15 to 24 years who do not study or work and live in households in which the adults have less than
nine years of schooling, 1996.............................................................................................................................. 
Brazil (Rio de Janeiro): percentage of women aged 15 to 18 years who are mothers, by level of education
and income quintile of the weighting area in which they live, 2000.................................................................. 
.
Chile (Santiago): percentage of women aged 15 to 19 years who are mothers, by level of education and
income quintile of the census district in which they live, 2002.......................................................................... 
Uruguay (Montevideo): neighbourhoods ordered by percentage of unmarried mothers aged 15 to 19 years,
with up to nine years of schooling, and percentage of high-status jobs, 1996.................................................... 
Latin America (18 countries): current personal well-being, future well-being
of children and availability of basic goods and services in the home, 2006....................................................... 
Latin America (18 countries): current personal well-being, future well-being
of children and perceptions of the social structure, 2006.................................................................................... 
Latin America (18 countries): current personal well-being, future well-being
of children, by area of residence and assets in the home, 2006.......................................................................... 
Latin America (18 countries): future well-being of children and availability
of basic goods and services in the home, 2006................................................................................................... 
Latin America (18 countries): confidence in State institutions, sufficiency
of household income and per capita GDP of the country, 2006.......................................................................... 
Latin America (18 countries): confidence in State institutions by income sufficiency
of the household, confidence in the neighbourhood and area of residence, 2006. ............................................. 
.
Latin America (18 countries): confidence in State institutions,by sufficiency of
household income and country, 2006.................................................................................................................. 
Latin America (17 countries): political participation, availability of goods and services
in the home, 2006................................................................................................................................................ 
Latin America (18 countries): people who perceive discrimination, by sufficiency
of household income and country, 2006. ............................................................................................................ 
.

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Social Panorama of Latin America • 2007

Figure I.26

Figure I.27


Latin America (18 countries): people who perceive discrimination,
by sufficiency of household income and area of residence, 2006....................................................................... 
Latin America (18 countries): main causes of discrimination cited
by members of households with insufficient incomes, 2006.............................................................................. 

Figure II.1
Figure II.2

Figure II.3

Figure II.4

Figure II.5

Figure II.6

Figure II.7

Figure II.8

Figure II.9


Figure II.10

Figure II.11

Figure II.12
Figure II.13
Figure II.14
Figure II.15

Latin America (21 countries): per capita public social spending, 1990-1991 to 2004-2005.............................. 
Latin America (21 countries): public social spending as a percentage of GDP,
1990-1991 to 2004-2005..................................................................................................................................... 
Latin America and the Caribbean: ratio of per capita GDP to public social spending as
a percentage of GDP. .......................................................................................................................................... 
.
Latin America and the Caribbean (21 countries): public social spending as a percentage
of GDP, by sector, 1990-1991 to 2004-2005....................................................................................................... 
Latin America and the Caribbean (21 countries): annual variation in total public social
spending and GDP............................................................................................................................................... 
Latin America (18 countries): distribution of public social spending by primary income
quintiles, 1997-2004............................................................................................................................................ 
Latin America (11 countries): distribution of public spending on education, overall and
by level of education, by primary income quintile, 1997-2004.......................................................................... 
Latin America (18 countries): distribution of public spending on health and of primary
and hospital care, by primary income quintiles, 1997-2004............................................................................... 
Latin America (11 countries): distribution of public spending on social welfare and
examples of direct monetary transfers from certain conditional transfer programmes,
by primary income quintile, 1997-2004.............................................................................................................. 
Latin America (18 countries): redistributive effect of public social spending on income,
by primary income quintile, 1997-2004.............................................................................................................. 
Latin America (18 countries): breakdown of spending by primary income distribution
quintiles, 1997-2004............................................................................................................................................ 
Number of dependents per formal worker and per capita GDP.......................................................................... 
Trends in public social spending by groups of countries, percentages of GDP.................................................. 
Spending trends over the business cycle............................................................................................................. 
Levels of per capita GDP and social spending by target population................................................................... 

Figure III.1

Figure III.2

Figure III.3


Figure III.4

Figure III.5

Figure III.6

Figure III.7

Figure III.8


Latin America (17 countries): school attendance rates among school-age children and
young people, irrespective of their cycle, by selected per capita income quintiles, around 2005...................... 
Latin America and the Caribbean (30 countries/territories): students of general secondary
school programmes who repeated the school year, 2004.................................................................................... 
Latin America (17 countries): children and young people achieving timely progression in
primary and secondary education cycles, by household per capita income deciles,
around 1990 and 2005......................................................................................................................................... 
Latin America (19 countries): completion of cycles of education among young people
aged 15 to 19 (primary), 20 to 24 (secondary) and 25 to 29 (tertiary), around 1990 and 2005.......................... 
Latin America (18 countries): indicators of educational access and achievement, by sex and
index of disparity between men and women, around 2005................................................................................. 
Latin America (16 countries): educational achievement by area of residence and ethnic group,
around 2005......................................................................................................................................................... 
Latin America (18 countries): educational completion among different age groups, by education
background of household, around 2005.............................................................................................................. 
Latin America (5 countries), OECD (27 countries) and others (11 countries): distribution of
15-year old students, by level of performance in the 2000 PISA language test.................................................. 

9

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10

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure III.9


Figure III.10

Figure III.11

Figure III.12

Figure III.13


Figure III.14


Latin America (5 countries), OECD (25 countries) and others (11 countries):
average scores in the 2000 PISA language test among tenth-grade students, 2000 per capita
GDP in purchasing power parity dollars and the Gini coefficient...................................................................... 
Latin America (17 countries): average annual ratio of teachers’ income and wages to those
of other waged professionals and technical workers, around 2005. ................................................................... 
.
Latin America (5 countries), selected OECD countries (7 countries) and others (5 countries):
range and categories of performance for the highest scoring decile of tenth-grade students............................. 
Latin America (5 countries), selected OECD countries (7 countries) and others (5 countries):
language test scores of tenth-grade students, by parents’ educational level....................................................... 
.
Latin America (5 countries), selected OECD countries (7 countries) and others (5 countries):
proportion of tenth-grade students attending educationally well-equipped schools, by quartiles
of parents’ socio-occupational status................................................................................................................... 
Latin America (5 countries): distribution of levels of performance in the reading test among
tenth-grade students, by socio-occupational status of their parents and educational equipment
of their schools.................................................................................................................................................... 

Figure IV.1


Ratio between net rural-to-urban migration from 1990 to 2000 and the rural and urban
population in 1990............................................................................................................................................... 

219

Box I.1
Box I.2
Box I.3
Box I.4
Box I.5
Box I.6
Box I.7

Method used for poverty measurement............................................................................................................... 
Updating the methodology for measuring poverty............................................................................................. 
.
Poverty, inequality and vulnerability in the Caribbean....................................................................................... 
Indicators for measuring poverty........................................................................................................................ 
The demographic dividend.................................................................................................................................. 
Methodology used for analysing per capita income trends................................................................................. 
The Latinobarómetro study................................................................................................................................. 

57
57
58
60
66
70
91

Box II.1
Box II.2
Box II.3
Box II.4
Box II.5
Box II.6

The role of the State in the financing of higher education.................................................................................. 
Social policy and reduction of poverty: optimizing social spending.................................................................. 
Early conditional transfer programmes............................................................................................................... 
Conditional transfers in Cuba: a comprehensive improvement course for young people.................................. 
.
Countercyclical policies in Chile........................................................................................................................ 
Updating of social spending................................................................................................................................ 

106
109
112
114
121
122

Box III.1

Box III.2
Box III.3
Box III.4
Box III.5
Box III.6
Box III.7

Duration of education cycles, compulsory nature of secondary education and indicators
used to measure educational inequality............................................................................................................... 
Pre-school education coverage in Chile.............................................................................................................. 
Universalization of higher education in Cuba..................................................................................................... 
Sandwich education for the third cycle of general basic education, Province of Santa Fe, Argentina............... 
Selected opinions on affirmative action in Brazilian universities....................................................................... 
Notions of quality in different theoretical approaches........................................................................................ 
PISA skills assessment tests................................................................................................................................ 

153
155
161
166
169
171
173

Box IV.1

Two options for measuring recent migration with censuses............................................................................... 

200

Box V.1
Box V.2

The right to health of indigenous peoples in various international instruments................................................. 
National health care policy for indigenous peoples in Brazil............................................................................. 

239
247

175
176
177
178

179

180

Boxes

Social Panorama of Latin America • 2007

Box V.3

Box V.4

Box V.5

Public policies and programmes for indigenous health in the Bolivarian
Republic of Venezuela and Colombia................................................................................................................. 
Regional observatory for health equity in terms of gender and the Mapuche
people, region of Araucanía, Chile...................................................................................................................... 
Tenth Regional Conference on Women in Latin America and the Caribbean.................................................... 
.

11

250
255
261

Maps
Map IV.1

Map IV.2


South America (selected countries): major administrative division by
migratory status (census rounds 1990 and 2000)................................................................................................ 
Central America and the Caribbean (selected countries): major administrative
division by migratory status (census rounds 1990 and 2000)............................................................................. 

233
234

Social Panorama of Latin America • 2007

13

Abstract

Per capita GDP has grown more in 2003-2007 than at any
other time since the 1970s. ECLAC projections indicate
that this trend will continue in 2008, which will thus be
the fifth year in a row in which per capita GDP has risen
at over 3% per annum. This increase has made further
progress in poverty reduction possible, together with a
decline in unemployment. Some countries have seen
improvements in income distribution as well. A number of
problems persist, however, and Latin America continues to
lag behind other regions in various areas. Levels of social
and economic inequality remain extremely high. After
rising sharply during the past decade, social expenditure
—measured as a percentage of GDP— has been levelling
off and continues to fall short in terms of the coverage of
existing social needs. In addition, migratory flows continue
to be spurred by unequal levels of development in various
locations and areas within individual countries.
The Social Panorama of Latin America, 2007 provides
the latest poverty estimates available for the countries of
Latin America. These estimates indicate that 36.5% of
Latin America’s population (195 million people) were
poor and 13.4% (71 million) were extremely poor.
As noted in the chapter devoted to the subject of
poverty, these percentages signal a 3.3% drop in poverty
and a 2.0% decrease in extreme poverty, or indigence, from
these indicators’ 2005 levels. This means that 14 million
people escaped from poverty in 2006 and 10 million who
had been classified as indigent ceased to be so. As a result,
the region is well on track to reaching the first Millennium
Development Goal target of halving the 1990 extreme
poverty rate by 2015. A portion of the progress made in
this respect may be accounted for by changes in family

composition and in household members’ participation
in the labour market. Countries are therefore urged to
develop ways to reconcile care work in the home with
gainful employment, increase occupational productivity
and improve the targeting of expenditure on the most
vulnerable groups.
A preliminary analysis is also undertaken of the problem
of residential segregation, which limits opportunities
for learning to live with others under circumstances of
inequality. This type of segregation can hinder access to
employment and education, thereby contributing to the
perpetuation of poverty. This is an issue that calls for a
thorough-going review of State action in relation to urban
land management and social housing.
This chapter concludes with a discussion of the many
psycho-social divides separating the most vulnerable
groups from those that are economically better off, which
militate against social cohesion. It notes that, in order
to make progress in overcoming poverty and achieving
social cohesion, multidimensional policies are required
that include measures for creating opportunities that will
provide vulnerable groups with greater expectations of social
mobility, give them greater confidence in their country’s
institutions, and allow them to feel more included and to
participate more actively in decision-making processes
that influence their quality of life.
In the chapter on social expenditure, the available
statistics are examined in the light of the main social
policy challenges facing the region. The discussion of
this subject underscores the fact that, apart from a few
exceptions, public social expenditure has continued to
be accorded a high macroeconomic and fiscal priority,

14

which ensures funding, stability and greater institutional
legitimacy for social policy. Despite the greater effort
being made to finance social policies (especially in the
less developed nations), however, public social spending
is still insufficient, and the structure of such expenditure
has to constantly be adapted to changing risk profiles and
social needs. The way in which it is administered continues
to be highly procyclical, although in recent years it has
not been any more so than the trend of GDP.
The impact of such expenditure on people’s wellbeing is analysed on the basis of a review of various case
studies. These studies indicate that the gradual expansion
of coverage increases the progressiveness of spending on
education, that the composition of expenditure on health
services influences its neutrality from the standpoint of
considerations of equity, that the contributory nature of the
social security system’s funding makes these expenditures
regressive, and that social assistance is becoming markedly
pro-poor as conditional transfer programmes come into
greater and greater use, although they are not entirely
free of leakage issues.
This analysis underscores the importance of
distinguishing among countries based on the differing
phases they have reached in the demographic transition and
their labour markets’ degree of maturity, and a typology
is outlined for use in examining the level and structure
of social spending. It is also noted that a far-reaching
social contract will be required in order to overcome the
challenges facing the region in relation to the allocation
of public social expenditure.
The chapter on education reviews the major advances
that the region has made in this field since the early 1990s.
It looks at how social inequality is manifested in access
to education and in the pace at which students progress
through the primary, secondary and tertiary levels as well
as their completion rates, and concludes that the degree
of inequality has diminished in the last 15 years. It notes
that there has been a reduction in the differences in terms
of passage through formal education systems associated
with economic inequalities, gender inequities, areas of
residence, ethnic origin and the stock of educational capital
in the home. It also points out, however, that, despite
the considerable progress made in all areas, the intergenerational transmission of educational opportunities
persists, although, for the most part, this process is now
being expressed in access to and completion of the last
few years of secondary school and, most of all, at the
level of higher education.
The quality of education in five Latin American
countries is examined on the basis of the findings of the
2000 Programme for International Student Assessment
(PISA) test. The main focus of the 2000 PISA test was
reading comprehension, and the assessment shows that

Economic Commission for Latin America and the Caribbean (ECLAC)

a close correlation exists between inequalities in terms
of socioeconomic origin and the acquisition of language
competencies. It also indicates that educational curricula
are lacking in relevance (judging from the poor scores
of even the best students) and that the extent of teachers’
commitment is a very important factor in the learning
process. The chapter also includes a discussion of the
markedly segregated nature of the school environment
in the region, its association with a highly segmented
supply of educational services, and the major differences
in performance to which this situation leads. A case is
made for the need to redesign educational policy in
order to address the problem of social inequality through
affirmative action in order to give the poorest students
a head start and to improve the quality of the learning
process by diminishing the sharp stratification of the
countries’ educational systems.
The chapter on internal migration notes that 1 out of
every 3 Latin Americans lives in a different town from
the one in which he or she was born and that nearly 1 in
10 Latin Americans moved to a different town in the last
five years of the twentieth century. Migrants are usually
younger and have a higher skill level than non-migrants,
and they are therefore generally an asset for the host area.
Conversely, emigration from the more socioeconomically
backward areas within countries (including rural zones,
chronically poor areas and ones in which indigenous
population clusters are located) erodes their human resource
base, thereby hindering their progress and hampering
efforts to improve the living conditions of those who
remain there (geographical poverty traps). A majority of
migrants move from one city to another or within cities.
In the case of intra-city migration, residential rather than
labour-related factors are more influential.
Policies designed to influence internal migration
patterns must address a much more diverse and complex
set of factors than they did when rural-to-urban migratory
flows predominated. Such policies should be based on
a recognition of the right of all persons to freely decide
when and where to migrate within a given country. No
form of coercion should therefore be used to achieve
policy objectives. Instead, differing types of incentives
for individuals and businesses should be employed to
promote the development of given areas within a country.
Indirect action may also be taken through various sorts
of social policies (particularly policies on housing,
transportation and infrastructure) that may influence
migration decisions.
The chapter on the social policy agenda offers
an assessment of health policies and programmes
designed to benefit the indigenous peoples of Latin
America based on 16 countries’ responses to a survey
conducted by ECLAC on this subject and the findings

Social Panorama of Latin America • 2007

of the Workshop-Seminar on Indigenous People in
Latin America: Health Policies and Programmes, How
Much and How Has Progress Been Made? Both the
survey and the seminar, which was held at ECLAC
on 25 and 26 June 2007, were conducted as part of a
project funded by the Government of France.1
In the first section of this chapter, emphasis is placed
on the existence of minimum standards for the rights of
indigenous peoples and on the fact that, although legislative
advances have been made in this respect, public policy
must do more to ensure the fulfilment of those rights. The
discussion covers the persistent structural inequity which
puts indigenous people at a disadvantage and which, in
the field of health, is manifested in higher morbidity and
mortality rates. The evidence also points to more limited
access and a failure to ensure the cultural appropriateness
of health care services, as well as indigenous peoples’ very
limited participation and representation in the relevant
policies and programmes.
The second section of the chapter discusses the
more conducive environment for the design and

1

15

implementation of health policies and programmes for
indigenous peoples created by health-sector reforms
and legislative advances. It notes that most countries
are taking action in this connection and describes the
widely varying situations to be found in this regard,
along with major achievements and problems. Two
of the main issues covered by this assessment are the
management and participation by indigenous peoples
of health policies and programmes and the availability
of the information needed to design, implement and
evaluate measures taken in this area.
Based on the information presented, a number
of recommendations are then offered with a view to
improving health policies and programmes for indigenous
peoples and to fully enforcing their rights.
The international social agenda provides an overview
of major United Nations meetings and agreements
on social issues. In this year’s edition, this section is
devoted to the tenth session of the Regional Conference
on Women in Latin America and the Caribbean, held
in Quito, Ecuador, from 6 to 9 August 2007.

Project on Advances in Policies and Programmes for Indigenous Peoples of Latin America since the Implementation of the International
Decade for Indigenous Peoples, Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC/Government
of France.

Social Panorama of Latin America • 2007

17

Summary

Poverty in the region
The latest poverty estimates available for the countries of
Latin America indicate that, as of 2006, 36.5% of Latin

America’s population (194 million people) were poor and
13.4% (71 million) were extremely poor (see figure 1).

Figure 1
LATIN AMERICA: POVERTY AND INDIGENCE. 1980-2007 a
60

Percentage of population

50

43.5

43.8

250

44.0
39.8

36.5

30
22.5
20

19.0

18.6

18.5

19.4
15.4

150

204

12.7

93

89

89

10

1997

1999

221

209
194

190

71

69

136

100
13.4

211

200

200

35.1

Millions

Percentage

40

48.3
40.5

Number of people

300

97

81

62
50
0

0
1990

1997

1999

2002

2005

2006

2007 b

1980

Indigent

1980

2007 b

Non-indigent poor

1990

2002

2005

2006

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a Estimate for 19 countries of the region including Haiti. The figures shown in the orange sections of the bars are the percentages and total number of
poor persons (indigent plus non–indigent poor).
bProjections.

A comparison with the figures for 2005 shows that
further progress was made in reducing poverty and
extreme poverty, or indigence, with a 3.3% drop in
poverty and a 2.0% decrease in extreme poverty. This
means that 15 million people escaped from poverty in
2006 and 10 million who had been classified as indigent
ceased to be so.

A comparison of the figures for 2006 and 1990 shows
that the poverty rate has been reduced by 11.8 percentage
points and that the indigence or extreme poverty rate has
decreased by 9.1 points. This means that the number of
indigents has fallen by over 20 million and that, for the
first time since then. the total number of people living in
poverty has dropped below 200 million persons.

18

Economic Commission for Latin America and the Caribbean (ECLAC)

Projected per capita GDP growth for the Latin
American countries in 2007 is expected to make it
possible to bring poverty and indigence rates down
to 35.1% (190 million people) and 12.7% (69 million
people), respectively. If these projections are borne out,
Latin America will have not only the lowest poverty
and indigence rates to be recorded since the 1980s, but
also fewer poor people than at any other time in the last
17 years (see figure 1).
Poverty and indigence estimates for 2006 for 12
countries in the region reflect a widespread downward
trend. All of these countries registered considerable

reductions, and in most cases these decreases represented
a continuation of the trend observed in 2005.
When the year 2002 is used as a benchmark, Argentina
(data for urban areas) displays the greatest improvement, with
reductions of 24.4 and 13.7 percentage points in its poverty
and extreme poverty rates, respectively. The results for 2006
played an important role in this outcome, with decreases in
the two indicators of 5.0 and 1.9 percentage points. This
largely counteracted the deterioration in the situation that
occurred in 1999-2002. As a result. the poverty rate is now
2.7 points below the 1999 rate, although the indigence rate
is still 0.6 points above the figure for 1999 (see table 1).

Table 1
LATIN AMERICA (18 COUNTRIES): PERSONS LIVING IN POVERTY AND INDIGENCE,
AROUND 2002, 2005 AND 2006
(Percentages)
Country

Around 2002
Year

Argentina

a

Poverty

Around 2005
Indigence

Year

Poverty

2006
Indigence

Year

Poverty

Indigence

2002

45.4

20.9

2005

26.0

9.1

2006

21.0

Bolivia

2002

62.4

37.1

2004

63.9

34.7

…

…

7.2
…

Brazil

2001

37.5

13.2

2005

36.3

10.6

2006

33.3

9.0

Chile

2000

20.2

5.6

2003

18.7

4.7

2006

13.7

3.2

Colombia

2002

51.1

24.6

2005

46.8

20.2

…

…

…

Costa Rica

2002

20.3

8.2

2005

21.1

7.0

2006

19.0

7.2

Ecuador a

2002

49.0

19.4

2005

45.2

17.1

2006

39.9

12.8

El Salvador

2001

48.9

22.1

2004

47.5

19.0

…

…

…

Guatemala

2002

60.2

30.9

...

...

...

...

…

…

Honduras

2002

77.3

54.4

2003

74.8

53.9

2006

71.5

49.3
8.7

Mexico

2002

39.4

12.6

2004

37.0

11.7

2006

31.7

Nicaragua

2001

69.4

42.4

...

...

...

...

…

…

Panama

2002

34.0

17.4

2005

33.0

15.7

2006

30.8

15.2

Paraguay

2001

61.0

33.2

2005

60.5

32.1

…

…

…

Peru

2001 b

54.8

24.4

2005 b

48.7

17.4

2006 b

44.5

16.1

Dominican Rep.

2002

44.9

20.3

2005

47.5

24.6

2006

44.5

22.0

Uruguay a

2002

15.4

2.5

2005

18.8

4.1

2006

18.5

3.2

Venezuela
(Bolivarian Rep. of)

2002

48.6

22.2

2005

37.1

15.9

2006

30.2

9.9

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
aUrban areas.
bFigures compiled by the National Institute of Statistics and Informatics (INEI) of Peru. These values are not comparable with those of previous years
owing to changes in the sample framework used in the household survey. In addition, the figures given for 2001 correspond to the fourth quarter,
whereas those shown for 2004 and 2006 correspond to the entire year.

The Bolivarian Republic of Venezuela reduced its
poverty and extreme poverty rates by 18.4 and 12.3
percentage points, respectively, between 2002 and
2006. Thanks to rapid GDP growth and the ongoing
implementation of broad social programmes, in 2006
alone the poverty rate was lowered from 37.1% to 30.2%

and the indigence rate from 15.9% to 9.9%. This swift
pace of progress considerably brightens the prospects for
further reductions in poverty and significantly increases
the feasibility of meeting the first target associated with
the first Millennium Development Goal, which is analysed
in the following section.

Social Panorama of Latin America • 2007

These two countries are followed. in order of magnitude,
by Peru,1 Chile, Ecuador (urban areas), Honduras and
Mexico, which have marked up poverty reductions of
over five percentage points between 2000-2002 and 2006.
With the exception of Peru, at least half of this cumulative
reduction occurred in the more recent years in this period
in each of these four countries. This is particularly notable
in the case of Chile, where 5.0 of the 6.5 percentage points
by which the poverty rate was reduced in 2000-2006
correspond to 2003-2006.2 These countries also witnessed
significant reductions in their indigence rates. Particularly
share decreases were seen in this indicator for Ecuador
and Honduras, which recorded reductions of 8.3, 6.6 and
5.1 percentage points, respectively, Chile also made great
strides in this respect since, although its indigence rate
fell by just 2.4 percentage points, this amounted to a 43%
decrease in that rate relative to 2000.

19

Brazil registered decreases of 4.2 percentage points
in both its poverty and its extreme poverty rates between
2001 and 2006. This has a significant impact at the regional
level, since it represents a reduction in the number of
indigents of 6 million people. The “Bolsa Familia” public
transfer programmes implemented in the country has
played a decisive role in this achievement.
Costa Rica and the Dominican Republic also managed
to reduce their poverty levels in 2002-2006, although
less dramatically than the above-mentioned countries.
Actually, the Dominican Republic recorded a slightly
higher indigence rate due to the setbacks it experienced
between 2002 and 2004, which later progress has not yet
offset entirely. A somewhat similar situation is found in
Uruguay, where decreases in the poverty and indigence
rates in 2005 and 2006 have not enabled the country to
regain the levels it had attained in 2002.

Progress towards meeting the first target of the Millennium Development Goals
Latin America’s projected extreme poverty rate for 2007
amounts to 12.7%, which is 9.8 percentage points below
the 1990 figure (22.5%). This means that Latin America
is 87% of the way towards meeting that target at a point
in time when just 68% of the period provided for that
achievement has passed.3 This evidence gives reason
to believe that the region as a whole is fully on track to
meet its commitment to halve the 1990 extreme poverty
rate by 2015 (see figure 2).
The projections for extreme poverty rates in 2007
paint a bright picture for many countries. The most recent
figures for Ecuador (urban areas) and Mexico indicate that
they will join the ranks of countries that, like Brazil and
Chile, have already reached the first target established for
the first Millennium Development Goal. The Bolivarian
Republic of Venezuela, Colombia, El Salvador, Panama
and Peru have progressed as much or more than expected
(68%). All the other countries in Latin America have
lower extreme poverty rates than they did in 1990, but
some of them are behind where they should be in order to
reach this target on time. Argentina, Bolivia, Honduras,
Nicaragua, Paraguay and Uruguay are still less than 50%
of the way to this target.
1

2
3

Figure 2
LATIN AMERICA (17 COUNTRIES): PROGRESS IN REDUCING
EXTREME POVERTY BETWEEN 1990 AND 2007 a
Latin America
Argentina b

Bolivia
Brazil
Chile
Colombia
Costa Rica
Ecuador b

El Salvador
Guatemala
Honduras
Mexico
Nicaragua
Panama
Paraguay
Peru

Uruguay b
Venezuela
(Bolivarian Rep. of)
0

10

20

30

40

50

60

70

80

90

100

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of data from household
surveys conducted in the relevant countries.
aThe amount of progress made (expressed as a percentage) is calculated
by dividing the percentage–point reduction (or increase) in indigence
registered during the period by one half of the indigence rate for 1990. The
dotted line represents the amount of progress expected by 2007 (68%).
bUrban areas.

The figures for Peru from 2004 on are not wholly comparable with those for earlier years, since the former refer to the entire year whereas the
latter correspond to the last quarter only. No major differences are to be expected between quarterly and annual estimates, however. As a point
of reference, it may be noted that in 2006 the indigence and poverty rates estimated for the year as a whole were 0.7 and 1.5 percentage points
higher, respectively than the estimates for the final quarter.
Indigence and poverty estimates for Chile are available only for 2000, 2003 and 2006, and an analysis of what occurred in the intervening years
can therefore not be made.
The time allotted for reaching this target is 25 years (from 1990 to 2015); 17 of those 25 years have passed, which amounts to 68% of the total period
provided for this effort.

20

Economic Commission for Latin America and the Caribbean (ECLAC)

Taken as a whole, the region has a very good chance of
reaching this first target. Assuming that no major changes
in income distribution occur in the next few years, Latin
America will have to achieve GDP growth of 1.1% per
year, which is less than its population growth rate. The
low level of the required rate is partially due to the fact
that four countries have already surpassed the target and

are therefore “subsidizing” those that are further behind.
This is all the more so because the over-achievers include
Brazil and Mexico, which together account for over
half of the region’s population. In fact, the growth rate
for countries that have not yet attained this first target
averages 4.0% per annum, which translates into a 2.7%
annual increase in per capita GDP.

Factors linked with poverty reduction
In this section the influence on poverty reduction of various
demographic, household and labour-related factors in 19902005 in the countries of Latin America and the Caribbean
will be examined. In view of the progress already made
in reducing extreme poverty, the more ambitious target
(halving the entire poor population, rather than just the
extremely poor population) proposed in the 2005 interagency report on the Millennium Development Goals is
taken into consideration in this evaluation.4
Generally speaking, poverty trends can be understood
by looking at changes in three determinants of per capita
household income: the ratio of employed persons to total
population, labour income per employed person and nonlabour income (public transfers, remittances, etc.).5 When the
percentage of employed persons, wages per employed person
and non-labour income levels in low-income households
rise, poverty levels tend to diminish. These determinants
can, in turn, be broken down into a series of factors: changes
in labour income are linked with the behaviour of human
capital and productivity patterns,6 changes in non-labour
income stem from public and private transfers and from
the rate of return on capital, and changes in employment
levels can be traced back to demographic changes, shifts
in family structures and the way in which households react
to employment opportunities.
The high demographic dependency rates7 of poor
households are one of the factors that contribute to the
perpetuation of poverty. In Latin America, poor households
have higher fertility rates and thus have larger households.

4
5
6
7

and a majority of the members of those households are
children. This means that household income has to be
distributed among a larger number of people and, at the
same time, places limitations on working-age members’
participation in the labour market, especially in the case
of women. Nonetheless, in recent years the dependency
ratio has been on the decline. This situation, which has
been described as a “demographic bonus”, offers a window
of opportunity for poverty reduction.
Poor households’ low income levels are also associated,
among other factors, with the limited human capital of
their economically active members. This situation, which
ties in with the fact that these members have few job
opportunities, sets up another vicious circle: on the one
hand, the members of poor households have insufficient
job training and thus are employed in precarious jobs
and, on the other, the children and young people living
in such households have few educational and training
opportunities, are lacking in social capital and are employed
in low-productivity occupations if they manage to find
any employment at all.
An analysis of poverty trends in 1990-2005 based on
this scheme reveals a wide variety of different situations
(see table 2). Three points should be noted in this regard.
First. the commitment undertaken to achieve the Millennium
Development Goals coincides with a period in which the
proportion of the total population represented by economically
active household members has been on the rise. Second,
throughout this entire period no increase has been seen

See United Nations, The Millennium Development Goals: A Latin American and Caribbean Perspective (LC/G.2331-P), J.L. Machinea, A.
Bárcena and A. León (coords.), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), 2005.
This breakdown is valid when measuring poverty on the basis of money income, which can be used as a means of gauging people’s and
household’s ability to meet their basic food and non-food needs.
Certainly, there are other factors as well that influence labour income, such as the degree of protection enjoyed by the labour force and its
bargaining power (degree of unionization, existence of collective bargaining mechanisms, etc.).
Ratio of working-age population and total population.

Social Panorama of Latin America • 2007

21

in the labour incomes of employees from the poorest
households except in Chile, Brazil and Ecuador (urban
areas). Third, there has been a fairly widespread increase
in non-labour income in poor sectors of the population.
An analysis of the reasons for this increase will not be
offered here, however, since disaggregated figures on the
wide variety of income sources included under this heading
(State transfers, remittances, etc.) are unavailable.
Only 5 of the 16 countries that were analysed have
reduced poverty significantly since the early 1990s: the
three countries where labour income per employee has risen

(Chile, Brazil, Ecuador), Mexico and Panama, where the
proportion of employed persons climbed considerably. The
other countries have made little or no progress. The main
limitation in these cases has been the labour market’s poor
performance. In the countries that have witnessed sharp
reductions in poverty, the main underlying factors have
been changes in household composition and in household
members’ participation in the labour market. Although
this trend has been widespread in all the other countries
as well, it has not been reinforced by sufficiently large
increases in household transfers or remunerations.

Table 2
LATIN AMERICA (16 COUNTRIES): COUNTRY TYPOLOGY BASED ON TRENDS IN THE OVERALL EMPLOYMENT RATE, LABOUR INCOME PER
EMPLOYEE AND NON-LABOUR INCOME IN POPULATION DECILES THAT INCLUDE POOR HOUSEHOLDS,1990-2005
Annual variation in poverty,
by groups/countries a

Poverty – start
of period b

Overall
employment
rate c

Labour income
per employee

Per capita nonlabour income

Poverty – end
of period b

Sharp reduction d (variation of more than -1.5% per year)
Chile 1990-2003

38.3

++

++

++

18.6

Ecuador 1990-2005

61.8

++

+

+

45.1

Brazil 1990-2005

47.4

++

+

++

36.2

Panama 1991-2005

42.8

++

–

+

32.7

Mexico 1989-2005

47.4

++

–

+

35.5

Slight reduction d (variation of between -1.5% and -0.5% per year)
El Salvador 1995-2004

54.0

+

–

+

47.5

Costa Rica 1990-2005

26.2

+

+–

+

21.1

Colombia 1991-2005

55.6

+

=

+

46.8

Guatemala 1989-2002

70.3

++

=

++

58.4

Nicaragua 1993-2001

73.6

++

––

=

69.3

Honduras 1990-2003

80.5

++

––

++

74.6

40.0

++

––

–

37.1

No progress d (variation of between -0.5% and 0.5% per year)
Venezuela (Bolivarian
Rep. of) 1990-2005
Bolivia 1989-2004

52.1

++

––

+

51.6

Argentina 1990-2005

21.1

+

–

=

22.6

Uruguay 1990-2005

17.8

=

–

+

19.1

42.2

+–

––

+

47.7

Increase (variation of over 0.5% per year)
Paraguay 1990-2005

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of household surveys conducted in the relevant countries.
Note: ++: Significant progress; +: Progress; = / +-: No change / progress and setbacks; -: Setbacks; – –: Significant setbacks.
of the different years in which surveys are conducted, the values shown for poverty at the beginning and end of the period do not cover the
years 1990 and 2005 for all of the countries.
bThese percentages may not match those shown in last year’s edition of the Social Panorama of Latin America because of changes in the treatment of
the domestic service category. In the case of Guatemala, it was necessary to adjust the way in which the data were processed to compensate for the
absence of measurements covering children under 10 years of age in 1989 and 7 years of age in 2002.
cRefers to the number of employed persons relative to the total population.
dThe annual rate of reduction in total poverty for each country, which was used to classify the countries, was estimated using the following formula:
ARR = ((FP-IP) / PI) *100)/y, where ARR = annual rate of reduction in poverty, FP = final poverty percentage, IP = initial poverty percentage, and y =
number of years contained in the period.
aBecause

A comparison of the countries in which poverty has
decreased the most and the least underscores the importance
of behavioural patterns relating to the labour market (see
figure  3). For example, in Brazil, Chile and Ecuador
(urban areas), which reduced poverty the most, the effect

of the increase in the ratio of employed persons to the total
population (dark blue bars in figure 3a) has been bolstered by
an increase in labour income per employee (light blue bars).
This combination signals the presence of a highly dynamic
labour market. In addition, there has also been an increase

22

Economic Commission for Latin America and the Caribbean (ECLAC)

in non-labour income (orange bars). In Argentina (Greater
Buenos Aires), Bolivia, Paraguay (Asunción metropolitan
area), Uruguay (urban areas) and the Bolivarian Republic of
Venezuela, in contrast, labour income per employed person

declined in poor sectors of the population, and this decrease
was not offset by any increase in the employment rate or
non-labour income. Consequently, they made no progress
in reducing poverty.

Figure 3
DETERMINANTS OF CHANGES IN POVERTY LEVELS, DECILES I-IX:

0.7

Per capita income distribution, by decile, 1990

0.6
0.5

3

Poor population
(1990)

Poor population
(2003-2005)

0.4

0.2

4

2

Poverty line

1

0.1
0.0

I

II

III

IV

V

VI

VII

VIII

IX

0

Income deciles
Variation in per capita income due to changes in overall employment rate
(between 1990 and 2003-2005)
Variation in per capita income due to changes in overall employment rate
(between 1990 and 2003-2005)

Variation in per capita income
(in multiples of the poverty line)

Per capita income distribution, by decile, 2003-2005

0.8

Per capita income
(in multiples of the poverty line)

Variation in per capita income
(in multiples of the poverty line)

0.9

3

0,5

5

1.0

0.3

(b) Countries recording no progress or increases in poverty
(Argentina, Bolivarian Republic of Venezuela, Bolivia, Paraguay
and Uruguay, simple averages), 1990-2005

0,4

Per capita income distribution, by decile, 1989-1990

0,3

Per capita income distribution, by decile, 2004-2005
2

0,2
0,1
0,0
-0,1
-0,2

I

II

III

IV

V

VI

VII

VIII

IX
1

Poverty line
Income deciles

-0,3

Poor population Poor population
(2004-2005)
(1989-1990)

-0,4

Per capita income
(in multiples of the poverty line)

(a) Countries recording sharp reductions in poverty and increases
in labour productivity (Brazil, Chile and Ecuador,
simple averages), 1990-2005

0

Variation in per capita income due to changes in labour income
per employee (between 1989-1990 and 2004-2005)
Variation in per capita income due to changes in overall
employment rate (between 1989-1990 and 2004-2005)

Variation in per capita income due to changes in overall employment rate
(between 1990 and 2003-2005)

Variation in per capita income due to changes in per capita
non-labour income (between 1989-1990 and 2004-2005)

Per capita income - 1990

Per capita income 1989-1990

Per capita income - 2003-2005

Per capita income 2004-2005

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of household surveys conducted in the relevant countries.

Quite a few countries in the region are on track to
reach the first target associated with the first Millennium
Development Goal, thanks in large part to their success
in capitalizing upon the “demographic bonus”, as
declining dependency ratios have been coupled with rising
employment levels among the poorest households. There
is still a shortfall in terms of increases in labour income
and greater job opportunities for the poorest sectors of
the population, however. One fact that the countries of

the region should bear in mind is that the advantages
afforded by this demographic bonus will ultimately be
reversed and that, in order to continue making progress,
public policies will have to be devised that will reconcile
care work in the home with gainful employment, boost
productivity in occupations performed by the poorest
members of the population and, in the event that this
does not occur, target social expenditure at the demands
of the most vulnerable groups.

Poverty and residential segregation in urban areas
There are clear signs that changes in the labour and
housing markets in Latin America are resulting in the
increased geographic segregation of low-income (as well
as middle- and upper-income) urban households. The
possible negative implications of this growing degree of
isolation —including the hardening of poverty and its
inter-generational reproduction— are a cause of concern.
At the same time, these patterns could pose a threat for

social cohesion, inasmuch as residential segregation
reduces and interferes with the spheres of activity that
provide opportunities for learning to live with others
under circumstances of inequality and for building bridges
between different social groups.
Given the constraints that exist in terms of
methodological limitations and the availability of data, it
would be premature to say that urban residential segregation

Social Panorama of Latin America • 2007

23

is a causative factor in the perpetuation of poverty over
time. There is, nonetheless, evidence of the existence of
a relationship in Latin America between patterns of urban
segregation involving the poorest sectors of the population
and a number of behavioural outcomes in connection with
participation in the labour market, educational attainment,
reproductive decisions and adolescents’ alienation from
society’s principal institutions.
Entry into the labour market and chances of finding
work in the formal sector of the economy are associated
with the social make-up of the neighbourhood of residence,
above and beyond the individual’s level of education.
For example, unemployment rates are higher in census
districts in Montevideo where educational levels are
low than they are in districts with high educational

levels, regardless of the years of schooling that people
have completed (see figure 4). Analyses of own-account
employment rates and the percentage of private-sector
employees lacking health coverage or access to services
provided by the Ministry of Public Health reveal similar
situations. Factors that may account for these tendencies
include the distance between residential areas and places
of employment, the stigmatization of people residing
in poor neighbourhoods, such people’s limited access
to information and contacts that would allow them
to obtain jobs, and the socialization of children and
adolescents living in such neighbourhoods in ways that
inculcate anti-social modes of behaviour that reinforce
their reluctance to utilize education and employment as
ways of escaping poverty.

Figure 4
URUGUAY (MONTEVIDEO): OPEN UNEMPLOYMENT RATE, BY AVERAGE EDUCATIONAL LEVEL OF THE CORRESPONDING
CENSUS DISTRICT, BY AGE AND YEARS OF SCHOOLING, 1996 a
(Percentages)
(b) 30 years of age and over

(a) 15-29 years of age

16.2

Total

22.7

14.6
14.8

12 or more

17.1

9-10 years
7-8 years
Complete primary
Incomplete primary
0

5

10

15

20

30

13.4

8.5

Incomplete primary

27.0
25

13.1

8.4

Complete primary

25.3

19.7

10.9
8.0

7-8 years

23.5
21.6

10.1
6.8

9-10 years

20.3
19.0

7.7
6.0

11 years

18.2

12.4

3.3

12 or more

15.5

11 years

5.4

Total

0

2

4

6

8

14.1
10

12

Census segment with low educational level

16

Census segment with low educational level

Census segment with high educational level

14

Census segment with high educational level

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Uruguay’s 1996 population and housing census.
a In Uruguay, the primary education cycle covers a six-year period; secondary education is divided into two three-year cycles. Data for 1996 were used
because the relevant tabulations for 2004 census data are not available.

The type of neighbourhood may also influence the
stock of human capital. The findings of a study undertaken
in Mexico indicate that if the socioeconomic situation
in a given neighbourhood deteriorates, the likelihood
that students will drop out of school after the end of
the first cycle of secondary education rises. Research
in Buenos Aires, Santiago and Montevideo also reveals
that children and adolescents residing in disadvantaged
neighbourhoods score more poorly on achievement tests
even when individual, household and school-related traits
are controlled for. A study carried out in São Paulo indicates
that the effects that neighbourhoods’ social make-up can

have on educational outcomes can be transmitted indirectly
through those neighbourhoods’ impact on teachers,
since, under the system used to regulate the distribution
of teachers in state and municipal schools, teachers who
score the lowest in competitive application processes and
those who are new entrants into the educational system
are assigned to schools in outlying areas.
Residential segregation in urban areas may also be
associated with higher teenage pregnancy rates and higher
levels of institutional alienation. For example, a study
conducted in Montevideo found that young people residing
in underprivileged neighbourhoods exhibit higher rates

24

of non-participation in societal institutions (persons who
neither attend an educational institution nor work) regardless
of their parents’ educational levels. Research findings on
how the nature of urban neighbourhoods may influence
teenage pregnancy rates in Rio de Janeiro, Santiago and
Montevideo indicate that the social make-up of people’s
places of residence accounts for much of the differences
observed in the prevalence of early motherhood.
Aside from the methodological constraints that may
be a factor in this regard, in an effort to shed light on the
causal relationships between residential segregation and the
reproduction of poverty, this section will present evidence
that illustrates how the character of neighbourhoods does

Economic Commission for Latin America and the Caribbean (ECLAC)

indeed have an impact. It also shows why it is so important
for public policymakers to pay more attention to changes
in urban residential segregation, have greater control
over the determinants of these processes and undertake
a thorough-going review of urban land management
measures and social housing programmes. Changes in
the location of social housing, transportation and rental
subsidies, and the extension of credit to low-income
families so that they can purchase dwellings in formally
constituted areas of urban centres are some of the types
of actions that can shorten commutes between places of
residence and employment or that can help rectify their
negative effects.

Poverty and social cohesion: psycho-social divides
An analysis of poverty and inequity should not be confined
to their material components. An exploration of some of
the psycho-social divides existing in 18 Latin American
countries demonstrates how widely separated the various
socioeconomic strata are in terms of their expectations of
social mobility, confidence in State institutions, citizen
participation and perceptions of being discriminated
against. These divides are the subjective correlates of
poverty and inequity. They hinder the inclusion of the
poorest sectors, are a threat in terms of social cohesion
and underline the need to implement multidimensional
policies that will complement material transfers with
initiatives designed to narrow the subjective distances
separating different sectors from one another.
In terms of expectations of inter-generational mobility,
people living in the more vulnerable households have lower
expectations regarding their children’s future well-being
than members of households that are in a better economic
position (see figure 5). Perceptions of the social structure
also influence expectations of mobility. Regardless of the
level of household well-being, people who believe that
the social structure is open or egalitarian have greater
expectations for their children than those who feel that
it is closed or inegalitarian.
Although the most vulnerable sectors have lower
expectations in terms of inter-generational mobility,
this does not mean that they think their children will be
worse off than they are. In fact, of all the socioeconomic
groups, the people who think that their children will
see the greatest improvement relative to their current
situation (i.e., the sector in which the biggest jump in
expectations is found) are in the poorest sectors of the
countries’ capital cities, whereas the least difference is
found in the most vulnerable sectors of the most sparsely

Figure 5
LATIN AMERICA (18 COUNTRIES): CURRENT PERSONAL
WELL-BEING, FUTURE WELL-BEING OF CHILDREN
AND AVAILABILITY OF BASIC GOODS AND SERVICES
IN THE HOME, 2006 a b
(Values expressed as averages on the basis of a
self-evaluation scale of 1-10, where 1 = poorest persons
and 10 = richest persons)

8 basic goods

6.5

5.4

7 basic goods

6.2

5.0

6 basic goods

6.0

4.8

5 basic goods

5.7

4.6

4 basic goods

5.5

4.4

3 basic goods

5.2

4.1

2 basic goods

4.8

3.8

1 basic good

4.4

3.4

0 goods

2.9
0

1

2

3

3.8
4

5

6

Current personal well-being
Future well-being of children

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of the Latinobarómetro
2006 survey.
aCurrent personal well-being and expectations regarding the future
well-being of the respondents’ children are measured on the basis of
a self-evaluation scale. Respondents were asked to rate their current
personal well-being and the future level of well-being that they believe
their children will have.
bThe indicator of household ownership of durable goods and basic
services includes the possession of: (1) refrigerator; (2) washing
machine; (3) fixed-line telephone; (4) computer; (5) piped-in hot water;
(6) automobile; (7) sewerage system and (8) cellular telephone.

7

Social Panorama of Latin America • 2007

populated areas. Policymakers in urban areas therefore
face the greatest challenges, especially in connection
with the creation of opportunities for employment,
education and social inclusion.
Levels of confidence in State institutions are associated
with households’ economic well-being and per capita
GDP, with higher levels being found among households
in a more comfortable economic position and in the richer
countries, and lower ones among households with lower
levels of well-being and those located in poorer countries.
These lower levels of trust in State institutions are evident
among members of more vulnerable households, people
who reside in the most densely populated urban zones and
people who say they have less trust in their neighbours, as
well. A fairly similar situation exists in terms of political
participation, with members of the most vulnerable
households participating the least.
This suggests that a segment of the poorest sectors
of the urban population is suffering from a syndrome
of mistrust that takes the form of low expectations
regarding public institutions, very limited civic
participation and a tendency to take refuge in familybased relationships and to hold markedly individualistic
values. This may not only jeopardize the extent of
the poorest sectors’ access to social forms of support
(owing to the deterioration of relations within their
home communities), but may also stop them from
organizing and from bringing their needs and demands
to the attention of public institutions.

25

In the 18 countries that were analysed, the percentage
of people who feel they are discriminated against is greater
among those living in households with insufficient incomes
and lower among households that are better off. When the
area of residence is factored into the analysis, the highest
levels of perceived discrimination are found among the
members of the most vulnerable households located in areas
with populations of over 100,000. One possible explanation
for this is that in the most heavily populated urban areas
the exclusions arising out of ascriptive behaviours are
more conspicuous due to their dissonance with widely held
egalitarian and meritocratic values. It is also plausible that
there is a greater chance of being discriminated against in
urban areas because of the greater diversity of social identities
and actors with whom people come into contact.
Some of the forms of discrimination most frequently
reported by people in the more vulnerable sectors of the
population are associated with the denial of opportunities
to improve their living conditions and ascend the social
ladder because they lack various types of “capital” (lack
of education and contacts). Age, identification with
given ethnic groups (skin colour, race), disabilities and
gender represent 31% of the cases of discrimination.
This indicates that members of the poorest groups may
feel discriminated against because of their membership
in different social categories. These latter factors would
include the denial of opportunities for social integration
based on the obsolescence and/or lack of certain capacities
(elderly persons or persons with disabilities).

26

Economic Commission for Latin America and the Caribbean (ECLAC)

Public social expenditure
in Latin America
The level and structure of public social expenditure in Latin
America continue to fall short of what is required to meet
the social needs of the vulnerable population. Considerable
advances in reducing indigence notwithstanding, these
shortcomings are clearly a factor in the slow pace of
progress in alleviating non-extreme poverty and in
reducing inequalities in the region. On the one hand, the
level of such spending is insufficient, and these funds are
administered under severe budgetary constraints. On the
other, the structure of expenditure has to be constantly
adapted to address emerging social needs before existing
ones have been met.
Adapting the level and structure of public social expenditure
to constantly changing risk profiles and social needs should
figure as one of the core elements of a new social contract in
which rights constitute the normative horizon for efforts to
address existing inequalities and budgetary restrictions. As

part of this effort, the allocation of public funds for social ends
should be designed to increase the coverage and quality of
benefits provided by social programmes through a combination
of contributory and non-contributory financing, together with
a significant solidarity component.
The following section will explore the main
characteristics of the level and structure of public social
expenditure in the region and how they have changed
over the past 15 years. It will also look at which income
groups have been the main recipients of that expenditure
and the impact it has had in terms of increased levels of
well-being. Finally, with a view to the design of a new
social contract, countries will be grouped into various
categories based on an indicator that measures the distance
existing between social needs and emerging risks, on
the one hand, and the State resources allocated to social
policies, on the other.

Level and composition of public social expenditure
The level of public social expenditure rose by nearly 10%
between 2002-2003 and 2004-2005 to US$ 660 per capita
(at 2000 prices). There are enormous differences across
countries, however. Per capita expenditure is 15 times greater
in the country that spends the most than in the country that
spends the least. In all, 12 out of the 21 countries analysed
spend less than US$ 350 per capita per year, 6 spend between
US$ 550 and US$ 870 per capita, and only two spend more
than US$ 1,000 per person per annum.
An examination of the figures points up five main
characteristics:
• The trend towards allocating larger amounts of
public resources for social policies has levelled
off, but has not reversed itself. The upward trend
seen up to 2000-2001 in the percentage of GDP
that governments are using for social expenditure
(or, in other words, the macroeconomic priority
assigned to these items of expenditure, which
is a measurement of the effort being made by a
government to allocate resources for social policies)
has been changing since 2002-2003 (see figure 6).

Nevertheless, the simple fact that, at the regional
level, the macroeconomic and fiscal priority
assigned to public social expenditure has been
maintained (albeit with some exceptions) provides
an assurance of continued financing, stability and
greater institutional legitimacy for social policy.
• Public social expenditure remains subject to
strong budgetary constraints and in many cases is
associated with small tax burdens. As a result, the
level of such expenditure is too low in a number
of countries, particularly since there are signs that
the international assistance and borrowings that
used to provide countries with some sort of margin
may cease to be available as financing options for
countries that no longer receive official development
assistance (ODA).
•  n the past one and one-half decades, the less
I
developed countries have made greater increases in
their efforts to allocate resources for social policies.
The effort made by countries in this connection
declines as they become richer. The less developed

Social Panorama of Latin America • 2007

27

Figure 6
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES):
PUBLIC SOCIAL EXPENDITURE AS A PERCENTAGE OF GDP, 1990-1991 TO 2004-2005
35

28.7

30

22.0
20

19.4

18.6

17.7

17.5
13.1

15.9

13.4
11.7

11.6

10.8

10.2

9.9
6.3

5.6

7.9

8.0

10

12.6

Latin America
(simple average)

15

Venezuela
(Bolivarian Rep. of )

Public social expenditure

25

9.4

8.9
7.1

6.3

1990-1991

1998-1999

2000-2001

2002-2003

Uruguay

Trinidad and Tobago

Dominican Republic

Peru

Paraguay

Panama

Nicaragua

Mexico

Jamaica

Honduras

Guatemala

El Salvador

Ecuador

Cuba

Costa Rica

Colombia

Chile

Brazil

Bolivia

Argentina

0

Latin America
(weighted average)

5

2004-2005

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.

Figure 7
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES):
PUBLIC SOCIAL EXPENDITURE AS A PERCENTAGE OF GDP,
BY SECTOR, 1990-1991 TO 2004-2005 a
3.0

18.0

15.9

16.0
14.0 12.9

Percentage of GDP

countries that receive ODA have tended to increase
their efforts in this area more than the relatively
more developed ones have. Bolivia, Honduras and
Nicaragua, which are high-priority ODA recipients,
are cases in point.
• Social security and assistance continue to be the
top priority, followed by education. At the regional
level, over the long term (1990-1991 to 2004-2005)
the increase in this spending effort is equivalent
to three percentage points of GDP. Most of this
increase has been channelled into social security
and assistance, followed, in order of priority, by
education and health (see figure 7). These allocation
decisions presumably reflect a growing concern
about poverty and about protection for older adults
as the population ages.

12.0
10.0

1.7

8.0

7.0

1.0

0.3

6.0
4.0

3.3

5.3

4.3

0

3.4

3.1

2.0
0.0

1.2
Total social
expenditure

Expenditure
on education

Expenditure
on health

Expenditure
on social
security and
assistance

1.2

Expenditure
on housing
and other

1990-1991

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of information available in the Commission’s
social expenditure database.
aWeighted average of the countries.

8

The diversity of functional classifications for public social expenditure in the region makes it difficult to separate the social security component
from the social assistance component in order to make time series comparisons across countries.

28

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure 8
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES):
ANNUAL VARIATION IN TOTAL public SOCIAL EXPENDITURE AND GDP a
(Percentages)
16
14
12
10
8
6
4
2

2005

2004

2003

2001

2002

2000

1999

1998

1997

1996

1995

1994

1991

1993

-4

1992

0
-2

Annual variation in GDP
Annual variation in total public social spending

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database and national accounts.
aWeighted average of the countries.

Orientation and redistributive impact of public social expenditure

The general information available on the
orientation of social spending reveals the following four
characteristics:
• A degree of progressiveness is linked to increases
in the coverage of spending on education. The
9

10

Figure 9
LATIN AMERICA (18 COUNTRIES): DISTRIBUTION OF PUBLIC
SOCIAL SPENDING BY PRIMARY INCOME QUINTILE, 1997-2004 a
(Percentages)
100

Cumulative percentage of expenditure

In the presence of budgetary constraints, governments will
try to channel more resources into social services for the
lowest-income sectors. Because of budget commitments
and the nature of access to public services, however, some
components of public expenditure will not exhibit the
expected degree of progressiveness, despite governments’
best efforts and use of targeting instruments to this end.
In recent decades, public social policy has —with some
differences across countries— had to counteract the impact
of State reforms that have gradually increased the level
of private social-service financing and delivery and have
tended to be of greater benefit to higher-income sectors.9
Social spending has become more progressive as the
coverage of public services has expanded (particularly
in the cases of education and health) to include more
economically depressed or isolated geographic (e.g.,
rural) areas, which tends to benefit lower-income strata
proportionately more.10

90
Education

80
70

Health

60
Public social
expenditure
(indudes social welfare
and housing)

50
40

Social
security

30
20

Primary
income

10
0
0

20

40

60

80

100

Cumulative percentage of population

Source: Economic Commission for Latin America and the Caribbean
(ECLAC) on the basis of national studies.
aWeighted average for the significance of each item of expenditure in
the primary income of each country. The progressive items in absolute
terms are on the diagonal, which is the line of equidistribution.

Sectors with greater payment capacity or the ability to exert political pressure due, in part, to their concentrate in large metropolitan areas.
This gives medium- and low-income sectors gradual access to education and health care and, at the same time, as part of explicit efforts to
combat poverty, caters to population sectors that have traditionally suffered from exclusion.

Social Panorama of Latin America • 2007

order to curb or mitigate the deterioration in the well-being
of those sectors that are most vulnerable to changes in the
business cycle. The wide range of programmes that provide
such assistance focus on the sectors subject to the highest
degrees of social exclusion. Generally speaking, spending
on social assistance in the region is quite progressive: on
average, 55% of social assistance expenditure is received
by the poorest 40% of the population, and 60% of that
reaches the poorest quintile.
Anti-poverty programmes, particularly those that
use conditional transfer mechanisms, are among the most
progressive categories of social expenditure (see figure 10).
The information gathered for this study does indicate,
however, that even with these programmes there is some
“leakage” into higher-income sectors. This points to the
existence of certain problems in the area of targeting.
Figure 10
LATIN AMERICA (11 COUNTRIES): distribution of public
spending on social welfare programmes by primary
income quintile, 1997-2004 a
(Percentages)
100

Heads of household programme
(Argentina, 2003)

90

Cumulative percentage of expenditure

increase that has occurred over time in the coverage
of the various levels of public education (preschool,
primary, secondary and tertiary) has made it possible
to gradually incorporate lower-income sectors of the
population into the education system. As a result,
today, spending on primary education is highly
progressive, unlike the case in the other cycles
of the education system. Since progress through
these cycles is linked to students’ socioeconomic
status, public funding for higher education tends
to favour the most affluent sectors. In fact, in all
countries, public financing for tertiary education
is highly regressive.
• The composition and location of benefits determine
what impact they will have in terms of the equity
of health expenditures. The redistributive effect of
such expenditure has increased, and it has become
more progressive than spending on education
due to the scale of expenditures on preventive
health care, first aid and outpatient services in
the poorest sectors of the population relative to
spending on hospital services (which, depending
on the country in question, may be either slightly
progressive or actually regressive). The main reason
for this is the high investment costs involved in
expanding hospital coverage, since this means
that such services are frequently confined to the
most densely populated areas and those who can
afford to make co-payments.
• Because of the essentially contributory nature of social
security, expenditure in this category is regressive.
Social security systems are generally designed in
such a way that access to benefits is determined by
people’s contributory capacity and, hence, by their
position in the labour market. This is why social
security expenditure is so highly regressive, since
it favours people with formal-sector jobs that give
them a greater contributory capacity. Efforts to
increase coverage have tended to retain or expand
the contributory funding mechanisms that were
designed decades ago, which in some cases include
subsidies or solidarity components.
• Social assistance is becoming a pro-poor form of
social expenditure. The purpose of social assistance
is to counterbalance disequilibria in access to
productive resources and the labour market as
well as to other social benefits. In the case of this
type of expenditure, targeting gives expression to
a principle of social policy by permitting priority
to be placed on minimum levels of benefits for
the poorest sectors.
Social assistance should be countercyclical so that, at
times of economic crisis, these benefits can be expanded in

29

Oportunidades
programme
(México, 2002)

80

70

Chile Solidario
programme
(Chile, 2003)

60

Total social welfare
50

40

Human development bond
programme (Ecuador, 1999)

30

20

10

0
0

20

40

60

80

100

Cumulative percentage of population

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national studies.
aWeighted average for the significance of each item of expenditure in
the primary income of each country.

30

Economic Commission for Latin America and the Caribbean (ECLAC)

Redistributive impact of public social spending 11
One way of assessing the management of public policy
and social programmes is to measure their effect on the
distribution of primary income. This involves quantifying
goods and services transferred to the population and
assessing their monetary value. The way in which social
programmes help to increase disposable household income
and make short-term changes in the household’s primary
income distribution can thus be evaluated.
Public social spending does not have a significant
redistributive effect in the sense of substantially reducing
income concentration. This is mainly because such spending
only represents 19.4 % of primary household income.
Another reason is that this resource is not allocated solely
for the purposes of improving equity. Social spending
provides a dramatic boost to the well-being of the poorest
in society: on average it doubles the disposable income of
the poorest quintile, while also having significant effects
on other strata. For the wealthiest quintile, social spending
increases their income by 9 % (see figure 11).
Of all the forms of social spending, that which has
the greatest impact on the primary income of the poorest
groups is education, as it accounts for 40% of the transfers
received by the lowest quintile (7.4% of total social spending,
see figure 12). The next most important heading is health,
followed by social assistance. The order is the same for
the second quintile, with social security becoming more
important for the third quintile, while representing the
most significant transfer for the fourth and fifth quintiles
(social security represents 59% of the public resources
received by the higher income quintile).
The manoeuvring room that public policy makers
have for increasing the progressivity of social spending
is understandably limited, as the distribution of certain
headings that make up a large proportion of resources
(such as social security) are the result of long-standing
contractual commitments. In addition, the targeting of
expenditure in areas like education and health depends
on the level of coverage and widespread access to public
services. It also depends on the development of publicprivate partnerships to guarantee both access for the poorest,
as well as high-quality yet affordable private options for
those with less resources. This will reopen the debates on
which components should be guided by the principle of
universality and which expenditure should be targeted;

11

Figure 11
Latin America (18 countries): a redistributive impact of
public social spending on income, by primary income
quintiles, 1997-2004
(Percentages)
100

9

90
80
70
60
91

50
40
16

30
22

20
10
0

30
51
49
Quintile I

Quintile II

84
78

70

Quintile III

yprim

Quintile IV

Quintile V

social spending

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national studies.
aAverage weighted by the significance of spending for primary income
in each country.

Figure 12
Latin America (18 countries): a Breakdown of spending
by primary income distribution quintiles, 1997-2004
(In percentages of total social spending)
30%
1.1
25%

0.9

20%
3.3
15%

0.8
2.0

10%

5.1

5%

0%

1.3
1.4

1.6
1.1

2.1
0.9

16.5

2.8

4.3

6.3

4.7

4.2

4.0

3.7

7.4

6.5

6.3

5.9

5.8

Quintile I

Quintile II

Quintile III

Quintile IV

Quintile V

Education

Health

Social security

Housing

Social assistance

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national studies.
aAverage weighted by the significance of spending for primary income
in each country.

Although it is important to improve means of targeting to focus resources on those who most need them, it is also vital to increase the cost
effectiveness of the many social programmes. Low-cost measures (such as distributing food rations to tackle or prevent child undernutrition)
often have a significant social impact in terms of improving a situation or reducing the risks for households or the State.

Social Panorama of Latin America • 2007

31

and also, in the light of the principle of efficient allocation
of resources, debates on how to set up solidarity-based

and non-contributive mechanisms for benefits that should
be universal in a social protection system.

Public social spending by groups of countries: towards a composite typology
One aid to understanding the challenges of social policy
funding is a new indicator of dependency between citizens
working in the formal sector and the rest of the population.12
The purpose of this indicator is to assess the potential
capacity of social protection systems (financed through
contributive mechanisms used by formal workers) to meet
the needs of those people who do not directly access social
services in the context of such a system of financing. The
indicator makes it possible to define countries according
to their level of development and the stages they have
reached in terms of demographic transition and maturity
of the labour market (see figure 13).
Figure 13
Number of dependents for every formal worker,
according to per capita GDP

Number of dependents per formal worker

10

BOL
HND

9
8
GROUP I

7

PRY
ECU
JAM
PER
GTM
NIC
SLV

6
5
4
3

Latin America
(simple average)
DOM
Latin America
(weighted average)
VEN
COL
MEX
PAN
URY
BRA
CRI
CHL

GROUP
II
ARG

GROUP III

2
1
0

0

5 500

11 000

16 500

Per capita GDP, 2000 purchasing power parity

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national accounts and household surveys of
the countries concerned.

There emerges a first group of countries with per capita
GDP of under US$ 5,500 (purchasing power parity (PPP)
of 2000), that are at an early stage in terms of demographic
transition and mature labour markets. Such countries
therefore have high levels of dependency for each formal

12

worker, with needs mainly concentrated among young
people and the underemployed. The second group of
countries has surpassed the development threshold of
a per capita GDP equivalent to US$ 5,500, but is still
trailing in the demographic transition and maturing of
its labour markets, with between 4.5 and 6 dependents
per formal worker. In these countries, the needs of
young people remain paramount, although to a lesser
degree, while non-workers and the underemployed
make up a larger proportion. Like the second group, the
third group of countries has exceeded the US$ 5,500
threshold for per capita GDP and has between 3 and
4.5 dependents for every formal worker. The burden of
young people’s needs remains high, and other groups
to emerge include the underemployed, non-workers
and older adults (see table 3).
This typology shows six characteristics of the implicit
social contracts that govern the allocation of expenditure.
First, transition societies in group II have needs that are
increasingly similar to those of group III, but with a spending
structure that remains more like group I (i.e. a marked
lack of spending on social security and assistance).
Second, irrespective of their level of development, all
countries allocate a relatively similar percentage of public
social spending to health spending. Spending on housing,
however, falls in proportion with the rise in a country’s level
of development. Health spending represents around 20%
of public social expenditure. Social spending on housing,
on the other hand, differs according to a country’s level of
development and dependency ratio.
Third, the biggest contrast in the groups of countries
is between the allocation of resources for education and
those for social assistance and security. The countries of
groups I and II allocate the largest percentage of their
spending (between 30% and 40%) to education, and
the remainder to a combination of social assistance and
security and housing (especially the former). In countries
of group III, spending on housing represents a mere 5%
of the total, whereas they allocate over 50% to social
assistance and security.

Ratio of children under 15 years of age, older adults, non-workers, the unemployed and informal workers to every worker employed by the
formal sector. See Economic Commission for Latin America and the Caribbean (ECLAC)/Ibero-American Secretariat (SEGIB), Espacios
iberoamericanos (LC/G.2328), Santiago, Chile, October 2006.

32

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 3
TYpologY of countries, by challenges to social contract

GDP per
capita,
PPP in
2000
dollars

GDP per
capita,
in 2000
dollars

Dependents
Social
Social
per formal
spending spending
worker
per capita, per capita,
PPP in
in 2000
2000
dollars
dollars

Breakdown of dependents
per formal worker
(percentage)

Breakdown of public
social spending
(percentages)

Concentration
index

Young people

42.4 Education

Older adults

8.3 Health
19.5 Health
Social security
30.7 Social security
18.7
and social welfare

Non-workers
2 000 5 500

800 2 800

6 to 10

230 - 480

90 - 290

Unemployed or
informal workers

30.6

Total dependents

Group I

Housing and
others

41.5 Education

100

8.3

Social welfare
Housing and
others
Total public
spending

Percentage of
formal workers a

38.7 Education

Older adults

10.0 Health
21.9 Health
Social security
24.4
27.1 Social security
and social welfare

Non-workers

Group II

4.5 to 6

500 1 210

Unemployed or
200 - 845 informal workers
Total dependents

Housing and
26.9
others

36.8 Education

14.2 Social welfare
Housing and
others
Total public
spending

100

Percentage of
formal workers a

35.4 Education

Older adults

12.0 Health
21.3 Health
Social security
23.5
52.2 Social security
and social welfare

Non-workers

Group III

3 to 4.5

1 400 2 400

700 1 550

0.504
-0.089
0.206
0.143

0.116
-0.073
0.568
-0.154
0.067
0.042

45.9

Young people

more than
US$ 5 500
more than
US$ 2 800

0.074

31.7

Young people

-0.087

Unemployed or
informal workers

29.1

Total dependents

100

Percentage of
formal workers a

Housing and
others

21.6 Education

4.9

Social welfare
Housing and
others
Total public
spending

-0.138
-0.192
0.349
-0.484
-0.026
0.044

54.2

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the relevant countries, national
reports, household surveys, population estimates from the Latin American and Caribbean Demographic Centre (CELADE) - Population Division of
ECLAC and World Bank, World Development Indicators [online database] www.worldbank.org/data/onlinedatabases/onlinedatabases.html.
aRefers to people aged 15 to 59 employed in the formal sector in relation to total employed for that age group.

Fourth, the less developed countries made more
effort to increase public funding channelled into social
policy between 1990-1991 and 2004-2005 (see figure 8).
In all countries, the main priorities are social assistance
and security, followed by education. This represents
growing concern over the financing of retirement and
pension systems, and the priority governments attach
to improving the coverage and quality of education.
Despite this progress, groups I and II still lag behind in
spending on social assistance and security and health
in relation to the levels of expenditure of group III and
their ageing societies.

Fifth, all three groups of countries tend to manage
public social spending on a completely procyclical basis
(see figure 14). This is partly to do with the significance of
wage expenditure in all countries, and partly to do with the
need to manage country risk. Only group I countries display
a counter-cyclical trend due to the nature of the official aid
they receive for development and natural disasters.
Sixth, the greater levels of social security coverage in
countries with higher levels of development and population
ageing involves allocating more resources to programmes
that do not have a major impact in terms of reducing
inequity. However, the regressiveness of such spending
falls as countries increase social security coverage.

Social Panorama of Latin America • 2007

33

Figure 14
Trends in public social spending, by groups of countries

(b) Group II: Venezuela (Bolivarian Rep. of), Panama, Dominican
Republic, Mexico, Trinidad and Tobago

(a) Group I: Bolivia, Honduras, Jamaica, Ecuador, Guatemala,
Paraguay, El Salvador, Peru
3.4

10.0

25.0
8.6

9.0
8.0

20.0

7.0
6.0

5.2

15.0

1.3

5.0
4.0
3.0

0.4

2.3

2.0

10.8

1.3

3.6

10.0
2.7

1.7

1.3

Education
spending

Health
spending

-0.1

5.0

Social
security
spending

2.2

4.0

2.8

0.7

0.4
Total social
spending

1.2

6.9

0.3

1.4

1.0
0.0

3.8

2.5

1.0

0.7
0.0

Housing and
other spending

Total social
spending

Education
spending

Health
spending

0.5
2.9

2.4

Social
security
spending

1.5

Housing and
other spending

1990-1991

1992-1993

1994-1995

1996-1997

1990-1991

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

1998-1999

2000-2001

2002-2003

2004-2005

(c) Group III: Brazil, Costa Rica, Uruguay, Chile, Argentina
25.0

20.0

2.4
20.5
18.1
1.4

15.0

10.7
9.3

10.0
0.8
5.0

0.7
4.4

3.6

-0.5

4.4

3.7

1.5
0.0

Total social
spending

Education
spending

Health
spending

Social
security
spending

1.0

Housing and
other spending

1990-1991

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the Commission’s social expenditure
database.

Public spending and social contract
Efforts to increase public social spending seek to bridge
the gap between needs and emerging risks, on the one
hand, and the scarce resources available in social protection
systems, on the other.
The creation of mortgage management sectors has
resulted in a gradual handover of housing provision from
the public to the private sector, with financing now in
the hands of families supported by State subsidies. The

same has happened with education in the most developed
countries, where private supply has grown to meet the
demands of high-income groups. Many countries have
changed the ways in which social security and health
benefits are funded and provided, basing the system on
workers’ contributions to social security systems.
The rising presence of the region in global markets has
also required spending policy to be linked to the business

34

Economic Commission for Latin America and the Caribbean (ECLAC)

cycle to avoid harming countries’ access to credit markets,
except when fiscal surplus policies have been established
in periods of robust growth (as in Chile) to give stability
to social investment when the economy stalls. Marketoriented reforms and the practice consisting in making
social benefits subject to individual insurance contracts
highlight the need for greater regulation and availability of
non-contributive financing in order to reconcile efficiency
and solidarity. This should form the basis for the debate
on a new social contract for social cohesion, as the current
system leaves many risks uncovered and requires correction
to redistribute resources to the most vulnerable groups and
apply the countercyclical rule to social spending.13

13
14
15

16

Latin American societies cannot escape the challenges
inherent in the nature of social spending. Sooner or
later they will have to discuss specific arrangements
and guidelines. Social change is forcing the authorities
to devise a feasible strategy for meeting new needs
without having satisfied existing ones. Given current
low levels of expenditure, resources should be allocated
with increasing transparency on the basis of redefined
priorities.14 The right combination of efforts by families
and the State should be at the heart of a social contract.15
Such a contract should study the correct dimension
of public funding and identify priorities for the main
social investments.16

See Economic Commission for Latin America and the Caribbean (ECLAC) and the Ibero-American Secretariat (SEGIB), Social cohesion.
Inclusion and a sense of belonging in Latin America and the Caribbean (LC/G.2335), Santiago, Chile, January 2007.
With universal coverage at certain levels of education to invest in children and young people in group I countries, then support to families to
help reconcile work and caregiving in group II countries, and on to basic pension and health guarantees for the countries of group III.
In the absence of a social contract, the region has put into practice different proposals aimed at strengthening the market and reducing the role
of the State. These have proved costly and resulted in exclusion. To counter this, ECLAC and the Ibero-American Secretariat (SEGIB) suggest
the need for an agreement to rebuild public social policy and improve well-being.
See Economic Commission for Latin America and the Caribbean (ECLAC), Shaping the Future of Social Protection: Access, Financing and
Solidarity (LC/G.2294(SES.31/3)/E), Santiago, Chile, March, 2006.

Social Panorama of Latin America • 2007

35

The quality of education:
inequalities that go beyond access
and educational progression
The considerable expansion of education coverage,
which in some countries applies to the entire school-age
population, is one of the sector’s most striking advances
in recent decades. These advances have been the result of
pro-active social and educational policies, often involving
transformations of management methods in education
systems, sustained budgetary increases, diversification
of funding systems and participation of economic agents
and social stakeholders.
Nevertheless, the achievements have not been evenly
spread throughout all spheres of education, and have

served to highlight shortcomings in terms of the quality
of education. To a large extent, the various problems
relating to quality and other difficulties of the education
system (school completion, repetition and drop-outs)
are manifestations of a much deeper and entrenched
phenomenon: social inequality.
This document examines different educational
advances in the region, the various manifestations of
inequality throughout the education cycle, and the
way in which some of these are part of the problem of
education quality.

Advances in the right to education:
access, progression and completion
Access to education. One of the main achievements has
been the increased access of children and young people
to the formal education system. This is partly the result
of significant investment that countries have made in
infrastructure, which has made it possible to extend the
coverage of educational services. However, this has not
always gone hand in hand with the necessary expansion in
the number of teachers and the provision of the materials
needed to support the learning process.
Since the beginning of the 1990s, access by the
school-age population has increased throughout education,
especially at the higher levels. This is mainly a reflection of
rising standards of attainment in primary education, which
are needed for pupils to go on to the next level. However,
progress in access to pre-school education has been more
moderate, despite the acknowledged importance of early
education in stimulating the learning process for the rest
of children’s lives. Around 2005, just over 84% of children
were attending the final year of pre-primary education.
School attendance among children of primary-school
age is practically universal (97%), although access was
already widespread (91%) at the beginning of the previous
decade. There have been significant rises in net access (pupils
attending school at the level that corresponds to their age) of
17

children in the lower and upper cycles of secondary education
and at the post-secondary level: the net attendance rate in
the lower cycle has gone from 45% to 69%; has almost
doubled in the upper cycle from 27% to 47%; and in the
post-secondary level has risen from 11% to 19%.
General advances in terms of coverage and access
have been of greater benefit to low-income strata, although
these are also more affected by the progressive reduction
in access over all levels of education.
Educational progression. Under-attainment and
grade repetition act as a disincentive for retaining lowincome students, as the opportunity cost of finishing
education cycles rises. High costs are also involved for
education systems. According to estimates by the United
Nations Educational, Scientific and Cultural Organization
(UNESCO), the region spends some US$ 12 billion per
year as a result of grade repetition.
According to information from household surveys,
between 1990 and 2005 there was a considerable increase
in the timely progression of children aged 10 to 14
throughout primary education17 and in some levels of
secondary education (from 55% to 78%). The percentage
of timely promotions among students aged 15 to 19 also
rose significantly (from 43% to 66%).

Most countries have automatic promotion processes in the first two years of primary school, and sometimes up to the fourth grade of primary.
This therefore significantly brings down the level of underachievement for those particular cohorts.

36

Economic Commission for Latin America and the Caribbean (ECLAC)

In the youngest cohort, the advances have been
proportionally more beneficial to low-income pupils, except
those from the first income quintile. In the cohort aged 15
to 19, the advances have been more unequal: favouring
mainly students from middle-income strata (see figure
15). Despite considerable increases in access for the most
disadvantaged strata, students from such groups nonetheless
find it more difficult to progress, particularly when they
reach early and late secondary cycles. As a result, disparities
in educational underachievement have widened.
Figure 15
LATIN AMERICA (17 COUNTRIES): YOUNG PEOPLE, AGED
15 TO 19, who have moved up steadily through THE
SECONDARY school system BY PER CAPITA INCOME DECILE
of their households, AROUND 1990 AND 2005 a
(Percentages)
100
90
80
69

70
60
50

72

68

48

40

36

30

26

62
47

44
38

25
71

62

56

52

85

80

76

51

20

54
15

40

30

10

20

5

10
0

Total

Decile 1 Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Decile 10

1990

2005

Amount of progress (percentage points)

30
88

Completing levels of education. Advances in this area
have been even more impressive than progress in terms of
access, mainly because levels of achievement recorded in the
late 1980s and early 1990s were considerably lower.
Around 2005, approximately 92% of young people
aged 15 to 19 had completed their primary education.
Completion of the early-secondary cycle rose from
53% to 71%, partly thanks to the efforts of many of the
region’s countries to make this cycle compulsory. The
most significant progress was made in the completion of
the second cycle of secondary education. Over the course
of about 15 years, the percentage of young people aged
20 to 24 to have completed that cycle almost doubled
from 27% to 50%. There were also improvements in the
completion of higher education, although on a smaller
scale: the percentage of young people aged 25 to 29 to
have completed at least five years of higher education
increased from 4.8% to 7.4%.
Although the various advances have reduced inequality
in educational achievement, the effect has been much less
significant at higher levels of education, to the extent that
completion progress in higher education has involved a
low proportion of low-income students and has almost
exclusively benefited young people from middle- and
high-income strata.

0

Amount of progress (percentage points)

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of data from household
surveys conducted in the respective countries.
aAllowance is made for one year’s lag in cases of late entry into the
school system.

Transmission of educational opportunities
The principle of universalizing access to education aims
to provide people with the necessary opportunities for
accessing, progressing through and completing a learning
process, plus the certification thereof. Although equal
opportunities in education do not guarantee individual
and family well-being, unequal opportunities certainly
perpetuate poverty. Inequality of opportunities is a factor
of reproduction, in that it can either facilitate or hamper
the main mechanism for accessing long-term well-being.
This has led to claims that educational capital is, to a
certain extent, inherited.

The differences in access to education between
those from households with low educational capital
and those whose parents completed higher education
tends to increase in proportion with the age of the
children concerned. This difference in educational
opportunities is not too great up to the age of 14 or
15 but increases from then onwards, such that only
26% of young people aged 18-19 whose parents have
low levels of education continue their studies. There
are also major differences in terms of progression
through school.

Social Panorama of Latin America • 2007

37

Figure 16
LATIN AMERICA (18 COUNTRIES): COMPLETION OF PRIMARY
EDUCATION (YOUNG PEOPLE AGED 15 TO 19),
SECONDARY EDUCATION (AGES 20 TO 24) AND HIGHER
EDUCATION (AGES 25 TO 29), BY HOUSEHOLD EDUCATIONAL
ENVIRONMENT, a AROUND 2005
(Percentages)
97.1

100
90

85.5

98.3
92.7

80

98.8

98.4
91.1

90.8

71.6

70
60
50

51.9

40
30

32.7

18.7

20
10
0

5.9

3.1
Primary
incomplete

Up to secondary
incomplete

5.4
Secondary
complete

Technical and
higher
education
incomplete

Higher education
complete

The across-the-board increase in attainment at the
primary level has benefited the children of parents with
a lower level of education in particular. Although there
has also been significant progress in completion rates at
the secondary level, the differences remain as entrenched
and affect students in the two lowest strata whose parents
have a lower level of education. No improvement has been
observed in higher education. Although completion rates
have risen in higher education, the pattern of attainment
remains dependent on the educational environment of
the household (see figure 16). All of the above serves to
maintain the highly rigid social structure in Latin America,
and continues to hinder social mobility. This is because,
as the completion of primary and secondary education
becomes more commonplace, so such achievements lose
some of their value.

Household educational environment
Primary

Secondary

Higher

Source: Economic Commission for Latin America and the Caribbean (ECLAC),
on the basis of special tabulations of data from household surveys.
aAverage number of years of schooling of the head of household and
spouse, as a way of estimating parents’ education. Among those
aged 25 to 29, the indicator is more biased as a relatively significant
proportion has set up their own households. However, using young
people of that age who describe themselves as children of the head of
household considerably reduces sample sizes.

Quality of education: another manifestation of inequality
Children enter a system that offers very different services
and from the outset are affected by structural inequalities.
Initial inequalities are maintained or deepened within the
education system, and it can no longer be assumed that
children inevitably learn once in school. In this context,
equity cannot be conceived as an educational equality
whereby all children are treated in the same way, but
rather a process of differentiation must be undertaken so
that discrepancies can be compensated for in a way that
will lead to equal opportunities.
In this sense, ensuring quality education for all
would constitute a lifelong process of inclusion (ensuring
respect for the right to education, equal opportunities and
participation), which would provide the tools needed to
face the various obstacles that exclude or discriminate
against students and limit their learning or full development
as people. Quality education for all, in addition to being
18

the response to a demand for equity, must be significant
and relevant.
According to the results of the reading comprehension
test organized in 43 countries by the Organisation for
Economic Co-operation and Development (OECD) as part
of the Programme for International Student Assessment
(PISA),18 the Latin American nations that took part (Argentina,
Brazil, Chile, Mexico and Peru) generally obtained the
worst distributions of results: in the 27 OECD countries
about 15% of students were below level 1 (out of 5),
compared with 45% in 11 countries from other regions
(mainly Asia), and over 54% in Latin America.
Given that the heterogeneity of results within in each
country is partly due to the variety of grades or levels
among pupils of the same age, students from one grade
only were selected: 10th grade, which is usually the final
cycle of early secondary school.

The 2000 round of the Programme for International Student Assessment (PISA), which involved the largest number of Latin American countries
to date, was based on the language test administered to the entire sample. The mathematics and science tests were only given to partial samples.
It was therefore decided to analyse the language test, as this had the most robust statistical results.

38

Economic Commission for Latin America and the Caribbean (ECLAC)

Factors associated with differences in educational results

In addition, teachers’ commitment may be strengthened
or weakened by other work conditions: teaching materials
and equipment, management, student ability and motivation,
school environment, etc.
• The relevance of education. Although some problems
of education quality are usually attributed to social
inequality and educational segmentation, the general
characteristics of education systems should not be
ignored. According to international criteria, not
even the more affluent Latin American students

19

Figure 17
LATIN AMERICA (17 COUNTRIES): AVERAGE ANNUAL RATIO OF
TEACHERS’ INCOME AND WAGES TO THOSE OF OTHER WAGED
PROFESSIONALS AND TECHNICAL WORKERS, AROUND 2005
(Purchasing power parity in 2000 United States dollars
and percentages)
25 000

90

22 500

80

20 000

70

17 500

60

15 000

50

12 500

40

10 000

30

7 500

20

5 000

Colombia

Chile

Costa Rica

Mexico

Honduras

Brazil

Argentina

El Salvador

Nicaragua
Venezuela (Bol
Rep of)
Uruguay

Paraguay

Guatemala

Bolivia

Dominican Rep

2 500
Peru

0

Ecuador

10

PPP in 2000 dollars

100

Percentages

General evidence suggests a strong link between levels of
per capita GDP and educational performance. However,
the performance of the region’s students is lower than
expected given the countries’ level of wealth, which
points to the existence of other factors that have a more
direct impact on performance.
• Teachers and school environment. According to
evidence from the PISA test, the level of teacher
training and support in the region is less associated
with heterogeneous performance than in OECD
countries. This suggests that, in Latin America,
extra-scholastic factors have more effect on
differences in performance. There is also a lack
of significant difference in the characteristics of
teachers (number of teachers, level of training,
experience, and so on) in various forms of
educational institutions (public as opposed to private,
with good or poor infrastructure, or with poor
rather than wealthy pupils). The most significant
aspect was the level of teacher commitment to
activities and to the students,3 and is associated
with the aforementioned characteristics of specific
schools. One of the issues that kept cropping up
in the analysis of the education sector’s problems
was that of performance incentives for teachers,
particularly in the form of wages. Although wages
are not necessarily a source of motivation, they
can become a cause of dissatisfaction. Despite the
fact that teachers’ wages enable most families to
live free of poverty, they often do not provide a
standard of living that lends itself to professional
development (see figure 17). This has a negative
effect on continuing professional development
and discourages young people in higher education
from becoming teachers.

0

Teachers wages/wages of other professional and technical workers
Annual wage of teachers
Annual wage of other professional and technical workers

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of United Nations Educational, Scientific and
Cultural Organization (UNESCO)/UNESCO Regional Office for Education
in Latin America and the Caribbean (OREALC)/International Institute for
Educational Planning (IIEP), La inversión educativa en América Latina y
el Caribe. Las demandas de financiamiento y asignación de recursos,
Buenos Aires, 2007.

sufficiently develop skills in reading comprehension,
interpretation, relations and abstraction. The results
suggest that educational curricula do not match
the skills required in today’s world, which is why
even the wealthiest students are affected. This
strengthens the argument put forward by UNESCO
that the need to improve the quality of education
is now essential for the region.
• Social inequality and unequal capacity building.
The main factors associated with differences in
scores are extra-scholastic: parents’ educational
level and socio-occupational status, material
well-being of the household (general equipment)
and educational and communication materials
available at home. In all countries analysed,
the intergenerational transmission of education
opportunities continued to operate, this time in
the building of capacities and skills essential for
a full participation in society.

Measured using an index of headteachers’ evaluations of teacher morale, commitment to their work, pride and identification with the school
and valuing of the academic achievement of pupils.

Social Panorama of Latin America • 2007

Figure 18
LATIN AMERICA (5 COUNTRIES) AND OECD (7 COUNTRIES):
COMPOSITION OF EDUCATIONAL COMMUNITIES BY SOCIOOCCUPATIONAL LEVEL OF PARENTS, AND PARTICIPATION
OF STUDENTS a IN SCHOOLS WITH GOOD EDUCATIONAL
EQUIPMENT, b ACCORDING TO PARENTAL SOCIOOCCUPATIONAL QUARTILES
(Ratios and percentages)

25
19

20

19

15

11
9

9
6

5

Mexico

Chile

Brazil

5
0

10

4.8

5.4

OECD
countries c

10

13
10

Latin American
countries

12

Peru

20

Argentina

Ratio of belonging to low- and high-level
educational communities

(a) Homogeneity of educational communities (school segregation)

Low-level school communities: number of pupils from a low level for every
high-level pupil
High-level school communities: number of pupils from a high level for every
low-level pupil

(b) Students who attend schools with well-equipped schools
100
90
80
70

61

60

59

38

Argentina

Chile

23

38

32

25

Mexico

30
20

65

58

39

40

OECD
countries c

Latin American
countries

10
Peru

0

64

47

50

10

64

Brazil

Percentages

However, in developed countries there are fewer
inequities than in Latin America when people enter
education, and the education obtained has less effect on
the level of well-being that can be reached in a lifetime.
In this sense, socioeconomic inequality is less pronounced
and, above all, has less impact on the development of
language skills. Differences in the educational “premium”
(income) are also smaller. One important challenge facing
the region is therefore to reduce inequalities in the quality
of employment associated with level of education.
• Educational segregation. One of the common
problems in education systems is the socioeconomic
and geographic segmentation of service quality.
Wealthier parents prefer to send their children to
schools with more resources, and those schools
usually favour the entry of pupils from families
with higher levels of well-being. Those from lowerincome backgrounds, on the other hand, often have
a very small number of educational options. The
schools that take low-income pupils tend to have
shortcomings in terms of infrastructure, educational
inputs and the number and training level teachers.
These are almost always public schools in lowincome or rural areas, where they are practically
the only school available for nearby students.
This “self-selection” process, which tends to be
concentrated at the two ends of the social spectrum, can
turn schools into “ghettos”, with both high-income and
low-income school communities (educational segregation).
This results in some schools having environments conducive
to learning and skill-building, while in others difficulties
are more likely to be generated.
Latin American countries display much more
homogeneity in the composition of school communities
(in terms of parents’ socio-occupational status and
levels of material well-being) compared with developed
countries. This is even more true of students from the
most comfortable backgrounds, except in Argentina,
where the trend is more pronounced among poorer
students. In OECD countries, a high-income student is
five times more likely to belong to a school community
with high well-being than a low-income student. In
Latin America, this ratio is 10 to 1. The situation is
acute in Peru and Chile, where the ratio is over 20 to 1
(see figure 18a).
Added to this is the segmentation of educational
supply. In the region’s countries, inequalities in access
according to classification in the upper or lower quartiles
of the socio-occupational index are more pronounced than
in developed countries. Whereas 59% of students from
the highest quartile attend schools with a good level of
educational equipment, the same can only be said of 32%
of those from the lowest quartile (see figure 18b).

39

Pupils from quartile 4 who attend well-equipped schools
Pupils from quartile 1 who attend well-equipped schools
Average

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of Organisation for Economic Co-operation
and Development (OECD), “Programme for International Student
Assessment” [online database] http://www.pisa.oecd.org.
aStudents in 10th grade.
bSchools were divided into two levels on the basis of educational
equipment (library, multimedia tools, computer laboratories, chemistry
laboratories, etc.).
cTotal of 27 countries excluding Mexico. Regional totals are weighted.

At the two ends of the social spectrum, school
communities tend to be more homogenous. Rich and poor
students are separated, with a significant proportion of
the latter attending public schools with infrastructure and
other problems, while the former attend well-equipped
private schools.

40

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure 19
LATIN AMERICA (5 COUNTRIES):
DISTRIBUTION OF LEVELS OF PERFORMANCE IN THE READING
TEST AMONG TENTH GRADE STUDENTS,
BY SOCIO-OCCUPATIONAL STATUS OF THEIR PARENTS AND
EDUCATIONAL EQUIPMENT OF THEIR SCHOOLS
(Percentages)
100

40

3
0.3 15
0 0.1 6
24 37
11 17

20

38 32 38 31

80
60

0

12
34 37 24 2
8
11
16

20
40
60

Peru

Brazil

Chile

Argentina

Mexico

Below level 1

Level 1
Level 4

Quartile 4 least well-equipped
Quartile 4 best-equipped

Latin
American
countries

Level 2

Level 3

Quartile 1 least well-equipped
Quartile 1 best-equipped

Quartile 4 least well-equipped
Quartile 4 best-equipped

Quartile 1 least well-equipped
Quartile 1 best-equipped

Quartile 1 least well-equipped
Quartile 1 best-equipped

Quartile 4 least well-equipped
Quartile 4 best-equipped

Quartile 4 least well-equipped
Quartile 4 best-equipped

Quartile 1 least well-equipped
Quartile 1 best-equipped

Quartile 1 best-equipped
Quartile 4 least well-equipped
Quartile 4 best-equipped

Quartile 1 least well-equipped

Quartile 1 least well-equipped
Quartile 1 best-equipped
Quartile 4 least well-equipped
Quartile 4 best-equipped

80
100

Level 5

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of Organisation for Economic Co-operation
and Development (OECD), “Programme for International Student
Assessment” [online database].

High levels of educational segregation and segmentation
reinforce inequalities in how pupils make use of the
educational process: the sociocultural disadvantages of
low-income students are combined with access to lowerquality educational services, which all results in lower
levels of learning. Among poor students who attend
poorly equipped schools, 12% performed adequately at
the third level or higher in terms of reading skills, while
the percentage was 20% among those who attend better
equipped schools. In the richest quartile, these percentages
rise to 30% and 55%, respectively (see figure 19).
Generally speaking, the educational system in Latin
America is more affected by the region’s highly unequal
social structure. The rise in secondary schooling accentuates
the stratification of institutional service provision, and the
territorial nature of education services increases school
segmentation. Both the traditional and more modern elites
send their children to schools that provide a full day of
teaching and a varied curriculum. In addition, within
their strata these students form bonds that reinforce the
social networks and capital needed to find a good job.
Poorer students, on the other hand, usually attend schools
with greater shortcomings in terms of infrastructure,
curriculum and general resources. Social stratification
is therefore reproduced at school, thereby weakening
the capacity of educational systems to provide children
and young people with more equal opportunities. Given
the above, the educational system acts more like a social
differentiation mechanism that lays the foundations for
the inequalities that will be subsequently reproduced on
the labour market.

Conclusion
The quality of the education received by children and
young people is largely dependent on their economic
resources. This is linked to the educational environment of
the household, the effects of which include the existence
of a home environment more or less suited to reinforcing
the learning process. As attainment at the primary and
secondary school levels has become more widespread,
disparities in educational quality now plays a major
differentiating role in the transition to post-secondary
education, which provides the key to decent jobs and
sufficient wages. The quality of education therefore
becomes a focus in the intergenerational reproduction
of opportunities for well-being.
Although such extra-scholastic factors carry some
weight, any review of student performance shows that
these can be offset from within the educational system.

Studies of schools with outstanding performance in adverse
socioeconomic conditions indicate the importance of
school management, including less emphasis on hierarchy
and authoritarianism, respect for people, close relations
with parents and participation in the decision-making
process. In terms of teaching practice, positive factors
include a wide range of teaching strategies, emphasis on
homework, group work and high expectations for pupils
on the part of teachers.
It is also vital to ensure that teachers have postsecondary training to enable them to: acquire the necessary
pedagogical tools, earn a wage that is sufficient and
perceived as such (to avoid having to hold down another
job), and feel that their expertise and working methods
help pupils to acquire skills. It is essential to provide
schools with enough equipment and support materials

Social Panorama of Latin America • 2007

so that teachers have the right tools with which to guide
the learning process. Other recommendations include not
grouping students according to particular characteristics,
involving parents in school activities, promoting a respectful
classroom environment and harmonious relations between
pupils, allocating more time for reading for pleasure and
developing a more positive attitude towards reading, as
well as providing a wider range of materials.
Countries must set up or strengthen various
compensatory mechanisms to level the conditions of
the most disadvantaged pupils, so as to enable them
to face promotion systems that provide a higher more
homogenous standard of assessment of the skills needed
to fully develop social citizenship. This implies, inter
alia, ensuring that automatic promotion processes do not
become a disincentive for teacher performance.
Lastly, the region must not lose sight of the fact that
the high level of school segregation not only reproduces

41

educational gaps between the rich and the poor, but also
perpetuates feelings of belonging and social integration
in school microcosms, thereby sowing the seed for the
high levels of socioeconomic polarization present in
Latin American society. Reducing school segregation and
segmentation is not only about improving the quality of
education for all, but is also part of the strategy needed
to tackle the region’s economic, social and political
fragility. An indispensable part of this task is to build
a new social cohesion covenant in Latin America and
the Caribbean, while the major stumbling block is the
persistent and yawning social inequality in the region. The
new social contract must explicitly include educational
policies that tackle the problem of social inequality head
on, by means of affirmative action to compensate for the
disadvantages of the poorest students and improve the
quality of the learning process while reducing the high
level of stratification within education systems.

42

Economic Commission for Latin America and the Caribbean (ECLAC)

Internal migration and development in
Latin America and the Caribbean:
continuity, changes and policy challenges
Internal migration, which means moving residence from one
administrative division to another within the same country,
has been experienced by many people in Latin America
and the Caribbean. However, the intensity of migration
in the region is unexpectedly falling (see table 4). Some
of the hypotheses put forward to explain this, which all
require further research, include: the replacement of internal

migration by international migration or commuting to work
or study; increased house ownership as a result of higher
incomes; settlement patterns influenced by tele-commuting;
and a slowdown of rural-to-urban migratory flows due to
urbanization. What can be ruled out as an explanation is
a reduction in territorial inequalities within countries, as
these remain extremely high in the region.20

Table 4
LATIN AMERICA AND THE CARIBBEAN:
PERCENTAGE OF INTERNAL MIGRANTS BY TYPE OF MIGRATION, 1990 AND 2000 a
Census round

Lifetime migration
Major administrative
division (percentage)

Recent migration (last 5 years)

Minor administrative
division (percentage)

Major administrative
division (percentage)

1990

17.5

34.2

5.1

2000

17.7

35.2

4

Minor administrative
division (percentage)
12.6
8.7

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of special processing of census
microdatabases.
a18 countries in 1990 and 20 in 2000 (not all had data for all four types of migration).

Areas of net in-migration tend to be those offering better
living conditions. In this case, migrants’ quest for better
opportunities appears compatible with a territory’s capacity
to comfortably receive migrants. Nonetheless, there are some
emerging phenomena that may upset this balance. These
include suburbanization into areas with limited infrastructure
on the outskirts of large cities. Thus, suburbanization, which
usually involves private-sector businesses and decisions,
requires major public investments.
Socio-economically disadvantaged areas within
countries, for their part, tend to be sources of migration.
This is the case for the countryside (see table 5) and
various poverty-stricken and mainly indigenous areas
(see maps 1 and 2). Given that this loss of population
is not random, but rather consists mainly of young
and generally more skilled migrants, this type of
emigration erodes the human-resource base needed

20

for the development of poor areas that are losing
population. Migration can therefore offer a means
of escape for those who leave, but can aggravate the
situation of those who remain, in what could be termed
a geographical poverty trap.
The advance of urbanization in the region has modified
the profile of internal migrants, who now mainly move
between or within cities. In addition, current movements
no longer follow the patterns of urban concentration
of previous decades. Although the capital city remains
attractive in most countries, other large cities have begun
to register net emigration since the 1990s, as people leave
for other dynamic urban centres. Internal migration is
therefore promoting a more diverse and less asymmetric
system of cities that is more conducive to economic and
social development than the high urban primacy typical
of many countries in the region.

Latin American and Caribbean Institute for Economic and Social Planning (ILPES), “Economía y territorio en América Latina y el Caribe:
desigualdades y políticas”, document presented at the twelfth Conference of Ministers and Heads of Planning of Latin America and the
Caribbean, Brasilia, 26 and 27 June 2007.

Social Panorama of Latin America • 2007

43

Table 5
LATIN AMERICA AND THE CARIBBEAN: NET MIGRATION FROM THE COUNTRYSIDE TO THE CITY AND GROWTH OF THE URBAN
POPULATION, REGIONAL TOTAL AND SELECTED COUNTRIES
(With different levels of urbanization)
Selected countries and regional total

Net rural-to-urban
migration, 1990-2000

Growth of urban population
aged 10 and over, 1990-2000

Relative significance of
rural-to-urban migration
for urban growth

Chile

382 623

1 939 951

19.7

Venezuela (Bol. Rep. of)

847 392

4 235 917

20.0

Brazil

9 483 867

26 856 555

35.3

Mexico

4 183 486

13 103 802

31.9

824 486

1 384 850

59.5

303 742

685 610

44.3

19 636 438

58 344 252

33.7

Guatemala
Honduras
Total

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of indirect processing of intercensal survival ratios.

Figure 20
Latin America: net internal migration from LARGEST
cities, selected countries and dates

100 000

50 000

Panama City
(1995-2000)
Guayaquil
(1996-2001)
Guatemala City
(1997-2002)

Santa Cruz
(1996-2001)

Net migration

0

-50 000

San José
(1995-2000)
Santiago
(1997-2002)

-100 000

Asunción
(1997-2002)

Tegucigalpa
(1996-2001)

Mexico City
(1995-2000)

-150 000

-200 000

-250 000

São Paulo
(1995-2000)

Source: Latin American and Caribbean Demographic Centre (CELADE)
– Population Division of ECLAC, on the basis of special processing of
census microdatabases.

Despite its increasingly urban nature, internal
migration continues to drive the physical expansion of
major cities through intra-metropolitan migration. This
form of migration is determined by very different factors
from those underlying traditional migration (countryside
to city or between regions). Furthermore, this form of
migration also has a direct effect on residential segregation,
and thus has worrisome implications for the fight against
poverty and the promotion of social cohesion.
Migrants tend to be young people, women and
people with above average levels of education. Indeed,
the stereotype of the unskilled internal migrant from the
era of country-to-city migration does not even apply to
groups who are still located in mainly rural areas, such as

indigenous migrants (see table 6). Predictably, given that
many migrants move for work-related reasons, migrants
have higher labour participation rates even in countries with
high levels of unemployment. This reveals a somewhat
complicated adjustment process under way in migrants’
areas of destination.
In terms of policies, the underlying principle is to
combine the right to migrate in the best possible conditions
within a given country, with the fight against territorial
discrimination that tends to force outflows from certain
disadvantaged areas. There is no place for interventions
geared towards hindering migration or pressuring people
to move, as they are incompatible with every person’s right
to freely decide when and where to move within a country.
Incentives to move or stay in a particular place of residence
should be offered directly to individuals or companies in
the form of, inter alia, subsidies, “zonal attachment”, tax
breaks and labour or professional compensation. Public
action in the context of subnational development (through
the provision of infrastructure and basic support services
for productive clusters) also plays a vital role, although the
aim is not always explicitly linked to migration.
Interventions in migration and the spatial distribution
of the population are not limited to signals from the market
or the State. The high proportion of intra-metropolitan
displacement makes current migration more sensitive to
urban regulations and the secondary effects of social policy
in cities (particularly in terms of housing, transport and
infrastructure). Policy instruments, such as development
plans or city master plans, have a powerful effect on
migration. The same can be said of housing and public
transportation policies, which have direct and sometimes
mechanical consequences on changes of residence within
cities. Examples of interventions that combine the offer
of incentives with urban planning and public investment
include repopulation programmes in the city centres

44

Economic Commission for Latin America and the Caribbean (ECLAC)

of various metropolises in the region. While the costs,
benefits and results of such programmes have yet to be

fully assessed in detail, they definitely appear to offer a
means of intervening in the decision to migrate.

Table 6
LATIN AMERICA AND THE CARIBBEAN: PROPORTION OF POPULATION WITH HIGHER EDUCATION,
ACCORDING TO INDIGENOUS STATUS AND RECENT MIGRATION BETWEEN MAJOR ADMINISTRATIVE DIVISIONS,
SELECTED COUNTRIES AND YEARS
Country and year

Indigenous
Migrant

Non-indigenous
Non-migrant

Migrant

Non-migrant
8.4

Bolivia, 2001

16.4

12.0

13.2

Brazil, 2000

3.7

1.8

6.7

5.5

Chile, 2002

14.6

8.8

29.2

17.7

5.3
1.6

2.6

12.3

10.1

Guatemala, 2002

0.7

6.3

5.6

Mexico, 2000

4.2

2.2

13.4

8.8

Costa Rica, 2000

Source: Fabiana del Popolo and others, “Indigenous peoples and urban settlements: spatial distribution, internal migration and living conditions”,
Population and development series, No. 78 (LC/L.2799), Santiago, Chile, Economic Commission for Latina America and the Caribbean (ECLAC),

Map 1
South America, selected countries:
major administrative divisions by migration status, census rounds 1990 and 2000)

kilometers

National borders
Major divisions of net in-migration
Major administrative divisions on the decline
(changing from net in-migration to net outmigration)

Major divisions of net out-migration
Major administrative divisions on the rise
(changing from outmigration to net in-migration)
Major administrative divisions with no information available

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of figures from the database on Internal
Migration in Latin America and the Caribbean (MIALC) [online database] http://www.eclac.cl/migracion/migracion_interna/ and information from countries.
Note: The boundaries and names shown on this map do not imply official endorsement or acceptance by the United Nations.

Social Panorama of Latin America • 2007

45

Map 2
Central America and the Caribbean, selected countries:
major administrative divisions by migration status, census rounds 1990 and 2000

kilometers

National borders
Major administrative divisions of attraction
Declining major administrative divisions
(from net inmigration to net outmigration)

kilometers

Major administrative divisions of displacement
Rising major administrative divisions
(from net emigration to net inmigration)
Major administrative divisions with no information available

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of figures from the database on
Internal Migration in Latin America and the Caribbean (MIALC) [online database] http://www.eclac.cl/migracion/migracion_interna/ and information from
countries.
Note: The boundaries and names shown on this map do not imply official endorsement or acceptance by the United Nations.

46

Economic Commission for Latin America and the Caribbean (ECLAC)

Social agenda: health programmes and
policies for indigenous peoples in Latin
America and the Caribbean and the
international social agenda
In Latin America, the emergence of indigenous movements
as political actors in democratic contexts more conducive to
the creation of pluricultural States has enabled progress to
be made towards the recognition of the rights of indigenous
peoples. Following 20 years of negotiations, one explicit
manifestation of this is the adoption by the United Nations
General Assembly of the Declaration on the Rights of
Indigenous Peoples (13 September 2007), which consists
of 46 articles establishing minimum parameters in terms
of land ownership rights, access to natural resources in
settlement territories, respect and conservation of their
traditions, self-determination, etc. The Declaration also
recognizes individual and collective rights to education,
health and employment.

The above-mentioned Declaration and other
international human rights instruments can be used to
establish a set of minimum health standards: the right to
the highest level of physical and mental health by means
of non-discriminatory, adequate and quality access; the
right to comprehensive indigenous health including the
use, strengthening and monitoring of traditional medicine
and the protection of their territories as living areas;
the right to participate in the design, implementation,
management, administration and evaluation of health
policies and programmes, with special emphasis on the
autonomy of resources.
These standards bring with them new State obligations
in terms of legislation and public policy. Although only

Table 7
LATIN AMERICA (16 COUNTRIES): SPECIAL LEGISLATION ON THE HEALTH OF INDIGENOUS PEOPLES
Country

Free and
preferential
access

Traditional
practices

Protection
of medicinal
plants

Health care
according to
customs

Indigenous
participation in
management and
promotion of the
health system

Autonomous
management of
health resources

a

X
X
X
X

X
X
X
X

--X
--X

ILO Convention No. 169 ratified
Argentina b
Bolivia
Brazil
Colombia
Costa Rica
Ecuador
Guatemala
Honduras
Mexico b
Paraguay
Peru
Venezuela
(Rep. Bol. de) b

X
X
X
X
X
X
X

X
X
X
X
a

X
X

X
a
a

Xc
X
a

a

a

a
a
a
a
a
a

X

X

X
----------X

a

a

a

a

X

X

X

a

a

a

a

X

X

X

X

X

a

X

X

X
--X
X

----Xc
X

------Xc

X
--Xc
X

---

a
a

Not ratified
Chile
El Salvador
Nicaragua
Panama

---

Xc
Xc

----X
X

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Inter-American Development Bank (IDB), “Indigenous
legislation database” [online database] 2006 http://www.iadb.org/sds/ind/site_3152_s.htm.
aILO Convention concerning Indigenous and Tribal Peoples in Independent Countries (ILO Convention No. 169).
bSome provinces and states have additional legislation.
cOnly in indigenous territories (reserve, autonomous regions, comarcas).

Social Panorama of Latin America • 2007

the constitutions of the Bolivarian Republic of Venezuela,
Ecuador and Mexico explicitly recognize the collective
health rights of indigenous peoples, some progress can
be seen in the legislation of most countries (see table 7).
Despite this, the legislative recognition of indigenous
peoples’ health rights remains far removed from the actual
application of those rights, as the indigenous population
has more a negative epidemiological profile than the rest
of the population.
Health sector reforms geared towards the equity,
efficiency and quality of health benefits are conducive

47

to furthering the application of indigenous health rights,
with priority given to the active participation of the
communities themselves.
Countries fall into four groups when it comes to
indigenous health policies: a large number of countries
have a national indigenous peoples’ plan; a second group
has begun the process to devise and implement such a
policy; a third group has an explicitly intercultural approach
as part of their national health policies; and finally there
are those countries that have no specific policies for
indigenous peoples (see table 8).

Table 8
LATIN AMERICA (16 COUNTRIES): HEALTH POLICIES AND INDIGENOUS PEOPLES
Situation

Countries

Countries with a national policy in terms of health and indigenous peoples

Bolivia
Brazil
Chile
Costa Rica
Ecuador
Mexico
Nicaragua
Panama
Peru
Venezuela (Bolivarian Rep. of)

Countries in the process of formulating a policy

Argentina
Colombia

No specific policy, but it is a cross-cutting issue in national health policy

Guatemala
Honduras

No relevant policy or focus

El Salvador
Paraguay

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of results from a survey sent out to countries.

An overview of such programmes shows a
heterogeneous supply with two main trends: programmes
specially designed to improve the health of indigenous
peoples (particularly those that concentrate on specific
aspects such as traditional medicine and human resources
training); and regular programmes that are part of
strategic or policy lines within health systems. Some
of the achievements to date include the consolidation
of differentiated health models and the improvement
of the health conditions of indigenous peoples. There
are also limitations, however, including the scarce
availability of trained human resources, low levels
of financing and a lack of continuity in the allocation
of resources. Some programmes have successfully
incorporated the participation of indigenous peoples
in these processes, while other programmes need to

make more progress in this area. The widespread lack
of systematic information on the health situation and
epidemiological profile of indigenous peoples is one
of the main obstacles to defining health goals and
assessing the results of enforcing their individual and
collective rights.
The major challenge for public policy is to continue
advancing towards implementing standards for the health
rights of indigenous peoples. This implies considering
indigenous health as an integral concept (including
territorial rights and the right to cultural integrity)
and the full participation of indigenous peoples in
the definition, management and assessment of health
programmes and policies. This should form the basis
for differentiated health care models (intercultural,
integral, and complementary).

48

Furthermore, it is vital to make progress in the
training of human resources (in order to achieve
an intercultural health dialogue) and in producing
knowledge to sustain the development of such models
and facilitate the formulation, follow-up and evaluation
of health goals. Examples include appropriate systems
of indicators, studies on sociocultural epidemiology,
participatory community health diagnostics and local
research into traditional medicine and health/disease,
with an assessment of effectiveness in each context.
Adequate and continuous funding is key if these

Economic Commission for Latin America and the Caribbean (ECLAC)

objectives are to be achieved, as this will guarantee
the autonomy of indigenous peoples as holders of
collective rights.
Implementing minimum standards in the collective
health rights of indigenous peoples undoubtedly poses
huge challenges for the formulation of public policies,
as it involves a State-level rethink of everything from
conceptual frameworks to the definition of health targets
and actions, as well as requiring indigenous peoples and
organizations to make effective progress in exercising
and protecting their right to health.

International agenda
The main aims of the tenth session of the Regional
Conference on Women in Latin America and the Caribbean,
organized by ECLAC from 6 to 9 August 2007 in Quito,
Ecuador, were to review political participation and gender
parity at all levels of decision-making processes and
analyse women’s contribution to the economy and social
protection (especially in terms of their unpaid work).
Country representatives adopted the Quito Consensus,
which contains 36 agreements including ones relating to
parity, women’s political representation and participation
and their contribution to the economy and social protection
through unpaid domestic work.
Countries also made a commitment to adopt measures
aimed at eliminating the diverse forms of violence perpetrated
against women (especially homicide of women), to develop
comprehensive, non-sexist public education programmes

designed to counter gender and racial stereotypes and other
cultural biases against women and promote relationships of
mutual support between women and men, and to undertake
efforts to sign, ratify and disseminate the Convention on
the Elimination of All Forms of Discrimination against
Women and its Optional Protocol.
Lastly, countries asked the Presiding Officers of the
Conference to specifically devote one of the meetings
they hold each year to an evaluation of the fulfilment of
the commitments, and agreed that, at the next session
of the Regional Conference (scheduled to be held in
Brazil in 2010), a general medium-term assessment
of the progress made should be undertaken. They also
asked ECLAC, together with other organizations in
the United Nations system, to create a gender equality
observatory.

Social Panorama of Latin America • 2007

49

Chapter I

Advances in poverty reduction and
challenges in attaining social cohesion

A.  Poverty trends
Poverty and extreme poverty rates in Latin America fell once more in 2006 to 36.5% and
13.4%, respectively, thanks to four years of sustained economic growth. These are the lowest
rates recorded since 1980. The number of people living in poverty in the region is now below
the 200 million mark recorded in 1990.

1. 

The Economic Situation

The economies of Latin America and the Caribbean
performed well in 2006. The 5.6% increase in GDP, which
represented a 4.2% rise in per capita GDP, marked the
continuation of a period economic expansion. During the
preceding four years, per capita GDP had increased 3.3%
per annum, peaking at 4.8% in 2004.1
Nearly all the economies of Latin America posted
positive results. The most remarkable per capita GDP

1

increases were observed in the Dominican Republic and
the Bolivarian Republic of Venezuela (9.1% and 8.5%,
respectively), followed by Argentina (7.4%), Peru (6.8%)
and Uruguay (6.8%). Per capita GDP in Haiti grew only
0.7%, but per capita GDP growth in all the other countries
was over 2%, an achievement that has not been seen
in Latin America for over 20 years (see table 1 in the
statistical appendix).

See the detailed analysis of the factors contributing to these results in ECLAC (2007b).

50

Economic Commission for Latin America and the Caribbean (ECLAC)

Though barely 1.6%, average per capita GDP growth in
2000-2006 was higher than in 1990-1999 and is expected to

continue to increase over the next few years, by 3.7% in 2007
and probably at a slower pace in 2008 (see table I.1).

Table I.1
LATIN AMERICA (20 COUNTRIES): SELECTED SOCIO-ECONOMIC INDICATORS, 1990-2006
Country
Year

Per capita
GDP
(average
annual rate
of change) a

Urban
unemployment

Average real
earnings c

Simple average
for the period b
(percentages)

(Average annual
rate of change)

Argentina

Country
Year

Per capita
GDP
(average
annual rate
of change) a

Urban
unemployment

Average real
earnings c

Simple average
for the period b
(percentages)

(Average
annual rate
of change)

Honduras

1990-1999

2.5

11.9

0.9

1990-1999

-0.2

6.1

…

2000-2006

1.5

15.0

1.2

2000-2006

2.1

6.6

…

Bolivia

Mexico

1990-1999

1.6

5.3

3.0

1990-1999

1.5

3.6

1.0

2000-2006 d

0.6

8.0

2.0

2000-2006 f

1.9

4.3

2.3

1990-1999

0.2

5.6

-1.0

1990-1999

0.6

14.0

8.0

2000-2006

1.6

9.8

-1.9

2000-2006

2.0

9.5

0.8

Brazil

Nicaragua

Chile

Panama

1990-1999

4.6

7.6

3.5

1990-1999

3.5

16.7

…

2000-2006

3.1

9.4

1.7

2000-2006

2.7

14.5

…

Colombia

Paraguay

1990-1999

0.9

11.6

2.2

1990-1999

-0.3

6.3

0.3

2000-2006

2.2

16.0

1.8

2000-2006

-0.1

10.7

0.0

Costa Rica

Peru

1990-1999

2.8

5.4

2.2

1990-1999

1.3

8.5

-0.8

2000-2006

2.3

6.3

0.5

2000-2006

3.3

9.2

0.9

Cuba

Rep. Dominicana

1990-1999

-2.8

6.9

…

1990-1999

2.8

16.9

…

2000-2004

3.4

3.4

…

2000-2006

3.6

16.4

…

Ecuador

Uruguay

1990-1999

0.3

9.4

5.3

2000-2006

3.2

10.7

…

1990-1999

2.8

7.8

…

2000-2006

0.6

6.5

…

El Salvador

1990-1999

2.5

9.9

0.5

2000-2006
1.3
Venezuela
(Bolivarian Republic of)
1990-1999
0.2

14.2

-2.5

2000-2006

10.3

-4.0

2.0

14.1

-1.8

1.1
1.8

7.7
10.1

1.0
0.1

Guatemala
1990-1999

1.7

4.0

5.4

2000-2006 e

0.9

5.0

-0.5

-2.0
-1.6

…
…

…
…

Haiti
1990-1999
2000-2006

Latin America
1990-1999
2000-2006

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official figures.
on the per capita GDP value in dollars, at constant 2000 prices. The 2006 figure is a preliminary estimate.
bIn the Bolivarian Republic of Venezuela, Chile, Dominican Republic, Guatemala and Nicaragua, the figure refers to total national unemployment. In
addition, the period used for Cuba was 1991-1999 instead of 1990-1999.
cIn general, the coverage of this index is very incomplete. In most of the countries it refers only to formal-sector workers in the manufacturing sector.
The figure shown for 2006 is a preliminary estimate.
dThe figures for urban unemployment and real average earnings correspond to the period 2000-2005.
eAverage urban unemployment corresponds to the period 2002-2004.
f From 2000 onwards, a new methodology for measuring the unemployment rate was used which is not comparable with that used in earlier years.
aBased

Social Panorama of Latin America • 2007

51

Unemployment fell in 2006 thanks to the ongoing
expansion of the economy. The positive employment trends
recorded during the previous three years thus continued and
translated into a 2% accumulated increase in employment
levels since 2002. Interestingly, wage employment rose
4.1% and accounted for 89% of the new jobs created in
2006. Most of these consisted of jobs in the formal sector,
i.e., jobs covered by employment contracts and a social
security scheme (ECLAC, 2007b).
Average urban unemployment fell from 9.1% to
8.7%, a smaller decrease than in 2005, but nonetheless
the third consecutive drop since 2000. Unemployment
is therefore at its lowest level since the mid-1990s, even
though the average rate for 2000-2006 is higher than for

2. 

1990-1999. Most countries also significantly reduced
their overall unemployment rate. In nine countries
unemployment fell at least 0.5%, and only Brazil
recorded a slight increase in unemployment (see table
I.1 and table 1 of the statistical appendix).
In 2006, for the first time since the turn of the century,
average real earnings rose more than 2% on average. In some
countries, including Argentina, the Bolivarian Republic of
Venezuela, Brazil, Colombia and Uruguay, the increase was
over 3%, and only Guatemala recorded a drop in real wages.
The deterioration of average real earnings in the region in
previous years, however, especially in 2003, means that the
average increase for 2000-2006 was only 0.1%, compared
with 1% for 1990-1999.

Poverty in the region

The latest poverty estimates for the countries of Latin
America indicate that, as of 2006, 36.5% of the region’s
population (194 million people) were poor and 13.4%

(71 million) were extremely poor or indigent (see figure
I.1 and tables I.2 and I.3).2

Figure I.1
LATIN AMERICA: POVERTY AND INDIGENCE RATES, 1980-2007 a

60

Percentage of population

50

43.5

43.8

250

44.0
39.8

36.5

30
22.5
20

19.0

18.6

18.5

19.4
15.4

150

204

12.7

93

89

89

10

1997

1999

221

209
194

190

71

69

136

100
13.4

211

200

200

35.1

Millions

Percentage

40

48.3
40.5

Number of people

300

97

81

62
50
0

0
1990

1997

1999

2002

2005

2006

2007 b

1980

Indigent

1980

2007 b

Non-indigent poor

1990

2002

2005

2006

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys conducted in
the respective countries.
aEstimate for 18 countries of the region plus Haiti. The figures shown in the orange sections of the bars are the percentage and total number of poor
persons (indigent plus non-indigent poor).
bProjections.

2

In 12 countries (Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Costa Rica, Dominican Republic, Ecuador, Honduras, Mexico,
Panama, Peru and Uruguay), the 2006 figures correspond to a combination of estimates based on household surveys conducted that year, and in
the other countries, on projections made on the basis of previous surveys. The new poverty and indigence rates are lower than those projected
for 2006, reaching 38.5% and 14.7%, respectively.

52

Economic Commission for Latin America and the Caribbean (ECLAC)

Table I.2
LATIN AMERICA: POVERTY AND INDIGENCE RATES, 1980-2006 a
Percentage of population
Poor b

Indigent c

Total

Urban

Rural

Total

Urban

Rural

1980

40.5

29.8

59.9

18.6

10.6

32.7

1990

48.3

41.4

65.4

22.5

15.3

40.4

1997

43.5

36.5

63.0

19.0

12.3

37.6

1999

43.8

37.1

63.7

18.5

11.9

38.3

2002

44.0

38.4

61.8

19.4

13.5

37.9

2004

42.0

36.9

58.7

16.9

12.0

33.1

2005

39.8

34.1

58.8

15.4

10.3

32.5

2006

36.5

31.1

54.4

13.4

8.6

29.4

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys conducted in
the respective countries.
aEstimate for 18 countries of the region plus Haiti.
bPercentage of the population living below the poverty line. Includes people living in indigence.
cPercentage of the population living below the indigence line.

Table I.3
LATIN AMERICA: POOR AND INDIGENT POPULATION, 1980-2006 a
Million people
Poor b

Indigent c

Total

Urban

Rural

Total

Urban

1980

135.9

62.9

73.0

62.4

22.5

Rural
39.9

1990

200.2

121.7

78.5

93.4

45.0

48.4

1997

203.8

125.7

78.2

88.8

42.2

46.6

1999

211.4

134.2

77.2

89.4

43.0

46.4

2002

221.4

146.7

74.8

97.4

51.6

45.8

2004

217.4

146.5

71.0

87.6

47.6

40.0

2005

209.0

137.9

71.1

81.1

41.8

39.3

2006

194.4

127.6

66.8

71.3

35.2

36.1

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys conducted in
the respective countries.
aEstimate for 18 countries of the region plus Haiti.
bNumber of people living below the poverty line. Includes people living in indigence.
cNumber of people living below the indigence line.

A comparison with figures for 2005 shows that further
progress was made in reducing poverty and extreme
poverty, or indigence: there was a 3.3% drop in poverty
and a 2.0% decrease in extreme poverty. This means that
15 million people escaped poverty in 2006, and 10 million
who had been classified as indigent ceased to be so.
It is not just the magnitude of these figures that is
impressive. They reflect steady gains in poverty reduction
since 2004, in sharp contrast to the stagnant situation in
preceding years. Since 2002, poverty in the region has
plummeted 7.5% and extreme poverty 6%. Moreover, in
that time, 40 million people have been saved from falling
into poverty as they would have done if the poverty
reduction rates had not improved.

From a more long-term perspective, a comparison of
the figures for 2006 and 1990 shows that the poverty rate
has been lowered by 11.8 percentage points and that the
indigence rate by 9.1 points. This means that the number
of indigents has fallen by over 20 million and that, for the
first time since 1990, the total number of people living in
poverty has dropped below 200 million persons.
The results for 2005 showed that the poverty rate
was falling for the first time since 1980, when 40.5% of
the population was ranked as poor, and that the indigence
rate had fallen 3 percentage points from the 1980 level of
18.6%. The figures for 2006 reveal a 4.0 and 5.2 percentagepoint drop in the poverty and indigence rates, respectively,
since 1980. This implies that poverty reduction efforts are

Social Panorama of Latin America • 2007

53

achieving increasingly significant results. Poverty levels
are still high in the region, however, and lowering them
remains a formidable task.
The increases in per capita GDP that the region is
expected to enjoy in 2007 means that poverty and indigence
rates can be expected to fall even lower, to around 35.1%

3. 

and 12.7%, respectively, and that the number of people
living in poverty and extreme poverty should drop to 190
million and 69 million. These rates would not only be the
lowest seen in Latin America since the 1980s, but also
represent the smallest number of people living in poverty
in the last 17 years (see figure I.1).

Poverty and indigence in the different countries

Poverty and indigence estimates for 2006 for 12 countries
in the region reflect a general downward trend. Nearly
all of these countries registered considerable reductions
in both poverty and indigence, which already were
diminishing in 2005.
When the year 2002 is used as a benchmark, Argentina
(data for urban areas) displays the greatest improvement,
with reductions of 24.4 and 13.7 percentage points in

its poverty and extreme poverty rates, respectively. The
results for 2006 played an important role in this outcome,
recording decreases in the two indicators of 5.0 and 1.9
percentage points. This largely counteracted the deterioration
in the situation that occurred in 1999-2002. As a result,
the poverty rate is now 2.7 points below the 1999 rate,
although the indigence rate is still 0.6 points above the
figure for 1999 (see figure I.2 and table 1.4).

Figure I.2
LATIN AMERICA (16 COUNTRIES): POVERTY AND INDIGENCE RATES, AROUND 2002-2005 AND AROUND 2002-2006 a


Poverty

Indigence
5

2002-2005

2002-2006

2002-2005

Uruguay b

Dominican Rep.

Costa Rica

Panama

Paraguay

Chile

Bolivia

El Salvador

Brazil

Mexico

-15

Colombia

-10

Honduras

Bolivia

Uruguay b

Paraguay

Dominican Rep.

Costa Rica

El Salvador

Brazil

Panama

Colombia

Chile

Honduras

Mexico

Peru

Ecuador b

-25

Venezuela (Bol. Rep. of)

-20

-5

Peru

-15

Ecuador b

-10

0

Argentina b

-5

Venezuela (Bol. Rep. of)

Percentage points

0

Argentina b

Percentage points

5

2002-2006

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys conducted in
the respective countries.
aThe data for 2002 are based on the most recent available estimates for 2000-2002. The data for 2005 reflect the most recent estimates for 2003-2005.
The years used in each country are given in table I.4.
bUrban areas.

54

Economic Commission for Latin America and the Caribbean (ECLAC)

Table I.4
LATIN AMERICA (18 COUNTRIES): POVERTY AND INDIGENCE INDICATORS, 1990-2006 a
(Percentages)
Country

Households and population below the:

Year
Poverty line
H
Households

Argentina c

Population

b

Indigence line
PG

FGT2

H
Households

Population

PG

FGT2

1990 d

16.2

21.2

7.2

3.4

3.5

5.2

1.6

0.8

1999

16.3

23.7

8.6

4.3

4.3

6.6

2.1

1.1

2002

34.9

45.4

21.1

12.8

13.9

20.9

8.4

4.6

2005

18.7

26.0

10.4

5.8

6.0

9.1

3.4

1.8
1.5

2006

14.7

21.0

8.3

4.6

4.9

7.2

2.8

1989 e

48.9

52.6

24.5

15.0

21.9

23.0

9.7

6.1

1999

Bolivia

54.7

60.6

33.9

24.1

32.1

36.4

20.3

14.7
13.5

2002
Brazil

55.5

62.4

34.4

23.8

31.7

37.1

19.5

2004

56.4

63.9

32.1

20.1

29.9

34.7

15.0

8.9

1990

41.4

48.0

23.5

14.7

18.3

23.4

9.7

5.5

1999

29.9

37.5

17.0

10.2

9.6

12.9

5.3

3.3

2001

29.9

37.5

17.3

10.7

10.0

13.2

5.8

3.8

2005
Chile

28.5

36.3

15.9

9.4

7.8

10.6

4.3

2.6

2006

26.1

33.3

14.3

8.4

6.7

9.0

3.7

2.3

1990

33.3

38.6

14.9

8.0

10.6

13.0

4.4

2.3

1998

17.8

21.7

7.5

3.8

4.6

5.6

2.0

1.1

2000

16.3

20.2

7.0

3.7

4.5

5.6

2.1

1.2

2003

15.3

18.7

6.3

3.2

3.9

4.7

1.7

1.0

2006
Colombia

11.3

13.7

4.4

2.2

2.7

3.2

1.1

0.7

1994

47.3

52.5

26.6

17.5

25.0

28.5

13.8

9.1

1999

48.7

54.9

25.6

15.7

23.2

26.8

11.2

6.9

2002

45.0

51.1

23.9

14.8

21.6

24.6

10.4

6.5

2004
Costa Rica

45.2

51.1

23.8

14.6

21.4

24.2

10.2

6.3

2005

40.6

46.8

20.7

12.3

17.4

20.2

8.3

5.0

1990

23.6

26.3

10.7

6.5

9.8

9.9

4.8

3.4

1999

18.2

20.3

8.1

4.8

7.5

7.8

3.5

2.3

2002

18.6

20.3

8.4

5.2

7.7

8.2

3.9

2.7

2005

19.5

21.1

7.9

4.4

7.1

7.0

2.9

1.9

2006

18.0

19.0

7.6

4.5

7.3

7.2

3.1

2.0

c

55.8

62.1

27.6

15.8

22.6

26.2

9.2

4.9

1999 c

58.0

63.5

30.1

18.2

27.2

31.3

11.5

6.3

2002 c

42.6

49.0

20.8

11.8

16.3

19.4

6.9

3.7

2005

Ecuador

41.7

48.3

20.9

12.0

17.7

21.2

7.9

4.2

1990

2006
El Salvador

36.8

43.0

17.2

9.2

13.6

16.1

5.4

2.7

1995

47.6

54.2

24.0

14.3

18.2

21.7

9.1

5.6

1999

49.8

22.9

14.0

18.3

21.9

9.4

5.8

42.9

48.9

22.7

14.0

18.3

22.1

9.5

5.7

2004
Guatemala

43.5

2001

40.4

47.5

21.1

12.6

15.6

19.0

8.1

5.0

63.0

69.1

35.9

23.1

36.7

41.8

18.5

11.2

53.5

61.1

27.3

15.4

26.1

31.6

10.7

5.1

2002
Honduras

1989
1998

52.8

60.2

27.0

15.4

26.9

30.9

10.7

5.5

1990

75.2

80.8

50.2

35.9

53.9

60.9

31.5

20.2

1999

74.3

79.7

47.4

32.9

50.6

56.8

27.9

17.5

2002

70.9

77.3

45.3

31.2

47.1

54.4

26.6

16.2

2003

68.5

74.8

44.5

30.9

47.4

53.9

26.3

16.3

2006

65.7

71.5

...

...

43.4

49.3

...

...

Social Panorama of Latin America • 2007

55

Table I.4 (concluded)
LATIN AMERICA (18 COUNTRIES): POVERTY AND INDIGENCE INDICATORS, 1990-2006 a
(Percentages)
Country

Households and population below the:

Year
Poverty line b
H
Households

Mexico

Nicaragua

Panama

Paraguay

Peru

Dominican
Republic

Uruguay c

Venezuela
(Bolivarian
Republic of)

Latin
America h

1989
1998
2000
2002
2004
2006
1993
1998
2001
1991 c
1999 c
2002
2005
2006
1990 f
1999
2001
2004
2005
1997
1999
2001 g
2005 g
2006 g
2000
2002
2004
2005
2006
1990
1999
2002
2005
2006
1990
1999
2002
2005
2006
1990
1999
2002
2004
2005
2006

Population

39.0
38.0
33.3
31.8
29.8
24.6
68.1
65.1
62.9
27.4
17.0
28.4
26.4
24.3
36.8
51.7
52.0
57.1
51.9
40.5
42.3
46.8
40.5
37.2
43.0
40.9
50.4
43.7
41.1
11.8
5.6
9.3
11.8
11.8
34.2
44.0
43.3
32.9
26.2
41.0
35.4
36.1
34.1
32.0
29.8

47.7
46.9
41.1
39.4
37.0
31.7
73.6
69.9
69.4
32.7
20.8
34.0
33.0
30.8
43.2
60.6
61.0
65.9
60.5
47.6
48.6
54.8
48.7
44.5
46.9
44.9
54.4
47.5
44.5
17.9
9.4
15.4
18.8
18.5
39.8
49.4
48.6
37.1
30.2
48.3
43.9
44.0
42.0
39.8
37.3

Indigence line
PG

18.7
18.4
15.8
13.9
13.2
10.5
41.9
39.4
36.9
13.7
7.6
15.8
14.8
14.1
16.1
30.2
30.3
33.0
29.5
20.8
20.6
...
…
…
22.1
20.5
27.0
23.0
21.1
5.3
2.7
4.5
6.0
5.5
15.7
22.6
22.1
16.6
11.5
...
...
...
...
...
...

FGT2
9.9
9.4
8.1
6.7
6.5
4.9
29.3
27.3
24.3
8.1
4.1
9.7
9.1
8.6
8.0
19.0
19.5
20.6
18.0
12.0
11.7
...
…
…
13.9
12.9
16.9
14.4
13.0
2.4
1.2
1.9
2.7
2.4
8.5
13.7
13.4
10.3
6.3
...
...
...
...
...
...

H
Households

Population

14.0
13.2
10.7
9.1
8.7
6.0
43.2
40.1
36.3
10.1
4.9
13.9
12.0
11.3
10.4
26.0
26.5
29.2
25.4
20.4
18.7
20.1
13.7
12.7
20.6
18.6
26.1
22.4
20.2
2.0
0.9
1.3
2.2
1.9
11.8
19.4
19.7
14.4
9.0
17.7
14.1
14.6
13.1
11.8
10.5

18.7
18.5
15.2
12.6
11.7
8.7
48.4
44.6
42.4
11.5
5.9
17.4
15.7
15.2
13.1
33.8
33.2
36.9
32.1
25.1
22.4
24.4
17.4
16.1
22.1
20.3
29.0
24.6
22.0
3.4
1.8
2.5
4.1
3.2
14.4
21.7
22.2
15.9
9.9
22.5
18.7
19.4
16.9
15.4
13.8

PG
5.9
5.3
4.7
3.5
3.5
2.4
24.3
22.6
19.0
5.2
2.3
7.4
6.9
6.6
3.6
14.5
15.4
15.3
13.1
10.1
9.2
...
…
…
10.1
9.3
12.2
10.4
9.1
0.9
0.4
0.6
1.0
0.7
5.0
9.0
9.3
7.4
3.8
...
...
...
...
...
...

FGT2
2.7
2.2
2.1
1.4
1.6
1.0
16.2
15.1
11.7
3.4
1.4
4.2
4.1
3.9
1.5
8.5
9.6
8.6
7.4
5.7
5.1
...
…
…
6.7
6.3
6.9
6.2
5.4
0.4
0.2
0.2
0.4
0.3
2.4
5.5
5.7
5.0
2.4
...
...
...
...
...
...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys conducted in
the respective countries.
Note: H = Headcount index; PG = Poverty gap, and FGT2 = Foster, Greer and Thorbecke index.
aSee box I.4 for the definition of each indicator. The PG and FGT indices are calculated on the basis of the distribution of the poor population.
2
bIncludes households (people) living in extreme poverty.
cUrban areas.
dGreater Buenos Aires.
eEight departmental capitals plus El Alto.
f Metropolitan area of Asunción.
gData from the National Institute of Statistics and Informatics (INEI) of Peru. These figures are not comparable with those of previous years owing to the
change in the sample framework used for the household survey. The figures for 2001 refer to the fourth quarter, while those for 2005 and 2006 refer to
the whole year.
hEstimate for 18 countries of the region plus Haiti.

56

Economic Commission for Latin America and the Caribbean (ECLAC)

The Bolivarian Republic of Venezuela reduced its
poverty and extreme poverty rates by 18.4 and 12.3
percentage points, respectively, between 2002 and
2006. Thanks to rapid GDP growth and the ongoing
implementation of broad social programmes, in 2006
alone the poverty rate was lowered from 37.1% to 30.2%
and the indigence rate from 15.9% to 9.9%. This swift
pace of progress considerably brightens the prospects for
further reductions in poverty and significantly increases
the feasibility of meeting the first target associated with
the first Millennium Development Goal, which is analysed
in the following section.
These two countries (Argentina and the Bolivarian
Republic of Venezuela) are followed, in order of
magnitude, by Peru,3 Ecuador (urban areas), Mexico,
Chile and Honduras, which chalked up poverty reductions
of over five percentage points between 2000-2002
and 2006. With the exception of Peru, at least half of
this cumulative reduction occurred in the later part
of this period in each of these four countries. This is
particularly notable in the case of Chile, where 5.0 of
the 6.5 percentage points by which the poverty rate was
reduced in 2000-2006 correspond to 2003-2006.4 These
countries also witnessed significant reductions in their
indigence rates. Particularly notable decreases were
seen in this indicator for Peru, Ecuador and Honduras,
which recorded reductions of 8.3, 6.6 and 5.1 percentage
points, respectively. Chile also made great strides in this
respect since, although its indigence rate fell by just 2.4
percentage points, this amounted to a 43% decrease in
that rate relative to 2000.
Brazil registered decreases of 4.2 percentage points
in both its poverty and its extreme poverty rates between
2001 and 2006. This has a significant impact at the
regional level, since it represents a reduction of 6 million
from the total number of indigents in the region. Public
transfer programmes implemented in the country, most
notably the “Bolsa Familia” have played a decisive role
in this achievement.

3

4
5

Costa Rica and the Dominican Republic also managed
to reduce their poverty levels in 2002-2006, although less
dramatically than the aforementioned countries. Actually,
the Dominican Republic recorded a slightly higher indigence
rate due to the setbacks it experienced between 2002 and
2004, which subsequent progress has still not been able
to offset entirely. A somewhat similar situation is found
in Uruguay, where decreases in the poverty and indigence
rates in 2005 and 2006 have not enabled the country to
regain the levels it had attained in 2002.
A significant portion of the poverty reduction
recorded in Latin America in 2002-2006 was achieved by
Argentina, where the number of people living in poverty
was slashed by 9 million, followed by Brazil, Mexico and
the Bolivarian Republic of Venezuela, where the numbers
were cut by 4 to 6 million. Together, these four countries
accounted for 23 million less people living in poverty in
the region, a notable reduction considering that the poor
population of Latin America as a whole is 27 million. The
26 million drop in the number of indigents, on the other
hand, was largely attributable to Brazil, which accounted
for approximately a quarter of that figure, and Argentina
and Mexico, which each lowered their indigent populations
by about 5 million.
In several countries, the drop in the number and
percentage of people with insufficient income to cover
their basic needs has been accompanied by a more even
distribution of wealth. Between 2002 and 2006, the
Gini coefficient fell significantly in Argentina (data for
urban areas), Brazil, Chile and the Bolivarian Republic
of Venezuela.5 In Argentina and the Bolivarian Republic
of Venezuela, the value of the Gini coefficient decreased
approximately 10%, from 0.58 to 0.52 and from 0.5 to
0.44, respectively. In Brazil and Chile, the decline was
about 6% and 7%, respectively. No significant changes in
income distribution were recorded in the other countries for
which data was available for 2006, except in the Dominican
Republic where the Gini coefficient increased slightly (see
tables 14 and 15 of the statistical appendix).

The figures for Peru from 2004 on are not wholly comparable with those for earlier years, since the former refer to the entire year whereas the
latter correspond to the last quarter only. No major differences are to be expected between quarterly and annual estimates, however. As a point
of reference, it may be noted that in 2006 the indigence and poverty rates estimated for the year as a whole were 0.7 and 1.5 percentage points
higher, respectively, than the estimates for the final quarter.
Indigence and poverty estimates for Chile are available only for 2000, 2003 and 2006, and it is therefore impossible to perform an analysis of
what occurred in the intervening years.
The Gini coefficient, which is the most commonly used indicator of inequality in income distribution, takes values ranging from 0 (absolute
equality) to 1 (absolute inequality). For further information on this and other inequality indicators, see Box I.7 of Social Panorama of Latin
America, 2006.

Social Panorama of Latin America • 2007

57

Box I.1
METHOD USED FOR POVERTY MEASUREMENT

The method used in this report to estimate
poverty classifies a person as “poor” when
the per capita income of the household in
which he or she lives is below the “poverty
line”, or the minimum income the members
of a household must have in order to meet
their basic needs. Poverty lines expressed
in national currency are based on the
calculation of the cost of a basket of
particular goods and services, employing
the “cost of basic needs” method.
Where the relevant information
was available, the cost of a basic
food basket covering the population’s
nutritional needs was estimated for
each country and geographical area,
taking into account consumption habits,
the effective availability of foodstuffs
and their relative prices, as well as the
differences between metropolitan areas,
other urban areas and rural areas. To this
value, which constituted the “indigence
line”, was then added an estimate of the
resources households need to satisfy
their basic non-nutritional needs, to
make up the total value of the poverty

line. For this purpose, the indigence
line was multiplied by a constant factor
of 2 for urban areas and 1.75 for rural
areas.a/ The monthly equivalent in
dollars of the most recent poverty lines
varies between US$ 45 and US$ 161 in
urban areas, and between US$ 32 and
US$ 101 in rural areas. The figure for
indigence lines ranges from US$ 23 to
US$ 81 in urban areas, and from US$ 18
to US$  58 in rural areas (in all cases,
the lower values relate to Bolivia and
the higher ones to Mexico (see table 5
of the statistical appendix).b
In most cases, data concerning the
structure of household consumption, of
both foodstuffs and other goods and
services, came from surveys on household
budgets conducted in the respective
countries.c/ As these surveys were carried
out before the poverty estimates were
prepared, the value of the poverty lines
was updated according to the cumulative
variation in the consumer price index.
Data on family income were taken
from household surveys conducted in

the respective countries, in the years
that correspond to the poverty estimates
contained in this publication. In line with
the usual practice at ECLAC, both partial
non-response to income questions —in
the case of wage-earners, independent
workers and retirees— and probable
biases arising from underreporting
were corrected. This was done by
comparing the survey entries for income
with figures from an estimate of the
household income and expenditure
account of each country’s System of
National Accounts (SNA), prepared for
this purpose using official information.
The concept of income corresponds to
total current income; i.e., income from
wage labour (monetary and in kind),
independent labour (including self-supply
and the consumption value of homemade products), property, retirement
and other pensions and other transfers
received by households. In most of the
countries, household income included
the imputed rental value of owneroccupied dwellings.

Source: Economic Commission for Latin America and the Caribbean (ECLAC).
aThe

sole exceptions to this general rule were Brazil and Peru. For Brazil, the study used new indigence lines estimated for different geographical
areas within the country, in the framework of a joint project conducted by the Brazilian Geographical and Statistical Institute, the Brazilian
Institute of Applied Economic Research and ECLAC in the late 1990s. For Peru, the indigence and poverty lines used were estimates prepared
by the National Institute of Statistics and Informatics under the Programme for the Improvement of Surveys and the Measurement of Living
Conditions in Latin America and the Caribbean implemented in that country.
bThe exchange rate used is the average rate from the reference month used to compile information on income through household surveys.
cWhen data from the processing of a recent survey of this type were not available, other information on household consumption was used.

Box I.2
UPDATING THE METHODOLOGY FOR MEASURING POVERTY

In late 2005, ECLAC embarked upon
a review of the method it has used to
measure poverty and indigence for
almost three decades. The review has
two main objectives. The first is to use
the most recent income and expenditure
surveys in the various countries of the
region to construct new basic baskets.
Most of the indigence and poverty lines
currently in use are based on consumption
patterns inferred from surveys conducted

in the 1980s. Only recently has ECLAC
had access to income and expenditure
surveys in 18 Latin American countries,
most of which were conducted in the
1990s and in some cases more recently.
These provide the information needed to
construct consumption baskets that better
reflect prevailing habits and conditions.
The second aim is to look at introducing
methodological changes in line with
progress made in poverty measurement

worldwide, both in the academic domain
and in terms of the practical experience
of countries themselves. The method
developed by ECLAC in the late 1970s
became a model which the countries of the
region replicated, albeit adapting some of
its characteristics to their specific national
needs. Since that time, other considerations
worth taking into account have emerged on
how to quantify household living standards;
and rapid technological process has made

58

Economic Commission for Latin America and the Caribbean (ECLAC)

it possible to process survey data from new
perspectives that were previously unviable.
The resulting measures aim to provide
comparable data on the social situation
in Latin American countries. In order to
achieve results that are as comparable
between countries as they can be,
the aim is to standardize as far as
possible the way the method is applied
and introduce common criteria for all
countries. These aims are complemented
by making every effort to keep the
system simple, replicable and transparent.

The methodological aspects that are
under review cover the whole process
of constructing poverty lines. Broadly
speaking, these include selection of
the reference group for basic baskets;
review of the content of the non-food
goods basket; calculation of updated
Orshansky coefficients; and the possibility
of constructing poverty lines differentiated
by household type. When measuring
household resources, the main points of
interest concern the breadth of the income
concept used and the review of mechanisms

for evaluating the quality and correction
of income data from household surveys.
The ongoing methodological review aims
to obtain better quality and more accurate
statistics, as an essential requirement for
designing and implementing more appropriate
social policies that are better able to alleviate
the population’s basic needs. In some cases,
application of the new standards, together
with an updating of information sources,
can be expected to produce changes in
the indigence and poverty results that have
been reported thus far.

Source: Economic Commission for Latin America and the Caribbean (ECLAC).

Box I.3
POVERTY, INEQUALITY AND VULNERABILITY IN THE CARIBBEAN

The most recent information available on
poverty and inequality in the Caribbean was
examined using a procedure similar to that
employed in previous editions of the Social
Panorama. Although several of the countries
of the subregion have continuous household
survey programmes that focus mainly on
employment (Bahamas, Barbados, Belize,
Cuba, Jamaica, Netherlands Antilles,
Puerto Rico, Saint Lucia and Trinidad and
Tobago), only a few (Dominican Republic,
Guyana, Jamaica and Puerto Rico) have
two or more estimates of poverty that
are comparable time-wise. The data
come from very diverse sources and
methodologies, so extreme caution must
be exercised in comparing them with each
other and —except for the Dominican
Republic— with ECLAC estimates for
Latin America. The comparability of the
poverty and inequality estimates of the
countries of the Caribbean and those of
ECLAC is affected by factors such as the
type of indicator selected for household
resources (income or expenditure) and
its conceptual scope, the criteria used to
determine nutritional requirements and to
prepare the basic consumption basket and
the way non–nutritional needs are built into
the value of the poverty line.
A few general conclusions may
nevertheless be drawn concerning poverty

and inequality in the Caribbean. Haiti has the
highest incidence of poverty and indigence
not only in the Caribbean, but probably
in the entire region. This situation has
been worsened by a deep and prolonged
economic recession, in which per capita
GDP has shrunk steadily since 2000. The
gradual restoration of political and civil order,
however, has triggered in slight increase
in per capita GDP since 2006, providing
grounds for optimism that living standards
might improve in the country.
Other countries with high poverty
rates in the Caribbean are Dominica,
Dominican Republic, Grenada, Guyana,
Saint Kitts and Nevis, Saint Vincent and
the Grenadines and Suriname. At the
other end of the spectrum, Antigua and
Barbuda, Barbados, and the Bahamas have
particularly low levels of absolute poverty
which are similar to those of economically
highly developed countries. Special mention
should be made of Cuba and Puerto Rico.
In Cuba, poverty is measured by using
the concept of “population at risk”, which
refers to sectors with insufficient income
to purchase a basic basket of food and
non-food goods, but who at the same
time enjoy guaranteed access to free and
subsidized education, health care, social
security and welfare. According to this
method, in 1999, 20% of Cuba’s urban

population was “at risk”. The National
Statistics Office plans, together with ECLAC,
to look into coming up with measurements
that can be more readily compared with
the figures reported by other countries. In
Puerto Rico, the poverty rate is based on
the official poverty line of the United States
Federal Government, which, in 2005, was
US$ 15,577 per year for a three-person
family. The use of a parameter from a
high-income country accounts for the
high incidence of poverty on the island
in 2006 (45%).
The values of the poverty gap (which
vary between 2.3% in Barbados and 31.4%
in Suriname) and the Gini coefficient (with
a minimum of 0.23 in the British Virgin
Islands and a maximum of 0.65 in Haiti)
are generally lower in the Caribbean than
in the Latin American countries. Thus, the
share of the poorest quintile in national
income or consumption, which ranges
from 2.4% in Haiti to 10% in the British
Virgin Islands, is low but not as low as in
Latin America.
The available data show that poverty
declined substantially in the 1990s, at least
in Guyana, where it diminished from 43%
in 1993 to 35% in 1999; in Jamaica, where
it fell from 28% in 1990 to 15% in 2005;
and in Puerto Rico, where the decline was
from 59% in 1989 to 45% in 2006. In the

Social Panorama of Latin America • 2007

Dominican Republic —where the changes
introduced in the household survey in
2000 prevent comparisons being made
with previous years (see box I.3, ECLAC,
2004b)— poverty increased between 2002
and 2004 and then declined in 2005 and

59

2006, such that the level of 44.5% reported
for 2006 is barely lower than the 44.9%
recorded in 2002 (see table I.4).
Nonetheless, exogenous economic
shocks (such as the rise in oil prices) or
natural disasters (such as hurricanes, storms

or volcanic eruptions) can damage the
prospects for continued poverty reduction
not only in these four countries but also in
the other small and vulnerable countries
of the Caribbean.

DEMOGRAPHIC, POVERTY AND INEQUALITY INDICATORS IN THE CARIBBEAN
Economies

Population
2007
(Thousands
of people)

Anguila

13

Antigua and Barbuda

85

Netherlands Antilles

192

Aruba

104

Year of estimation
of poverty and
inequality indicators

2002
Start of 1990s
…
…

Poverty
rate

Indigence
rate

(% of people)

Poverty gap

Gini
Share of consumption/national
coefficient
income received by the:

(% of
poverty line)

poorest
20% of the
population
(%)

richest 20% of
the population
(%)

23.0

2.0

6.9

0.31

6.5

39.7

12.0
…

...
…

...
…

0.53
…

...
…

...
…

…

…

…

…

…

…
42.0

Bahamas

331

2001

9.3

...

...

0.46

4.4

Barbados

294

1997

13.9

1.0

2.3

0.39

...

...

Belize

288

2002

33.5

10.8

11.1

0.40

...

...

Cuba

11 248

1999

20.0 a

67

2002

39.0

Dominica

...
15.0

4.3 b
10.2

0.38 c

...

...

0.35

7.6

44.6

Grenada

106

1998

32.1

12.9

15.3

0.45

...

...

Guyana

738

1993

43.2

20.7

16.2

0.40

6.3

46.9

1999

35.0

21.3

12.4

0.43

4.5

49.7

9 602

2001

75.0

56.0

10.0

0.65

2.4

63.4

Turks and
Caicos Islands

26

1999

25.9

3.2

5.7

0.37

…

…

British Virgin Islands

23

2002

22.0

1.0

4.1

0.23

10.0

36.0

111

2000

32.5

…

…

…

…

…

Haiti

United States
Virgin Islands
Jamaica

1990

28.4

...

7.9

0.38

6.0

46.0

2005
Montserrat

2 714

14.8

...

4.6 d

0.38 d

6.1 d

45.9 d

6

…

…

…

…

…

…

…

Puerto Rico

3 991

1989

58.9 e

...

...

0.51

2.9

53.2

2006

45.4 e

Dominican Republic

9 749

2000

46.9

2006

…

…

…

…

…

22.1

22.1

0.55

2.7

59.5

Saint Vincent and
the Grenadines

50

62.2

120

44.5

22.0

21.1

0.58

2.5

2000 (Saint Kitts)

30.5

11.0

2.5

0.40

...

...

2000 (Nevis)

Saint Kitts and Nevis

32.0

17.0

2.8

0.37

...

...

37.5

25.7

12.6

0.56

...

...
48.3

1996

Saint Lucia

165

1995

25.1

7.1

8.6

0.43

5.2

Suriname

458

2000

69.2

...

31.4

0.46

12.6 f

51.8

1 333

1992

21.2

11.2

7.3

0.40

5.5

45.9

Trinidad and Tobago

1998

24.0

8.3

…

…

…

…

2005

16.7

1.2

…

…

…

…

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys conducted
in Dominican Republic and information from Elena Álvarez and Jorge Mattar (coords.), Política social y reformas estructurales: Cuba a principios
del siglo XXI (LC/L.2091), Mexico City, ECLAC Subregional Headquarters in Mexico/Instituto Nacional de Investigaciones Económicas/United
Nations Development Programme (UNDP), April 2004; Caribbean Development Bank (CDB), Anguilla Poverty Assessment Report, Saint Michael,
2004, Dominica Poverty Assessment Report, Saint Michael, 2003, British Virgin Islands Poverty Assessment Report, Saint Michael, 2003, Saint
Kitts and Nevis Poverty Assessment Report, Saint Michael, 2001, Grenada Poverty Assessment Report, Saint Michael, 1999, Saint Vincent and
the Grenadines Poverty Assessment Report, Saint Michael, 1996, Saint Lucia Poverty Assessment Report, Saint Michael, 1995, Turks and Caicos

60

Economic Commission for Latin America and the Caribbean (ECLAC)

Box I.3 (concluded)
Islands Poverty Assessment Report, Saint Michael, 2000; World Bank, World Development Indicators 2006, Washington, D.C., Poverty Reduction
and Human Resource Development in the Caribbean, Washington, D.C., May 1996; Economic Commission for Latin America and the Caribbean
(ECLAC), “CEPALSTAT” [online database] http://websie.eclac.cl/sisgen/ConsultaIntegrada.asp; Ministry of Finance, Department of Statistics,
The Bahamas Living Conditions Survey 2001: Preliminary Findings, Nassau, 2001, Labour Force and Household Income Report 2001, Nassau,
2001; Government of Belize, 2002 Belize Poverty Assessment Report, Belmopan, 2004; Government of Guyana, Poverty Reduction Strategy Paper,
Georgetown, May 2002; Government of Jamaica, Millennium Development Goals, Kingston, April 2004, National Poverty Eradication Programme,
Kingston, 2006; Haiti/United Nations Development Programme (UNDP), Rapport national sur les objectifs du millénaire pour le développement,
Port-au-Prince, 2004; United Nations, The Millennium Development Goals: A Latin American and Caribbean Perspective (LC/G.2331-P), José
Luis Machinea, Alicia Bárcena and Arturo León (coords.), Santiago, Chile, August 2005; Census Bureau, 2000 Census of Population and Housing,
Washington, D.C., August 2003; P. Sletten and W. Egset, “Poverty in Haiti”, FAFO-paper, No. 2004; M.D. Thomas and E. Wint, Inequality and
Poverty in the Eastern Caribbean, document presented at the Seventh Annual Development Conference of the Eastern Caribbean Central Bank
(ECCB), Basseterre, 21-22 November 2002; United Nations Development Programme (UNDP), Suriname MDG Baseline Report, Paramaribo, 2005;
United Nations University/World Institute for Development Economics Research (UNU/WIDER), World Income Inequality Database (WIID2.0a),
Helsinki, June 2005; American FactFinder, official site [online] http://factfinder.census.gov; Caribbean Net News “Trinidad publishes poverty survey
report for 2005”, 11 October 2007, http://www.caribbeannetnews.com/; Economic Commission for Latin America and the Caribbean / United
Nations Development Programme (ECLAC/UNDP), Report of the Caribbean preparatory meeting of the annual ministerial review (LC/CAR/L.122),
June 2007.
a Urban areas only; refers to population at risk of falling into poverty.
b 1996.
c 1996-1998; urban areas.
d 2001.
e Official poverty line established by the Federal Government of the United States of America.
f Refers to the poorest 40% of the population.

Box I.4
INDICATORS FOR MEASURING POVERTY

The process of measuring poverty encompasses at least two stages:
(i) the identification of the poor, and (ii) the aggregation of poverty
into a synthetic measurement. The first stage, which is described
in box I.1, consists in identifying the population whose per capita
income is lower than the cost of a basket of items that will satisfy
basic needs. The second stage consists in measuring poverty using
indicators that synthesize the information into a single figure.
The poverty measurements used in this document belong to the
family of parametric indices proposed by Foster, Greer and Thorbecke
(1984), which are obtained from the following equation:


(1)

where n represents the size of the population, q denotes the
number of people with income below the poverty line (z), and
the parameter α  0 assigns varying weights to the difference
between the income (y) of each poor or indigent individual and
the poverty or indigence line.
When α = 0 equation (1) corresponds to what is known as
the headcount index (H), which represents the proportion of the
population with income lower than the poverty or indigence line:


(2)

Because it is easy to calculate and interpret, this indicator
is the one most commonly used in poverty studies. However,
the headcount index provides a very limited view of poverty,
since it offers no information on “how poor the poor are”, nor
does it consider income distribution.
When α = 1, however, the equation yields an indicator
that measures the relative income shortfall of poor people with
respect to the value of the poverty line. This indicator is known
as the poverty or indigence gap (PG):


(3)

The poverty and indigence gap index is considered more
complete than the headcount index because it takes into account
not only the proportion of poor people, but also the difference
between their incomes and the poverty line. In other words, it
adds information about the depth of poverty or indigence.
Lastly, an index that also considers the degree of disparity in
the distribution of income among the poor or indigent is obtained
when α = 2. This indicator also measures the distance between the
poverty line and individual income, but it squares that difference
in order to give greater relative weight in the final result to those
who fall furthest below the poverty or indigence line:


(4)

The values of the FGT2 index are not as simple to interpret
as those of the H and PG indices. Since this index is more
comprehensive, however, it is the preferred choice for use in
designing and evaluating policies and in comparing poverty
between geographical units or social groups.
All three of these indicators have the property of “additive
decomposability”, meaning that a population’s poverty index
is equal to the weighted sum of the indices of the different
subgroups of which it is composed. Accordingly, the national
poverty and indigence indices contained in this publication were
calculated by averaging the indices for different geographical
areas, weighted according to the percentage of the population
living in each area.

Source: James Foster, Joel Greer and Erik Thorbecke, “A class of decomposable poverty measures”, Econometrica, vol. 52, 1984.

Social Panorama of Latin America • 2007

61

B. Progress towards meeting the first target
of the millennium development goals
Considering the progress made in reducing extreme poverty in the region in the last two years,
attaining the target set out in the Millennium Declaration of halving extreme poverty between
1990 and 2015 has become highly feasible in Latin America and the Caribbean. The region is
already 87% of the way towards reaching the target and, according to some estimates, all that
is needed to complete the task is for GDP growth to keep up with population growth for the
next eight years. Latin America should therefore now take on a more significant challenge,
such as halving total poverty. For this challenge to be met, however, there will have to be
considerable improvements in resource distribution in the region.

The progress made towards meeting the first Millennium
target, which consists of halving the number of people
living in extreme poverty or indigence between 1990 and
2015, can be measured on the basis of the poverty and
indigence estimates presented in the previous section.
Latin America’s projected extreme poverty rate for
2007 amounts to 12.7%, which is 9.8 percentage points
below the 1990 figure (22.5%). This means that Latin
America is 87% of the way towards meeting the first
Millennium target at a point in time when just 68% of the
period provided for that achievement has passed.6 This
evidence gives reason to believe that the region as a whole
is fully on track to meet its commitment to halve the 1990
extreme poverty rate by 2015 (see figure I.3).
The projections for extreme poverty rates in 2007
paint a bright picture for many countries. The most recent
figures for Ecuador (urban areas) and Mexico indicate that
they will join the ranks of countries that, like Brazil and
Chile, have already reached the first target established for
the first Millennium Development Goal. The Bolivarian
Republic of Venezuela, Colombia, El Salvador, Panama
and Peru have progressed as much as, or more than,
expected (68%). All the other countries in Latin America

6

have lower extreme poverty rates than they did in 1990,
but some of them are behind where they should be in order
to reach this target on time. It should be pointed out that
although Argentina and Uruguay are still less than 40%
of the way, they are only 2.5 and 1.0 percentage points,
respectively, from their target in absolute terms. On the
other hand, Bolivia, Honduras, Nicaragua and Paraguay,
who are also less than half way to meeting their target,
still have a considerable way to go.
Taken as a whole, the region has a very good chance of
reaching this first target. Assuming that no major changes
in income distribution occur in the next few years, Latin
America will only have to achieve GDP growth of 1.1%
per year, which is less than its population growth rate.
The low level of growth required is partially due to the
fact that four countries have already surpassed the target
and are therefore “subsidizing” those that are further
behind. This is all the more so because the over-achievers
include Brazil and Mexico, which together account for
over half of the region’s population. In fact, the growth
rate for countries that have not yet attained this first target
averages 4.0% per annum, which translates into a 2.6%
annual increase in per capita GDP (see figure I.4).

The time allotted for reaching this target is 25 years (from 1990 to 2015); 17 of those 25 years have passed, which amounts to 68% of the total
period provided for this effort.

62

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure I.3
LATIN AMERICA (17 COUNTRIES): PROGRESS IN REDUCING EXTREME POVERTY AND TOTAL POVERTY BETWEEN 1990 AND 2007 a


Extreme poverty 

Total poverty

Latin America

Latin America

Argentina b

Argentina b

Bolivia

Bolivia

Brazil

Brazil

Chile

Chile

Colombia

Colombia

Costa Rica

Costa Rica

Ecuador b

Ecuador b

El Salvador

El Salvador

Guatemala

Guatemala

Honduras

Honduras

Mexico

Mexico

Nicaragua

Nicaragua

Panama

Panama

Paraguay

Paraguay

Peru

Peru

Uruguay b
Venezuela
(Bolivarian Rep. of)

Uruguay b
Venezuela
(Bolivarian Rep. of)
0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
aThe amount of progress made (expressed as a percentage) is calculated by dividing the percentage–point reduction (or increase) in indigence
registered during the period by one half of the indigence rate for 1990. The dotted line represents the amount of progress expected by 2007 (68%).
bUrban areas.

Figure I.4
LATIN AMERICA (16 COUNTRIES): PER CAPITA GDP
GROWTH RATES NEEDED TO HALVE THE 1990
EXTREME POVERTY RATE BY 2015
8%
6%
4%
2%
0%
-2%
-4%
-6%
Paraguay

Brazil

Venezuela (Bol. Rep. of)

Bolivia

Ecuador

Guatemala

Mexico

Nicaragua

Colombia

El Salvador

Latin America

Uruguay

Argentina

Peru

Costa Rica

Chile

Panama

-8%

Growth needed without a change in income distribution
Growth required with a 10% reduction in Gini coefficient
Per capita GDP growth 1990-2006 plus 1%
Per capita GDP growth 1990-2006

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of household surveys
conducted in the respective countries.

The situation among the countries that have still not
attained the target of halving the 1990 indigence rate
varies considerably. Six of them (the Bolivarian Republic
of Venezuela, Costa Rica, El Salvador, Panama, Peru and
Uruguay) could meet the target as long as their GDP keeps
growing at the average rate recorded between 1991 and
2006 and provided that their income distribution levels
do not deteriorate. Given their economic performance
in recent years, Argentina and Colombia could also be
included in this group as they are highly likely to attain
the slightly above-average GDP growth rates they need
in order to halve their indigence rates.
The remaining countries will have to make far
greater progress than they have so far if they are to meet
the target. Huge inequalities in income distribution
need to be addressed throughout the region, but in these
countries in particular, implementing economic growth
policies hand in hand with policies aimed at increasing
the participation of the poor in the fruits of that growth
has become absolutely imperative. The magnitude of the
problem varies from country to country. Guatemala is
in the best situation in this respect inasmuch as it could
attain the first Millennium target without having to bring

Social Panorama of Latin America • 2007

about significant changes in income distribution. Bolivia
and Nicaragua, on the other hand, need to increase GDP
growth by one percentage point above average and achieve
a redistribution of income equivalent to a 10% reduction in
the Gini coefficient. The situation in Honduras and Paraguay
is even more complicated because they will need to attain
even higher levels of growth and greater changes in income
distribution than Bolivia and Nicaragua. Priority needs to
be awarded to providing regional support to the countries
that are most behind in meeting the Millennium targets
so as to ensure that they really contribute to improving
living conditions in Latin America.
ECLAC has, both in previous editions of Social
Panorama of Latin America and the inter-agency report
on the Millennium Development Goals (United Nations,
2005), proposed a more ambitious target that is, in principle,
more in accordance with the region’s level of economic
development. This new proposed target consists of halving
the total poor population by 2015. Progress in this respect
(13.2 percentage points, from 48.3% to 35.1%) has been
slower than in the reduction of extreme poverty, and
only 55% of the target has been attained by the region
so far. Chile is the only country that has met the target

63

and halved total poverty. Ecuador, Mexico and Panama
are on track to do so, having already attained 70% of the
reduction required. Next come Argentina, the Bolivarian
Republic of Venezuela, Brazil, Colombia, Costa Rica and
El Salvador, with 50% or more of the required reduction
already attained. Less than 50% progress has been recorded
in the remaining countries (see figure I.3).
Improving income distribution is an essential factor
for attaining this target as it can boost the positive effect
economic growth has on poverty reduction. If, for
example, in 2008-2015, there is a slight improvement
in distribution equivalent to a 5% decline in the Gini
coefficient, the target can be met with an annual per
capita GDP increase of around 2%, which is barely higher
than the historic growth recorded by this indicator in
the region. Other demographic, household and labourrelated factors, which are analysed in the next section,
have contributed to poverty reduction during the past
two decades. These can be taken advantage of to ensure
that living conditions continue to improve in the region.
Halving not only extreme poverty, but also total poverty,
is therefore a challenge that is fully compatible with the
region’s development prospects.

64

Economic Commission for Latin America and the Caribbean (ECLAC)

C. Factors linked with poverty reduction
The countries that made the most progress in poverty reduction between 1990 and 2005
also recorded substantial drops in unemployment. This implies that the composition of a
household and the extent to which its members can and do participate in the labour market
plays a significant role in reducing poverty. The presence of declining dependency rates,
also known as the “demographic dividend”, has favoured poverty reduction in the region.
This dividend is only a window of opportunity, however, and in order to take full advantage
of it, countries need to pursue initiatives that increase worker productivity, improve public
spending programmes for the more vulnerable sectors of the population and enable people
to reconcile the demands of the home with remunerated work.

This section examines the influence of various demographic,
household and labour-related factors on poverty reduction
in 1990-2005 in the countries of Latin America and the
Caribbean. This period constitutes the first 15 years of the
25-year framework established for reaching the first target
of the Millennium Development Goals, which consists
of halving the percentage of people living in extreme
poverty between 1990 and 2015. In view of the progress
already made by some of the region’s countries in reducing
extreme poverty, the more ambitious target of halving
the entire poor population, rather than just the extremely
poor population, proposed in the inter-agency report on
the Millennium Development Goals (United Nations,
2005), is taken into consideration in this evaluation. In
order to achieve this new target, the factors that contribute
to poverty reduction need to be identified because, in the
current situation, unless new initiatives are undertaken,
it is unlikely that most of the region’s countries will be
able to meet this additional challenge.
Generally speaking, poverty trends can be understood
by looking at changes in three determinants of per capita
household income: the ratio of employed persons to total

7
8

population, labour income per employed person and nonlabour income (public transfers, remittances, etc.).7 When
the percentage of employed persons, wages per employed
person and non-labour income levels in low-income
households rise, poverty levels tend to diminish. These
determinants can, in turn, be broken down into a series
of factors: changes in labour income are linked with the
behaviour of human capital and productivity patterns;
changes in non-labour income stem from public and private
transfers and from the rate of return on capital; and changes
in employment levels can be traced back to demographic
changes, shifts in family structures and the way in which
households react to employment opportunities.8
The analysis performed in this section focuses on
the influence of demographic changes and shifts in the
structure and composition of families on poverty in
Latin America during 1990-2005. This is particularly
important given that the region currently faces a historic
window of opportunity, known as the “demographic
dividend”, which has been created by the declining
dependency ratio, i.e., by the increase in the number
of working-age people in relation to the population as

This breakdown is valid when measuring poverty on the basis of money income, which can be used as a means of gauging people’s and
households’ ability to meet their basic food and non-food needs.
Certainly, there are other factors that influence labour income as well, such as the degree of protection enjoyed by the labour force and its
bargaining power (degree of unionization, existence of collective bargaining mechanisms, etc.).

Social Panorama of Latin America • 2007

whole. If the demographic dividend is to help reduce
poverty, however, other conditions need to be met as
well. Job opportunities, for example, that encourage
people to join the labour market need to be created, and

1. 

10

the restrictions derived from the cultural attitudes and
economics of caring for the home and family, which
prevent women from participating in wage work, need
to be lifted (Cecchini and Uthoff, 2007).

Preliminary considerations

Two factors contribute to the perpetuation of poverty: the
high demographic dependency rates of poor households,
in which income has to be distributed among a larger
number of people; and the low incomes workers in these
households obtain on account of their limited accumulation
of human capital and their low productivity. In both cases,
but especially with regard to family size, the choices and
decisions made by the family, as the basic socio-economic
unit, play an essential role.9
Decisions regarding the size and composition of the
family group and the participation of its members in the
labour market directly affect the dependency ratio in a
household. The possibilities of generating more income
rise when such decisions increase the proportion of
working-age members in the family. There is an element
of inertia in the impact of these decisions: family size
and composition will change anyway according to the
different stages of the family life cycle and changes in the
fertility of its members. Decisions that affect the family’s
circumstances, however, such as decisions about where to
live, how many children to have, whether to stay together
or what new living arrangements to make, also have an
impact on the dependency ratio. The break-up of the family
or a change in its structure can modify the dependency
relationships in different ways: the economically active
members might leave the home, younger couples might
start to take care of the inactive members, or new family
units might be formed to share expenses.
The size and structure of Latin American families vary
considerably and are determined by a series of factors,
such as the country’s level of economic development, the
stage of demographic transition and the state of decline
of the patriarchal family.10 In countries that are in an
advanced stage of demographic transition, for example,
9

65

childless couples make up a larger proportion of nuclear
families, and more and more economically autonomous
elderly and young people live alone. In countries in
the moderate or full stages of demographic transition,
there are more families with young children, and in the
less developed countries, there is a higher proportion of
one-parent nuclear families and extended or composite
families (ECLAC, 2007a).
The outcome of the interplay of these factors is that
poor families in the region have more members than
the non-poor and that most members of poor families
are children, which drives up the dependency rate. The
largest families nowadays are mainly found among the
quintile with the lowest income, and the smallest families
among the quintile with the highest income. The number
of members of the average urban family in the poorest
quintile ranges from 4.2 in the Dominican Republic to
6.2 in Guatemala, while the average number in the richest
quintile ranges from 2.1 in Uruguay to 4 in Nicaragua.
Despite the declining dependency ratio and the
resulting “demographic dividend” (see box I.5),
dependency is still high among the most vulnerable socioeconomic groups because they have higher fertility rates
(see table I.5). Teenage pregnancies are more common
among poor girls, and pregnant teenagers tend to drop
out of school, which means that poverty is perpetuated
from one generation to the next. In Latin America, the
fertility rate of teenagers from the poorest quintile is
three times higher or more than among girls from the
richest quintile, and up to five times higher in some
countries. Unlike the total fertility rate, which has come
down, the teenage fertility rate has shown few signs of
budging in the past 20 years (ECLAC/UNICEF, 2007;
ECLAC, 2006a).

The family is a vitally important strategic resource in the region. It is the main institution for support and social protection in times of economic
crisis, unemployment, illness, the death of a family member or other traumatic events. The family is also linked to social inequalities, however,
that are perpetuated primarily in two ways: through the influence of family origins and ties on behaviour and attitudes and through the influence
of the family on access to employment and job hierarchies (Arriagada, 2004).
The stages of demographic transition are: (i) incipient, with high birth and mortality rates; (ii) moderate, with high fertility rates but a moderate
decline in mortality; (iii) full, with declining mortality and fertility; and (iv) advanced, with low fertility and mortality. When fertility drops
to below replacement rates and remains at that low level for a prolonged period of time, a fifth stage may be reached in which the population
growth rate is negative and the aging of the population is more pronounced. This is beginning to occur in Cuba and other Caribbean countries
(Chackiel 2004; ECLAC, 2005a).

66

Economic Commission for Latin America and the Caribbean (ECLAC)

Table I.5
LATIN AMERICA (6 COUNTRIES): TOTAL FERTILITY RATE, BY SOCIO-ECONOMIC STRATA
Country

Stratum

Year

Low / high
ratio

1 (low)

Honduras
Panama
Paraguay
Venezuela
(Bolivarian
Republic of)

4

5 (high)

4.3
3.5
2.9
2.3
7.3
4.6
5.2
4.4
6.3
6.2
4.3

3.0
2.6
2.6
2.0
5.5
4.7
3.7
3.1
5.8
3.7
3.8

2.7
2.4
2.6
2.1
5.8
3.2
2.7
2.6
4.1
4.4
3.4

2.2
1.9
2.6
2.0
5.3
3.5
2.5
2.3
4.3
3.5
3.0

2.1
1.7
2.5
2.0
3.5
2.5
2.0
1.8
3.2
2.7
2.5

2.1
2.1
1.1
1.1
2.1
1.8
2.6
2.4
2.0
2.3
1.7

2001

Chile

3

1991
2000
1992
2002
1988
2001
1990
2000
1992
2002
1990

Brazil

2

4.1

3.4

2.6

2.5

2.1

2.0

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of specialprocessing of census
microdatabases.
Note: The table presents survey data. The socio-economic stratum variable was therefore constructed using a combination of two sub-indices: one refers
to the assets in the home and the other to the level of education of the head of the household. For further information, see box III.3, ECLAC, 2006a.
Box I.5
THE DEMOGRAPHIC DIVIDEND

Experts on the subject refer to the period in
which the demographic dependency ratio
declines as a “demographic dividend”. This
“dividend” only lasts for a certain period of
time because the combination of a lower
fertility rate and greater longevity eventually
increases the proportion of elderly people
in the population to the point at which the

dependency ratio rises again and creates
new demands for health care and economic
security. The figure below presents the
demographic dependency ratio in 2005
for 20 Latin American countries, together
with estimates of the year in which the
ratio will rise again and the demographic
dividend will peak.

The year in which the dividend peaks
is linked to the stage of demographic
transition that the country has reached.
In Latin America, most countries
are in the advanced stage in which
birth and death rates are low and the
demographic dependency ratio is less
than 62%. In some countries, such as

LATIN AMERICA (20 COUNTRIES): YEARS IN WHICH THE DEMOGRAPHIC DIVIDEND WILL PEAK AND DEMOGRAPHIC
DEPENDENCY RATIO IN 2005, ACCORDING TO STAGE OF DEMOGRAPHIC TRANSITION, 2005-2010a b

Demographic transition stage (2005-2010)

2040

Advanced
with declining
population

with rising population

Year

2030
2020

43.5

48.9

51.2 51.7

Moderate 100
90
90.1
78.3
80
73.7
69.3 71.8
68.2
70
63.9 64.7
Full

59.5 61.6 57.4
59.2
56.4 57.0 57.0
54.8 57.5

60
50
40

2010

30
20

2000

Guatemala

Bolivia

Paraguay

Honduras

Haiti

Nicaragua

El Salvador

Dominican Republic

Argentina

Peru

Ecuador

Panama

Venezuela (Bol. Rep. of)

Latin America

Mexico

Uruguay

Colombia

Costa Rica

Chile

Brazil

10
Cuba

1990

0

Demographic dependency ratio (2005)

2050

Year in which the demographic dividend peaks
Demographic dependency ratio

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of population estimates and projections
from the Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC.
aThe demographic dependency ratio is equal to: [(population aged between 1 and 14 years + population aged 65 years and over) /population
aged 15 to 64 years] x 100.
bThe countries were grouped as follows: moderate transition = birth rate of 32 to 42 per 1,000; full transition = birth rate of 22 to 32 per 1,000;
advanced transition = birth rate of 22 to 12 per 1,000.

Social Panorama of Latin America • 2007

67

Box I.5 (concluded)

Argentina and Uruguay, the fertility
and mortality rates have been low for
some time. Seven countries are in the
full transition stage, with high, but
falling, birth rates and a demographic
dependency ratio of between 64% and
78%. The dependency ratio in Cuba
is already very low, and the country’s
demographic dividend is expected to
be over in 2010. At the other extreme,
Guatemala is in the moderate stage of
transition with high fertility rates, that
are however declining, albeit slowly, and
a high demographic dependency ratio
(90%) that will probably keep falling until
2050. No Latin American country is at
the incipient stage in which birth and
mortality rates are both very high.
The year at which the demographic
dividend is expected to peak was
estimated on the basis of periods of
steady decline in the demographic
dependency ratio. There may be
exceptions, however. The ratio might
rise again briefly during the lifetime of
the dividend as part of the demographic
transition process or as a result of

international migration. In Chile, for
example, the demographic dependency
ratio in 1995 was slightly higher than in
1990, but has declined steadily since
then and is expected to continue to do
so until 2015. Obviously any projections
40 or 50 years into the future entail a
degree of uncertainty. The years given
for the demographic dividend to peak
must therefore be considered to be
indicative estimates only.
For the potential benefits of the
dividend to be anything more than
demographic, an increasing number of
people at the age to be economically active
need to actually participate in economic
activity. This will require the confluence of
a set of less predictable factors, however,
linked to: (i) the capacity of the region’s
economies to create jobs that offer wages
that are high enough to motivate people
to join the workforce; (ii) the willingness
of people to put in more hours of work to
satisfy their income needs; and (iii) attitudes
towards the care of family members that
allow women to overcome the limitations

that currently prevent them from devoting
more time to paid work.
In other words, attention needs to
be paid to the employment conditions
awaiting the swelling ranks of the active
population to ensure that the benefits of
the demographic dividend are reaped and
maximized. Significant investments need
to be made in innovation to boost the
productivity of those that will be joining
the workforce in the future. The effects
of the demographic dividend on poverty
and social inclusion have the potential
to reduce the insecurity, precariousness
and informality that characterize the
labour markets in the region. For this
is to happen, however, huge efforts will
need to be made in areas such as youth
education and training, job creation and
the development of comprehensive
social protection schemes. Otherwise
the number of jobseekers will rise
without there being a parallel increase
in employment opportunities, and the
demographic dividend will turn into
another burden for countries.

Source: Inter-American Development Bank (IDB), Good Jobs Wanted: Labor Markets in Latin America, Washington, D.C., 2003; Simone Cecchini
and Andras Uthoff , “Reducción de la pobreza, tendencias demográficas, familias y mercado de trabajo en América Latina”, Políticas sociales
series, No. 136, Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), 2007. United Nations publication, Sales
No. S.0X.II.G.110; Economic Commission for Latin America and the Caribbean (ECLAC), Social Panorama of Latin America 2004 (LC/G.2220–
P/E), Santiago, Chile, 2005. United Nations publication, Sales No. E.04.II.G.148 and G. Standing, Labour Force Participation and Development,
Geneva, International Labour Organization (ILO), 1982.

Most families in the initial, expansion and consolidation
stages of the family life cycle are in the poorest quintiles.
Resources are stretched thin because the family is large
and includes dependent-age children. Those who live
alone, young couples without children, families in the exit
stage of the family life cycle and older couples without
children, on the other hand, are mostly found in the richest
quintiles (see figure I.5).
Attitudes towards the division of labours in the home
can impose significant restrictions on women and their
participation in economic life. Around 2005, the number of
women working outside the home among the poorest decile
was 37%, compared with 61% for the richest decile. The
difference among men was minimal: 76% of the poorest
and 80% of the richest men were economically active (see
figure I.8). The limited scope of the care economy has

made it very difficult for women to reconcile remunerated
work with the demands of the home and the need to take
care of children and elderly relatives.
It is not just low employment and high dependency
rates that perpetuate poverty, however. The low income
levels of poor households are also associated, among
other factors, with the limited human capital of their
economically active members. This situation, which
is linked to the fact that these members have few job
opportunities, generates another vicious circle: members
of poor households are inadequately prepared for anything
but the most precarious jobs, and the children and young
people living in such households have few opportunities
for receiving high-quality education and training, which
means they fail to accumulate sufficient social capital and
end up in low-productivity occupations when they enter

68

Economic Commission for Latin America and the Caribbean (ECLAC)

Stages of the family life cycle
40
35
30

Non-family
household

Young
couple
without
children

Initial
stage

Expansion
stage

Consolidation
stage

Exit stage

Older
couple
without
children

25
20
15
10

Figure I.6
LATIN AMERICA (18 COUNTRIES): WORKING-AGE POPULATION
AND PARTICIPATION IN ECONOMIC ACTIVITY, BY INCOME
DECILES, NATIONAL TOTALS, AROUND 2005 a b
(Simple average)
80

WAP as a percentage of total population
EAP as a percetnage of the working-age population

Percentage of households and families in each income quintile

Figure I.5
LATIN AMERICA (18 COUNTRIES): PERCENTAGE
DISTRIBUTION OF HOUSEHOLDS AND FAMILIES IN DIFFERENT
STAGES OF THE FAMILY LIFE CYCLE, BY INCOME QUINTILE,
URBAN AREAS, AROUND 2005
(Simple average)

74.8
75

73.0
70.9

63.4

60

1 2 3 4 5

1 2 3 4 5

1 2 3 4 5

1 2 3 4 5

1 2 3 4 5

63.7
60.3

58.0

58.2
55.5

55
51.8
50

47.9

45

1 2 3 4 5

65.5

61.3

61.5

Total

5
0

68.4

67.5
65.5

65

73.5
70.7

69.1

68.6

70

75.5

Decile I Decile II Decile III Decile IV Decile V Decile VI Decile VII Decile VIII Decile IX Decile X
(poorest)
(richest)

Working-age population (WAP/N)

1 2 3 4 5

Participation rate (EAP/WAP)

Income distribution quintiles
aThe

the labour market as well.11 Being out of work is more
common among the poor, and those who do manage to
find a job often do so in the informal labour market and
not as pay-rolled employees (see figure I.7).12

11

12

Figure I.7
LATIN AMERICA (18 COUNTRIES): UNEMPLOYMENT RATE,
EMPLOYMENT RATE AND PROPORTION OF TOTAL WORKERS
EMPLOYED IN THE FORMAL SECTOR OF THE ECONOMY, BY
INCOME DECILE, NATIONAL TOTALS, AROUND 2005 a b
80
70

62.5

60

Percentage

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of data from household surveys conducted in the
relevant countries.
Notes:
Quintile 1: poorest; Quintile 5: richest. The percentages represented by
the bars for quintiles 1 to 5 for each type of household and family add
up to 100%.
Non-family household: single-person homes (occupied by only one
person) and homes without a conjugal nucleus (father/mother and son/
daughter) although other family ties may exist.
Stages of the family life cycle: (i) young couple: couple that has not
had children and the woman is under 40; (ii) initial stage: families with
one or more children aged 5 or under; (iii) expansion stage: families
whose oldest children are aged 6 to 12 years regardless of the age of
the youngest child; (iv) consolidation stage: families whose children are
aged 13 to 18 or in which the age difference between the eldest and
youngest child is generally 12 to 15 years. The largest proportion of
reconstituted families are in this stage because the large age difference
between the eldest and youngest children is the result in some cases of
the formation of new unions with young children; (v) exit stage: families
whose youngest children are 19 or older, and (vi) older couple: couple
without children in which the woman is over 40.

data in Argentina, Bolivia, Ecuador, Paraguay and Uruguay only
refer to the urban population and not the national total.
bThe working age population refers to people aged 15 to 64 years.

50

53.1
48.0

55.8

65.5

68.4

71.0

72.6
66.4

60.6
54.1

50.6

47.4

43.5

39.6

36.1
29.6

30
22.2

20

0

60.9

45.5

40

10

58.4

63.3

8.9

Total

20.0
13.6

12.2

10.9

9.6

8.4

7.6

6.2

5.0

3.8

Decile I Decile II Decile III Decile IV Decile V Decile VI Decile VIIDecile VIII Decile IX Decile X
(richest)
(poorest)

Unemployment rate
Workers in the formal sector
Employment rate

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of data from household surveys conducted in the
relevant countries.
Note: WAP = working-age population; EAP = economically active
population; N = total population.
aThe data on Argentina, Bolivia, Ecuador, Paraguay and Uruguay only
refer to the urban population and not the national total.
bThe employment rate refers to the number of employed divided by the
working-age population (“gross” employment rate).

See chapter III on quality in education.
According to ILO (2005), in 2005, the unemployment rate among the poor in the region was on average 2.9 times higher than among the nonpoor, and unemployment among the indigent population was 4.1 times higher than among the non-poor.

Social Panorama of Latin America • 2007

69

Figure I.8
LATIN AMERICA (18 COUNTRIES): PARTICIPATION IN ECONOMIC
ACTIVITY OF MEN AND WOMEN, BY INCOME DECILES,
NATIONAL TOTAL, AROUND 2005 a
(Simple average)

Percentage of the working-age population of the same sex

90
80

79.9

81.0

80.1

78.7

76.3

80.3

80.3

80.0

80.5

80.6

79.7

70
60
50

56.1
49.8
40.2

40

42.5

44.8

47.2

49.7

59.0

61.1

51.8

36.5

30
20
10
0

Total

The statistics reveal a perverse interplay among factors
whereby labour and family dynamics actually worsen the
shortage of income in poor households and thus ensure
the perpetuation of poverty from one generation to the
next. The poor tend to only find employment in lowproductivity occupations and be at greater risk of ending
up unemployed. They also live in households and belong
to families that have larger numbers of small children
and economic dependents. Moreover, less women from
poor households, as a proportion, are economically active
than women from the higher income deciles. This means
that poor families not only obtain less income, but that
that income has to be used to support a larger number
of people. The high levels of demographic dependency,
low levels of participation in economic activity, low
productivity and frequent episodes of unemployment
together exacerbate the situation of families living below
the poverty line.

Decile Decile II Decile III Decile IV Decile V Decile VI Decile VII Decile VIII Decile IX Decile X
(richest)
(poorest)

Women

Men

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of data from household surveys conducted in the
relevant countries.
aThe data on Argentina, Bolivia, Ecuador, Paraguay and Uruguay only
refer to the urban population and not the national total.

2. The factors linked to poverty reduction, 1990 - 2005
The analysis of the factors linked to poverty reduction
in Latin America and the Caribbean is based on the
breakdown of the determinants of the per capita income
of households living below the poverty line: the ratio of
employed persons to total population, labour income per
employed person and non-labour income (see box I.6.).13
Improvements in human capital and productivity raise the

13

labour income per employed person, while demographic
changes and shifts in family structures affect employment
levels. Decisions about the participation of members of the
household in the labour market are in turn affected by the
attractiveness of the new jobs created and the restrictions
imposed by the need to provide care for family members
in each country.

It is important to take into account the changes in labour income per employed person, overall employment and non-labour income per capita
in households living around or below the poverty line when analysing poverty trends. Increases in the median income can conceal situations
of poverty as they may reflect improvements recorded by the richest decile or a reduction in the number of poor.

70

Economic Commission for Latin America and the Caribbean (ECLAC)

Box I.6
METHODOLOGY USED FOR ANALYSING PER CAPITA INCOME TRENDS

The indicator used to classify families according to their monetary poverty measures their capacity to generate income in the
labour market and to obtain income from other sources, such as public transfers, remittances and financial investments. This
indicator can be analysed by examining the three main components of per capita income in a given population (Y/N):
• Overall employment rate or number of employed (O), divided by the total population (N): broad measurement of the participation
of different age groups in the labour market and a given economy’s capacity to absorb more workers;
• Labour income per employed person (YL/O): measurement that approximates labour productivity;
• Per capita non-labour income (YNL/N): refers to a range of sources of income, from public and private-sector transfers to
income from properties and income from imputed rents.
 

(1)

The global employment rate can be broken down as follows:
• Demographic dependency rate: ratio between the working-age population (WAP) and the total population (N);
• Participation rate: economically active population (EAP) divided by the working-age population (WAP), and
• Net employment rate: number of employed (O) divided by the economically active population (EAP).


(2)

In order to analyse per capita income trends between 1990 and 2005, the values of the three main components of this
indicator, (overall employment rate, labour income per employed person and non-labour income per capita) are presented in
annex I.1 according to the following formula:
(3)
Any increase in the number of employed, labour income per employed person, and non-labour income will help reduce the
monetary poverty of poor families and help some escape poverty.
The comparability of the data poses problems for several reasons. The periods taken into consideration vary from country to
country: in the case of the Bolivarian Republic of Venezuela, Brazil, Ecuador, Paraguay and Uruguay, for example, the period covered
is 1990-2005, while in El Salvador it is 1995-2004. In the case of Argentina, Bolivia, Ecuador, Paraguay and Uruguay, the data only
refers to the urban population and not the whole country. In some cases, the data obtained through surveys conducted in the same
country but on different dates may not be comparable. Finally, the use of only two points of reference during the period 1990-2005
may conceal natural oscillations of factors that have cyclical components, such as labour income and the net employment rate.
Source: Simone Cecchini and Andras Uthoff , “Reducción de la pobreza, tendencias demográficas, familias y mercado de trabajo en América
Latina”, Políticas sociales series, No. 136, Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), 2007. United
Nations publication, Sales No. S.OX.II.G.110.

The procedure consisted of first classifying households
by per capita income level, then ordering the population
into deciles from poorest to richest. Table I.6 presents
the values of per capita family income for each decile
(expressed as multiples of the poverty line) around
1990 and 2005 together with estimated variations of
that income according to changes in its three main
components: labour income per employed person, the

14

global employment rate and non-labour income per
capita.14 On the basis of the data presented in table I.6,
the countries of Latin America are classified in table
I.7 according to the variations recorded between 1990
and 2005 in the three components of income in the
deciles that around 1990 were below the poverty line.
The general variation in total poverty in each country
during the period is also given.

As highlighted in box I.6, the analysis of the variations occurring between 1990 and 2005 may conceal the oscillations occurring in the
intervening years.

Social Panorama of Latin America • 2007

71

Table I.6
Latin America (16 countries): per capita family income and breakdown of its variation by changes in labour
income per employed person, the overall employment rate and per capita non-labour income (in multiples
of the poverty line), by deciles of income distribution, 1989-1995 and 2001-2005 a
Country

Per capita
income

Total

Decile
I

Decile
II

Decile
III

Decile
IV

Decile
V

Decile
VI

Decile
VII

Decile
VIII

Decile
IX

Decile
X

Y/N 1990

2.41

0.3

0.5

0.7

0.9

1.1

1.4

1.8

2.4

3.7

11.1

Y/N 2003

3.71

0.5

0.9

1.2

1.5

1.8

2.2

2.8

3.7

5.5

17.2

Δ Y/N (Δ YL/O)

0.85

0.06

0.15

0.21

0.23

0.40

0.48

0.64

0.83

1.23

4.21

Δ Y/N (Δ O/N)

0.31

0.02

0.05

0.10

0.14

0.11

0.17

0.21

0.35

0.48

1.51

Δ Y/N (Δ YNL/N)

0.14

0.10

0.11

0.12

0.15

0.14

0.14

0.14

0.09

0.10

0.37

Y/N 1990

3.09

0.6

0.9

1.2

1.5

1.8

2.2

2.6

3.2

4.3

12.7

Countries with low poverty rates
Chile

Uruguay b

2.77

0.5

0.8

1.1

1.4

1.8

2.1

2.6

3.3

4.5

Δ Y/N (Δ YL/O)

-0.36

-0.10

-0.14

-0.11

-0.15

-0.13

-0.08

-0.10

-0.07

0.20

-2.71

Δ Y/N (Δ O/N)

0.00

0.00

0.01

0.01

0.04

0.05

0.01

-0.02

-0.03

-0.08

-0.16

Δ Y/N (Δ YNL/N)

0.03

0.05

0.04

0.02

0.04

0.04

0.05

0.12

0.17

0.09

-0.24

Y/N 1990

2.17

0.3

0.7

0.9

1.2

1.5

1.8

2.2

2.8

3.6

7.0

Y/N 2005

2.78

0.4

0.8

1.1

1.4

1.7

2.1

2.6

3.4

4.7

9.8

Δ Y/N (Δ YL/O)

0.16

0.02

-0.02

-0.02

-0.02

0.00

-0.02

-0.02

0.09

0.45

1.21

Δ Y/N (Δ O/N)

0.33

0.02

0.08

0.13

0.17

0.22

0.27

0.39

0.47

0.46

0.96

Δ Y/N (Δ YNL/N)

0.13

0.07

0.05

0.04

0.07

0.03

0.05

0.04

0.05

0.21

0.62

Y/N 2005

Costa Rica

9.6

Countries with low-medium poverty rates
Argentina c

0.8

1.1

1.4

1.8

2.2

2.7

3.5

4.8

12.2

0.4

0.8

1.1

1.4

1.7

2.1

2.6

3.4

4.8

13.1

-0.27

-0.15

-0.14

-0.11

-0.09

-0.06

-0.22

-0.33

-0.45

-0.62

-0.12

Δ Y/N (Δ O/N)

0.28

0.06

0.15

0.12

0.25

0.04

0.09

0.15

0.23

0.60

0.76

Δ Y/N (Δ YNL/N)

0.02

-0.02

-0.04

-0.03

-0.16

-0.01

0.05

0.07

0.10

0.02

0.25

Y/N 1991

2.17

0.2

0.4

0.6

0.8

1.0

1.3

1.8

2.4

3.6

9.5

Y/N 2005

2.68

0.2

0.5

0.8

1.0

1.4

1.8

2.3

3.2

4.7

11.0

Δ Y/N (Δ YL/O)

0.02

-0.06

-0.05

0.01

0.02

0.08

0.10

0.08

0.04

0.01

0.24

Δ Y/N (Δ O/N)

0.34

0.04

0.05

0.08

0.15

0.13

0.20

0.28

0.39

0.72

1.01

Δ Y/N (Δ YNL/N)

0.16

0.02

0.06

0.07

0.08

0.13

0.13

0.22

0.30

0.32

0.25

Y/N 1989

1.87

0.3

0.5

0.6

0.8

0.9

1.2

1.5

1.9

2.7

8.5

Y/N 2005

2.27

0.3

0.5

0.7

1.0

1.2

1.5

1.9

2.4

3.4

9.8

Δ Y/N (Δ YL/O)

0.03

-0.04

-0.04

-0.01

-0.03

0.01

-0.01

0.07

0.05

0.06

0.30

Δ Y/N (Δ O/N)

0.36

0.04

0.08

0.10

0.16

0.19

0.30

0.24

0.44

0.58

1.39

Δ Y/N (Δ YNL/N)
Brazil

0.5

3.14

Δ Y/N (Δ YL/O)

Mexico

3.10

Y/N 2005

Panama

Y/N 1990

0.01

0.04

0.05

0.04

0.06

0.05

0.04

0.10

0.03

0.07

-0.31

2.40

0.2

0.3

0.5

0.7

0.9

1.2

1.7

2.4

4.0

12.1

2.95

0.2

0.5

0.7

1.0

1.3

1.6

2.1

2.8

4.4

15.0

Δ Y/N (Δ YL/O)

-0.23

-0.01

0.04

0.05

0.04

0.04

-0.03

-0.11

-0.25

-0.45

-1.22

Δ Y/N (Δ O/N)

0.22

0.04

0.04

0.07

0.09

0.09

0.17

0.09

0.35

0.36

0.53

Δ Y/N (Δ YNL/N)
Venezuela
(Bolivarian
Republic of)

Y/N 1990
Y/N 2005

0.56

0.02

0.07

0.09

0.13

0.23

0.27

0.47

0.33

0.52

3.51

Y/N 1990

1.80

0.3

0.5

0.7

0.9

1.1

1.4

1.7

2.2

3.0

6.5

Y/N 2005

1.97

0.2

0.5

0.7

1.0

1.2

1.5

1.9

2.4

3.2

7.2

-0.13

-0.06

-0.07

-0.08

-0.11

-0.11

-0.10

-0.07

-0.08

-0.07

0.11

Δ Y/N (Δ YL/O)
Δ Y/N (Δ O/N)
Δ Y/N (Δ YNL/N)

0.34

0.06

0.12

0.19

0.22

0.28

0.30

0.28

0.31

0.32

0.60

-0.03

-0.09

-0.06

-0.07

-0.06

-0.06

-0.06

-0.04

-0.03

0.02

0.04

4.3

Countries with medium-high poverty rates
Ecuador b

Y/N 1990

1.19

0.2

0.4

0.5

0.6

0.7

0.9

1.1

1.4

1.9

Y/N 2005

1.83

0.2

0.5

0.6

0.8

1.0

1.3

1.6

2.1

2.9

7.4

Δ Y/N (Δ YL/O)

0.27

-0.01

-0.02

0.01

0.04

0.06

0.12

0.16

0.30

0.48

1.86

Δ Y/N (Δ O/N)

0.24

0.04

0.08

0.11

0.11

0.15

0.18

0.24

0.20

0.36

0.63

Δ Y/N (Δ YNL/N)

0.13

0.03

0.02

0.04

0.05

0.04

0.08

0.11

0.19

0.22

0.64

72

Economic Commission for Latin America and the Caribbean (ECLAC)

Table I.6 (concluded)
Latin America (16 countries): per capita family income and breakdown of its variation by changes in labour
income per employed person, the overall employment rate and per capita non-labour income (in multiples
of the poverty line), by deciles of income distribution, 1989-1995 and 2001-2005 a
Country

Decile
I

Decile
II

Decile
III

Decile
IV

Decile
V

Decile
VI

Decile
VII

Decile
VIII

Decile
IX

Decile
X

Y/N 1995

1.42

0.1

0.3

0.5

0.7

0.8

1.0

1.3

1.6

2.3

5.6

1.55

0.2

0.4

0.6

0.7

0.9

1.1

1.4

1.9

2.6

5.7

Δ Y/N (Δ YL/O)

0.00

-0.12

-0.03

0.01

0.02

0.03

0.04

0.09

0.11

0.09

-0.04

Δ Y/N (Δ O/N)

0.06

0.01

0.04

0.02

0.05

0.06

0.01

0.03

0.09

0.05

0.00

Δ Y/N (Δ YNL/N)

0.07

0.05

0.03

0.05

0.01

0.00

0.07

0.06

0.06

0.20

0.12

Y/N 1991

1.52

0.2

0.4

0.5

0.6

0.8

1.0

1.2

1.6

2.3

6.6

Y/N 2005

2.08

0.2

0.4

0.6

0.8

0.9

1.2

1.5

2.0

3.1

10.2

Δ Y/N (Δ YL/O)

0.10

0.01

-0.01

-0.01

0.01

0.03

0.06

0.06

0.12

0.26

0.55

Δ Y/N (Δ O/N)

Colombia

Total

Y/N 2004

El Salvador

Per capita
income

0.06

-0.02

0.01

0.03

0.04

0.06

0.06

0.12

0.12

0.13

-0.12

Δ Y/N (Δ YNL/N)

0.03

0.04

0.05

0.05

0.05

0.07

0.10

0.16

0.37

3.18

1.69

0.3

0.5

0.7

0.9

1.1

1.2

1.5

2.0

2.8

5.9

1.67

0.3

0.5

0.6

0.8

0.9

1.2

1.4

1.8

2.6

6.6

Δ Y/N (Δ YL/O)

-0.21

-0.11

-0.13

-0.19

-0.13

-0.18

-0.27

-0.27

-0.42

-0.50

-0.14

Δ Y/N (Δ O/N)

0.09

0.02

0.03

0.05

-0.04

-0.02

0.11

0.08

0.10

0.11

0.62

Δ Y/N (Δ YNL/N)

0.10

0.04

0.05

0.07

0.06

0.08

0.09

0.08

0.13

0.14

0.24

Y/N 1989

1.18

0.1

0.2

0.3

0.4

0.5

0.7

0.9

1.2

1.8

5.7

Y/N 2002

1.47

0.2

0.3

0.5

0.6

0.7

0.9

1.2

1.6

2.4

6.3

Δ Y/N (Δ YL/O)

0.00

0.03

0.02

-0.02

-0.03

-0.04

-0.08

0.12

0.06

0.14

0.51

Δ Y/N (Δ O/N)

0.24

0.03

0.05

0.12

0.13

0.13

0.15

0.16

0.30

0.32

0.24

Δ Y/N (Δ YNL/N)

0.05

0.03

0.04

0.04

0.03

0.06

0.16

0.06

0.08

0.15

-0.08

Y/N 1989

1.67

0.1

0.4

0.5

0.7

0.9

1.1

1.4

1.9

2.8

7.0

Y/N 2004

1.71

0.3

0.5

0.6

0.7

0.9

1.1

1.3

1.8

2.7

7.3

Δ Y/N (Δ YL/O)

-0.38

0.01

-0.07

-0.10

-0.10

-0.19

-0.24

-0.35

-0.45

-0.58

-1.10

Δ Y/N (Δ O/N)

0.21

0.13

0.11

0.10

0.09

0.14

0.14

0.15

0.10

0.20

0.27

Δ Y/N (Δ YNL/N)

0.21

0.00

0.03

0.05

0.06

0.07

0.08

0.16

0.26

0.31

1.13

Y/N 1993

0.99

0.0

0.2

0.3

0.4

0.5

0.6

0.8

1.1

1.6

4.5

Y/N 2001

Guatemala e

0.41

Y/N 1990
Y/N 2005

Paraguay d

1.16

0.1

0.2

0.3

0.4

0.6

0.7

0.9

1.2

1.8

5.5

-0.06

0.00

0.00

0.00

-0.01

-0.03

-0.11

-0.07

-0.15

-0.18

0.59

0.24

0.03

0.05

0.06

0.10

0.11

0.20

0.18

0.25

0.32

0.47

-0.01

0.00

0.00

0.00

0.00

0.01

0.00

-0.02

0.00

0.02

-0.10
4.4

Countries with high poverty rates
Bolivia f

Nicaragua

Δ Y/N (Δ YL/O)
Δ Y/N (Δ O/N)
Δ Y/N (Δ YNL/N)
Honduras

Y/N 1990

0.87

0.1

0.1

0.2

0.3

0.4

0.5

0.6

0.9

1.4

Y/N 2003

0.95

0.1

0.2

0.2

0.3

0.4

0.6

0.8

1.1

1.6

4.4

Δ Y/N (Δ YL/O)

-0.13

0.00

-0.02

-0.02

-0.02

-0.05

-0.03

-0.05

-0.10

-0.11

-0.68

Δ Y/N (Δ O/N)

0.09

0.00

0.02

0.03

0.06

0.06

0.06

0.06

0.10

0.14

0.07

Δ Y/N (Δ YNL/N)

0.13

0.02

0.02

0.03

0.02

0.06

0.06

0.13

0.19

0.18

0.52

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from household surveys conducted in the relevant
countries.
Note: The figures in bold type and highlighted in grey indicate deciles whose per capita income is below the poverty line (1.0). The countries are
ordered by poverty level in the period 2001-2005 from lowest to highest proportion of poor people.
aThe components of the variation of per capita income due to changes in labour income per employed person [Δ Y/N(Δ YL/O)], changes in the overall
employment rate [Δ Y/N(Δ O/N)] and changes in per capita non-labour income [Δ Y/N(Δ YNL/N)] (in multiples of the poverty line) were calculated using
formula 3 of box I.1.
bUrban areas.
cGreater Buenos Aires.
dMetropolitan area of Asuncion.
eIn the case of Guatemala, the number of deciles below the poverty line is higher than the number obtained on the basis of the poverty levels published
in box I.4 because those levels did not take into account the population aged under 10 years in 1989 and under 7 years in 2002, and adjustments
therefore had to be made.
f Cochabamba, El Alto, La Paz, Oruro, Potosí, Santa Cruz, Tarija and Trinidad.

Social Panorama of Latin America • 2007

73

Table I.7
LATIN AMERICA (16 COUNTRIES): COUNTRY TYPOLOGY BASED ON TRENDS IN THE OVERALL EMPLOYMENT RATE, LABOUR INCOME PER
EMPLOYED PERSON AND NON-LABOUR INCOME IN POPULATION DECILES THAT INCLUDE POOR HOUSEHOLDS, 1990-2005a
Poverty trends (annual average) /
countries b

Poverty
–start of
period c

Overall employment
rate (O/N)

Labour income
per employed
person (YL/O)

Per capita
non-labour
income(YNL/N)

Poverty
–end of
period c

Sharp reduction (variation of more than -1.5% per year)
Chile

38.3

++

++

++

18.6

Ecuador

61.8

++

+

+

45.1

Brazil

47.4

++

+

++

36.2

Panama

42.8

++

–

+

32.7

Mexico

47.4

++

–

+

35.5

Slight reduction (variation of between1.5% and 0.5% per year)
El Salvador

54.0

+

–

+

47.5

Costa Rica

26.2

+

+–

+

21.1

Colombia

55.6

+

=

+

46.8

Guatemala

70.3

++

=

++

58.4

Nicaragua

73.6
80.5

––
––

=
++

69.3

Honduras

++
++
++
++
+
=

––
––
–
–

–
+
=
+

37.1

+–

––

+

47.7

74.6

No progress (variation of between 0.5% and 0.5% per year)
Venezuela (Bolivarian Republic of)

40.0

Bolivia

52.1

Argentina

21.1

Uruguay

17.8

51.6
22.6
19.1

Increase (variation of more than 0.5% per year)
Paraguay

42.2

Note:
++: Significant progress
+: Progress
= / +-: No change/ progress and setbacks
-: Setbacks
– –: Significant setbacks
Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of household surveys conducted in the relevant countries.
aBecause of the different years in which surveys are conducted, the values shown for poverty at the beginning and end of the period do not cover the years
1990 and 2005 for all of the countries. The data for Chile and Honduras correspond to 1990-2003, the data for Panama and Colombia to 1991-2005, for
Mexico to 1989-2005, for El Salvador to 1995-2004, for Guatemala to 1989-2002, for Nicaragua to 1993-2001 and for Bolivia to 1989-2004.
bThe annual rate of reduction in total poverty for each country, which was used to classify the countries, was estimated using the following formula:
ARR = ((FP-IP) / PI) *100)/y, where ARR = annual rate of reduction in poverty, FP = final poverty percentage, IP = initial poverty percentage, and y =
number of years contained in the period.
cThese percentages may not match those shown in table I.4 because of changes in the treatment of the domestic service category. In the case of
Guatemala, it was necessary to adjust the way in which the data were processed to compensate for the absence of measurements covering children
under 10 years of age in 1989 and under 7 years of age in 2002.

Table I.7 reveals a wide variety of situations. Three salient
points need to be made in this regard. First, the commitment
undertaken to achieve the Millennium Development Goals
coincides with a period in which the proportion of the total
population represented by economically active household
members has been on the rise. The most notable exceptions
in this respect are Uruguay (urban areas) and to a lesser
extent, Paraguay (metropolitan area of Asunción). Second,
throughout this entire period, no increase has been seen
in the labour incomes of employed persons from the
15

poorest households except in Chile, Brazil and Ecuador
(urban areas). Third, there has been a fairly widespread
increase in non-labour income among poor sectors of the
population. An analysis of the reasons for this increase is
beyond the scope of this report, however, since without a
more detailed breakdown of the wide variety of income
sources included in this category, it is impossible to draw
conclusions about the relative importance of remittances,
State support programmes for families and other sources
of income, such as pensions and retirement funds.15

In recent years, it has become customary to make State transfers to low-income families conditional upon changes in behaviour. The idea
is to help families increase their productivity either by investing more in human capital, helping them spend their time more efficiently or
increasing their access to productive assets (CEPAL 2006c). For an examination of the effect of remittances on poverty and inequality, see
Social Panorama of Latin America, 2005 (ECLAC 2006a).

Figure I.9
DETERMINANTS OF CHANGES IN POVERTY LEVELS,
DECILES I-IX
(a) Countries recording a significant drop in poverty and
increase in labour productivity (Brazil, Chile and Ecuador,
simple averages), 1990-2005

0.9
Per capita income distribution, by decile, 2003-2005

0.8
0.7

Per capita income distribution, by decile, 1990

0.6
0.5

0.2

3

Poor population
(1990)

Poor population
(2003-2005)

0.4
0.3

4

2

Poverty line

1

0.1
0.0

I

II

III

IV

V

VI

VII

VIII

IX

Per capita income
(in multiples of the poverty line)

5

1.0

Variation in per capita income
(in multiples of the poverty line)

0

Income deciles
Variation in per capita income due to changes in overall employment rate
(between 1990 and 2003-2005)
Variation in per capita income due to changes in overall employment rate
(between 1990 and 2003-2005)
Variation in per capita income due to changes in overall employment rate
(between 1990 and 2003-2005)
Per capita income - 1990
Per capita income - 2003-2005

(b) Countries recording no progress or increases in poverty
(Argentina, Bolivarian Republic of Venezuela, Bolivia, Paraguay
and Uruguay, simple averages), 1989-1990 and 2004-2005

3

0,5
0,4

Per capita income distribution, by decile, 1989-1990

0,3

Per capita income distribution, by decile, 2004-2005
2

0,2
0,1
0,0
-0,1
-0,2
-0,3
-0,4

I

II

III

IV

V

VI

VII

VIII

IX
1

Poverty line
Income deciles
Poor population Poor population
(2004-2005)
(1989-1990)

Per capita income
(in multiples of the poverty line)

Only 5 of the 16 countries that were analysed have
reduced poverty significantly since the early 1990s:
the three countries where labour income per employed
person has risen (Chile, Brazil, Ecuador), and Mexico
and Panama, where the proportion of employed persons
climbed considerably. The other countries have made
little or no progress. The main limitation in these cases
has been the labour market’s poor performance. In
the countries that have witnessed sharp reductions in
poverty, the main underlying factors have been changes
in household composition and in household members’
participation in the labour market. Although this trend
has been widespread in all the other countries as well, it
has not been reinforced by sufficiently large increases in
productivity or in transfers to households.
A comparison of the countries in which poverty
has decreased the most and the least underscores the
importance of behavioural patterns relating to the labour
market (see figure  I.9). For example, in Brazil, Chile
and Ecuador (urban areas), the effect of the increase in
the ratio of employed persons to the total population
(dark blue bars in figure I.9-A) has been bolstered by an
increase in labour income per employed person (light blue
bars). This combination signals the presence of a highly
dynamic labour market. In addition, there has also been
an increase in non-labour income (orange bars). All this
helped increase household incomes and lower poverty
rates. This progress explains why the per capita income
distribution curve for 2003-2005 (grey line) crosses the
(red) poverty line among the lower deciles of income
distribution, to the left of the per capita income distribution
curve for 1990 (black line). In Argentina (Greater Buenos
Aires), Bolivia, Paraguay (Asunción metropolitan area),
Uruguay (urban areas) and the Bolivarian Republic of
Venezuela, in contrast, labour income per employed
person declined in poor sectors of the population, and this
decrease was not offset by any increase in the employment
rate or non-labour income. Consequently, they made no
progress in reducing poverty.
The data presented in figure I.9 reveals three other
important facts that should be taken into consideration
in policy design. First, the more similar the family
structure among the deciles and hence the better the
income distribution among the families classified into
those deciles (shown in the figure by less steep curves),
the greater poverty reduction will be when income per
employed person rises or State transfers increase.
Second, around one third of the population of the
countries included in figure I.9, according to per capita
income figures, lived below the poverty line around
2005. An even larger number of persons were in a highly
vulnerable situation at that time, however, with an income
that placed them just above the poverty line but in no

Economic Commission for Latin America and the Caribbean (ECLAC)

Variation in per capita income
(in multiples of the poverty line)

74

0

Variation in per capita income due to changes in labour income
per employee (between 1989-1990 and 2004-2005)
Variation in per capita income due to changes in overall
employment rate (between 1989-1990 and 2004-2005)
Variation in per capita income due to changes in per capita
non-labour income (between 1989-1990 and 2004-2005)
Per capita income 1989-1990
Per capita income 2004-2005

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of household surveys conducted in the relevant
countries.

Social Panorama of Latin America • 2007

position to handle any crisis situation.16 This applies to
the other countries in the region too: in no country in Latin
America is the average per capita income of the fifth decile
at least twice that of the poverty line (see table I.6).
Third, in terms of the poverty line, the variation of labour
income per employed person mirrors the pattern for income

3. 

distribution: it is substantially greater in the higher income
deciles. This reflects the fact that the increase in productivity
originates from formal enterprise, benefits workers in the
formal sector most and is proportionally distributed among
the lower income levels. The effects of the increase are not
redistributive; they trickle down the salary scale slowly.

Public policy challenges

The evidence shows that quite a few countries in the
region are on track to reach the first target associated
with the first Millennium Development Goal, thanks
in large part to their success in capitalizing upon the
demographic dividend. Declining dependency ratios
have been complemented by rising employment levels
among the poorest households. Improvements in labour
income and job opportunities for the poorest sectors of
the population, however, are still inadequate.
Policymakers in the region need to remember that the
advantages afforded by the demographic dividend will
not last forever, in fact, they will ultimately be reversed.
In order to continue advancing with poverty reduction,
therefore, countries will have to devise policies that make
it possible to reconcile care work in the home with gainful
employment and boost productivity in the occupations
held by the poorest members of the population. Also, if
these do not work, they will have to ensure that social
spending targets the needs of the most vulnerable segments.
Measures that aim to help women, especially in poor
families, reconcile the care of the dependent members of
the household with remunerated work so that more of them
can become economically active need to be implemented

16

75

and elevated to the status of public policy. Women should
also be able to fully enjoy their reproductive rights so
that they can decide on the size of their families and
the dynamics of the family life cycle. At the same time,
comprehensive and targeted labour training policies and
initiatives for reinsertion into the labour force need to
be developed for the active population at the lower end
of the income scale so as to improve their options in the
labour market.
These are not new requirements within the context
of the countries’ socio-economic development strategies.
The steady aging of the population will, however, make
them increasingly urgent as the rise in per capita income
ceases to benefit from demographic trends after the
“demographic dividend” peaks.
This challenge is not arising in a vacuum. Solutions
can and need to be sought. Public policy must be used to
bring about major changes in three areas: the response to
the aging of the population and the declining birth rate in
the countries of region; the performance of the countries’
economic agents (such as raising productivity in a more
competitive international context) and the influence of the
political economy on the role and size of the State.

In figure I.9, the slope of the per capita income curve is steeper after decile VIII, which implies that 70% of the population are in a highly
vulnerable situation as far as subsistence is concerned.

76

Economic Commission for Latin America and the Caribbean (ECLAC)

D. Poverty and residential segregation in urban areas
Spatial segregation is polarizing Latin America’s largest cities. The formation of poor ghettos
at one extreme and gated middle- and upper-income residential areas at the other has serious
implications for social cohesion and poverty in the region. Residential segregation reduces
and interferes with the spheres of activity that provide opportunities for people to learn to live
with others under circumstances of inequality. This poses a threat to social cohesion and blocks
access for those from the poorest neighbourhoods, who are also the people most affected by
the crises in the labour market, to employment and education. This in turn perpetuates poverty.
Public policymakers therefore need to pay more attention to changes in residential segregation
in urban areas, exert greater control over the determinants of these processes, and undertake a
thorough review of urban land management and social housing programmes.
A series of studies published over the last decade provide
new insights into poverty in urban areas. These studies
pay more attention than previous works to the reshaping
at the local level of the framework that affords the
opportunities for upward mobility and to the influence that
the community environment has on people’s perceptions.
The situation of the poor is thus interpreted in light of
the immediate social context and the relationships people
form with the community. The studies emphasize the
probable negative consequences of urban residential
segregation, such as the erosion of opportunities for the
most vulnerable members of the population to improve
their situation and the widening of the gap between the
poor and the rest of society.
This approach is inspired by the pioneering work of
James J. Wilson, in Chicago, who suggested that changes
in the labour and housing markets were resulting in the
increased geographic segregation of low-income (as well
as middle- and upper-income) urban households and that
the growing isolation of the poor from the main social
and economic realms of the large cities was hardening
poverty and its inter-generational reproduction.17 With
some differences, other authors adopted this more
structuralist approach to analyse the dynamics of urban
poverty (for example, Borja and Castells, 1997) and began

17

For further detail, see Wilson (1987).

to draw attention to a number of worrying issues. These
are summed up below.
The first warning was that the neighbourhoods with
the highest levels of privation -which is where unskilled
workers, who rarely have a steady job and only precarious
ties with the world of employment, tend to live- were being
constantly bombarded by the mass media with images of
abundance and messages encouraging them to consume.
This confluence could trigger the most disruptive correlates
of poverty, which would in turn upset social relations in
cities and weaken the opportunities for cooperation and
solidarity between citizens with different socio-economic
backgrounds.
A second source of concern, which is closely linked
to the first, is the rapid disappearance of one of the virtues
that has characterized cities throughout history: their
capacity to provide spaces in which people can learn to
live with others under circumstances of inequality. The
opportunities for this are fading under the increasing
territorial polarisation of urban society (the final expression
of which is the formation of poor ghettoes at one end
of the spectrum and of gated middle- and upper-class
neighbourhoods at the other) and the fragmentation that
is taking place with the segregation of services (such as
primary education), which are basically organized along

Social Panorama of Latin America • 2007

territorial lines. Both processes deepen the social divide
and reduce the opportunities for fostering cooperation
and building consensus-based norms and mechanisms
for dispute settlement.
Another cause for concern is the suspicion that the
residential segregation underway in urban areas is somehow
rooted in and fuelled by the workings of the new modes
of capitalism that are emerging with globalization. It is to
be feared that, if this proves to be the case, the increased
physical separation of rich and poor into different areas
and the negative influence this has on social harmony
in cities will be part of a long-term trend rather than a
momentary problem.
Finally, concerns have been voiced about the fate of
the poor at the micro-social level. Residential segregation
runs the risk of reproducing poverty from one generation
to the next. Regardless of individual and family traits,
living in neighbourhoods with high concentrations of
low-income households seems to affect both the ability
of adult residents to use the conventional means cities
offer for improving living standards and the possibility
of the next generation escaping poverty.
All these concerns were incorporated into the studies of
what is now termed “urban residential segregation”. These
studies aim to do more than simply describe cities whose
differences have become apparent in concrete forms of social
and territorial organization. They propound the idea that
the effects of urban residential segregation are increasingly
negative and that the discrepancies between social groups
tend to mutually reinforce one another and hence become
deeply entrenched, which fosters the polarisation of society
and the “hardening” and widening of the social divide.

1. 

This approach is used in the description of the situation
of Latin America presented in this section. Given the
impracticality of addressing all the sources of concern
mentioned above, only those most closely related to the
poverty issues usually examined in Social Panorama of
Latin America are analysed here. In the 2004 edition, it
was suggested that poverty is closely linked to educational
opportunities, job opportunities and reproductive patterns.
The examination of the influence of the social composition
of neighbourhoods therefore focuses on the evidence of
its effects on these three factors.
It should be pointed out that although this approach
is highly promising for furthering understanding of the
phenomena related to urban poverty, empirical progress
has been slow in Latin America, and the approach is
only just beginning to be developed. This is partly
because academic and political interest in the topic is
only quite recent and partly due to the complexity of the
methodological challenges involved in the corresponding
research. The difficulty mainly lies in constructing models
that incorporate the mechanisms at work between the
social structure of the immediate environment and people’s
behaviour and in compiling the data needed to test the
resulting hypotheses.
One of the purposes of this section is to offer a
summary of the empirical knowledge in the region on the
influence of the neighbourhood on residents’ behaviour.
This will hopefully stimulate a debate on the extent to
which it would be justifiable for public policymakers to
incorporate measures into their social agendas to try to
halt or reverse the trend towards residential segregation
in urban areas.

Employment

People who have problems finding a job also have
problems paying the rent, putting up down payments
for housing contracts and obtaining loans. It is therefore
no surprise that the neighbourhoods with the highest
unemployment rates are situated on the cheapest plots
in town or wherever there is land for the taking. The fact
that the problem of unemployment is largely concentrated
in the neighbourhoods where low-skilled workers live
can be seen simply as an aggregated result of the crisis
in the labour market.

18

77

However, the relationship between people’s position
in the labour and housing markets depends on the action
of the public sector. The state can help to weaken the link
between labour and housing markets depends on the action
of the public sector. The state can help to weaken the link
between labour and housing disadvantages through the
creation of rental subsidies, the extension of soft loans
for home buyers, the location of social housing projects
and changes in the public transport system (Muster and
Ostendorf, 1998).18

Social housing policies can also promote the residential segregation of the poorest members of society. The policies implemented in Chile at
the beginning of the 1980s, through which supply subsidies were replaced with a money certificates scheme whereby low-income families
could purchase housing constructed by private enterprises, is an example of this. For more details, see Sabatini and Arenas (2000).

78

Economic Commission for Latin America and the Caribbean (ECLAC)

The data presented below suggest a slightly more
complex relationship between employment and the social
composition of the neighbourhood (Kaztman and Retamoso,
2005). Figures I.10, I.11 and I.12 show that even when

the skills level is controlled, the probabilities of a person
entering the labour market and of finding work in the
formal sector of the economy are systematically linked
to the social make-up of his or her place of residence.

Figure I.10
URUGUAY (MONTEVIDEO): OPEN UNEMPLOYMENT RATE, BY
AVERAGE EDUCATIONAL LEVEL OF THE CORRESPONDING
CENSUS DISTRICT, BY AGE AND YEARS OF SCHOOLING, 1996
(Percentages)

Figure I.11
URUGUAY (MONTEVIDEO): OWN-ACCOUNT WORKERS, BY
AVERAGE EDUCATIONAL LEVEL OF THE CORRESPONDING
CENSUS DISTRICT AND YEARS OF SCHOOLING, 1996
(As a percentage of the population)

(a) 15 to 29 years of age
16.2

Total

17.1

9 to 10 years of
schooling

20.3

5

10

15

25

12 years or more
of schooling

7.7

Complete primary
education
Incomplete primary
education

8.5
0

2

4

6

7.4

8

12 years or more
of schooling

13.1

8.4

14

Census segment with low educational level
Census segment with high educational level

16

13.4
7.5

18.8

7 to 8 years of
schooling

14.3

6 years of
schooling
Less than 6
years of
schooling

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of Uruguay’s 1996 population and
housing census.
Note: Data for 1996 were used because the relevant tabulations for
2004 census data are not available.
In Uruguay, the primary education cycle covers a six-year period;
secondary education is divided into two three-year cycles.

11.3

4.9

9 to 10 years of
schooling

14.1
12

30

27.6

3.6

11 years of
schooling

13.4

10

25

Census segment with high educational level

Total
10.9
8.0

7 to 8 years of
schooling

24.8

20

Census segment with low educational level

10.1
6.8

9 to 10 years of
schooling

15

Figure I.12
URUGUAY (MONTEVIDEO): PRIVATE-SECTOR EMPLOYEES
WITHOUT HEALTH COVERAGE OR ACCESS TO THE
PUBLIC HEALTH SERVICE, BY YEARS OF SCHOOLING AND
EDUCATIONAL CONTEXT OF THE CENSUS DISTRICT, 1996
(As a percentage of the population)

12.4

6.0

11 years of
schooling

10

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of Uruguay’s 1996 population and housing
census.
Note: Own-account workers excludes company executives, professionals
and technicians.

(b) 30 years of age and over

3.3

5

30

Census segment with high educational level

5.4

18.9
20.5

27.0

Census segment with low educational level

Total

16.9

0

20

15.5

Less than 6
years of
schooling

25.3

19.7

Incomplete primary
education

13.5
12.8

6 years of
schooling

23.5
21.6

Complete primary
education

10.8
8.9

7 to 8 years of
schooling

19.0

7 to 8 years of
schooling

0

8.5

9 to 10 years of
schooling

18.2

17

6.5

11 years of
schooling

15.5

11 years of
schooling

3.0

12 years or more
of schooling

22.7

14.6
14.8

12 years or more
of schooling

7.1

Total

27.5
18.6

34.6

18.3
0

5

10

15

20

37.5
25

30

35

Census segment with low educational level
Census segment with high educational level

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of Uruguay’s 1996 population and housing
census.
Note: According to current legislation, private-sector employees have the
right to medical attention in the country’s collective medical assistance
institutions (IAMC). The number of people without this possibility and
without medical coverage or access to medical attention in the Ministry
of Public Health probably reflects the number of employed persons not
registered with the national social security scheme.

40

Social Panorama of Latin America • 2007

A look at the data presented in figures I.10, I.11 and
I.12 raises the question of why people who live in certain
neighbourhoods and have a certain amount of schooling
(for example, 11 years of formal education in the case
of Montevideo) have completely different opportunities
when it comes to finding work and the quality of the
jobs they obtain than other people who have attained
the same level of education but live in neighbourhoods
with a different social make-up. Two approaches, each
emphasising different causes, will be used to answer
this question.
The first approach is based on the classic theory of
human capital and maintains that the number and type of
employment problems a neighbourhood faces will depend
on the individual characteristics of its residents. People
with similar levels of education who live in different
neighbourhoods have different employment rates because
people always have individual traits that can determine
their success in the labour market and, consequently, the
geographical location of their place of residence.
The second approach, which underscores the importance
of structural factors of behaviour, tends to interpret
employment differences in terms of the causality that
operates within neighbourhoods. This does not so much
attempt to override the other approach as to complement
it by examining how the influence of the neighbourhood
can steadily weaken its residents’ ties with the labour
market. The characteristics of neighbourhoods that play
a role in this process are examined below.
(a)  Distribution of job opportunities in urban areas:
distance between the place of residence and the
place of employment
It has been claimed that the further away people live,
the more problems they will have finding and keeping
a job, probably due to the time and money that need to
be spent on travelling to and from work and the reduced
opportunities there are to access information and make
contacts with people in the labour market. The experience
of working-class neighbourhoods in some Latin American
cities that used to be near the shipyards, meatpacking
plants, factories, railroad workshops and other sites would
seem to bear this argument out.
Since the 1970s there has been a substantial reduction
in the number of people working in industry in Latin
America and a steady increase in the skills levels required
in factory work. Unskilled workers have therefore been
forced to find work in the personal services sector. Unlike
factories, however, which (like the homes of unskilled
workers) tend to be located on the cheapest plots of land
in town, the middle class homes in which service jobs

79

can be found are situated in the more upmarket areas. The
distance between home and the workplace has therefore
become a far more important issue than it was in the past
for low-skilled workers.
How much of an issue the commute between places of
residence and employment is depends on the layout of the
city in question. In Rio de Janeiro, for example, the location
of the favelas (shanty towns) in different parts of the city
enables a significant portion of the poorer population to
live near areas with a high demand for personal services.
In Buenos Aires and Montevideo, on the other hand, the
distance between home and the workplace is far greater
because most poor people’s homes are on the outskirts
of the city.
Part of the problem posed by the distance between
home and the workplace for first-time job seekers is the
slackness of the economies of poor neighbourhoods. The
more stable and protected workers there are in an area,
the greater the flow of money and the more dynamic the
exchange of goods and services, and vice versa. The fact
that the employment rate of people with similar levels of
education varies according to the social make-up of the
neighbourhood in which they live can be partially attributed
to the differences they encounter in job opportunities at
the local level.
A study conducted in São Paulo, which compiled
data on companies in different types of neighbourhoods
(Gomes and Amitrano, 2004), sheds some light on
the subject. As shown in table I.8, average wages
vary considerably according to the social make-up of
the district in which the company is located. These
differences are still significant even when adjustments
are made for skills levels, company size and the
economic sector in which the companies operate. The
results of the study seem to indicate that people from
poor neighbourhoods end up in low-paying jobs not
just because of the distance between where the work
is and their place of residence, but because of other
factors as well: working conditions in the areas they
live in are worse than in more upmarket parts of town;
employers discriminate against workers from the more
stigmatized neighbourhoods and there is a surplus of
unskilled labour in poor neighbourhoods.
The differences in job opportunities suggest that
living near the wealthier neighbourhoods represents an
important advantage for low-skilled workers. It is therefore
not surprising that in Santiago, Montevideo, Buenos
Aires and Río de Janeiro, among other cities, pockets of
poverty have sprung up around middle and upper class
neighbourhoods as people with limited resources try to
live close to where they are most likely to find work
(Brain and Sabatini, 2007).

80

Economic Commission for Latin America and the Caribbean (ECLAC)

Table I.8
BRAZIL (METROPOLITAN REGION OF SÃO PAULO): AVERAGE WAGES OF WORKERS BY EDUCATIONAL LEVEL,
ECONOMIC SECTOR AND THE SOCIAL COMPOSITION OF THE DISTRICT IN WHICH THE COMPANY IS LOCATED, 2000
(Values in minimum wages of 2000)
Characteristics of establishments

Social composition of the district
Poor

Middle class

Total
Wealthy

Level of education of employees
Incomplete primary

3.64

3.93

4.29

3.86

Complete primary

3.73

4.10

4.67

4.02

Secondary

4.72

5.32

6.49

5.23

Incomplete tertiary

7.32

8.16

10.03

8.09

10.71

12.54

16.19

12.29

Complete tertiary
Economic sector
Industry

4.65

5.36

7.89

5.40

Services

4.06

5.17

7.43

5.02

Commerce

3.40

3.92

5.48

3.90

Civil engineering

3.46

3.80

4.94

3.84

Public administration

6.39

8.81

13.48

10.29

Average wage (all areas)

4.71

5.36

7.25

5.35

Source: S. Gomes and C. Amitrano, “Local de moradía na metropole e vulnerabilidade ao emprego e desemprego”, Segregaçao, pobreza e desigualdades
sociais, E. Marques and Haroldo Torres (comps.), São Paulo, Editora SENAC, 2004.

(b) Stigmas
The increased separation of poor neighbourhoods, in
both physical and social terms, from the rest of the city
is altering how the different social classes view one
another. Two processes are at work in this. On the one
hand, as opportunities for mixing socially with other
classes diminish, the members of the upper classes of
urban society lose their ability to “put themselves in the
shoes of others” (empathize), which means that they
are no longer moved by the inequality and misery they
see in the streets. On the other hand, the extent of the
privation in poor neighbourhoods creates cracks in the
social structure which turn into breeding grounds for
marginal subcultures. The resulting disorder harms the
public image of the neighbourhood. Neighbourhoods
whose patterns of behaviour are seen by the rest of urban
society to be strange or dangerous are soon labelled as
“bad parts of town”.
The combination of these two processes leads to the
creation of stigmas. Negative images can seriously affect
the collective identification of people who, exposed to
similar experiences of discrimination, discover they share
a painful set of problems and fate with their neighbours.19
Most importantly for the purposes of this study, the negative
images of certain areas of a city are taken into account
by employers when hiring unskilled labour.

19
20

(c) Social capital: job information and contacts opportunities that depend on the social composition
of each neighbourhood
People whose neighbours have only fragile links with
the labour market interact less with working people and,
consequently, have limited access to information and
contacts that would allow them to obtain a job. The negative
synergies in these situations affect people’s attitudes to
work in different ways: first, because the neighbourhood
network turns out to be a useless resource as far as finding
a job is concerned; second, because the routines and
disciplines of the world of work no longer frame the social
and everyday life of the neighbourhood (in addition to
lowering the tone of life in the community, this makes it
more difficult to uphold the belief that steady work is the
best way to escape poverty); and third, because people
cannot, in these kinds of neighbourhoods, learn the social
skills that would help them obtain and keep a job.
(d) Insecurity
Studies conducted in the neighbourhoods with the most
unemployment reveal that these are also the neighbourhoods
with the worst public safety and the highest levels of
mistrust.20 Fear of assault and robbery and of exposing
their children to dangerous and undesirable influences

For more details on the perception of being the victim of discrimination among the poor in Latin America, see the following section on psychosocial divides.
The next section presents some empirical background information on interpersonal mistrust in the region’s countries.

Social Panorama of Latin America • 2007

stops households from mobilizing their resources. Instead
of sending out their working-age members to find jobs
and bring home money, families are forced to assign
them to the protection of other family members and the
safekeeping of the home and its contents. The lack of
security can also make it unsafe to walk through parts of
the neighbourhood at certain times of day. This affects
the hours people can work and consequently the jobs they
can accept (Suárez, 2004; Zaffaroni, 1999).
(e) Socialization
For children and teenagers, the neighbourhood is where they
develop their social skills. How well a neighbourhood’s
young residents are integrated into society depends on the
proportion of examples they witness of the relationship
between work and success in life. It also depends, however,

2. 

on the effectiveness of local standard patterns of behaviour
and on the extent to which the streets are controlled by the
marginal subcultures that reject the conventional means
of improving one’s situation (education and work) and
encourage behaviour that is totally incompatible with
making progress by either route. There is a running battle
in the poorest neighbourhoods between one option and
the other, between those who try not to become alienated
from society and those who, disheartened, drop out to
explore less legitimate means of making ends meet.
Neighbourhoods where people only have weak ties with
the world of work cannot offer children and adolescents
suitable models for social integration. Nor can they
effectively counteract the messages, images and modes
of behaviour promoted by the subcultures that justify and
reinforce young people’s reluctance to utilize education
and work as ways of escaping poverty.

Education

The formation of human capital is also affected by the
type of neighbourhood in which people grow up before
they venture into the labour market. The studies described
below, which were conducted in large Latin American cities,
examined the links between the place of residence and the
educational level attained by children and adolescents. In
four of these studies (those carried out in Rio de Janeiro,
Buenos Aires, Montevideo and Santiago), educational levels
were measured by the academic performance tests given
to students in the fourth or sixth grade of primary school.
In Mexico, the study focused on the school dropout rate
among students in their third year of secondary school,
and in Sao Paulo, the study examined the indirect effects
of the neighbourhood on learning in light of the quality
of the teachers working in the neighbourhood.
The results of the research in Buenos Aires show that
children living in low-income neighbourhoods scored lower
on mathematics and language tests than other children with
similar individual, family and educational backgrounds
(Groissman and Suarez, 2007). Overall the test scores
varied by 21 points in the city of Buenos Aires. Children
from poor neighbourhoods, however, scored on average
5 points less than children living in other areas.
The study performed in Santiago, in which
neighbourhoods were classified by their unemployment rate,
21

81

found an inverse relationship between the concentration
of unemployed people and the performance of children
at school according to the tests administered under the
Education Quality Measuring System (SIMCE) of the
Chilean Ministry of Education (Flores, 2007). This finding
is in keeping with the theories that in neighbourhoods in
which the adults have weak ties with the labour market, the
sense of community tends to fade and the neighbourhood
is incapable of providing useful information and examples
that could foster the social integration of the children
and teenagers living there. The study also leads to three
more conclusions. First, a one- point increase in the
unemployment rate of a neighbourhood results in a 1.13
point drop in the SIMCE scores of the children attending
the school in that neighbourhood. Second, the SIMCE
scores vary according to the administrative status of the
school, with public schools scoring lower than subsidised
private schools, and these in turn scoring lower than nonsubsidised private schools. This is partially explained
by the neighbourhood in which the different types of
schools are found.21 Finally, residential segregation also
seems to indirectly affect how well children learn in
another way: when all other factors are kept constant, a
1% increase in job satisfaction among teachers working
in non-segregated neighbourhoods results in a 4.4 point

The ratio between the administrative status of the schools and the score obtained on the assessment tests declines when the local employment
rate is used as a control variable, which suggests that part of the variation in children’s academic performance is due to the socio-economic
characteristics of the neighbourhood in which they live.

82

Economic Commission for Latin America and the Caribbean (ECLAC)

increase in the children’s performance. In segregated
neighbourhoods, however, the same increase in job
satisfaction only translates into 0.4 additional points on
the SIMCE tests (Flores, 2007).
In Rio de Janeiro, academic performance was
measured using an indicator of the number of children
who had fallen behind after eight years of schooling
(Queiroz Ribeiro, Franco and Alves, 2007). The studied
showed that the children living in the favelas (shanty
towns) near neighbourhoods with a high percentage of
middle and upper class residents are more likely to fall
behind than those living in the favelas surrounded by
poor neighbourhoods. The influence of the surrounding
neighbourhood became even more apparent when the
authors of the studied analyzed school dropout rates among
teenagers aged between 14 and 17. The results indicated
that the risk of dropping out of school among youths from
favelas located near wealthy or poor neighbourhoods is,
respectively, 74% and 57% higher than among youths
living elsewhere.
These findings challenge the hypothesis that the
social heterogeneity of a given geographical area improves
the academic achievement level of the school children
in that area. They therefore have interesting heuristic
potential for developing theories about the influence of
the neighbourhood and open up a several possible lines of
research. Which combinations of children from different
social backgrounds, for example, would generate mainly
feelings of resentment and rejection among the poor children
as they become aware of their relative privation? Or under
what circumstances could social mixing, on the contrary,
foster empathy and conformity and encourage poor children
to integrate as they aspire to social mobility? Also, what
kind of (legitimate and illegitimate) opportunities arise
in the border zones between rich and poor areas where
poor children are constantly and directly exposed to life
styles and living conditions so far removed from their
own experience?
A study of academic performances in Mexico examined
the effects of the social make-up of neighbourhoods on
the school dropout rate from primary school through high
school (Solís, 2007). The study revealed that if the socioeconomic situation of a given neighbourhood deteriorates,
the likelihood that students will drop out of school at
the end of the first cycle of secondary education rises.22
The dropout rate remains high even when individual and
household traits are controlled for and only falls when
the characteristics of the schools are factored into the
equation. The study showed that it is the schools that

22

tend to internalize socio-economic inequalities (such
as the public or private status of the school, the social
background of the teachers and the average socio-economic
level of the pupils) that also tend to absorb the effects
of the neighbourhood. Rather than being independent
influences then, it seems that any deterioration in the socioeconomic situation of the neighbourhood combines with
and reinforces the internalized socio-economic inequality
of the school, and this disproportionately lowers the
chances of a student in that neighbourhood completing
their secondary education.
A study carried out in São Paulo indicates that the
effects of a neighbourhood’s social make-up on educational
outcomes can be transmitted indirectly to children through
the quality of their teachers (Torres et al., 2007). Under
the system used to regulate the placement of teachers
in state and municipal schools, teachers who score the
lowest in competitive application processes and those who
are new entrants in the education system are assigned to
the schools in outlying areas. The more experienced and
qualified teachers, on the other hand, can choose to work
in the schools that offer the best conditions in terms of the
location, organization and infrastructure of the school, the
security of the surrounding area, and the composition of
the student body. The rotation and absenteeism of teachers
in poor areas is therefore extremely high, especially in
the favelas (shanty towns), and this makes it difficult to
implement permanent measures to improve education
in these parts of the city. The incentive schemes set
up to reverse this situation are having little success in
persuading the more qualified teachers to alter their
preferences. A series of in-depth interviews conducted
as part of the study with teachers working in different
types of neighbourhoods revealed that they consider the
marginal areas of the city to be highly dangerous and
have very low expectations of what children from those
areas can achieve at school.
Another study carried out in Montevideo used
linear hierarchical models to determine the effects of the
neighbourhood on the academic test scores of children
in their sixth year of primary education (Katzman and
Retamoso, 2007). The study showed that the impact of
one unit of improvement in the socio-economic level
of the neighbourhood was greater than the impact of a
similar improvement in the socio-economic level of the
school or the family, and that this applied even when other
characteristics of schools and children were taken into
consideration. Another finding was that, using the same
control variables, the influence of the neighbourhood on

For each standard deviation from the socio-economic index of the neighbourhood, the probability of dropping out of school after the first basic
cycle of secondary school (ninth grade) increases 58%. For further details, see Solís (2007).

Social Panorama of Latin America • 2007

83

the academic scores/socio-economic level ratio was
even more pronounced in neighbourhoods in which
people had high-status jobs. It was also shown, again
using the same control variables, that the greater the
geographical extension of neighbourhoods with little
educational capital around the residence of a given
child, the less influence an improvement in the family’s

3. 


socio-economic level will have on the child’s academic
test scores.
In short, although much still remains to be discussed,
the results of the aforementioned studies support the notion
that, in large cities, the social composition of the area in
which a child or adolescent lives can significantly affect
how well they do at school.

The institutional alienation
of adolescents

The preceding two sections examined how the social
composition of the neighbourhood in which people live
affects their education and their employment prospects.
This section looks briefly at how the place of residence
shapes the ties that adolescents establish with the social
institutions of work and education, given the vital role
these play in determining their future standard of living.
The notion of “institutional alienation” or “disaffiliation”
refers to a total weakening of those ties, i.e. to adolescents
who neither work nor study. The labour market and the
education system are the two most important means
by which young people can be integrated into society.
Alienation from both increases the likelihood of them
ending up living in poverty on the edges of society.
A report by the Ministry of Labour, Employment
and Social Security of Argentina identified a hard core
of 320,000 young people who did not work, look for
work or study, and who had become social outcasts
that were “especially prone to situations of anomie and
social risk, often linked with the pursuit of illegal or
extra-legal forms of subsistence” (Bermúdez, 2005). A
study of three Brazilian cities revealed that institutional

disaffiliation among Brazilian teenagers and youth was
largely concentrated in the poorest areas of town (Queiroz
Ribeiro, 2004).
Although the data presented in table I.9 clearly
shows that social alienation among adolescents and
young people is far more prevalent in the underprivileged
neighbourhoods of Brazil’s large cities, it is impossible to
isolate the hypothetical impact of the social make-up of the
neighbourhood from the influence of family characteristics.
Table I.10, however, shows data for Montevideo which, in
addition to the social composition of the neighbourhood,
controls the educational background of the households
in which unemancipated adolescents live. This control
variable was chosen as one of the most efficient indicators
of institutional alienation among young people (ECLAC,
1994; MEMFOD, 2002). Figure I.13 classifies and orders
all the neighbourhoods of Montevideo according to the
percentage of high-status, high-income jobs held and
the percentage of young males aged 15 to 24 that do not
study, work or look for work and are living in households
in which the adults on average have no more than nine
years of schooling.

Table I.9
BRAZIL (THREE CITIES): PERCENTAGE OF THE POPULATION AGED 15 TO 24 THAT DOES NOT STUDY, WORK OR SEEK WORK, BY SOCIAL
COMPOSITION OF THE AREA OF RESIDENCE, 2004
City

Social composition of the residential area
Low

Middle

High

Total

Río de Janeiro

55

36

9

100%

São Paulo

63

30

7

100%

Belo Horizonte

73

21

6

100%

Source: L.C. Queiroz Ribeiro, “Segregación residencial y segmentación social: el efecto vecindario en las metrópolis brasileñas”, Trabajo y producción
de la pobreza en Latinoamérica y el Caribe. Estructuras, discursos y actores, S. Leguizamón (comp.), Buenos Aires, Clacso Libros, 2004.
Note: The classification of the residential areas by social composition was based on the level of education of the population aged 16 and over and on
the individual income level of all persons aged 14 and over.

84

Economic Commission for Latin America and the Caribbean (ECLAC)

Table I.10
URUGUAY (MONTEVIDEO): PERCENTAGE OF UNEMANCIPATED BOYS AGED 15 TO 19 WHO DO NOT STUDY, WORK OR SEEK WORK,
BY EDUCATIONAL CONTEXT OF THE SEGMENT AND THE EDUCATIONAL BACKGROUND OF THE HOME, 1996
Educational background
of the home
(in years of schooling)

Low

Middle

High

Up to 6 years

28.2

24.9

19.1

26.3

Over 6 to 9 years

26.2

23.3

16.1

23.1

Educational context of the segment
Total

Over 9 years

21.9

18.1

12.5

15.5

Total

26.8

22.0

13.8

21.4

Source: Rubén Kaztman, “El vecindario también importa”, Activos y estructura de oportunidades: estudio sobre las raíces de la vulnerabilidad social
(LC/MVD/R.180/E), R. Kaztman (coord.), Montevideo, ECLAC office in Montevideo, 1999.

Percentage of young people aged 15 to 24
who neither work nor study

Figure I.13
URUGUAY (MONTEVIDEO): NEIGHBOURHOODS ORDERED BY THE PERCENTAGE OF HIGH-STATUS JOBS AND MALES AGED 15
TO 24 YEARS WHO DO NOT STUDY OR WORK AND LIVE IN HOUSEHOLDS IN WHICH THE ADULTS HAVE LESS THAN
NINE YEARS OF SCHOOLING, 1996
(Percentages)

30
25
20
15
10
5
0
0

10

20

30

40

50

60

70

Percentage of high-status jobs

Source: Rubén Kaztman, “El vecindario también importa”, Activos y estructura de oportunidades: estudio sobre las raíces de la vulnerabilidad social
(LC/MVD/R.180/E), R. Kaztman (coord.), Montevideo, ECLAC office in Montevideo, 1999.
Note: Business-owners, managers, executives, administrators, scientists, artists, intellectuals and professionals fall into the high-status job category.
Unemancipated 15 to 24 years olds who do not study, work or seek work are included in the numerator of the indicator for institutional alienation.
The curve was adjusted using the LOWESS smooth procedure, which operates with weighted moving averages without supposing a specific functional
relationship for the purpose of the adjustment.

The results presented in table I.10 and figure I.13
reveal a negative relationship between the average socioeconomic level of the neighbourhood in which young
people reside and their degree of institutional alienation,
regardless of the educational level of their parents.23
As far as the validity of this finding is concerned, the
age of the subjects under study (especially in table
I.10) allows one to suppose that the vast majority were
born and grew up in the neighbourhood in which they

23

24

were living and that it was not their decision to do
so. Studies of the effects of the social composition of
the neighbourhood on adolescents are less likely to
be contaminated by the bias of choice.24 Therefore,
when a significant relationship between the effects
of the social composition of the neighbourhood and
behaviour is detected in the case of adolescents, it is
less risky to attribute causality to the neighbourhood
context than in the case of adults.

It is possible that the same unobserved family variables that influence where the parents live could affect the institutional alienation of
adolescents though the socialization that takes place at the family level. In this case, the relationship between the neighbourhood and teenage
behaviour is spurious as it is intermediated by the family. Given that the parents’ level of education is known to influence the institutional
alienation of children, this would seem to be a valid conclusion. Some data from table I.10, however, contradict this idea because in some cases,
the effects of the neighbourhood seem to have a greater influence than the educational level of the family. The rate of institutional alienation
among adolescents from households with high educational levels that live in neighbourhoods with a low socio-educational ranking (21.9%),
for example, is higher than among those with the opposite circumstances, i.e., a household with a low educational level in a neighbourhood
with a high socio-educational ranking (19.1%).
This refers to the possibility that the determinants of the variations in the behaviour under study could be attributed to the concentration in one
part of town of people that share unobserved individual attributes related to their decision to make their home in that area.

Social Panorama of Latin America • 2007

The reproductive behaviour of adolescents
(Rodríguez, 2006) and in Montevideo, the percentage
of high-status jobs held in each neighbourhood are used
(Kaztman, 1999).
Figure I.14
BRAZIL (RIO DE JANEIRO): PERCENTAGE OF WOMEN AGED 15
TO 18 YEARS WHO ARE MOTHERS, BY LEVEL OF EDUCATION
AND INCOME QUINTILE OF THE WEIGHTING AREA IN WHICH
THEY LIVE, 2000
30

Percentage of mothers

Early motherhood tends to be seen as a phenomenon
that makes it difficult to reduce social inequalities and
break the cycle of poverty because it has such a direct
impact on the future welfare of women and children.
The risk of early motherhood is particularly high
among the poorest strata of society: girls from poor
neighbourhoods in Latin America are five times more
likely to be mothers than their counterparts among the
upper classes (ECLAC, 2005a).
Early motherhood constitutes a risk for several reasons.
First, it prevents girls from finishing their education.
Although most girls who drop out do so before they get
pregnant, motherhood reduces the probabilities that they
will return to school at any point in the future. Second,
without education, teenage mothers are at a disadvantage
when it comes to entering the labour market, and, as
reported in a previous issue of Social Panorama of Latin
America, the vast majority end up in domestic work (see
figure II.11, ECLAC, 2005a). Third, a growing proportion
of children born to teenage mothers are born outside of
wedlock. This raises the likelihood, given that she is not
in a stable relationship with the father, that the mother
has to raise the child on her own. Children born in these
circumstances grow up without the material or emotional
support of their father and without the social capital that
their father could pass on to them through his family and
his other connections.
By removing them from the education system and
the labour market, early motherhood prevents young
women with little schooling from accumulating assets
during a vital stage for the incorporation of human and
social capital and drastically lowers any expectations of
upward social mobility that they may have harboured.
Early motherhood thus seems to keep low-income women
firmly rooted in poverty (Buvinic, 1998).
Some research into the impact of the neighbourhood
on the teenage pregnancy rate in the cities of Rio de
Janeiro, Santiago and Montevideo indicates that as far as
early motherhood is concerned, the social composition
of the place of residence is a significant factor. All three
studies, acknowledging education as an important indicator
of type of behaviour, use the last year of schooling
completed by the girls under study as the control variable
for analysing the relationship between the neighbourhood
and early motherhood. The studies use different criteria
for classifying neighbourhoods, however: in Rio de
Janeiro, income quintiles of the sample weighting area; in
Santiago, the socio-economic quintile of the census district

27.7
25.2

25

15

25.1
22.2

20

19.5

17.8

15.4

15.3
9.6

10

16.3

14.3

15.5

14.1

12.2

11.4

8.2
7.5

9.1

18.5

16.3

9.8

6.9
5.8

5
0

12.6

11.5

6.0 6.4
3.2
1.2

1 (poorest)

2

3

4

5.6

5 (richest)

Income quintile of the weighting area
No schooling
1 to 3 years

8 to 10 years
11 to 14 years

4 to 7 years

Total

Source: Jorge Rodríguez, “Segregación residencial socioeconómica (SRS)
y sus relaciones con la migración intrametropolitana en cuatro aglomerados
urbanos de América Latina. Los casos de Ciudad de México, Santiago
de Chile, São Paulo y Río de Janeiro en los decenios de 1980 y 1990”,
paper presented at the second congress of the Latin American Population
Association (ALAP), Guadalajara, 3 to 5 September 2006.

Figure I.15
CHILE (SANTIAGO): PERCENTAGE OF WOMEN AGED
15 TO 19 YEARS WHO ARE MOTHERS, BY LEVEL OF
EDUCATION AND INCOME QUINTILE OF THE CENSUS
DISTRICT IN WHICH THEY LIVE, 2002

40

Percentage of mothers

4. 

85

35

36.2

33.0

30

28.6
24.2

25
20
15
10

15.5

18.5

7.9

5
0

1 (poorest)

12.4

14.5

11.4

9.5

5.8
2

6.5

4.6
3

8.3
4.1
4

11.8
2.9 1.8 3.8
5 (richest)

Socio-economic quintile of the district
Basic/Primary

University

Secondary

Total

Source: Jorge Rodríguez, “Segregación residencial socioeconómica (SRS)
y sus relaciones con la migración intrametropolitana en cuatro aglomerados
urbanos de América Latina. Los casos de Ciudad de México, Santiago
de Chile, São Paulo y Río de Janeiro en los decenios de 1980 y 1990”,
paper presented at the second congress of the Latin American Population
Association (ALAP), Guadalajara, 3 to5 September 2006.

86

Economic Commission for Latin America and the Caribbean (ECLAC)

Percentage of unmarried mothers aged
15 to 19 with up to 9 years of schooling

Figure I.16
URUGUAY (MONTEVIDEO): NEIGHBOURHOODS ORDERED BY
PERCENTAGE OF UNMARRIED MOTHERS AGED 15 TO 19 YEARS,
WITH UP TO NINE YEARS OF SCHOOLING, AND PERCENTAGE OF
HIGH-STATUS JOBS, 1996
20
18
16
14
12
10
8
6
4
2
0

0

10

20

30

40

50

60

70

Percentage of high-status jobs

Source: Rubén Kaztman, “El vecindario también importa”, Activos y
estructura de oportunidades: estudio sobre las raíces de la vulnerabilidad
social (LC/MVD/R.180/E), R. Kaztman (coord.), Montevideo, ECLAC
office in Montevideo, 1999.
Note: Business-owners, managers, executives, administrators, scientists,
artists, intellectuals and professionals fall into the high-status job category.
Unemancipated 15 to 24 years olds who do not study, work or seek
work are included in the numerator of the indicator for institutional
alienation.
The curve was adjusted using the LOWESS smooth procedure, which
operates with weighted moving averages without supposing a specific
functional relationship for the purpose of the adjustment.

Even though the mechanisms whereby the socioeconomic make-up of the place of residence affects
the reproductive behaviour of adolescents have not

5. 

been identified, the evidence produced by the studies
conducted in these three cities confirms the significant
influence of the neighbourhood’s social composition.
In Santiago, the probability of a teenage girl who has
not completed her basic education being a mother is
37% if she lives in an area that falls into the lowest
socio-economic quintile of the city, and only 12% if
she lives in an area in the highest quintile (Rodríguez,
2006). In Rio de Janeiro, the proportion of teenage
mothers with one to three years of schooling ranges
from 28% in the weighting areas of the first income
quintile to 18% in the highest income quintile. In
Montevideo, the maternity rate is about 18% for
teenagers with less than nine years of schooling who
live in the neighbourhoods with the lowest proportion
of high-status jobs, and only 4% for teenagers from
the neighbourhoods with the highest proportion of
such jobs.
The findings are by no means conclusive. In addition
to education, other household and individual characteristics
would have to be controlled for the premise that the place
of residence has a decisive influence on the reproductive
behaviour of adolescents to be accepted. In the absence
of more precise evidence, however, it would seem
advisable for those responsible for formulating strategies
and policies to reduce poverty and stop poverty being
reproduced from one generation to the next to pay close
attention to the results of research into the influence of
the neighbourhood on teenage pregnancy rates.

Conclusions

Given the multiple factors that would need to be
controlled, testing the hypothesis that there is a causeeffect relationship between the specific features of
poor neighbourhoods and certain behaviour patterns of
their residents would be a complex and expensive task.
Progress in the research into this topic in the region
is therefore likely to be slow and, in the short term
at least, it will be impossible to make any conclusive
statements about causalities. In the face of such obvious
limitations evidence-wise, researchers are forced to
formulate hypotheses that are sufficiently sensible and
suggestive to persuade colleagues to further their lines
of investigation. How well they achieve this depends, to
some extent, on the data, despite its weaknesses, lending
some credibility to the hypotheses in question and, more
importantly, on the researcher’s ability to make sense
of the data. This means the researcher needs to be able

to create an embryonic conceptual framework for the
data that orders the different pieces into an intelligible
and interesting picture.
The basic idea underlying the summary presented in
the previous section is that the social fabric of the urban
neighbourhoods in which most people with only tenuous
ties to the labour market live is sifting and shifting the
opportunities for social improvement that cities usually
afford their inhabitants. Neighbourhoods thus become
ecological contexts that hamper people’s access to the
most important sources of physical, social and human
assets that the market, the state and the community can
offer. The term “the geography of opportunity” coined by
Galster and Killen (1995) neatly describes the mediating
role that the social composition of neighbourhoods plays
in the geographical distribution of sources of assets in
large cities.

Social Panorama of Latin America • 2007

For the vast majority, work is the main route to amassing
physical and financial capital. The findings of some of
the studies discussed in this chapter reveal the limitations
imposed by the geography of employment opportunities
on the people who live in outlying neighbourhoods that
have high proportions of unskilled workers. It is not just
the distance from their places of employment and their
exclusion from the main social and cultural circles of
the city that erode people’s ties with the labour market.
Having a large concentration of constantly frustrated
people living in the same area, without the resources they
need to satisfy their material aspirations has an aggregated
effect that enhances the stigmatized image that the people
of the neighbourhood identify themselves with. It also
generates mistrust, undermines security, and lowers the
tone of social interaction in the community.
Another set of studies revealed a significant link
between the homogeneity of the social make-up of poor
neighbourhoods and the possibilities of accumulating
human capital, which is reflected in the poor academic
performance of children and adolescents from those
neighbourhoods. This is due to the inability of parents
and neighbours to play a complementary role to that of
the school and to the numerous difficulties that schools in
poor neighbourhoods have in performing their fundamental
role as a force for social integration that stops social
factors affecting educational achievement. The large
cities of Latin America no longer seem to provide the
conditions that at one point in time fostered the harmonious
interaction of school, home and neighbourhood and
enabled children from poor households to accumulate
the necessary human capital to escape the clutches of
intergenerational poverty.
One basic feature of social capital is that people can
obtain useful resources through their participation in the
social network. Social capital in poor urban neighbourhoods
today, however, is fragile at best, largely due to the lack
or instability of such resources. The neighbourhood

87

as a source of social capital is gone, as are the days of
the working-class neighbourhoods where life revolved
around the factories and working-class values rooted in
the shared experience of steady work were bolstered by
the daily interaction with the neighbours. Gone too are
the illusions held by some urban reformers that social
housing projects, land occupation movements and such
could recreate the solidarity eroded by the crisis in the
labour market.
In the large cities of the United States and Europe, a
sweeping range of housing and urban planning policies
has been implemented with a view to promoting social
integration and reducing the geographical segregation
of the homes of the more vulnerable members of the
population. The same process, but on a far smaller scale is
underway in some parts of Latin America (Brain, Cubillos
and Sabatini, 2007). The policies vary considerably in
kind and are too many to describe here. They all aim,
however, to reduce the physical distances and social
differences between the poor and the non-poor. Changes
in the location of social housing, transportation and rental
subsidies, the extension of soft loans to low-income
families so that they can purchase homes in the formally
constituted areas of the city, and improvements in the
flow of information from where the jobs opportunities
for unskilled workers are to where those workers live
are some of the types of direct action that can shorten
commutes between places of residence and employment
or rectify their negative effects.
The creation of crossed housing subsidies, the setting
aside of some land in each district in the city for social
housing, the promotion of the “social mixing” of the student
population in schools, and the upgrading of public services
and areas are also measures that, deliberately or not, have
the positive side effect of reducing social distances. The idea
is to generate, and in some cases recreate, environments
that foster the “natural” development of friendly and
convivial relations between the classes.

88

Economic Commission for Latin America and the Caribbean (ECLAC)

E.  Poverty, exclusion and social cohesion:


psycho-social divides

An analysis of poverty and inequity should not be confined to the study of their material
components. Numerous psycho-social divides currently separate the economically vulnerable
from the economically comfortable population and are threatening social cohesion in the
region. In order to reduce poverty and foster social integration, efforts to improve the material
conditions of the poor need to be complemented with comprehensive policies in order to
raise the confidence of the most vulnerable sectors in institutions and encourage them to
feel more included and participate more actively in decisions that affect their circumstances
and thus meet their expectations of increased well-being.

Greater interest has been shown in the non-material aspects
of poverty and inequity in the region in recent years. This
interest largely stems from the new dynamics generated
by Latin America’s insertion in the global economy, a
process which has created new modes of exclusion that are
threatening social cohesion in the region. The widening social,
economic and cultural divides, a waning confidence in State
institutions, an increasingly tenuous sense of belonging and
a lack of interest in public affairs is thought to be generating
conditions that will exclude the poor even more than in the
past (ECLAC, 2007). Faced with fading solidarity, weaker
community ties, the exhaustion of the survival mechanisms
traditionally used by the poor to overcome hardship, and
minimal levels of citizen participation and faith in State
institutions, the more vulnerable members of the population
now find themselves with less resources and in a worse
situation for handling crises than before, which could
perpetuate the intergenerational transmission of poverty in
the region (ECLAC, 2007; Narayan et al., 2000).

25

26

Despite the importance now awarded to the nonmaterial aspects of poverty and inequity in the rhetoric
underpinning social policy in the region, no quantitative
studies have been conducted in Latin America at the
regional level to identify the main psycho-social
divides among the various socio-economic strata in
terms of the quality of social relations, participation
and confidence in institutions, and expectations of
social mobility (Kaztman, 2007), which are crucial
for the design of any social inclusion or cohesion
policies that aim to address more than the material
aspects of development. 25 This section therefore
examines some of these psycho-social divides by
analyzing the perceptions and behaviour of people
from different socio-economic strata in 18 Latin
American countries with regard to the following: (i)
inter-generational social mobility; (ii) confidence in
State institutions and citizen participation and (iii)
perceptions of discrimination.26

The available evidence on the psycho-social aspects of poverty and inequity consists only of qualitative data. Some of the first ethnographies
include the studies performed by Oscar Lewis in the 1960s which led to the coining of the term the “culture of poverty”. More recent research
includes Voices of the poor: can anyone hear us? (Narayan et al., 2000), a study that covered Argentina, Bolivia, Brazil, Ecuador and Jamaica.
It is important to highlight the exploratory nature of this exercise. No attempt is made to the identify characteristics of the countries (or groups
of countries) that could determine different types of rips in the social fabric nor to dismiss the theories that have attempted to explain the
perpetuation of poverty as the result of a subculture or the product of adaptation to unfavourable situations (Rankin and Quane, 2000).

Social Panorama of Latin America • 2007

1. 


Expectations of inter-generational
social mobility

Expectations of social mobility are the driving force of
any society founded on the principles of meritocracy and
equal opportunity. These expectations explain people’s
motivation as they rest on the belief that by personal effort,
people can climb the social ladder and improve their
standard of living. In societies in which access to resources
is severely limited, however, it is highly unlikely that the
poor will have much faith in the principle of meritocracy.
This poses a threat to social cohesion. Limitations of this
kind tend to increase the gap between expectations and
aspirations and can turn into sources of frustration or
trigger aggressive reactions that erode social integration
(ECLAC, 2007). Repeatedly failing to move up the social
ladder and constantly facing a series of disadvantages
can create the sensation among poor people that there
are no opportunities open to them and no possibilities
whatsoever of inter-generational mobility.
Studies on the subject indicate that low expectations
of the future are core manifestations of exclusion and
extreme poverty. When unemployed for long stretches,
people end up feeling powerless to take on forces beyond
their control. This logic can be equally applied to those
working in the informal economy, where holding a stream
of unsteady and poorly paid jobs leads to a similar sense
of hopelessness (Atkinson, 1998). Some researchers
claim that poverty is reproduced through the transfer of
beliefs and attitudes and that despair is one of the most
important aspects of living for prolonged periods in
marginal conditions (Lewis, 1969). Others maintain that
low expectations of mobility and other manifestations of
the disintegration of the social fabric are largely attributable
to the concentration of poverty in urban areas and the
social isolation of those living in them, both of which are
mechanisms that perpetuate inequality and hardship.27
One way to analyse the gaps in expectations of intergenerational mobility is to examine how different socioeconomic groups perceive their current level of well-being
and the level of well-being they expect their children to
attain. The data for 18 countries in the region show that
perceptions of current well-being and expectations of
their children’s future vary systematically according to
the socio-economic situation of the household in question
and that people with the most access to goods and services

27

89

For further details, see the previous section of this chapter.

have higher expectations regarding their children’s future
than people from poorer households. Nevertheless, it
should be pointed out that at all socio-economic levels,
children are expected to enjoy a better standard of living
in the future than their parents do at present. Even people
from low-income households believe that their children’s
situation will be better than their own. They still expect
their children to be worse off than average (3.8 on a scale
of 1 to 10), however, which implies that the poor believe
their children will fare better but still have a below-average
standard of living (see figure I.17).
Figure I.17
LATIN AMERICA (18 COUNTRIES): CURRENT PERSONAL WELLBEING, FUTURE WELL-BEING OF CHILDREN AND AVAILABILITY
OF BASIC GOODS AND SERVICES IN THE HOME, 2006
(Values expressed as averages on the basis of a self-evaluation scale of
1-10, where 1 = poorest persons and 10 = richest persons)

8 assets

6.5

5.4

7 assets

6.2

5.0

6 assets

6.0

4.8

5 assets

5.7

4.6

4 assets

5.5

4.4

3 assets

5.2

4.1

2 assets

4.8

3.8

1 asset

4.4

3.4

0 assets

2.9
0

1

2

3

3.8
4

5

6

7

Current personal well-being
Future well-being of children

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of the Latinobarómetro
2006 survey.
Note: Current personal well-being and expectations regarding the future
well-being of the respondents’ children are measured on the basis of
a self-evaluation scale. Respondents were asked to rate their current
personal well-being and the future level of well-being that they believe
their children will have.
The indicator of household ownership of durable goods and basic
services includes the possession of: (1) refrigerator; (2) washing
machine; (3) fixed-line telephone; (4) computer; (5) piped-in hot water;
(6) automobile; (7) sewerage system and (8) cellular telephone.

90

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure I.18 compares perceptions of current personal
well-being and the future well-being of one’s children
among people from different socio-economic strata, but
controls the perception of the social structure.28 The data
reveal the influence of the perception of social structure
on expectations of mobility. Regardless of the level of
household well-being, people who believe that the social
structure is open or egalitarian have greater expectations
for their children than those who feel that it is closed or

inegalitarian. All people, however, even those who have
few resources and think the social structure is closed and
inegalitarian, expect their children to be better off than
they are. This phenomenon might be explained by factors
related to the upward turn in the economic cycle, but the
absence of data on expectations during periods of economic
recession make it impossible to prove this hypothesis.29 It is
also possible that expectations vary for reasons that having
nothing to do with the socio-economic structure.30

Figure I.18
LATIN AMERICA (18 COUNTRIES): CURRENT PERSONAL WELL-BEING, FUTURE WELL-BEING OF CHILDREN AND PERCEPTIONS
OF THE SOCIAL STRUCTURE, 2006
(Values expressed as averages on the basis of a self-evaluation scale of 1-10,
where 1 = poorest persons and 10 = richest persons)


Households with 0-1 assets

7.0

Households with 2-3 assets
7.0

6.0

6.0

5.0

4.8

4.0

3.7

5.0
3.8
2.9

3.0

4.0

5.4
4.6

4.3

3.6

3.0

2.0

2.0

1.0

1.0

0.0

Egalitarian-open

Inegalitarian-closed

0.0

Egalitarian-open

Inegalitarian-closed

Current personal well-being


Current personal well-being

Future well-being of children

Future well-being of children

Households with 4-6 assets 
7.0

7.0
6.0
5.0

Households with 7-8 assets

6.1
5.4

4.9

4.3

4.0

6.0

6.6

6.1

5.5

5.0

5.0
4.0

3.0

3.0

2.0

2.0

1.0

1.0

0.0

Egalitarian-open

Inegalitarian-closed

Current personal well-being
Future well-being of children

0.0

Egalitarian-open

Inegalitarian-closed

Current personal well-being
Future well-being of children

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of the Latinobarómetro 2006 survey.
Note:Current personal well-being and expectations regarding the future well-being of the respondents’ children are measured on the basis of a self-evaluation
scale. Respondents were asked to rate their current personal well-being and the future level of well-being that they believe their children will have.
The indicator of household ownership of durable goods and basic services includes the possession of: (1) refrigerator; (2) washing machine; (3) fixed-line
telephone; (4) computer; (5) piped-in hot water; (6) automobile; (7) sewerage system and (8) cellular telephone.

28
29
30

For more details on this indicator, see box I.7.
In all the countries analysed, the average variation of per capita GDP in 2004-2006 was positive. For more details, see Economic Commission
for Latin America and the Caribbean (ECLAC) “CEPALSTAT” [online database] http://websie.eclac.cl/sisgen/ConsultaIntegrada.asp..
In terms of basic motivation, people may “need” to believe that their children will be better off than they are. This reflects an emotional
response rather than a rational formation of expectations of inter-generational mobility based on the evaluation of existing opportunities and
the ability to take advantage of them.

Social Panorama of Latin America • 2007

91

Box I.7
THE LATINOBARÓMETRO STUDY

The Latinobarómetro study is conducted annually in 18 countries
of Latin America by Corporación Latinobarómetro on the basis
of a survey of the opinions, attitudes, behaviour and values
of the population in Latin America aged 18 and over towards
democracy, political and social institutions, civic participation,
public policies, poverty, economic issues, international relations,
the media, the environment, gender issues and discrimination.
The study focuses on a main theme each year, but the repetition
of identical questions in each survey allow opinions on a range
of subjects to be traced since 1995.
In 2006, in 16 countries, the survey was conducted in three
stages, using probabilistic samples in the first two stages and
a quota sample in the last. In Argentina and Chile, probabilistic
samples were used in all three stages. Approximately 1,200
people were interviewed in each national sample, and the
margins of error were about 3% even though they were only
interpretable in the countries in which probabilistic samples
were used in all three stages. It should be pointed out that in a
few countries, some rural and densely populated urban areas
were underrepresented.
Any interpretation of opinion survey data should take
into account that the results will be extremely sensitive to the
particular situation in the country at the time the survey is taken.
Only those indicators that met at least a basic criterion for
validity and reliability, were included in this analysis, however.
These were as follows:
• Confidence in State institutions and political parties. Likert
scale, in which individual scores are estimated as a sum
of the responses to questions about confidence in: (i) the
judiciary, (ii) the president, (iii) political parties, (iv) the police,
(v) parliament, (vi) the government and (vii) the electoral
tribunal. Each institution was rated on a scale of 1 to 4, where
1 = no confidence and 4 = total confidence. The items of the
scale are included in one main component that explains
53% of the variance. The questions that correlate most with
that component refer to confidence in the president, the

congress and the government, in that order. The scale has
an Alpha coefficient of 0.85, which indicates good internal
consistency.
• Indicator of political activity. Simple sum, in which individual
scores are estimated on the basis of total responses to
questions about how often the interviewees: (i) talk about
politics, (ii) try to convince someone about what they think,
(iii) work for a political party or candidate, (iv) sign petitions
and (v) participate in demonstrations. The Alpha coefficient
of the index is 0.76, which indicates an acceptable level of
internal consistency.
• Indicator of how the social structure is perceived. Ratio
between the people aged 18 and over who believe that
the social structure is open and egalitarian and the total
population of the same age group, multiplied by 100. The
index is constructed on the basis of a simple sum in which
people are classified into groups that consider the social
structure to be either: (i) open and egalitarian, (ii) ambivalent
or (iii) closed and inegalitarian. The classification was made
on the basis of whether people agreed or disagreed with
the following statements: (i) someone who is born poor and
works hard can become rich and (ii) everyone has an equal
opportunity to escape poverty. This indicator is a more reliable
measurement of people’s perceptions of the social structure
than the use of separate questions because it also identifies
those with ambivalent attitudes.
-Sense of belonging to a social group that is discriminated
against. Ratio between the number of people aged 18 and
over that claim to belong to a group that is for some reason
discriminated against and the total population of the same
age group, multiplied by 100.
- Causes of discrimination. This indicator is based on the
interviewees’ selection of one type of social discrimination
from among several. If an individual feels that he or she is
the subject of more than one type of discrimination, the
predominant type is selected.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Economic Commission for Latin America and the
Caribbean (ECLAC)/EUROsociAL, Un sistema de indicadores para el seguimiento de la cohesión social en América Latina y el Caribe, Santiago,
Chile, 2007, in press.

The biggest “jump” in expectations of inter-generational
mobility is found among the poorest sectors of the countries’
capital cities, whereas people from the most vulnerable
sectors in rural or sparsely populated urban areas expect
the least improvement for their children relative to their
current situation. Among this group, expectations are never
above half way up the scale. In the poor communities

living in capital cities, however, people think their children
will enjoy a level of well-being equal to the average for
the whole population (see figure I.19). Beyond the fact
that these differences obviously respond to the historic
pattern of expectations associated with moving from the
country to the city, on the whole, people in the cities do
not live up to the picture of hopelessness painted by the

92

Economic Commission for Latin America and the Caribbean (ECLAC)

ethnographies, which now seems to be more applicable
to people in rural areas.31 These high expectations pose
enormous challenges to policymakers in the more heavily
populated urban areas, especially as regards the creation
of sufficient opportunities for education, employment
and social inclusion.

Figure I.19
LATIN AMERICA (18 COUNTRIES): CURRENT PERSONAL
WELL-BEING, FUTURE WELL-BEING OF CHILDREN,
BY AREA OF RESIDENCE AND ASSETS IN THE HOME, 2006
(Values expressed as averages on the basis of a self-evaluation scale
of 1-10, where 1 = poorest persons and 10 = richest persons)
7
6
5
4
3
2

5.1
3.9
3.1

3.6

5.5

5.6

5.9

4.6
3.7

4.1

4.5

4.6

6.4
5.2

6.3
5.2

El Salvador, Honduras and Mexico, and the smallest in
Argentina, Brazil and Guatemala. At first glance, it would
seem that there is no relationship between the gap in
expectations of mobility and the objective poverty and
inequality indicators. One of the problems of examining
the effects of the asymmetry in income distribution on
expectations of mobility in the region is that the level of
inequality is very high in nearly all the countries.
Figure I.20
LATIN AMERICA (18 COUNTRIES): FUTURE WELL-BEING
OF CHILDREN AND AVAILABILITY OF BASIC GOODS
AND SERVICES IN THE HOME, 2006
(Values expressed as averages on the basis of a self-evaluation scale
of 1-10, where 1 = poorest persons and 10 = richest persons)
Argentina

Chile

7-8 assets/capital city

7-8 assets/up to
5000 inhabitants

4-6 assets/capital city

4-6 assets/up to
5000 inhabitants

2-3 assets/capital city

2-3 assets/up to
5000 inhabitants

0-1 assets/capital city

0-1 assets /up to
5000 inhabitants

6.4

3.4

El Salvador

5.5

3.1

Guatemala

Mexico

6.6

4.2

Panama

5

3.5

5.7

4

Paraguay

The trends observed for the region as a whole are
also apparent in each country (see figure I.20). In all
countries, people with a comfortable economic situation
have higher expectations regarding the future well-being
of their children, and people in a more vulnerable socioeconomic position have lower expectations. The largest
differences were detected in Costa Rica, Colombia, Ecuador,

31

6.5

3.7

Nicaragua

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of the Latinobarómetro
2006 survey.
Note: The analysis included data on the capital cities of 17 countries.
No data were available for San José de Costa Rica.
In most countries, with the exception of Brazil, the capital city is the
most heavily populated urban area.
Settlements with fewer than 5,000 inhabitants were considered to be
approximations of rural residential areas because no data was available
for settlements with 2,000 inhabitants or less.

5.7

4.7

Honduras

Future well-being of children

6

3.8

Ecuador

6.7

4.8

Peru

6.7

4.6

Dominican Republic

5.8

4.3

Uruguay

5.9

4.2

Venezuela
(Bolivarian Rep. of)

5.5

4.3
1

2

3

6.9

6.7

4.3

Costa Rica

Current personal well-being

6.1
6.4

4.4

Colombia

0

6.3

4.8

Brazil

1

6.6

5.7

Bolivia

4

5

6

7

8

Households with 0-1 assets
Households with 7-8 assets

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of the Latinobarómetro
2006 survey.
Note: Current personal well-being and expectations regarding the future
well-being of the respondents’ children are measured on the basis of
a self-evaluation scale. Respondents were asked to rate their current
personal well-being and the future level of well-being that they believe
their children will have.
The indicator of household ownership of durable goods and basic
services includes the possession of: (1) refrigerator; (2) washing
machine; (3) fixed-line telephone; (4) computer; (5) piped-in hot water;
(6) automobile; (7) sewerage system and (8) cellular telephone.

The lack of comparable measurements of residential socio-economic segregation in most countries in the region makes it difficult to prove
empirically the hypotheses about the effects of the isolation of the poor on their expectations of social mobility. The evidence of the influence
of residential socio-economic segregation on employment opportunities, education, reproductive behaviour and the institutional alienation of
adolescents was analyzed in the preceding section.

Social Panorama of Latin America • 2007

2. 


Confidence in state institutions
and participation in politics

There has been renewed interest in the “confidence gaps”
that threaten to undermine the legitimacy of institutions
(Paxton, 1999) and hamper social inclusion and cohesion.
Confidence is a fundamental component of social capital
and has been defined as the expectations people have of
other people, institutions and the social order (Paxton,
2002). Confidence in public institutions is essential for
social cohesion: a socially efficient and transparent State can
generate confidence among its citizens by building bridges
between different social groups, creating opportunities for
social mobility and developing forums for participation.
A lack of confidence in State institutions, on the other
hand, weakens the political support for inclusion initiatives
(ECLAC, 2007) and, in the case of institutional collapses,
can worsen pre-existing asymmetries and create the
conditions in which delinquency and corruption thrive.
In Latin America, the shrinking of the State, the
privatization of public services, the incidences of government
corruption and the continuously high levels of poverty
and inequity, among other phenomena, have gradually
eroded citizens’ confidence in State institutions. Some
qualitative studies performed in a few countries in the
region have shown that, as far as the poor are concerned,
public institutions are in crisis. Even in cases when they
work well, State institutions are often seen as inefficient
and inaccessible by the more vulnerable members of the
population. People point to the cases of corruption and
display a deep mistrust of public institutions, often referring
to them in tones of despair (Narayan et al., 2000).
Figure I.21 shows how the level of confidence in State
institutions varies according to a person’s economic situation
and per capita GDP in Latin American countries. Confidence
is greater among those from wealthier households and those
living in countries with a higher per capita GDP, and lower
among those living below the poverty line and in countries
with a lower per capita GDP. The level of confidence in
public institutions among people from the poorest countries,
regardless of their personal economic situation, is always
lower than among people from countries with an average
or high per capita GDP. This implies that the amount of
resources available in a country affects the solidity of its
institutions, which in turn affects the confidence that citizens
place in the State institutions of that country.

32
33

93

Figure I.21
LATIN AMERICA (18 COUNTRIES): CONFIDENCE IN STATE
INSTITUTIONS, SUFFICIENCY OF HOUSEHOLD INCOME AND
PER CAPITA GDP OF THE COUNTRY, 2006
(Values expressed as averages, in which a higher score
denotes greater confidence)
20.0
18.0
16.0
14.0
12.0

12.4

13.3

14.1

14.8

15.0

16.6
15.7 16.0

15.6

16.5

17.3 17.8

10.0
8.0
6.0
4.0
2.0
0.0

Low GDP

Medium GDP

High GDP

Insufficient income. major difficulties
Insufficient income. difficulties
Income just sufficient
Sufficient income to save

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of the Latinobarómetro
2006 survey.
Note: The households were classified according to a self-assessment of
how sufficient income was to cover basic needs.
The countries were classified according to per capita GDP as follows: high
GDP countries = Argentina, Bolivarian Republic of Venezuela, Costa Rica,
Chile, Mexico and Uruguay; medium GDP countries = Brazil, Colombia,
Dominican Republic, El Salvador, Panama and Peru; low GDP countries =
Bolivia, Ecuador, Guatemala, Honduras, Nicaragua and Paraguay.

People from the poorer households in densely populated
urban areas who have little confidence in their neighbours
also display the least confidence in State institutions (see
figure I.22). It seems that a segment of the more vulnerable
urban population suffers from a syndrome of mistrust
that takes the form of low expectations regarding public
institutions and a lack of confidence in social relations
with people outside the family circle.32 These people
tend to hold markedly individualistic values, according
to which, efforts to improve one’s situation are based on
personal initiative and achievement, not on participation in
collective organizations and social movements.33 This not
only poses a problem for conflict management in poor urban
neighbourhoods, it threatens to limit the poorest sectors’
access to social forms of support and may stop them from
organizing their communities and from bringing their needs
and demands to the attention of public institutions.

“Syndrome” is understood to be a set of attitudes that are related to one another.
As far as expectations of social mobility are concerned, there is no difference between the urban poor that have no confidence in institutions
and the urban poor that do.

94

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure I.22
LATIN AMERICA (18 COUNTRIES): CONFIDENCE IN STATE INSTITUTIONS BY INCOME SUFFICIENCY OF THE HOUSEHOLD,
CONFIDENCE IN THE NEIGHBOURHOOD AND AREA OF RESIDENCE, 2006
(Values expressed as averages, in which a higher score denotes greater confidence)

Areas with up to 10 000 inhabitants
20

17.0
15

15.4

Areas with over 100 000 inhabitants
20

18.3
15.0

17.4

17.0
14.2

17.1
15

14.5

13.2

10

16.1

15.5

13.4

12.4

10

5

16.5
14.2

5

0

Sufficient income
to save

Income just sufficient

Insufficient income,
difficulties

Insufficient income,
major difficulties

0

Sufficient income
to save

Income just sufficient

Insufficient income,
difficulties

Insufficient income,
major difficulties

Does not trust neighbours
Trusts neighbours

Does not trust neighbours
Trusts neighbours

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of the Latinobarómetro 2006 survey.
Note: The households were classified according to a self-assessment of how sufficient income was to cover basic needs.
The category “trusts neighbours” included those who claimed to trust somewhat or a great deal, while the category “does not trust neighbours”
included those who trusted little or not at all.

The validity of measuring the lack of confidence
in State institutions against indicators of well-being is
born out by the findings at the country level. Figure I.23
shows that, except for in Bolivia, the level of confidence
among people living with insufficient income to cover
basic needs is lower than among people with higher
levels of well-being. The widest gaps were detected in the
Bolivarian Republic of Venezuela, Paraguay, Costa Rica,
Chile and Argentina, and the smallest in Brazil, Colombia
and Mexico. In the Bolivarian Republic of Venezuela, the
size of the gap is largely accounted for by the level of
confidence displayed by people who are relatively welloff. In Paraguay, the difference between the economic
groups originates from the minimal confidence displayed
by the poorest sectors of the population. In Mexico, the
small gap is explained by the lack of confidence of the
wealthier sectors. A separate analysis should be performed
of the situation in Nicaragua, Honduras, El Salvador,
Guatemala, Ecuador and Paraguay because the level of
confidence among all socio-economic groups in these
countries is worryingly low.
It has been suggested that in order to understand
people’s lack of confidence in State institutions, it may be
necessary to look beyond the formal organization and norms
of these institutions and examine their actual behaviour
patterns. The stated purpose of State institutions may be to
serve the common good, but, in practice, the asymmetries
of society are often reproduced in their activities and the
poorest are often excluded (Narayan et al., 2000). Corruption
is one example of deviation from the established norm and
could explain the lack of confidence in State institutions.
This seems to be the situation in Nicaragua, Honduras,

Figure I.23
LATIN AMERICA (18 COUNTRIES): CONFIDENCE IN
STATE INSTITUTIONS, BY SUFFICIENCY OF HOUSEHOLD
INCOME AND COUNTRY, 2006
(Values expressed as averages, in which a higher score
denotes greater confidence)
Argentina

16.2

13.8

15.7
15.7

Bolivia

16.7
16

Brazil
Chile

17.9

15
16.3
15.4

Colombia
Costa Rica

16.8

13.5

Ecuador

10.4

12.1

El Salvador

12.4

Guatemala

12.7

14.3
14.5

Honduras

15.5
14.7

Mexico

15.6
14.9

Nicaragua

13

14.7
17.8
16.5

Panama
Paraguay

14.4

10.9

Peru

13.3

15.6
17.3
15.9

Dominican Republic
Uruguay

17.4

Venezuela
(Bolivarian Rep. of)

18.9
20.8

16.7
0

5

10

15

20

25

Households with sufficient income to save
Households with insufficient income and major difficulties

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of the Latinobarómetro
2006 survey.
Note: The households were classified according to a self-assessment of
how sufficient income was to cover basic needs.

Social Panorama of Latin America • 2007

Guatemala, Ecuador and Paraguay, whose State institutions
all scored low transparency ratings in international studies
of corruption.34 The situation of the Bolivarian Republic
of Venezuela suggests, however, that the question is not
quite so simple. The level of corruption in the country
was high according to the Corruption Perceptions Index
calculated by Transparency International in 2006, but its
citizens displayed the highest level of confidence in its
public institutions.35
Participation in political and social institutions is
another factor in the level of confidence citizens have
in public institutions. Participation is important not only
because of the role it plays in strengthening democracy
but also because it constitutes one way to build up social
capital and confidence in institutions, especially among
the poor. Much still remains to be done in this respect,
however. In all the countries of the region, the poor
participate less in politics than the wealthy (see figure
I.23). This could worsen the plight of the poor even further
because exercising citizenship is one way for people to
access the resources that can improve their prospects. The
challenge for policymakers, therefore, lies in creating
opportunities for the more vulnerable members of the
population to not just hold citizens’ rights, but to actively
exercise them as well.

95

Figure I.24
LATIN AMERICA (17 COUNTRIES): POLITICAL PARTICIPATION,
AVAILABILITY OF GOODS AND SERVICES IN THE HOME, 2006
(Values expressed as averages, in which a higher score denotes greater
political participation)
Argentina

7.8

6.9

8.1
7.7

Bolivia
Brazil

10.1

8.7

Chile

8.2

5.8

8.7
8.4

Colombia
Costa Rica

8.3

7.7

Ecuador

9.6

7.0

El Salvador

8.6

6.2

Guatemala

8.1

7.4

Honduras

8.1

7.2

8.4
8.2

Mexico
Panama

7.8

6.5

Paraguay

8.2

Peru

9.4

8.0

Dominican Republic

7.8

Uruguay

9.5

8.6
9.6

7.0

Venezuela
(Bolivarian Rep. of)

9.1
0

2

4

6

8

10.1
10

12

Households with 0-1 assets
Households with 7-8 assets

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of the Latinobarómetro
2006 survey.
Note: For more details on the indicator of political participation, see box I.7
The indicator of household ownership of durable goods and basic
services includes the possession of: (1) refrigerator; (2) washing
machine; (3) fixed-line telephone; (4) computer; (5) piped-in hot water;
(6) automobile; (7) sewerage system and (8) cellular telephone.

3. 

Discrimination

Social inclusion and cohesion policies need to address the
fact that the groups that wield the most power in society in
material and symbolic terms use a number of mechanisms
to hold onto, obtain and control resources. These include
discriminatory practices whereby one social elite limits

34

36

access to resources to its own circle and denies opportunities
to individuals from other social groups that it classifies as
inferior or ineligible on the grounds of a particular feature
associated with those groups (Murphy, 1986). These
mechanisms need to be understood within the cultural

In 2006, these countries obtained a score of 2.6, 2.5, 2.6, 2.3 and 2.6, respectively, on the Corruption Perceptions Index. This index ranks a
country’s public institutions on a scale of 1 to 10, where 10 = totally transparent and 1 = not transparent at all. For further details, see Transparency
International [online] (http://www.transparency.org/policy_research/surveys_indices/cpi/2006).
In 2006, the Bolivarian Republic of Venezuela obtained a score of 2.3. For further details, see Transparency International [online] (http://www.
transparency.org/policy_research/surveys_indices/cpi/2006).

96

context of each country. Cultural standards and traits are
firmly rooted in a nation’s history and largely determine to
what extent social interaction is regulated by people’s shared
notions of hierarchy-equality and ascription-acquisition.
These constitute the framework for relations between
different socio-economic strata in a society and underpin
people’s attitudes and behaviours (Kaztman, 2007).
In Latin America, discrimination has been traditionally
associated with ethnicity or gender, and studies on
discrimination have overlooked the denial of opportunities
on the grounds of being “poor”. Narayan and others (2000)
point out that discrimination on socio-economic grounds may
be a powerful factor in the inter-generational perpetuation
of exclusion. Discrimination and segregation (the most
distinctive features of exclusion) have severe negative
repercussions on people’s quality of life. Being poor can
lead to stigmatization and discrimination by institutions,
which leads to more poverty. In terms of healthcare, research
has shown that the stigmatization of the mentally ill and
HIV/AIDS carriers leads to the isolation and exclusion of
both these groups. Stigmatization plays an important role
in excluding people from the health system and increases
their marginalization in other areas, such as education and
employment as well (Joffe, 1995; Foucault, 1998).
No comparable data is currently available on discriminatory
attitudes or behaviour towards the poor in the region. One
way to examine the issue is to look at the perceived level of
discrimination among people from different socio-economic
strata. Figure I.24 shows that in all the countries the percentage
of people who feel they are discriminated against is higher
among those living in households with insufficient incomes
than among households that are better off. The largest
differences were reported in Paraguay, Argentina, Bolivia,
Chile and Mexico, and the smallest in Panama and Brazil.
The situation in Brazil is highly unusual inasmuch as both
socio-economic groups in the country perceive a high level
of discrimination. This warrants further investigation beyond
the scope of this analysis.
When the area of residence is factored into the analysis,
the highest levels of perceived discrimination are found
among the members of the most vulnerable households
located in areas with populations of over 100,000, while
the lowest levels are found among better-off households in
areas with populations of less than 10,000. These findings
question the validity of a linear interpretation, according to
which, there should be less discrimination in large urban
areas because, in cities, the logic of estates (in which
social position is determined on the basis of ascription)
has been replaced by the logic of status groups (in which
position is attained through individual achievement).
Another interpretation is that the rise of capitalism in
developing countries was based on the coexistence of
estate and status (Boroez, 1997).

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure I.25
LATIN AMERICA (18 COUNTRIES): PEOPLE WHO PERCEIVE
DISCRIMINATION, BY SUFFICIENCY OF HOUSEHOLD INCOME
AND COUNTRY, 2006
(Values as a percentage of the population)
5.0

Argentina

35.0
7.8

Bolivia

37.5
35.2
36.4

Brazil
3.4

Chile

28.6
5.6

Colombia

22.9

2.9

Costa Rica

15.5
5.8

Ecuador

20.8

4.8

El Salvador

21.8
9.0

Guatemala

18.2

10.6

Honduras

16.9

3.3

Mexico

26.4
14.5

Nicaragua

23.6

13.2
16.0

Panama
6.3

Paraguay

47.0
11.0

Peru

30.3
16.4

Dominican Republic
4.5

Uruguay
Venezuela
(Bolivarian Rep. of)

22.9
7.9

0

5

22.1

23.7

10

15

20

25

30

35

40

45

50

Households with sufficient income to save
Households with insufficient income and major difficulties

Source: Economic Commission for Latin America and the Caribbean (ECLAC),
on the basis of special tabulations of the Latinobarómetro 2006 survey.
Note: For more details on the indicator of perceived discrimination, see box I.7
The households were classified according to a self-assessment of how
sufficient income was to cover basic needs.
Figure I.26
LATIN AMERICA (18 COUNTRIES): PEOPLE WHO PERCEIVE
DISCRIMINATION, BY SUFFICIENCY OF HOUSEHOLD INCOME
AND AREA OF RESIDENCE, 2006
(Values as a percentage of the population)
30
25
20
15
10
5
0

Sufficient income
to save

Income just sufficient,
without major difficulties

Insufficient income,
difficulties

Insufficient income,
major difficulties

Up to 10 000 inhabitants
Over 100 000 inhabitants

Source: Economic Commission for Latin America and the Caribbean (ECLAC),
on the basis of special tabulations of the Latinobarómetro 2006 survey.
Note: For more details on the indicator of perceived discrimination, see box I.7

Social Panorama of Latin America • 2007

97

The households were classified according to a
self-assessment of how sufficient income was to cover
basic needs.
Along this line of argument, it is plausible that in
the more densely populated urban areas, the principles of
ascription clash with the principles of achievement, which
results in a higher perception of discrimination. In more
modern urban areas, exclusion on the basis of ascription
is the most noticeable because of its dissonance with the
egalitarian and meritocratic values that are widely held in
such areas. In less populated areas, however, where social
relations are more firmly anchored in traditional notions of
hierarchy and ascription, people may not even think that
determining people’s access to resources on the basis of the
social group they belong to is an act of discrimination. They
may see such practices as “natural”, part of the “way of life”,
especially in the countryside. It is also possible that there
is a greater chance of being discriminated against in urban
areas because city dwellers come into contact with more
diverse social identities and actors. In less urban areas, the
population is more homogeneous and has fewer opportunities
for contact with members of other social groups. This can
be particularly the case in rural areas where communities
often live in relative isolation. Either way, the data shows
that inequality is still one of the most important problems
for social cohesion.

Figure I.27 presents the causes of discrimination
described by people with insufficient income. The most
common was being “poor” (36.5%), followed by “being
old” (16.1%), having insufficient education (12.4%) and
not having contacts (7.2%). Several of the discriminatory
practices reported by those surveyed are associated with
the denial of opportunities to improve living conditions and
climb the social ladder. People are discriminated against
because they lack certain types of “capital”, namely: human
capital (education), social capital (contacts) and symbolic
capital (sense of “being someone”). Together, the factors
directly and indirectly related to poverty and social mobility
account for 60% of the causes of discrimination reported
by the more vulnerable sectors of the population.
Age (“being young”), ethnic ascription (skin colour,
race), disabilities, and gender or sexual orientation (“being a
woman” or “being homosexual”) were cited as the reasons
for a further 31% of discrimination experienced by people
living in households with insufficient income, together
with practices that deny opportunities for social integration
based on the obsolescence and/or lack of certain capacities
(discrimination against the elderly and the disabled). This
indicates that the poor may feel discriminated against in
more than one way because they fall into several different
social categories. They may, for example, feel excluded
because of their socio-economic situation and because of
their age or the ethnic group to which they belong.

Figure I.27
LATIN AMERICA (18 COUNTRIES): MAIN CAUSES OF DISCRIMINATION CITED BY MEMBERS
OF HOUSEHOLDS WITH INSUFFICIENT INCOMES, 2006
(Values in percentages of the population)

2.8

2.6

4.6

3.0
4.3
36.5
4.6

5.9

7.2

12.4

16.1

For being poor

For not having contacts

For being disabled

For being young

For being old

On account of race

For being homosexual

Other

For being uneducated

For being a nobody

For being a woman

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of the Latinobarómetro 2006 survey.
Note: For more details on the indicator of causes of discrimination, see box I.24

Social Panorama of Latin America • 2007

99

Chapter II

Public social expenditure and the need
for a social contract in Latin America

The level and structure of public social expenditure in Latin
America continue to fall short of what is required to meet
the social needs of the vulnerable population. Considerable
advances in reducing indigence notwithstanding, these
shortcomings have led to slow progress in alleviating
non-extreme poverty and reducing inequalities in the
region. On the one hand, the level of such spending is
insufficient, and funds are administered under severe
budgetary constraints resulting from low rates of taxation
and the narrow coverage of contributory social protection
programmes; on the other, the structure of expenditure
has to be constantly adapted to address emerging social
needs before existing ones have been met.
Adapting the level and structure of public social
expenditure to constantly changing risk profiles and social
needs should figure as one of the core elements of a new
social contract in which rights constitute the normative
horizon for efforts to address existing inequalities and

budgetary restrictions. As part of this effort, the allocation
of public funds for social ends should be designed to
increase the coverage and quality of benefits provided by
social programmes through a combination of contributory
and non-contributory financing, together with a significant
solidarity component.
The following section will explore the main
characteristics of the level and structure of public social
expenditure in the region and how they have changed
over the past 15 years. It will also look at which income
groups have been the main recipients of that expenditure
and the impact it has had in terms of increased levels of
well-being. Lastly, with a view to the design of a new
social contract, countries will be grouped into various
categories based on an indicator that measures the distance
existing between social needs and emerging risks, on
the one hand, and the State resources allocated to social
policies, on the other.

100

Economic Commission for Latin America and the Caribbean (ECLAC)

A. Level and composition of public social expenditure
The recent evolution of public social expenditure suggests that the trend towards allocating
larger amounts of public resources for social policies has levelled off, but has not reversed
itself. This will ensure future financing, stability and improved institutional legitimacy in social
policy. These efforts remain largely dependent on the levels of development achieved and, in
many cases, on small tax burdens, which result in insufficient levels of public social expenditure
in a number of countries in the region. Furthermore, the lack of countercyclical public social
expenditure policies in most of the countries makes it difficult to maintain a policy for offsetting
social risks when slowing economic activity reduces the ability of the authorities to maintain a
social protection system for the most vulnerable sectors of the population.

spends the most than in the country that spends the least.
Twelve of the 21 countries analysed spend less than US$
350 per capita per year, six spend between US$ 550 and
US$ 870 per capita, and only two spend more than US$
1,000 per person per annum.

The level of public social expenditure rose by nearly
10% between 2002-2003 and 2004-2005 to US$ 660
per capita (at 2000 prices) (see figure II.1). There are
enormous differences across countries, however. Per
capita expenditure is 15 times greater in the country that

Figure II.1
LATIN AMERICA (21 COUNTRIES): PER CAPITA PUBLIC SOCIAL SPENDING, 1990-1991 TO 2004-2005 a
(In dollars at 2000 prices)
1 800
1 521

1 400
1 200

Regional average
2004-2005: US$ 658
2002-2003: US$ 615
2000-2001: US$ 624
1998-1999: US$ 610

1 087

1 000

870

860

845

800

772

729
618
562

Regional average 1990-1991: US$ 440
289

1990-1991

1998-1999

2000-2001

2002-2003

120

108

100

96

90

Nicaragua

120

Ecuador

190

Guatemala

Dominican

Jamaica

Colombia

Panama

Venezuela
(Bolivarian Rep. of)

Mexico

Chile

Costa Rica

Trinidad and Tobago

Brazil

Cuba

Uruguay

Argentina

0

204

Paraguay

208

200

Honduras

291

El Salvador

344

Republic

400

Bolivia

600

Peru

Per capita public social spending

1 600

2004-2005

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
aOwing to changes in the GDP base year (1997), information in dollars is available only from 2000 onwards (see box II.6). The regional average does
not include Cuba.

Social Panorama of Latin America • 2007

101

An examination of the figures for public social
spending points up five main characteristics:
(i) The trend towards allocating larger amounts of
public resources for social policies has levelled off, but has
not reversed itself. The upward trend seen up to 2000-2001
in the percentage of GDP that governments are using for
social expenditure, that is, the macroeconomic priority
given to that spending —which is a measurement of the

effort being made by a government to allocate resources
for social policies— has been changing since 2002-2003
(see figure II.2). Nevertheless, the simple fact that, at the
regional level, the macroeconomic and fiscal priority
assigned to public social expenditure has been maintained
—albeit with some exceptions— provides an assurance
of continued financing, stability and greater institutional
legitimacy for social policy.

Figure II.2
LATIN AMERICA (21 COUNTRIES): PUBLIC SOCIAL SPENDING AS A PERCENTAGE OF GDP, 1990-1991 TO 2004-2005
(Percentages)

35

Total social spending

30

28.7
Regional average
2004-2005: 15.9%
2002-2003: 15.8%
2000-2001: 15.7%
1998-1999: 15.5%

25
22.0
19.4

20

18.6

17.7

17.5

15

13.4

13.1

11.7

Regional average 1990-1991: 12.9%

11.6
10.8

10

10.2

9.9

9.4

8.9

8.0

7.9

7.1

6.3

6.3

5.6

5

1990-1991

1998-1999

2000-2001

2002-2003

El Salvador

Ecuador

Guatemala

Dominican
Republic

Paraguay

Panama

Peru

Trinidad and Tobago

Jamaica

México

Nicaragua

Honduras

Venezuela
(Bol. Rep. of)

Chile

Colombia

Costa Rica

Uruguay

Bolivia

Argentina

Brasil

Cuba

0

2004-2005

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.

(ii) The profile of public social spending according to
the level of GDP shows budgetary constraints resulting
from small tax burdens. In a number of countries in
the region, public social spending remains limited and
procyclical in relation to per capita GDP (see figure
II.3). This suggests that the international assistance and
borrowings that used to provide countries with some
sort of margin may cease to be available as financing
options for countries that no longer receive official
development assistance (ODA). In terms of the priority
they allocate to social spending in relation to their
current levels of development, Cuba and Brazil show
the highest levels, followed by Argentina, Uruguay
and Costa Rica. The efforts being made recently
by Bolivia are noteworthy. On the other hand, the
countries showing the biggest lags are Trinidad and

Tobago and, to a lesser extent, Guatemala, Ecuador, El
Salvador, Dominican Republic, Bolivarian Republic of
Venezuela and Mexico. In the last two cases, figures
relate to central government coverage, the only level
for which figures are available, as can be seen in the
methodological appendix. This subject is discussed
further under item 5 of this section.
(iii) Over the past 15 years, the less developed
countries have made greater increases in their efforts to
allocate resources for social policies. The effort made by
countries in this connection declines as they become richer.
The less developed countries that receive ODA financing
have tended to increase their efforts in this area more
than those with relatively higher levels of development.
Bolivia, Honduras and Nicaragua, which are high-priority
ODA recipients, are cases in point.

102

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure II.3
LATIN AMERICA AND THE CARIBBEAN: RATIO OF PER CAPITA GDP TO PUBLIC SOCIAL SPENDING AS A PERCENTAGE OF GDP
(Percentages)

35

30

Public social spending (PSS)

CUB
25

URY

BRA

20

ARG

CRI
ALC a

15
BOL
COL

HON
NIC

5

ECU

PAR
PER RDO
GTM

CHI

ALC b

10
JAM

VEN

PAN

MEX

TTO
SLV

0
0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

9 000

10 000

Per capita GDP in dollars at 2000 prices

PSS 1994-1995

PSS 2004-2005

PSS 2000-2001

Linear (PSS 2004-2005)

PSS 2002-2003

Linear (PSS 1994-1995)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
aLatin America and the Caribbean, weighted average.
bLatin America and the Caribbean, simple average.

(iv) Social security and welfare continue to be the
top priority, followed by education. At the regional level,
over the long term (1990-1991 to 2004-2005) the increase
in this spending effort is equivalent to three percentage
points of GDP. Most of this increase has been channelled
into social security and welfare, followed, in order of
priority, by education and health (see figure II.4). These
allocation decisions presumably reflect a growing concern
about poverty and about protection for older adults as the
population ages.
(v) As a result of the budgetary constraints to which
governments are subject, social expenditure remains
highly procyclical, rising when GDP increases and
falling when it shrinks. This pattern not only reflects

an ill-advised macroeconomic policy, but also prevents
the implementation of a policy for offsetting social risks
during economic slumps (see figure II.5). This, in turn,
weakens the public sector’s ability to maintain a social
protection system for the most vulnerable sectors of
the population.
The figures in figure II.5 relate to weighted
average levels of GDP and spending in the region
and therefore mostly represent that which occurs in
larger countries. They may also show that the coverage
of spending has a strongly wage-related component
whose behaviour is necessarily procyclical. This is
detrimental to protection of those sectors most affected
by economic downturns.

Social Panorama of Latin America • 2007

103

Figure II.4
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PUBLIC SOCIAL SPENDING AS A PERCENTAGE OF GDP,
BY SECTOR, 1990-1991 TO 2004-2005 a
(Percentages)

3.0
18
15.9

16

Percentage of GDP

14

12.9

12
1.71

10
8

1.0

4

4.29

3.29

6.97

0.33

6

5.26

- 0.07

3.39

3.06

2

1.28

1.21

0
Total social spending

Health-care spending

Education spending

Spending on social
security and welfare

1990-1991

1992-1993

1994-1995

1998-1999

2000-2001

2002-2003

Spending on housing
and others

1996-1997
2004-2005

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
aWeighted average of the countries.

Figure II.5
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES):
ANNUAL VARIATION IN TOTAL PUBLIC SOCIAL SPENDING AND GDP a
(Percentages)

16
14

Annual variation

12
10
8
6
4
2
0
-2
-4

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Annual variation of GDP
Annual variation of total public social spending

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database and the countries’ national accounts.
aWeighted average of the countries.

104

Economic Commission for Latin America and the Caribbean (ECLAC)

B. Orientation and redistributive impact


of public social expenditure

The progressive nature of public social spending depends on the coverage achieved by the
social benefits it finances, the means of financing and the use of appropriate tools in targeting
the resources used in combating poverty and social vulnerability. Education spending has
become more progressive and access to education has improved, particularly in primary
education. The same has happened with health expenditure thanks to improvements in primarycare coverage. Furthermore, the eminently “pro-poor” nature of social welfare services has
been strengthened, although targeting difficulties persist. Social security, however, remains
highly regressive because of the continuing existence of contributory financing systems.
In sum, public social spending has a limited impact in terms of reducing poverty, but the
level of well-being of the poorest sectors is improving significantly. Social welfare currently
focuses on investing in the human capital of the recipient families.

In the presence of budgetary constraints, governments
will try to channel more resources into social services
for the lowest-income sectors. Because of budget
commitments and the nature of access to public services,
however, some components of public expenditure will
not exhibit the expected degree of progressiveness,

1.

Orientation of public social spending

Subject to certain differences between countries, public
social spending policy in recent decades has been
conducted against the background of State reforms which
have gradually increased the financing and provision
of social services in private hands, and have tended to
bring about selection by ability to contribute or to make
out-of-pocket payments.1 The orientation of public

1
2

despite governments’ best efforts and use of targeting
instruments to this end. These realities raise the question
of which population groups benefit the most from public
social spending and its various components (including
education, health care, social security, social welfare,
housing and sanitation).

social spending has had to counteract that trend.2 The
progressiveness of public social spending policies has
been increasing, to the extent that the coverage of public
services has expanded to the more depressed or isolated
geographical areas, such as rural areas. As a result, those
at low- to medium-income levels have enjoyed gradually
improving access to education, health care and sanitation.

This is due in part to their concentration in major urban areas, in sectors where the ability to pay is higher or political pressure is strong.
In the early 1990s, major efforts were made to boost the rather depressed levels of public social spending, against a background of high levels
of poverty.

Social Panorama of Latin America • 2007

2.

4
5

100
90
Education

80
70

Health

60

Public social spending b

50
40

Social
security

30
20

Primary
income

10
0

0

20

40

60

80

100

Cumulative percentage of population

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national studies.
aWeighted average for the significance of each item of expenditure in
the primary income of each country.
bIncludes education, health, social security and welfare, housing and
sanitation.

Orientation of sectoral spending

Promoting opportunities in areas considered of social
value, so that all citizens can enjoy the benefits and take
part in development, requires institutions which sustain
the principles of universality, solidarity and efficiency,
simultaneously and as a matter of priority. Although it is
vital that these principles are applied in the design and
financing, provision and regulation of social services,
there are still major dilemmas for which there are no
single solutions, especially when the involvement of
private agents is considered (see ECLAC, 2000). In fact,
there are major differences among the sectors targeted by
public social spending.
Public spending on education: progressiveness in
this area relates to increased coverage. The main efforts to

3

Figure II.6
LATIN AMERICA (18 COUNTRIES): DISTRIBUTION OF PUBLIC
SOCIAL SPENDING BY PRIMARY INCOME QUINTILES, 1997-2004 a
(Percentages)

Cumulative percentage of spending

At the same time, in the framework of direct anti-poverty
initiatives, a number of social welfare programmes have
been implemented to benefit population segments which
had traditionally been excluded and had generally suffered
from high levels of extreme poverty.
Owing to the different characteristics of investment
spending and current spending in the various sectors
—and of their financing mechanisms— two different
trends can be distinguished. Much of the increase in
social spending was directed to increasing the coverage
of a variety of social services, especially education
and health. Spending on social security also increased
significantly. The growth rates of those services have
varied from country to country and the inclusion of new
beneficiaries has followed differing patterns: the changes
have benefited the lowest-income sectors in some cases,
and medium- or high-income sectors in others.
The available data indicate that the absolute level of
progressiveness of public social spending varies a great
deal: only in three of the 15 countries under consideration
is that spending progressive, meaning that a significant
portion reaches lower-income strata (see table II.1).3
Social expenditure is not more regressive than primary
income distribution in any of the countries, however. This
shows that to a greater or lesser extent, the execution of
public social expenditure in the region does diminish
inequality (see figure II.6).

105

universalize education have been relatively recent (from
the 1980s onward, particularly in the 1990s) and have
focused on increasing the coverage of primary education.
Not until the mid-1990s were encouraging results seen
in respect of improved secondary-education coverage,
and that improvement was not free of difficulties and
deficiencies (see chapter III).
Public spending on the higher levels of education
tends to be regressive because extending the coverage of
public education at the various educational levels has led
to “top-downwards” increases in access;4 furthermore,
difficulties with access, advancement and completion
of education are greater for the lower-income strata.5
This is why countries with a variety of combinations of

Excludes the countries which recorded only spending on education (Dominican Republic, Jamaica and Paraguay).
In other words, it initially benefited higher-income sectors and then gradually expanded to the poorest sectors.
This involves a process of selection at the most advanced levels of education, favouring those who have the greatest financial resources and
who therefore experience fewer difficulties in their passage through the educational system.

106

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure II.7
LATIN AMERICA (11 COUNTRIES): DISTRIBUTION OF PUBLIC
SPENDING ON EDUCATION, OVERALL AND BY LEVEL OF
EDUCATION, BY PRIMARY INCOME QUINTILE, 1997-2004 a
(Percentages)

100
90

Cumulative percentage of spending

public and private supply in education will tend to boost
the progressiveness of spending, insofar as there are
self-selection processes for higher-income groups in the
private sector and, additionally, higher levels of access
to public education for the needier sectors.
Improvements in public-education coverage at the
different educational levels (preschool, primary, secondary
and tertiary) have gradually, over the years, enabled
the poorest sectors of the population to gain access.
Public spending on preschool education is relatively
less progressive than that on primary education, partly
because in most countries preschool education is not
compulsory. Although the better-off sectors generally use
private services, a high proportion of children from the
lowest-income sectors do not attend preschool centres.
On the other hand, access to primary education is almost
universal in the region, making it more progressive (see
figure II.7). This is less true in secondary education, with
the exceptions of Argentina, Colombia and Costa Rica.
On the other hand, public financing at the highest levels
of education tends to favour high-income groups: public
financing of tertiary education is highly regressive in all
the countries. In Brazil, Guatemala, Honduras, Jamaica
and Nicaragua, spending on higher education is even more
concentrated than primary income (see table II.16).

Preschool and
primary

80
70
60

Total education

50
40
30

Tertiary
education

Secondary
education

20

Primary
income

10
0

0

20

40

60

80

100

Cumulative percentage of population

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national studies.
aAverage weighted by the significance of each spending item in each
country’s primary income.

Box II.1
THE ROLE OF THE STATE IN THE FINANCING OF HIGHER EDUCATION

The highly regressive nature of spending
on higher education often gives rise to
questions as to the role of the State in
financing higher education, particularly
universities. A number of positions
have been taken in respect of the role
of social spending, especially when
the issue is whether all its components
must have a pro-poor bias —and must
therefore also have appropriate targeting
instruments— or whether they should
follow universalistic principles, even if it
means some of the resources being spent
on upper-income groups which could
afford to use private services. When it

comes to higher education, the high cost
of private educational institutions should
be borne in mind. If no public financing
were involved, access would be more
difficult for many young people from
middle-income sectors. Furthermore,
access for lower-income groups would
be practically impossible if there were
no such financing, as can be seen in
the study conducted in Ecuador which
measured public and private spending
on higher education. In other words,
deciding to withhold public resources
from higher education because they
mostly benefit middle-income groups

would bring about the perverse effect
of excluding the poorest students from
that educational level. It should not be
forgotten, moreover, that nowadays higher
education is of strategic importance
for the development of the countries’
economies since it promotes technological
research and development, which are
vital for maintaining and increasing levels
of competitiveness in the countries of
Latin America. Governments have the
greatest capacity for coordination and
can guide investment in human capital
in the long term.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of national studies.

Public spending on health: the composition and
location of services determine what impact they will have
in terms of equitable distribution. The redistributive effect
of health expenditure has increased, and it has become
more progressive than education spending because of the

scale of investment in preventive health care, first aid and
outpatient services in the poorest sectors of the population,
compared to spending on hospital services —which,
depending on the country, may be slightly progressive or
even regressive (see figure II.8 and table II.17).

Social Panorama of Latin America • 2007

107

Figure II.8
LATIN AMERICA (18 COUNTRIES): DISTRIBUTION OF PUBLIC
SPENDING ON HEALTH AND OF PRIMARY AND HOSPITAL CARE,
BY PRIMARY INCOME QUINTILES, 1997-2004 a b
(Percentages)
100

Cumulative percentage of spending

90

Primary care

80
70
Health spending

60
50

Hospital care

40
30
20

Primary
income

10
0

0

20

40

60

80

100

Cumulative percentage of population

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national studies.
aAverages weighted by the proportion of health spending in each
country’s primary income.
bSimple average of four countries.

The main constraint preventing hospital care from
producing redistributive effects is the high investment
cost involved in expanding its coverage. Given the cost
of purchasing and installing highly complex hospital
equipment, together with the hygiene and sanitation
services required in order to operate such centres and the
cost of maintaining specialized staff, the coverage of such
services is often restricted to areas where population density
is high and patients can afford to make co-payments. In
practice, this makes access difficult or impossible for
those who live on the outskirts of towns or in rural areas,
who generally have lower incomes.
The greatest challenge in the area of health care will
undoubtedly be to increase the coverage of hospital care,
together with finding the right way to blend contributory
regimes (linked to the formal labour market) with noncontributory ones, to avoid the replacement of the latter
by the former and reduce the mechanisms which exclude
large segments of the population. A number of attempts are
being made in the region to overcome these constraints.

6

In practice, there are a number of combinations of
health-care systems determined by the priorities of their
components.6
Spending on social security: its highly contributory
nature makes it very regressive. Social security is a key
component of social welfare systems and, as such, should
be governed by the principles of universality, solidarity
and efficiency. Nonetheless, the design of social security
systems generally makes access to benefits subject to
the ability of their members to pay contributions and,
therefore, to their labour market integration. As a result,
spending on social security is highly regressive, favouring
those who have the best labour market integration (formal
employment with greater ability to contribute).
In recent decades, as in the area of health care,
systems of social security coverage have diversified in
the countries, accentuating the tendency towards selection
which is usually linked to potential users’ ability to pay.
Unlike traditional contributory systems, private-sector
management with individual contracts has been promoted,
weakening the solidarity or distribution components
of the region’s reformed systems so that they are even
more regressive than the traditional systems. There are
some exceptions, of course, such as the Rural Social
Security system in Ecuador, which is fairly progressive
(see table II.18).
These predominant characteristics of the region’s
social security systems —in which affiliation is based on
the type of employment and is therefore financed mostly
through contributory mechanisms— tend to deny benefits
to a large percentage of the population. Consequently,
there is a growing trend towards expanding affiliation
through a rights-based approach; significantly, this requires
financing of the solidarity type. The debate on how
solidarity financing should be secured, whether through
non-contributory sources or cross-transfers within the
system to ensure access to basic social security benefits,
has been the essence of the second-generation reforms
to social security systems.
The intertemporal and intergenerational repercussions
of the costs and benefits of social security reforms lay the
foundations for future modernizations of fiscal policy. The
consequences for public social spending policies include
improved measurement, monitoring and management of
contingent liabilities and their medium-term effects.

In Argentina, for example, a public health system is combined with a social insurance system provided by the National Institute of Social
Services for Retirees and Pensioners (INSSJP) and charitable entities (non-profit bodies such as trade unions and associations of various kinds),
of a contributory nature. Colombia, however, combines public health systems which subsidize users, supply-side subsidies and a contributory
system. Reports from other countries show the existence of systems with non-contributory financing only. The differing combinations of
financing mechanisms are reflected in varying levels of progressiveness from country to country. Of course, non-contributory health-care
systems tend to be progressive and contributory ones regressive — another example of the latter is the armed forces’ health programme and
the EsSALUD programme in Peru.

108

Economic Commission for Latin America and the Caribbean (ECLAC)

Not all the national programmes analysed, however,
are designed to target the poorest population groups.
The way in which the possible beneficiaries of a social
programme are identified entails the problem of not
reaching the most marginal groups, precisely because
they do not have access to the most traditional services.8
There are also serious problems which can affect targeting
mechanisms, leading to inclusion errors in relation to
groups which were not originally selected as beneficiaries
and exclusion errors in respect of groups which should
be receiving welfare benefits.
In fact, the information collected shows that such
programmes show some degree of “leakage” towards

7
8

Figure II.9
LATIN AMERICA (11 COUNTRIES):
DISTRIBUTION OF PUBLIC SPENDING ON SOCIAL WELFARE
AND EXAMPLES OF DIRECT MONETARY TRANSFERS FROM
CERTAIN CONDITIONAL TRANSFER PROGRAMMES,
BY PRIMARY INCOME QUINTILE, 1997-2004 a
(Percentages)

100

Head of Household Plan
(Argentina, 2003)

90

Cumulative percentage of spending

Public spending on social welfare: a “pro-poor”
spending modality. Social welfare includes a variety of
social programmes such as school meals, maternal nutrition
programmes, emergency employment programmes,
monetary subsidies (on the supply or demand side) and
other direct or indirect transfers (see table II.19). Such
programmes sometimes provide or improve access to
traditional services such as universal education and
health care. Their purpose is to make up for imbalances
in access to productive resources and the labour market,
and to other social benefits.
In this type of spending, targeting acts as a principle of
social policy to prioritize a minimum level of services for
the poorest sectors. It should also apply a countercyclical
approach, expanding benefits at times of economic crises in
order to contain or reduce falls in the levels of well-being
in sectors which are vulnerable to the economic cycle.7
Generally, spending on social welfare in the region is fairly
progressive. On average, 55% of the resources spent on
social welfare are captured by the poorest 40%, and 60%
of that amount goes to the poorest quintile. Among the
most progressive spending is that used for anti-poverty
programmes, particularly those using conditional transfers
(see figure II.9).

Oportunidades
(Mexico, 2002)

80

Chile Solidario
(Chile, 2003)

70
60

Total social welfare
50
40
Human Development Bond
(Ecuador, 1999)

30
20

Primary income
10
0

0

20

40

60

80

100

Cumulative percentage of population

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national studies.
aAverage weighted by the significance of each spending item in each
country’s primary income.

higher-income sectors. Thus, the extent to which a
programme can be described as pro-poor depends both on
the goal of the programme and the methods for selecting
beneficiaries, and on failures of those mechanisms. While
it is important to improve targeting instruments to optimize
the use of funds in favour of those who need them most,
it is also necessary to raise the cost-efficiency ratio of the
various social programmes.

Although the principle of targeting should predominate during normal periods of economic growth, it may be necessary during economic crises
to extend social welfare to higher-income sectors in order to contain or lessen falls in levels of well-being, which are often very sharp.
For example, in some countries the definition of social welfare includes various subsidies in relation to housing and access to basic services.
Furthermore, there are a number of difficulties in targeting social welfare programmes towards the poorest sectors of the population. In many
cases, the target population groups are defined in terms of their access to various social services such as schools, health centres, hospitals and
municipal employment agencies.

Social Panorama of Latin America • 2007

109

Box II.2
SOCIAL POLICY AND REDUCTION OF POVERTY: OPTIMIZING SOCIAL SPENDING

In order to strengthen the analysis and
knowledge traditionally provided by the
Social Development Division through the
statistics —and sometimes descriptive
chapters— on social spending which are
included in the successive editions of
the Social Panorama of Latin America,
it was decided that a work proposal
should be drafted on the basis of these
results. This led to the project entitled
Social policy and reduction of poverty:
optimizing social spending, as a first
step to contribute to the effectiveness
of the governments of the region in
the formulation and implementation of
public programmes to eliminate hunger
and reduce poverty. The objective of
this project, conducted with financial
support from the German Agency for
Technical Cooperation (GTZ), is to
develop methodologies to improve
the effectiveness and efficiency of
public policies through evaluation and
analytical disaggregation of resources to
improve their allocation in the medium
and long terms.
The statistical data available in the
Division show that over the past 13 years,
the regional average of social spending
has risen by more than two percentage

points to 15% of GDP, with the fastest
growth in spending on social security
and welfare. Analysis shows that over
half the growth in per capita social
spending is due to overall GDP growth
and the increase in macroeconomic
priority and, to a lesser extent, results
from specific targeted spending policies.
Although social spending as a whole is
progressive, the breakdown of growth
factors shows that even in situations
where the fiscal priority given to social
spending is falling, there can be a
progressive effect if it is applied in
sectors with procyclical impacts such as
education, especially primary education,
and health care. Similarly, some elements
of social security spending are of greatest
benefit to the higher income quintiles,
although they represent only a limited
supplement to primary income. In the
lower income quintiles, however, social
spending on education and health care
complement primary income by close
to 50%, but the impact is lower in the
poorest countries owing to reduced
levels of social investment. Thus, shared
methodological tools and precise and
standardized quantification of social
expenditure items provide the means

to improve the quality of policies, the
transparency of management, and the
impact of social spending on the most
vulnerable sectors.
The current project is intended to help
improve social management by means
of an analytical model for the effective
assessment of the cost/impact ratio of
each country’s social programmes in
a way that will be comparable regionwide. The proposed analysis model
harmonizes the development of satellite
accounts through the joint exploitation
of government finance statistics and the
System of National Accounts, in order to
strengthen the analysis of social spending.
The analysis of social administration and
its results seeks to make use of impact
analysis through the assessment of specific
programmes and of censuses, household
surveys and similar sources. Thus, the
aim is to move forward with a number of
categories such as function, social sector,
type of cost and source of financing, as
well as eliminating differences in coverage
and classifications and contributing a
functional framework which will make
possible a deepening of the analysis and
presentation of the results, means and
beneficiaries to be reached.

Source: Rodrigo Martínez and Ernesto Espíndola, “Gasto social en América Latina: una propuesta para su análisis”, a document presented
at the technical meeting “La medición del gasto social: avances y desafíos metodológicos,” Santiago, Chile, Economic Commission for Latin
America and the Caribbean (ECLAC), 9 and 10 August 2007.

3.

Redistributive impact of public social spending

In the area of public social spending, both targeted interventions
and those of a more universal nature seek to produce a positive,
and if possible permanent, impact on the living conditions of
the population. The effects are however difficult to assess,
since they may be in the form of: (i) A social impact on
the target population, reflected in variations in the social

9

indicators representing the problems which brought about the
intervention; (ii) A medium- to long-term economic impact
resulting from transfers of goods and services to households;
and (iii) A redistributive effect insofar as the spending helps
to increase households’ disposable income and, in the short
term, to alter the distribution of primary income.9

The analysis should include the net estimate of the changes in income resulting from taxation policies (direct and indirect taxes), which can
decrease it in a progressive or regressive way, followed by its redistribution in the form of public spending, which increases it. The information
available reflects only the latter situation.

110

Economic Commission for Latin America and the Caribbean (ECLAC)

The room for manoeuvre that public policy has for
increasing the progressiveness of social spending is limited,
as the distribution of certain spending items that make up
a large proportion of resources (such as social security)
are the result of long-standing contractual commitments.
While the orientation of the various spending items may
vary, their ultimate redistributive impact depends on the
volume of resources used.10 In addition, the targeting of
expenditure in areas like education and health depends
on the level of coverage and on widespread access to
public services. It also depends on the development of
public-private partnerships to guarantee both access for
the poorest groups, as well as high-quality yet affordable
private options for those with fewer resources; this requires
agreement on which components should be stressed, in
accordance with the principle of universality and which
expenditure should be targeted. Also, in light of the
principle of efficiency in resource allocation, decisions
have to be made on how to set up solidarity-based and
non-contributory mechanisms for benefits that should be
universal in a social protection system.
It must be recognized that public social spending has
only a limited redistributive effect in terms of reducing
income concentration. This is mostly because it represents
only 19.4% of primary household income, but also because
it is not allocated for the sole purpose of improving equity.
Social spending provides a dramatic boost to the wellbeing of the poorest sectors: on average it doubles the
disposable income of the poorest quintile. Nonetheless,
it also has significant effects on higher strata, particularly
the second quintile, whose income is raised by 43%. For
the wealthiest quintile, social spending increases income
by 9% (see figure II.10). Thus, while social spending does
not have a significant redistributive effect on inequality,
it has a considerable impact in increasing the well-being
of the lowest income groups.
It should be noted that, given the nature of the
components of public social spending, the richest quintile
captures some 28% of the resources allocated for social
purposes, followed by the fourth quintile (18.8%). The
first quintile receives only about 18.6%. This is mostly

10

Figure II.10
LATIN AMERICA (18 COUNTRIES): REDISTRIBUTIVE EFFECT OF
PUBLIC SOCIAL SPENDING ON INCOME, BY PRIMARY INCOME
QUINTILE, 1997-2004 a
(Percentages)
Total income of quintile V = 100
100

9%

90
80
70
60

91%

50
40
16%

30
22%

20
10

30%
70%

Quintile I

0

51%
49%

Quintile II

yprim

78%
Quintile III

84%

Quintile IV

Quintile V

Social spending

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national studies.
aAverage weighted by the significance of each spending item for
primary income in each country.

due to the fact that the richest quintile receives over 50%
of social security spending (resources distributed on the
basis of contributory systems).
Measuring the effect on household incomes, public
spending on education has the greatest impact on the
primary income of the poorest sectors, representing 40%
of the transfers received by the first quintile (7.4% of
social spending) (see figure II.11). Next in importance
are health and social welfare, respectively. The ratio is
similar in the second quintile. Social security begins to
take on greater relative significance in the third quintile.
The most significant transfers are seen in the fourth and
fifth quintiles, rising to 59% of public resources captured
by the highest income quintile. If social security is
excluded, the richest quintile receives only 17% of total
resources, while the poorest quintile receives just over 24%
(1.4 times more than the highest quintile).

In this way, there can be spending items or specific programmes which are highly progressive, but their redistributive impact may be only
modest, so that they are not very significant in terms of increasing disposable income. This does not mean that they are unimportant in combating
poverty or improving the standard of living of the lower-income sectors; low-cost actions (such as the distribution of food rations to combat
or prevent child undernutrition, or the various conditional transfer programmes) often have a significant social impact in terms of improving a
specific situation or reducing risks which in the long term can entail significant costs for households or the State. On the other hand, there are
also social spending items which concentrate large-scale expenditure, with an improved redistributive effect, but do not necessarily lead to a
significant improvement in various social indicators.

Social Panorama of Latin America • 2007

111

Figure II.11
LATIN AMERICA (18 COUNTRIES): BREAKDOWN OF SPENDING
BY PRIMARY INCOME DISTRIBUTION QUINTILES, 1997-2004 a
(Percentages of total social spending)

Total social spending = 100

30

1.1
0.9

25
20
3.3
15

0.8
2.0

10

5.1

5

7.4

2.1
0.9

1.6
1.1

1.3
1.4

16.5

4.3

6.3

4.7

4.2

4.0

3.7

6.5

6.3

5.9

5.8

Quintile II

Quintile III

Quintile IV

Quintile V

2.8

0
Quintile I

Education

Health

Social security

Hounsing

In short, primary income distribution in the region is
highly concentrated (Gini coefficient of 0.476 by quintile
group) and, although public social spending affects total
disposable income and its distribution among primary
income quintiles —making it possible to assess both
its impact on income deconcentration and its relative
redistributive effectiveness— its effects in terms of primary
income redistribution are limited.11 As a result, Latin
America has the world’s worst record for socio-economic
inequalities. According to the measurements used (see the
methodological note at the end of this chapter), the total
of social spending items reduces income concentration by
0.064. This means that income concentration, including
public social spending transfers, is reduced only slightly
(to a Gini coefficient of 0.412).

Social welfare

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of national studies.
aAverage weighted by the significance of each spending item for
primary income in each country.

4.


Social welfare spending and
anti-poverty programmes

In accordance with the reduced redistributive effect
of public social spending, the authorities in the region
continue to be concerned at the persistence of large pockets
of poverty and numbers of people who are left out of the
benefits of economic growth.
On the basis of experiences with social investment
funds —the purpose of which was to finance public
investments in small projects identified, requested
and executed, fully or in part, by local groups of poor
people— and of social protection networks —which
served as emergency programmes to overcome the impacts
of crises— the authorities are now promoting what are
known as conditional transfer programmes.
These programmes, implemented in Latin America in
recent years, use social welfare programmes not only to
alleviate poverty but also to combat its intergenerational
reproduction by supporting families’ investments in
education, health and nutrition. The aim of the conditional

11

transfers is to produce the incentives needed to maintain
and increase investment in human capital among poor
individuals and families (ECLAC, 2000).
(a) Characteristics
Outstanding among their main characteristics is the
fact that they are multidimensional interventions,
combining increased monetary incomes in the short
term with the goal of building human capital in at
least one of its dimensions. The differences lie in the
dimensions selected for intervention (mainly education,
health and nutrition) and their combination, in the
conduct of supply-related interventions, in order to
ensure the provision of quality services, and in the
level of coordination of transfers with general social
welfare mechanisms.

The public social spending items which have the greatest redistributive impact, given their progressiveness and their effect on primary income,
are education and health care. Those which contribute the least to reducing inequality are, of course, social security and housing expenditure.
Nonetheless, in terms of relative redistributive effectiveness, the expenditure which proportionally produces the greatest primary income
redistribution is social welfare, followed by health care. Table II.6 details this information in relation to Latin America as a whole and each of
the countries.

112

Economic Commission for Latin America and the Caribbean (ECLAC)

The formula for calculating the value and structure
of the transfers varies among the different countries
implementing conditional transfer programmes. In the
case of programmes with education components, in some
countries the transfers cover the direct costs of sending
children to school (such as enrolment, transport and
supplies) and the opportunity cost resulting from the loss of
income resulting from the decision to send them to school
instead of work; this is the case in Jamaica and Mexico.
In low-income countries, the transfers generally cover
those costs partially (Rawlings and Rubio, 2003).
The new transfer programmes consider the family
as the basic intervention unit and allocate a significant
role to women as the direct recipients and managers of
the transfers within the family group (Villatoro, 2005a).
The policy of delivering transfers to women appears to be
a good approach from the viewpoint of the use of funds,
since women are more efficient than men in managing
the financial aid.
The sustainability of financing systems for conditional
transfer programmes has become critically important,
since many of these initiatives —which initially were of a
temporary nature— now constitute permanent components
of the poverty reduction strategies of some countries in the
region. The available information, however, suggests that
transfer programmes targeting the poorest sectors are subject
to considerable budgetary vulnerability. The evidence shows
that many welfare programmes are being financed wholly
or partially through external borrowing, which represents a
risk for their medium-term financial viability and restricts
their independence in terms of the design and flexibility
of their implementation (Villatoro, 2005b).
These programmes have become very significant. There
are three different types, depending on the breadth of their
coverage: those which reach over 20% of the population
(Brazil and Mexico); those which cover between 6% and
10% (Chile, Costa Rica, Dominican Republic, Ecuador,

Honduras and Jamaica); and those where the proportion
is under 6% (see table II.2).
As for their impact on poverty, conditional transfer
programmes have achieved mixed results. In some cases
they have narrowed the poverty gap which affects poor
families, and in others they have alleviated the consequences
of economic crises. There is some doubt as to whether
they can enable recipients to move above the poverty
line, although the probability of this occurring will clearly
depend on the amounts of transfers, the targeting of the
programme and the absence of economic contractions
(Villatoro, 2005c).
Furthermore, these programmes have made great
contributions to the building of human capital. As for
their educational impact, assessments have shown that
conditional transfer programmes have positive impacts in
both the short and medium terms, when indicators such as
enrolment rates and school attendance, grade promotion
and increases in the number of years of schooling are
taken into account. There have also been favourable
effects, although to a lesser degree, in terms of reducing
child labour. The overall impact in terms of health and
nutrition is positive: significant improvements have been
observed in preventive health check-ups, access to health
services and the use of outpatient care, as well as greater
consumption of high-calorie and high-protein foodstuffs
and a more varied diet (ECLAC, 2006c).
(b) The challenges of conditional transfer
programmes
The following five aspects remain central to the debate
on conditional transfer programmes: calculating the
amount of monetary aid; monitoring the counterpart
contributions; psychosocial components of the programme;
programme exit criteria; and assessment and monitoring
mechanisms.

Box II.3
EARLY CONDITIONAL TRANSFER PROGRAMMES

Conditional transfer programmes were
pioneered by Brazil and Mexico, which
are among the few countries in the region
that had no social investment funds.
The first such programmes in Brazil
appeared around 1995, with the Programa
de Garantia de Renda Famíliar Mínima
and the Programa Bolsa Famíliar para
a Educação. By 2001 there were more
cash transfer programmes, including the

School Scholarship Programme, the
Programme to Eradicate Child Labour
(PETI), the Federal Minimum Income
Programme, Bolsa Alimentação, Agente
Jovem and Auxílio-Gás. Currently,
the multisectoral Zero Hunger plan
includes Cartão Alimentação, the
Emergency Nutrition programme, a
nutritional education programme, a
workers’ nutrition programme, anti-

undernourishment initiatives and
Bolsa Familia.
In Mexico, beginning in 1988, the
authorities responded to high levels of
poverty by creating a series of major social
programmes which gave a distinctive
character to the country’s social policies.
The first was the National Solidarity
Programme (PRONASOL) (1989-1994). The
problems that arose with that programme

Social Panorama of Latin America • 2007

113

Box II.3 (concluded)

and the social impact of the economic
crisis which struck the country in 19941995 made it necessary to implement
a substantial reform of its anti-poverty
programmes. This gave rise to the basic
food basket programme for family wellbeing, based on monetary transfers using
an electronic card to be used at food

shops affiliated with the programme;
the condition was that pregnant women,
breastfeeding mothers and children aged
under five must attend check-ups at health
centres. In 1997, on the basis of that
programme, the Education, Health and
Nutrition Programme (initially “Progresa”,
now “Oportunidades”) was created.

It was designed to deal with targeting
problems and other shortcomings of
the instruments which had so far been
used in combating poverty, improving the
supply of health and education services
(particularly in the most disadvantaged
areas) and promoting their use by means
of cash transfers.

Source: Rolando Franco and Ernesto Cohen, “Los programas de transferencias con corresponsabilidad en América Latina. Similitudes y
diferencias”, Transferencias con corresponsabilidad. Una mirada latinoamericana, R. Franco and E. Cohen (comps.), Mexico City, Latin American
Faculty of Social Sciences (FLACSO), 2006.

A crucial issue in the design of conditional transfer
programmes in the field of education is determining the
amount of monetary aid. Methods differ considerably
from one programme to another. Perhaps the optimal
way of setting an amount to promote school attendance
and the eradication of child labour is to estimate it on
the basis of the opportunity cost of sending children to
school. If we consider that that cost may increase with the
children’s age and may also be higher in the case of girls,
the reasonable choice would be to establish larger transfers
for adolescent girls and girl children, as is the case in the
Oportunidades programme (Villatoro, 2005c).
Another important challenge is the monitoring
of counterpart contributions. In practice, they are not
monitored under all conditional transfer programmes,
although they are crucial to the thinking behind such
programmes. This omission is due to the fact that the
monitoring would make managing the programme more
expensive and it is difficult to implement, may lead to
problems if an attempt is made to withdraw the transfer
from those who fail to comply, and may incite those whose
job it is to certify compliance to levy a charge for issuing
the certificate (Franco and Cohen, 2006).
Studies conducted within the PETI and Oportunidades
programmes showed that families continued to attach only
limited value to education and did not believe that child
labour was harmful for their children’s future opportunities.
This shows the importance of complementary psychosocial

interventions which seek to change such perceptions (World
Bank, 2001; González de la Rocha y Escobar, 2002).
Exit strategy is also important. Disconnection between
the programme and a recipient family may occur for three
reasons: (i) When it is proved that the family should not be
benefiting, because of its income; (ii) When it fails to comply
with counterpart contributions, or (iii) When the maximum
period of connection, if any, is completed. Nonetheless,
disconnection should take place at a time when the families
do not need the transfers. There appears to be a contradiction
between the period of connection to the programme, for which
a limit is generally set (four years in the longest programmes),
and the time needed for the accumulation of the human capital
needed to fulfil the programme’s goals.
The wide variety of periods set by different programmes
suggests that they are not based on criteria resulting from
any theoretical exercise or empirical test as to when the
incentives or psychosocial support begin to take effect.
It seems that the timing of exit from the programme may
have been determined more by financial criteria than on
the basis of whether the interventions have yielded results
during the selected period (Franco and Cohen, 2006).
Lastly, there is still a need to improve the development
and application of systems for the monitoring and
assessment of results as a basis for effective programme
management. and to conduct comparative evaluations to
determine the relative efficiency of various programmes
and policies (Rawlings and Rubio, 2003).

114

Economic Commission for Latin America and the Caribbean (ECLAC)

Box II.4
CONDITIONAL TRANSFERS IN CUBA: A COMPREHENSIVE IMPROVEMENT COURSE FOR YOUNG PEOPLE

The comprehensive improvement course
for young people is one of the programmes
that have the greatest social impact, owing
to its high level of popular acceptance
and the positive changes it has brought
about in the behaviour of the young
people who have taken part. Its goal
is to encourage young people aged
between 18 and 30 to return to work or
to full-time schooling when they have
dropped out for some reason. The goal
is for them to be reintegrated into the
appropriate level of education (primary,
middle school or high school) until they
reach higher education or return to work.
The young people involved receive a
monthly income of between 80 and 150
pesos, or 36% to 67% of the minimum
wage for Cuban workers, depending on
the year of study and the educational
level they have attained.

This programme has proved to be
a good choice for young people who
have dropped out of education or work,
since it plays a positive preventive role
which contributes to improving the
social climate.
This initiative was implemented
initially in 2001 in the eastern part of
the country, and was then extended
to all the provinces thanks to its high
level of social acceptance. The teaching
takes place in functioning educational
establishments, so that existing facilities
and audio-visual and computer equipment
can be used. Resources are allocated
for the printing of teaching materials,
classes are given on the educational
channel of Cuban television, and other
materials are used, especially the courses
of the University for All programme. The
necessary books are available from the

establishments’ school libraries and at
the information centres in the various
parts of the country.
Attendance at these courses is
high, and the lessons take place five
evenings a week. The student retention
rate is about 90%. When students drop
out, it is mostly because they have found
jobs, are entering active military service
or transferring to other courses.
Annual enrolments in this programme
have remained above 100,000 students
since 2002. In the academic year 20062007, the number rose to over 110,000.
All those graduating from this programme
have the opportunity to move on to
university studies.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the Educational Department of
the Ministry of Education and the National Statistical Office, Anuario estadístico. Cuba 2006, Havana.

Social Panorama of Latin America • 2007

115

C. Public social spending by groups of countries:


towards a composite typology

Public social spending policies have to take into account the constraints imposed by
inequalities and budgetary restrictions. Grouping the countries of Latin America and the
Caribbean according to the maturity of their labour markets and their stage of demographic
transition is helpful in that task. The former affects the number of workers contributing to
the financing of a contributory social insurance system; the latter determines the level and
the structure of dependents.
One aid to understanding the challenges of social policy
funding is a new indicator of dependency between
citizens employed in the formal sector and the rest of the
population.12 The purpose of this indicator is to assess the
potential capacity of the social protection systems paid
for by formal workers through contributory mechanisms

to meet the needs of those people who do not have direct
access to that type of social security. The indicator makes
it possible to define countries according to their level of
development and the stages they have reached in terms
of demographic transition and maturity of the labour
market (see figure II.12).

Figure II.12
NUMBER OF DEPENDENTS PER FORMAL WORKER AND PER CAPITA GDP
11
10
BOL

Number of dependents per formal worker

9

HND
PRY

8

GROUP I

ECU
JAM
NIC
GTM

PER

7
SLV

6

Latin America (simple average)
COL
VEN

5

DOM
PAN

4

GROUP II

Latin America (weighted average)
MEX
URY
BRA

CRI

ARG
CHL

3

GROUP III

2
1
0
0

5 500

11 000

16 500

Per capital GDP in purchasing power parity terms (dollars at 2000 prices)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries and World Bank, “World Development Indicators” [online database] http://devdata.worldbank.org/dataonline/

12

Ratio of children under 15 years of age, older adults, non-workers, the unemployed and informal workers to every worker employed by the
formal sector. See ECLAC/SEGIB, 2006.

116

A first group of countries can be defined, with per
capita GDP of under US$  5,500 (purchasing power
parity (PPP) of 2000), that are at an early stage in terms
of demographic transition and labour market maturity.
Such countries have high levels of dependency for every
formal worker, with needs mainly concentrated among
young people and the underemployed. The second group
of countries has surpassed the development threshold
of per capita GDP equivalent to US$ 5,500, but they
are still trailing in the demographic transition and
maturing of their labour markets, with between 4.5 and
6 dependents per formal worker. In these countries, the
needs of young people remain paramount although they
are less acute, while non-workers and the underemployed
make up a larger proportion. Like the second group, the
third group of countries has exceeded the US$ 5,500
threshold for per capita GDP; but it has between 3 and
4.5 dependents for every formal worker. The burden
of young people’s needs remains high, and those of
the underemployed, non-workers and older adults are
also considerable (see table II.3).
This typology shows six characteristics of the implicit
social contracts that govern the allocation of expenditure.
First, transition societies in group II have needs that are
increasingly similar to those of group III, but with a
spending structure that remains more like group I, with
a marked lack of spending on social security and welfare
(see table II.3, columns 7 and 8).
Second, irrespective of their level of development,
all countries allocate a relatively similar percentage of
public social spending to health spending. Spending on
housing, however, falls in proportion with the rise in a
country’s level of development. Health spending represents
around 20% of public social expenditure. Social spending
on housing, on the other hand, differs according to a
country’s level of development and dependency ratio
(see table II.3, column 8).

Economic Commission for Latin America and the Caribbean (ECLAC)

Third, the biggest contrast in the groups of countries
is between the allocation of resources for education
and those for social security and welfare (see table II.3,
column 8). The countries in groups I and II allocate the
largest percentage of their spending to education, between
30% and 40%, and the remainder to a combination of
social security and welfare and housing (especially the
former). In the countries of group III, spending on housing
represents a mere 5% of the total, whereas they allocate
over 50% to social security and welfare.
Fourth, the less developed countries made more effort
to increase the public funding channelled into social policy
between 1990-1991 and 2004-2005 (see figure II.13). In all
countries, the main priorities are social security and welfare,
followed by education. This represents growing concern over
the financing of retirement and pension systems as well as
the priority governments attach to improving the coverage
and quality of education. Despite this progress, groups I and
II still lag far behind in spending on social security, welfare
and health in relation to the levels of expenditure of the
countries in group III with their ageing societies.
Fifth, all three groups of countries tend to manage
public social spending on a completely procyclical basis
(see figure II.14). This relates to the significance of
wage expenditure in the countries, as well as the need
to maintain macroeconomic and fiscal balances and
manage country risk. Only the group I countries display
a countercyclical trend, owing to the nature of official
development assistance (ODA) and of the aid they receive
in response to natural disasters.
Sixth, the increased social security coverage observed
in countries which are more developed and more advanced
in the ageing process implies that greater resources are
devoted to programmes which have no notable impact on
reducing inequality. Nonetheless, as countries increase
social security coverage, the regressiveness of spending on
such programmes diminishes (see table II.3, column 9).

Social Panorama of Latin America • 2007

117

Figure II.13
TRENDS IN PUBLIC SOCIAL SPENDING BY GROUPS OF COUNTRIES, PERCENTAGES OF GDP
25

Group I: Bolivia, Honduras, Jamaica, Ecuador, Guatemala, Paraguay, El Salvador, Peru

Percentage of GDP

20

15
3.4
10

8.6
1.3

1.3

5.2

0.4

5

0.3

3.6
2.3

1.7

1.2

2.7
1.3

0.7

0.4

0
Total social spending

Health spending

Education spending

1990-1991

1992-1993

1994-1995

1996-1997

Social security spending

1998-1999

2000-2001

Housing and other spending

2002-2003

2004-2005

Group II: Venezuela (Bol. Rep. of), Panama, Dominican Republic, Mexico and Trinidad and Tobago

25

Percentage of GDP

20

15

3.8
10.8

10
6.9

1.2
2.2

-0.1

5

0.5

4.0
2.8

2.5

2.9

2.4

0

Total social spending

1990-1991
25

Health spending

Education spending

1992-1993

1994-1995

1996-1997

Social security spending

1998-1999

1.5

1.0

0.7

2000-2001

Housing and other spending

2002-2003

2004-2005

Group III: Brazil, Costa Rica, Uruguay, Chile and Argentina

2.4

20.5
20

Percentage of GDP

18.1

15

1.4

10.7
9.3

10
0.8
0.7
5

4.4

3.6

-0.5

4.4

3.7

1.5
0

Total social spending

Education spending

1990-1991

1992-1993

1994-1995

Health spending

1996-1997

1998-1999

Social security spending

2000-2001

2002-2003

1.0
Housing and other spending

2004-2005

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.

118

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure II.14
SPENDING TRENDS OVER THE BUSINESS CYCLE

Annual variation (percentages)

Group I : Annual variation of total public social spending and total gross domestic product
25
20
15
10
5
0
-5
-10
1991

1992

1993

1994

1995

1996

1997

1998

Total gross domestic product

1999

2000

2001

2002

2003

2004

2005

Total public social spending

Annual variation (percentages)

Group II : Annual variation of total public social spending and total gross domestic product

25
20
15
10
5
0
-5
-10

1991

1992

1993

1994

1995

1996

1997

1998

Total gross domestic product

1999

2000

2001

2002

2003

2004

2005

Total public social spending

Annual variation (percentages)

Group III : Annual variation of total public social spending and total gross domestic product

25
20
15
10
5
0
-5
-10

1991

1992

1993

1994

1995

1996

1997

1998

Total gross domestic product

1999

2000

2001

2002

2003

2004

2005

Total public social spending

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.

Social Panorama of Latin America • 2007

119

D. Public spending and the social contract
To comply with legal requirements for economic, social and cultural rights, social contracts
need to overcome constraints relating to budgeting and inequity, perhaps by allocating greater
resources to education and health in order to ensure education for children and young people
in the countries of group I, to family support in order to reconcile gainful employment and
care work in the home in the countries of group II, and initiatives to provide basic guarantees
in the area of pensions in the countries of group III. They will also need to make progress in
reducing the procyclical nature of the management of public social spending.

The societies of Latin America cannot ignore the
challenges relating to changes in their risk profiles and the
characteristics of public social spending. Social changes
are forcing the authorities to design viable strategies to
meet new needs without having satisfied the earlier ones.
They must continually seek solutions to the problems
resulting from current patterns and modalities in public
social spending and their relationship to the population’s
need profiles and social risks.
A number of reforms have been introduced in the
region to close the gap between social needs and the
funding of social welfare systems. The creation of mortgage
management sectors has resulted in a gradual handover
of housing provision from the public to the private sector,
with financing now in the hands of families supported by
State subsidies. The same has happened with education
in the most developed countries, where private supply
has grown to meet the demands of high-income groups.
Many countries have changed the funding and provision
of social security and health benefits which are based on
workers’ contributions to social security systems.
In light of the constraints affecting the countries, it
may be useful to measure the authorities’ willingness to
finance social spending. This involves dividing sectoral
social spending among the target population and, once

13

14

the “spending per target population” has been determined,
expressing that spending as a percentage of per capita
GDP.13 This calculation shows that the willingness to
allocate resources to education is very similar in the three
groups of countries (the simple average of spending per
minor aged under 15 years varies from 12% to 16% of
per capita GDP among the three groups. The final result
depends, however, on each country’s level of development.
“Spending by target population” allocated to education is
only US$ 202 (US$ 476 at purchasing power parity (PPP)
of 2000) in group I, compared with US$ 598 (US$ 977 at
PPP of 2000) and US$ 902 (US$ 1,557 at PPP of 2000) in
groups II and III, respectively.14 The conclusion is that the
countries in group I need to overcome a huge gap in the
funding of education for children and young people (see
table II.4 and figure II.15).
It is noteworthy that, despite rising numbers of
working-age adults and older adults, the countries’ spending
structures are unchanged. While the structure in the countries
of group II is not changing in relation to that in group I,
in the countries of group III there is a considerable rise
in willingness to fund social security and welfare and,
to a lesser extent, health care. Comparing the “spending
per target population” on health with per capita GDP, the
willingness to fund that expenditure in the countries of group

This refers to total sectoral spending divided among the target population. The following criteria have been used for this analysis: young people
aged under 15 years in the case of education, people aged 15 and above in the case of social security and welfare, and the total population in
the case of health.
In all cases, these levels of spending by target population are very low compared with international standards, so public education cannot be
considered as a factor of upward social mobility. The United Nations Educational, Scientific and Cultural Organization (UNESCO) recommends
that 5% of GDP should be dedicated to education spending, but the figures analysed here reveal much lower percentages.

120

Economic Commission for Latin America and the Caribbean (ECLAC)

I is equivalent to 2.3% of per capita GDP. The percentage
is 2% of per capita GDP in the countries of group II, but
almost double that amount (3.7% of per capita GDP) in
the group III countries. The gaps are much wider in respect
of social security and welfare spending. Expenditure in
that area is equivalent to 3% and 4% of per capita GDP
in groups I and II, and 12.3% of per capita GDP in group
III. Once again, the levels of development attained by the
countries affect the final amount of spending allocated per
person in the target group. In dollars at 2000 prices, health
spending is US$ 33 in group I, three times that amount at
US$ 103 in group II, and almost seven times more in
group III, at US$ 202. The gaps are much wider in the
areas of social security and welfare, where expenditure
amounts to US$ 48 in group I, four times that amount
at US$ 197 in group II, but 14 times higher in group III,
standing at US$ 685 at 2000 prices.
These gaps sum up the objective factors relating to
differences in levels of development, stages in demographic
transition and the maturity of labour markets in the
different countries, which ultimately affect the coverage
and quality of social protection services in public health,

social security and welfare. These in turn reflect the
constraints on the authorities’ attempts to promote access
to social protection services in order to provide highly
diverse populations with entitlement to economic, social
and cultural rights. The social contract must assume
responsibility for these issues and lay the foundations
for reforming social protection systems and promoting
universal access to the corresponding services.
The above analysis reveals three characteristics of
implicit social contracts (see figure II.15 and table II.4).
First, with the exception of countries eligible for international
development assistance or, incidentally, disaster relief, the
spending is restricted by each country’s level of development,
and development gaps therefore tend to be reflected in social
protection gaps. Second, despite the priority allocated by
the three groups of countries to the education of young
people and the health of the population, the inclination to
give greater protection to those sectors increases with the
level of development. Third, social security and welfare
programmes to serve other vulnerable groups (employment,
ageing, poverty alleviation) become more significant as
the level of development rises.

Figure II.15
LEVELS OF PER CAPITA GDP AND SOCIAL SPENDING BY TARGET POPULATION
(United States dollars)
1 000

Per capita GDP; 5 575
Education spending; 902

Per capita GDP; 4 872

5 000

800
Social security
and welfare
spending; 685

4 000

700
600

Education spending; 598

500

3 000

2 000

1 000

900

Social security
and welfare
spending; 197
Per capita GDP; 1 637
Social
security
and
welfare
spending;
48

Health spending; 202

Education spending; 202

300
200

Health spending; 103
Health spending; 33

GPS per cápita; 477

GPS per
capita; 994

Per capita PSS; 147

0
Group I

Per capita GDP

400

Spending by target population

GDP and social spending per capita

6 000

0
Group II

Per capita PSS

Health spending

100

Group III

Social security and welfare spending

Health spending

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database and population estimates by the Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC.

In addition to these characteristics, evolution over
time shows that public social spending continues to be
implemented with a strong procyclical bias. The region’s
growing integration into world markets has led to expenditure

policies being linked to the business cycle in order to avoid
jeopardizing the countries’ access to credit markets. In a
way which is contrary to the nature of a social protection
programme, spending increases during boom periods and

Social Panorama of Latin America • 2007

121

falls during recessions; thus, it fails to act as a compensating
mechanism for groups which are vulnerable to the business
cycle. To rectify this trend, major agreements are needed
on the responsibilities of public finances in the course

of the cycle. One clear exception is the establishment of
policies for fiscal surpluses during periods of strong growth,
giving greater stability to social spending during periods
of economic slowdown, as in the case of Chile.

Box II.5
COUNTERCYCLICAL POLICIES IN CHILE

The countercyclical role played by public
social spending in Chile in recent years
is the result of the implementation of
a fiscal rule based on the preservation
of a structural surplus of 1% of GDP.
Its application has brought stability to
the conduct of public policies which,
together with the maintenance of the

one hand, stability, and on the other, the
capacity for countercyclical action and
credibility as a medium-term signal. By
stabilizing levels of public spending,
the structural-surplus rule has made it
possible to continue increasing public
social and investment spending, and this
has given legitimacy to social policy. Its

This rule has laid the foundations for
other fiscal policy modernizations in relation
to measures designed to strengthen the
management of public finances using an
approach which is intertemporal as well as
countercyclical. This involves, for example,
improved measurement, monitoring and
management of contingent liabilities

necessary fiscal equilibria, has guided
the expectations of economic agents in
relation to the direction of fiscal policy.
The application of this rule has given
two characteristics to social policies: on

countercyclical nature has made it possible
to implement new programmes in the face
of periods of economic slowdown without
harming the fiscal equilibria which affect
views of country risk.

and their medium-term effects, as was
demonstrated in the analysis which led to
the recent pension-system reform.

Source: Alberto Arenas and Julio Guzmán, “Política fiscal y protección social: sus vínculos en la experiencia chilena”, Financiamiento del
desarrollo series, Nº 136 (LC/L.1930-P/E), Economic Commission for Latin America and the Caribbean (ECLAC), Santiago, Chile. United Nations
publication, Sales no. S.03.II.G.86.

The low levels of service provision mentioned above
show that public social spending is still insufficient, so
that families have to make huge efforts to deal with their
needs and social risks, whether through family solidarity
or out-of-pocket payments. In a number of countries,
reforms to social protection systems have expanded the
use of individual social protection contracts at market
prices, ensuring efficiency through agreements linking
the benefits to the participants’ counterpart contributions.
In order to combine efficiency and solidarity, this
system requires improved regulation and the use of noncontributory financing. These issues should be the basis
for discussions on a new contract for social cohesion,
since the current formula leaves many risks uncovered and
requires corrections to redistribute resources in favour of
the most vulnerable groups. The correct combination of
households’ individual efforts and the input of State entities
should become the nucleus of a social contract.15 What is
needed is an agreement which takes into account the ways

15

16

in which public and private funding can be combined,
using both contributory and non-contributory systems,
and identifies priorities for the principal investments in
the social field (ECLAC, 2006c).
The agenda should make a distinction between the
three groups of countries. The countries should take
account of the increasing need to take a countercyclical
approach to the management of expenditure and should
include different priorities in their respective social
contracts.16 Those in group I are still lagging in terms
of educational coverage for young people and the health
of their populations. Overcoming this deficiency will be
the basis for achieving gradual improvements in equity.
The countries in groups II and III have more scope for
considering policies to reconcile paid employment with
the needs of the home and —in cases where progress
is recorded in the privatization of social protection
systems— ensuring explicit minimum guarantees of
a universal nature. In a context of severe budgetary

In the absence of a social contract, the region has experimented with proposals designed to strengthen the market and reduce the role of the
State, which have proved to be exclusive and costly. In contrast, the Economic Commission for Latin America and the Caribbean (ECLAC) and
the Ibero-American Secretariat (SEGIB) have suggested the need for an agreement to rebuild public social policies and improve well-being.
See the recent ECLAC/SEGIB 2007 publication.

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Economic Commission for Latin America and the Caribbean (ECLAC)

constraints and considerable levels of inequality, the
countries of the region should apply selective targeting
of benefits to ensure universal access to minimum
standards of well-being. This should constitute —for

some time to come— the criterion for strengthening
integrated solidarity in social protection systems,
combining contributory and non-contributory financing
mechanisms.

Box II.6
UPDATING OF SOCIAL SPENDING

For this edition of the Social Panorama of Latin America, updated
data have been obtained for public social spending to 2005,
to match the global and sectoral series published in earlier
editions. Although data for 2006 were received from 13 of the
21 countries considered, the decision was made not to publish
them because of their provisional, estimated or incomplete
nature. Data updating took place in the first half of 2007 and
ended in mid-September.
In most cases data were collected on central government
budget execution, and information was also available in several

cases on the actual spending of bodies having an independent
budgetary setup, local governments and public non-financial
corporations. Although differences in institutional coverage make
comparisons between countries difficult, the widest available
coverage for each country has been published except when to
do so would create significant constraints in constructing a series
for the period 1990-2005. This is because the Commission’s
essential interest is in establishing, to the extent possible, the
greatest quantity of public social spending in order to represent
the efforts being made by States in this area.

The following table classifies countries according to the institutional coverage of the social spending series used.
Institutional coverage

Country

Total public sector = NFPS + FPS

Costa Rica

Non-financial public sector = GG + NFPE

Argentina, Bolivia, Brazil, Colombia and Peru

General government = CG + LG

…

Central government = GCB + AA

Chile, Cuba, Dominican Republic, Ecuador,a/ El Salvador, Guatemala,
Honduras, Jamaica, Panama, Trinidad and Tobago, Uruguay

Central government budget

Mexico, Nicaragua, Paraguay and Venezuela (Bol. Rep. of)

Where:
AA: agencies with budgetary autonomy; LG: local government; NFPE: non-financial public enterprises; FPS: financial
public sector.
Since several countries have only very recently adopted
the classification system of the Manual on Government Finance
Statistics 2001 of the International Monetary Fund, harmonized
with the System of National Accounts (SNA) of 1993, the series
for 1990-2005 is not always compatible at the subfunction
level. For this reason, only the series for total public social
spending has been published, at the level of major functions
or sectors. In certain particular cases, the change has meant a
lack of information in the complete series or in certain functions
(Bolivia from 1990 to 1994, El Salvador from 1990 to 1992, and
in the case of Trinidad and Tobago the social welfare —social
security— function from 1990 to 1999). In the case of other
countries it was not possible to construct the complete series
because of insufficient information relating to intermediate
periods: Jamaica and Trinidad and Tobago from 1997 to 1999.
In Cuba, there was a change in the base year for GDP (1997)
and the 1989-1995 series was retropolated at 1997 prices and
structures, an adjustment which had not yet, at the time this

edition went to press, been implemented in respect of the GDP
series in dollars at 2000 prices and the implicit deflators needed
for that transformation. As a result, per capita social spending
figures expressed in dollars are available only for the period
2000-2005, valued according to the country’s official exchange
rate. In Peru, whereas the 1990-1999 series corresponds to the
central government budget, the series for 2000 onwards includes
the non-financial public sector. As for public social spending,
the differences between the two types of coverage between
the years 2000 and 2003 —for which common information is
available— average 1.1% of GDP and are growing. Lastly, in the
Bolivarian Republic of Venezuela, the series relates to agreed
public social spending (the budgetary law and its modifications
at 31 December each year) rather than actual expenditure.
Since it is a federal State, the institutional coverage of data for
that country relates to the central government budget, and the
published figures may underestimate total social spending to a
greater extent than in other countries reporting that coverage.

Social Panorama of Latin America • 2007

The same is true of Mexico, but the available information on
the highly-decentralized execution of its spending show that
the figures should be studied more carefully than in other cases
because the underestimation of social spending levels may be
quite considerable (see ECLAC 2006a for some examples of the
centralized and decentralized execution of social spending).
As in earlier editions, the Social Panorama of Latin America
2007 presents social spending data on the basis of two-yearly
averages. The indicators shown are for overall public social
spending and spending by function or sector —education, health,
social security and welfare, and housing, sanitation and other
functions not included in the previous categories— as percentages
of GDP, in dollars per capita and as percentages of total public
spending. In the case of this last indicator, official information
from the countries on total public spending is used, but these
figures may differ from those based on other classification
systems (such as the economic or administrative classification
of spending) because interest payments on public debt may or
may not be included and different methodological options may
be applied to the classification of expenditure.
The figures used for the calculation of percentages are in
current prices for each year and each country. These proportions
are then applied to the GDP series in dollars at 2000 prices so
that per capita social spending can be derived, expressed in
dollars. This may result in certain variations in relation to the data
in constant currency reported by the countries, which depend
on the degree of exchange-rate appreciation or depreciation
implicit in the official parity of each country’s currency in relation
to 2000, and also on the population data on which the per capita
calculations are based.
Figures at current prices on overall and social public spending,
and the sectoral breakdown of the latter, are official data provided
by the corresponding government bodies. Depending on the
country, these may be directorates, departments, sections or
units for planning, budgeting or social policy within the ministries
of the treasury, finance or the economy. In addition, information
on budgetary execution was obtained from the countries’ general
accounting offices or treasury departments, and occasionally
from central banks, national statistical institutes, and national
social and economic information systems.
Gross domestic product in constant dollars at 2000
prices is derived from official figures contained in the Statistical
Yearbook for Latin America and the Caribbean (ECLAC, 2004c),
and population figures are taken from projections by the Latin
American and Caribbean Demographic Centre (CELADE) Population Division of ECLAC.
Measuring the redistributive impact of public social
expenditure
The measurement of the distribution of social spending and its
impact on primary income distribution, and that of the payment

123

of direct taxes and levies affecting households, present a
number of problems.
1. There are few instruments that can be used to make that
measurement and relate it to the various characteristics of
the households, particularly primary income. The main tools
for that purpose are surveys of living conditions in various
forms and surveys of household income and expenditure.
2. The various surveys and the corresponding reports tend
to differ in respect of how primary and (total) disposable
income are measured: some measure households’ income,
others their spending and in some cases their consumption
is measured. Furthermore, the figures contained in the reports
may be expressed at the household level (total or per capita
income) or at the individual level, as a percentage of the
total income of the entire universe or as average values in
the country’s currency.
3. Such instruments do not tend to allow the “primary income”
construct to be elaborated in the same way as for national
accounts, which do not take into account the payment of
taxes and levies. For surveys, what is usually declared is
net income or expenditure, with income taxes and social
security and health contributions already discounted.
4. It is not possible to measure all transfers, monetary or in
kind, and the latter tend to be valued using methods of
imputation according to the average amount of the benefits
or figures from fiscal accounts. In some cases, this may lead
to underestimation of the amount of the transfers, and in
others, to its overestimation.
5. Transfers are generally valued at factor cost (the cost to the
State of making the transfers), which may include indirect
social spending (administration, transport and other costs)
in addition to the actual transfers; the valuation is not
necessarily equivalent to the alternative cost of obtaining
the services at market prices, so this could be considered
as an underestimation of the impact of social spending.
The supply of information in this regard generally comes
from national studies specifically oriented towards this issue
and based on household surveys, and containing data for only
one year. The bibliography of this chapter lists the studies which
have been used on this occasion.
Measurements for analysing the redistributive effect
There is a series of conventional measurements of the degree of
progressiveness or regressiveness of public social spending, its
impact in terms of improving or worsening income distribution,
its contribution to each item of social spending and the degree of
relative sectoral effectiveness in reducing inequalities according
to the volume of resources involved.
One of the most widely used indicators is the Gini coefficient,
which measures the bias, or degree of concentration, of income.
Similarly, it is used for evaluating the orientation of taxation

124

Economic Commission for Latin America and the Caribbean (ECLAC)

Box II.6 (concluded)
and public spending. The Gini coefficient varies between the
values -1 and 1, where 1 represents maximum concentration
(and maximum regressiveness in the distribution of income,
taxation or public spending) and -1 maximum progressiveness
(of taxation or public spending).
The formula used to obtain the Gini coefficient of
concentration is:
N

G = 1 − ∑ (δYi −1 + δYi )× (δX i −1 − δX i )

i =0

where σX and σY are the cumulative percentages of X
(population) and Y (income or public spending), respectively.
N is the number of percentiles used to divide the population
(for example, into quintiles or deciles). For a given distribution
of income or public spending, as the number of comparison
groups is reduced, the concentration coefficient diminishes. In
this chapter, the concentration of income and public-spending
has been calculated by quintile (this is generally referred to as
a quasi-Gini). These calculations may not coincide with those
published in the respective national reports, the analyses for
which were in many cases conducted using microdata.
While the calculation of the progressiveness (or regressiveness)
of social spending is based only on the concentration coefficient
(CC) for spending, the measurement of the progressiveness
of spending in relation to income distribution is also derived
from the income concentration coefficient (Gini). In 1986,
Kakwani proposed a simple measurement known as the relative
concentration coefficient or Kakwani index (Ps), whose values
vary between -2 and 1. The index is negative when spending
is progressive in relation to income distribution, and positive
when spending is regressive in relation to it.

Where Ginii is the distribution of primary income. To
disaggregate the impact of each item of public social spending
on the trend in income concentration, the following formula
was used:
The change in income concentration
(a)

∆Gini = Gini f − Gini i

Where Ginif is income distribution after State transfers
(total disposable income).
b)

∆Gini =

Ps × γ
1+ γ

Where γ is the proportion of financial assistance in total
primary income. Given that Ps = CC − Gini i , then

(c)

∆Gini =

(CC

− Gini i )× γ
1+ γ

This identity may be used both for social spending and
for each item j (since Ginifj is the change in the Gini which
produces item j). Lastly, the relative effectiveness coefficient
(REC) is used. It corresponds to the ratio of the weight of each
item as a proportion of total social spending to its weight in
the total Gini variation.

Where n is the total of public social spending items.

Ps = CC − Gini i
Source: Economic Commission for Latin America and the Caribbean (ECLAC), Social Panorama of Latin America 2005 (LC/G.2288-P), Santiago,
Chile. United Nations Publication, Sales No. S.05.II.G.161, Nanak Kakwani, Analyzing Redistribution Policies: A Study Using Australian Data,
Cambridge: Cambridge University Press, 1986; Francisco Lasso, “Incidencia del gasto público social sobre la distribución del ingreso y la
reducción de la pobreza,” Lima, Misión para el diseño de una estrategia para la reducción de la pobreza y la desigualdad (MERPD), December
2004, unpublished.
aCorresponds to budgetary central government and evaluations of results from the Ecuadorian Social Security Institute. Results for the latter for
2005 are based on estimates.

Social Panorama of Latin America • 2007

125

Table II.1
LATIN AMERICA (18 COUNTRIES): INCIDENCE OF PUBLIC SOCIAL SPENDING BY INCOME
QUINTILE AND CONCENTRATION COEFFICIENT a
(Percentage distribution and quasi-Gini)
Income quintile a
Quintile
I

Quintile
II

Quintile
III

Total
Quintile
IV

Quasi
Gini

Sector b

Quintile
V

Argentina, 1998

21

19

19

21

20

100

-0,004

E, H, SS, W, HO, SAN, O

Argentina, 2003

29

22

19

17

14

100

-0,137

E, H, SS, W, HO, SAN, O

Bolivia, 2002

13

16

17

23

30

100

0,167

E, H, SS

Brazil, 1997

11

12

17

20

41

100

0,272

E, H, SS

Chile, 2006

43

28

18

7

4

100

-0,393

E, S, AS

Colombia, 2003

18

18

17

19

29

100

0,098

E, H, SS, W, HO, SAN, O

Costa Rica, 2004

21

19

17

17

26

100

0,027

E, H, SS, W

Ecuador, 1999

14

18

21

22

25

100

0,108

E, H, SS; W, O
(not disaggregated)

El Salvador, 2002

23

23

23

19

12

100

-0,105

Guatemala, 2000

14

18

19

21

29

100

0,131

E, H, SS, W

E, H

Honduras, 2004

20

17

18

18

27

100

0,060

E, H, SS, W

Jamaica, 1997

29

26

21

17

7

100

-0,208

E

Jamaica, 2000

20

19

21

18

22

100

0,012

E

Mexico, 2002

17

18

19

23

23

100

0,066

E, H, SS, W, O

Nicaragua, 2005

19

20

21

21

20

100

0,011

E, H, W, HO, SAN, O

Panama, 2003

15

18

19

21

27

100

0,106

E, H, SS, W

Paraguay, 1998

21

20

19

20

11

100

0,009

E

Peru, 2004
Dominican Republic, 1998

9

12

17

21

40

100

0,284

E, H, SS, W

15

20

23

23

19

100

0,035

E

Uruguay, 1999

22

18

17

19

24

100

0,020

E, H, SS

Uruguay, 2003

21

18

16

18

27

100

0,044

E, H, SS

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of national studies.
aPer capita income, spending or consumption.
bE = education; H = health; SS = social security; W = welfare; HO = housing; SAN = sanitation; O = others.

126

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.2
CONDITIONAL TRANSFER PROGRAMMES IN LATIN AMERICA AND THE CARIBBEAN
Country

Name of conditional
transfer programme

Start
date

Objective

Target population

Argentina

Familias por la Inclusión Social

2004

Promote children’s development,
health and retention in the educational
system and prevent social exclusion

Families with children aged under 19
and low-income pregnant women

Brazil

Bolsa Familia

2003

Reduce poverty and inequality
in the short and long term

Families living in extreme poverty with
per capita income less than US$ 28

Chile

Chile Solidario

2002

Provide integrated support to
families living in extreme poverty

Families living in extreme poverty

Colombia

Familias en Acción

2001

Proteger y promover la formación
de capital humano en niños

Poor families with children (0 to 17 years)

Costa Rica

Superémonos

2000

Protect and promote human capital
formation among children

Poor families with children aged 7-18
years who are attending school

Ecuador

Human Development Bond

2001

Promote access to and
retention in education

Families living in extreme poverty

El Salvador

Red Solidaria

2005

Help to mitigate extreme
poverty and hunger

Families living in extreme poverty
with children aged under 15
years or pregnant women

Honduras

Programa de Asignación
Familiar (PRAF)

1990

Increase human capital among children,
persons with disabilities, pregnant women
and older adults from poor families

Poor families with children,
persons with disabilities, pregnant
women and older adults

Jamaica

Programme of Advancement
through Health and
Education (PATH)

2002

Contribute to progress in education
and health, reduce child labour
and overcome poverty

Poor families with children,
persons with disabilities, pregnant
women and older adults

Mexico

Oportunidades

1997

Increase the capacities of families
living in extreme poverty by
means of human capital

Families below the poverty line

Nicaragua

“Mi Familia” social
protection network

2000

Increase educational, nutritional
and health-related human capital
among children of poor families

Children aged 0-13 years (those
over 6 must be enrolled at school)

Panama

Red Oportunidades

2006

Integrate families living in extreme poverty
into the country’s development dynamic

Families living in extreme poverty

Paraguay

Tekoporâ

2005

Contribute to reducing extreme
poverty and increase human and social
capital, improving living conditions

Families living in extreme
poverty (rural population)

Peru

Juntos

2005

Promote the exercise of fundamental
rights by coordinating the supply of
services in health, nutrition and education

Families living in extreme poverty
and social exclusion

Dominican
Rep.

Tarjeta Solidaridad

2005

Reduce extreme poverty and hunger

Population living in extreme poverty

Uruguay

Ingreso Ciudadano,
of the National Social
Emergency Plan (PANES)

2005

Reduce extreme poverty and hunger

Population living in extreme poverty

Social Panorama of Latin America • 2007

127

Table II.2 (continued)
CONDITIONAL TRANSFER PROGRAMMES IN LATIN AMERICA AND THE CARIBBEAN
Country

Human capital
component

Condition

Percentage
of total
population

Spending/
GDP

Argentina

Education
and health

Educational assistance
and health check-ups

2.6% (2006)

0.12% (2006)

Brazil

Education, health
and nutrition

Educational assistance
and health check-ups

22.2% (2006) 0.43% (2006)

Chile

Education,
health, nutrition,
employment,
identification,
habitability and
family development

Fulfilment of 53 minimum
standards in education,
health, identification,
habitability, family
development, monetary
income and employment

6.45% (2005)

Colombia

Education, health
and nutrition

Costa Rica

Funding
source

Transfer
amount

IDB

US$ 50 to 99
per month

Ministry
of Social
Development
and Hunger
Alleviation and
World Bank

Targeting
mechanism
Geographical
targeting

US$ 7 to 44
per month

0.10% (2005) Solidarity
US$ 5.90 to
and Social
19.80 per
Investment Fund month
of the Ministry
of Planning and
Cooperation

Through the
Social Welfare
Card, formerly
Social Action
Committee
(CAS) card

Educational assistance
4.2% (2006)
(80%), assistance to health
facilities for check-ups

0.3% (2006)

World Bank

For education,
US$ 6 to 12;
for health,
US$ 20

Beneficiary
Identification
System
(SISBEN)

Education
and health

Educational assistance
and health check-ups

1.12% (2002)

0.02% (2005)

World Bank

Food coupons

Target
Population
Identification
System
(SIPO) and
identification
card (FIS)

Ecuador

Education
and health

Educational assistance
and health check-ups

8.88% (2007)

0.49% (2006)

IDB, World
Bank

US$ 30

System for
Identification
and
Selection of
Beneficiaries
(SELBEN)

El Salvador

Education, health
and nutrition

Educational assistance
and health check-ups

24 106
families
(2006)

0.023%
(2006)

World Bank
and IDB

US$ 15 to 30
per month

...

Honduras

Education, health
and nutrition

Educational assistance
8.55% (2005)
(fewer than 7 days’
absence), health check-ups

0.022%
(2006)

IDB and
Government
of Honduras

From US$ 3

....

Jamaica

Education, health
and nutrition

Educational assistance
(85%) and health
check-ups

8.86% (2006)

0.267%
(2005)

World
Bank and
Government
of Jamaica

Education
and health,
US$ 9 each

...

Mexico

Education, health
and nutrition

Educational assistance
(85%) and health checkups and workshops

25% (2005)

0.435%
(2006)

World
Bank and
Government
of Jamaica

US$ 10 to
63 per child
per month

...

Nicaragua

Education, health
and nutrition

Educational assistance,
parents’ meetings and
health check-ups

2.7% (2005)

0.237%
(2005)

IDB and
Government
of Nicaragua

Education,
US$ 15
per month;
health, US$
28 per month

Geographical

Panama

Education, health
and nutrition

Educational assistance
and health check-ups0}

12 000
families
(2006)

US$ 46.9
million
(project total)

World Bank
and IDB

US$ 36
per month

...

Paraguay

Education, health,
nutrition and
social welfare

Educational assistance
and health check-ups

0.65% (2006)

0.0026%
(2006)

...

...

Geographical,
then individual

Peru

Education,
health, nutrition
and human
development

Educational assistance
(85%) and health
check-ups

3.6% (2006)

0.114%
(2006)

Government
of Peru and
other sources

US$ 30
per month

Geographical,
then individual

128

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.2 (concluded)
CONDITIONAL TRANSFER PROGRAMMES IN LATIN AMERICA AND THE CARIBBEAN
Dominican
Republic

Education, health
and nutrition

Educational assistance
(85%) and health
check-ups

8% (2005)

0.043% (2004) ...

“Comer es
primero”
programme,
US$ 17;
the school
attendance
programme
ILAE, US$ 4.50

The single
beneficiary
identification
system
(SIUBEN)

Uruguay

Education, health
and nutrition

Educational assistance
and health check-ups

9.46% (2006)

0.394 (2006)

US$ 55 per
household
per month

n/a

n/a

Source: Ministry of Social Development, Argentina [online] www.desarrollosocial.gov.ar; Ministry of Social Development and Hunger Alleviation, Brazil
[online] www.mds.gov.br/bolsafamilia; Ministry of Planning and Cooperation, Chile [online] www.chilesolidario.gov.cl; Presidency of the Republic,
Colombia [online] www.accionsocial.gov.co; Joint Institute for Social Aid, Costa Rica [online] www.imas.go.cr; Social protection program, Ecuador
[online] www.pps.gov.ec; Red Solidaria, El Salvador [online] www.redsolidaria.gov.sv, department of the Secretary of State to the Office of the President,
Honduras [online] www.sdp.gob.hn and Ministry of Finance; Ministry of Finance and Planning, Jamaica [online] www.mof.gov.jm; Oportunidades [online]
www.oportunidades.gob.mx and Secretariat of Social Development (SEDESOL), “Informe de rendición de cuentas. Oportunidades 2000-2006”,
“Oportunidades, un programa de resultados, 2007”; Inter-American Development Bank (IDB), “Nicaragua. Red de protección social, fase II (NI-0161).
Informe de evaluación” [online] www.iadb.org/EXR/doc98/apr/ni1109s.pdf; Ana Fonseca, Los sistemas de protección social en América Latina: un
análisis de las transferencias monetarias condicionadas, New York, Regional Bureau of Latin America and the Caribbean (RBLAC), United Nations
Development Programme (UNDP); Department of Social Welfare, Paraguay [online] www.sas.gov.py; Juntos, Programa nacional de apoyo directo a
los más pobres, Peru [online] www.juntos.gob.pe; Presidency of the Republic, Dominican Republic, “Programas de transferencias condicionadas de
ingreso”, December 2006, unpublished; Ministry of Social Development, Uruguay [online] www.mides.gub.uy; Presidency of the Eastern Republic of
Uruguay, “Balance del Plan de Atención Nacional para Emergencia Social (PANES)” [online] www.presidencia.gub.uy.

b

 5 500

2 000 - 5 500

 2 800

800 - 2 800

3 a 4.5

4.5 a 6

6 a 10

Dependants
per formal
worker

1 400 - 2 400

500 - 1 210

230 - 480

Per capita
social spending
(purchasing power
parity in dollars
at 2000 prices)

700 - 1 550

200 - 845

90 - 290

Per capita
social spending
(in dollars at
2000 prices)

100

31.7
38.7

Total dependants

Percentage of
formal workers a
Young people
10.0

30.6

Unemployed or
informally employed

100

45.9
35.4

Unemployed or
informally employed
Total dependants

Percentage of
formal workers a
Young people

12.0

26.9

Inactive

23.5
29.1
100

54.2

Older adults

24.4

Older adults

18.7

8.3

42.4

Inactive

Older adults

Young people

Composition of
dependants
per formal worker
(percentages)

Inactive
Unemployed or
informally employed
Total dependants

Percentage of
formal workers a

21.3

21.6

14.2

27.1

21.9

36.8

8.5

30.7

19.5

41.3

Housing and other

4.9

Social security and
welfare
52.2

Health

Education

Housing and other

Social security
and welfare

Health

Education

Housing and other

Social security
and welfare

Health

Education

Structure of public
social spending
(percentages)

Total public
social spending

Housing and other

Welfare

Social security

Health

Education

Total public
social spending

Housing and other

Social security
and welfare

Health

Education

Total public
social spending

Housing and other

Social security
and welfare

Health

Education

0.044

-0.02647

-0.48369

0.34885

-0.19227

-0.13828

0.042

0.06679

-0.15359

0.56832

-0.07334

0.11581

0.143

0.20611

-0.08883

0.50404

0.0736

-0.0866

Concentration
index

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the relevant countries, national reports, household surveys, population estimates
from the Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC and World Bank, World Development Indicators [online database] www.worldbank.org/data/
onlinedatabases/onlinedatabases.html.
a Refers to people aged 15 to 59 employed in the formal sector in relation to total employed for that age group.
b The Bolivarian Republic of Venezuela and Mexico are classified in group II. Since they are federal countries, the available statistics refer only to central government.

Group III

Group II

Group I

Per capita GDP
Per capita
(purchasing power
GDP (in
parity in dollars
dollars at
at 2000 prices)
2000 prices)

Table II.3
TYPOLOGY OF COUNTRIES, BY CHALLENGES TO SOCIAL CONTRACT

Social Panorama of Latin America • 2007
129

Venezuela
(Bolivarian
Republic of)
Colombia
Panama
Dominican
Republic
Mexico
Trinidad and
Tobago
Simple
average
Weighted
average

Bolivia
Honduras
Nicaragua
Jamaica
Ecuador
Guatemala
Paraguay
El Salvador
Peru
Simple
average
Weighted
average

1 024
1 032
831
2 939
1 527
1 568
1 359
2 119
2 341

4 149

4 810

1 722

3 860

2 865

6 042

9 021

4 872

4 787

6 740

12 648

7 956

8 105

6 433
6 637

9 535

2 166
4 327

5 743

1 637

2 483
3 025
3 421
3 794
3 802
4 049
4 266
4 652
5 250

860
772
1087
729
1521

509

477

845

618

204

291
344

562

150

147

190
120
90
289
96
100
108
120
208

955

457
658

3.8

6.0
4.8

15.7

11.8

20.5

17.9

175

148

207

233

178
242
201
198
350

187

196

407

229

56

82
165

240

62

69

75
79
39
158
40
39
52
63
73

Social security and welfare and employment

4.2

4.2

4.4

4.3

4.6
5.5
3.3
3.5
4.5

4.0

3.7

4.5

3.8

2.0

3.7
3.8

5.0

3.6

4.4

7.3
7.7
4.7
5.4
2.6
2.5
3.8
2.9
3.1

30.0

31.7

27.4

26.3

27.8
28.4
23.8
24.9
26.4

30.9

29.8

22.2

30.8

33.5

30.3
30.4

31.4

35.7

36.1

38.0
39.8
37.8
31.7
32.4
43.2
35.9
34.0
31.8

13.9

13.2

16.2

16.2

16.3
19.2
13.7
14.2
16.8

12.8

12.3

20.2

12.3

5.8

12.3
12.5

15.9

10.1

12.3

19.1
19.3
12.4
17.1
8.1
5.8
10.7
8.6
9.8

1059

865

1382

1557

1239
1709
1234
1476
2061

1040

977

2559

1175

392

794
830

914

421

476

474
583
423
649
306
234
456
402
513

583

476

755

903

638
851
843
793
1318

614

598

1825

745

167

267
541

765

175

202

195
199
103
503
123
91
145
183
229

4.5
0.3

295

183

499

508

467
234
759
364
718

138

115

128

130

42

148
47

198

47

7.0

4.1

10.7

9.1

12.0
5.3
12.3
6.5
9.2

2.9

2.8

1.4

2.2

1.5

6.8
1.1

4.1

2.7

1.9

13
34
16
33
1
98
30

0.5
2.2
1.0
2.4
0.1
4.2

46
3

70.0

68.3

72.6

73.7

72.2
71.6
76.2
75.1
73.6

69.1

70.2

77.8

69.2

66.5

69.7
69.6

68.6

64.3

63.9

62.0
60.2
62.2
68.3
67.6
56.8
64.1
66.0
68.2

9.9

6.0

14.7

12.3

16.6
7.4
16.2
8.7
12.5

4.2

4.0

1.8

3.1

2.2

9.7
1.6

6.0

4.1

2.9

0.7
3.3
1.8
3.7
0.1
6.1

7.2
0.4

759

390

1257

1181

1256
657
1456
902
1526

337

321

229

296

149

627
103

344

171

114

26
126
73
158
3
322

179
13

418

214

686

685

646
327
995
484
976

199

197

164

188

63

211
67

288

71

48

20
50
28
50
1
143

74
5

Spending/
population

141

96

204

202

180
220
107
156
347

111

103

199

153

40

50
98

77

30

33

36
37
28
81
19
15
16
33
37

3.4

2.5

4.4

3.7

4.6
5.0
1.7
2.8
4.4

2.4

2.0

2.2

2.5

1.4

2.3
2.3

1.6

1.7

2.2

3.5
3.5
3.3
2.8
1.2
1.0
1.1
1.5
1.6

256

164

372

356

349
442
156
290
541

191

160

279

240

92

147
151

92

72

84

88
106
114
106
46
39
48
72
82

Per capita
spending
(purchasing
per
Percentage
capita
of GDP power parity
in dollars at
(in
2000 prices)
dollars
at 2000
prices)

Public spending
on health

Health

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the relevant countries, household surveys, population estimates from the Latin American and
Caribbean Demographic Centre (CELADE) - Population Division of ECLAC and World Bank, World Development Indicators [online database]

994

3.8

22.1
17.4
17.7
13.1
19.4

10.8

10.1

9.4

10.2

7.1

13.4
8.0

11.7

8.7

9.5

18.6
11.6
10.8
9.9
6.3
6.3
7.9
5.6
8.9

Education
Spending per target
Public social
Persons
Young Spending per target population
population
spending on
aged 15
people
social security
and over percentage Spending per
aged Percentage
Amount spent
and welfare
as % of
under 15
person aged
per young person
of per
of per
pop. 2005
as % of
15 and over
aged under 15
capita
Percentage pop. 2005 capita
Percentage
per
GDP
GDP (purchasing (in
of GDP
capita
of GDP
(in
(purchasing
(in dollars
power dollars
power parity dollars
at 2000
parity in at 2000)
in dollars at at 2000
prices)
dollars
2000 prices) prices)
at 2000
prices)

Public social
spending
on education

per
capita
(in dollars Percentage
(in
at 2000 of GDP
dollars
prices)
at 2000
prices)

Total
Per
social
capita
spending
social
spending

3.8
3.9
4.2
3.2
4.0

5.0

5.0

4.9

5.5

4.7

5.0

8.0

8.1

7.5
8.9
6.4
7.7

9.6
9.4
7.5

2002 a

Per
Dependants
capita per formal
worker
GDP

(purchasing
(in
power
dollars
parity in at 2000)
dollars
at 2000
prices)

Per
capita
GDP

Brazil
7 580
3 901
Costa Rica
8 889
4 423
Uruguay
8 989
6 145
Chile
10 389
5 582
Argentina
12 232
7 825
Simple
9 616
5 575
average
Weighted
8 523
4 656
average
Latin America and the Caribbean (20 countries)
Simple
6 528
3 592
average
Weighted
7 629
4 203
average

Grupo III

Grupo II

Grupo I

Country

Table II.4
LATIN AMERICA AND THE CARIBBEAN: ESTIMATED SPENDING BY TARGET POPULATION ON EDUCATION, SOCIAL SECURITY AND WELFARE AND HEALTH,
BY GROUPS OF COUNTRIES, 2004-2005

130
Economic Commission for Latin America and the Caribbean (ECLAC)

Social Panorama of Latin America • 2007

131

Table II.5
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PER CAPITA PUBLIC SOCIAL SPENDING
(In dollars at 2000 prices)
Period

Country
1990-1991
Argentina
Bolivia a

1992-1993

1994-1995

1996-1997

1 179
…

1 414
…

1 553
118

1 548
143

1998-1999
1 686
163

2000-2001

2002-2003

2004-2005

1 640
179

1 305
193

1 521
190

Brazil

604

584

725

710

781

776

811

860

Chile

403

474

508

594

682

746

755

729

Colombia

123

153

237

322

281

266

280

291

Costa Rica

486

516

566

606

651

728

769

772
870

Cuba b

…

…

…

…

…

570

659

Ecuador

94

105

81

76

65

65

77

96

El Salvador c

…

76

90

96

107

113

129

120

Guatemala

44

55

57

62

89

93

100

100

Honduras

67

71

61

63

70

97

112

120

Jamaica

d

Mexico
Nicaragua

243

234

245

267

…

273

276

289

324

416

449

438

507

564

588

618

45

42

46

45

57

63

73

90

Panama

229

317

287

315

377

371

328

344

Paraguay

45

95

115

128

129

107

119

108

Peru e

64

85

125

141

152

173

206

208

Dominican Republic

74

111

133

153

176

209

211

204

Trinidad and Tobago f

303

312

294

304

…

588

728

845

Uruguay

820

1 008

1 150

1 285

1 382

1 322

1 094

1 087

Venezuela
(Bolivarian Rep. of)

441

490

396

439

435

563

486

562

287

333

362

387

423

446

432

457

440

481

553

560

610

624

616

658

Latin America
and the Caribbean g
Latin America
and the Caribbean h

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
a

The figure for the biennium 1994-1995 relates to 1995.
Owing to changes in the basis of GDP, information in dollars has been available only since 2000 (see box II.6).
c The figure for the biennium 1992-1993 relates to 1993.
d The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
e Figures earlier than 2000 relate to the central government budget.
f The figure for the biennium 1996-1997 relates to 1996.
g Simple average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba.
h Weighted average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba.
b

132

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.6
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PUBLIC SOCIAL SPENDING
AS A PERCENTAGE OF GROSS NATIONAL PRODUCT
(Percentages)
Period

Country
1990-1991
Argentina
Bolivia a

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

19.3
…

20.1
…

21.1
12.4

19.9
14.6

20.9
16.2

21.8
18.0

19.5
19.4

19.4
18.6

Brazil

18.1

17.6

20.4

19.4

21.6

21.1

21.8

22.1

Chile

12.7

12.8

12.4

12.8

14.2

15.1

14.7

13.1

6.6

7.9

11.5

15.2

13.7

13.2

13.7

13.4

Costa Rica

Colombia

15.6

15.2

15.8

16.8

16.4

18.0

18.6

17.4

Cuba

27.6

32.8

28.5

25.0

24.3

22.2

24.7

28.7

7.4

8.0

6.1

5.6

4.9

4.9

5.5

6.3

…

4.1

4.8

5.2

5.4

6.1

5.6

0.0

Guatemala

3.3

4.1

4.1

4.3

5.9

6.1

6.5

6.3
11.6

Ecuador
El Salvador b
Honduras

7.5

7.6

6.6

6.6

7.4

10.0

11.3

Jamaica c

8.4

8.0

8.2

9.0

…

9.5

9.5

9.9

Mexico

6.5

8.1

8.9

8.5

9.2

9.7

10.2

10.2
10.8

Nicaragua

6.6

6.5

7.2

6.5

7.6

8.1

9.3

Panama

7.5

9.3

8.3

8.8

9.7

9.5

8.3

8.0

Paraguay

3.2

6.6

7.8

8.7

9.1

8.0

9.1

7.9

Peru d

3.9

5.1

6.5

6.9

7.4

8.3

9.5

8.9

Dominican Republic

4.3

5.9

6.7

6.9

7.1

7.7

7.6

7.1

Trinidad and Tobago e
Uruguay
Venezuela
(Bolivarian Rep. of)
Latin America
and the Caribbean f
Latin America
and the Caribbean g

6.9

7.3

6.6

6.4

…

9.1

9.7

9.4

16.8

18.9

20.2

21.3

22.0

22.2

20.8

17.7

8.8

9.2

7.8

8.6

8.8

11.6

11.7

11.7

9.7

10.8

11.1

11.3

11.8

12.4

12.7

12.6

12.9

13.5

14.9

14.6

15.5

15.7

15.8

15.9

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
a The figure for the biennium 1994-1995 relates to 1995.
b The figure for the biennium 1992-1993 relates to 1993.
c The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
d Figures before 2000 relate to the central government budget.
e The figure for the biennium 1996-1997 relates to 1996.
f Simple average of the countries. Includes estimates for years and countries for which information is not available.
g Weighted average of the countries. Includes estimates for years and countries for which information is not available.

Social Panorama of Latin America • 2007

133

Table II.7
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PUBLIC SOCIAL SPENDING
AS A PERCENTAGE OF TOTAL PUBLIC SPENDING a
(Percentages)
Period

Country
1990-1991
Argentina
Bolivia b

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

62.2
…

63.4
…

65.6
39.7

65.4
44.1

64.2
50.0

62.7
54.4

66.2
60.1

64.1
63.0

Brazil

48.9

47.2

58.6

51.0

55.8

61.6

69.3

72.0

Chile

61.2

62.8

64.2

65.2

65.7

67.5

67.6

66.9

Colombia

28.8

32.2

39.9

41.8

32.7

33.2

32.8

…

Costa Rica

38.9

41.2

38.2

42.0

40.6

40.5

37.5

35.8

Cuba

35.6

34.7

39.4

45.7

44.8

47.1

51.4

53.0

Ecuador

42.8

48.5

33.7

27.6

21.7

20.9

25.2

28.5

El Salvador c

…

32.1

31.6

35.5

40.0

34.9

30.9

31.2

Guatemala

29.9

33.3

41.3

42.7

45.1

47.3

50.4

53.8
52.8

Honduras

40.7

36.6

40.6

40.5

39.5

45.4

49.9

Jamaica d

26.8

23.2

20.6

19.2

…

17.1

17.3

16.3

Mexico

41.3

50.2

53.1

52.3

59.4

61.3

57.8

58.5

Nicaragua

34.0

38.5

39.9

37.0

37.1

38.4

42.0

47.9

Panama

38.1

50.6

48.6

39.6

46.4

42.5

39.1

39.3
40.2

Paraguay

39.9

42.9

43.3

47.1

44.5

38.2

41.6

Peru e

39.0

41.3

46.6

46.8

49.5

49.7

51.4

50.8

Dominican Republic

38.4

37.0

45.4

45.5

43.3

47.5

41.4

34.5

Trinidad and Tobago f

40.6

40.6

42.8

40.7

…

70.8

73.2

76.4

Uruguay

62.3

67.7

70.8

70.8

69.5

66.6

57.7

57.4

Venezuela
(Bolivarian Rep. of)

32.8

40.1

35.3

35.4

36.6

37.8

38.6

41.0

Latin America
and the Caribbean g

40.4

42.6

44.2

44.2

45.7

46.9

47.7

48.4

Latin America
and the Caribbean h

46.6

48.8

55.0

51.7

54.3

56.8

59.3

60.6

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
a Official figures for total public spending are taken from the countries’ functional classifications of public spending, but may differ from other reports
which are also of an official nature, based on different types of classification (see box II.6).
b The figure for the biennium 1994-1995 relates to 1995.
c The figure for the biennium 1992-1993 relates to 1993.
d The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
e Figures before 2000 relate to the central government budget.
f The figure for the biennium 1996-1997 relates to 1996.
g Simple average of the countries. Includes estimates for years and countries for which information is not available.
h Weighted average of the countries. Includes estimates for years and countries for which information is not available.

134

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.8
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES) : PUBLIC SOCIAL SPENDING ON EDUCATION
AS A PERCENTAGE OF GROSS NATIONAL PRODUCT
(Percentages)
Period

Country
1990-1991
Argentina
Bolivia a

3.6
…

1992-1993
4.0
…

1994-1995
4.2
5.3

1996-1997
4.2
5.9

1998-1999
4.7
6.0

2000-2001
5.1
6.7

2002-2003
4.2
7.6

2004-2005
4.5
7.3

Brazil

3.7

3.0

5.3

4.3

5.5

5.0

4.7

4.6

Chile

2.4

2.5

2.6

3.0

3.7

3.9

4.0

3.5

Colombia

2.6

3.3

3.3

4.8

4.6

4.1

4.8

3.7

Costa Rica

3.9

4.2

4.2

4.6

4.4

5.1

5.7

5.5

10.8

11.9

9.0

7.9

8.4

8.5

10.3

12.4

2.8

3.0

2.6

2.5

2.5

2.1

2.6

2.6

…

1.9

2.0

2.3

2.5

3.0

3.2

2.9

Guatemala

1.6

1.8

1.7

1.7

2.3

2.6

2.6

2.5
7.7

Cuba
Ecuador
El Salvador b
Honduras

4.3

4.3

3.7

3.9

4.5

6.2

7.1

Jamaica c

4.1

4.0

4.1

4.9

…

5.8

5.2

5.4

Mexico

2.6

3.5

3.9

3.7

3.8

3.9

4.0

3.8

Nicaragua

2.6

2.2

2.8

2.9

3.4

3.7

4.4

4.7

Panama

3.6

3.7

3.5

4.1

4.1

4.2

4.1

3.8
3.8

Paraguay

1.3

2.9

3.6

4.2

4.4

4.3

4.4

Peru d

1.6

2.0

2.7

2.5

2.5

2.9

3.0

3.1

Dominican Republic

1.2

1.7

2.1

2.3

2.7

2.9

3.1

2.0

Trinidad and Tobago e

3.2

3.3

3.0

3.0

…

4.1

4.4

4.5

Uruguay

2.5

2.5

2.5

3.0

3.2

3.4

3.6

3.3

Venezuela
(Bolivarian Rep. of)

3.5

4.0

3.8

3.2

4.0

5.1

5.1

5.0

3.2

3.5

3.6

3.8

4.1

4.4

4.7

4.6

3.3

3.5

4.3

3.9

4.5

4.5

4.4

4.3

Latin America
and the Caribbean f
Latin America
and the Caribbean g

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
a The figure for the biennium 1994-1995 relates to 1995.
b The figure for the biennium 1992-1993 relates to 1993.
c The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
d Figures before 2000 relate to the central government budget.
e The figure for the biennium 1996-1997 relates to 1996.
f Simple average of the countries. Includes estimates for years and countries for which information is not available.
g Weighted average of the countries. Includes estimates for years and countries for which information is not available.

Social Panorama of Latin America • 2007

135

Table II.9
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES) : PUBLIC SOCIAL SPENDING ON HEALTH
AS A PERCENTAGE OF GROSS NATIONAL PRODUCT
(Percentages)
Period

Country
1990-1991
Argentina
Bolivia a

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

4.3
…

4.6
…

4.9
3.1

4.6
3.3

4.9
3.3

5.0
3.6

4.4
3.7

4.4
3.5

Brazil

3.6

2.6

4.2

3.8

3.8

4.1

4.3

4.6

Chile

2.0

2.2

2.4

2.4

2.7

2.9

3.0

2.8

Colombia

1.0

1.2

2.9

3.2

3.7

3.0

2.8

2.3

Costa Rica

4.9

4.5

4.7

4.7

4.8

5.2

5.7

5.0

Cuba

5.0

6.6

5.6

5.3

5.8

5.2

5.3

6.0

Ecuador

1.4

1.6

0.8

0.9

0.7

0.8

1.1

1.2

El Salvador b

…

1.2

1.3

1.4

1.5

1.3

1.5

1.5

Guatemala

0.9

1.0

0.9

0.8

1.1

1.1

1.0

1.0
3.5

Honduras

2.9

2.8

2.6

2.3

2.4

3.3

3.8

Jamaica c

2.2

2.4

2.2

2.3

…

2.2

2.5

2.8

Mexico

2.9

3.4

2.3

2.2

2.3

2.3

2.3

2.5

Nicaragua

2.8

2.5

2.8

2.5

2.7

2.9

3.3

3.3

Panama

1.6

1.9

1.8

1.9

2.0

2.3

2.0

2.3
1.1

Paraguay

0.3

1.1

1.2

1.3

1.4

1.2

1.3

Peru d

0.9

0.9

1.3

1.4

1.5

1.5

1.6

1.6

Dominican Republic

1.0

1.3

1.2

1.4

1.5

1.8

1.6

1.4

Trinidad and Tobago e

2.6

2.8

2.2

2.0

…

2.1

2.3

2.2

Uruguay

2.9

3.0

3.4

2.5

2.7

2.6

2.0

1.7

Venezuela
(Bolivarian Rep. of)

1.6

1.7

1.1

1.1

1.4

1.5

1.6

1.6

2.3

2.6

2.6

2.4

2.6

2.7

2.7

2.7

3.1

3.0

3.3

3.0

3.2

3.3

3.3

3.4

Latin America
and the Caribbean f
Latin America
and the Caribbean g

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
a The figure for the biennium 1994-1995 relates to 1995.
b The figure for the biennium 1992-1993 relates to 1993.
c The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
d Figures before 2000 relate to the central government budget.
e The figure for the biennium 1996-1997 relates to 1996.
f Simple average of the countries. Includes estimates for years and countries for which information is not available.
g Weighted average of the countries. Includes estimates for years and countries for which information is not available.

136

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.10
LATIN AMERICA AND THE CARIBBEAN (20 COUNTRIES) : PUBLIC SOCIAL SPENDING ON SOCIAL SECURITY AND
WELFARE AS A PERCENTAGE OF GROSS NATIONAL PRODUCT
(Percentages)
Period

Country
1990-1991
Argentina
Bolivia a

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

9.7
…

9.9
…

10.3
1.4

9.8
2.8

9.9
3.9

10.3
4.5

9.7
4.7

9.2
4.5
12.0

Brazil

9.2

10.6

10.4

10.6

11.7

11.1

11.9

Chile

8.1

7.9

7.2

7.2

7.6

7.9

7.5

6.5

Colombia

2.5

2.9

4.5

6.1

4.3

4.8

5.0

6.8

Costa Rica

4.9

4.7

5.2

5.8

5.7

6.1

5.5

5.3

Cuba

7.0

9.9

8.6

7.6

7.6

6.1

6.6

7.6

Ecuador

3.2

3.4

2.2

2.0

1.5

1.7

1.7

2.2

…

0.0

0.0

0.0

0.0

0.1

0.0

0.1

Guatemala

0.7

0.8

0.7

0.7

0.9

1.0

1.2

1.0
0.3

El Salvador b
Honduras

0.4

0.4

0.3

0.3

0.3

0.2

0.3

Jamaica c

0.6

0.4

0.4

0.3

…

0.4

0.5

0.5

Mexico

0.1

0.1

1.3

1.5

1.9

2.3

2.4

2.2

Panama

1.2

2.2

1.5

1.0

1.9

1.6

1.2

1.1

Paraguay

1.2

2.3

2.4

2.7

3.1

2.1

3.0

2.4

Peru d

1.3

2.2

2.5

2.8

3.2

3.9

4.9

4.2

Dominican Republic

0.4

0.5

0.4

0.7

0.8

1.1

0.4

1.5

Trinidad and Tobago e

…

…

…

…

…

1.4

1.8

1.4

11.2

13.1

13.9

15.3

15.6

15.8

14.8

12.3

Venezuela
(Bolivarian Rep. of)

2.0

2.1

2.3

3.0

2.5

3.7

4.1

4.1

Latin America
and the Caribbean f

3.2

3.7

3.8

4.0

4.2

4.3

4.3

4.2

Latin America
and the Caribbean g

5.3

5.8

6.3

6.5

6.8

6.8

7.0

7.0

Uruguay

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commissions social
expenditure database.
aThe figure for the biennium 1994-1995 relates to 1995.
bThe figure for the biennium 1992-1993 relates to 1993.
cThe figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
dFigures before 2000 relate to the central government budget.
eIn this function, figures before 2000 are not comparable.
f Simple average of the countries. Includes estimates for years and countries for which information is not available. Does not include Nicaragua.
gWeighted average of the countries. Includes estimates for years and countries for which information is not available. Does not include Nicaragua.

.

Social Panorama of Latin America • 2007

137

Table II.11
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PUBLIC SOCIAL SPENDING ON HOUSING AND OTHERS
AS A PERCENTAGE OF GROSS NATIONAL PRODUCT
(Percentages)
Country

Period
1990-1991

Argentina
Bolivia a

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

1.7
…

1.6
…

1.6
2.5

1.4
2.6

1.5
2.9

1.4
3.2

1.1
3.4

1.4
3.3

Brazil

1.5

1.4

0.4

0.8

0.6

0.9

1.0

0.9

Chile

0.2

0.2

0.2

0.2

0.2

0.3

0.2

0.2

Colombia

0.5

0.6

0.8

1.1

1.1

1.3

1.1

0.6

Costa Rica

1.9

1.8

1.7

1.8

1.5

1.6

1.7

1.7

Cuba b

1.8

1.7

1.9

2.0

2.5

2.4

2.5

2.7

Ecuador

0.0

0.1

0.4

0.2

0.1

0.4

0.2

0.2

El Salvador c

…

1.1

1.2

1.1

1.2

1.0

1.4

1.1

Guatemala

0.1

0.5

0.7

1.2

1.7

1.4

1.7

1.9
0.1

Honduras

0.0

0.0

0.0

0.0

0.2

0.2

0.1

Jamaica d

1.5

1.2

1.6

1.4

…

1.1

1.4

1.2

Mexico

0.9

1.2

1.3

1.2

1.1

1.3

1.5

1.8

Nicaragua

1.2

1.8

1.5

1.2

1.5

1.5

1.6

2.8

Panama

1.1

1.4

1.4

1.9

1.7

1.3

1.0

0.8
0.6

Paraguay

0.5

0.3

0.6

0.4

0.2

0.5

0.4

Peru e

0.1

0.1

0.1

0.2

0.3

0.1

0.1

0.1

Dominican Republic

1.8

2.5

3.0

2.6

2.1

2.0

2.6

2.3

Trinidad and Tobago f

1.0

1.1

1.3

1.3

…

1.5

1.3

1.2

Uruguay

0.3

0.4

0.5

0.5

0.5

0.5

0.4

0.3

Venezuela
(Bolivarian Rep. of)

1.7

1.4

0.6

1.3

0.9

1.3

0.9

1.0

1.0

1.1

1.1

1.2

1.2

1.2

1.2

1.3

1.2

1.3

0.9

1.0

1.0

1.1

1.1

1.2

Latin America
and the Caribbean g
Latin America
and the Caribbean h

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commissions social
expenditure database.
a The figure for the biennium 1994-1995 relates to 1995.
b Housing and sanitation.
c The figure for the biennium 1992-1993 relates to 1993.
d The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
e Figures before 2000 relate to the central government budget.
f The figure for the biennium 1996-1997 relates to 1996.
g Simple average of the countries. Includes estimates for years and countries for which information is not available.
h Weighted average of the countries. Includes estimates for years and countries for which information is not available.

138

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.12
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES):
PER CAPITA PUBLIC SOCIAL SPENDING ON EDUCATION
(In dollars at 2000 prices)
Period

Country
1990-1991

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

Argentina
Bolivia a

220
…

279
…

312
50

328
58

375
60

383
67

283
76

350
75

Brazil

125

101

190

157

199

183

174

178

Chile

77

94

107

139

176

195

206

198

Colombia
Costa Rica

49

63

69

101

95

82

98

82

123

142

151

165

176

206

235

242

Cuba b

…

…

…

…

…

218

277

375

Ecuador

36

39

35

35

33

27

36

40

El Salvador c

…

34

40

47

52

62

67

63

Guatemala

21

24

24

25

35

39

40

39

Honduras

39

41

34

37

43

61

71

79

Jamaica d

119

117

121

148

…

166

150

158

Mexico

129

178

200

188

211

227

233

229

17

14

19

20

26

30

35

39

Panama

109

128

122

145

160

164

162

165
52

Nicaragua
Paraguay

18

41

53

62

63

57

58

Peru e

27

33

51

51

51

60

66

73

Dominican Republic

20

32

41

50

68

77

84

56

Trinidad and Tobago f

139

142

134

164

…

264

330

407

Uruguay

120

131

140

183

203

201

189

201

Venezuela
(Bolivarian Rep. of)

177

214

192

165

199

249

212

240

82

94

104

114

128

140

140

148

111

121

161

151

178

178

170

175

Latin America
and the Caribbean g
Latin America
and the Caribbean h

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
a The figure for the biennium 1994-1995 relates to 1995.
b Owing to changes in the basis of GDP, information in dollars has been available only since 2000 (see box II.6).
c The figure for the biennium 1992-1993 relates to 1993.
d The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
e Figures before 2000 relate to the central government budget.
f The figure for the biennium 1996-1997 relates to 1996.
g Simple average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba.
h Weighted average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba.

Social Panorama of Latin America • 2007

139

Table II.13
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES):
PUBLIC SOCIAL SPENDING ON HEALTH, PER CAPITA
(In dollars at 2000 prices)
Period

Country
1990-1991
Argentina
Bolivia a
Brazil

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

264

321

363

356

393

378

295

347

…

…

30

33

33

36

37

36

119

87

150

138

137

150

160

180
156

Chile

62

82

97

113

130

144

153

Colombia

18

23

60

69

75

61

57

50

153

154

168

171

189

210

236

220

Costa Rica
Cuba b

…

…

…

…

…

135

141

182

Ecuador

18

21

11

12

10

10

15

19

El Salvador c

…

22

26

27

31

28

32

33

Guatemala

12

13

12

11

16

16

16

15

Honduras

26

27

24

22

22

32

38

37

Jamaica d

63

70

65

68

…

64

72

81
153

147

172

118

111

129

132

135

Nicaragua

Mexico

19

17

18

18

20

23

26

28

Panama

49

66

63

67

79

90

79

98
16

4

16

18

20

20

16

17

Peru e

Paraguay

15

15

25

29

31

32

34

37

Dominican Republic

17

24

25

30

36

50

44

40

Trinidad and Tobago f

115

119

99

101

…

136

170

199

Uruguay

142

160

196

151

169

153

105

107

79

89

56

59

70

71

66

77

Latin America
and the Caribbean g

68

77

81

80

88

91

89

96

Latin America
and the Caribbean h

105

106

122

117

125

129

127

141

Venezuela
(Bolivarian Rep. of)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commissions social
expenditure database.
a
b
c
d
e
f
g
h

The figure for the biennium 1994-1995 relates to 1995.
Owing to changes in the basis of GDP, information in dollars has been available only since 2000 (see box II.6).
The figure for the biennium 1992-1993 relates to 1993.
The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
Figures before 2000 relate to the central government budget.
The figure for the biennium 1996-1997 relates to 1996.
Simple average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba.
Weighted average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba.

140

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.14
LATIN AMERICA AND THE CARIBBEAN (20 COUNTRIES): PUBLIC SOCIAL SPENDING
ON SOCIAL SECURITY AND WELFARE, PER CAPITA
(In dollars at 2000 prices)
Period

Country
1990-1991

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005

592

699

759

757

797

775

653

718

…

…

14

28

39

45

47

46

Brazil

308

351

371

388

422

410

441

467

Chile

259

290

296

333

367

393

387

364

Argentina
Bolivia a

Colombia
Costa Rica

47

56

93

129

88

97

102

148

152

160

187

208

226

248

228

234

Cuba b

…

…

…

…

…

156

176

231

Ecuador

41

44

29

27

21

23

23

34

El Salvador c

…

1

1

1

1

1

1

1

Guatemala

10

11

11

10

13

16

19

16

Honduras

3

4

3

3

4

2

3

3

Jamaica d

17

12

12

10

…

11

13

13
130

Mexico

6

6

65

78

105

132

136

Panamá

37

76

54

35

72

64

48

47

Paraguay

17

33

36

40

44

27

40

33

Peru e

23

36

48

57

65

81

106

98

7

9

9

15

20

28

12

42

Dominican Republic
Trinidad and Tobago f

…

…

…

…

…

90

133

128

Uruguay

544

699

787

924

980

939

780

759

Venezuela
(Bolivarian Rep. of)

101

110

115

153

125

179

169

198

121

145

160

178

189

193

178

186

184

212

240

255

272

276

278

296

Latin America
and the Caribbean g
Latin America
and the Caribbean h

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commissions social
expenditure database.
a The figure for the biennium 1994-1995 relates to 1995.
b Owing to changes in the basis of GDP, information in dollars has been available only since 2000 (see box II.6).
c The figure for the biennium 1992-1993 relates to 1993.
d The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
e Peru: figures from 1990 to 1999 relate to the central government budget.
f Information in dollars has been available since 2000. In this function, earlier figures are not comparable.
g Simple average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba,
Nicaragua or Trinidad and Tobago.
h Weighted average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba,

Social Panorama of Latin America • 2007

141

Table II.15
LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES):
PUBLIC SOCIAL SPENDING PER CAPITA ON HOUSING AND OTHERS
(In dollars at 2000 prices)
Period

Country
1990-1991
Argentina

1992-1993

1994-1995

1996-1997

1998-1999

2000-2001

2002-2003

2004-2005
108

102

116

121

108

121

103

75

Bolivia a

…

…

24

25

30

32

33

34

Brazil

52

46

15

29

23

34

36

37

Chile

6

8

8

10

10

15

10

12

Colombia

9

11

16

24

23

27

23

13

Costa Rica

58

61

61

64

60

64

71

77

Cuba b

…

…

…

…

…

62

66

83

0

1

6

3

2

6

3

4

El Salvador c

…

20

24

21

25

22

29

24

Guatemala c

30

Ecuador

…

8

11

17

26

22

27

Honduras

0

0

0

0

2

2

1

1

Jamaica d

44

35

48

43

…

33

42

36

Mexico

43

61

68

61

63

73

86

106

8

11

10

8

11

12

13

23

Panama

35

49

49

68

67

52

40

36

Paraguay

6

5

9

6

4

7

6

8

Peru e

0

1

1

1

2

2

1

1

31

47

59

58

52

54

72

66

Nicaragua

Dominican Republic
Trinidad and Tobago f

46

47

58

64

…

98

95

112

Uruguay

15

19

28

28

32

30

20

21

Venezuela
(Bolivarian Rep. of)

85

77

33

64

44

64

39

48

29

32

32

35

35

37

36

40

42

45

35

40

38

44

44

50

Latin America
and the Caribbean g
Latin America
and the Caribbean h

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information available in the Commission’s social
expenditure database.
a The figure for the biennium 1994-1995 relates to 1995.
b Owing to changes in the basis of GDP, information in dollars has been available only since 2000 (see box II.6).
Includes housing and sanitation.
c The figure for the biennium 1992-1993 relates to 1993.
d The figures for the biennium 1996-1997 relate to 1996, and those for 2004-2005 relate to 2004.
e Figures before 2000 relate to the central government budget.
f The figure for the biennium 1996-1997 relates to 1996.
g Simple average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba.
h Weighted average of the countries. Includes estimates for years and countries for which information is not available, and does not include Cuba.


142

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.16
LATIN AMERICA (18 COUNTRIES): ORIENTATION OF EDUCATION SPENDING BY PRIMARY INCOME QUINTILE
(Percentages)
Total

Income quintile
Quintile I
Latin America

Education

Argentina, 2003

Educational, scientific and technical

23

Quintile II

21

Quintile III

20

Quintile IV

18

Gini

Quintile V

18

100

-0.048

25

22

20

18

15

100

-0.097

26

23

20

17

14

100

-0.122

Elementary education

35

26

19

13

7

100

-0.273

Secondary education

27

24

23

16

10

100

-0.169

9

14

21

29

31

100

0.196

Tertiary education

12

17

26

22

23

100

0.112

Higher education

5

12

17

32

35

100

0.320

27

21

19

17

17

100

-0.094

Cultural, scientific and technical

13

14

16

20

37

100

0.217

Education

Education

Total tertiary

Other education

17

17

21

22

23

100

0.068

Preschool and primary

25

25

23

18

10

100

-0.146

Secondary and alternative

15

18

24

24

19

100

0.056

3

5

17

30

45

100

0.440

Education

17

18

18

19

27

100

0.094

Primary

26

27

23

17

8

100

-0.194

Secondary

7

12

28

33

19

100

0.190

Tertiary

Bolivia, 2002

0

1

3

22

76

100

0.672

Higher university level

Brazil, 1997

Chile, 2006

Education (subsidies)

35

27

19

9

10

100

-0.273

Colombia, 2003

Education

24

23

20

19

14

100

-0.094

Primary

37

28

19

12

4

100

-0.322

Secondary

24

27

23

19

8

100

-0.162

Higher

3

8

17

31

42

100

0.403

Education

26

23

18

18

15

100

-0.112

Primary

40

26

18

10

5

100

-0.349

Secondary

23

28

20

20

9

100

-0.150

Higher

5

11

13

26

44

100

0.371

Education

15

20

20

22

23

100

0.072

Primary

35

26

20

13

6

100

-0.284

Secondary

15

24

25

22

14

100

-0.016

3

13

16

28

40

100

0.356

0

1

6

22

70

100

0.649

Education

21

23

24

20

12

100

-0.089

Primary

27

25

23

17

8

100

-0.184

Secondary

11

20

26

25

18

100

0.076

17

21

21

21

21

100

0.032

25

24

23

20

10

100

-0.147

Preschool

39

18

24

14

4

100

-0.301

Primary

21

25

23

21

10

100

-0.104

Secondary

3

12

23

31

32

100

0.306

University

0

0

6

11

82

100

0.705

16

25

27

20

11

100

-0.055

Costa Rica, 2004

Ecuador, 1999

Tertiary
Private tertiary

El Salvador, 2002

Guatemala, 2000

Education
Preschool and primary

School meals
Scholarships
School supplies
School transport

9

4

23

16

48

100

0.360

18
0

24
2

24
15

20
56

13
27

100
100

-0.051
0.432

Social Panorama of Latin America • 2007

143

Table II.16 (concluded)
LATIN AMERICA (18 COUNTRIES): ORIENTATION OF EDUCATION SPENDING BY PRIMARY INCOME QUINTILE
(Percentages)
Total

Income quintile
Quintile I

Quintile II

Quintile III

Quintile IV

Gini

Quintile V

Honduras, 2004

Education
Primary
Secondary
Higher

20
28
18
1

18
25
18
2

18
21
20
6

20
17
23
23

23
9
21
69

100
100
100
100

0.037
-0.184
0.042
0.627

Jamaica, 2000

Education
Preschool and primary
Preschool
Primary
Secondary
Tertiary

20
28
28
28
20
5

19
24
24
24
21
6

21
23
23
23
23
13

18
16
16
16
21
15

22
9
9
9
15
61

100
100
100
100
100
100

0.012
-0.184
-0.184
-0.184
-0.040
0.484

Mexico, 2002

Education
Preschool and primary
Preschool
Primary
Secondary
Lower secondary
Higher secondary
Tertiary

19
30
30
30
17
14
20
1

20
26
27
26
22
20
24
7

19
20
20
20
21
21
21
15

23
16
16
16
25
26
22
33

19
8
7
8
17
19
14
44

100
100
100
100
100
100
100
100

0.011
-0.217
-0.227
-0.214
0.013
0.063
-0.054
0.453

Nicaragua, 2005

Education
Preschool and primary
Preschool
Total primary
Primary
Subsidized private primary
Total secondary
Secondary
Technical
University
Adults

18
27
21
26
27
0
9
11
5
1
39

19
26
22
26
26
6
16
18
9
4
25

20
23
23
23
23
12
24
26
20
14
17

20
18
21
18
17
32
27
26
30
23
14

24
8
13
8
7
50
23
19
37
58
5

100
100
100
100
100
100
100
100
100
100
100

0.051
-0.180
-0.071
-0.178
-0.192
0.503
0.150
0.099
0.346
0.530
-0.317

Panama, 2003

Education
Primary
Secondary
Higher

21
34
17
3

22
26
26
10

22
20
25
20

20
14
22
30

15
6
11
38

100
100
100
100

-0.051
-0.270
-0.063
0.358

Paraguay, 1998

Education
Preschool and primary
Preschool
Primary
Secondary
Total higher education
Non-university higher education
University

21
33
33
33
17
7
7
0

20
28
25
28
22
12
15
1

20
23
3
23
30
10
14
6

20
16
25
15
29
29
34
27

19
8
14
1
2
61
30
66

100
100
100
100
100
100
100
100

-0.015
-0.297
-0.149
-0.306
-0.091
0.259
0.259
0.627

Peru, 2004

Total education
Preschool and primary
Primary
Secondary
Total tertiary
Non-university tertiary
University tertiary
Postgraduate

19
30
20
32
18
2
4
1
0

21
26
21
27
24
7
17
6
0

23
23
26
22
27
17
33
13
0

21
17
24
14
21
30
28
31
17

16
7
10
6
10
44
19
49
83

100
100
100
100
100
100
100
100
100

-0.026
-0.235
-0.064
-0.262
-0.083
0.431
0.166
0.484
0.732

Education

15

20

23

23

19

100

0.035

25
14
2

26
19
13

24
25
18

16
26
28

9
16
39

100
100
100

-0.168
0.044
0.356

36

24

17

13

10

100

-0.257

Inicial

Dominican
Republic, 1998

Primary
Secondary

Secundaria
Uruguay, 2003

Education

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of national studies

144

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.17
LATIN AMERICA (16 COUNTRIES): ORIENTATION OF HEALTH SPENDING BY PRIMARY INCOME QUINTILE
(Percentages)
Total

Income quintile

Gini

Quintile I Quintile II Quintile III Quintile IV Quintile V

Latin America

Health

24

22

20

18

17

100

-0.067

Argentina, 2003

Health
Publicly-funded health care
Health insurance
Social work – health care
National Institute of Social Services for Retirees and
Pensioners (INSSJP) – health care

20
35
8
7
9

21
27
17
16
19

19
18
21
20
22

21
13
27
27
29

19
7
28
30
20

100
100
100
100
100

-0.001
-0.277
0.202
0.228
0.134

Bolivia, 2002

Health
Health funds
Insurance and other

11
4
18

15
11
20

14
13
14

25
27
22

35
45
26

100
100
100

0.232
0.389
0.075

Brazil, 1997

Health

16

20

22

23

19

100

0.036

Chile, 2006

Health subsidies

55

33

18

4

-10

100

-0.633

34
41
28
18

29
32
27
50

19
16
22
91

12
8
16
121

6
3
8
-180

100
100
100
100

-0.295
-0.395
-0.203
…

Costa Rica, 2004 Health

25

24

24

17

10

100

-0.150

Ecuador, 1999

Colombia, 2003 Health
Subsidized system
Supply subsidies
Health – contributory system

19

23

23

24

11

100

-0.060

El Salvador, 2002 Health

26
29
20

23
23
23

21
21
22

18
17
19

12
10
16

100
100
100

-0.132
-0.176
-0.048

Guatemala, 2000 Total health

17
13
20
40
39

18
16
23
22
20

23
21
28
27
23

25
29
20
6
8

17
22
9
5
10

100
100
100
100
100

0.028
0.119
-0.100
-0.344
-0.280

Honduras, 2004 Health

21

22

23

20

14

100

-0.066

Mexico, 2002

15
16
10
3

18
18
19
15

21
21
23
32

23
23
31
21

22
22
18
30

100
100
100
100

0.078
0.061
0.107
0.236

Nicaragua, 2005 Health

21

22

22

20

16

100

-0.046

Panama, 2003

Health

17

24

20

21

19

100

-0.002

Peru, 2004

Total health

6
11
20
5
17
1
0

11
19
24
15
27
5
2

19
26
23
29
25
15
9

26
24
20
27
22
30
19

39
20
13
24
9
49
70

100
100
100
100
100
100
100

0.324
0.089
-0.068
0.205
-0.081
0.482
0.631

4

8

14

25

49

100

0.424

25
31
26
31
32
33

23
25
24
24
26
15

21
20
21
21
18
17

19
15
19
15
16
29

13
9
10
8
8
6

100
100
100
100
100
100

-0.107
-0.216
-0.148
-0.225
-0.232
-0.160

Curative care Military hospital

18

5

19

16

42

100

0.236

Health

48

28

15

7

3

100

-0.438

Health and nutrition (Ministry of Public Health)
Primary health care
Hospital care
Hospital
Health centres
Health post
Community centre
Health
Primary
Maternal
Hospital

Ministry of Health (MINSA)
MINSA primary care
MINSA hospitals
MINSA comprehensive health insurance
EsSALUD a
Armed forces
Private care

Dominican
Republic, 1998

Preventive medicine: Vaccinations
Preventive medicine: Pregnancy care
Preventive medicine: Pap tests
Preventive medicine: Childhood
Curative care Hospital services for mothers
Curative care Hospital services (Social Security)

Uruguay, 2003

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of national studies.
a

Insurance for dependent workers.

Social Panorama of Latin America • 2007

145

Table II.18
LATIN AMERICA (18 COUNTRIES): ORIENTATION OF SOCIAL SECURITY SPENDING BY PRIMARY INCOME QUINTILE
(Percentages)
Total

Income quintile

Gini

Quintile I Quintile II Quintile III Quintile IV Quintile V

Latin America

Social security

Argentina, 2003 Social insurance and non-contributory
pensions (excl. health)

6

9

14

20

52

100

0.409

29

23

22

18

9

100

-0.176

Social insurance and non-contributory pensions

13

19

21

25

23

100

0.099

Social insurance

11

19

21

25

24

100

0.130

22

25

23

19

11

100

-0.114

Social work – health care

Social insurance not including health

7

16

20

27

30

100

0.228

National Institute of Social Services for Retirees
and Pensioners (INSSJP) – health care

9

19

22

29

20

100

0.134

Non-contributory pensions

53

14

16

14

3

100

-0.400

Employment
Other employment and unemploymentrelated programmes
Other employment and unemploymentrelated programmes without
unemployment programmes a
Family allowances

50

25

13

9

4

100

-0.429

56

22

12

7

3

100

-0.485

61

25

10

4

1

100

-0.574

18

26

23

21

13

100

-0.066

Bolivia, 2002

Social security

10

13

14

24

39

100

0.276

Brazil, 1997

Social security

7

8

15

19

51

100

0.396

Colombia, 2003 Pensions

0

2

5

13

80

100

0.680

Training

9

10

17

34

31

100

0.269

Costa Rica,
2004

Pensions

6

7

11

16

60

100

0.471

Ecuador, 1999

Instituto Ecuatoriano de Seguridad Social (IESS)
Rural social security

Guatemala,
2000

4

7

21

22

46

100

0.396

26

35

13

21

5

100

-0.224

Social insurance

1

3

5

15

76

100

0.648

Pensions

1

2

4

12

81

100

0.680

Survival

4

4

4

13

75

100

0.604

Family maintenance

1

6

10

24

60

100

0.539

Honduras, 2004 Pensions

0

1

4

9

85

100

0.710

Mexico, 2002

3

11

17

28

42

100

0.377

Social security

Panama, 2003

Pensiones

1

4

11

24

60

100

0.552

Peru, 2004

Pensions

1

4

9

18

69

100

0.605

Uruguay, 2003

Retirements and pensions

6

12

17

24

43

100

0.346

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of national studies.
a Not including unemployment programmes (see table II.19).

146

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.19
LATIN AMERICA (11 COUNTRIES): ORIENTATION OF WELFARE SPENDING BY PRIMARY INCOME QUINTILE
(Percentages)
Total

Income quintile

Gini

Quintile I Quintile II Quintile III Quintile IV Quintile V

Latin America

Social welfare

35

22

17

14

12

100

-0.218

Argentina, 2003

Social promotion and assistance (SPaA)
Public SPaA
SPaA – social work and National Institute of Social
Services for Retirees and Pensioners (INSSJP)

45
47

25
25

17
16

9
8

4
4

100
100

-0.389
-0.415

27

27

24

15

7

100

-0.205

55
50
62
43

25
25
25
17

13
13
9
18

6
9
4
13

2
4
0
7

100
100
100
100

-0.496
-0.429
-0.581
-0.291

Welfare and employment (without insurance)
Employment
Heads of Households programme
Unemployment programmes
Chile, 2006

Monetary subsidies
Targeted subsidies
Bono Puente (Bridge Bond)
Bono Egreso (Exit Bond)
Total bonds CHS
Non-targeted subsidies

52
59
58
59
58
28

25
22
21
27
23
33

15
12
14
11
13
23

5
4
6
4
5
9

4
2
1
0
1
8

100
100
100
100
100
100

-0.460
-0.523
-0.517
-0.566
-0.533
-0.253

Colombia, 2003

Total welfare
Care for children under 7
Instituto Colombiano de Bienestar Familiar (ICBF)
Other official assistance
School meals
Family Subsidies (Caja de Compensación
Familiar -- CCF)

27
33
36
31
37

25
29
28
29
29

20
21
18
23
19

17
14
15
13
12

11
4
3
4
3

100
100
100
100
100

-0.163
-0.292
-0.314
-0.278
-0.336

1

14

19

31

35

100

0.339

Costa Rica, 2004 Social welfare
Nutrition programme

53
53

23
27

9
11

8
9

7
0

100
100

-0.433
-0.488

Ecuador, 1999

Social welfare and others (incl. rural insurance)
Human Development Bond

15
27

20
28

20
25

22
16

23
4

100
100

0.072
-0.232

Guatemala,
2000

Social welfare
School meals
Snack
Breakfast
Powdered milk
Glass of milk
Glass of atole (hot maize drink)
Scholarships
School supplies
School transport subsidies
Electric power subsidies
Other social welfare

14
16
13
17
30
16
17
9
18
0
2

21
25
21
28
26
29
22
4
24
2
3

24
27
26
29
14
25
25
23
24
15
9

21
20
26
17
16
19
23
16
20
56
22

20
11
14
9
14
12
14
48
13
27
65

100
100
100
100
100
100
100
100
100
100
100

0.048
-0.061
0.028
-0.108
-0.168
-0.071
-0.021
0.360
-0.057
0.432
0.575

13

20

16

17

34

100

0.156

Honduras, 2004

Social welfare
Nutrition programme

32
34

20
22

17
16

17
14

14
13

100
100

-0.157
-0.200

Mexico, 2002

Direct transfers
“Oportunidades” programme (direct transfers)
“Procampo” programme (direct transfers)
Other (direct transfers)

49
60
33
60

21
25
16
25

12
10
13
20

11
4
20
1

8
1
18
-6

100
100
100
100

-0.373
-0.558
-0.104
-0.619

Nicaragua, 2005 Social welfare

20

21

21

19

19

100

-0.022

Panama, 2003

Social welfare
Nutrition programme

21
41

18
26

18
18

19
11

24
5

100
100

0.028
-0.349

Peru, 2004

Total food programmes
Glass of milk
Community kitchens
School breakfasts
Mothers’ clubs
School lunches
Children’s canteens
Others (panFar, pacFo, etc.)

24
18
16
53
8
39
28
23

26
23
19
24
30
38
43
41

25
29
33
16
55
15
24
14

20
24
26
5
5
7
6
20

5
7
6
2
1
1
0
3

100
100
100
100
100
100
100
100

-0.177
-0.085
-0.055
-0.482
-0.154
-0.423
-0.370
-0.248

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of national studies.

Social Panorama of Latin America • 2007

147

Table II.20
LATIN AMERICA (18 COUNTRIES): REDISTRIBUTIVE EFFECT OF THE VARIOUS SOCIAL SPENDING ITEMS
(Percentages, concentration and progressiveness coefficients,
and reason for change in the Gini for the weight of each item as part of total social spending)
Country

Public social spending

Aggregate and sector

Significance Concentration Progressiveness Variation in
Relative
as part of
coefficient
coefficient
concentration redistributive
primary
coefficent effectiveness
income
Latin
América

Public social spending
Education, health and social security
Social welfare
Education and Health
Education
Health
Social assistance
Housing, sanitation and others
Primary income
Total income a
Total income

19.4
16.5
6.2
10.4
6.2
4.2
1.8
1.0
100.0
…
…

0.082
0.118
0.409
-0.056
-0.048
-0.067
-0.218
0.042
0.476
0.425
0.412

-0.394
-0.358
-0.067
-0.532
-0.524
-0.543
-0.694
-0.434
…
-0.051
-0.064

-0.064
-0.051
-0.004
-0.050
-0.030
-0.022
-0.012
-0.004
…
…
…

…
0.93
0.19
1.46
1.50
1.58
2.07
1.30
…
…
…

Argentina,
1998

Total public social spending
Education, health and social security
Social insurance
Education and health
Education
Health
Housing, sanitation and others
Drinking water and sewerage
Housing and town planning
Other urban services
Social promotion and assistance
Primary income
Total income a
Total income

21.3
17.0
6.2
10.8
7.7
7.9
2.7
0.3
0.9
1.6
1.6
100.0
...
...

-0.004
0.032
0.212
-0.072
-0.025
0.079
0.060
0.032
0.100
0.042
-0.484
0.514
0.444
0.423

-0.518
-0.482
-0.302
-0.587
-0.539
-0.435
-0.455
-0.483
-0.414
-0.472
-0.998
...
-0.070
-0.091

-0.091
-0.070
-0.018
-0.057
-0.038
-0.032
-0.012
-0.001
-0.003
-0.007
-0.016
...
...
...

...
0.97
0.67
1.24
1.17
0.94
1.04
1.13
0.96
1.09
2.30
...
...
...

Argentina,
2003

Total public spending
Education, health and social security
(insurance and non-contrib. pensions)

Social insurance (not including health)
Social insurance
Social insurance and non-contributory
Seguros sociales y Pensions no
contributivas (no incluye Health)
Non-contributory pensions
Education and health (incl. social insurance)
Education and health (not incl. social insurance)
Education, science and technical studies
Health
Health (not including social insurance)
Housing, sanitation and others
Water and sewers
Housing and town planning
Urban services

15.3

-0.137

-0.683

-0.090

...

11.0

-0.064

-0.610

-0.061

0.93

3.9

0.099

-0.447

-0.017

0.73

3.7
0.8

0.130
-0.114

-0.415
-0.659

-0.015
-0.006

0.68
1.10

1.1

-0.176

-0.722

-0.008

1.21

Primary income
Total income a
Total income

0.2
10.0
7.1
4.9
5.1
2.3
1.3
0.1
0.4
0.9
1.7
2.9
100.0
...
...

-0.400
-0.052
-0.154
-0.097
-0.001
-0.277
0.042
0.001
-0.172
0.138
-0.389
-0.496
0.545
0.485
0.455

-0.945
-0.598
-0.699
-0.642
-0.555
-0.822
-0.504
-0.544
-0.717
-0.408
-0.934
-1.041
...
-0.061
-0.090

-0.002
-0.054
-0.046
-0.030
-0.027
-0.018
-0.007
-0.001
-0.003
-0.003
-0.016
-0.029
...
...
...

1.59
0.92
1.10
1.03
0.89
1.36
0.84
0.92
1.21
0.68
1.55
1.71
...
...
...

Public social spending
Education, health and social security
Social security
Education and health
Education
Health
Primary income
Total income a
Total income

19.2
19.2
5.9
13.3
9.2
4.1
100.0
...
...

0.167
0.167
0.276
0.118
0.068
0.232
0.447
0.402
0.402

-0.280
-0.280
-0.171
-0.329
-0.379
-0.216
...
-0.045
-0.045

-0.045
-0.045
-0.001
-0.039
-0.032
-0.008
...
...
...

...
1.00
0.69
1.24
1.48
0.88
...
...
...

Social promotion and assistance
Welfare and employment (without social insurance)

Bolivia,
2002

148

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.20 (continued)
LATIN AMERICA (18 COUNTRIES): REDISTRIBUTIVE EFFECT OF THE VARIOUS SOCIAL SPENDING ITEMS
(Percentages, concentration and progressiveness coefficients,
and reason for change in the Gini for the weight of each item as part of total social spending)
Country

Public social spending

Aggregate and sector

Significance Concentration Progressiveness Variation in
Relative
as part of
coefficient
coefficient
concentration redistributive
primary
coefficent effectiveness
income

Total income

30.3
30.3
18.9
11.4
5.8
5.6
100.0
...
...

0.272
0.272
0.396
0.065
0.094
0.036
0.560
0.493
0.493

-0.288
-0.288
-0.164
-0.495
-0.466
-0.524
...
-0.067
-0.067

-0.067
-0.067
-0.026
-0.050
-0.025
-0.028
...
...
...

...
1.00
0.62
2.01
1.99
2.24
...
...
...

Chile,
2006

Public social spending
Education and health
Education subsidies
Health subsidies
Monetary subsidies (social welfare)
Primary income
Total income

10.7
9.0
6.3
2.8
1.7
100.0
...

-0.393
-0.384
-0.273
-0.633
-0.460
0.452
0.370

-0.845
-0.836
-0.725
-1.085
-0.912
...
-0.082

-0.082
-0.069
-0.043
-0.029
-0.015
...
...

...
1.00
0.89
1.38
1.18
...
...

Colombia,
2003

Public social spending
Education, health and social security
Pensions
Education and health
Education
Health
Social welfare
Housing, sanitation and others
Public services not including sanitation
Water supply-basic sanitation
Housing
Primary income
Total income a
Total income

16.2
13.7
5.4
8.3
5.3
3.0
1.4
0.8
0.6
0.3
0.0
100.0
...
...

0.098
0.166
0.680
-0.167
-0.094
-0.295
-0.163
-0.040
0.008
-0.150
0.102
0.536
0.491
0.475

-0.438
-0.370
0.144
-0.703
-0.630
-0.831
-0.699
-0.576
-0.528
-0.686
-0.434
...
-0.045
-0.061

-0.061
-0.045
0.007
-0.054
-0.032
-0.024
-0.009
-0.005
-0.003
-0.002
-0.000
...
...
...

...
0.86
-0.36
1.72
1.59
2.14
1.83
1.52
1.40
1.82
1.15
...
...
...

Costa Rica,
2004

Public social spending
Education, health and social security
Pensions
Education and health
Education
Health
Social welfare
Primary income
Total income a
Total income

19.3
18.3
5.5
12.8
6.6
6.2
0.9
100.0
...
...

0.027
0.050
0.471
-0.130
-0.112
-0.150
-0.433
0.518
0.446
0.439

-0.491
-0.468
-0.047
-0.648
-0.630
-0.668
-0.951
...
-0.072
-0.079

-0.079
-0.072
-0.002
-0.074
-0.039
-0.039
-0.009
...
...
...

...
0.96
0.11
1.39
1.43
1.53
2.29
...
...
...

Ecuador,
1999

Public social spending
Education, health and social security
Social Security - Instituto Ecuatoriano de
Seguridad Social (IESS)
Education and health
Education
Health and nutrition (Ministry of Health MINSAL)
Social welfare and others (incl. rural insurance)

9.3
5.9

0.108
0.129

-0.376
-0.355

-0.032
-0.020

...
0.98

Brazil,
1997

Public social spending
Education, health and social security
Social security
Education and health
Education
Health
Primary income
Total income a

Primary income
Total income a
Total income
El Salvador,
2002

Public social spending
Education and health
Education
Health
Primary income
Total income

1.5

0.396

-0.088

-0.001

0.25

4.5
3.4

0.041
0.072

-0.443
-0.412

-0.019
-0.014

1.23
1.16

1.1

-0.060

-0.544

-0.006

1.56

3.4
100.0
...
...

0.072
0.484
0.464
0.452

-0.412
...
-0.020
-0.032

-0.014
...
...
...

1.16
...
...
...

5.0

-0.105

-0.571

-0.027

...

5.0
3.2
1.9
100.0
...

-0.105
-0.089
-0.132
0.466
0.439

-0.571
-0.555
-0.598
...
-0.027

-0.027
-0.017
-0.011
...
...

1.00
0.99
1.08
...
...

Social Panorama of Latin America • 2007

149

Table II.20 (continued)
LATIN AMERICA (18 COUNTRIES): REDISTRIBUTIVE EFFECT OF THE VARIOUS SOCIAL SPENDING ITEMS
(Percentages, concentration and progressiveness coefficients,
and reason for change in the Gini for the weight of each item as part of total social spending)
Country

Public social spending

Aggregate and sector

Relative
Significance Concentration Progressiveness Variation in
as part of
coefficient
coefficient
concentration redistributive
primary
coefficent effectiveness
income
Guatemala,
2000

Public social spending
Education, health and social security
Social insurance
Education and health
Education
Health
Social welfare
Primary income
Total income a
Total income

6.4
5.1
0.9
4.2
2.9
1.3
1.3
100.0
...
...

0.131
0.138
0.648
0.031
0.032
0.028
0.048
0.549
0.529
0.524

-0.418
-0.411
0.099
-0.518
-0.517
-0.521
-0.501
...
-0.020
-0.025

-0.025
-0.020
0.001
-0.021
-0.015
-0.006
-0.006
...
...
...

...
1.00
-0.25
1.27
1.28
1.31
1.26
...
...
...

Honduras,
2004

Public social spending
Education, health and social security
Pensions
Education y Health
Education
Health
Social welfare
Primary income
Total income a
Total income

12.8
11.1
1.4
9.7
6.6
3.1
1.7
100.0
...
...

0.060
0.094
0.710
0.005
0.037
-0.066
-0.157
0.511
0.470
0.460

-0.451
-0.418
0.199
-0.507
-0.474
-0.577
-0.668
...
-0.042
-0.051

-0.051
-0.042
0.003
-0.045
-0.030
-0.017
-0.011
...
...
...

...
0.94
-0.49
1.16
1.11
1.40
1.64
...
...
...

Jamaica,
1997

Education
Primary income
Total income

5.8
100.0
...

-0.208
0.352
0.322

-0.560
...
-0.031

-0.031
...
...

…
...
...

Jamaica,
2000

Education
Primary income
Total income

9.1
100.0
...

0.012
0.352
0.324

-0.340
...
-0.028

-0.028
...
...

…
...
...

México,
2002

Public social spending
Education, health and social security
Social security
Education and Health
Education
Health
Direct transfers (Social welfare)
Housing, sanitation and others
(residential electricity subsidy)
Primary income
Total income a
Total income

12.8
11.4
1.5
9.9
6.5
3.4
0.6

0.066
0.078
0.377
0.034
0.011
0.078
-0.373

-0.385
-0.373
-0.074
-0.417
-0.440
-0.373
-0.824

-0.044
-0.038
-0.001
-0.038
-0.027
-0.012
-0.005

...
0.98
0.21
1.11
1.21
1.06
2.40

0.8
100.0
...
...

0.236
0.451
0.413
0.407

-0.215
...
-0.038
-0.044

-0.002
...
...
...

0.62
...
...
...

Nicaragua,
2005

Public social spending
Education y Health
Education
Health
Social welfare
Housing, sanitation and others
Primary income
Total income

18.3
14.8
8.5
6.3
2.9
0.7
100.0
...

0.011
0.001
0.051
-0.046
-0.022
0.193
0.434
0.369

-0.423
-0.425
-0.384
-0.480
-0.456
-0.242
...
-0.066

-0.066
-0.055
-0.030
-0.028
-0.013
-0.002
...
...

...
1.04
0.99
1.26
1.24
0.67
...
...

Panama,
2003

Public social spending
Education, health and social security
Pensions
Education and Health
Education
Health
Social welfare
Primary income
Total income a
Total income

16.5
16.1
3.9
12.1
8.4
3.7
0.5
100.0
...
...

0.106
0.108
0.552
-0.036
-0.051
-0.002
0.028
0.538
0.478
0.476

-0.432
-0.430
0.014
-0.574
-0.589
-0.539
-0.510
...
-0.059
-0.061

-0.061
-0.059
0.001
-0.062
-0.046
-0.019
-0.002
...
...
...

...
1.00
-0.04
1.38
1.47
1.40
1.37
...
...
...

150

Economic Commission for Latin America and the Caribbean (ECLAC)

Table II.20 (concluded)
AMÉRICA LATINA (18 PAÍSES): EFECTO REDISTRIBUTIVO DE LAS DIFERENTES PARTIDAS DE GASTO SOCIAL

(En porcentajes, coeficientes de concentración y progresividad, y razón de cambio en el Gini
al peso de cada partida dentro del gasto social total)
Country

Public social spending

Aggregate and sector
Significance
as part of
primary
income

Concentration Progressiveness Variation in
Relative
coefficient
coefficient
concentration redistributive
coefficent effectiveness

Paraguay,
1998

Education
Primary income
Total income

4.0
100.0
...

-0.015
0.441
0.425

-0.457
...
-0.017

-0.017
...
...

…
...
...

Peru, 2004

Public social spending
Education, health and social security
Pensiones
Education and health
Education
Health
Nutrition programmes (social welfare)
Primary income
Total income a
Total income

27.1
4.9
9.3
16.9
9.2
7.7
0.9
100.0
...
...

0.284
0.065
0.605
0.133
-0.026
0.324
-0.177
0.429
0.411
0.398

-0.144
-0.364
0.176
-0.296
-0.455
-0.105
-0.606
...
-0.017
-0.031

-0.031
-0.017
0.015
-0.043
-0.038
-0.007
-0.006
...
...
...

...
3.05
-1.42
2.23
3.67
0.86
5.29
...
...
...

Dominican
República,
1998

Education
Primary income
Total income

3.3
100.0
...

0.035
0.428
0.416

-0.393
...
-0.012

-0.012
...
...

…
...
...

Uruguay,
1999

Public social spending
Education, health and social security
Retirements and pensions
Education and health
Education
Health
Social security and welfare
Primary income
Total income a
Total income

27.4
16.9
8.4
8.4
4.3
4.1
9.5
100.0
...
...

0.020
-0.046
0.268
-0.361
-0.274
-0.452
0.171
0.408
0.342
0.324

-0.388
-0.454
-0.139
-0.769
-0.681
-0.860
-0.237
...
-0.065
-0.083

-0.083
-0.065
-0.011
-0.060
-0.028
-0.034
-0.021
...
...
...

...
1.28
0.42
2.33
2.15
2.71
0.71
...
...
...

Uruguay,
2003

Public social spending
Education, health and social security
Retirements and pensions
Education and health
Education
Health
Social security and welfare
Primary income
Total income a
Total income

26.5
25.3
17.3
8.0
4.3
3.7
18.5
100.0
...
...

0.044
0.130
0.346
-0.341
-0.257
-0.438
0.211
0.421
0.362
0.342

-0.377
-0.291
-0.074
-0.762
-0.678
-0.858
-0.210
...
-0.059
-0.079

-0.079
-0.059
-0.011
-0.056
-0.028
-0.031
-0.033
...
...
...

...
0.78
0.21
2.37
2.18
2.78
0.59
...
...
...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of national studies.
aPrimary income and redistributive impact of education, health and social security.

Social Panorama of Latin America • 2007

151

Chapter III

The quality of education:
inequalities that go beyond
access and educational
progression

The considerable expansion of education coverage,
which in some countries applies to the entire school-age
population, is one of the sector’s most striking advances
in recent decades. These advances, which are the result of
pro-active social and educational policies, have occurred
in periods characterized by relatively sustained (but not
very high) economic growth, a gradual modernization
of State management and increased institutional
development, as well as major sociocultural changes
in society and in terms of the relationships between
social actors. Such improvements have often involved
transformations of management methods in education
systems, sustained budgetary increases, diversification
of funding systems and participation of economic agents
and social stakeholders.
There is consensus around the importance and the
benefits of educational achievement for human development,
citizenship and rights entitlement, increased economic
productivity and a resulting increase in competitiveness,
as well as higher and improved levels of social equity and
participation. Nevertheless, the achievements have not
been evenly spread throughout all spheres of education,

and have served to highlight shortcomings in terms of
the quality of education. To a large extent, the various
problems relating to quality and other difficulties of the
education system (school completion, repetition and dropout) are manifestations of a much deeper and entrenched
phenomenon: social inequality.
States have made considerable efforts in education,
by steadily increasing public spending in that area.
International agencies have proposed guidelines that have
been included in legal instruments and agreed at regional
and international summits, where participants have also
suggested the setting of concrete targets with specific time
frames. Although many such targets are on track to being
achieved, the effects that major social inequalities have on
educational systems have not been significantly tackled.
This has been highlighted by the issue of the quality of
education, which is linked to the success of universal
access to education and higher retention rates.
This chapter examines different educational advances
in the region, the various manifestations of inequality
throughout the education cycle, and the way in which some
of these are part of the problem of education quality.

152

Economic Commission for Latin America and the Caribbean (ECLAC)

A. Advances in the right to education:


access, progression and completion

Since the early 1990s, Latin America and the Caribbean has made considerable progress
in the field of education. Follow-up to the Millennium Development Goals reveals that,
although there are some differences among countries, the region is on track to achieving
the main educational targets by 2015. Some of this progress, such as increased access to
various levels of education, has benefited almost all school-age children and young people.
However, most progress has not been sufficiently equitable or has had unequal effects on
educational progression and achievement. Having said that, socio-economic inequalities of
origin are gradually losing significance in the passage of children and young people through
the educational system.

Education is a fundamental part of every human being’s
development. As stated in article 26 of the Universal
Declaration of Human Rights (1948):
(1) Everyone has the right to education. Education shall
be free, at least in the elementary and fundamental
stages. Elementary education shall be compulsory.
Technical and professional education shall be made
generally available and higher education shall be
equally accessible to all on the basis of merit.
(2) Education shall be directed to the full development
of the human personality and to the strengthening of
respect for human rights and fundamental freedoms. It
shall promote understanding, tolerance and friendship
among all nations, racial or religious groups, and
shall further the activities of the United Nations for
the maintenance of peace.
(3) Parents have a prior right to choose the kind of
education that shall be given to their children.1
Knowledge about the world, as well as about other
people and their codes of conduct, enables people to
interact, integrate and take on different roles in society.
Much of the knowledge acquired in education is adaptive,

1

See http://www.unhchr.ch/udhr/lang/eng.htm.

which facilitates access to new knowledge and advances
concerning reality and how that can change. The content
of education should therefore enable individuals to adapt
to the codes of modernity in their social environment and
consider the changes (particularly technological ones)
they will face in a globalized world.
Generally speaking, formal education tends to be
progressive, that is it establishes steps of increasing difficulty
for the development of skills and abilities among children
and young people. Pre-primary education is the first stage
of organized education, and is mainly intended to prepare
very young children for the school environment. Primary
education is the beginning of the systematic study of reading,
writing and mathematics. As for secondary education, its
first cycle is intended to complete basic education and lay
the foundation for ongoing education. The second cycle of
secondary education is aimed at greater subject specialization
and a deeper understanding of particular subjects, while
specific new content is also introduced. The completion
of the secondary cycle provides access to post-secondary
education (tertiary or non-tertiary), where labour and academic
specializations are acquired (UNESCO, 1997a).

Social Panorama of Latin America • 2007

153

Unlike developed countries, where secondary
education is compulsory, most Latin American countries
only stipulate the basic cycle (primary and early
secondary) as obligatory (see box III.1). However,
educational content is delivered when appropriate in
the learning process and according to the maturity

of pupils, with content relevant to the labour market
imparted later in the educational systems (upper
secondary and post-secondary). This means that dropping
out of school often leaves children and young people
without the basic skills needed to function properly in
the world of work.

Box III.1
DURATION OF EDUCATION CYCLES, COMPULSORY NATURE OF SECONDARY EDUCATION AND INDICATORS
USED TO MEASURE EDUCATIONAL INEQUALITY

Adequate monitoring of the situation of the region’s countries,
taking account of the specificities of their education systems,
requires a consideration of the following general aspects of

school cycles: duration, official age of entry and the number
of years’ compulsory schooling. The table below provides that
information for 19 countries.

Latin America (19 countries): duration of subcycles, age of entry and
number of years compulsory schooling, 1998
Country

Secondary education

Primary education
Duration of cycle (years)

Age upon entry

Years of obligatory
schooling

Age upon
entry
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Ecuador
El Salvador
Guatemala
Honduras
Mexico
Nicaragua
Panama
Paraguay
Peru
Dominican Republic
Uruguay
Venezuela (Bol. Rep. of)

Duration

Lower
secondary

Upper
secondary

Lower
secondary

Upper
secondary

Lower
secondary

Upper
secondary

6
6
7
6
6
6
6
6
7
7
7
6
7
6
6
6
7
6
6

6
6
4
6
5
6
6
6
6
6
6
6
6
6
6
6
6
6
6

3
2
4
2
4
3
3
3
3
3
3
3
3
3
3
3
2
3
3

3
4
3
4
2
2
3
3
3
2
3
3
2
3
3
2
4
3
2

12
12
11
12
12
12
12
12
13
13
13
12
13
12
12
12
12
12
12

15
14
15
14
14
15
15
15
16
16
16
15
16
15
15
15
14
15
15

3
2
4
2
4
3
3
3
3
3
0
3
0
3
3
3
2
3
3

0
0
0
4
0
1
0
0
0
0
0
0
0
0
0
2
0
0
1

ECLAC (with the support of the UNESCO Regional
Office for Education in Latin America and the Caribbean
- OREALC) recently produced a proposal to expand the
targets for the second Millennium Development Goal. The
official target is to ensure that all boys and girls complete a
full course of primary schooling by 2015, and the following
three additional targets considered viable in the region have
been added: (i)  progressive universalization of pre-school
education; (ii) universal completion of lower secondary school
with increasing access to the upper secondary cycle, and
(iii) gradual eradication of illiteracy in the adult population.

The proposal also identified various indicators and data
sources relevant to the monitoring of those targets. There
are plans to use indicators from institutional records, as they
constitute official archives, are generally available in many
countries and tend to be representative. However, such records
often present shortcomings that range from a lack of more
specific indicators (such as information by degree), to their
variable quality and the lack of disaggregated information for
heterogeneous social groups. It is therefore necessary to use
complementary sources, with household surveys constituting the
most common and reliable example. As a result, the proposal

154

Economic Commission for Latin America and the Caribbean (ECLAC)

Box III.1 (concluded)

included a series of indicators from household surveys, as they
have the advantage of displaying inequities according to the
different characteristics of children and young people and, in
the case of educational completion, provide a highly relevant
indicator. It is vital to keep sight of the limitations of household
surveys, such as the fact that they use sample information (which
may be less representative in the case of small population strata)
or the imprecise nature of measuring in complete years for the
purposes of educational statistics.

This chapter studies inequities based on household
surveys carried out in 18 of the region’s countries. The
indicators used are: attendance rate irrespective of level or
cycle and net rates of attendance and completion for each
educational cycle. Indicators of educational progression and
drop out are based on methodology from the 2002-2003
edition of the Social Panorama of Latin America, and use
the criteria indicated in the table above to define age groups
and cycle duration.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), “Hacia la ampliación del segundo objetivo del milenio. Una
propuesta para América Latina y el Caribe”, Políticas sociales series, No. 132 (LC/L.2712-P/E), Santiago, Chile, April 2007. United Nations
publication, Sales No. S.07.II.G.60; United Nations Educational, Scientific and Cultural Organization (UNESCO), Regional EFA Monitoring Report
2003. Education for all in Latin America: a goal within our reach, Santiago, Chile, January 2004; Economic Commission for Latin America and
the Caribbean (ECLAC), Social Panorama of Latin America 2002-2003 (LC/G.2209-P/I), Santiago, Chile, May 2004. United Nations publication,
Sales No. E.03.II.G.185.

1.

Access to education

One of the main achievements has been the increased access
of children and young people to the formal education system.
This is partly the result of significant investment that countries
have made in infrastructure, which has made it possible
to extend the coverage of educational services. However,
this has not always gone hand in hand with the necessary
expansion in the number of teachers and the provision of
the materials needed to support the learning process.
A higher level of supply within the education system
is a necessary yet insufficient condition for increasing
access by the school-age population. Besides the lack
of education services, this population group faces many
problems such as scarce resources (such that families steer
children and young people towards income-generating
activities); the effects of child undernutrition (which
can delay children’s entry into primary education and
hamper educational progression (ECLAC/WFP, 2007));
the large distances to be covered in rural areas (often
accompanied by adverse weather conditions); and the lack
of incentives for older children to remain in school, due
to the opportunity costs associated with studying or the
irrelevance of the curriculum to their interests or reality
(UNESCO/OREALC, 2007).
Since the beginning of the 1990s, access by
the school-age population has increased throughout
education, especially at the higher levels, although there
are differences among countries (see table III.1). This

2

is mainly a reflection of rising standards of attainment
in primary education, which are needed for pupils to
go on to the next level. However, progress in access to
pre-school education has been more moderate, despite
the acknowledged importance of early education in
stimulating the learning process for the rest of children’s
lives. Accordingly the World Education Forum (UNESCO,
2000) set the target of extending and improving protection
and integral education in the early years, especially for
the most vulnerable and disadvantaged children. The
Regional Educational Indicators Project, for its part, set
a target of universalizing early education, which involves
increasing the net rate of enrolment of children aged from
3 to 5 years in Latin America by 100%.2
There is evidence to suggest that the benefits of
pre-primary education are demonstrated by improved
cognitive development and school attainment, lower
drop-out rates, higher enrolment in basic education, adults
with a greater ability to integrate society, higher social
returns, better employment opportunities and increased
productivity. Early education makes a lifelong difference
to children from low socio-economic groups, as it often
provides access to nutrition and food services, primary
health care, family support, etc.
In around 2005, almost 84% of boys and girls one
year younger than the legal age for starting primary
education were attending pre-school education (ages 5

The Regional Educational Indicators Project is supported by the United Nations Educational, Scientific and Cultural Organization (UNESCO).

Social Panorama of Latin America • 2007

155

or 6), which was 24 percentage points higher than the
figure recorded in the early 1990s (less than 63%). In
Costa Rica and the Dominican Republic, the net rate of
pre-primary attendance is still below the Latin American
average from the early 1990s. The rates are also low in

Bolivia and Honduras, with figures of less than 70%. In
Chile, although attendance rates remain relatively low,
State institutions have been making considerable efforts
to increase them (especially among the lower socioeconomic strata) (see box III.2).

Box III.2
PRE-SCHOOL EDUCATION COVERAGE IN CHILE

Pre-school education is not compulsory in Chile, and families
decide on the type of care received by their children. A
significant proportion of services are provided by State
institutions or State-financed institutions such as the National
Board for Nursery Schools (JUNJI), the National Foundation
for Integral Child Development (INTEGRA) and municipal
establishments with pre-kinder and kindergarten services
(mainly for disadvantaged children).
In 2005, out of the 493,709 children attending pre-school
education, 61% were covered by the regular Ministry of Education
system, while 24.7% attended JUNJI or INTEGRA institutions.
Between 2003 and 2006, the net rate of pre-school attendance rose
from 15.9% to 36.9% (with the rate in the first income quintile rising
from 25.4% to 32.3%). However, there remain major differences
in the fifth quintile (households with the highest incomes), where
the net rate of pre-school attendance was as high as 47.4% in
2006 (National Socio-economic Survey, CASEN, 2006).
The priorities of the Government of President Bachelet
concerning young children include providing boys and girls with

more opportunities; offering more equitable coverage; guaranteeing
quality care; facilitating higher levels of learning; respecting diversity,
creating conditions of equality from birth for all girls and boys;
and advocating family participation and integration.
According to data from the Ministry of Education,
when the policy to extend coverage for the first level
of transition was launched in 2001, only 14% of 4-year
olds were covered. By the end of 2006, this figure was
in excess of 60%. Although coverage has increased for
children aged between 5 and 6, there remain significant
gaps in terms of younger children. This limits the economic
participation of women in the poorest quintiles, increases
the workload of those who are employed and hampers
the potential development of the children concerned. In
2006, a quarter (25.5%) of children aged between 0 and
3 were attending day-care centres or nurseries (CASEN,
2006). The challenge of building 800 nurseries has been
met, and the new aim is to assess the quality and equity
achieved in pre-school education.

Source: Ministry of Education, Chile [online] http://www.mineduc.cl/index0.php?id_portal=1; Consejo Asesor Presidencial para la Reforma de las
Políticas de Infancia, El futuro de los niños es siempre hoy. Propuestas del Consejo Asesor Presidencial para la Reforma de las Políticas de Infancia,
Santiago, Chile, June 2006 and National Socio-economic Survey, CASEN 2006.

Attendance among children of primary-school age is
practically universal (97%), although access was already
widespread (91%) in the early 1990s.3 Access by children
and young people at the higher cycles of education has
also increased considerably (in comparison with the low
levels of access of the early 1990s), due to increased school
coverage and higher retention rates in education systems.
Since 1990, attendance among children and young people
of early-secondary age has risen by 12% (from 84% to
94%), while attendance among those of upper-secondary
age rose by over 15 percentage points (from about 61%

3

to 76%). Growth was slightly slower at the tertiary level
(either secondary or post-secondary), with attendance
rising from 28% to 35%. This was mainly due to social
pressure on young people to enter the labour market.
Considerable increases were also recorded in the net
access of young people in the first and second cycles of
secondary education (considering those students who
attend at the level appropriate to their age): the net rate
of attendance in the first cycle rose from 45% to 69%,
while the rate for the second cycle almost doubled from
27% to 47%. This shows that, in just 15 years, significant

Considering only those children of primary school age who actually attend primary school, the net rates were 90% in 1990 and 94% in 2005.
Unlike in higher cycles, at primary level the difference between the two sets of rates is due to pupils who have jumped forward a class. For
further details on the indicators based on household surveys, see box III.1.

156

Economic Commission for Latin America and the Caribbean (ECLAC)

progress has been made in the percentage of 14 to 17 year
olds attending upper-secondary school education. A similar
increase was observed in the net access to tertiary education:
the percentage of young people aged 18 to 23 studying at
post-secondary level rose from 11% to 19%.4
However, this significant progress in access to
education is undermined by the high level of inequality

in the social structure of the region’s countries. One
of the problems inherent in the structure of education
systems —and one that makes them vulnerable to social
inequality— is the cumulative dimension. Throughout
the life cycle, exclusion factors come into play and have
differential (and often permanent) effects on children and
young people (see figure III.1).

Latin America

Chile 03

Argentina 05

Brazil 05

Dominican Rep. 05

Colombia 05
Venezuela (Bol. Rep. of)
05
Uruguay 05

Costa Rica 05

Latin America

Costa Rica 05

Average

Rep. Dominican 05

Quintile I

Peru 03

Chile 03
Venezuela (Bol.Rep. de)
05
Uruguay 05

Average

Argentina 05

Peru 03

Quintile V

Bolivia 04

Mexico 05

Ecuador 05

Panama 05

Quintile I

Ecuador 05

Colombia 05

Brazil 05

Mexico 05

Paraguay 05

Nicaragua 01

Honduras 03

100
90
80
70
60
50
40
30
20
10
0

El Salvador 04

Attendance rate among young
people of tertiary-education age

Latin America

Chile 03

Dominican Rep. 05

Argentina 05

Peru 03
Venezuela (Bol. Rep. of)
05
Brazil 05

Average

Paraguay 05

El Salvador 04

Bolivia 04

Nicaragua 01

Honduras 03

Attendance rate among children and young
people of early-secondary school age

Latin America

Chile 03

Argentina 05

Uruguay 05

Brazil 05

Mexico 05

Panama 05

Costa Rica 05

Quintile V

Average

Costa Rica 05

Panama 05

Quintile I

100
90
80
70
60
50
40
30
20
10
0

Panama 05

Quintile V

Quintile I

Uruguay 05

Ecuador 05

Paraguay 05

Bolivia 04

Mexico 05

El Salvador 04

Honduras 03

100
90
80
70
60
50
40
30
20
10
0

Nicaragua 01

Attendance rate among young people
of upper-secondary school age

Quintile V

Colombia 05

Peru 03

Colombia 05
Venezuela (Bol. Rep. of)
05
Dominican Rep. 05

Ecuador 05

Paraguay 05

Honduras 03

El Salvador 04

Bolivia 04

100
90
80
70
60
50
40
30
20
10
0
Nicaragua 01

Attendance rate among children of
primary-school age

Figure III.1
LATIN AMERICA (17 COUNTRIES): SCHOOL ATTENDANCE RATES AMONG SCHOOL-AGE CHILDREN AND YOUNG PEOPLE,
IRRESPECTIVE OF THEIR CYCLE, BY SELECTED PER CAPITA INCOME QUINTILES, AROUND 2005
(Percentages of total children/young people of that age group)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.

4

The reference used was the quinquennial age group that should have left secondary education under normal conditions (i.e. those who entered
on time without repeating a year or dropping out). This varied among countries (17, 18 or 19 years of age).

Social Panorama of Latin America • 2007

There is a close link between the level of access to
education and reducing disparities.5 General advances
in terms of coverage and access were of greater benefit
to lower income strata, although these same strata are
more affected by the gradual reduction in access to

Educational progression
Figure III.2
LATIN AMERICA AND THE CARIBBEAN (30 COUNTRIES/
TERRITORIES): STUDENTS OF GENERAL SECONDARY SCHOOL
PROGRAMMES WHO REPEATED THE SCHOOL YEAR, 2004
(Percentages)
Brazil a

17
10

Costa Rica
Venezuela (Bol. Rep. of)

8

Argentina a

8
7

Nicaragua

Latin America

Underachievement and grade repetition act as a disincentive
for retaining low-income students, as the opportunity
cost of finishing education cycles rises. High costs are
also involved for education systems. According to the
UNESCO Institute for Statistics, in around 2000, the
cost of grade repetition (albeit with differences among
countries) represented a non-negligible proportion of GDP
in the region. The percentage was less than 0.1% of GDP
in Chile and 0.7% in Brazil, while that proportion was
just below or above 2% of GDP in Argentina, Colombia,
Jamaica, Panama, Peru and Uruguay. It has been calculated
that the region loses around US$ 12.0 billion per year due
to grade repetition (ECLAC/UNESCO, 2005).
Figure III.2 illustrates the percentage of pupils who
repeated secondary level (general programmes) during
2004, according to ministerial records and UNESCO
estimates. The regional situation is fairly uneven, with high
levels of grade repetition observed in several Caribbean
countries/territories, Brazil, Costa Rica, Argentina and the
Bolivarian Republic of Venezuela. However, some of these
differences are as much to do with each country’s varying
demands for school progression and the complexity of
subjects or the number of subjects that pupils are allowed
to fail without having to repeat the entire grade.
The indicators commonly used to measure educational
underachievement (rate of timely completion, estimated
time of completion and grade repetition rate) are adequate
for analysing the internal efficiency of education systems.
Unfortunately, this information does not usually include
student characteristics, which means it cannot be used to
analyse inequalities. One option is to develop indicators
that assess school progression on the basis of household
surveys, although these do not isolate the effects of grade
repetition on drop-out or re-entry situations that occur
prior to measurement.
According to information from household surveys,
between 1990 and 2005 there was a considerable

5

higher levels of education. This is particularly relevant
to net attendance rates, as it is children and young
people from low-income homes who have the most
difficulties in progressing through and completing
levels of education.

Peru a

6

Panama

5
4

Ecuador
Dominican Republic b

3

Guatemala b

3

El Salvador b

3

Colombia b

3

Bolivia b

3

Mexico a

2

Chile a

2

Paraguay a

1

Cuba

0.6
10

Saint Vincent  the Grenadines
British Virgin Islands b
Grenada

Caribbean

2.

157

9
8

b

8

Dominica
Belize

6

Saint Kitts  Nevis

3

Jamaica a

2

Turks  Caicos Islands

2

Trinidad  Tobago

1

Suriname b
Saint Lucia b
Montserrat
Cayman Islands
0

2

4

6

8

10

12

14

16

18

Percentage of repeaters

Source: United Nations Educational, Scientific and Cultural Organization
(UNESCO), Global Education Digest 2006, Paris, 2006.
aProvisional data.
bEstimates from the UNESCO Institute for Statistics.

increase in the timely progression of children aged 10 to
14 throughout primary education and in some levels of
secondary education (from 55% to 78%). The percentage
of timely promotions among students aged 15 to 19 also

The statistical evidence (correlations by periods and cycles) indicates that disparities between quintiles are considerably more rigid in terms
of access to tertiary education. Increased access to tertiary education in the region benefited mainly middle-income strata.

158

Economic Commission for Latin America and the Caribbean (ECLAC)

rose significantly (from 43% to 66%). In both age groups,
the increase was almost 24 percentage points.6
In the youngest cohort, the advances have been
proportionally more beneficial to low-income pupils
(who still have high drop-out rates not captured by
the indicator), except those from the first income
decile (see figure III.3). In the cohort aged 15 to 19,
the advances have been more unequal: favouring

mainly students from middle-income strata (advances
among the richest strata are naturally smaller as
they already had higher rates of timely progression
in the early 1990s). Despite considerable increases
in access for the most disadvantaged strata, students
from such groups nonetheless find it more difficult
to progress, particularly when they reach early and
upper secondary cycles.

Figure III.3
LATIN AMERICA (17 COUNTRIES): CHILDREN AND YOUNG PEOPLE ACHIEVING TIMELY PROGRESSION IN PRIMARY AND SECONDARY
EDUCATION CYCLES, BY HOUSEHOLD PER CAPITA INCOME DECILES, AROUND 1990 AND 2005 a
(Percentages)

100
90

80

Percentages

80
70
60

61

50

46

39

40

81

76

72
63
51

56

63

91

87

84
68

76

70

94
83

87

95

25
20
15
10

30
20

5

10
0

30

Total

Decile 1 Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Decile 10

1990

2005

0

Advances in percentage points

Children and young people aged 10 to 14

Advances in percentage points

100

30

90

Percentages

80
69

70
60
50

44

40
30

26

30

62

56

52

48

36

38

40

76

72

68

88

85

80

71
62

47

51

54

20
15
10

20

5

10
0

25

Total

Decile 1 Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Decile 10

1990

2005

0

Advances in percentage points

Young people aged 15 to 19

Advances in percentage points

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a  ossibility of one year’s underachievement due to late entry into the school system.
P

6

Despite the strong link between the progression of pupils aged 10 to 14 and those aged 15 to 19, this is not a longitudinal analysis. Strictly
speaking, the situation of the two cohorts is therefore independent.

Social Panorama of Latin America • 2007

As a result, disparities in educational underachievement
have widened: among pupils aged 10 to 14, the ratio
between the percentage of underachieving pupils from
the first and fifth per capita income quintiles went from
3:1 to 4:2, while among students aged 15 to 19 the
ratio rose from 2:5 to 3:8. A comparison of quintiles of
students according to their household per capita income
shows that, in 1990, among pupils aged 10 to 14, there
were four underachievers from the first quintile for
every one underachiever from the fifth quintile. In 2005,
there were five underachievers from the first quintile
for every one from the fifth quintile (among students
with late progression, 35.4% are from the lowest 20%
of households in terms of income).7 Among students
aged 15 to 19, the ratio went from 1:2 to 1:4. The lower

3.

8

level of progression inequality among this cohort is
mainly due to the drop-out rate among young people
from low-income households. However, educational
underachievement is precisely one of the factors that
influences school drop-out rates.
It is vital for countries to identify the causes of
underachievement and grade repetition and to formulate
policies that universalize enrolment at a timely age and
improve the rate of progression and retention within the
system. The savings achieved by tackling such efficiencies
can then be used to reinforce those very policies, especially
if they incorporate means of compensating for the effects of
social inequality, so as to improve the quality of the learning
process for those students facing the greatest socio-economic
difficulties at school (ECLAC/UNESCO, 2005).

Completing levels of education

The most substantial progress has been made in the
completion of levels of education, which gives some
indication of knowledge-acquisition achievements associated
with the learning process of each educational cycle.8
Advances in this area have been even more impressive
than progress in terms of access, mainly because levels
of achievement recorded in the late 1980s and early
1990s were considerably lower. Although completion
levels for primary education (5 or 6 years study) were

7

159

already fairly high in the 1990s (79% among 15 to 19
year olds), by 2000 almost 92% of young people were
completing the primary cycle. This progress bodes well
for achieving universal primary education in less than one
generation. However, some countries such as Guatemala,
Nicaragua, Honduras and El Salvador are still a long way
from achieving this target, as levels of completion there
are even lower than the Latin American average from the
early 1990s (see figure III.4).

Households with higher dependency rates tend to have lower per capita incomes, which is why there tends to be a higher concentration of
children and young people in low income strata when the population is divided up into per capita income quintiles. Given that it is not therefore
possible to calculate ratios, quintiles of students were constructed based on age group.
Although completion of educational cycles is a good indicator of various stages of learning being fulfilled, there are many reasons to point
out that its validity is not conclusive: the automatic promotion mechanisms used in some countries (in the first grades of primary education),
along with other factors such as differences in the quality of educational services and the learning tools available to students from different
social groups, make it difficult to formulate concrete statements on the significance of such completion.

160

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure III.4
LATIN AMERICA (19 COUNTRIES): COMPLETION OF CYCLES OF EDUCATION AMONG YOUNG PEOPLE AGED 15 TO 19 (PRIMARY),
20 TO 24 (SECONDARY) AND 25 TO 29 (TERTIARY), AROUND 1990 AND 2005
(Percentages of the total number of children/young people in that age group)

Primary

Early secondary

América Latina alrededor de 199092
2005

Latin America around 1990-2005

71

Chile 1990-2003

98

Cuba 2002

98
Argentina (Gran Buenos Aires)
98
Uruguay (Zonas urbanas) 19901997-2005
96
2005
95
Ecuador (Zonas urbanas) 1990-

Argentina (Greater Buenos Aires) 1997-2005
Uruguay (urban areas) 1990-2005
Panamá 1991-2005
Ecuador (urban areas) 1990-2005

94
93
84
71
71

95
2005
Bolivia (8 ciudades) 1994-2004
94
Paraguay (Zonas urbanas) 1994-

Bolivia (8 cities) 1994-2004
Paraguay (urban areas) 1994-2005

2005

Mexico 1996-2005
Brazil 1990-2005

75
84
72

94

74

94

71

93
56

Costa Rica 92
1990-2005
Venezuela (Rep. Bol. de) 199092
2005
Colombia 1991-2005
91

Costa Rica 1990-2005
Venezuela (Bol. Rep. of) 1990-2005
Colombia 1991-2005
Peru 1997-2003

68
68
73

91

76

República Dominicana 1997-2005
86

Dominican Rep. 1997-2005

58

El Salvador 1995-2004
76

El Salvador 1995-2004

29

71 Honduras 1990-2003

Honduras 1990-2003
Nicaragua 1993-2001
Guatemala 2004

36

Nicaragua 1993-2001

65

33

58
0

20

40

60

80

0

100

20

2005

9
11

69

Argentina (Greater Buenos Aires) 1997-2005

5

39

Panama 1991-2005

13

53

Ecuador (urban areas) 1990-2005

13

59

Bolivia (8 cities) 1994-2004

11

63

Paraguay (urban areas) 1994-2005

10

54
8

41

Brazil 1990-2005

4

49

7

41

Venezuela (Bol. Rep. of) 1990-2005

10

52

Colombia 1991-2005

18

60

Peru 1997-2003

15

65

Dominican Rep. 1997-2005

3

47

El Salvador 1995-2004

5

37

Honduras 1990-2003

2

18

Nicaragua 1993-2001

4

26

Guatemala 2004

4

25
0

20

100

10

74
48

Costa Rica 1990-2005

80

7

Chile 1990-2003

Mexico 1996-2005

100

Tertiary (university, 5 years)

50

Uruguay (urban areas) 1990-2005

80

1990

Upper secondary

Cuba 2002

60

Percentages

Percentages

Latin America around 1990-2005

40

40

60

80

0

100

20

40

60

Percentages

Percentages
2005

1990

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries; the information from Cuba is from the 2002 Housing and Population Census.

Social Panorama of Latin America • 2007

The most striking advances were made in the
completion of secondary education. Completion of the
early-secondary cycle rose from 53% to 71%, partly
thanks to the efforts of many of the region’s countries to
make this two or three year cycle compulsory.
The most significant progress was made in the
completion of the second cycle of secondary education.
Over the course of about 15 years, the percentage of young
people aged 20 to 24 to have completed that cycle almost
doubled from 27% to 50%.
There were also improvements in the completion
of higher education, although on a smaller scale: the
percentage of young people aged 25 to 29 to have
completed at least five years of higher education increased
from 4.8% to 7.4%.
The importance of these advances for the region is
that they have benefited mainly low-income children and
young people. Although advances in educational progression

161

have been somewhat uneven, the retention capacity of
education systems has nonetheless improved.
In summary, increased access to education systems
has mostly benefited low-income strata, although this
has not had a wide enough impact in terms of reducing
disparities in educational achievement.
In all age groups eligible to attend school, increased
access to education has gone hand in hand with a reduction in
inequality. As the level of education increases, however, the
disparities increase because educational underachievement
has a proportionally larger effect on lower income pupils.
As a result, although much of the progress made has
reduced inequality in school attainment, this reduction is
less significant in higher levels of education. This means
that, in tertiary education, advances in completion rates
benefit only a small proportion of low-income young
people, with almost all the progress benefiting students
from middle and higher strata.

Box III.3
UNIVERSALIZATION OF HIGHER EDUCATION IN CUBA

Although higher education in Cuba has been governed by the
idea of universalizing knowledge, the latest phase is one of
transcending the traditional definition of university to develop
the processes involved in close harmony with communities.
The main purpose is to provide mass opportunities for
accessing higher education, which involves providing third-level
studies within all the country’s municipalities so as to facilitate
access by young people who have completed levels 3 or 4 of the
International Standard Classification of Education (ISCED) but were
unable to continue with university studies for some reason.
The new stage is based on three pillars: a new and flexible
model of “blended learning” (face-to-face and distance) that
encourages students to complete their studies and recognizes
the fact that the pace of learning depends on the individual;
the use of public human resources and materials from within
local areas; and other equipment guaranteed to be provided
by the State.
The design of blended learning plans is intended to help
young people combine studies with work responsibilities, on the
basis that they should be trained to the same level, receive the
same qualification and be able to work in the same areas. Unlike
other university programmes, these students are assessed on

their individual progress throughout the course, according to
those subjects passed. The programme does not use concepts
such as grade repetition common in other models of education.
There is no time limit for finishing the course, which ends with
a state exam that is taken once all the relevant subjects have
been passed.
Municipalization promotes the use of the infrastructure
of secondary education at different times of day, guarantees
essential teaching materials and the use of information
and communication technologies (ICTs) and boosts parttime contracts for university teachers and other resident
professionals who are qualified to teach and willing to support
the programme. These professionals have become key players
in the local management of knowledge and the development
of human capital.
Municipalized higher education has made it possible to
raise the gross take-up rate of tertiary education from 21% in
1998 to 33% in 2002, and up to around 60% in 2007, which is
similar to the levels of developed countries.
For the 2006-2007 school year, matriculation for municipal
university places made up 80% of total higher education
enrolment.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of A. López, “Las tendencias de la educación superior
y su expresión en el proceso de universalización de la educación superior cubana”, Havana, Educación Universitaria, 2005; R. Sánchez and
others, “La nueva universidad cubana. Universalización de la educación superior”, document presented at the high level seminar “Construyendo
equidad con políticas sociales”, Havana, 2006 and F. Benítez and others, “El impacto de la universalización de la educación superior en el
proceso docente educativo”, Revista pedagogía universitaria, vol. 11, No. 2, 2006.

162

Economic Commission for Latin America and the Caribbean (ECLAC)

B. Inequality in educational opportunities:


more than differences in income

In recent years, advances in terms of educational access, progression and completion have
not been evenly spread through all sections of the population. Girls and young women
record better educational achievement, which is offset by the deep inequalities that take
hold once they enter employment. Advances have also been made in rural areas, especially
among indigenous populations, although these have not been sufficient to close the gaps
observed in the early 1990s. The intergenerational transmission of educational opportunities
still appears to operate in the form of difficulties in accessing and completing the cycles of
upper secondary, and especially tertiary, education.

Although significant progress has been made in
education, levels of access to the various cycles, as
well as the characteristics of educational progression
and achievement remain seriously affected by economic
inequalities. However, income disparities are only the
expression of a series of processes that differentiate
individuals throughout their lives and that often affect
how their skills develop There are many individual,
family and environmental factors that influence how
individuals tackle and make use of life experiences,
particularly that of education. Given that many of the
variables that affect the ability to compete on equal terms
are interlinked, reference is often made to the “syndrome”
of social exclusion and inequality. In the same sense,
the intergenerational reproduction of poverty is due to
the combined effect of a number of factors including
undernutrition, low levels of education, non-existent
or weak social networks, social discrimination (based
on race or gender), lack of access to various social
services (especially in rural areas), unemployment,
underemployment, informal employment, lack of access
to social protection systems, low income and higher
rates of dependence.

Many editions of the Social Panorama of Latin
America and other ECLAC publications have tackled
the intergenerational transmission of opportunities for
well-being (ECLAC, 1998; 2004c). They have found
long-standing transmission mechanisms of opportunities
related to family characteristics, especially in terms of
assets, educational and cultural levels and capital, family
structure, area of residence and ethnic group.
As access to education systems becomes more
generalized to include a greater number of children
and young people from a range of economic strata,
the foundations should be laid for a transition to more
meritocratic societies in which individuals’ level of
well-being is basically dependent on their own efforts
and choices, rather than on their origins. However, even
as access to education becomes more widely available,
socio-economic origin remains a major determining
factor for differences in educational progression and
completion. The following section outlines the scale
of those differences based on certain characteristics of
origin that can be measured using household surveys:
gender, area of residence and ethnic group, and household
educational capital.

Social Panorama of Latin America • 2007

163

1.Gender differences

30

17

20

0.92

20

0.88

10

0.84

1.12
1.08

60

1.04

48

42

50

1.00

40

0.96

30

0.92

17

20

Parity index

70

91

94

95

Post-secondary
net attendance
rate

Upper-secondary
net attendance
rate

1.50

97

1.40

81

1.30

80

Percentages

69

65

84

66

70
60

30

Completion of primary
cycle

Men

Women

Gender parity index
Men

29

40

55

76

1
1

1
1

3
2

Quintile II

Quintile IV

Quintile V

Quintile I

Quintile II

Quintile III

Quintile IV

19

Completion of secondary
cycle

Women

0.80
0.70

7
5

Quintile III

97

Quintile I

94

Quintile V

Post-secondary
net attendance
rate

Upper-secondary
net attendance
rate

Early-secondary
net attendance
rate

Primary net
attendance
rate

91

Quintile IV

0

88

Quintile III

0.80

81
Quintile I

0

20

Quintile II

10

0.90
24

22

20

0.84

1.00

35

40

10

1.10

50

50

0.88

1.20

Parity index

90

1.16

80

Percentages

100

1.20

93

90

20
Quintile V

93

0.80

(b) Completion of educational cycles
by per capita income quintiles

(a) Net access to various cycles of education

100

Early-secondary
net attendance
rate

Primary net
attendance
rate

0
Figure III.5
LATIN AMERICA (18 COUNTRIES): INDICATORS OF EDUCATIONAL ACCESS AND ACHIEVEMENT,
BY SEX AND INDEX OF DISPARITY BETWEEN MEN AND WOMEN, AROUND 2005 a
(Percentages and rates)


Parity index

the population, especially among girls. Increasing
education offers women different life paths: promoting
autonomy and self-esteem, delaying marriage and
motherhood and better equipping them to care for
children and stay in school.
Governmental and international agencies alike agree
that the greatest advances for women have been precisely
those observed in the sphere of education. In all cycles and
levels of education, access, progression and achievement
93
100
1.20
93
among girls and young women exceed that of males. Gender
90
1.16
parity has been achieved in terms of access to education. If
80
1.12
69
65
overage children (starting or leaving school late) are excluded,
70
1.08
60
1.04
women outnumber men to a greater 48
extent as they progress
42
50
1.00
higher up in the educational system (see figure III.5a).
40
0.96
Percentages

Within the international community, there is wide political
recognition of the importance of gender equality as an end
in itself and as a means to development. In the context of
international goals concerning education, gender equality has
become important as an integral part of anti-discrimination
policies to tackle the various manifestations of inequality.
As stated in the regional report on the implementation
of the Millennium Development Goals (United Nations,
2005), these include labour discrimination, lack of
access to productive resources, inequality in the home,
violence against women and a low level of participation
in decision-making.
The report stresses that combating poverty needs
to involve improvements to the level of education of

0.60
0.50

Completion of tertiary
cycle

Gender parity index

1.10

50

50

1.00

35

40
30

0.90
24

22

Men

29

40

55

76

1
1

1
1

3
2

7
5

20

Quintile V

Quintile I

Quintile II

Quintile III

Quintile IV

Quintile V

Quintile V

Completion of primary
cycle

Completion of secondary
cycle

Women

0.80
0.70

19

Quintile III

97

Quintile IV

94

Quintile I

91

Quintile II

88

Quintile IV

0

81

Quintile III

10

Quintile I

20

Completion of tertiary
cycle

Gender parity index

0.60
0.50

Parity index

60

Quintile II

Percentages

Source: Economic 95 97
Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
1.50
100
91 94
conducted in the relevant countries.
1.40
90 84
81
a  he gender parity index is the ratio between the percentage of women and men and vice versa (depending on the indicator), such that a value over
T 80
1.30
1:00 is favourable to women, while a66
value below 1:00 is favourable to men.
1.20
70

164

Differences in timely access at each level are associated
with two major factors: rates of drop-out and progression
within and between cycles of education. First, although
there are no significant gender differences for drop-out
rates in the region as a whole, boys do tend to drop out
more than girls in all cycles and subcycles of education.
However, trends differ in some countries: in Bolivia,
Guatemala and Peru, the disparity favours males in all
cycles (although this decreases in secondary education).
The proportion of girls who drop out during or after
completing primary education is substantially higher
than among boys. This tendency is even stronger among
indigenous populations in rural areas. In Guatemala, the
situation is reversed in secondary education, with males
displaying higher drop-out rates. Other exceptions include
El Salvador, where drop-out rates are higher among girls
at the end of primary education and during secondary
school. In Mexico, female drop-out is concentrated at the
end of primary education, while in Honduras, Paraguay
and the Dominican Republic, a higher proportion of girls
than boys drop out during the secondary cycle. This is
despite the fact that, in all countries, women have higher
levels of timely progression through all cycles. One
plausible reason for girls’ dropping out is the prevalence of
cultures and subcultures that, to a greater or lesser extent,
define female roles in which the skills acquired in formal
education are of no social relevance. This means that less
value is attached to their progression through school and
improvements in their educational attainment.
On the other hand, women record higher levels of
completion of educational cycles than men, with the female
bias increasing in the higher levels of education (except in
terms of tertiary education). This is because, among women
who complete secondary education, a smaller percentage
go on to tertiary education than among men.
Although the disparities between men and women in
the completion of primary education decreased between
1990 and 2005, amidst a widespread increase in educational
achievement, the differences in the completion of the two
subcycles of secondary education have remained relatively
stable. The trend is different for tertiary education: in
1990, the percentage of men who had completed tertiary
education was slightly higher than among women; today,
that situation has been reversed.

Economic Commission for Latin America and the Caribbean (ECLAC)

The disparities in favour of women in the completion
of primary education widen further down the income
scale, as the poorest groups have a greater incentive to
encourage sons to enter the labour market early. The
situation is different for secondary education, as the
largest achievement disparities are noticeable in the
middle-income strata, which may be a continuation of
the process observed at the primary level: more teenage
boys from low- to middle-income groups enter the labour
market, combined with increased drop out rates among
girls from low-income groups at the end of primary
education. Lastly, tertiary education appears to show
a consolidation of earlier processes, because although
women tend to outperform men in terms of educational
achievement at this level, this trend is more striking in
middle-income strata.
In the early 1990s, the situation was different: although
the overall levels were lower, in the first three quintiles
more men than women completed tertiary education (due
to the traditional reproductive role of women that still
exists, albeit to a lesser degree). Cultural bias in the type
of profession chosen by men and women still exists: in
2004 (according to UNESCO), around 57% of graduates
from tertiary education were women. In the areas of
education, health and well-being and services, women
accounted for 70% of graduates, while only representing
34% of science and technology graduates. Two thirds of
the just under 400,000 women who graduated in 2004
had studied education, social sciences, business and law
(UNESCO, 2006).
In summary, although the situation was already
favourable to women in the early 1990s, further advances
have since been made in terms of gender equity within
education. On the one hand, disparities between men and
women have decreased as part of widespread progress in
education and, on the other, tertiary education has seen
increased access and achievement by women, thereby
reversing the male bias from the beginning of the decade.
This constitutes a major step forward for increasing equal
opportunities for both genders, as increased educational
achievement among women goes some way towards
offsetting the deep inequities they experience in the
labour market, despite some ongoing segmentation of
professions.

Social Panorama of Latin America • 2007

2.


Inequities between urban and rural
areas and ethnic groups

Children and young people living in rural areas find
it more difficult to access education services. Besides
being more likely to be affected by poverty and other
hardships (malnutrition, limited access to health and other
basic services), such children are often unable to attend
school because of the limited supply of establishments
or the distances they would have to cover. In some cases,
the inadequate conditions of schooling are the result of
insufficient infrastructure, maintenance, teaching materials
and teachers.
In the 1980s and 1990s, Latin American countries
made significant efforts to extend the supply of education
in rural areas. In many countries, such investment (mainly
in infrastructure) was made through social investment funds
(ECLAC, 1997), and was not always accompanied by a
corresponding investment in teacher training, furniture
and teaching materials. Nowadays, the difficulties in
accessing education faced by low-income groups (often
concentrated in rural areas) are combined with a lack of
supply of secondary education establishments. This forces
young people and their families to develop migration
strategies for students to study away from home, in
small towns or major cities (depending on the resources
available for that purpose).
In countries that are home to various native and Afrodescendent populations, the above-mentioned exclusion
factors combine with racial discrimination, which manifests
itself in the form of increased marginalization and a
more engrained reproduction of poverty in such groups.
Indigenous peoples, who mainly live in isolated rural
or forest areas, often have huge problems in accessing
education, the content of which is ill-suited to their
sociocultural characteristics and specific needs.
Although disparities in access to education by children
from urban and rural areas are not striking at the level of
primary education, they do increase noticeably in higher
cycles. At the beginning of the period in question, 86% of
children of primary-school age in rural areas had access to
education, and this figure increased by almost 10 percentage
points by 2005. In urban areas, on the other hand, access
increased by just under four percentage points. The most

9

10

165

noteworthy progress in rural areas is undoubtedly the
increased retention rate of young people aged 14 to 18,
with 63% of young people of that age continuing to study,
irrespective of the level of underachievement, compared
with only 41% in 1990.
In terms of educational completion, although there
are major differences between young people from urban
and rural areas, the disparities are smaller than for level of
income (except in the completion of primary education).
Furthermore, extremely significant progress has been
made in rural areas: the level of primary completion rose
from 63% to 84%, completion of early secondary from
28% to 47% and completion of the entire secondary cycle
climbed from 9% to 24%.9 These advances do not seem
to translate into considerable increases in the completion
of tertiary education (up from 0.9% to 1.9%). The lack
of supply of tertiary establishments in rural areas means
that young people with sufficient resources travel and to
and often end up living in the country’s main urban areas
where universities and other post-secondary institutions
are located (see table III.5).
According to the information available for seven
of the region’s countries (Brazil, Chile, Ecuador,
Guatemala, Nicaragua, Panama and Paraguay), there
are some educational disparities based on ethnic origin.
When education begins, 88% of the indigenous and
Afro-descendent children of primary school age are
attending class, compared with 93% among the rest of the
population. In rural areas, access among ethnic minorities
is as low as 85%.
Among indigenous children, 82% of those of early
secondary school age (12 to 14 years) access education,
as do 66% of those of upper secondary age (14 to 17
years).10 Of the latter, only 34% actually attend at
secondary school level (compared with 48% among the
non-indigenous population).
The overall drop-out rate among indigenous pupils is
almost a third higher than among non-indigenous pupils (37%
compared with 23%). In both groups, the highest percentage
of drop-outs occur in secondary school, although 30% of
indigenous pupils who drop out do so in primary school.

Among countries (and areas of geographical coverage) that can be compared over time.
The figures include Bolivia, where the question on ethnic group applied to individuals aged 12 and over in the 2003-2004 Continuous
Household Survey.

166

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure III.6
LATIN AMERICA (16 COUNTRIES): EDUCATIONAL ACHIEVEMENT
BY AREA OF RESIDENCE AND ETHNIC GROUP, AROUND 2005 a
(Percentages and rates)
100
90
80

Percentages

All of these processes translate into striking differences
in achievement between indigenous and non-indigenous
individuals, differences that only increase throughout
education in urban areas. In rural areas, disparities are
only wide in primary school, before narrowing during
secondary and tertiary education (see figure III.6), because
poverty and difficulty in accessing education are common
to all inhabitants.
In summary, although there remain major shortfalls
in educational coverage in rural areas, these are mainly
limited to secondary level. Clear progress has been made
in terms of educational access and achievement, although
rural areas still lag behind their urban counterparts. This
situation increases the challenge of planning educational
investment in rural areas, as it is dependent on the population
structure but also affects the structure of educational
demand through, for instance, youth migration for the
purposes of studying, which reinforces the process of
rural-to-urban migration.
Besides the inequities arising from the lack of
resources in rural areas, another factor that definitely
reinforces inequality is the presence of indigenous and
other minority populations. The settlement patterns of
indigenous peoples tend to be concentrated in rural areas
that are often isolated from large or even medium-sized
cities, which is a further barrier to social inclusion. In

70

94.5

88.3
80.2
65.8
56.7

60
50

43.4

40
30

21.2

20

17.4
5.6

10

2.7

0
Completion of primary cycle

Completion of
secondary cycle

0.8

0.5

Completion of
tertiary cycle

Urban non-indigenous

Rural non-indigenous

Urban indigenous

Rural indigenous

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of special tabulations of data from household
surveys conducted in the relevant countries.
aThe figures only refer to the following eight countries: Bolivia, Brazil,
Chile, Ecuador, Guatemala, Nicaragua, Panama and Paraguay.

addition, the continued existence of single curricula with
no pluricultural content reinforces inequality in access
to education services and prevents such services from
being adequate, culturally appropriate and relevant to the
customs and needs of native ethnic groups.11

Box III.4
SANDWICH EDUCATION FOR THE THIRD CYCLE OF GENERAL BASIC EDUCATION, PROVINCE OF SANTA FE, ARGENTINA

In 1993, Argentina implemented a reform to transfer the
administration of education systems to provinces, extend general
basic education from seven to nine years (divided up in three
two-year cycles) and create a polymodal level to cover the final
three years of secondary education.
The provincial government of Santa Fe decided to
implement the third cycle of general basic education in rural
areas by hiring one or two teachers and an itinerant teacher who
would periodically visit schools to support students’ education.
Furthermore, the provincial government decided that, in the
first year of this cycle, students would go to schools previously
attended for primary education, while the following two years
would be taught in the new secondary schools. These proposals,
born of financial constraints, had a negative effect on the quality
of rural education, as they reduced the number of teachers per

11

pupil, teaching hours and the subject areas covered. This meant
that students from rural areas were clearly at a disadvantage
compared with children from urban areas, especially in terms
of entering the polymodal level.
In this context, parents and teachers of the Agricultural
Family Schools set up the Union of Agricultural Family Schools
in Santa Fe (UEFAS), whose first task was to formulate a study
plan involving sandwich education for the third cycle, while
maintaining the seventh year in general basic education and
adjusting the number of teaching hours and curricula in a way
that did not affect the quality of education. They successfully
implemented a model of sandwich education in which students
board at school for two weeks and then stay at home for two
weeks, carrying out research and pre-defined tasks. This method
has a series of advantages: lower transport costs (as pupils are not

According to article 3 of the United Nations Declaration on the Rights of Indigenous Peoples (2006) “Indigenous peoples have the right of
self–determination. By virtue of that right they freely determine their political status and freely pursue their economic, social and cultural
development” (Social Panorama of Latin America 2006, chap. III). ECLAC and other regional and national agencies have promoted the
implementation of innovative integral bi-literacy methods (simultaneous bilingual literacy) for adults. However, this type of initiative is far
from widespread, and does not tend to involve the formal school system (and therefore misses children and young people) (see the chapter on
Social Agenda).

Social Panorama of Latin America • 2007

167

Box III.4 (concluded)

travelling every day), fewer pupils dropping out due to distance,
a more efficient use of school infrastructure and teaching staff
and increased involvement of families in the education of their
children (now considered key for quality education).
The main results are: lower costs than the traditional
education system (2,867 pesos per pupil per year in agricultural
family schools compared with 2,928 pesos per pupil per year
in State school); lower rates of grade repetition and higher
retention rates (90% of pupils who enter seventh grade go on
to the polymodal level, and 85% of them complete that level).

In the traditional school system, progression from general
basic education to polymodal level is 75.4%, and the average
retention rate is 64.2%.
What happens to pupils once they complete schooling
is also striking: 52% go on to university, 38% enter labour or
productive enterprises in rural areas and 10% work in urban
areas. This means that that pupils have put paid to one of the
main concerns underpinning the programme: that students
from such rural areas may be at a disadvantage compared
with those from rural areas.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the ECLAC-Kellogg project.

3.

Transmission of educational opportunities

ECLAC has often emphasized the fundamental importance
of education and employment as means of economic and
social development. Knowledge and skills constitute
capital that can be used in the labour market to facilitate
social mobility and the maintenance of status through
generations. At the macroeconomic level, a society’s
educational capital increases the productivity and potential
growth of the economy.
The principle of universalizing access to education
aims to provide people with the necessary opportunities for
accessing, progressing through and completing a learning
process, plus the certification thereof. Although equal
opportunities in education do not guarantee individual
and family well-being, unequal opportunities certainly
perpetuate poverty. Inequality of opportunities is a factor
of reproduction, in that it can either facilitate or hamper
the main mechanism for accessing long-term well-being.
This has led to claims that educational capital is, to a
certain extent, inherited.
According to evidence from household surveys,
the differences in access to education between those
from households with low educational capital and
those whose parents completed higher education tends
to increase in proportion with the age of the children
concerned (except in pre-school). This difference in
educational opportunities is not too great up to the age
of 14 or 15 but increases from then onwards, such that
only 26% of young people aged 18-19 whose parents

have low levels of education continue their studies.
This is clearly reflected in net rates of attendance:
only 8% of the low-education group of this age attend
post-secondary education, compared with 68% of those
from households with high educational capital. Young
people whose parents did not complete secondary
education currently have a 30% probability of not
finishing secondary school themselves.
The above shows the strong differences in school
progression among children from households with one
of the two levels of educational capital: the figures for
timely progression among 10 to 14 year olds are 65%
compared with 95%, and among 15 to 19 year olds
the figures are 50% and 90%. In that group, the high
percentage of students who are three or more years behind
(30%) is indicative of the shortfalls with which students
from households with lower levels of education enter the
education system.
However, efforts to increase coverage and school
retention rates have yielded fairly impressive results in
terms of dismantling the main mechanism for transmitting
opportunities. There has been a generalized increase in
the probability of achievement at primary level, especially
to the advantage of children of parents with a lower
level of education. There have also been advances in the
completion of secondary education, although intense
differences remain in terms of the two lowest levels of
education (see figures III.7a and III.7b).

Percentages

98.3

97.1

98.8

95.6

93.6
70.6

Primary
incomplete

98.4
95.8

94.2

Completion of primary in 1990
Completion of primary in 2005
98.4
95.8

100
90
80
70
51.9
60
50
32.7
40
30
32.7
Tertiary
Up to secondary
Secondary20
Technical and
incomplete
complete
complete 10 incomplete tertiary
16.2
0
Education background of household a
Primary
Up to secondary
incomplete
incomplete

Completion of primary in 1990
Completion of primary in 2005

100
90
80
92.7 70
60
50
81.4 40
30
20
10
0

Secondary
complete

Tertiary
complete

Completion of primary in 1990

(b) Completion of secondary education
Completion of primary in 2005
among young people aged 20 to 24

Education background of household a

Percentages

Percentages

85.5

94.2

Economic Commission for Latin America and the Caribbean (ECLAC)

(a) Completion of primary education
among young people aged 15 to 19

100
90
80
70
60
50
40
30
20
10
0

98.8

95.6

93.6

92.7

Percentages

LATIN

98.3

97.1

85.5

98.8
97.1
100
98.4
85.5
70.6
90
95.8
94.2
93.6
80
70
70.6
60
50
40
Figure
30
Primary
Up to secondary
Technical and
AMERICA (18 20
COUNTRIES): EDUCATIONAL COMPLETION AMONG DIFFERENT Secondary
AGE GROUPS,
incomplete
incomplete tertiary
incomplete
complete
10
BY EDUCATION BACKGROUND OF HOUSEHOLD, AROUND 2005 a b
0
Education background of household a
(Percentages)
Tertiary
Primary
Up to secondary
Secondary
Technical and
incomplete
incomplete tertiary
complete
incomplete
complete

Percentages

168

100
90
80
98.3 70
60
95.6 50
40
30
20
10
III.7 0

90.8

91.1
51.9

32.7
76.1

90.8

91.1

76.1

75.5

Technical and
incomplete tertiary

Tertiary
complete

81.4

75.5
32.7

16.2
Primary
incomplete

Up to secondary
incomplete

Secondary
complete

Education background of household a

Technical and
incomplete tertiary

Tertiary
complete

Education background of household a

Completion of secondary in 1990
Completion of secondary in 2005

Completion of secondary in 1990
Completion of secondary in 2005

90.8

100
76.1
90
80
70
60
50
40
30
20
Secondary10
Technical and
3.1
complete
incomplete tertiary
0
81.4

51.9
32.7
32.7
16.2
Primary
incomplete

91.1

Percentages

92.7

75.5

Percentages

Percentages

(c) Completion of tertiary education among young people aged 25 to 29
100
90
80
70
60
50
40
30
20
10
0

Up to secondary
incomplete

5.9
Tertiary
complete

a
Primary
Education background of householdUp to secondary

incomplete

Completion of secondary in 1990
Completion of secondary in 2005

incomplete

100
90
80
70
60
50
40
30
20
10
0

5.4
Secondary
complete

71.6

71.6
18.7
5.9

3.1
18.7
Primary
incomplete

5.4

Up to secondary
incomplete

Technical and
incomplete tertiary

Education background of household a

Secondary
complete

Technical and
incomplete tertiary

Tertiary
complete

Education background of household a

Tertiary
complete

Completion of tertiary in 1990
Completion of tertiary in 2005

Completion of tertiary in 1990
Completion of tertiary in 2005

Percentages

100
90
80
Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
71.6
70
conducted in the relevant countries.
60
aAverage number of years of schooling of the head of household and spouse, as a way of estimating parents’ education. Among those aged 25 to 29, the
50
40
indicator is more biased as a relatively significant proportion has set up their own households. However, using young people of that age who describe
30
18.7
themselves as children of the head of household considerably reduces sample sizes (see ECLAC, 2004c, methodological annex to chapter V).
20
5.9
5.4
bThe information comparing 1990 and 2005 does not include Guatemala, but refers to Bolivia (eight main cities and El Alto) and urban areas in
3.1
10
0
Argentina, Ecuador, Paraguay and Uruguay.
Technical and
Tertiary
Primary
Up to secondary
Secondary
incomplete
incomplete tertiary
complete
incomplete
complete

Education background of household a
Completion of tertiary in 1990
Completion of tertiary in 2005

There is no improvement as far as tertiary education is
concerned. Despite the increase in the completion of tertiary
education, the structure of achievement based on household
educational background (average number of years schooling
of head of household and spouse) remains unchanged
(see figure III.7). It is certainly necessary to incorporate
differentiated mechanisms for accessing post-secondary and
tertiary education that can promote the integration of young
people from traditionally excluded social groups through
various forms of affirmative action (see box III.5).

Significant progress has doubtlessly been made
in combating poverty reproduction by reducing the
transmissibility of educational opportunities. However,
the fact that the children of parents who did not complete
formal education are less likely to complete secondary
education suggests that economic growth and government
efforts have not been effective enough to dismantle
those mechanisms.
Only a complete secondary education offers a
high probability of escaping poverty (ECLAC, 2000b).

Social Panorama of Latin America • 2007

169

Box III.5
SELECTED OPINIONS ON AFFIRMATIVE ACTION IN BRAZILIAN UNIVERSITIES

In Brazil, the growing expansion of the education system at the
basic and secondary levels is posing problems for the population
in terms of entering higher education. As the university system
expands, there is increasing demand for the inclusion of groups
traditionally excluded from public education such as the poor,
Afro-descendents and women. According to the 2003 university
census, public university education had one place for every 8.4
applicants (with one place for every 1.5 applicants in private
universities).
In Brazil the proportion of Afro-descendent population
decreases as level of education increases: while people of African
descent make up 53.2% of the total population at the level of
basic education, the proportion drops to 23% in higher education,
and again to 17.6% among post-graduate students.
Many organizations are involved in tackling the situation
through affirmative action, although these measures have been
resisted on the basis of certain myths. Such myths and their
refutations are as follows:
(i)  The quota system is anti-constitutional as it ignores the
principle of equality enshrined in the Constitution of Brazil.
The Constitutions enshrines de jure rather than de facto
equality, which should be guaranteed by equal opportunities.
Policies that affirm rights are therefore constitutional.
(ii) Quotas go against the principle of academic merit, which
should be the only requirement for entering university.
Academic merit reflects the deep inequalities in Brazilian
society. Social opportunities expand and multiply educational
opportunities. Public policies to repair injustice are ethically
essential.
(iii)Quotas are pointless, as the real problem is the poor quality of
public education. Problems of coverage and quality should be
tackled at the same time, rather than in a given order. Education
needs to improve and be more democratic at all levels.

(iv)The quota system tends to lower the academic standard of
universities. Studies show no loss of quality of education in
universities where the quota system has been introduced.
(v) Brazilian society is opposed to quotas. Various opinion polls
show that Brazilian society recognizes the importance of
quota systems. Over half of federal university chancellors
(both sexes) are favourable to quota policies.
(vi)Quotas cannot include racial or ethnic criteria, as the high
proportion of mestizos in Brazilian society makes it impossible
to distinguish “black” or “white”. In Brazil, almost half of the
population is black. The vast majority are poor, discriminated
against and excluded. This is no coincidence.
(vii) uotas favour black people and discriminate even further
Q
against white poor people. Bill 73/99 favours male and female
pupils from the public education systems and stipulates a
racial and ethnic representation that reflects the region where
the university is located.
(viii) uotas will turn Brazil into a racist society. Racism already
Q
exists in Brazil and it permeates public and private institutions
alike. Quota systems do not create racism but make it visible,
and the debate is a stand against racism.
(ix)Quotas are pointless because the problem is not accessing
but staying in education. It is not a case of choosing between
access and retention, but rather quotas are an effective
means of democratizing opportunities in higher education.
(x) Quotas harm black people themselves as they stigmatize
them as incapable and unworthy of their places at university.
The quota system is considered a democratic victory rather
than a blow to the self-esteem of those who benefit from
it. Groups that are excluded and discriminated against
feel socially recognized when the law creates effective
conditions for combating various forms of discrimination
and segregation.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Pablo Gentili, “Exclusión y desigualdad en el acceso
a la educación superior brasileña: el desafío de las políticas de acción afirmativa”, Caminos para la inclusión en la educación superior en Chile,
Pamela Díaz-Romero (ed.), Acción afirmativa: hacia democracias inclusivas series, vol. 5, Santiago, Chile, Fundación Equitas, 2006.

Although basic education (primary and early secondary)
is no longer a differentiating factor, completing
secondary education and accessing and completing
tertiary education are important. This means that the
social structure observed in previous studies remains
highly rigid (ECLAC, 2004c; ECLAC/GTZ, 2007). This

hampers social mobility, as the fact that it is common
to complete primary (and even secondary) education
reduces its relative value. Widely generalized levels
of education are therefore devalued, as the knowledge
and skills they provide become commonplace within
the labour market.

170

Economic Commission for Latin America and the Caribbean (ECLAC)

C. Quality of education:


another manifestation of inequality

Latin America and the Caribbean is trailing behind developed countries in the acquisition
of the skills needed to function fully in the knowledge society, and this has generated a
debate on the quality of education and inequalities in the system. One of the region’s main
characteristics is the high level of school segregation, which combines with many problems
affecting teacher performance and school environment to reinforce the strong hereditary
nature of educational opportunities that reproduce the striking structure of social inequality
in the education system.

1.

Quality of education: a variety of approaches

In recent decades, the efforts of Latin American and
Caribbean countries in the sphere of education have resulted
in a significant increase in coverage and the expansion of
compulsory education, which in turn provides access to
formal education for a greater diversity of pupils. In the
early 1990s, however, although the demand for education
had become more heterogeneous, it was noted that
supply within the system remained relatively unchanged.
The quantitative growth in access to education was not
accompanied by the required levels efficiency, quality
and equity, which suggested that traditional models of
education were somehow obsolete (Arancibia, 1997).
In this period, policymaking institutions in the field
of education stopped focusing solely on the coverage of
education services and turned their attention to the quality
of teaching and learning processes. This was because,
despite considerable investment in education, the results
were lower than expected. Given that initial inequalities
are maintained or accentuated in the education system
(Marchesi, 2000), it is no longer tenable to believe that
children inevitably learn once in school. Indeed, inequities
affect learning processes and results. Today, the need to
improve the quality of education has become an urgent
need in the region (UNESCO, 2004).
There is no agreed definition of the quality of education,
given that it is multidimensional and covers all aspects of

the education sector. Initially, quality of education was
conceived as the (internal and external) efficiency of
the education system —as an investment contributing to
economic development— and its effectiveness in terms
of the concrete impact of education on the population
(Cohen, 2002). However, these concepts have proved
insufficient in providing a global view of the quality
of education. According to UNESCO (2004b, p. 35),
quality has become a dynamic concept that constantly
has to adapt itself to societies undergoing major social
and economic changes, and it is increasingly important
to encourage predictive and pre-emptive capacity rather
than relying on old quality criteria.
Nowadays, children join a system that offers highly
differentiated services, although they are also strongly
affected by structural inequalities. In this context, equity
cannot be conceived as an educational equality whereby all
children are treated in the same way, but rather a process
of differentiation must be undertaken so that discrepancies
can be compensated for in a way that will lead to equal
opportunities (UNESCO/OREALC, 2007). In this sense,
ensuring quality education for all would constitute a
lifelong process of inclusion (ensuring respect for the
right to education, equal opportunities and participation,
Ministry of Education, Chile, 2004), which would provide
the tools needed to face the various obstacles that exclude

Social Panorama of Latin America • 2007

171

or discriminate against students and limit their learning
or full development as people (Blanco, 2006). Quality
education for all, in addition to being the response to
a demand for equity, must be significant and relevant.
In other words, the content must be appropriate to the
demands of society and the integral development of the
individual, and suited to the specific needs of students
and the social and cultural context.
According to UNESCO, quality education for all
must be based on the following four pillars:
(i) Learning to know, combining a sufficiently wide
general knowledge with the ability to deepen
knowledge in a small number of subjects. This also
involves “learning to learn”, to be able to make the
most of the opportunities of lifelong education;
(ii) Learning to do, to obtain not only a professional
qualification but also a skill that enables the
individual to face a large number of situations and
work in a team, in the context of various social and
employment experiences;
(iii)Learning to live together, developing an understanding
of others and perceiving forms of interdependence
(common plans and being prepared to tackle conflict),
while respecting the values of pluralism, mutual
understanding and peace; and
(iv) Learning to be, so that the individual personality
may blossom and function with increasing autonomy,
good judgement and personal responsibility.
The most important lesson is “learning to learn”. In the
new information society, it is vital to be able to organize the
bewildering amount of information available, select what
is important and subsequently use that knowledge. Such
tasks involve the assimilation of a series of strategies. In a
constructivist conception of school learning, “learning to

learn” involves discovering and making use of cognitive
and metacognitive strategies and conceptual models (the
framework for learning and thought). “Learning to learn”
involves equipping individuals with the tools to learn and
thus develop their learning potential.
The ultimate purpose of learning strategies is teaching
to think: educating pupils so they can achieve autonomy,
independence and critical judgement. It is vital to develop
the ability to reflect critically on the process of learning
itself, so that individuals improve how they learn on a
daily basis, so that learning becomes a personal adventure
that allows them to discover their surroundings and gain
knowledge about and explore their personality. This enables
individuals to constantly recreate and adapt knowledge
and skills in accordance with the economic, social and
cultural changes of the new knowledge society.
A significant and relevant education must also
consider students as individuals, members of a family and a
community, and also citizens of the world who are learning
how to fulfil these roles effectively. With this in mind,
education must be moulded to the specific social, economic
and environmental context by adapting the curriculum or
programme to reflect those conditions: quality education
must be locally important and culturally appropriate. Such
education must therefore be based on the past (native
knowledge and traditions), prove significant in the present
and prepare people for the future by creating knowledge,
essential skills, perspectives, attitudes and values. Quality
education should also promote human rights and defend and
spread the ideals of a fair, equitable and peaceful world in
which people care for the environment, thereby contributing
to intergenerational equity and providing means of making
today’s societies more sustained (Delors and others, 1996;
UNESCO, 2004a).

Box III.6
NOTIONS OF QUALITY IN DIFFERENT THEORETICAL APPROACHES

The issue of quality in education can be
studied through various approaches based
on previous reflections on education.
Although one can clearly distinguish
between such visions, in practice they are
combined and can be complementary. The
approach developed by UNESCO seeks
to integrate several of these visions.
Humanistic approaches: this
ideology is at the crossroads between
humanism (Locke, Rousseau) and the
constructivist theory of learning (Dewey,
Piaget, Vygotsky). From this point of view,

pupils are at the centre of education and
actively participate in learning, with the
teacher as mediator in the learning process.
In this framework, the sole purpose of
assessment is to show pupils the quality of
their learning. Any standardized curriculum
is rejected, since failing to match the
particular needs of the pupils would be
to limit their opportunities.
Behavioural approaches: this is
based on behavioural theories (Skinner,
Pavlov), which are in turn build around
subject conditioning, or using specific

stimuli to manipulate individuals’ behaviour.
From this perspective, pupils are unable
to produce knowledge themselves, so
that the teacher’s role is to direct learning
by adjusting stimulus and response.
Organized teaching is promoted in which
assessment offers an objective indicator of
learning, which is then used to introduce
a positive or negative response based on
the behaviour observed.
Critical approaches: these take a
critical position on the above-mentioned
approaches. According to this view, quality

172

Economic Commission for Latin America and the Caribbean (ECLAC)

Box III.6 (concluded)

is defined by measuring the effectiveness
of the transmission of values, as it is
values that enable order and stability to
be maintained in society. This approach
highlights inequalities in educational
access and defines education as a
legitimization and reproduction of the
structure of inequalities within society.
This view advocates an education that
promotes social change, in which pupils
play an active role in learning, and in which
the curriculum and teaching stimulate a
critical analysis of society.

Indigenous approaches: these stress
how important it is for education to be
relevant to the sociocultural circumstances
of the country and the pupil. This promotes
the local formulation of pedagogical
methods, assessment and study plans,
all with active student participation. This
view promotes a notion of learning that
transcends the boundaries of school to
encompass lifelong learning that builds
on previous knowledge.
Adult education approaches:
generally speaking, these approaches

consider adult experiences as a fundamental
element of education. The more radical
versions of this view state the importance of
adult education as the key to social change.
The work of people such as Paulo Freire
displays a concern for education and its link
with the processes of citizenship building, in
the sense that school must create a space
for participation where the various actors
can make active, voluntary and equitable
interventions, thereby encouraging a
critical view of reality and stimulating the
emergence of political awareness.

Source: United Nations Educational, Scientific and Cultural Organization (UNESCO), EFA Global Monitoring Report 2005. Education for All: the
Quality Imperative, Paris, 2004; Regional Office for Education in Latin America and the Caribbean (UNESCO/OREALC), Quality education for
all: a human rights issue. Educational policies within the framework of the II Intergovernmental Meeting of the Regional Project in Education for
Latin America and the Caribbean (EFA/PRELAC). Background document, Santiago, Chile, 2007; Paulo Freire, La educación como práctica de
la libertad, Mexico City, Siglo XXI editores; Jacques Delors and others, La educación encierra un tesoro. Informe a la UNESCO de la Comisión
Internacional sobre la Educación para el siglo XXI, Paris, United Nations Educational, Scientific and Cultural Organization (UNESCO), 1996.

2.

Measuring the quality of education

Although the characteristics of educational services may
be what springs to mind at the mention of “quality of
education”, quality assessment usually focuses on the
results of education. Despite the fact that the various studies
differ as to which educational results to measure, the main
indicator is an assessment of academic achievement. There
are several ways of measuring achievement, ranging from
the average marks obtained at a given level, this corrected
to the percentage of attendance and the implementation of
tests to measure knowledge, to the use of national (based
on the country’s curriculum) or international standardized
tests that aim to measure skills considered essential to
function in today’s world. International tests have their
share of problems, as they need to be linguistically adapted
and the cultural specificities of the communities involved
must also be considered.
This section uses the reading results from the
2000 round of the Programme for International

Student Assessment (PISA). Unlike mathematics and
science tests, the reading test was administered by the
Organisation for Economic Co-operation and Development
(OECD) in the entire sample of 43 countries including
Argentina, Brazil, Chile, Mexico and Peru (see box
III.7). The regional coverage was less extensive than
in the 1997 study by the Latin American Laboratory for
Assessment of the Quality of Education (LLECE), which
administered language and mathematics tests to third
and fourth grade primary school pupils in 11 countries
(UNESCO/OREALC, 1998a and 1998b). Despite this, the
advantage of the PISA test is that it enables the region’s
countries to be compared with developed countries
and is administered to 15 year olds, which provides
an assessment of the results of learning at the end of
compulsory education. The evidence is illustrative and
the aim is not to establish conclusions on the relevance
of certain factors to student performance.

Social Panorama of Latin America • 2007

173

Box III.7
PISA SKILLS ASSESSMENT TESTS

The Programme for International Student Assessment (PISA) was
developed by the Directorate for Education of the Organisation
for Economic Co-operation and Development (OECD) to measure
how far students approaching the end of compulsory education
have acquired some of the knowledge and skills essential for
full participation in the knowledge society.
Three rounds of PISA have been implemented to date,
with at least three more planned by 2015. The 2000, 2003 and
2006 rounds concentrated on language, mathematics and
science, respectively. Given the relevance of reading skills for
developing other skills and the higher number of Latin American
countries involved, the focus here will be on the 2000 round.a In
this round, students were given nine generally booklets (which
included the reading test) and only four with the mathematics
or science test.
In accordance with recommendations from the PISA
technical team, population parameters were estimated using
the standardized plausible scores in the reading test of each
student (mean = 500 and standard deviation = 100 in OECD
countries), based on the estimated distribution of skills
according to various response patterns and other information.
The statistical tests were carried out using weighted probability
estimates of reading skill.
Five categories were used to analyse the distribution of
plausible scores:
Level 1 (334.76-407.47): students are only capable of
completing less complex tasks such as identifying a single
unit of information, the main theme of a text or making simple
connections with day-to-day knowledge.
Level 2 (407.48-480.18): students are able to carry out
basic tasks such as locating direct information, making simple
inferences, finding the meaning of specified parts of a text and
using some knowledge to understand it.
Level 3 (480.19-552.89): students are able to carry out
moderately complex texts such as locating various units of

information, associating different parts of a text and linking
texts with knowledge they are familiar with.
Level 4 (552.9-625.61): students are able to carry out
more complex tasks such as locating hidden information,
constructing meaning from nuanced language and critically
evaluating a text.
Level 5 (625.62 +): students are able to carry out sophisticated
reading tasks, handle information from complex tests, deduce which
information is relevant to the task at hand, critically evaluate and
establish hypotheses with the ability to use specialized concepts
and knowledge that may go against expectations.
The international database contains a series of indices that
summarize scholastic and extra-scholastic conditions, based on
questionnaires given to students and school principals.b/ Some
individual indices can be worked on by the school community. The
statistical tests used indices summarizing family characteristics
(socio-occupational status, material well-being, educational
equipment, family support for learning, etc.), individual school
indices (pressure to achieve, disciplinary environment, school
integration) and school indices (teacher commitment, education
equipment, proportion of teachers with tertiary education). Interval
and ordinal levels were used, on the basis of quartile groups
within countries, except in the cases of educational equipment
and infrastructure (that used the complete sample) and some
with an unequal distribution (such as the index for household
educational resources). In accordance with the recommendations
made, the unit of analysis was the student (even in analyses of
school characteristics).
Lastly, to control for the effect of untimely progression on
scores, students attending tenth grade were chosen, except when
the official school starting age or the level of underachievement
made it recommendable to use the ninth grade as the sample.
This was the case for Bulgaria, Brazil, Czech Republic, Denmark,
Finland, Germany, Ireland, Hungary, Liechtenstein, Luxembourg,
Macedonia, Poland, Romania, Sweden and Thailand.

Source: Organisation for Economic Co-operation and Development (OECD), “PISA Brochure” [on line] (http://www.pisa.oecd.org) and Regional
Office for Education in Latin America and the Caribbean (UNESCO/OREALC), Universal primary completion in Latin America: Are we really so near
the goal? Regional report on Education-related Millennium Development Goals, Santiago, Chile, October, 2004.
a  ECD has already published the results of the 2006 PISA round that placed greater emphasis on science and again included a high number of
O
Latin American and Caribbean countries.
bAvailable at http://www.pisa.oecd.org.

Based on reading scores classified into five levels of
performance, Latin American countries in general recorded
the worst distributions of results (see figure III.8). Around
31% of students achieved only a rudimentary level of

comprehension of the contents of the reading tests (level 1),
while 23% did not even attain this basic level. This is in sharp
contrast with OECD countries in particular, where only 15%
of students did not exceed level 1 in language skills.

174

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure III.8
LATIN AMERICA (5 COUNTRIES), OECD (27 COUNTRIES) AND OTHERS (11 COUNTRIES): DISTRIBUTION OF 15-YEAR OLD STUDENTS,
BY LEVEL OF PERFORMANCE IN THE 2000 PISA LANGUAGE TEST a
(Percentages)
100
80

9
24

60

30

27

21

28

31

20

Percentages

1.4

0.5
4
14

40

10
5

27

7

0
20
40

18

18

23

60

Bellow level 1

Level 2

Level 3

Level 4

Other countries

Liechtenstein

Hong Kong (SAR, China)

Russian Federation

Israel

Latvia

Bulgaria

Thailand

Romania

Macedonia

Albania

Indonesia

OECD countries a

Republic of Korea

Canada

Finland

Japan

Netherlands

Ireland

Sweden

Australia

United Kingdom

Austria

New Zealand

Iceland

Spain

France

Norway

Czech Republic

Denmark

Italy

Level 1

United States

Belgium

Germany

Switzerland

Poland

Hungary

Greece

Portugal

Luxembourg

Latin American countries

Argentina

Chile

Mexico

Peru

100

Brazil

80

Level 5

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Organisation for Economic Co-operation and
Development (OECD), “Programme for International Student Assessment PISA 2000” [online database] http://www.pisa.oecd.org.
aNot including Mexico.

The results reflect not only lower average performance
among the region’s countries, but also the heterogeneous
nature of achievement among students within a given country,
due to the variety of grades or levels studied by pupils of a
certain age (age 15 in the case of the PISA study). As shown

3.


in previous sections, this is the result of grade repetition,
underachievement and late entry. To control for the effects
of underachievement on performance, students were selected
from one level only (tenth grade), the one that usually
corresponds to the final year of early secondary school.

Factors associated with differences
in educational results

One of the main questions that emerges from the score
differences among countries is if these are associated with
their level of development. This question is related to the
effects of poverty and general levels of well-being in certain
societies, and is implicitly linked to level of investment in
(particularly public) education. It is also worth wondering
whether the low scores of Latin American countries are
due to their high levels of social inequality, which could
be giving rise to education services of differing quality.
General evidence suggests a strong link between levels
of per capita GDP and educational performance, which
is also partly affected by an unequal income distribution
(see figure III.9).

The above-mentioned questions are not intended to
ignore the complex nature of educational processes and
systems: the performance of the region’s students are
below that expected for the countries’ level of wealth
(see figure III.9.a), which points to the existence of other
factors having a more direct effect on achievement.
Differentiating between scholastic and extra-scholastic
factors separates out the various sets of variables that can
effect educational results. Analytically, the results of learning
can be understood as the confluence between both sets
of factors. In this way, it is possible to distinguish factors
associated with the supply of education (infrastructure,
teaching materials, teachers, school autonomy and, at

Social Panorama of Latin America • 2007

175

Figure III.9
LATIN AMERICA (5 COUNTRIES), OECD (25 COUNTRIES) a
AND OTHERS (11 COUNTRIES): AVERAGE SCORES IN THE 2000
PISA LANGUAGE TEST AMONG TENTH-GRADE STUDENTS,
2000 PER CAPITA GDP IN PURCHASING POWER PARITY
DOLLARS AND THE GINI COEFFICIENT
(Averages)

(a) Per capita GDP and performance
550

FIN
KOR

NZL

500

(a) Teachers and school environment

POL

Reading scores

RUS
ISR

450
MEX
CHL

400

ARG

2
R = 0.7668

BRA
350
PER
300
0

5 000

10 000

15 000

20 000

25 000

30 000

35 000

40 000

2000 per capita GDP in PPP dollars

(b) Gini coefficient and performance
550

FIN

CAN

NLD

NZE

500

Reading scores

2
R = 0.2611

HKG
USA

450

BGR

ROM

THA

MEX

ARG

400

CHL
BRA

IDN
350

MKD

ALB

PER

300
0.20

0.25

0.30

education in the region are due to general shortcomings
of education systems (associated with the management of
the curriculum, teachers and classroom factors) or to the
segmentation of education supply and the socio-economic
inequalities affecting pupils, or else a much more complex
process of educational segmentation that is the combined
result of inequalities of origin and unequal distribution
of education services.

0.35

0.40

0.45

0.50

0.55

0.60

Gini coefficient (more recent available)

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of the Organisation for Economic Co-operation
and Development (OECD), “Programme for International Student
Assessment PISA 2000” [online database] http://www.pisa.oecd.org
and World Bank, World Development Indicators [online database] http://
devdata.worldbank.org/dataonline/.
aNot including Iceland and Luxembourg.

the macro level, education spending and its breakdown)
from factors associated with the demand for educational
services (school-age children and, in this section, those
who actually study) and aspects related to the interaction
between the two sets of factors (characteristics of the
education community, disciplinary environment, teacher
support, pressure to achieve and other school attributes).
The question is therefore whether problems of quality in

A common notion in the field of education is that the
achievement of pupils depends on their teachers. This
implies a whole series of individual and group characteristics
that may include the number of teachers, their level of
training, teaching experience, level of support for the
learning process, student commitment, and so on. However,
the evidence provided by the PISA test does not lead to
the conclusion —in terms of a systematic pattern in the
region’s countries— that the characteristics of teachers
(as a profession or in the classroom) are more decisive in
the acquisition of language skills (even after controlling
for extra-scholastic factors and the characteristics of the
school community).
Although there are some differences linked to sufficient
teachers within the school, the level of teacher training and
support is less associated with heterogeneous performance
in this region than it is in OECD countries. This suggests
that, in Latin America, extra-scholastic factors are more
relevant to differences. Nor are teacher characteristics
decisively linked to segmented educational supply or school
segregation: number of pupils per teacher, proportion of
teachers with university training and other well-known
characteristics are not very different between public and
private schools, or between those with differing level
of equipment or with higher concentrations of high- or
low-income students.
However, the evidence suggests that the level of
teacher commitment to activities and to students is more
significant (see table III.8).12 These results are similar to
those obtained in the first study carried out by the Latin
American Laboratory for Assessment of the Quality of
Education (UNESCO/OREALC, 1998b). One of the recurring
themes in the analysis of the education sector’s problems is
that of incentives for teacher performance. Although many
mechanisms exist (from wages to assessment systems), it
is wages that are usually considered key to performance,
not because they are necessarily a factor of motivation, but
because they can be a cause of dissatisfaction. Wages are
also a way of attracting new applicants to the profession
(Morduchowicz and Duro, 2007). In Latin America and the
Caribbean, teachers’ wages are lower than those of other
waged professional and technical workers. Teachers earn just

176

Economic Commission for Latin America and the Caribbean (ECLAC)

over 50% of the average wages of other waged professional
and technical workers in Peru, while teachers earn just
over 90% of the wages of other professions in El Salvador,
Nicaragua and the Bolivarian Republic of Venezuela. In real
terms, wages range from US$ 6,000 per year (in purchasing
power parity, PPP) to just over US$ 15,000 per year (see

figure III.10). Although such wages enable most teachers’
families to avoid poverty, they often do not contribute to a
standard of living conducive to professional development.
This hampers teachers’ continuing professional development
and training, and discourages young people entering tertiary
education from becoming teachers in the future.

PPP in 2000 dollars

Colombia

Costa Rica

Chile

Mexico

Argentina

Honduras

Brazil

Uruguay

El Salvador

Nicaragua

Venezuela
(Bol. Rep. of)

Paraguay

Guatemala

Bolivia

Dominican Rep.

25 000
22 500
20 000
17 500
15 000
12 500
10 000
7 500
5 000
2 500
0
Peru

100
90
80
70
60
50
40
30
20
10
0
Ecuador

Percentages

Figure III.10
LATIN AMERICA (17 COUNTRIES): AVERAGE ANNUAL RATIO OF TEACHERS’ INCOME AND WAGES TO THOSE
OF OTHER WAGED PROFESSIONALS AND TECHNICAL WORKERS, AROUND 2005
(Purchasing power parity in 2000 United States dollars and percentages)

Teachers wages/wages of other professional and technical workers
Annual wage of teachers
Annual wage of other waged professional and technical workers

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations Educational, Scientific and Cultural
Organization/Regional Office for Education in Latin America and the Caribbean/International Institute for Educational Planning (UNESCO/OREALC/
IIEP), La inversión educativa en América Latina y el Caribe. Las demandas de financiamiento y asignación de recursos, Buenos Aires, 2007.

Despite the usual assertion that teachers’ level of
commitment is closely linked to salary incentives, it is no
less true that such commitment can also be strengthened or
compromised by other work conditions: teaching material
and school equipment, management, student ability
and motivation, school environment, and so forth. This
reflects the fact that students from less integrated school
communities (with a weak sense of belonging) perform
significantly worse in the language test (see table III.8).
This gives an indication of the potentially negative effect
that a poor school environment with more aggressive or
excluding relational patterns can have on the learning
process, and also reinforces the findings of the 1997
study carried out by UNESCO/OREALC (UNESCO,
1998a and 1998b).
The challenge of improving teacher performance
(as a way of raising the level of learning) must go hand
in hand with the necessary investment in resources that
enable teachers to optimize their performance. In particular,
12

teachers’ wages need to be the equivalent of other waged
professionals. It is also vital to provide schools with the
sufficient equipment and support materials to guide the
learning process. Furthermore, consideration must be
given to psychosocial aspects and student behaviour that
may promote or hamper the acquisition of skills (such as
how the family values education, communication, family
support for education, study time and strategies, discipline
and the level of school integration).
(b) Issues of the relevance and significance of
education
Although some problems of education quality are usually
attributed to social inequality and educational segmentation,
the general characteristics of education systems should
not be ignored. Students benefiting from better conditions
for the learning process could be expected to attain a
Latin
similar effective level in different countries. However, America

This was measured using an index of the assessment made by school principals of teachers in terms of their morale, involvement in their work,
their pride in and identification with the school and how they valued the educational achievement of students.

Social Panorama of Latin America • 2007

177

a comparison between the top 10% of scores in Latin
American countries and OECD countries reveals a greater
dispersion and a lower range of scores among the former
(see figure III.11).
Figure III.11
LATIN AMERICA (5 COUNTRIES), SELECTED OECD COUNTRIES
(7 COUNTRIES) AND OTHERS (5 COUNTRIES): RANGE AND
CATEGORIES OF PERFORMANCE FOR THE HIGHEST SCORING
DECILE OF TENTH-GRADE STUDENTS a
(Percentages)
850

(c) Social inequality and unequal capacity building
Level 5

800
750
700
650
N 2 Level 3 Level 4

Scores

results in an inappropriate “one-size-fits all’ model.
Manifestations of this include the lack of adaptation of
the school calendar (which fails to consider that children
in rural areas will not attend continuously at harvest
time), or the way that the curriculum is taught, such that
the teachers interacting with the least able pupils talk a
language they do not understand, using examples that
have nothing to do with their situations (thereby implying
that their own life experiences are not valued in school)
(Reimers, 2002).

600
550
500

Israel

Hong Kong (SAR,
China)

Thailand

Russian Federation

Indonesia

United States

United Kingdom

Ireland

France

Italy

Germany

Spain

Argentina

Chile

Mexico

Peru

Brazil

450

Source: Economic Commission for Latin America and the Caribbean
(ECLAC), on the basis of the Organisation for Economic Co-operation
and Development (OECD), “Programme for International Student
Assessment PISA 2000” [online database] http://www.pisa.oecd.org.
aAs ninth-grade students were used in Brazil, estimates are not
comparable in terms of number of years of schooling.

According to international criteria, not even the more
affluent Latin American students sufficiently develop
skills in reading comprehension, interpretation, relations
and abstraction. The results flag up some aspects of the
educational curricula, as they suggest that score differences
could be attributable to the main characteristics of pupils’
learning strategies or the content of the teaching they
receive in formal education. As the above-mentioned
skills are required to participate fully in the knowledge
society, the relevance of curricula to developing such
skills needs to be seriously examined.
This strengthens the argument put forward by UNESCO
that the need to improve the quality of education is now essential
for the region. In addition to the various problems of social
equity within the education system and beyond, educational
curricula do not match the skills required in today’s world,
which is why even the wealthiest students are affected.
Education also lacks relevance in relation to the
characteristics of pupils. Failing to take into account the
particular characteristics of pupils (especially those who
have entered following the generalization of education)

Efforts to generalize educational coverage and access
are based on the fact that it constitutes one of the main
mechanisms of creating equal opportunities for well-being
and social mobility. If capacity building is unequal, it
will be difficult for the education system to become a
key factor in a more inclusive and sustained long-term
economic development.
The main factors associated with differences in the
scores of the tenth-grade pupils are extra-scholastic:
parents’ educational level and socio-occupational status,
material well-being of the household (general equipment)
and educational and communication materials available
at home (see table III.9). The most directly related factor
in all of the five countries from the region that took part
was the availability of educational materials. In this sense,
there is a certain linkage between factors: there is a strong
correlation between parents’ educational level and sociooccupational status, then between the latter and material
well-being, and in turn between that and the availability
of educational resources.
In OECD countries, the situation is somewhat
different. Although this group of factors remains the most
relevant, there are weaker associations between them.
Thus although score differences remain strong, the scores
are significantly higher overall. The exceptions are the
scores of pupils from households with low educational
capital, especially in those countries that have experienced
major migratory inflows, such as Germany or the United
States. Having said that, in all countries analysed, the
intergenerational transmission of education opportunities
continued to operate, this time in the building of capacities
and skills essential for a full participation in society (see
figure III.12).
This poses a major problem as, even in developed
countries, levels of education and skills appear to remain
strongly inherited. However, in developed countries
there are fewer inequities than in Latin America when
people enter education, and the education obtained has
less effect on the level of well-being that can be reached
in a lifetime. In this sense, socio-economic inequality

178

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure III.12
LATIN AMERICA (5 COUNTRIES), SELECTED OECD COUNTRIES (7 COUNTRIES) AND OTHERS (5 COUNTRIES):
LANGUAGE TEST SCORES OF TENTH-GRADE STUDENTS, BY PARENTS’ EDUCATIONAL LEVEL

550
500
450
400

Up to secondary

Up to primary

Other countries

Russian Federation

Special Administrative Region
of Hong Kong, China

Israel

Thailand

Indonesia

a
OECD countries

France

United States

Spain

United Kingdom

Italy

Ireland

Germany

Latin American countries

Mexico

Chile

Tertiary

Argentina

300

Peru

350

Brazil

Language test scores

600

Total tenth-grade students

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Organisation for Economic Co-operation and
Development (OECD), “Programme for International Student Assessment PISA 2000” [online database] http://www.pisa.oecd.org.
aTotal of 26 countries, not including Mexico or Japan.

is less pronounced and, above all, has less impact on
the development of language skills. Differences in the
educational “premium” (income) are also smaller. One
important challenge facing the region is therefore to reduce
inequalities in the quality of employment associated with
level of education.
(d) Educational segregation
One of the common problems in education systems is the
socio-economic and geographic segmentation of service
quality. Wealthier parents prefer to send their children to
schools with more resources, and those schools usually
favour the entry of pupils from families with higher levels of
well-being. Those from lower-income backgrounds, on the
other hand, often have a very small number of educational
options. The schools that take low-income pupils tend to
have shortcomings in terms of infrastructure, educational
inputs and the number and training level teachers. These
are almost always public schools in low-income or rural
areas, where they are practically the only school available
for nearby students. Broadly speaking, education systems
have schools for the poor and schools for the rich.
This “self-selection” process, which tends to be
concentrated at the two ends of the social spectrum, can
turn schools into “ghettos”, with both high-income and
low-income school communities (educational segregation).
This results in some schools having environments conducive
to learning and skill-building, while in others difficulties
are more likely to be generated. There are also considerable
differences in the quality of educational supply.

The characteristics of the education system and the
school environment, are comparatively less relevant
if pupils’ family backgrounds are taken into account.
However, scholastic factors become more important once
extra-scholastic factors are controlled for (except in the
case of individual characteristics).
According to the results of the PISA test carried out
in 43 countries, the characteristics of the educational
community are the next most important factor after
family aspects in estimating score variability in the
reading test. In Latin American countries, in terms of
parents’ socio-occupational status and levels of material
well-being, there is more homogeneity among students
than in developed countries due to a considerably more
endogenous reproduction of education communities
than in developed countries. This is especially true
of students from more affluent backgrounds: while
in OECD countries a high-income pupil is five times
more likely to belong to a school community with
higher levels of well-being, in Latin America the ratio
is 10 to 1 (and as much as 20 to 1 in Peru and Chile).
Although there are about 80 points difference in the
reading test scores between communities with high
and low resources, that difference is 114 points in Peru
and 102 points in Chile. There is also a segmented
supply of education services. In the Latin American
countries that participated in the test, 78% of students
were attending tenth grade in public schools, which is
a slightly lower proportion than in the other groups of
countries. However, the region’s public schools have

Social Panorama of Latin America • 2007

179

a lower level of educational equipment (computers,
laboratories, teaching material, libraries, multimedia
systems, etc.). In the region’s countries, 72% of pupils
in the private system attend well-equipped schools,
while this is the case for only 35% of students in the
public system. This discrepancy is considerably wider
than in other regions studied (see table III.10).
Differences in the availability of educational equipment
between the most developed countries and the remainder
are not as marked as could be expected. On average, 62%
of students in OECD countries attend well-equipped
schools, compared with 44% of students in Latin American
countries. However, there are sharp inequalities in access
depending on whether pupils are from the upper or lower
quartiles of the socio-occupational index: whereas 59%
of students from the highest quartile attend well-equipped
schools, this only applies to 32% of pupils from the lowest
quartile (see figure III.13). This reveals the high degree
of segmentation of educational services depending on the
socio-economic status of the school communities they
serve, with communities at both ends of the social spectrum
tending to be more homogenous. Rich and poor pupils are
therefore separated, and a significant proportion of the
poor students attend public schools with infrastructurerelated and other problems, while most rich students attend
extremely well-equipped private schools.

The high degree of educational segmentation in the
region’s countries reinforces inequality in the use made of
education, as the sociocultural disadvantages of low-income
pupils at the outset combine with the fact that the education
services they access are of a lower quality than those attended
by higher-income pupils, which results in a lower level of
learning among poorer students (see figure III.14).
Generally speaking, the educational system in Latin
America is more affected by the region’s highly unequal social
structure. The rise in secondary schooling accentuates the
stratification of institutional supply and the territorial nature of
the supply increases school segmentation. Both the traditional
and more modern elites send their children to schools that
provide a full day of teaching and a varied curriculum. In
addition, within their strata these students form bonds that
reinforce the social networks and capital needed to find a
good job. Poorer students, on the other hand, usually attend
schools with greater shortcomings in terms of infrastructure,
curriculum and general resources (Morduchowicz and
Duro, 2007). Social stratification is therefore reproduced
at school, thereby weakening the capacity of educational
systems to provide children and young people with more
equal opportunities. Given the above, the educational system
acts more like a social differentiation mechanism that lays
the foundations for the inequalities that will be subsequently
reproduced on the labour market.

Figure III.13
LATIN AMERICA (5 COUNTRIES), SELECTED OECD COUNTRIES (7 COUNTRIES) AND OTHERS (5 COUNTRIES):
PROPORTION OF TENTH-GRADE STUDENTS ATTENDING EDUCATIONALLY WELL-EQUIPPED SCHOOLS,
BY QUARTILES OF PARENTS’ SOCIO-OCCUPATIONAL STATUS a
(Percentages)

Quartile 4 students who attend well-equipped schools

79
66

65
58

55

33
20

26

14

b
OECD countries

France

United States

Italy

Spain

12

13

Quartile 1 students who attend well-equipped schools

78

54

21

26

20
Other countries

79

Israel

71

85

Special Administrative Region of
Hong Kong, China

58

68

Thailand

47

53
48

Ireland

32

Germany

38

United Kingdom

38

Latin American countries

25

Chile

23

49

59

Russian Federation

59
39

Brazil

Peru

10

64

47

Argentina

39

64

Indonesia

82
61

Mexico

100
90
80
70
60
50
40
30
20
10
0

Students who attend well-equipped schools

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Organisation for Economic Co-operation and
Development (OECD), “Programme for International Student Assessment PISA 2000” [online database] http://www.pisa.oecd.org.
aSchools were grouped into two categories based on their level of educational equipment (library, multimedia tools, computer and chemistry
laboratories, etc.).
bTotal of 27 countries, not including Mexico.

180

Economic Commission for Latin America and the Caribbean (ECLAC)

Figure III.14
LATIN AMERICA (5 COUNTRIES): DISTRIBUTION OF LEVELS OF PERFORMANCE IN THE READING TEST AMONG TENTH-GRADE
STUDENTS, BY SOCIO-OCCUPATIONAL STATUS OF THEIR PARENTS AND EDUCATIONAL EQUIPMENT OF THEIR SCHOOLS
(Percentages)

100
3
80

0.3
1

0.1
2

11

17

38

32

20

34

37

40

16

11

Quartile 1 least
well-equipped

Quartile 1
best-equipped

0

15

60
40
20

6
24

38

0
24

37

31
12
2

8

60

Peru

Brazil

Chile

Bellow level 1

Level1

Argentina

Level 2

Level 3

Mexico

Level 4

Quartile 4
best-equipped

Quartile 4 least
well-equipped

Quartile 4
best-equipped

Quartile 4 least
well-equipped

Quartile 1
best-equipped

Quartile 1 least
well-equipped

Quartile 4
best-equipped

Quartile 4 least
well-equipped

Quartile 1
best-equipped

Quartile 1 least
well-equipped

Quartile 4
best-equipped

Quartile 4 least
well-equipped

Quartile 1
best-equipped

Quartile 1 least
well-equipped

Quartile 4
best-equipped

Quartile 4 least
well-equipped

Quartile 1
best-equipped

Quartile 1 least
well-equipped

Quartile 4
best-equipped

Quartile 4 least
well-equipped

Quartile 1
best-equipped

100

Quartile 1 least
well-equipped

80

Latin American countries

Level 5

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Organisation for Economic Co-operation and
Development (OECD), “Programme for International Student Assessment PISA 2000” [online database] http://www.pisa.oecd.org.

Social Panorama of Latin America • 2007

181

D. Conclusion
Spending a higher or lower number of years in school is not the only source of inequality
in education. The quality of the education received by children and young people is largely
dependent on their economic resources. This is linked to the educational environment of
the household, the effects of which include the existence of a home environment more or
less suited to reinforcing the learning process. As attainment at the primary and secondary
school levels has become more widespread, disparities in educational quality now play a
major differentiating role in the transition to post-secondary education, which provides the
key to decent jobs and sufficient wages. The quality of education therefore becomes a focus
in the intergenerational reproduction of opportunities for well-being.

It is vital to establish or strengthen various compensatory
mechanisms to create a level playing field in which
the most disadvantaged students can progress through
promotion systems that use higher standards to conduct a
more homogenous evaluation of the skills now considered
essential for the full development of social citizenship. This
means levelling upwards, rather than simply raising pupil
retention and completion by compromising the quality and
effectiveness of teaching processes. This involves, inter
alia, ensuring that automatic promotion processes do not
become a disincentive for teacher performance.
Although such extra-scholastic factors carry some
weight, any review of student performance shows that these
can be offset from within the educational system. Studies
of schools with outstanding performance in adverse socioeconomic conditions indicate the importance of school
management, including less emphasis on hierarchy and
authoritarianism, respect for people, close relations with
parents and participation in the decision-making process.
In terms of teaching practice, positive factors include a
wide range of teaching strategies, emphasis on homework,
group work and high expectations for pupils on the part
of teachers (UNESCO/OREALC, 2002).
Educational reform processes need to be boosted
not only for the organic restructuring of the education
system, a more efficient use of resources and improved
infrastructure in a context of the gradual unversalization
of education, but also to introduce major innovations in
educational models, both in terms of learning methods

and content and the participation of various actors in
school life.
It is also vital to ensure that teachers have postsecondary training to enable them to: acquire the necessary
pedagogical tools, earn a wage that is sufficient and
perceived as such (to avoid having to hold down another
job), and feel that their expertise and working methods
help pupils to acquire skills. It is essential to provide
schools with enough equipment and support materials
so that teachers have the right tools with which to guide
the learning process. Other recommendations include not
grouping students according to particular characteristics,
involving parents in school activities, promoting a respectful
classroom environment and harmonious relations between
pupils, allocating more time for reading for pleasure and
developing a more positive attitude towards reading, as
well as providing a wider range of materials (UNESCO/
OREALC, 2004).
It should be borne in mind that education is a fundamental
human right, and should therefore contribute to the integral
development of individuals. Education should not been seen
as simply instrumental, or as merely a preparation for entry
into the productive system. Education is a constant learning
process, which includes elements from school, non-school
and informal systems that come together to promote values,
the arts, science and technical skills, interculturalism,
respect for ethnic minorities and widespread access to
new technologies. At the same time, systems should also
promote in students a vocation for democracy, human

182

rights, peace, freedom, solidarity, acceptance of diversity,
tolerance and gender equity (ECLAC/Ibero-American
Youth Organization (OIJ), 2004; OIJ, 2005).
Lastly, the region must not lose sight of the fact that
the high level of school segregation not only reproduces
educational gaps between the rich and the poor, but also
perpetuates feelings of belonging and social integration
in school microcosms, thereby sowing the seed for the
high levels of socio-economic polarization present in
Latin American society (see Gasparini and Molina,
2006). From childhood, school can therefore trigger the
construction of what are often well-defined but conflicting
social identities and subcultures that may undermine the
sense of belonging to a common society and hamper the
formulation of a new contract to reinforce social cohesion

Economic Commission for Latin America and the Caribbean (ECLAC)

(ECLAC/ Ibero-American Secretariat (SEGIB), 2007).
Reducing school segregation and segmentation is
not only about improving the quality of education for
all, but is also part of the strategy needed to tackle the
region’s economic, social and political fragility. An
indispensable part of this task is to build a new social
cohesion covenant in Latin America and the Caribbean,
while the major stumbling block is the persistent and
yawning social inequality in the region. The new social
contract must explicitly include educational policies
that tackle the problem of social inequality head on,
by means of affirmative action to compensate for the
disadvantages of the poorest students and improve the
quality of the learning process while reducing the high
level of stratification within education systems.

Social Panorama of Latin America • 2007

183

Table III.1
LATIN AMERICA (18 COUNTRIES): ATTENDANCE RATES IN DIFFERENT CYCLES OF EDUCATION AMONG SCHOOL-AGE
CHILDREN AND YOUNG PEOPLE, a NATIONWIDE TOTALS, AROUND 1990 AND 2005
(Percentages)
Country

Year

Children of pre-school Children of primaryschool age attending…
age attending…b

Children and
young people of
early-secondary
age attending…

Young people of
upper-secondary
age attending…

Young people of
post-secondary
age attending…

school

pre-school
education

school

primary
education

school

earlysecondary
school

school

uppersecondary
school

school

postsecondary
school

Argentina (Greater
Buenos Aires)

1997
2005

…
93.1

73.3
92.8

98.8
98.9

97.7
96.5

97.3
98.4

76.1
76.8

74.5
86.5

45.1
42.4

40.0
40.3

27.9
32.1

Argentina
(urban areas)

2005

89.3

89.0

99.0

97.0

97.7

76.0

85.7

39.1

44.9

35.6

Bolivia
(8 main cities
and El Alto)

1994

55.7

54.8

95.9

92.7

97.6

54.4

87.9

65.2

53.4

36.4

2004

69.4

68.7

97.6

93.9

96.7

56.4

89.0

65.4

49.4

34.4

Bolivia

2004

52.2

52.0

76.1

74.1

71.9

39.2

65.4

43.9

35.5

22.5

Brazil

1990
2005

58.7
90.3

58.1
88.5

86.3
97.9

85.3
94.3

82.3
96.7

39.3
73.3

56.2
81.6

16.1
46.1

23.9
33.6

5.7
13.4

1990
2003

…
…

53.0
77.7

96.6
99.1

96.0
99.1

97.1
99.0

48.7
62.3

80.8
93.1

60.0
71.1

27.8
41.7

15.5
26.6

Costa Rica

1990
2005

…
…

6.7
57.5

87.2
98.7

86.8
98.6

77.4
91.8

39.2
54.1

53.3
79.6

17.6
26.8

26.6
48.0

13.8
21.7

Colombia

1991
2005

43.4
80.5

39.5
79.3

83.2
96.3

80.6
93.7

81.0
92.9

46.4
65.4

63.6
77.4

21.6
36.9

32.2
33.6

10.6
18.4

Chile

Ecuador
(urban areas)

1990

…

…

96.9

94.9

92.3

65.3

78.5

46.6

45.3

24.4

2005

85.5

75.1

96.5

81.7

90.8

57.6

77.9

65.5

41.9

29.6

Ecuador

2005

77.8

67.5

95.7

82.7

85.9

54.4

69.5

55.9

35.2

22.8

El Salvador

1995
2004

62.2
75.3

58.1
75.1

86.0
92.5

83.2
89.3

72.3
81.8

36.0
50.7

46.5
57.4

25.3
31.6

21.5
19.8

12.2
12.7

Guatemala

2004

…

…

84.7

82.5

65.8

29.0

46.4

12.9

18.5

10.8

Honduras

1990
2003

35.9
69.0

34.5
67.7

81.3
90.6

80.2
88.8

55.5
66.0

19.4
33.0

27.5
41.4

7.6
18.9

13.0
21.1

4.8
8.9

Mexico

1996
2005

…
…

76.8
89.8

96.7
98.2

94.9
96.9

84.0
90.8

58.4
72.1

54.6
63.7

36.5
47.2

23.9
30.9

12.8
21.0

Nicaragua

1993
2001

48.8
…

32.9
77.2

78.8
87.9

75.5
83.5

65.7
77.3

27.8
39.2

48.3
51.8

11.5
17.2

23.1
28.1

7.0
14.6

Panama

1991
2005

45.6
70.5

45.1
70.0

95.2
97.9

93.5
97.2

86.5
91.3

58.3
65.9

68.1
79.0

42.5
51.9

32.2
37.1

19.9
25.2

Paraguay
(urban areas)

1994
2005

…
…

35.3
74.2

92.5
96.9

92.3
95.9

89.2
94.8

40.4
62.6

64.8
83.1

34.9
48.4

29.1
38.2

13.9
21.5

Paraguay

2005

…

60.5

95.3

94.4

89.2

53.3

71.3

38.1

31.8

15.5

Peru

1997
2003

…
76.7

69.6
76.4

94.5
95.8

94.4
93.6

88.9
91.1

29.2
61.4

77.1
79.6

11.8
45.8

37.1
36.5

12.6
21.0

Dominican
Republic

1997

74.4

61.3

92.6

91.3

96.0

22.5

82.6

31.6

39.1

13.1

2005

95.6

50.6

97.8

92.8

97.5

44.4

88.3

53.7

45.8

21.6

Uruguay
(urban areas)

1990
2005

…
…

72.2
96.3

98.5
98.6

97.3
97.7

93.9
95.4

65.7
71.6

71.0
78.4

44.2
53.6

34.2
44.8

18.0
26.0

Bol. Rep. of
Venezuela

Latin America

1990

…

64.1

92.2

91.5

88.6

42.9

68.6

20.8

36.8

15.8

2005

85.9

84.3

96.8

91.8

94.3

68.4

81.0

45.0

43.1

26.6

1990
2005

61.6
86.3

60.5
84.2

91.1
97.2

89.7
94.3

83.6
93.5

44.8
68.7

60.5
76.2

26.7
46.6

27.8
34.5

11.0
18.5

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
aCriteria adopted in accordance with the International Standard Classification of Education (ISCED), 1997.
bChildren one year younger than the country’s official age for entering primary education (see box III.1).

184

Economic Commission for Latin America and the Caribbean (ECLAC)

Table III.2
LATIN AMERICA (18 COUNTRIES): TIMELY SCHOOL PROGRESSION AMONG STUDENTS AGED 10 TO 14 AND STUDENTS AND GRADUATES
AGED 15 TO 19, BY SELECTED QUINTILES OF PER CAPITA INCOME, NATIONWIDE TOTALS, AROUND 1990 AND 2005 a
(Percentages)
Country

Students aged 10 to 14 with…

Year

timely progression
Total

Per capita
income quintile

Total

Quintile I Quintile V
Argentina
(Greater
Buenos Aires)
Argentina
(urban areas)
Bolivia (8 main
cities and
El Alto)

Students aged 15 to 19 with…

3 or more years behind
Per capita
income quintile

timely progression
Total

Quintile I Quintile V

Per capita
income quintile

3 or more years behind
Total

Quintile I Quintile V

Per capita
income quintile
Quintile I Quintile V

1997

95.8

93.5

98.0

3.4

6.0

0.8

85.3

72.0

94.8

14.7

29.5

3.9

2005

93.9

90.4

96.5

4.7

5.9

3.7

88.8

79.4

94.8

7.3

13.9

4.0

2005

93.4

89.7

97.3

5.0

7.2

2.6

87.6

79.2

93.4

9.9

18.6

4.4

1994

89.9

87.3

93.7

7.9

10.0

2.9

86.7

81.8

92.8

12.0

17.9

7.1

2004

90.8

86.8

95.8

6.0

6.3

0.8

86.0

82.4

93.6

11.7

18.0

6.0

Bolivia

2004

89.0

82.8

95.0

9.4

19.2

3.1

84.4

75.5

91.8

15.5

29.6

5.9

Brazil

1990
2005

71.6
88.0

50.6
79.7

90.6
97.4

33.5
11.5

59.3
21.6

7.3
2.1

56.4
78.7

23.1
58.6

78.7
93.4

52.0
25.3

83.6
49.8

23.9
6.2

Chile

1990
2003

88.4
91.9

83.6
89.1

92.1
95.2

8.2
2.8

13.2
5.2

3.0
0.9

85.5
87.2

79.8
82.0

89.3
91.0

11.6
6.7

19.1
10.7

4.0
2.5

Costa Rica

1990
2005

82.9
85.6

74.8
79.8

91.9
95.6

15.1
10.3

25.6
16.0

4.5
2.4

76.8
74.6

70.3
65.1

87.1
86.8

27.4
30.0

35.8
41.9

13.7
14.9

Colombia

1991
2005

80.4
86.4

71.8
81.1

91.9
93.1

22.3
12.6

33.0
19.2

7.6
4.7

69.4
83.5

53.7
75.0

79.9
91.6

36.7
18.6

55.4
29.6

23.5
6.6

Ecuador
(urban areas)

1990

90.8

88.2

96.3

8.0

10.2

2.7

81.0

76.1

86.8

21.5

26.8

15.5

2005

96.6

94.2

98.2

3.3

4.1

2.1

91.6

86.8

95.8

8.0

14.3

3.3

Ecuador

2005

94.6

90.3

97.6

5.1

8.6

2.8

89.9

84.3

94.6

10.2

18.3

4.2

El Salvador

1995
2004

80.7
87.3

68.3
79.1

93.3
96.5

21.4
12.7

37.8
23.2

6.9
2.0

80.0
84.2

61.1
67.0

91.3
92.5

23.9
17.7

46.6
39.7

9.9
5.5

Guatemala

2004

81.0

73.8

90.5

16.8

28.5

5.0

75.2

50.1

89.3

29.7

58.8

12.2

Honduras

1990
2003

77.6
83.9

67.5
74.8

89.0
94.3

23.8
16.3

37.5
27.6

7.5
5.0

66.0
74.8

48.5
46.5

75.6
87.9

41.0
30.2

61.5
62.2

28.2
12.6

Mexico

1996
2005

90.0
94.4

80.6
89.8

97.8
98.6

9.2
4.1

19.8
8.6

1.4
0.6

83.3
89.7

73.9
82.8

89.7
94.0

17.0
8.8

30.4
14.2

9.0
4.3

1993
2001

80.5
83.0

68.8
72.3

89.5
89.8

21.7
18.5

37.6
32.9

8.8
9.7

67.9
75.9

51.4
53.3

75.3
86.2

38.4
28.4

58.3
55.6

28.4
15.2

1991
2005

89.4
91.7

82.3
84.6

98.2
99.3

10.1
7.1

18.1
14.9

2.0
0.4

85.3
88.5

76.5
80.7

92.5
94.5

15.8
11.5

27.7
20.6

7.4
2.4

1994

79.7

69.5

87.8

17.9

34.0

4.8

79.7

68.0

86.3

22.4

38.0

16.0

2005

88.0

79.8

96.4

9.0

14.9

0.8

83.0

78.6

89.7

15.4

21.2

8.2

2005

85.1

77.2

96.4

12.1

21.1

2.7

81.5

74.8

88.5

18.1

27.4

7.9

1997
2003

68.9
88.8

52.2
79.8

75.3
97.3

34.3
9.6

57.7
19.9

12.1
1.6

59.4
86.7

37.4
71.6

69.0
95.0

48.3
15.1

72.6
34.1

31.6
6.0

Dominican
Republic

1997

79.2

72.1

88.9

23.2

29.5

12.2

70.7

60.5

79.0

35.4

47.7

25.2

2005

91.8

87.3

94.7

7.6

10.2

5.7

85.3

79.6

90.0

16.8

24.4

9.7

Uruguay
(urban areas)

1990

90.6

83.4

96.8

5.6

11.6

1.9

84.4

75.6

89.2

15.1

26.9

6.1

2005

91.7

84.6

99.2

4.5

8.6

0.7

85.2

73.5

92.3

14.6

30.1

3.1

Venezuela
(Bol. Rep. of)

1990

79.5

72.1

88.2

21.3

31.3

9.1

70.3

62.2

80.6

35.6

45.6

22.0

2005

91.3

87.4

95.7

7.1

11.3

3.1

85.0

79.5

90.9

17.4

24.3

10.3

1990
2005

76.3
88.9

61.8
82.1

89.1
95.6

27.8
10.4

47.6
18.8

7.7
3.5

65.9
82.1

44.2
66.7

80.2
92.5

42.2
21.2

66.3
41.2

22.1
7.1

Nicaragua
Panama
Paraguay
(urban areas)

Peru

Latin America

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a  riteria adopted in accordance with the International Standard Classification of Education (ISCED), 1997. For further details see box III.1.
C

Social Panorama of Latin America • 2007

185

Table III.3
LATIN AMERICA (18 COUNTRIES): YOUNG PEOPLE OF DIFFERENT AGE GROUPS WHO HAVE COMPLETED PRIMARY EDUCATION,
EARLY SECONDARY AND UPPER SECONDARY AND AT LEAST FIVE YEARS OF TERTIARY EDUCATION,
BY SELECTED QUINTILES OF PER CAPITA INCOME, AROUND 1990 AND 2005
(Percentages)
Country

Year

Young people aged 15 to
19 who have completed
primary education

Young people aged 20 to
24 who have completed
early secondary school

Young people aged 20 to
24 who have completed
secondary education

Total

Total

Total

Per capita
income quintile
Quintile I Quintile V

Argentina
(Greater
Buenos Aires)

Per capita
income quintile
Quintile I Quintile V

Per capita
income quintile

Young people aged 25 to 29
who have completed at least
five years of tertiary education
Total

Quintile I Quintile V

Per capita
income quintile
Quintile I Quintile V

1997

97.3

93.6

99.3

68.5

35.0

92.3

49.9

13.8

84.3

11.6

0.0

33.2

2005

97.8

96.2

99.6

84.4

61.9

97.4

69.2

44.0

91.4

11.4

1.4

29.1

2005

97.1

94.6

99.4

83.2

64.2

96.0

68.7

45.0

90.2

10.8

0.8

26.7

Bolivia
(8 main cities
and El Alto)

1994

91.2

90.1

88.9

81.5

79.8

87.6

58.4

54.3

69.7

7.9

2.4

19.8

2004

94.2

92.2

93.9

84.2

72.5

92.5

63.3

47.7

83.5

11.5

0.5

29.5

Bolivia

2004

88.7

73.4

94.8

74.5

43.4

90.2

51.4

19.6

73.5

7.9

0.1

22.8

1990

73.2

46.7

92.7

41.7

12.9

76.6

21.1

3.1

51.5

2.1

0.1

7.4

2005

92.6

83.9

98.5

70.9

37.4

95.3

48.8

15.2

85.6

3.5

0.1

14.4

1990
2003

93.5
98.3

90.0
97.1

97.6
99.5

82.9
94.4

67.5
85.6

95.0
99.0

51.0
73.9

23.1
50.0

79.8
92.5

6.0
9.8

0.2
1.0

19.8
30.0

1990

82.4

70.8

94.4

38.6

16.0

65.3

28.9

10.6

54.2

4.3

0.0

12.4

2005

92.3

86.7

97.6

55.5

33.7

79.0

41.2

17.0

69.4

6.8

0.0

20.2

Colombia

1991
2005

80.0
91.1

70.6
86.5

88.8
96.7

43.8
68.4

21.7
49.7

66.2
88.1

32.8
60.3

12.9
40.0

55.9
84.1

8.3
18.4

0.7
2.4

24.1
50.3

Ecuador
(urban areas)

1990

93.2

91.1

93.9

67.7

55.2

79.2

48.1

32.4

64.6

9.9

2.8

22.5

2005

95.0

90.9

96.2

74.9

53.5

93.5

58.8

32.9

85.1

12.9

1.6

33.5

Ecuador

2005

92.8

86.8

96.4

63.3

35.3

89.7

48.3

22.2

79.4

9.8

0.5

26.5

El Salvador

1995
2004

61.2
76.1

37.1
58.6

84.3
92.9

47.3
58.4

16.3
24.6

79.6
84.1

27.2
36.5

6.2
8.2

58.0
67.7

3.6
4.6

0.0
0.5

12.0
14.4

Guatemala

2004

58.3

36.2

82.2

33.2

10.3

62.7

24.9

6.9

51.6

3.9

0.0

13.0

Honduras

1990
2003

57.9
70.6

39.5
48.1

79.9
90.1

22.8
28.9

7.0
4.9

48.1
62.5

12.7
17.6

1.9
1.2

31.1
42.9

2.2
2.3

0.0
0.0

6.8
7.4

Mexico

1996
2005

87.2
93.9

69.3
85.4

97.5
99.2

62.2
74.1

24.9
42.0

87.2
93.2

23.3
40.6

3.0
11.9

52.6
71.5

7.5
7.7

0.0
0.4

20.7
21.8

Nicaragua

1993
2001

55.2
64.5

34.2
37.4

81.4
86.3

27.7
36.2

12.2
11.4

51.2
64.9

14.4
26.4

6.3
4.4

30.3
55.4

3.2
3.8

0.0
0.3

9.0
12.4

Panama

1991
2005

91.4
95.0

83.6
85.6

97.2
99.4

62.8
70.7

34.9
33.8

81.4
90.2

44.6
52.6

20.5
16.9

69.5
76.9

7.9
13.2

1.4
0.8

23.5
34.4

1994

84.3

71.6

91.3

56.5

26.1

80.0

36.5

12.4

57.8

4.0

0.0

13.6

2005

94.0

86.5

98.4

72.0

38.9

92.5

54.3

18.7

76.4

9.7

0.4

22.6

2005

89.5

80.9

96.5

61.1

31.7

83.3

43.9

13.5

69.1

6.9

0.3

17.2

1997
2003

74.2
91.0

46.6
76.6

91.2
97.5

66.9
73.3

21.7
32.6

87.0
94.4

29.7
64.7

7.3
23.8

47.4
89.5

0.8
14.8

0.0
2.2

2.6
33.8

Dominican
Republic

1997

70.3

59.3

83.7

58.5

41.8

72.7

28.5

14.5

45.1

4.0

0.0

11.4

2005

86.1

81.5

92.0

75.8

60.5

85.5

46.9

29.8

63.3

2.6

0.3

7.7

Uruguay
(urban areas)

1990
2005

96.5
96.4

92.2
91.7

99.7
99.4

66.8
71.3

33.8
34.1

87.9
95.5

31.9
39.2

7.7
7.3

60.0
75.4

4.6
5.1

0.0
0.3

14.3
15.5

Venezuela
(Bol. Rep. of)

1990
2005

83.6
91.5

75.5
87.5

93.0
94.6

50.1
67.6

37.2
51.0

68.8
84.7

33.0
52.5

23.7
35.4

50.3
72.6

5.2
9.5

0.7
2.6

13.9
22.9

Latin America

1990
2005

79.4
91.9

61.0
84.1

92.9
97.5

52.8
71.3

23.9
42.4

78.8
91.8

27.1
49.6

7.9
20.5

53.9
79.6

4.8
7.4

0.2
0.7

14.2
22.6

Argentina
(urban areas)

Brazil
Chile
Costa Rica

Paraguay
(urban areas)

Peru

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
aCriteria adopted in accordance with the International Standard Classification of Education (ISCED), 1997. For further details see box III.1.

2005

Argentina

Bolivia

Nicaragua

Mexico

Honduras

Guatemala

77.5

87.7

46.2

78.1

2005

1993

2001

70.1

2003

1996

33.5

1990

75.1

2004
…

61.2

1995

2004

76.7

2005

Ecuador

El Salvador

…

84.0

2005

80.5

1990

43.0

2005

2005

1991

5.6

54.6

1990

89.9

2005

54.1
78.1

57.7

1990

1990
2003

51.6

2004

67.0

2004

Ecuador
(urban areas)

Colombia

Costa Rica

Chile

87.1

89.6

75.1

58.3

2005

Buenos Aires)

Men

76.2

51.6

91.8

76.0

68.1

38.3

…

75.5

63.2

79.0

87.2

…

80.5

43.8

60.1

7.7

51.9
77.3

90.6

59.7

52.7

71.6

53.2

91.2

96.0

71.5

Women

Pre-school
attendance rates

1994

1997

Argentina (Greater

Bolivia
(8 main cities
and El Alto)

Year

Country

Brazil

Table III.4

83.9

74.1

97.1

94.8

88.0

79.6

83.1

89.6

83.3

82.0

80.6

94.8

93.6

80.0

98.5

86.7

95.8
99.0

94.6

84.5

73.4

94.0

92.6

96.7

96.3

97.4

Men

83.0

77.0

96.7

95.0

89.7

80.8

81.9

89.1

83.2

83.5

83.0

95.1

93.9

81.1

98.8

87.0

96.3
99.1

94.1

86.1

74.9

93.8

92.9

97.4

96.8

98.0

Women

Primary

35.6

24.7

72.4

58.4

29.6

17.3

28.5

48.3

35.2

54.0

58.3

61.3

62.0

44.0

49.2

40.0

46.4
59.3

69.6

36.1

38.4

55.6

52.6

74.5

75.4

75.2

Men

43.3

30.9

71.8

58.4

36.3

21.6

29.5

53.1

36.9

54.7

56.9

69.5

69.0

48.9

58.9

38.3

51.1
65.2

77.3

42.4

40.0

57.3

56.1

77.9

78.6

77.2

Women

Early secondary

18.0

16.0

52.3

45.9

31.7

13.8

24.2

44.6

37.9

63.2

63.2

44.3

40.4

29.6

26.8

29.5

64.6
71.5

46.9

18.0

48.5

64.4

67.4

35.3

38.6

40.4

Men

31.0

20.5

55.1

50.9

33.6

16.9

19.2

39.2

38.5

67.9

67.9

49.0

46.8

30.9

36.1

25.0

66.5
74.4

55.5

23.3

50.0

66.3

63.2

42.9

46.0

50.9

Women

Upper secondary

Net attendance rates

11.5

8.1

20.2

13.9

7.9

4.7

11.8

13.4

11.7

21.6

28.6

23.9

17.4

9.7

19.7

13.8

16.7
27.2

11.5

4.8

24.0

35.9

39.3

31.1

28.0

25.0

Men

17.9

6.0

21.8

11.8

9.8

4.9

9.9

12.1

12.7

24.0

30.5

24.9

19.4

11.4

23.9

13.7

14.4
26.1

15.3

6.6

21.0

32.9

34.0

39.9

36.3

31.0

Women

Post-secondary
or tertiary

23.9

25.4

4.2

9.4

21.3

30.0

21.3

15.6

24.4

4.6

3.1

4.4

7.4

17.8

5.6

13.2

4.7
1.1

3.3

15.3

7.2

2.9

3.9

1.7

1.3

1.4

Men

15.6

21.8

3.8

9.6

15.2

24.8

31.1

14.8

24.8

3.6

2.2

2.7

4.6

13.4

4.1

10.9

3.9
0.7

1.6

11.4

10.1

5.4

8.6

0.8

0.4

0.7

Women

Drop-out rate
during primary
school

46.4

40.3

76.9

63.5

50.9

39.0

50.7

65.2

57.9

77.3

81.2

60.0

62.6

41.8

48.2

56.1

69.4
74.7

55.2

29.0

68.0

69.9

72.5

71.2

75.0

64.7

Men

61.9

43.5

82.7

69.9

56.8

41.4

60.4

73.3

68.3

82.6

85.1

66.0

72.4

48.0

56.7

57.2

74.4
80.9

66.3

35.1

69.8

75.1

74.9

80.2

83.3

77.2

Women

Young people
aged 15 to 19
with timely
progression

58.6

51.6

94.2

87.4

66.8

54.4

64.1

74.4

59.3

91.9

70.8

58.8

93.7

86.9

74.4

61.4

52.7

77.9

63.0

93.7

94.5
95.8

91.9

93.3

82.8

93.7

84.0

94.1
98.7

94.6

77.5

86.8

92.7

89.1

97.7

98.1

97.7

Women

94.2

89.0

77.1

91.0

81.0

93.0
98.0

90.6

69.0

90.5

96.0

93.5

96.6

97.4

96.9

Men

primary school
among young
people
aged 15 to 19

22.8

12.5

40.1

26.0

14.7

10.7

26.8

36.9

25.8

47.4

58.1

44.8

57.8

30.6

39.0

26.6

49.3
71.7

44.1

17.7

56.2

66.7

63.0

65.0

63.8

46.0

Men

29.7

16.1

41.0

20.8

20.4

14.5

23.3

36.1

28.5

49.3

59.5

51.0

62.6

34.6

43.4

31.3

52.6
76.1

53.6

24.4

46.9

60.0

54.3

72.5

74.7

53.6

Women

secondary
school among
young people
aged 20 to 24

Completion of

3.3

2.8

8.5

7.7

2.2

3.0

3.3

4.9

4.2

8.4

11.3

9.7

17.0

8.3

6.0

4.3

5.8
10.0

3.1

2.3

7.8

11.9

9.4

9.2

9.0

9.2

Men

4.3

3.5

7.1

7.2

2.4

1.5

4.3

4.2

3.0

11.1

14.4

10.0

19.5

8.3

7.6

4.2

6.1
9.7

3.9

1.8

8.0

11.1

6.6

12.1

13.5

14.0

Women

tertiary education
among young
people aged
25 to 29 a

LATIN AMERICA (18 COUNTRIES): SELECTED EDUCATIONAL INDICATORS FOR CHILDREN AND YOUNG PEOPLE OF DIFFERENT AGE GROUPS, BY SEX, NATIONWIDE TOTALS
(Percentages)

186
Economic Commission for Latin America and the Caribbean (ECLAC)

Table III.4

43.0

71.6

1991

2005

Panama

67.2

75.9

2005

1997

2003

Paraguay

Peru

1990

Venezuela

1990

72.9
95.8

1990
2005

Uruguay

62.2

84.7

62.9

2005

87.1

62.8

87.3

65.5

65.5

71.5
96.8

95.0

75.0

77.5

71.9

65.2

76.8

31.9

69.2

48.1

Women

94.4

89.4

92.3

91.0

31.8

97.5
97.7

93.1

90.4

93.7

94.7

93.6

95.5

92.8

97.0

93.1

Men

94.2

90.1

91.2

92.0

31.1

97.1
97.6

92.4

92.2

93.5

94.2

95.2

96.4

91.8

97.4

93.9

Women

Primary

66.4

42.7

65.4

38.5

39.6

64.8
69.5

37.8

17.6

61.6

29.0

52.1

63.8

39.3

63.6

56.7

Men

71.2

46.9

71.6

47.3

49.0

66.6
74.0

50.8

27.7

61.2

29.4

54.4

61.6

41.4

68.3

59.9

Women

Early secondary

49.0

31.0

40.3

17.0

19.6

38.9
48.7

53.4

30.9

54.7

15.5

43.2

43.2

35.0

54.6

43.7

Men

55.3

35.4

49.9

24.9

27.7

49.8
58.7

61.9

46.5

58.2

16.2

53.5

53.5

34.8

66.8

53.6

Women

Upper secondary

Net attendance rates

16.8

10.5

22.2

13.9

13.9

15.5
21.8

19.2

10.9

19.1

10.9

13.4

20.5

13.3

20.3

17.8

Men

20.1

11.5

31.2

17.8

17.8

20.4
30.0

24.3

15.3

23.0

14.2

17.6

22.4

14.4

30.2

22.1

Women

Post-secondary
or tertiary

4.6

12.6

6.8

12.2

12.1

2.9
3.2

7.3

11.9

5.0

16.3

10.4

4.7

12.5

2.8

6.9

Men

3.2

10.5

3.2

7.6

7.6

1.5
1.6

5.2

8.1

7.5

16.3

5.8

3.3

12.3

2.8

4.6

Women

Drop-out rate
during primary
school

61.1

35.3

65.7

41.3

41.3

65.0
65.4

63.9

41.7

71.9

21.7

57.9

61.7

56.8

69.6

66.1

Men

71.0

40.6

76.6

50.9

50.9

72.2
75.3

79.5

56.5

77.0

28.4

68.3

70.5

62.9

84.5

75.4

Women

Young people
aged 15 to 19
with timely
progression

90.6

77.3

89.1

80.5

80.5

95.6
95.4

82.8

64.2

92.5

73.8

87.1

93.7

84.4

94.8

90.0

Men

93.2

81.6

94.0

87.0

86.9

97.4
97.5

89.7

75.9

89.3

74.7

92.0

94.2

84.1

95.2

92.8

Women

primary school
among young
people
aged 15 to 19

28.6

58.8

36.3

36.3

36.2
43.2

52.0

32.9

64.5

32.1

44.1

52.7

38.8

57.3

47.2

Women

52.6

25.4

46.4

29.7

29.7

27.2
35.2

42.2

23.8

64.9

27.0

43.6

56.1

33.8

48.1

42.0

Men

secondary
school among
young people
aged 20 to 24

Completion of

46.6

aRefers

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the relevant countries.
to five years of post-secondary education.

85.5

1990

(Bol. Rep. of)

Latin America

2005

Venezuela

62.9

96.2

2005

(Bol. Rep. of)

73.8

1997

Dominican Republic

72.0

2005

56.0

38.8

1994

Paraguay
(urban areas)

Men

Pre-school
attendance rates

Year

Country

6.9

4.8

6.6

4.4

10.8

4.5
4.3

2.0

3.6

14.0

1.0

5.7

7.5

4.6

9.7

6.8

Men

7.9

4.7

12.5

6.0

13.0

4.7
5.9

3.1

4.4

15.6

0.6

8.1

11.7

3.5

16.6

8.8

Women

tertiary education
among young
people aged
25 to 29 a

LATIN AMERICA (18 COUNTRIES): SELECTED EDUCATIONAL INDICATORS FOR CHILDREN AND YOUNG PEOPLE OF DIFFERENT AGE GROUPS, BY SEX, NATIONWIDE TOTALS
(Percentages)

(Concluded)

Social Panorama of Latin America • 2007
187

188

Economic Commission for Latin America and the Caribbean (ECLAC)

Table III.5
LATIN AMERICA (18 COUNTRIES): SELECTED EDUCATIONAL INDICATORS FOR CHILDREN AND YOUNG PEOPLE
OF DIFFERENT AGE GROUPS, BY GEOGRAPHICAL AREA, NATIONWIDE TOTALS
(Percentages)
Country

Net attendance rates

Year
Primary

Early secondary

Completion of

Upper secondary

Primary among
young people
aged 15 to 19

Secondary among
young people
aged 20 to 24

Tertiary among
young people
aged 25 to 29 a

Urban Rural Indigenous Urban Rural Indigenous Urban Rural Indigenous Urban Rural Indigenous Urban Rural Indigenous Urban Rural Indigenous
Argentina
(Greater
Buenos Aires)
Argentina
(urban areas)

1997 97.7
2005 96.5

…
…

… 76.1
… 76.8

…
…

… 45.1
… 42.4

…
…

… 97.3
… 97.8

…
…

… 49.9
… 69.2

…
…

… 11.6
… 11.4

…
…

…
…

2005 97.0

…

… 76.0

…

… 39.1

…

… 97.1

…

… 68.7

…

… 10.8

…

…

Bolivia
(8 main cities
and El Alto)

1994 92.7

…

91.1 54.4

…

41.2 65.2

…

45.3 91.2

…

77.2 58.4

…

39.0

7.9

…

2.8

2004 93.9

…

… 56.4

…

56.0 65.4

…

65.0 94.2

…

92.7 63.3

…

56.7 11.5

…

7.7

Bolivia

2004 74.5 73.7

… 44.0 32.0

36.3 49.3 34.0

43.5 93.5 78.9

85.4 60.6 26.7

46.3 10.4

1.3

4.9

Brazil

1990 90.0 74.4
2005 94.5 93.4

76.3 49.3 16.5
94.4 77.3 58.1

26.0 20.7 4.6
67.2 51.2 25.0

6.7 81.6 51.0
36.8 94.6 84.0

62.7 26.2 5.0
91.0 54.0 20.8

10.6
40.7

2.5
4.1

0.4
0.3

0.3
1.2

1990 97.1 91.2
2003 99.3 97.5

… 51.4 36.4
98.1 62.7 59.5

… 65.5 33.1
58.5 72.9 59.2

… 95.2 85.3
63.0 98.7 96.1

… 57.1 19.7
96.5 77.5 45.6

… 6.8
60.0 10.9

1.5
1.6

…
3.2

Costa Rica

1990 89.5 84.9
2005 99.1 98.0

… 54.8 27.6
… 60.7 46.2

… 27.4 9.9
… 31.2 20.7

… 90.2 76.5
… 94.9 88.8

… 44.5 17.1
… 49.0 28.1

…
…

8.4
9.2

1.0
3.1

…
…

Colombia

1991 86.8 73.6
2005 94.3 92.5

… 62.7 28.1
… 72.4 48.3

… 30.3 11.2
… 43.6 20.2

… 90.3 67.1
… 95.2 80.5

… 44.0 14.4
… 70.3 29.4

… 12.3
… 23.4

1.0
2.6

…
…

Ecuador
(urban areas)

1990 94.9
2005 81.7

…
…

… 9.9
35.6 12.9

…
…

…
3.9

Ecuador

2005 81.7 84.3

86.9 57.6 49.1

51.3 65.5 37.9

36.1 95.0 88.5

87.9 58.8 23.7

26.6 12.9

El Salvador

1995 87.8 79.1
2004 90.6 87.9

… 52.5 19.5
… 61.3 38.1

… 38.2 9.1
… 41.8 18.7

… 78.7 39.9
… 85.7 64.2

… 40.8 8.1
… 49.0 16.6

Guatemala

2004 85.9 80.2

81.4 43.2 19.4

18.6 21.7

5.8

6.1 75.4 44.8

41.5 42.0

Honduras

1990 87.2 75.9
2003 91.6 87.0

… 37.5 7.2
… 51.3 19.0

… 15.4
… 32.7

1.7
6.7

… 75.8 44.1
… 84.4 58.1

… 22.5
… 31.0

1996 95.3 94.5
2005 97.5 96.1

… 71.6 43.1
… 79.1 63.3

… 48.3 20.4
… 53.6 37.3

… 93.7 77.7
… 96.2 90.2

… 30.8 9.6
… 48.4 24.8

Nicaragua

1993 83.7 66.5
2001 86.7 79.7

… 43.9 8.7
78.3 52.9 21.1

… 18.2
20.0 25.2

2.8
5.9

… 75.1 29.9
6.0 81.2 40.3

Panama

1991 94.5 91.3
2005 98.3 95.6

… 65.0 43.5
92.1 75.7 51.7

… 48.6 28.2
26.5 60.7 36.3

… 93.8 85.4
13.2 98.1 89.1

Paraguay
(urban areas)

1994 92.3
2005 95.9

86.5 40.4
93.8 62.6

25.4 34.9
39.0 48.4

16.3 84.3
28.5 94.0

Paraguay

2005 95.9 92.6

92.1 62.6 43.1

38.2 48.4 25.6

Peru

1997 97.5 90.6
2003 95.4 91.4

… 38.5 16.3
… 73.6 44.4

… 15.8 5.3
… 56.4 27.3

1997 91.7 90.9

… 29.4 15.8

2005 91.8 94.3

… 49.3 36.0

Uruguay

1990 97.3
2005 97.7

… 65.7
… 71.6

Venezuela
(Bol. Rep. of)
(urban areas)

Chile

Mexico

República
Dominicana
(urban areas)

Venezuela
(Bol. Rep. of)

…
…

… 65.3
87.8 57.6

…
…

… 46.6
59.0 65.5

…
…

… 93.2
42.8 95.0

…
…

2.0

2.6

…
…

5.7
6.7

0.1
0.4

…
…

8.1

10.3

6.6

0.8

0.9

3.5
4.1

…
…

4.3
4.5

0.2
0.1

…
…

… 10.4
… 10.0

1.6
2.8

…
…

4.2
5.4

1.4
1.2

…
0.0

… 50.3 28.4
72.7 63.4 30.0

… 9.4
11.9 17.1

3.3
5.1

…
1.5

62.6 36.5
87.7 54.3

…
…

13.8
30.1

4.0
9.7

…
…

0.5
3.6

23.2 94.0 83.4

83.2 54.3 27.1

26.4

9.7

1.8

2.0

… 86.0 51.0
… 95.9 81.4

… 37.7 9.5
… 77.9 32.2

… 1.1
… 19.4

0.1
4.0

…
…

… 39.4 21.7

… 78.5 59.5

… 36.8 14.9

…

5.7

1.1

…

… 57.7 46.5

… 89.2 80.3

… 54.8 31.5

…

3.4

0.7

…

…
…

… 44.2
… 53.6

…
…

… 96.5
… 96.4

…
…

… 31.9
… 39.2

…
…

…
…

4.6
5.1

…
…

…
…

1990 32.1 28.7

… 49.5 21.2

… 23.6

7.0

… 87.9 60.1

… 36.7

9.9

… 13.4

1.2

…

1990 91.5

…

… 42.9

…

… 20.8

…

… 83.6

…

… 33.0

…

…

5.2

…

…

2005 91.8

…

… 68.4

…

… 45.0

…

… 91.5

…

… 52.5

…

…

9.5

…

…

… 32.2

9.2

…

5.8

0.9

…

79.0 56.2 23.8

35.1

8.5

1.9

2.0

…
…

…
…

…
…

…
…

…
…

1990 92.2 84.7

… 54.5 26.3

… 32.1 12.5

… 86.2 62.9

2005 95.4 93.5

Latin America b

… 48.1
89.1 58.8

88.3 75.2 54.6

46.7 52.2 30.1

33.5 94.8 83.6

… 21.8
48.1 39.3

4.6
7.3

…
7.1

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
aRefers to five years of post-secondary education.
bWeighted average of countries that distinguish between urban and rural areas in the two periods considered. The total for indigenous population
includes Bolivia, Brazil, Chile, Ecuador, Guatemala, Nicaragua, Panama and Paraguay.

Social Panorama of Latin America • 2007

189

Table III.6
LATIN AMERICA (18 COUNTRIES): COMPLETION OF THE VARIOUS EDUCATION CYCLES, BY POVERTY STATUS, NATIONWIDE TOTALS
(Percentages)

Argentina
(Greater
Buenos Aires)
Argentina
(urban areas)
Bolivia
(8 main cities
and El Alto)

Year

Completion of primary education
among young people aged 15 to 19

Completion of secondary education
among young people aged 20 to 24

Total

Country

Total

Poverty status
NonIndigent indigent Non-poor
poor

Poverty status
NonIndigent indigent Non-poor
poor

Completion of tertiary education
among young people aged
Total

Poverty status
NonIndigent indigent Non-poor
poor

1997

97.3

95.1

92.1

98.4

49.9

7.4

13.8

55.2

11.6

0.0

0.0

13.5

2005

97.8

97.4

94.2

98.7

69.2

40.9

46.7

74.5

11.4

1.3

1.2

13.8

2005

97.1

93.7

95.1

98.4

68.7

38.5

49.6

75.2

10.8

1.1

1.4

13.5

1994

91.2

90.4

92.0

91.0

58.4

53.9

47.8

65.5

7.9

2.4

2.6

12.1

2004

94.2

91.7

93.9

95.2

63.3

48.6

53.9

71.2

11.5

0.5

2.8

19.2

Bolivia

2004

88.7

79.9

91.2

93.2

51.4

24.5

48.3

66.0

7.9

0.1

2.1

16.0

Brazil

1990
2005

73.2
92.6

50.5
81.4

68.7
89.6

85.0
96.3

21.1
48.8

4.2
13.5

8.1
24.8

30.6
62.1

2.1
3.5

0.1
0.1

0.0
0.1

3.3
5.3

Chile

1990
2003

93.5
98.3

89.2
95.9

92.8
97.5

94.9
98.7

51.0
73.9

23.2
45.4

33.8
54.4

61.3
77.9

6.0
9.8

0.2
1.0

0.8
1.2

9.0
11.4

Costa Rica

1990
2005

82.4
92.3

72.8
85.9

74.6
89.0

85.1
93.5

28.9
41.2

9.6
17.1

15.3
17.3

32.0
44.5

4.3
6.8

0.0
0.0

0.4
0.7

5.3
7.8

Colombia

1991
2005

80.0
91.1

73.7
87.4

80.3
90.9

83.2
92.9

32.8
60.3

14.4
41.1

24.0
50.2

43.8
69.5

8.3
18.4

0.6
2.6

2.5
5.2

14.3
27.8

Ecuador
(urban areas)

1990
2005

93.2
95.0

91.9
90.0

93.2
94.4

94.1
96.9

48.1
58.8

35.6
32.7

40.6
42.8

59.4
71.1

9.9
12.9

2.5
1.8

5.7
2.4

16.6
19.5

Ecuador

2005

92.8

87.5

92.4

95.0

48.3

25.2

35.8

59.9

9.8

1.1

1.8

15.5

El Salvador

1995
2004

61.2
76.1

43.9
62.4

55.2
69.0

71.5
85.1

27.2
36.5

10.2
10.4

13.3
23.6

39.5
48.8

3.6
4.6

0.3
0.8

0.2
0.6

6.4
7.2

Guatemala

2004

58.3

39.4

55.0

70.6

24.9

7.9

12.6

36.5

3.9

0.3

0.1

7.3

Honduras

1990
2003

57.9
70.6

47.9
58.5

66.2
79.2

75.6
86.5

12.7
17.6

3.8
3.6

11.8
16.4

29.8
37.2

2.2
2.3

0.2
0.1

0.7
1.0

7.3
6.3

Mexico

1996
2005

87.2
93.9

72.4
83.6

86.9
90.8

94.4
97.1

23.3
40.6

5.9
11.8

13.7
21.3

34.4
50.1

7.5
7.7

0.1
0.3

1.4
1.3

12.5
10.7

Nicaragua

1993
2001

55.2
64.5

41.3
49.2

60.6
71.2

73.5
78.7

14.4
26.4

7.4
10.7

13.6
22.8

24.8
43.5

3.2
3.8

0.9
0.5

1.8
2.4

7.3
8.2

Panama

1991
2005

91.4
95.0

85.6
85.3

89.9
93.0

94.4
97.8

44.6
52.6

22.7
17.8

31.0
33.2

54.4
61.3

7.9
13.2

1.3
1.0

2.3
1.8

11.3
17.3

Paraguay
(urban areas)

1994
2005

84.3
94.0

71.1
87.0

83.1
93.6

88.6
97.6

36.5
54.3

11.5
21.1

19.5
42.1

48.0
71.1

4.0
9.7

0.0
0.4

0.0
1.6

6.5
16.1

Paraguay

2005

89.5

82.7

90.6

94.7

43.9

18.6

35.9

61.1

6.9

0.2

1.3

12.7

Peru

1997
2003

74.2
91.0

50.7
75.5

74.0
92.9

84.4
96.3

29.7
64.7

8.5
25.9

22.3
53.9

37.9
80.3

0.8
14.8

0.0
1.4

0.0
5.7

1.3
23.5

Dominican
Republic

1997
2005

70.3
86.1

58.1
80.6

72.0
84.9

72.4
89.2

28.5
46.9

14.2
33.9

17.2
36.7

32.8
54.4

4.0
2.6

0.0
0.2

0.8
0.4

5.3
4.3

Uruguay

1990
2005

96.5
96.4

84.7
84.1

94.0
93.8

97.8
98.2

31.9
39.2

3.8
1.7

8.5
8.8

36.2
46.5

4.6
5.1

0.0
1.4

0.0
0.0

5.4
6.2

Venezuela
(Bol. Rep. of)
(urban areas)

1990

83.6

78.1

80.4

86.3

33.0

26.1

23.8

36.9

11.9

5.5

5.3

14.9

Venezuela
(Bol. Rep. of)
Latin America

1990

83.6

78.1

80.4

86.4

33.0

26.1

23.8

36.9

5.2

0.7

1.3

7.0

2005

91.5

87.3

89.6

93.3

52.5

36.1

38.7

59.2

9.5

2.9

3.0

12.7

1990
2005

79.4
91.9

63.9
80.5

78.1
89.8

87.6
95.7

27.1
49.7

9.3
20.7

15.8
30.8

36.9
60.8

4.8
7.4

0.2
0.8

1.0
1.5

7.5
10.6

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
aRefers to five years of post-secondary education.

190

Economic Commission for Latin America and the Caribbean (ECLAC)

Table III.7
LATIN AMERICA (18 COUNTRIES): COMPLETION OF THE VARIOUS EDUCATION CYCLES,
BY HOUSEHOLD EDUCATIONAL BACKGROUND, NATIONWIDE TOTALS a
(Percentages)
Country

Year

Completion of primary education
among young people aged 15 to 19

Completion of secondary education
among young people aged 20 to 24

Household educational background b
Total

Argentina
(Greater
Buenos Aires)

Primary Secondary Tertiary
incomplete completed completed

Completion of tertiary education among
young people aged 20 to 24 a

Household educational background b
Total

Primary Secondary Tertiary
incomplete completed completed

Household educational background b
Total

Primary Secondary Tertiary
incomplete completed completed

1997

97.3

94.8

100.0

97.1

49.9

25.2

88.1

92.4

11.6

2.2

14.8

77.2

2005

97.8

95.2

100.0

100.0

69.2

51.2

92.5

98.4

11.4

4.2

6.2

76.0

2005

97.1

93.6

99.6

99.5

68.7

46.8

93.4

98.2

10.8

3.1

5.6

74.8

1994
Bolivia (8 main
cities and El Alto) 2004

91.2
94.2

87.7
91.6

96.3
98.1

81.6
91.5

58.4
63.3

47.6
53.9

82.5
90.6

66.5
92.4

7.9
11.5

3.8
5.3

4.5
3.2

88.0
71.3

Argentina
(urban areas)

Bolivia

2004

88.7

84.1

98.3

91.6

51.4

37.8

92.5

92.4

7.9

2.8

3.1

71.8

Brazil

1990
2005

73.2
92.6

62.8
86.3

92.4
98.3

91.6
99.5

21.1
48.8

10.7
29.7

81.6
94.1

65.3
95.1

2.1
3.5

0.4
0.4

2.3
1.9

61.4
75.6

Chile

1990
2003

93.5
98.3

88.6
95.9

98.0
99.9

97.4
100.0

51.0
73.9

37.4
55.8

85.8
95.6

81.9
96.9

6.0
9.8

2.7
2.5

5.7
7.0

58.4
67.7

Costa Rica

1990
2005

82.4
92.3

75.4
86.3

96.4
95.4

93.6
100.0

28.9
41.2

21.2
26.8

78.1
73.0

83.6
90.9

4.3
6.8

2.6
1.9

5.3
5.0

41.4
72.2

Colombia

1991
2005

80.0
91.1

72.1
84.8

94.2
98.7

95.0
98.5

32.8
60.3

20.5
43.0

86.6
95.0

54.4
92.3

8.3
18.4

3.3
6.6

10.3
11.9

74.0
80.7

Ecuador
(urban areas)

1990

93.2

89.7

92.7

95.8

48.1

36.1

88.5

71.1

9.9

6.2

7.4

74.6

2005

95.0

89.7

97.9

98.0

58.8

38.9

87.4

94.6

12.9

4.8

9.4

61.6

Ecuador

2005

92.8

87.0

97.8

98.0

48.3

28.9

87.7

94.8

9.8

3.1

9.7

62.8

El Salvador

1995
2004

61.2
76.1

54.1
68.4

96.3
95.7

81.3
100.0

27.2
36.5

17.7
25.5

80.1
93.2

70.7
98.9

3.6
4.6

0.8
2.0

2.8
5.3

67.4
55.5

Guatemala

2004

58.3

52.2

98.8

94.9

24.9

16.4

74.8

98.8

3.9

2.2

0.4

87.3

Honduras

1990
2003

57.9
70.6

51.8
63.7

93.7
93.2

88.2
81.4

12.7
17.6

6.1
8.9

62.8
76.3

59.6
64.3

2.2
2.3

0.3
0.6

5.5
4.4

61.8
65.6

Mexico

1996
2005

87.2
93.9

81.3
89.5

100.0
96.7

100.0
99.5

23.3
40.6

15.1
26.1

73.8
90.5

89.3
81.1

7.5
7.7

3.3
3.8

2.2
10.0

90.2
69.7
100.0

Nicaragua
Panama
Paraguay
(urban areas)
Paraguay
Peru
Dominican
Republic
Uruguay
Venezuela
(Bol. Rep. of)
Venezuela
(Bol. Rep. of)
Latin America

1993

55.2

49.4

100.0

92.1

14.4

11.5

81.8

92.5

3.2

1.8

9.4

2001

64.5

58.0

93.5

100.0

26.4

18.9

80.8

100.0

3.8

1.8

3.4

89.9

1991
2005

91.4
95.0

86.4
88.1

99.1
99.7

94.3
99.3

44.6
52.6

28.8
29.8

77.4
86.5

70.6
82.3

7.9
13.2

4.6
5.2

4.1
11.3

66.7
76.2

1994

84.3

75.5

85.8

100.0

36.5

25.5

87.5

41.8

4.0

1.4

3.0

75.8

2005

94.0

89.1

100.0

100.0

54.3

41.5

92.7

67.6

9.7

6.3

7.6

75.5

2005

89.5

83.6

100.0

100.0

43.9

30.5

93.0

67.6

6.9

3.1

7.5

71.3

1997

74.2

64.9

94.8

100.0

29.7

20.2

73.7

100.0

0.8

0.2

0.0

10.5

2003

91.0

86.1

99.7

94.8

64.7

55.1

89.4

90.8

14.8

10.7

16.4

58.0

1997
2005

70.3
86.1

63.2
78.9

100.0
98.7

80.3
100.0

28.5
46.9

21.2
31.0

76.2
82.0

64.0
95.7

4.0
2.6

2.6
0.7

0.0
3.9

71.1
56.9

1990

96.5

93.2

100.0

100.0

31.9

18.3

65.0

78.6

4.6

1.9

2.6

82.7

2005

96.4

92.4

99.2

100.0

39.2

21.3

72.7

92.3

5.1

0.9

5.0

69.0

1990

83.6

76.9

96.5

92.0

33.0

23.9

83.8

75.1

11.9

6.9

10.4

74.0

1990

83.6

77.0

96.9

89.8

33.0

23.9

80.3

70.1

5.2

2.8

6.2

67.2

2005

91.5

86.0

98.5

97.8

52.5

40.7

87.0

92.8

9.5

4.9

7.2

64.6

1990
2005

79.4
91.9

70.6
85.5

95.6
98.3

95.8
98.4

27.1
49.7

16.2
32.7

81.4
92.7

75.5
91.1

4.8
7.4

1.8
3.1

4.4
5.4

75.5
71.6

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
aRefers to five years of post-secondary education.
bBased on the average number of years of schooling of head of household and spouse. In lone-parent families, this refers to the average years of
schooling of the male or female head of household.

440

492

Other countries

Total

477

443

415

473

402

393

476

497

531

470

504

524

532

504

456

457

378

…

…

0.017

-0.152

0.033

0.142

0.436

…

-0.018

0.313

0.094

-0.163

0.152

0.101

0.069

…

0.003 **

0.060

-0.108

-0.221

0.050

486

444

420

475

472

384

534

520

535

528

520

509

550

517

531

434

365

475

450

421

451

Low

487

446

429

467

431

412

539

520

534

459

512

520

553

520

445

439

404

458

442

432

451

High

…

…

0.030

0.006

-0.147

0.140

-0.024

…

-0.006

-0.259

0.020

0.041

-0.020

0.007

-0.335

…

0.187

-0.070

-0.029

0.072

-0.059

Pearson Level of teacher Pearson
support
correlation
correlation
(0 order)
(0 order)

481

430

407

452

465

383

545

530

530

523

526

517

573

535

507

415

353

461

427

403

428

High

477

…

…

0.100
440

-0.014
433

-0.023

-0.012

-0.017

…

-0.067

-0.172

-0.118

-0.021

-0.146

-0.067

-0.263

…

-0.213

0.114

-0.024

0.089

0.041

Pearson
correlation
(0 order)

460

445

399

503

499

525

489

496

523

537

515

430

459

360

472

442

466

453

Low

Pupils per
computer

(Scores and correlations)

504

458

429

489

442

406

569

547

548

527

528

554

567

534

512

435

384

466

458

423

450

Worse

470

432

405

450

493

404

499

493

514

464

498

496

545

513

477

448

370

475

449

443

459

Better

School
environment

…

…

0.090

0.168

-0.079

0.005

0.304

…

0.137

0.252

0.131

0.247

0.110

0.138

0.169

…

0.008

-0.052

0.056

-0.071

-0.056

Pearson
correlation
(0 order)

367

423

414

437

421

395

503

494

520

498

511

481

529

500

460

427

357

468

422

419

425

Low

352

454

429

492

505

407

572

539

554

502

525

554

564

531

478

454

390

471

467

446

477

High

Teacher
commitment

…

…

0.080

0.177

0.215

0.011

0.287

…

0.115

0.024

0.064

0.235

0.127

0.111

0.071

…

0.176

0.003 *

0.197

0.142

0.119

466

433

404

467

434

388

499

496

533

506

519

514

546

514

448

414

333

450

404

413

403

Low

510

470

448

502

483

407

556

539

538

493

504

522

553

528

515

471

428

493

469

459

502

High

…

…

0.236

0.182

0.143

0.138

0.276

…

0.053

-0.051

-0.066

0.065

0.023

0.098

0.288

0.375

0.226

0.301

0.210

0.357

Pearson Level of school Pearson
integration
correlation
correlation
(0 order)
(0 order)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Organisation for Economic Co-operation and Development (OECD), “Programme for International Student
Assessment PISA 2000” [online database] http://www.pisa.oecd.org.
a  ot including Mexico.
N
Note: (*) correlations only significant to 5%, and (**) non-significant. The others are significant to 1%.

447

418

Russian Federation

Thailand

409

567

Hong Kong Special
Administrative region

431

530

OECD countries b

Indonesia

528

United States

Israel

531

551

Ireland

United Kingdom

Italy

569

526

France

476

535

Germany

431

Latin American
countries

Spain

376

Peru

458

465

442

477

Chile

Mexico

461

415

Brazil

468

Low

456

Argentina

High

Pupils-toteacher ratio

LATIN AMERICA (5 COUNTRIES), SELECTED OECD COUNTRIES (7 COUNTRIES) AND OTHERS (5 COUNTRIES):
SCORES AND CORRELATIONS OF READING TEST ACCORDING TO VARIOUS CHARACTERISTICS OF THE TEACHING STAFF AND SCHOOL COMMUNITY

Table III.8

Social Panorama of Latin America • 2007
191

400

484
493
505
523
527
487

504

506

Latin
American
countries

Germany
Spain
France
Reino Unido
Ireland
Italy

United States

OECD
countries

533

520

531

489
522
553
520
517
502

436

459
425
442
467
374

487

421

405

417

396

402

387

514

480

451

397
495
504
477
479
464

408

420
395
402
446
324

Up to
primary

476

441

429

462

438

401

537

509

518

486
524
546
512
514
499

433

458
426
431
464
360

Up to
secondary

518

475

454

486

492

418

565

550

561

523
545
566
543
533
524

467

488
457
477
492
407

Tertiary

Parents’ educational level

…

…

0.108

0.145

0.319

0.163

0.218

…

0.250

0.263
0.265
0.174
0.225
0.185
0.208

…

0.288
0.259
0.313
0.237
0.346

Spearman
correlation
(0 order)

456

421

415

441

425

378

520

491

500

443
498
532
481
482
472

408

420
398
406
444
336

1

519

478

443

508

504

417

552

557

576

534
548
574
576
554
534

469

496
457
487
494
410

4

…

…

0.179

0.271

0.299

0.226

0.146

…

0.291

0.343
0.252
0.215
0.363
0.289
0.256

…

0.326
0.261
0.394
0.241
0.317

469

439

417

459

420

374

526

504

492

472
507
541
513
505
489

408

427
395
414
452
342

1

505

463

431

485

492

414

537

533

558

504
535
562
532
534
515

472

497
461
482
491
420

4

Quartiles of
Quartiles of
Cuartiles del
socio-occupational well-being índice de bienestar
b
index
index
b

…

…

0.198

0.213

0.255

0.164

0.222

…

0.238

0.170
0.120
0.122
0.224
0.241
0.116

…

0.294
0.272
0.245
0.200
0.284

Pearson
correlation
(0 order)

421

411

410

435

381

389

477

467

477

411
473
473
472
451
480

405

419
403
413
446
349

1

521

486

464

494

480

426

550

535

553

498
528
558
538
535
509

473

493
461
466
483
422

4

Strata of the index
of educational
resourcess b

…

…

0.189

0.206

0.244

0.160

0.205

…

0.230

0.152
0.104
0.078
0.204
0.214
0.114

…

0.297
0.262
0.242
0.206
0.285

124

118

113

114

126

109

115

115

116

121
111
118
114
119
106

117

118
114
113
108
121

Pearson Disparity
correlation index
(0 order)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Organisation for Economic Co-operation and Development (OECD), “Programme for International Student
Assessment PISA 2000” [online database] http://www.pisa.oecd.org.
aIn some countries the students selected were from the ninth grade (see box III.7).
bQuartile groups of the indices concerned.
cNot including Mexico.
Note: All correlations significant to 1%.

460

Total

445

462

431

422

471

421

371

452

Indonesia

Israel
Russian
Federation
Thailand

Other
countries b

399

456

525

Hong Kong
Special
Administrative
Region

b

418
396
410
422
327

Argentina
Brazil
Chile
Mexico
Peru

Total
Total
students tenth-grade
students a

(Scores and correlations)

Table III.9
LATIN AMERICA (5 COUNTRIES), SELECTE OECD COUNTRIES (7 COUNTRIES) AND OTHERS (5 COUNTRIES):
SCORES AND CORRELATIONS OF READING TEST ACCORDING TO MAIN EXTRA-SCHOLASTIC FACTORS

192
Economic Commission for Latin America and the Caribbean (ECLAC)

23.0

80.8

95.7

50.9

75.2

OECD countries b

Hong Kong Special
Administrative Region

Indonesia

Israel

88.0

81.9

Other countries

Total

18.1

12.0

4.6

...

24.8

49.1

4.3

19.2

5.7

6.7

59.8

11.0

4.3

22.2

12.0

5.5

0.8

2.1

…

20.4

…

3.6

6.4

1.2

0.9

57.6

…

14.4

32.3

4.3

8.6

1.2

0.0

33.7

…

43.6

12.6

11.3

2.5

…

4.4

49.1

0.6

12.8

4.4

5.8

2.3

11.0

8.6

10.6

…

13.5

10.7

21.9

16.0

11.7

8.8

25.5

55.9

59.6

61.6

10.8

57.2

6.2

9.3

0.7

10.6

9.5

30.7

3.2

16.7

12.9

32.9

54.1

46.3

31.4

26.2

40.0

(Percentages)

inadequate
educational
equipment a

21.8

6.3

3.1

4.7

36.3

5.1

55.0

31.3

44.4

35.7

29.8

5.9

66.2

25.6

25.4

14.2

1.7

11.7

8.4

16.9

9.3

adequate
educational
equipment a

Students
In public school with

10.6

34.4

27.9

…

10.5

35.0

0.0

3.3

0.0

0.0

22.5

0.0

0.0

4.9

0.0

11.3

15.0

13.8

7.1

3.4

17.6

inadequate
educational
equipment a

41.2

16.5

43.4

…

33.8

15.3

50.2

41.8

60.4

52.9

20.3

87.5

43.6

48.9

42.1

48.4

37.0

57.9

44.3

69.9

28.0

adequate
educational
equipment a

Students
in private schools with

481

452

421

470

455

404

537

514

526

501

490

511

553

513

485

425

355

460

424

416

437

Public

497

388

413

…

480

383

455

532

553

504

534

601

550

531

560

476

437

486

458

476

479

Type of private school

513

429

383

…

468

…

457

538

532

410

533

…

546

521

560

466

409

…

440

…

475

489

386

439

…

536

383

445

530

558

518

576

601

556

559

…

482

440

486

497

476

501

State-funded Independent
private
private
schools
schools

(Scores)

Total
private

Scores according to type of school

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Organisation for Economic Co-operation and Development (OECD), “Programme for International Student
Assessment PISA 2000” [online database] http://www.pisa.oecd.org.
aQuartile groups for educational equipment.
bNot including Mexico.

95.4

Thailand

100.0

94.3

United States

Russian Federation

40.2

93.3

Ireland

Italy

77.0

89.0

95.7

57.1

Germany

Spain

France

77.8

Latin American
countries

United Kingdom

42.9

88.0

Peru

49.7
21.9

50.3

78.1

Chile

Mexico

11.7

88.3

Brazil

52.4

47.6

State-funded Independent
private
private
schools
schools

Type of private school

Students attending
private
schools
(total)

Argentina

public
schools

(Percentages and scores)

LATIN AMERICA (5 COUNTRIES), SELECTD OECD COUNTRIES (7 COUNTRIES) AND OTHERS (5 COUNTRIES):
READING TEST SCORES AND STUDENT DISTRIBUTION BY SCHOOL CHARACTERISTICS

Table III.10

Social Panorama of Latin America • 2007
193

Social Panorama of Latin America • 2007

195

Chapter IV

Internal migration and development
in Latin America and the Caribbean:
continuity, changes and policy challenges

A. Introduction
Within the Social Panorama of Latin America and the Caribbean, 2007, the chapter on
population reviews the main internal migration trends in Latin American and Caribbean
countries over the last 25 years, and how these tie in with processes of national and subnational
development and the living conditions of the population. The notion of internal migration used
in this document refers exclusively to changes of residence across a pre-defined subnational
geographical boundary: be it political-administrative, socio-ecological or any other (Macció,
1985). In the context of the many forms of internal migration, this chapter concentrates on
movement among (minor and major) administrative divisions, between urban and rural
areas, and from one city to another. Most of the information comes from census microdata
in REDATAM format.

The chapter is structured around a series of hypotheses
outlined in the theoretical framework section. The
first concerns the relationship between the intensity of
internal migration and the degree of economic and social
development in the countries. Starting from the hypothesis
that internal migration involves a high percentage of the

population, and that its intensity increases in stride with
economic and social development, it is postulated that
internal migrants should represent a significant proportion
of the population, that this fraction should be increasing in
the region and that internal migration should be more intense
in countries with a relatively high level of development.

196

The second hypothesis deals with the relationship
between internal migration and development within the
countries, and suggests that in general, internal displacements
are driven by the search for better opportunities that are
distributed heterogeneously within a country’s territory,
which results in migrants being drawn to more developed
areas while rejecting less developed areas. Emigration from
the latter, due to its selectivity in terms age and education
level, may aggravate the existing situation.
According to the third hypothesis, concerning the
relationship between migration and urbanization, the
advance of urbanization in the region has consolidated
the predominance of interurban migratory flows,
whether from one city to another or within cities. Many
relocations, especially from the metropolises to the
suburbs, may be driven by residential opportunities
(either in terms of housing or environment), which
would represent a break from the traditional search for

Economic Commission for Latin America and the Caribbean (ECLAC)

work or education, or by a comparison between cities,
in which the differences in quality of life are crucial
and therefore make the large cities less attractive to
migrants. Also, persistent socioeconomic inequalities,
which leave rural areas in an unfavourable situation,
support the prediction that these areas will continue
to experience net emigration.
The fourth hypothesis concerns the relationship
between migration and characteristics of the population,
and raises doubts about whether the higher migration rates
(selectivity) among young people, women and those with
an above-average level of education will persist.
Lastly, the fifth hypothesis pertains to the integration
of the migrants into the workforce at the point of
destination, and holds that the predominance of the search
for work should lead to greater employment, while the
adjustment to the place of destination should lead to
greater unemployment.

Social Panorama of Latin America • 2007

197

B. Theoretical framework
There is an interrelationship between internal migration and the development of both countries
and individuals. The intensity and direction of internal migration flows depend on national
development indices and territorial inequalities within countries. Similarly, the propensity to
migrate depends on a wide range of individual characteristics. In addition, internal migration
contributes to the development of certain areas of a country, while leaving others at a disadvantage.
As far as individuals are concerned, internal migration is their right and may also be a means
of improving their living conditions or dealing with adverse situations.

1.


Internal migration and social
and economic development

Since the work of Ravenstein (1885), the prevailing idea
has been that material progress stimulates migration by
promoting the expansion of means of transport and a
reduction in travel costs (Aroca, 2004; Greenwood and
Hunt, 2003; Cardona and Simmons, 1975).
Although this idea remains predominant (Van der
Gaag and van Wisen, 2001), the work of Zelinsky (1971)
casts some doubts over the predictability of internal
migration. These doubts have been strengthened by
new arguments such as: (i) development tends to reduce
disparities between subnational areas, thereby eroding
the main trigger for internal migration; (ii) development
brings down the costs of mobility in general, which may
result in internal migration being replaced by international

2.


migration or daily commuting; (iii) development
raises family income and facilitates homeownership
(which is a strong factor in territorial fixation); (iv)
current development is conducive to the emergence
of virtual spaces that inhibit migration by making it
possible to “be there without being physically present”;
(v) development is concomitant with urbanization, with
the latter leading to the exhaustion of rural-to-urban
migration and a subsequent reduction in migratory
intensity (Van der Gaag and van Wisen, 2001). In short,
there is a continuing debate over the long-term trend
of migratory intensity and the relationship between
migration and development. This chapter provides
relevant information on both topics.

Relationship between internal
migration and development

Territorial inequalities are the main trigger for migratory
flows, which means that the countries with more internal
heterogeneity should show more intense migration.
Since there are many factors that differentiate one
territory from the next, it is necessary to determine which

of them have the greatest influence on internal migratory
flows. The prevailing theory (Rosenzweig and Stark,
1997) emphasizes the effect of employment and income
differences in this regard, and holds that individuals will
decide to emigrate if they expect the increased income

198

Economic Commission for Latin America and the Caribbean (ECLAC)

resulting from the relocation to compensate for the costs of
migrating. Potential migrants also consider the probability
of obtaining employment at the point of destination.
Consequently, another operating hypothesis about this
relationship is that internal flows should move from
less developed regions, where income is lower, to more
developed regions, characterized by higher income.
The theory operates on the assumption that individuals
maximize economic yield, making use of perfect rationality
and information to do so. This theory has been criticized,
particularly by authors who place fundamental importance
on the influence of the forces of expulsion in the place of
origin, which greatly reduces the likelihood of a rational
and informed choice regarding the destination (Lall, Selod
and Shalizi, 2006; Villa, 1991). It has also been criticized
for its focus on the search for a higher income, which is
not the primary motive for many migration decisions
(Rodríguez, 2004a; Aroca, 2004). Displacements for
residential reasons, for example, aim to improve the
surroundings or daily life, either by moving into a more
comfortable home or a more pleasant environment or
by reducing commuting time. In general, urbanization

3.


Contribution of migration to the convergence
or divergence of the human resource base at
the national level

Considering the previous hypothesis, which posits a positive
relationship between development and migratory attraction,
and taking into account the selectivity of internal migration
in terms of age and education level (a topic that will be
examined later), it can be said that internal migratory
flows tend to deepen differences between territories in
terms of gender and age structure and the availability of
human resources. Migration is therefore unlikely to be a
factor that favours regional convergence.

4. 


intensifies this type of displacement, either within a given
city or from one city to another.
In fact, there are specific cases in which the hypothesis
of a positive relationship between development and migratory
attraction does not apply. One such case is that of frontier
regions, whose main appeal is derived not from superior
living conditions or higher average wages, but from the
abundance of natural resources, expectations for fast earnings
and, in many cases, policies that encourage immigration.
Another example is regions that have experienced economic
progress only recently, due in part to successful integration
into the global economy after having relatively low levels
of development, but whose dynamic job market becomes a
magnet for migrants. A third case is metropolitan regions
in the process of suburbanization or deconcentration that,
despite having above-average development rates, expel
population due to lack of space, deteriorating quality of
life or city regulations and policies. A fourth case, which is
the flip side of the third, stems from the flow of emigrants
from metropolitan regions to areas that have scant resources
but are close enough to the metropolitan areas to allow
regular contact with them.

The empirical analysis of this hypothesis may be quite
varied. At the complex end of the scale are general-equilibrium
and partial-equilibrium economic models, and at the opposite
end, comparisons of the socioeconomic profiles of migrants to
those of the local population. The empirical analysis presented
in this text is based on a specific procedure developed by the
Latin American and Caribbean Demographic Centre (CELADE)
- Population Division of ECLAC and disseminated in various
publications since 2004 (Rodríguez, 2004b).

Changes in the patterns and characteristics
of internal migration caused by urbanization

As the result of an urbanization process that is taking
place in a context of low income, limited resources and
institutional deficiencies, the problems that affect cities may
be reducing their appeal and, by extension, increasing that of

the countryside. This attraction may also be strengthened by
the boom in raw materials that the region is experiencing as
a result of growing worldwide demand for natural resources,
typically located in rural areas. Nevertheless, the persistent

Social Panorama of Latin America • 2007

inferiority of living conditions in the countryside, in contrast
to those of the cities, lends support to the hypothesis of
a net immigration to urban areas, which will continue to
drive urbanization, since without such immigration the
region would become “ruralized” due to the greater natural
population growth in the countryside.
Additionally, urbanization should have consolidated
the predominance of interurban flows, whether between
cities or within them. Moreover, the increasing percentage
of the population represented by city dwellers should

5. 


between cities, and domestic service has lost relevance
as a source of employment for women.
In the same vein, selectivity in terms of age in the
region has historically been concentrated among young
people, which begs the question of whether selectivity
among the elderly could exist if there is a wider range of
living options or if the practice of returning after retirement
becomes more common.
And given that migration takes place primarily
between urban areas, it is relevant to ask if selectivity
according to education level still exists, taking into account
that differences in education levels between cities tend
to be small.

Integration of migrants
in places of destination

Adaptation in the place of destination is a multifaceted
and gradual process. In general, it should be simpler for
internal migrants than for international migrants, given
that the former share some attributes with the population
of the place of destination, e.g. nationality, a collection of
practices and knowledge, such as language and vernacular,

1

turn natural population growth in the cities into the main
driver of their growing population, relegating migration
from the countryside to second place.
Given the predominance of migration between
cities, large cities are likely to lose attraction due to the
higher cost of living, the decentralization of production
and the expansion of service networks to the rest of the
metropolitan area. It follows that migration should be
contributing to demographic deconcentration, in contrast
to the state of affairs 30 or 40 years ago.1

Emigrants as a representative
sample of the population

Although migratory selectivity in terms of age, sex and
education is documented in the region (Rodríguez, 2004a),
it is possible that the sociodemographic and economic
transformations that have taken place in Latin America
and the Caribbean over the last 20 years have modified
the factors determining the selectivity.
An example of this statement is the marked female
selectivity in internal migration observed in Latin America
(Lall, Selod and Shalizi, 2006; Villa, 1991), which was
associated with migration from the countryside to the
city and the growth of domestic service in the cities. It is
worth asking, then, whether this selectivity will continue
to exist in the region when migration is predominantly

6. 


199

and a set of symbols, icons and values, all of which are
very important for the purpose of integration into the
workforce.
The data used for this study make it possible to
examine some aspects of the integration and adaptation
of migrants in their place of destination. Unfortunately,

If net migration is positive in the bigger cities, migration will contribute to increasing concentration. While it was taken as a given until a few
decades ago that internal migration was a force that contributed to concentration, particularly in the capital, the current hypothesis holds that
this migration favours decentralization in urban areas, due to the saturation of the big cities and the relative improvement, in terms of productive
positioning and living conditions, of medium-sized and small cities, which ultimately become the “attractive” centres of the system (ILPES,
2007; UNFPA, 2007; Henderson, 2000). This phenomenon has given rise to the hypothesis of “deconcentrated concentration”, which posits
that behind the apparent deconcentration driven by the new migratory flows, the area of influence of the large cities is in fact expanding (Pinto
da Cunha, 2002; Rodríguez, 2002).

200

Economic Commission for Latin America and the Caribbean (ECLAC)

they provide no indication of whether the act of migration
has resulted in a change in status for the emigrants with
respect to their place of origin, as this information is not
collected in censuses.
Of all the facets of adaptation, the most relevant
are integration into the education system and, above all,
into the workforce. Regarding the latter, the employment

7. 

motive for most of the interregional migrations should
translate into a higher rate of employment among migrants
compared to the rest of the population, once extrinsic
factors have been eliminated. However, due to the process
of adapting in the place of destination, unemployment
rates for migrants should be higher than for the rest of the
population after adjusting for extrinsic factors.

Relevant definitions and clarifications

Most of the information presented in this chapter is
unpublished, since it was obtained by processing census
micro-databases in REDATAM format. Given that the
censuses include questions about the previous place of
residence, comparing them to data on the current place
of residence makes it possible to identify the migrants.
The most common methods of inquiring about previous
places of residence are questions about place of birth,
which make it possible to identify “absolute” or “lifetime”
migration, and about the place of residence on a given
date in the past, which make it possible to identify cases
of recent migration (see box IV.1).
This chapter studies both of the types of migration
mentioned above. However, in terms of policy-making
on migration in recent years, the second is more relevant,

since absolute migration has no reference period, making
it impossible to determine whether it corresponds to
current flows or outdated flows. Thus, four types of
displacements are considered systematically: (i) “permanent”
displacement between major administrative divisions;
(ii) recent displacement between major administrative
divisions; (iii) permanent displacement between minor
administrative divisions; and (iv) recent displacement
between minor administrative divisions. For rural-urban
migration, the direct measurement is used, making it
possible to estimate the four possible flows: (i) from one
city to another; (ii) from the countryside to the city; (iii)
from the city to the countryside; and (iv) from one rural
area to another. Since the direct measurement can only be
performed on the censuses of four countries in the region

Box IV.1
TWO OPTIONS FOR MEASURING RECENT MIGRATION WITH CENSUSES

The guidelines for measuring internal migration in the censuses
are documented in the manual Principles and Recommendations
for Population and Housing Censuses. Revision 2 (United Nations,
2007a) of the United Nations, which is currently undergoing
revision, the most recent draft having been published in
February of 2007. This draft includes at least two procedures
for recording recent migration, which, being relatively current,
is the most relevant type for policymaking. The first is based on
determining the place of residence on a given date prior to the
census (typically five years), and the second involves combining
two questions about the duration of residence and the previous
place of residence. The first option is more economical and
therefore more common in Latin American censuses. Also, its
simplicity makes it easier to answer and (in technical terms)
makes it possible to classify the entire population according to
common time and space coordinates, allowing the construction
of precise migration matrices and the calculation of migration

rates for the reference period.
However, some authors (Xu-Doeve, 2006) have questioned
this procedure because it does not allow the construction of
migratory cohorts, it excludes some migrants (all of those who
migrated outside the reference period and those who “returned”
in that period) and it presupposes a single (and therefore
direct) displacement between the place of residence on the
given date in the past and the current place of residence. The
second procedure, more expensive in every respect, would
mitigate some of these deficiencies and include a group of
the population that is particularly relevant: those who never
migrated. However, the construction of migration matrices with
the second procedure is not without weaknesses, particularly
because it involves grouping individuals by migratory cohort.
This results in previous places of residence being combined
with different times, raising doubts as to the validity of the
trends provided by such matrices.

Social Panorama of Latin America • 2007

201

Box IV.1 (concluded)
LATIN AMERICA AND THE CARIBBEAN: METHODS OF INQUIRING ABOUT INTERNAL MIGRATION ON CENSUS QUESTIONNAIRES,
1990 AND 2000 ROUNDS
Country and Census Year
Antigua and Barbuda: 1991 and 2001
Argentina: 2001
Barbados: 1990 and 2000
Belice: 1990 and 2000
Bolivia: 1992 and 2001
Brazil: 1991 and 2000
Chile: 1982, 1992 and 2002
Colombia: 1993 and 2005
Costa Rica: 1984 and 2000
Cuba: 1981
Cuba: 2002
Ecuador: 1982
Ecuador: 1990 and 2001
El Salvador: 1992
Guatemala: 1994
Guatemala: 2002
Honduras: 1988 and 2001
Mexico: 1990 and 2000
Nicaragua: 1995 and 2005
Panama: 1990
Panama: 2000
Paraguay: 1982, 1992 and 2002
Peru: 1993
Dominican Republic: 2002
Saint Lucia: 1991 and 2001
Uruguay: 1985 y 1996
Venezuela (Bol. Rep. of): 1990
Venezuela (Bol. Rep. of): 2001

Direct question: Place of
residence 5 years ago

Indirect question: Previous
place of residence

Indirect question:
Duration of residence

X

X

X

X

X
X

X
X

X
X

X
X

X

X

X

X

X
X
X
X
X
X
X
X

X

X
X
X
X
X
X
X
X
X
X

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of reviewing census
questionnaires and the database on Internal Migration in Latin America and the Caribbean (MIALC) [online database] http://www.eclac.cl/
migracion/migracion_interna/
Note: In principle, recent migration in almost all the countries included can be estimated both at the major administrative division (MAD) level and
at the minor administrative division (MIAD) level. The exceptions are Barbados, where only the parish of residence five years prior is requested;
Mexico 1990, where only the state of residence five years prior is requested; and the Bolivarian Republic of Venezuela, where only the state of
residence five years prior is requested. However, not all databases could be processed at the MIAD level, for various reasons. In fact, it has not yet
been possible to process at this level all of those that do not show MIAD values in table IV.1 (not to be confused with cases in which it is impossible
to perform the calculation), and therefore, they are not available in the MIALC database either.

(Brazil, Nicaragua, Panama and Paraguay), an indirect
method (that of intercensal survival ratios (Welti, 1998;
Villa, 1991)) has been used for estimating net migration
between the countryside and the city in all the countries
in the region.
Migration involving the three largest cities in each
country is assessed by estimating the entry and exit flows
and segmenting the corresponding origin and destination
into three categories identified in the literature, particularly
because of their relevance to the hypothesis of concentrated
deconcentration: the metropolis, its immediate surroundings
and the rest of the country.
This process involved using traditional instruments,
such as the origin and destination matrix; some newer
methods, particularly the matrix of flow indicators;

multivariate tables for estimating selectivity, conditional
probabilities of migrant status, and standardizations;
and maps that are essentially illustrative. In addition,
various procedures and calculations (traditional as well)
have been used for applying the origin-destination
matrices (trends, totals, rates); other newer ones for
applying the matrices of flow indicators, e.g. estimating
the net and exclusive effect of migration following
the methodology developed by Rodríguez (2004a
and 2004b); classification quadrants to synthesize
information on migration trends at the subnational
scale; standardizations designed to control factors
extrinsic to the propensity to migrate; and multivariate
techniques for more specific analyses and preliminary
models of migratory flows.

202

Economic Commission for Latin America and the Caribbean (ECLAC)

C. Internal migration and development in countries
In the region’s most developed nations, the most common type of migration is to a different
area within the same country. In some such countries, people change their municipality of
residence at least a couple of times during their lifetime. However, the relative frequency of
internal migration in its various forms is on the wane in the region, and this may be partly
because it is being superseded by international migration.

Table IV.1 shows the percentages of migrants in each
of the four categories of migration between politicaladministrative divisions in the countries studied in this
chapter. Although the figures for the region as a whole
suggest an unexpected downward trend in the internal
mobility rate, this result is greatly influenced by trends
in Brazil and Mexico. For this reason, the following
analysis focuses on the situation and the trends that have
been verified in the majority of countries.
First, in all of the countries, most of the population
resides in the same major administrative division where
they were born. Guatemala is in last place in this regard,
with 11 percent of the permanent migrant population
moving between major administrative divisions, while
Paraguay and some of the small island states of the
Caribbean are in the lead, with 27 percent or more of the
permanent migrant population moving between major
administrative divisions. These figures are the result of
the massive population displacements observed in the
region over the last 50 years. However, they are fewer
than those observed in the United States, a country
with high internal mobility (31 percent of permanent
migrants moving between major administrative divisions,
according to the 2000 census). The predominance of
non-migrants gives particular weight to the territorial
and legal macro-environment in terms of people’s sense
of belonging. By mere virtue of having remained in the
major administrative division of birth, residents are more
likely to be familiar with aspects such as the territory, the
climate, the authorities and institutions, the activities, the
people, the norms and customs, and to have a local social
network. This does not necessarily indicate conformity
or adhesion to this environment, since it may also be the
result of obstacles to leaving.

Second, the figures for lifetime migration between
minor administrative divisions indicate that the migratory
experience has a direct presence in the lives of a significant
proportion, and sometimes a majority, of the population.
The low proportion observed in Guatemala, which is barely
over 20 percent in the 2000 census, appears to be due to
various factors, including the low level of urbanization (this
deflates intra-metropolitan migration, which is normally
an important part of migration at the minor administrative
division level) and the high relative proportion represented
by the indigenous population, which tends to have stronger
ties to its ancestral lands (Rodríguez, 2007). However, in
other countries where indigenous peoples represent a large
portion of the population (such as Ecuador), the level of
this type of migration is considerably higher. Given that
this indicator remains constant in many of the countries,
and that the countries in which it falls are more or less
comparable to those in which it rises, there is no clear
trend in the region.
Thirdly, recent migration between major administrative
divisions does not surpass 10 percent in any country, and
in several cases it does not even reach 5 percent. In all
of the countries indicated in table IV.1 save one, recent
migration between major administrative divisions is lower
than that observed in the United States during the 19952000 period, which was 8.7 percent according to the 2000
census. This percentage was surpassed only in Paraguay
in the 1977-1982 and 1987-1992 periods, precisely the
most active periods of the programme called “March to
the East” (CELADE, 1984).
The data on recent migration between major
administrative divisions offer information on the current
intensity of migration. In contrast to the case of absolute
migration, most of the countries with more than one

Social Panorama of Latin America • 2007

203

Table IV.1
LATIN AMERICA AND THE CARIBBEAN: PERCENTAGE OF MIGRANTS BETWEEN MAJOR AND MINOR ADMINISTRATIVE DIVISIONS BY
MIGRATION TYPE (ABSOLUTE OR RECENT), COUNTRIES AND YEARS AVAILABLE
Country

Antigua and Barbuda
Argentina
Barbados
Belize
Bolivia
Brazil
Chile

Costa Rica
Cuba
Guatemala
Mexico

Colombia
Ecuador
El Salvador
Honduras
Nicaragua
Panama
Paraguay

Peru
Dominican Republic
Saint Lucia
Uruguay
Venezuela (Bol. Rep. of)
Latin America and the Caribbean

Census Year

1991
2001
2001
1990
2000
1990
2002
1992
2001
1991
2000
1982
1992
2002
1984
2000
1981
2002
1994
2002
1990
2000
2005 (count)
1993
2005
1982
1990
2001
1992
1988
2001
1995
2005
1990
2000
1982
1992
2002
1993
2002
1991
2001
1985
1996
1990
2001
1990 Round
2000 Round

Absolute or lifetime migration

Recent migration or migration
within the last five years

MAD
28.6
28.4
19.9
29.8
31.1
14.2
14.2
13.8
15.2
14.8
15.4
21.3
20.3
21.0
20.3
20.2
NA
15.2
10.8
11.1
17.4
18.5
NA
22.1
20.6
18.9
19.2
19.9
16.7
19.5
17.2
14.7
13.3
18.9
20.1
28.8
26.1
26.4
22.4

MIAD
ND
ND
ND
ND
ND
ND
ND
25.0
26.3
36.0
37.1
50.7
46.0
48.9
35.5
34.4
NA
28.1
16.9
20.0
NA
NA
NA
ND
36.8
31.0
28.1
32.8
22.9
27.5
23.3
19.4
19.4
32.9
34.0
38.7
31.7
35.1
ND

MAD
11.1
13.0
3.3
6.9
6.4
6.6
5.1
5.6
6.0
3.8
3.4
5.9
6.1
5.8
6.6
5.6
ND
2.1
2.6
2.9
5.0
4.4
2.7
8.1
4.3
8.5
5.8
5.2
4.8
4.9
4.2
3.5
2.5
4.4
6.3
10.8
9.1
7.6
8.6

MIAD
ND
ND
ND
ND
ND
ND
ND
9.6
10.0
13.4
10.0
15.3
17.1
16.0
13.2
10.8
ND
4.5
4.6
7.0
NA
6.9
NA
ND
7.6
12.9
8.3
8.7
14.4
6.8
6.0
5.2
4.0
9.3
12.6
16.8
12.6
11.5
ND

17.7
15.9
18.5
24.5
24.1
23.1
23.8
17.5
17.7

25.9
ND
ND
ND
ND
NA
NA
34.2
35.2

4.2
ND
8.0
7.5
6.5
6.0
5.1
5.1
4.0

6.4
ND
ND
ND
ND
NA
6.7
12.6
8.7

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of special processing of
census microdatabases; National Institute of Statistics, Geography and Informatics (INEGI) of Mexico, “Población de 5 años y más por entidad
federativa de residencia actual y lugar de residencia en octubre de 2000 según sexo” [on line] www.inegi.gob.mx/est/contenidos/espanol/sistemas/
conteo2005/datos/00/excel/cpv00_mig_1.xls; National Statistics Office (ONE), Cuba; National Statistics Department (DANE) of Colombia, “Sistema
de consulta información censal, CENSO 2005. Censo Básico” [on line] http://200.21.49.242/cgibin/RpWebEngine.exe/PortalAction?MODE=
MAINBASE=CG2005BASICOMAIN=WebServerMain.inl.
UA: Unavailable; that is, the result could be obtained, but it was impossible to due so because of problems with the database or undocumented codes.
NA: Not applicable, i.e. the census did not include the necessary questions to make the calculations.
Note: In the case of migration between major administrative divisions (MAD), the figures were taken directly from the estimates derived from the
respective migration matrices in the database on internal migration in Latin America and the Caribbean (MIALC) [online database] http://www.eclac.cl/
migracion/migracion_interna/ (“basic matrix”). For practical reasons, in the case of migration between minor administrative divisions (MIAD) in some
countries, the information was obtained from the tables on migratory status by sex available in MIALC. In all the calculations made on the basis of
data available in MIALC, there is a potential loss of migrants as a result of people claiming to be migrants without specifying their place of origin (or
of residence in the case of de facto censuses). In all cases, the proportion corresponds to the quotient between the total migrants (by type) and the
population included in the census that responded to the relevant questions in the migration module. The aggregate results for Latin America are derived
from the sums of the absolute numbers for the countries included in the table.

204

Economic Commission for Latin America and the Caribbean (ECLAC)

observation (10 out of 18) show a downward trend in recent
migration. Only in four (Antigua and Barbuda, Bolivia,
Guatemala and Panama) is there an upward trend, whereas
the rest show a constant rate or an erratic trend (countries
with three observations). These findings contradict most
of the literature, which, as mentioned in the theoretical
framework, does not foresee a decline in migratory
intensity until the advanced phases of economic and social
development (no country in the region has reached that
phase to date). This result is also surprising because the
available evidence suggests that regional inequalities, which
constitute the main trigger for migration between major
administrative divisions, have not decreased in the last
30 years (ILPES, 2007). The reasons for this moderation
may lie in other determining factors of migration between
major administrative divisions, including urbanization (and
the resulting decline in migration from the countryside
to the city), the strengthening of small-scale trends (such
as in the processes of “concentrated deconcentration”
and “rurbanization”), the end of major government
programmes for population redistribution (which were
important in several countries in the region between
the 1960s and 1980s), and the increase of international
migration, which could be replacing internal migration
(Canales and Montiel, 2007).
Lastly, migration in the last five years between
minor administrative divisions is particularly high in
several countries, surpassing 12 percent of the reference
population in all observations, though for different
reasons.2 In the case of Paraguay, the main factor is
large-scale redistribution, which was already present in
migration between major administrative divisions, as well
as the process of reconfiguring the metropolitan area of
Asuncion, which entails major exchanges between the
municipalities that comprise Greater Asuncion (Causarano,
2006). The process of reconfiguring the metropolitan
areas of Chile, particularly Santiago, explains a large part
of this high intensity. In contrast, Cuba, Guatemala and
Nicaragua stand out for their low intensity. Setting aside
the debate over the comparability of these results, the
differences are real and have practical implications for
the municipalities. Indeed, those of Chile and Paraguay
are much more exposed to migratory exchange than

2

those of Cuba, Guatemala and Nicaragua, which affects
their socioeconomic dynamics, their administrative
performance and resource management, and their
relationship with the community. From another angle,
the figures in table IV.1 pertaining only to migration in
the last five years suggest that in Chile, at the beginning
of the 21st century, people change their municipality
of residence at least twice in a lifetime, while in Cuba,
Guatemala and Nicaragua a considerable portion of the
population never does so.
Table IV.1 provides data on migration levels and their
evolution over time. However, these are insufficient to
answer the question regarding the relationship between this
level and the development of the countries. The statistical
correlation between the two variables, shown in table IV.2,
indicates that there is indeed a positive relation, that is,
internal migration levels tend to be higher in countries
with greater human development.
Despite the simplicity of the test, there are at least two
arguments that support this finding. First, no relation exists
between the human development index and the number
or size of the administrative divisions. Consequently, that
distorting factor does not affect the relation observed.
Second, the coefficients always have the same positive
sign, showing a significance level of 95 percent in nearly
every case and remaining constant in two measurements.
Moreover, when levels of recent migration between major
administrative divisions are correlated with an indicator
of regional inequality, the coefficient is not significant
(and is in fact negative, in contradiction to the theory),
which suggests that this other powerful factor triggering
migration may influence the direction of flows, but not
so much their intensity at the national level.
Thus, the first of the hypotheses in this chapter
can be affirmed with relative certainty: development
is linked to greater levels of migration because, among
other factors, it facilitates moves and makes them more
affordable, it erodes territorial fixation, and it stimulates
intra-metropolitan migration directly and by composition
(metropolization). Nevertheless, the data on the evolution
of migration indices show that this positive relation has
limits, and that once it reaches a certain point it may
weaken or even be reversed.

However, none of the observations shown in table IV.1 is higher than the level recorded in the United States for the 1995-2000 period: 47
million people (18.6 percent of the reference population) resided in a county other than the one where they lived in 1995. All of the figures on
internal migration in the United States were obtained from the web page of the US Census Bureau.

Social Panorama of Latin America • 2007

205

Table IV.2
SIMPLE CORRELATION BETWEEN PERCENTAGE OF MIGRANTS (FOUR TYPES) AND THE HUMAN DEVELOPMENT INDEX (HDI),
2000 AND 1990 CENSUS ROUNDS,SELECTED COUNTRIES
Census
round

2000

1990

Variable

Lifetime- MAD
(16 cases)

Lifetime-MIAD
(11 cases)

Recent-MAD
(16 cases)

Recent-MIAD
(12 cases)

Simple correlation between HDI and migration:

0.695

0.891

0.373

0.677

p-value

0.0014

0.0001

0.0773

0.0111

Simple correlation between HDI and migration:

0.690775

0.854701

0.511543

0.612066

p-value

0.00152

0.00082

0.02564

0.03000

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of indicators from table IV.1 and
official data from the countries’ human development index (HDI) [on line] http://hdr.undp.org/hdr2006/statistics/indicators/default.cfm; and Simple
Interactive Statistical Analysis (SISA) [on line] http://www.quantitativeskills.com/sisa/calculations/signif.htm, for the p-value of the correlations.

206

Economic Commission for Latin America and the Caribbean (ECLAC)

D. Internal migration and countries’ development
Areas of positive net migration are usually those with the best living conditions. In contrast,
socio-economically disadvantaged subnational areas (the countryside, pockets of chronic
poverty that tend to have a high concentration of indigenous peoples) tend to be population
exporters. Population losses in these areas are selective, with young people and the educated
being overrepresented among those who leave. This erodes the base of human resources
needed for development in those areas. Migration can therefore be an escape route for
those who emigrate, while worsening the situation of poor areas that export population and
adversely affecting those who stay behind.

Presenting a detailed panorama of the migratory situation
of the major administrative divisions is a complicated task
due to their number and their peculiarities at the local and
national levels. On the other hand, an in-depth analysis
of migration between minor administrative divisions
simply cannot be dealt with in this chapter. Consequently,
instruments and procedures have been used to synthesize
and condense the information in order to perform analyses
that are brief and representative of the countries, as well
as to present relevant comparisons between them.
The first procedure consists of correlating the level
of development of the major administrative divisions with
their migratory attraction. The second instrument will be the
classification quadrant, which consists of a double-entry table
delimiting four zones (quadrants), each one representing
a specific situation pertaining to migration between major
administrative divisions: (a) attraction (positive net migration
in both censuses); (b) expulsion (negative net migration in
both censuses); (c) rising (negative net migration in the first
census and positive in the second), and (d) falling (positive
net migration in the first census and negative in the second).

The results make it possible to establish regularities (some
predictable and others less so) and also detect national and
subnational peculiarities, which are covered in this text in
a very preliminary manner.
The main conclusions drawn from the application
of both instruments are: a) higher levels of human
development in major administrative divisions tend
to be concomitant with higher net migration rates, i.e.
greater attraction (or less expulsion) (see table IV.3);
b) stability in migratory status prevails, which suggests
that the forces that determine the attraction of territories
tend to persist (see table IV.4); c) nevertheless, the
number of major administrative divisions that oscillate
is significant and may be instrumental in discovering
the factors with the greatest influence on migratory
trends (see tables IV.3 and IV.4 and maps IV.1 and
IV.2 of the annex for the general location of the major
administrative divisions).
The following is a superficial analysis of the four
categories of the quadrant (see table IV.4), including a
few illustrative examples using selected cases.

Social Panorama of Latin America • 2007

207

Table IV.3
LATIN AMERICA AND THE CARIBBEAN: SIMPLE LINEAR CORRELATION BETWEEN THE HUMAN DEVELOPMENT INDEX (HDI) AND THE
NET INTERNAL MIGRATION RATE AT THE LEVEL OF MAJOR ADMINISTRATIVE DIVISIONS (MAD), SELECTED COUNTRIES,
CENSUSES FROM THE 2000 ROUND
Country, indicator, reference year
and number of MAD with data

Coefficient of simple correlation between the HDI and
the net migration rate (p-value in parentheses)

Argentina, 2001: 24 MAD, HDI 1996

0.407 (0.0242)a

Bolivia, 2002: 9 MAD, HDI 1994

0.619 (0.0378)a

Brazil, 2000: 27 MAD, HDI 1996

0.451 (0.0091)a

Chile, 2002: 13 MAD, HDI 1998

-0.01136 (0.5147)

Colombia, 2005: 24 MAD, HDI, 2000

0.414 (0.0222)a

Cuba, 2002: 14 MAD, HDI 1996

0.770 (0.0006)a

Ecuador, 2001: 15 MAD, HDI, 1999

0.650 (0.0044)a
0.442 (0.01972)a

Guatemala, 2002: 22 MAD, HDI 1995-1996
Honduras, 2001: 18 MAD, HDI 1996

0.697 (0.0006)a

Mexico, 2000: 32 MAD, HDI 1995

0.408 (0.0102)a

Nicaragua, 2005: 17 MAD, HDI 2000

0.055 (0.4170)

Panama, 2000: 12 MAD, HDI 2000

0.484 (0.0554)

Paraguay, 2002: 18 MAD, HDI 2000

0.133 (0.29936)

Uruguay, 1996: 19 MAD, HDI 1991

0.063 (0.60097)

Venezuela (Bol. Rep. of), 2001: 23 MAD, HDI 1996

0.0686 (0.3780)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special processing of census microdatabases for migration
rates; national human development reports and official subnational statistics for the human development index (HDI) on the subnational scale and Simple
Interactive Statistical Analysis (SISA) [on line] http://www.quantitativeskills.com/sisa/calculations/signif.htm, for p-value of correlations.
aSignificant coefficient with a significance level of 95 percent (p-value0.05).

Table IV.4
LATIN AMERICA AND THE CARIBBEAN, SELECTED COUNTRIES: CLASSIFICATION OF MAJOR ADMINISTRATIVE DIVISIONS
BY INTERNAL MIGRATION STATUS IN 1990 AND 2000 CENSUS ROUNDS

Antigua and Barbuda
Gaining population
NMR (+) 2001-1996
NMR (+)
1992-1987

St. John’s rural;
St. George’s; St. Peter’s

Gaining population
NMR (+) 2000-1995
NMR (+)
1991-1986

St. Phillip’s; St. Paul’s
St. Mary’s;
St. John’s City;
Barbuda

TMN (-)
1992-1987

Barbados

Losing population
NMR (-) 2001-1996

NMR (-)
1991-1986

Belize

NMR (-)
1992-1987

Losing population
NMR (-) 2001-1996

Cayo District

Belize District

TMN (+)
1992-1987

Corozal District;
Orange Walk District;
Toledo District

TMN (-)
1992-1987

Stann Creek District

St. Peter; St. Philip;
Christ Church;
St. James
St. George; St. Thomas

St. Michael;
St. John; St. Joseph;
St. Andrew; St. Lucia

Bolivia

Gaining population
NMR (+) 2001-1996
NMR (+)
1992-1987

Losing population
NMR (-) 2000-1995

Gaining population
NMR (+) 2001-1996

Losing population
NMR (-) 2001-1996

Cochabamba; Tarija;
Santa Cruz; Pando

Beni
Chuquisaca; La Paz;
Oruro; Potosí

208

Economic Commission for Latin America and the Caribbean (ECLAC)

Table IV.4 (continued)
LATIN AMERICA AND THE CARIBBEAN, SELECTED COUNTRIES: CLASSIFICATION OF MAJOR ADMINISTRATIVE DIVISIONS
BY INTERNAL MIGRATION STATUS IN 1990 AND 2000 CENSUS ROUNDS
Brazil
Gaining population
NMR (+) 2000-1995

NMR (+)
1991-1986

NMR (-)
1991-1986

Amazonas; Roraima;
Amapá; Tocantins;
Espírito Santo;
São Paulo; Santa
Catarina; Mato
Grosso; Goiás; Distrito
Federal; Rondônia
Rio Grande do
Norte; Minas Gerais;
Rio de Janeiro

Chile
Losing population
NMR (-) 2000-1995

Losing population
NMR (-) 2002-1997

NMR (+)
1992-1987
Pará; Sergipe; Mato
Grosso do Sul

Gaining population
NMR (+) 2002-1997
Valparaíso; Tarapacá

Atacama; Metropolitan
Santiago

NMR (-)
1992-1987

Antofagasta; Coquimbo;
Lib. Gral. Bernardo
O’Higgins; Los Lagos

Maule; Bío Bío;
La Araucanía; Aisén;
Magallanes; Antártica

Acre; Maranhão;
Piauí; Ceará; Paraíba;
Pernambuco; Alagoas;
Bahia; Paraná; Rio
Grande do Sul

Colombia a

Costa Rica

Gaining population
NMR (+) 2005-2000
NMR (+)
1993-1988

NMR (-)
1993-1988

Losing population
NMR (-) 2005-2000

Bogotá; Risaralda;
Valle; Casanare;
Cundinamarca; Quindío

Bolívar; Atlántico;
Guajira; Arauca

Antioquia;
Santander; Meta

Boyacá; Caldas; Cauca;
Córdoba; Chocó;
Huila; Magdalena;
Nariño; Sucre;
Tolima; Amazonas;
Caquetá; Cesar;
Norte; Santander;
Putumayo; San Andrés;
Guaviare; Vichada

Gaining population
NMR (+) 2001-1996
NMR (+)
1984-1979

NMR (+)
1981-1976

NMR (-)
1981-1976

Gaining population
NMR (+) 2001-1996
NMR (+)
1990-1985

Pinar del Río; Villa Clara;
Las Tunas; Holguín;
Ganma; Santiago de
Cuba; Guantánamo

NMR (-)
1990-1985

NMR (+)
1994-1989

NMR (-)
1994-1989

El Oro; Guayas;
Pastaza; Pichincha;
Galápagos; Sucumbíos

Morona Santiago; Napo;
Zamora Chinchipe

Azuay; Cañar

Bolívar; Carchi;
Cotopaxi; Chimborazo;
Esmeraldas; Imbabura;
Loja; Los Ríos;
Manabí; Tungurahua

Gaining population
NMR (+) 2001-1996

Losing population
NMR (-) 2002-1997

Guatemala;
Sacatepéquez; Peten

Chimaltenango;
Escuintla

Losing population
NMR (-) 2001-1996

Honduras

Guatemala
Gaining population
NMR (+) 2002-1997

San José; Guanacaste;
Puntarenas

Ecuador b
Losing population
NMR (-) 2002-1997

La Habana; Ciudad
Habana; Matanzas;
Cienfuegos; Ciego
de Ávila; Camagüey;
Isla de la Juventud
Sancti Spíritus

Alajuela; Cartago;
Heredia; Limón

NMR (-)
1984-1979

Cuba
Gaining population
NMR (+) 2002-1997

Losing population
NMR (-) 2001-1996

NMR (+)
1988-1983
El Progreso;
Santa Rosa; Sololá;
Totonicapán;
Quetzaltenango;
Suchitepéquez;
Retalhuleu; San Marcos;
Huehuetenango;
Quiche; Baja Verapaz;
Alta Verapaz; Izabal;
Zacapa; Chiquimula;
Jalapa; Jutiapa

NMR (-)
1988-1983

Losing population
NMR (-) 2001-1996

Atlántida; Cortés;
Francisco Morazán;
Islas de la Bahía

Colón; Comayagua;
Yoro
Copán; Choluteca;
El Paraíso; Gracias
a Dios; Intibuca;
La Paz; Lempira;
Ocotepeque; Olancho;
Santa Bárbara; Valle

Social Panorama of Latin America • 2007

209

Table IV.4 (concluded)
LATIN AMERICA AND THE CARIBBEAN, SELECTED COUNTRIES: CLASSIFICATION OF MAJOR ADMINISTRATIVE DIVISIONS
BY INTERNAL MIGRATION STATUS IN 1990 AND 2000 CENSUS ROUNDS
Mexico
Gaining population
NMR (+) 2000-1995

NMR (+)
1990-1985

NMR (-))
1990-1985

Nicaragua
Losing population
NMR (-) 2000-1995

Coahuila; Hidalgo;
Yucatán

Losing population
NMR (-) 2005-2000

NMR (+)
1995-1990

Atlántico Norte;
Managua; Río San Juan

Jinotega

NMR (-)
1995-1990

Aguascalientes;
Baja California;
Baja California Sur;
Campeche; Colima;
Chihuahua; Guanajuato;
Jalisco; México;
Morelos; Nuevo León;
Querétaro de Arteaga;
Quintana Roo; Sonora;
Tamaulipas, Tlaxcala

Gaining population
NMR (+) 2005-2000

Masaya; Granada;
Carazo; Rivas;
Nueva Segovia

Madriz; Estelí;
Chinandega; León;
Matagalpa; Boaco;
Chontales; Atlántico Sur

Chiapas; Distrito
Federal; Durango;
Guerrero; Michoacán;
Nayarit; Oaxaca;
Puebla; San Luis
Potosí; Sinaloa;
Tabasco; Veracruz
Llave; Zacatecas

Panama c

Paraguay

Gaining population
NMR (+) 2000-1995
NMR (+
1990-1979
NMR (-)
1984-1979

Losing population
NMR (-) 2000-1995

Panamá

Bocas del Toro; Darién

Coahuila; Hidalgo;
Yucatán

Coclé; Colón;
Chiriquí; Herrera;
Los Santos; Veraguas

Gaining population
NMR (+) 2002-1997
NMR (+)
1992-1987

NMR (-)
1992-1987

NMR (+)
1985-1980

NMR (-)
1985-1980

Canelones

Maldonado; San José

Alto Paraná; Boquerón;
Canindeyú; Central

Presidente Hayes

Alto Paraguay;
Amambay; Asunción;
Caaguazú; Caazapá;
Concepción; Cordillera;
Guaira; Itapú;
Misiones; Ñeembucu;
Paraguarí; San Pedro

Venezuela (Bolivarian Rep. of) d

Uruguay
Gaining population
NMR (+) 1996-1991

Losing population
NMR (-) 2002-1997

Gaining population
NMR (+) 2001-1996

Losing population
NMR (-) 2001-1996

NMR (+)
1990-1985

Lara; Anzoategui;
Aragua; Barinas;
Carabobo; Cojedes;
Miranda; Nueva
Esparta; Amazonas;

Bolívar

NMR (-)
1990-1985

Delta Amacuro; Mérida;
Monagas; Yaracuy

Zulia; Distrito Capital;
Portuguesa

Losing population
NMR (-) 1996-1991
Artigas; Cerro Largo;
Montevideo; Rivera;
Rocha; Treinta y Tres
Colonia; Durazno;
Flores; Florida;
Lavalleja; Paysandú;
Río Negro; Salto;
Soriano; Tacuarembó

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of Migration in Latin America
and the Caribbean (MIALC) [on line database] http://www.eclac.cl/migracion/migracion_interna/; special processing of census microdatabases; 2005
census of Colombia, Colombia and National Statistical Office, Cuba.
Note: NMR – net migration rate.
aNo information is available on the major administrative divisions of Guainia and Vaupes in the 1993 census.
b No information is available on the major administrative division of Orellana in the 1990 census.
cNo information is available on the major administrative divisions of Comarca Kuna Yala; Comarca Emberá and Comarca Gnobe Bugle in the 1990 census.
dNo information is available on the major administrative divisions of Vargas and Federal Dependencies in the 1990 census.

210

1. 

Economic Commission for Latin America and the Caribbean (ECLAC)

Expulsive major administrative divisions

This quadrant contains two main types of major administrative
division that differ greatly from one another. On the one
hand are those that have higher relative poverty, are more
affected by marginalization and tend to be inhabited by
indigenous peoples; these are major administrative divisions
that are expulsive because of poverty. On the other hand
are those in which the principal city has historically been
located, and which have overflowed over the last 50
years as a result of the process of metropolization and
suburbanization; these are major administrative divisions
that are expulsive because of overflow.
Expulsive major administrative divisions of the first
type tend to be grouped territorially, forming one or more
subnational areas that are very expansive and show a clear
socioeconomic lag (see maps 1 and 2 of the appendix). A
few examples are northwest Argentina, northeast Brazil,
western Bolivia, the centre-south of Chile, eastern Cuba
and southern Mexico. In the case of expulsive major
administrative divisions of the second type, the opposite
is true, as the neighbouring divisions tend to be attractive
precisely because they receive a significant portion of
the exit flow from the metropolitan major administrative
division. Such is the case for the Federal District of Mexico,
the city of Buenos Aires or Federal Capital in Argentina,
the department of Asuncion in Paraguay and the Federal
District of the Bolivarian Republic of Venezuela.
The differences between these two types of expulsive
major administrative division are not limited to their territorial
determinants and characteristics, but are also present in their
consequences. For major administrative divisions that are
expulsive because of poverty, net emigration means an erosion
of the human resource base needed for their development.
In those that are expulsive due to overflow, however, the
effects are more uncertain, partly because a portion of the
emigrating population actually maintains daily contact with
the metropolitan major administrative division of origin.

2. 

The conclusion regarding major administrative divisions
that are expulsive because of poverty is based on evidence
discussed further on. Its foundation lies in the notion of
selectivity in migration by age and education level. The
emigration flows from regions that are expulsive because
of poverty contain a disproportionate number of people of
working age, particularly youths, with an above-average
education level. This means that those who leave these
regions belong to their most dynamic and skilled human
resource base, which weakens the already deteriorating
production conditions in these regions and generates
territorial poverty traps. In short, although this emigration
also has positive aspects (obviously for the emigrants,
who undertake it to better their situation, but also for
the major administrative divisions of origin, which have
trouble productively absorbing their population and do
not have the necessary resources to meet its needs, not
to mention the remittances of internal emigrants, though
these are usually less substantial than remittances from
international migrants), its end result for the territory
of origin is an erosion of its human resources base for
development.
Regarding metropolitan major administrative divisions
that are expulsive due to overflow, the conclusion is based,
in addition to the aforementioned argument of continued
daily interaction between many emigrants and the major
administrative division, on evidence presented in previous
studies (Guzmán et al., 2006; Rodríguez, 2004a) and on
data that are analysed later on in this chapter. Its foundation
is that although these major administrative divisions
have net emigration, they still receive a large number of
immigrants attracted by factors such as employment and
intense social and cultural activity. Consequently, rather
than an erosion of the human resource base, a constant
replenishment of this base is observed, which does not
diminish their levels of skilled labour and productivity.

Attractive major administrative divisions

Most of these major administrative divisions are dynamic
in economic terms and particularly in terms of employment;
however the causes of this dynamism vary. In some cases
the major administrative divisions are located along an
international border and take advantage of border-related

externalities to improve their competitiveness and achieve
greater global integration in various sectors. The states along
Mexico’s northern border, which enjoy growth driven by
the industrial sector, exemplify this phenomenon. Other
examples are some of the departments along the eastern

Social Panorama of Latin America • 2007

borders of Paraguay, Uruguay and Bolivia, though in
these cases the dynamic sector is the commercial sector,
particularly with respect to trade with Brazil.
In other instances, the dynamism stems from the
condition of being a “border” (international or internal),
with advantages in terms of the availability of natural
resources, specific support from policies for territorial
development and promotion (including past settlement
programmes) or both.3 In countries such as Paraguay,
energy production in these areas has also been a driver
of economic growth and a factor in attracting population.
Lastly, tourism, particularly at the global level, has also
proven to be a powerful sector of production with an
enormous capacity for generating employment and,
consequently, attracting population. Quintana Roo, the
state in Mexico where Cancun is located, is one of the
more notable examples, although the phenomenon can
also be observed in the eastern region of the Dominican
Republic, among other countries.4
Many metropolitan major administrative divisions
(those which contain the principal city or at least one of the
country’s biggest cities) maintain their migratory attraction
by combining a booming economy with an ongoing focus
on public and private investment and living conditions

3.

4

5

far above the national average. The department of Santa
Cruz in Bolivia, the provinces of Guayas and Pichincha
in Ecuador, the department of Guatemala in Guatemala,
the departments of Francisco Morazán and Cortés in
Honduras and the province of Panama in Panama are a
few emblematic cases.
Last are the major administrative divisions that are
attractive for their “proximity” to a metropolis in the
process of suburbanization. The most notable examples are
the province of Buenos Aires in Argentina, the Valparaiso
region in Chile, the state of Mexico in Mexico, the
provinces of Heredia, Alajuela and Cartago in Costa Rica,
the department of Sacatepequez in Guatemala (Valladares
and Morán, 2006), Central in Paraguay (Causarano, 2006),
Canelones in Uruguay and the state of Miranda in the
Bolivarian Republic of Venezuela. What is important
about these examples is that their attraction is the result
of determinants very different from those of traditional
migration from the countryside to the city or between
regions, which is why some of the major administrative
divisions may even have below-average living conditions
but receive migrants from the city either because of the
suburbanization of high- and middle-income families or the
relocation of poor families to the outskirts of the city.

“Changing” major administrative divisions

There are few major administrative divisions whose net
migration oscillates considerably, but these cases offer
a great deal of information on emerging factors in the
attraction or expulsion of population.
One factor contributing to changes in the attraction
of subnational areas for internal migrants is recent
economic restructuring. The sudden attraction of regions
containing non-traditional export activity that has been
successfully integrated into global markets is emblematic.
An example is the region of Los Lagos in Chile, where
salmon, forest products and timber have contributed
to reversing the area’s historical net emigration. This
case serves to highlight a point that has not yet been
discussed: the heterogeneity that can exist within major

3

211

administrative divisions. The economic engine of the
Los Lagos region, Puerto Montt, has indeed become a
very attractive city, but the other two production and
political-administrative centres, Valdivia and Osorno,
have not experienced the same growth; in fact they
continue to have net emigration. 5
Another relevant factor is the recent suburbanization
and saturation of metropolitan areas. The metropolitan
region of Chile, where Santiago is located, is a good
example because it experienced net emigration for the
first time in its history during the 1997-2002 period. This
change in migratory trend is due to the combination of
negative externalities of build-up and the attraction of
alternative regions (including some neighbouring areas,

Examples of this situation are: the Patagonian provinces of Argentina, the department of Pando in Bolivia, the Tarapacá region in Chile, much of
eastern Ecuador and some departments of eastern Paraguay, the department of El Petén in Guatemala and several Amazonian states in Brazil.
However, not all major administrative divisions with a large tourism industry are attractive, as evidenced by the coastal areas of central-Pacific
and northern Costa Rica, where tourism companies with foreign or mixed-domestic capital undertake activities that do not always manage to
retain or productively absorb the local population, making these areas expulsive with regard to internal migrants (Barquero, 2007).
The regional structure in Chile changed in 2007, and a portion of the Los Lagos region broke off to form a new region called Los Ríos, which
has its seat of government in Valdivia.

212

Economic Commission for Latin America and the Caribbean (ECLAC)

but also other distant ones, which will be discussed later
on) with the significant increase in connectivity, which
makes it easier to relocate outside the metropolitan area
without losing contact with it.
A third relevant factor is the changing of territorialdevelopment policies, particularly in sparsely populated areas
that have been the beneficiaries of specific programmes.
The department of Beni in Bolivia is a clear example,
since its net emigration for the 1996-2001 period can
be explained in part by the decline in territorial support
programmes, particularly those that promoted settlement.
The case of San Luis in Argentina is an illustration of
rebounding migration tied to the cumulative effects over
much of the 1990s of a regional-promotion policy based

4.

on public investment, the development of infrastructure
and support for industrial activity.
Lastly, an emerging factor seems to be international
emigration. Although intuition would suggest that an
increase in this type of emigration should create a similar
rise in internal emigration, the opposite seems to be true
in some cases, both because departures abroad replace
moves to other parts of the country, and because of the
stimulating effect of remittances (at least in the short term)
on the economy of the place of origin. The mountain
provinces of Azuay and Cañar in Southern Ecuador are
examples of this change, since despite a long tradition
of internal emigration, both became attractive to internal
migrants according to the 2001 census.

Conclusion

To summarize, in addition to the persistent association
between chronic poverty and net internal emigration,
there is currently a complex mixture of forces that
determine the attraction of subnational areas. Without
doubt, better living conditions remain one of the most
powerful magnets, but they are counterbalanced by a
potential breakdown in these conditions (which have
been developed in a long process) or in the economic
expansion (which is less predictable than, and to some
extent independent of, these living conditions), and
the possibility of enjoying such advantages without
residing in the advantaged areas (by suburbanization).
Moreover, the production-driving forces that operate
with globalization and the new services and technology
economy may change territories’ attraction through
emerging and diversified factors.

Two factors appear crucial in this regard. The first
is the elasticity that results from employment, since for
migrants seeking work the relevant variable is job creation.
This is why there are large investments in production
that in the long term have little permanent impact on
employment and therefore do not necessarily create
a lasting migratory attraction. The other is residential
conditions, since even when migration is motivated by
the search for employment, it is becoming increasingly
possible to commute to and from work on a daily basis,
especially in work schedules based on shifts. This changes
the relationship between the workplace and the place
of residence and, by the same token, the effect on the
recipient region produced by the new workers, who are
not necessarily migrants, but people who come and go
with some frequency (Aroca, 2007).

Social Panorama of Latin America • 2007

213

E. Effect of internal migration on


the areas of origin and destination

Because migration is selective in nature, it alters the population composition in areas of origin
and destination. Net emigration appears to have a negative effect on the demographic structure
of poor areas that have historically been population exporters, according to calculations targeting
such areas in some of the region’s countries, and this contributes to the formation of territorial
poverty traps. Moreover, broader calculations show that territorial gaps in terms of age structure
and education are tending to widen, which suggests that internal migration does little to reduce
territorial inequalities within countries.

The first effect of internal migration on the areas of origin
and destination is observed in the volume of the population,
and measuring it is quite useful for making subnational
demographic projections, which until recently were prepared
with little or no information on this type of migration.
The effect of migration is also qualitative. Migrants can
change the profile of the population in both the area of origin
and the area of destination. Due to migratory selectivity
according to sex, age and education level (which will be
discussed later in this chapter), the structure of the areas of
origin and destination in terms of sex, age and education
level tends to be affected by internal migration. Thus,
migration directly affects socio-territorial gaps, particularly
those of a sociodemographic nature. For example, if ageing
adults tended to migrate towards regions with more elderly,
this would translate into a widening of disparities in age
structure between the subnational areas.

6

Several procedures have been tested for measuring
the effect of internal migration on the populations of
origin and destination, as well as its effect on trends in
territorial sociodemographic gaps (Soloaga and Lara, 2007;
Aroca, 2004; Rodríguez, 2004a and 2004b; Polese 1998;
Greenwood, 1997; Lucas, 1997). CELADE – Population
Division of ECLAC has developed one such procedure,
which has been disseminated and applied since 2004
(Rodríguez, 2007, 2004a and 2004b). The fundamental
idea is to use the matrix of flow indicators (derived from
the matrix of recent migration), compare its marginals
and determine on that basis whether the migration had
a positive or negative effect (net and exclusive) on the
attribute.6 The following section contains information
on the application of this procedure, which provides
evidence regarding two of the hypotheses put forward
in this chapter.

One of the marginals corresponds to the attribute at the time of the census, i.e. when the effect of migration has actually occurred, and the other
corresponds to the same attribute, but with the territorial distribution that it would have if there had been no migration during the reference period.
It is a comparison between a current, observed scenario and a hypothetical scenario. The key assumption of the procedure is the permanence of
the attribute over time (which is guaranteed for variables such as sex) or the uniform variation across the entire population (which is guaranteed
for variables such as age).

214

Economic Commission for Latin America and the Caribbean (ECLAC)

1.

Migration and territorial poverty traps

In the previous section it was mentioned that a positive and
significant correlation exists between the socioeconomic
situation of subnational areas and their migratory attraction,
and that in the case of subnational regions that are historically
depressed, the emigration that characterizes them may be
harmful because those who migrate are predominantly
young people with relatively high levels of education.
This combination of factors would mean that migration
contributes to producing territorial poverty traps.
Providing evidence related to this hypothesis requires
techniques that make it possible to isolate the effect of
migration and that take into account the number and
characteristics of those who leave and those who stay. The
procedure developed by CELADE – Population Division
of ECLAC produces conclusive results in favour of the
hypothesis of the formation of territorial poverty traps.

Table IV.5 presents a synthesis of the information
pertaining to six countries in the region for which it
is easy to identify the subnational regions that are
depressed. The results are displayed for each politicaladministrative division of the areas that had net emigration
according to the latest census. Without exception, this
migration produces a harmful effect on the age structure,
since it tends to increase the proportion of children
and the elderly while reducing the proportion of the
working-age population. Thus, emigration increases
the demographic dependency of the population of
these depressed areas, aggravating an already difficult
situation. Moreover, migration in the vast majority of
the major administrative divisions examined tends to
reduce average education levels, thereby eroding what
little human capital they have.

Table IV.5
LATIN AMERICA AND THE CARIBBEAN (SELECTED COUNTRIES): MAJOR ADMINISTRATIVE DIVISIONS (MAD) BELONGING TO
HISTORICALLY DEPRESSED SUBNATIONAL REGIONS WITH NET EMIGRATION, BY EFFECT OF INTERNAL MIGRATION ON THE AGE
STRUCTURE AND EDUCATION LEVEL OF THE POPULATION
Northern Argentina
MAD
with net
emigration

Bolivian Altiplano

Central-Southern Chile

Proportion Proportion Education
Net
MAD
Proportion Proportion Education
Net
Net
MAD
Proportion Proportion Education
with net migration of children of elderly level of
level of
migration of children of elderly
with net migration
of
of elderly level of
heads of emigration rate (per
rate (per
heads of emigration rate (per children
heads of
1,000)
household
1,000)
1,000)
household
household

Salta

-0.91

0.69

0.7

-0.082

Chuquisaca

-6.27

0.76

1.73

1.724

Del Maule

-0.42

1.73

1.22

0.19

Jujuy

-2.09

1.3

1.05

-0.735

La Paz

-3.11

0.14

0.2

-0.393

Bío Bío

-2.21

1.15

1.18

-0.46

Tucumán

-0.27

0.04

0.29

-0.006

Oruro

-8.88

2.38

2.94

-2.268

Araucanía

-0.48

1.66

1.19

0.25

Santiago
del Estero

-1.4

0.87

0.71

-0.143

Potosí

-14.76

1.67

3.34

-2.168

North-eastern Brazil
MAD
with net
emigration

Mountains of Ecuador

Southern Mexico

Proportion Proportion Education
Net
MAD
Proportion Proportion Education
Net
Net
MAD
Proportion Proportion Education
with net migration of children of elderly level of
level of
migration of children of elderly
with net migration
of
of elderly level of
heads of emigration rate (per
rate (per
heads of emigration rate (per children
heads of
1,000)
household
1,000)
1,000)
household
household

Maranhão

-6.88

0.77

2.52

-0.248

Carchi

Piauí

-4.06

1.32

1.83

-0.657

Imbabura

-13.13

2.91

2.27

-1.9833

Oaxaca

-4.24

0.79

1.68

0.039

-1.89

1.08

0.85

0.23049

Guerrero

-6.42

0.36

2.14

-0.149

Ceará

-0.72

0.47

0.57

0.599

Cotopaxi

-5.13

1.40

0.99

-0.2953

Chiapas

-2.85

Paraíba

-3.92

0.82

1.86

-0.173

Tungurahua

-1.79

0.94

0.20

-0.2927

Puebla

-1.14

0.69

0.99

-0.268

0.28

0.37

Pernambuco

-3.21

0.49

1.14

-0.072

Bolívar

-15.16

3.67

2.36

-3.0228

0.068

Alagoas

-5.70

0.4

2.61

-0.033

Chimborazo

-9.01

1.91

2.56

0.15052

Sergipe

-0.61

0.31

1.13

-0.063

Loja

-9.30

2.47

2.30

-0.5514

Bahia

-4.50

0.42

1.95

0.081

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of Internal Migration in Latin
America and the Caribbean (MIALC) [online database] http://www.eclac.cl/migracion/migracion_interna/ and procedures described in the text.

Social Panorama of Latin America • 2007

2.

215

Migration and sociodemographic disparities between territories

The analysis of the information in the previous section is
insufficient to determine the effect, on average, of migration
on disparities between territories. This calculation requires
another instrument: the simple correlation coefficient. If
the correlation between the net and exclusive effect of
migration and the initial value of the attribute is positive,
migration would tend to widen the territorial gaps, since
the major administrative divisions with higher levels of
the attribute at the initial point in time (five years prior
to the census) would tend to show a larger increase in
this attribute as a result of migration. If the correlation is
negative, migration would tend to narrow the territorial
gaps. Table IV.6 shows a summary of these correlations in
13 countries with the necessary data for all the indicators
measured. The main findings are the following:
• In the vast majority of countries, migration between
major administrative divisions tends to widen the
territorial disparities in terms of the proportion of
children. The widely-prevailing positive coefficients
seem to indicate that the major administrative
divisions with a higher initial proportion of children
(generally the poorer ones) are those in which
this proportion increases the most on average as
a result of migratory exchange with other major
administrative divisions. The mechanism that
produces this effect is rather complex, as it is

derived not from the arrival of children in these
divisions, but from a massive exodus of young
adults, which indirectly raises the proportion of
children under 15 years of age.
• Migration between major administrative divisions
clearly accentuates disparities in terms of the
territorial distribution of the population by sex. This
distribution, which is predetermined by migratory
flows, particularly from the countryside to the city, has
been marked by a basic imbalance: women represent
a majority in more urbanized major administrative
divisions that have historically been areas of attraction.
According to the coefficients in table IV.6 (most of
which have a significance level of 95 percent), recent
migration has widened this gap, inasmuch as major
administrative divisions with an initial majority of
men have increased this majority as a result of the
net and exclusive effect of migration.
• With respect to attributes pertaining to the
development of human resources, the coefficients
are less conclusive. Although negative coefficients
prevail, which would indicate that migration
contributes to reducing territorial disparities in terms
of education levels, only in three cases does this
coefficient have a significance level of 95 percent,
and in one of them the coefficient is positive.

Table IV.6
LATIN AMERICA AND THE CARIBBEAN (SELECTED COUNTRIES): CORRELATIONS BETWEEN SELECTED SOCIODEMOGRAPHIC
VARIABLES AND THEIR VARIATION DUE TO THE EFFECT OF RECENT INTERNAL MIGRATION, CENSUSES FROM THE 2000 ROUND
Simple correlation between the initial level of the indicator and the net
and exclusive effect of migration on the same indicatora

Country
Average Age

Argentina, 2001

Percentage
of Children

Percentage
of Elderly

Male Ratio

Average years of
schooling (population
aged 30-59 years)

-0.27

0.61

-0.04

0.64

Bolivia, 2002

0.26

-0.32

0.67

0.17

0.85

Brazil, 2000

-0.05

0.00

0.47

0.46

-0.02
-0.71

Chile, 2002

0.02

0.08

0.18

0.61

0.78

Costa Rica, 2000

-0.19

0.42

0.35

0.27

0.06

Ecuador, 2001

-0.27

-0.13

0.43

0.47

-0.55

Guatemala, 2002

-0.67

0.21

-0.21

0.48

-0.04

Honduras, 2001

-0.32

0.62

0.44

0.43

-0.70

Mexico, 2000

-0.17

0.29

0.50

0.19

-0.22

Panama, 2000

-0.34

-0.24

0.23

0.87

0.31

Paraguay, 2002

-0.11

0.26

0.17

0.84

-0.38

Dominican Republic, 2002

-0.43

0.80

0.20

0.92

-0.16

0.19

0.49

0.46

0.36

0.14

Venezuela (Bol. Rep. of), 2001

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of Internal Migration in Latin
America and the Caribbean (MIALC) [online database] http://www.eclac.cl/migracion/migracion_interna/ and procedures described in the text.
aSignificant coefficients have a significance level of 95 percent.

216

Economic Commission for Latin America and the Caribbean (ECLAC)

F. Urbanization and migration
As the region has become more urbanized, movements between cities have increased more
than any other type of population flow, and this has changed the profile of internal migrants.
The predominance of migration between cities means that those cities have increased in size
mainly as a result of their own natural growth. Nevertheless, rural-to-urban migration is
still considerable in the region overall because it remains the main type in some of the less
urbanized countries, where it is still the driving force behind urbanization (a proportional
increase in the urban population). In all countries, rural-to-urban migration continues to have
a considerable demographic impact on the rural population, whose reduction in absolute
terms across the region is attributable to emigration to cities.

As indicated in the theoretical framework section, the
persistent inequality between urban and rural areas (UNFPA,
2007; Guzmán et al, 2006; ECLAC, 2005a) should lead
to a continuous flow of migrants from the countryside
to the city. In addition, progressive urbanization should
accentuate the weight of migration between cities in
the total migratory flow from countryside to city. In the

1.


Direct estimates of migration
between countryside and city

The 2000 round of censuses included questions that
allowed for a direct estimate of migration between the
countryside and the city, and therefore the identification
of four possible migratory flows between the two, in only
four countries of the region: Brazil, Nicaragua, Panama
and Paraguay. Table IV.7 shows a summary of the results.7
The following conclusions can be drawn from the data:
• The predominance of migration between urban
areas has become stronger in every country but
7

8

section below, direct procedures are applied to generate
recent evidence related to both hypotheses. Since these
procedures can be applied in only a few countries in the
region, the following subsection refers to techniques for
making indirect estimates of rural to urban migration,
which will provide evidence supporting the first hypothesis
for the vast majority of countries in the region.

Nicaragua, where the migratory flow from the
countryside to the city is by far the most intense.8
It should be stressed that in countries such as
Brazil, this trend is entirely to be expected,
given the high levels of urbanization there
(above 80%); but it is also seen in countries
with considerably less urbanization (around
65%), such as Panama or even Paraguay (less
than 60%).

Only recent migration is taken into consideration, because it was not feasible to calculate absolute migration in at least one of the four countries
analysed. Furthermore, the lack of a period of reference introduces an additional ambiguity with respect to the answers respondents gave about
the residential area in which they were born (or the place where their mother lived when they were born).
There are solid grounds to conclude that this flow was overestimated in the case of Nicaragua, because it is not consistent with data from other
sources, such as the National Household Living Standards Survey of 2001 and in particular with the moderate rate of urbanization seen in the
country between 1995 and 2005.

Social Panorama of Latin America • 2007

217

• The net shift of population from the countryside
to the city continues, amounting to more than 1
million people in Brazil between 1995 and 2000,
more than 200,000 people in Nicaragua between
2000 and 2005, and just over 34,000 people in
Panama between 1995 and 2000. The exception
is Paraguay, where more than 60,000 internal
migrants reportedly moved to the countryside
in the 1997-2002 period; but this result has been
officially called into question (Sosa, 2007).
• Migration from one rural area to another tends to
be less significant, but it may be underestimated
because of the seasonal nature of many of
these moves. It has been documented that the
environmental effects of this type of migration

can be considerable, particularly in the case of
movements towards the agricultural frontier or
settlement areas (Reboratti, 1990; CELADE/IDB,
1996; Pinto da Cunha, 2007).
• Except in the striking and doubtful case of Paraguay,
there are no signs of a massive return to the countryside.
However, the flow from the city to the countryside
should be studied in more depth, because a significant
part of it could be the result of suburbanization of
metropolitan areas (Guzmán et al, 2006).
In this manner, the data tend to support two hypotheses
presented here: migration from the countryside to the
city continues as a result of persistent disparities, to
the detriment of rural areas, and there is a quantitative
predominance of migration between cities.

Table IV.7
POPULATION AGED 5 AND ABOVE: DIRECT ESTIMATES OF RECENT MIGRATION BETWEEN URBAN AND RURAL AREAS: COUNTRIES
WHOSE CENSUS INCLUDES RELEVANT QUESTIONS, 2000 ROUND OF CENSUSES a
Country and census year

Brazil, 2000
Nicaragua, 2005
Panama, 2000
Paraguay, 2002

Area of current
residence

Area of residence five years previously
No migration between minor
administrative divisions

Urban

Rural

Urban

111 027 460

10 775 021

3 244 288

Rural

24 965 713

2 168 599

1 161 891

Urban

2 109 103

67 567

338 008

Rural

1 744 706

119 443

64 210

Urban

1 297 825

152 089

74 836

Rural

832 551

40 798

29 741

Urban

2 175 943

248 014

31 361

Rural

1 734 786

91 592

53 867

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of special processing of census
microdatabases
aSome filters are used, such as considering children under the age of five in the case of recent migration; in addition, other standards are taken into
consideration for the analysis of internal migration, such as the exclusion of those born or living in other countries five years previously in the case
of absolute and recent migration, respectively; and in the interest of data quality, certain items were excluded, such as cases of no replies or outlier
replies to base questions (usual place of residence, birthplace and place of residence five years previously). Moreover, other filters apply depending
on the census (some countries in the table —Brazil, Paraguay— capture rural-to-urban migration within minor administrative divisions, whereas others
—Nicaragua, Panama— do not). Therefore caution should be exercised in making comparisons among them.

2.

Indirect estimates

Direct estimates can be made only in a few countries, so
procedures have been developed to make indirect estimates
that yield net balances combining migration with the
reclassification of urban and rural locations.
The figures in table IV.8 were obtained using the
indirect procedure known as “survival ratios”, and their
main contribution is to confirm the hypotesis that migration
from the countryside to the city represents a small and
shrinking proportion of the urban population expansion.
Indeed, for the region as a whole, the net transfer of

population from countryside to city, combined with the
net reclassification of urban and rural locations, accounted
for 36.6% of urban population growth in the 1980s and
33.7% in the 1990s. These figures comport with those
yielded by other studies (United Nations, 2001).
However, the persistent net rural-to-urban population
transfer continues to be the demographic source of
urbanization. Available sources of information (Guzmán et
al, 2006; Cohen, 2006; ECLAC, 2005a; MEASURE DHS
n/d) suggest that natural population growth is still higher in

218

Economic Commission for Latin America and the Caribbean (ECLAC)

rural areas as a result of that population’s greater fertility.
Consequently, in the absence of this net rural emigration,
the region would have become increasingly ruralized in
the last few years. The distinction between the effect of
migration on urban population growth, on the one hand,
and on urbanization, on the other hand, is an important

one. This is especially true in the area of policy-making,
because measures taken to manage urbanization involve
controlling the transfer of population from the countryside
to the city (in particular, on rural emigration), whereas
managing urban expansion entails controlling the natural
growth of the urban population.

Table IV.8
POPULATION AGED 10 AND ABOVE: NET RURAL-TO-URBAN MIGRATION AND URBAN POPULATION GROWTH
Country

Net rural-to-urban
migration
1980-1990

Growth of urban population
aged 10 and above

Relative share of rural-tourban migration in urban
population growth

1990-2000

1980-1990

1 248 867

829 981

4 146 455

3 414 868

30.1

24.3

565 718

341 525

882 210

1 174 625

64.1

29.1

Brazil

9 621 574

9 483 867

22 891 555

26 856 555

42.0

35.3

Chile

146 535

382 623

1 447 011

1 939 951

10.1

19.7

Argentina
Bolivia

Colombia
Costa Rica

1990-2000

1980-1990

1990-2000

-

-

-

-

-

-

82 656

338 002

194 507

717 006

42.5

47.1

Cuba

735 083

370 110

1 525 671

918 531

48.2

40.3

Ecuador

647 934

612 251

1 341 021

1 598 897

48.3

38.3

El Salvador

294 277

-

535 196

-

55.0

-

Guatemala

226 021

824 486

525 724

1 384 850

43.0

59.5

Honduras
Mexico

258 003

303 742

501 918

685 610

51.4

44.3

3 997 266

4 183 486

12 108 257

13 103 802

33.0

31.9

Nicaragua

139 920

-

484 649

-

28.9

-

Panama

113 677

234 038

292 298

432 624

38.9

54.1
45.5

Paraguay
Peru
Dominican Republic
Uruguay
Venezuela (Bol. Rep. of)
Total

280 103

296 914

504 441

652 302

55.5

1 001 406

-

2 990 661

-

33.5

-

218 172

553 575

709 784

1 096 408

30.7

50.5

83 300

34 446

233 238

132 306

35.7

26.0

735 042

847 392

3 171 190

4 235 917

23.2

20.0

20 395 554

19 636 438

54 485 786

58 344 252

37.9

33.7

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of intercensal survival ratios.

Table IV.8 suggests that the situation is highly uneven
among countries, which is to be expected in view of the
different levels of urbanization throughout the region. Not
unexpectedly, the most urbanized countries (Argentina,
Chile, Uruguay and the Bolivarian Republic of Venezuela)
report the lowest proportion of urban population growth
coming from rural emigration, while the highest levels tend
to occur in countries with less urbanization (Guatemala,
Honduras, Costa Rica, the Dominican Republic).
A more thorough analysis of the figures reveals
that there are some exceptions to the latter assertion
(Panama), and drastic changes from one decade to the
other that are difficult to understand (Bolivia). These
exceptions may be findings that warrant additional study,

or they may be anomalies caused by idiosyncrasies or
methodological changes. In other cases, the changes
may reflect foreseeable trends. This is true of Chile,
where the increasing weight of rural emigration in urban
growth and the low rates of natural population growth in
urban areas may mean that small net shifts of population
from the countryside to the city can have a considerable
impact on urban demographic expansion.
From the standpoint of the rural population, the net
transfer of population from the countryside to the city
is not at all insignificant, as can be seen in figure IV.1.
Moreover, in countries like Brazil, rural emigration could
be called a mass exodus because it represents a large share
of the country’s rural population.

Social Panorama of Latin America • 2007

219

Figure IV.1
RATIO BETWEEN NET RURAL-TO-URBAN MIGRATION FROM 1990 TO 2000 AND THE RURAL AND URBAN POPULATION IN 1990
(Percent)
40
35
30
25
20
15
10
5
0

Argentina

Bolivia

Brazil

Chile

Mexico

Country
Rural

Urban

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of intercensal survival ratios.

220

Economic Commission for Latin America and the Caribbean (ECLAC)

G. Internal migration, deconcentration of the city


system and metropolitan reconfiguration

Internal migration flows no longer follow the pattern of concentration observed in previous
decades. Although in most countries the main city still attracts migrants, since the 1990s
the largest cities have seen a migratory turnaround that has made them into net exporters of
population (as people leave for other dynamic parts of the urban system). Internal migration
is therefore leading to the consolidation of a more diverse and less asymmetrical system of
cities, which is more favourable to economic and social development than the urban systems
with populations highly concentrated in the main city that have been so typical of the region’s
countries. In addition, intra-metropolitan migration (usually towards the outskirts of cities)
tends to extend the area covered by large cities, thereby triggering complex processes of
territorial and functional reconfiguration.

It is not possible to analyse migration within minor
administrative divisions in the same manner as it has been
done with migration at the major administrative division
level in this chapter. It is also inadvisable in general terms,
because at that level the variety of different possible types
of migration multiplies. Identifying patterns associated
with territories of origin and destination is complex
enough in the case of major administrative divisions,
and it is even more so for minor administrative divisions.
Nevertheless, the possibility of working at that level is
a notable achievement, since the results have a wide
variety of applications and are of particular interest to
local authorities and analysts, insofar as this is the first
time it has been possible to quantify and characterize
migration at the municipal level.
Using computing tools to process the data for more
precision at this level makes it possible to examine
migration in metropolitan areas comprising one or more
minor administrative divisions. Once again, examining the
migratory patterns of all these areas is beyond the scope
and objectives of this chapter. However, it is possible
to examine selected metropolises. To contribute to the

9

present discussion of migration to cities and at the same
time continue the work on indigenous peoples presented in
the Social Panorama of Latin America 2006, this section
examines the hypothesis of “concentrated deconcentration”
in the three most populous cities of 10 countries that
included a question on ethnic identity in the 2000 round
of censuses. “Nearby migration” represents exchanges
with municipalities outside the metropolitan area but
within the same major administrative division. “Distant
migration” represents exchanges with municipalities
outside the major administrative division in which the
metropolis is located.
Tables IV.9A and IV.9B show, by way of example,
the particular case of the metropolitan area of La Paz-El
Alto (Bolivia).9 This analysis demonstrates that within
the same area there may be very different territorial and
ethnic migration patterns. With respect to territory, the
first distinction to be drawn is between the two parts of the
metropolitan area; whereas La Paz has lost nearly 41,000
inhabitants due to migration, El Alto has gained just over
46,000. Thus, the net positive migration of about 5,000
individuals conceals two contrasting patterns: attraction

Official definitions in Bolivia are rigorous; the two places are considered different cities even though they appear in every way to be a single
urban conglomerate. For this reason, in table IV.9A the city is shown with its two separate components, but a “total” column is included that
sums up the situation of the conglomerate as a whole.

Social Panorama of Latin America • 2007

221

Table IV.9
BOLIVIA: POPULATION AGED FIVE AND ABOVE (INDIGENOUS AND NON-INDIGENOUS)

(a) Matrix of recent migration from the La Paz-El Alto metropolitan area, 1996-2001
Residence five years ago

Habitual
residence

Ethnicity

Ciudad
El Alto

La Paz

Rest of the
department

Total

Rest of the
country

Indigenous

11 622

421 349

3 091

10 103

260 227

637 447

5 404

17 000

21 725

681 576

13 593
3 616
17 209

382 526
89 805
472 331

28 948
3 552
32 500

7 824
2 266
10 090

432 891
99 239
532 130

Indigenous

14 940

3 956

671 450

5 874

696 220

3 025

478

63 694

2 047

69 244

Total

17 965

4 434

735 144

7 921

765 464

Indigenous
Non-indigenous
Total

28 283
21 474
49 757

2 912
1 013
3 925

8 754
3 298
12 052

2 638 474
2 102 922
4 741 396

2 678 423
2 128 707
4 807 130

Indigenous

448 783

393 245

723 061

2 663 794

4 228 883

Non-indigenous

273 595

92 849

73 635

2 117 338

2 557 417

Total

722 378

486 094

796 696

4 781 132

6 786 300

Non-indigenous

Rest of the country

Total

13 909

1 553

Indigenous
Non-indigenous
Total

Rest of the
department

3 851

245 480

Total
Ciudad El Alto

391 967

Non-indigenous

La Paz

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of special processing of census
microdatabases

(b) Results derived from matrix of recent migration from the metropolitan area
La Paz-El Alto, 1996-2001
Indigenous

Non-indigenous

17 760

42 541

42 857

4 644

7 168

6 643

22 404

49 709

49 500

Distant

11 622

7 824

19 446

10 103

2 266

12 369

21 725

10 090

31 815

Total

29 382

50 365

62 303

14 747

9 434

19 012

44 129

59 799

81 315

Nearby
Emigrants

El Alto

Nearby
Immigrants

Total

La Paz

El Alto

Total

La Paz

Total

La Paz

El Alto

Total

28 533

7 807

18 896

6 641

2 031

3 503

35 174

9 838

22 399

Distant

28 283

2 912

31 195

21 474

1 013

22 487

49 757

3 925

53 682

Total

56 816

10 719

50 091

28 115

3 044

25 990

84 931

13 763

76 081

Nearby

-10 773

34 734

23 961

-1 997

5 137

3 140

-12 770

39 871

27 101

Distant

-16 661

4 912

-11 749

-11 371

1 253

-10 118

-28 032

6 165

-21 867

Total

Net migration

-27 434

39 646

12 212

-13 368

6 390

-6 978

-40 802

46 036

5 234

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of table IV.9a.

within the immediate region, that is, from other cantons
in the province of La Paz, and loss with respect to other
provinces in the country, particularly Santa Cruz. In other
words, migration in Bolivia reflects an actual deconcentration
and not a concentrated deconcentration, insofar as the
most populous city is seeing a significant flow of migrants
towards distant cities that are more socioeconomically
and demographically dynamic. Finally, the distinctions
are also a function of ethnicity; although the La Paz-El

10

Alto metropolitan area is attractive to indigenous people,
it is seeing a net emigration of non-indigenous people
(see table IV.9A).
If the regional situation is examined, taking into
consideration the 10 countries that have the necessary
information (see table IV.10), the following conclusions
can be reached:10
• The majority of cities continue to have net
immigration, which reveals how strong the attraction

These results, as tends to be the case in analyses of cities, depend fundamentally on where the metropolitan area’s borders are set. In this study,
we have followed the territorial-administrative specification proposed in the Spatial Distribution and Urbanization in Latin America and the
Caribbean (DEPUALC) of CELADE (CELADE, n/d), as indicated in the table, since it breaks down the data to the appropriate municipal level
for the study at hand.

222

Economic Commission for Latin America and the Caribbean (ECLAC)

still is to this upper echelon of the region’s urban
systems; and even in the majority of countries,
particularly the smallest or least urbanized (Bolivia,
Ecuador, Honduras, Panama, Paraguay, Ecuador),
the most populous city still attracts migrants. This
shows that the areas that have historically had the
most concentrated populations remain robust.
• However, one in three cities experienced net
emigration, which suggests a gradual spreading
of this trend —non-existent in the region until the
late 1980s— among the principal cities of these
countries. Considering the experience of developed
countries, this pattern could expand in the future
(Gans, 2007; Montgomery, 2004).
• The largest cities (especially those with 4 million or
more inhabitants) are the most likely to experience
net emigration, which could be linked to the
effects of saturation, diseconomies of scale and the
agglomeration that a variety of recent publications
on urban dynamics have highlighted (UNFPA,
2007; Montgomery, 2004; Henderson, 2000).
This situation does not mean that immigration to
these cities has ceased, since the inflows are still
considerable; rather, it is due to a marked increase
in emigration that may be to the surrounding region.
If so, it could be misinterpreted as expulsion,
when in fact it is a manifestation of metropolitan
expansion, as the concentrated deconcentration
hypothesis suggests. For this reason, it is necessary
to break down the migration figures and look at
flows to the surrounding region as well as those
to the rest of the country.
• When net migration from the cities to surrounding
areas is contrasted with that going to the rest of
the country, only Brazil seems to be experiencing

concentrated deconcentration. Net emigration from
São Paulo and Rio de Janeiro is due exclusively to
exchanges with other municipalities within the same
state, whereas both metropolises continue to gain
population in migratory exchanges with the other
states. In the other countries, expulsion cities are
seeing net emigration at both levels or just to the rest
of the country, which means that the deconcentration
is real and not apparent. It should be noted that
in several cities that are still areas of attraction,
a pattern of migratory exchange consistent with
the concentrated deconcentration hypothesis can
be seen, probably due to ongoing suburbanization
processes. This is the case in Guatemala City, Quito,
San Pedro Sula and Heredia.
• Generally, both indigenous and non-indigenous
populations have the same migration patterns,
which suggests that in most cases whether
cities attract or expel migrants is not a matter of
ethnicity. There are several exceptions, however:
In addition to the previously mentioned case of
La Paz, Cochabamba, Tegucigalpa, Mexico City,
Guadalajara and Asuncion fall into this exceptional
category. The Bolivian and Mexican cities are
noteworthy not only because of the weight of
the indigenous population in both countries, but
also because these are all cities that are losing
their non-indigenous populations while gaining
indigenous inhabitants. This obviously increases
the weight of indigenous populations in these
cities, but perhaps more important is the fact that
indigenous people are coming to cities that are
no longer attractive to the non-indigenous. The
reasons for this phenomenon and its implications
should be studied further.

Social Panorama of Latin America • 2007

223

Table IV.10
LATIN AMERICA (SELECTED COUNTRIES): INTERNAL MIGRATION INDICATORS FOR THREE MAIN METROPOLITAN AREAS, 1990 AND 2000
CENSUS ROUNDS
Indigenous

Country
and year

Metropolitan
area a

Bolivia,
2001

La Paz

12 212

Santa Cruz

24 279
752

2.9

23 961

-11 749

-6 978

-3.8

3 140

-10 118

5 234

27 101

-21 867

17.9

-338

24 617

21 532

7.0

2 110

19 422

45 811

1 772

44 039

0.6

-1 159

1 911

-2 528

-3.0

-1 242

-1 286

-1 776

-2 401

625

-164

-1.1

-747

583

-231 657

-2.9

-339 707

108 050

-231 821

-340 454

108 633

Río de Janeiro

435

3.1

-175

610

-29 854

-0.6

-49 505

19 651

-29 419

-49 681

20 262

311

4.3

89

222

61 886

3.4

42 691

19 195

62 197

42 780

Chile,
2002

19 417

-411

-0.5

-947

536

-49 306

-2.1

-30 945

-18 361

-49 717

-31 892

-17 825

231

5.4

24

207

8 927

2.5

1 361

7 566

9 158

1 385

7 773

-387

-5.4

-46

-341

-7 438

-2.5

711

-8 149

-7 825

665

-8 490

São Paulo

Santiago
Valparaíso
Concepción

Costa
Rica,
2000

Net
migration

Rate
Net
(per
nearby
1 000) migration

Total

Net
distant
migration

Belo Horizonte

Brazil,
2000

Rate
(per
1 000)

Non-indigenous

Net
nearby
migration

Cochabamba

Net
migration

Net
distant
migration

Net
migration

Net
Net
nearby
distant
migration migration

-78

-2.6

-13

-65

-13 849

-2.8

229

-14 078

-13 927

216

-14 143

Heredia

6

2.1

5

1

4 442

5.4

-2 265

6 707

4 448

-2 260

6 708

Cartago

28

36.8

8

20

2 874

3.9

644

2 230

2 902

652

2 250

Quito

5 005

28.6

-592

5 597

18 198

3.0

-29 157

47 355

23 203

-29 749

52 952

Guayaquil

3 068

23.9

31

3 037

41 068

4.3

11 609

29 459

44 136

11 640

32 496

714

49.1

147

567

11 322

9.4

2 968

8 354

12 036

3 115

8 921

Guatemala, Guatemala
2002
City

10 666

14.4

-3 028

13 694

489

0.1

-28 459

28 948

11 155

-31 487

42 642

Quetzalten

1 007

3.8

681

326

98

0.4

216

-118

1 105

897

208

-152

-6.7

-9

-143

-2 556

-5.2

-561

-1 995

-2 708

-570

-2 138

-219

-12.7

-32

-187

11 671

3.2

1 218

10 453

11 452

1 186

10 266

181

3.7

-42

223

6 708

3.1

-11 439

18 147

6 889

-11 481

18 370

258

6.7

-10

268

1 089

2.1

203

886

1 347

193

1 154

1 137

1.7

1 226

-89

-72 063

-1.0

17 596

-89 659

-70 926

18 822

-89 748

Ecuador,
2001

San José

Cuenca

Escuintla

Honduras, Tegucigalpa
2001
San Pedro Sula
La Ceiba

Mexico,
2000

Mexico City

1.1

-46

87

-14 719

-1.0

-8 256

-6 463

-14 678

-8 302

-6 376

1 965

52.9

-2

1 967

40 656

3.0

-148

40 804

42 621

-150

42 771

Panama City

8 101

67.7

161

7 940

74 220

14.5

5 979

68 241

82 321

6 140

76 181

Colón

270

17.3

8

262

1 499

2.1

2 105

-606

1 769

2 113

-344

David

Panama,
2000

41

Monterrey

651

62.2

287

364

266

0.5

5 402

-5 136

917

5 689

-4 772

-219

-12.7

-32

-187

11 671

3.2

1 218

10 453

11 452

1 186

10 266

88

200.0

11

77

-2 257

-2.4

-1 861

-396

-2 169

-1 850

-319

4

20.0

-2

6

-3 592

-8.7

-1 213

-2 379

-3 588

-1 215

-2 373

Guadalajara

Paraguay, Asunción
2002
Ciudad del Este
Encarnación

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of special processing of census
microdatabases
aFor a definition of metropolitan area on the basis of Spatial distribution and urbanization in Latin America and the Caribbean (DEPUALC) data [on line],
see www.eclac.cl.celade/depualc/.
bPopulation aged five and above, residents of the country five years before the census, with valid responses on questions about habitual place of
residence and place of residence five years ago.

224

Economic Commission for Latin America and the Caribbean (ECLAC)

H. Migration and individual characteristics
Migrants tend to consist mostly of young people, women and people with above-average levels
of education. Indeed, the stereotype of the unskilled internal migrant more representative
of the period when rural-to-urban flows were the main form of migration no longer applies,
even to groups located in mainly rural areas (such as indigenous communities). As is to
be expected from the fact that many of them move for work, migrants show higher levels
of labour participation, although they also have higher levels of unemployment in some
countries. This shows that settling in at destination is not an easy process.

1.

Selectivity

Three “individual” characteristics of internal migration that
have been well documented in the literature (Rodríguez,
2004a; Welti, 1998; Villa, 1991) are analysed below:
sex, education and age. To capture this information, the
proportion of males in the population, the proportion of
residents without any education and those with a university
education, and the percentage of young people among
migrants must be determined in each case. Using the
criteria applied in the chapter on population in Social
Panorama of Latin America 2006, the distinction between
indigenous and non-indigenous is introduced into the
analysis (see table IV.11).
The gender-based analysis of migration reveals
that the expected female selectivity cannot be verified
systematically, since in some countries the proportion of
males among migrants —with respect to both major and
minor administrative divisions— is smaller than that of
non-migrants, whereas in other countries it is greater. This
irregularity is seen in both indigenous and non-indigenous
populations. However, the finding is consistent with the
conclusion reached by Rodríguez (2004a) that the female
predominance among internal migrants has declined.
Moreover, in the case of indigenous migrants, female
selectivity in internal migration seems to be the exception
rather than the rule. These results should be viewed with
caution, because they may be a product of combinations

of different migratory currents, each with its own gender
selectivity. For example, consider the contrast between the
rural-to-urban flows (with a high female selectivity) and
flows towards frontier regions (with a high male selectivity)
that has been observed since this issue was first studied
(Cardona and Simmons, 1975).
The pattern that emerges with respect to education
is consistent with prevailing theories and previous
studies (Rodríguez, 2004a). In all countries analysed,
the proportion of individuals with university studies
among indigenous migrants is greater than among nonmigrant indigenous people, and in the same fashion, the
percentage of individuals with no education is smaller
among the former than among the latter. In some countries,
the differences are quite marked. For example, in Brazil
13.6% of indigenous persons migrating between major
administrative divisions have no education, and that figure
rises to 30.9% among non-migrant indigenous persons.
This pattern is also repeated systematically (with a couple
of exceptions) among non-indigenous individuals, leading
to the conclusion that educational selectivity is not affected
by ethnicity. In indigenous settlement areas —which are
generally rural areas with net emigration— this regularity
means there is a risk of losing human resources, since
those who emigrate tend to be more educated than those
who remain (or those migrating in).

Social Panorama of Latin America • 2007

225

Table IV.11
MIGRANTS BETWEEN MAJOR ADMINISTRATIVE DIVISIONS (MAD) AND MINOR ADMINISTRATIVE DIVISIONS (MIAD),
SELECTED CHARACTERISTICS ACCORDING TO ETHNICITY, 2000 CENSUS ROUND
Country and year

Recent between MADs

Higher education

Percentage of males

Indigenous
migrant

Nonindigenous
migrant

Nonmigrant
indigenous

Recent between MIADs
Non-migrant
nonindigenous

Indigenous
migrant

Nonindigenous
migrant

Nonmigrant
indigenous

Non-migrant
nonindigenous

Bolivia 2001

94.8

97.3

94.0

95.7

96.0

98.1

93.9

Brazil, 2000

92.0

97.4

98.6

95.9

…

…

…

95.6
…

Chile, 2002

105.4

109.0

100.9

94.4

98.6

101.4

101.7

94.1

Costa Rica, 2000

112.9

104.8

106.7

98.9

111.1

102.1

106.7

98.9

Guatemala, 2002

107.6

90.8

94.9

93.7

100.5

91.7

94.9

93.7

Mexico, 2000

97.2

94.5

99.3

93.9

97.6

91.9

99.3

94.0

Bolivia 2001

16.4

13.2

12.0

8.4

13.7

11.3

12.1

8.4

Brazil, 2000

3.7

6.7

1.8

5.5

…

…

…

…

Chile, 2002

14.6

29.2

8.8

17.7

14.2

28.1

8.2

16.5

5.3

12.3

2.6

10.1

4.9

13.1

2.5

9.9

1.6

6.3

0.7

5.6

1.2

9.0

0.7

5.4

Mexico, 2000

4.2

13.4

2.2

8.8

5.9

14.5

2.1

8.6

Bolivia 2001
No education

Costa Rica, 2000
Guatemala, 2002

7.5

9.1

10.9

15.3

8.1

9.7

11.0

15.5

Brazil, 2000

13.6

12.6

30.9

15.1

…

…

…

…

Chile, 2002

6.6

5.1

10.5

6.7

6.7

5.4

10.9

6.8

17.3

10.5

28.4

9.9

17.7

10.2

28.8

9.9

36.3

17.0

43.4

20.2

43.2

15.6

43.2

20.5

Mexico, 2000

19.1

9.4

26.3

11.9

19.2

9.4

26.4

12.0

Bolivia 2001
Young people

Costa Rica, 2000
Guatemala, 2002

46.6

46.3

33.9

30.2

46.0

45.2

33.4

29.6

Brazil, 2000

45.5

42.9

25.3

31.5

…

…

…

…

Chile, 2002

45.1

38.9

26.4

25.4

40.0

34.2

25.3

24.6

Costa Rica, 2000

41.5

37.2

30.8

29.0

39.8

36.0

30.5

28.7

Guatemala, 2002

47.4

44.8

33.5

33.2

40.7

39.7

33.4

33.1

Mexico, 2000

51.0

43.3

30.8

32.1

47.5

41.7

30.5

31.8

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of special processing of
census microdatabases.

With respect to age, it is also clear that indigenous
people cannot escape the strong correlation between the
life cycle and migration. Indeed, whereas the proportion
of young people among indigenous migrants at the level
of major administrative divisions is consistently above
40% and even reaches 50% in some cases, it is less than
35% among non-migrant indigenous people, and as low
as 25% in some cases.11 It should be pointed out that
this behaviour is not exclusive to indigenous migrants,
as non-indigenous migrants also include a much higher
percentage of young people than non-migrant nonindigenous groups. In general, however, the differences
in the proportion of young people among migrants
and non-migrants are greater in the case of indigenous

11

individuals, which suggests that age selectivity is more
intense in this group.
This analysis leads to the general conclusion that the
main selection factors for migration are the same now as they
were in the past, although gender selectivity is declining.
In addition, it can be stated that there is no strong evidence
of a double spike in migration probability (once during
youth and again after retirement), as is typically seen in
developed countries (Gans, 2007; Raymer and Rogers,
2007). Some very peculiar and noteworthy migration
patterns among older adults have been seen in countries
like Chile, however (Rodríguez and González, 2006). And
finally, education continues to be a factor contributing
to, or at least associated with, migration.

Measured as the percentage of persons aged 15 to 29 years in the total population aged 5 and over (the population aged 0 to 4 years is excluded
from the analysis of recent migration by definition).

226

Economic Commission for Latin America and the Caribbean (ECLAC)

2.

Integration in place of destination

A variety of individual or family characteristics tend
to be seen as heavily influenced by migration. Because
census data do not indicate what migrants’ situation was
before they left, the effect of migration can be measured
by comparing averages of relevant indicators in the
places of origin and destination. In this document, the
only indicator compared is the workforce integration
of migrants and non-migrants at the destination. Only
recent migration between major administrative divisions
is taken into consideration, because it is more in line with
a known conceptual model —labour migration— than
with hypotheses specific to the workforce integration
of migrants, as stated in the frame of reference section.
To control for exogenous factors (which stem from the

selectivity examined in the previous section), migration
indicators were standardized by age and education level.
This makes it possible to estimate the level that the indicators
used (workforce participation and unemployment) would
have if migrants had the same age and education structure
as non-migrants.
In the first place, it can be seen that in almost all
of the countries (the exception is Bolivia in 1992),
the rate of workforce participation among migrants
is higher than that of non-migrants, and in most cases
the difference is greater than three percentage points.
This corresponds with the prevailing opinion that
migration is undertaken for the purpose of seeking
work (see table IV.12).

Table IV.12
LATIN AMERICA: STANDARDIZATION OF WORKFORCE PARTICIPATION RATE AMONG RECENT MIGRANTS BETWEEN MAJOR
ADMINISTRATIVE DIVISIONS (MAD), SELECTED COUNTRIES, 1990 AND 2000 CENSUS ROUNDS
Country

Census

Nonmigrant

Migrant

Standardization

Difference 1:
Non-migrants
- migrants

Difference 2:
Non-migrants
- standardized
migrants

Difference 3:
Standardized
migrants migrants
-4.8

Argentina

2001

58.16

64.09

59.27

-5.93

-1.1

Bolivia

1992

62.86

61.64

62.02

1.23

0.8

0.4

Bolivia

2001

59.18

62.87

61.73

-3.70

-2.6

-1.1

Brazil

1991

58.86

65.94

62.44

-7.08

-3.6

-3.5

Brasil

2000

63.27

68.00

63.69

-4.73

-0.4

-4.3

Chile

1992

48.77

55.07

51.45

-6.30

-2.7

-3.6

Chile

2002

51.19

55.54

52.09

-4.35

-0.9

-3.5

Costa Rica

1984

51.20

53.55

51.78

-2.35

-0.6

-1.8

Costa Rica

2000

51.50

56.70

53.83

-5.20

-2.3

-2.9

Ecuador

1990

54.32

61.29

60.53

-6.97

-6.2

-0.8

Ecuador

2001

54.15

60.04

58.74

-5.89

-4.6

-1.3

Guatemala

1994

49.64

52.48

51.95

-2.84

-2.3

-0.5

Guatemala

2002

49.37

59.17

57.67

-9.80

-8.3

-1.5

Honduras

1988

55.07

56.87

57.88

-1.80

-2.8

1.0

Honduras

2001

50.62

53.08

52.80

-2.47

-2.2

-0.3

Mexico

1990

47.68

54.08

51.38

-6.40

-3.7

-2.7

Mexico

2000

54.71

61.77

58.64

-7.06

-3.9

-3.1

Nicaragua

1995

57.79

60.23

60.41

-2.44

-2.6

0.2

Nicaragua

2005

52.67

55.03

55.00

-2.36

-2.3

0.0

Panama

1990

54.79

58.28

57.22

-3.49

-2.4

-1.1

Panama

2000

59.33

66.64

63.80

-7.31

-4.5

-2.8

Paraguay

1992

55.04

61.01

59.22

-5.97

-4.2

-1.8

Paraguay

2002

59.57

66.10

64.72

-6.52

-5.2

-1.4

Venezuela
(Bol. Rep. of)

2001

54.51

58.94

56.97

-4.43

-2.5

-2.0

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of special processing of
census microdatabases.

Social Panorama of Latin America • 2007

227

Nonetheless, due to the interaction between migratory
selectivity and the propensity to work, this finding must
be refined using standardization. Thus, it is noted that
if migrants had the same age structure and educational
background as non-migrants, their workforce participation
rate would be lower than that reported (with the exception
of Bolivia in 1992, Honduras in 1988 and Nicaragua in
1995 and 2005). This confirms that the age structure of
migrants “extrinsically” favours their participation in
the workforce. Even after controlling for these extrinsic
factors with standardization, however, migrants’ workforce
participation remains higher than that of non-migrants
in all countries (except for Bolivia in 1992), which

reinforces the argument for the employment motivations
for migration.
The unemployment situation, in contrast, is less
consistent; the results vary by country and by census year
(see table IV.13). In the first place, only 7 of the 24 cases
studied show lower unemployment for migrants than
for non-migrants. Although this may seem to contradict
the previous finding and the focus on migration for
employment reasons, in fact it does not. When non-contract
migration is examined, it is seen that migrants go through
a process of looking for work and adapting to the place
of destination, which leads to a greater probability of
being unemployed.

Table IV.13
LATIN AMERICA: STANDARDIZATION OF MIGRANT UNEMPLOYMENT RATE,
SELECTED COUNTRIES, 1990 AND 2000 CENSUS ROUNDS
Country

Census

Non-migrant

Migrant

Standardization

Difference 1:
Non-migrants
- migrants

Difference 2:
Non-migrants
- migrants,
standardized

Difference 3:
Standardized
migrants migrants

Argentina

2001

28.49

24.41

26.45

4.08

2.0

2.0

Bolivia

1992

2.47

3.67

3.56

-1.20

-1.1

-0.1

Bolivia

2001

4.37

4.99

5.18

-0.62

-0.8

0.2

Brazil

1991

5.00

5.09

5.01

-0.08

0.0

-0.1

Brazil

2000

14.88

17.36

16.78

-2.48

-1.9

-0.6

Chile

1992

8.40

8.04

7.92

0.36

0.5

-0.1

Chile

2002

13.90

14.21

14.54

-0.31

-0.6

0.3

Costa Rica

1984

6.57

6.66

7.12

-0.09

-0.5

0.5

Costa Rica

2000

4.40

4.76

4.85

-0.36

-0.4

0.1

Ecuador

1990

2.68

2.93

2.81

-0.26

-0.1

-0.1

Ecuador

2001

2.71

2.94

2.95

-0.24

-0.2

0.0

Guatemala

1994

0.66

0.73

0.67

-0.07

0.0

-0.1

Guatemala

2002

0.86

0.79

0.77

0.07

0.1

0.0

Honduras

1988

8.02

7.39

7.46

0.63

0.6

0.1
-0.1

Honduras

2001

2.00

2.81

2.67

-0.81

-0.7

Mexico

1990

2.65

2.37

2.38

0.28

0.3

0.0

Mexico

2000

1.27

1.50

1.48

-0.23

-0.2

0.0
-0.1

Nicaragua

1995

17.51

14.56

14.50

2.95

3.0

Nicaragua

2005

4.15

4.45

4.43

-0.30

-0.3

0.0

Panama

1990

11.51

13.02

11.67

-1.52

-0.2

-1.3

Panama

2000

12.95

11.63

11.03

1.32

1.9

-0.6

Paraguay

1992

1.90

2.45

2.31

-0.55

-0.4

-0.1

Paraguay

2002

5.44

6.33

5.96

-0.89

-0.5

-0.4

Venezuela
(Bol. Rep. of)

2001

8.83

9.97

9.85

-1.14

-1.0

-0.1

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of special processing of
census microdatabases.

Unlike workforce participation, the standardized
unemployment rate of migrants does not change
much compared to the non-standardized rate, and
most importantly, the change is not systematic. In
10 of 24 cases the unemployment rate increases with

standardization. This is reflected in the absence of a
regular pattern —after controlling for extrinsic factors
of age and education level— although more often
than not the standardized rate for migrants is higher
than that for non-migrants. This suggests a period of

228

Economic Commission for Latin America and the Caribbean (ECLAC)

adaptation or bias in the labour market in the place
of destination that works against migrants, because
despite their greater propensity and need to participate
in economic activity, they are not more likely to be
employed than non-migrants.
In short, although employment continues to be the
predominant motivation for migrating between major
administrative divisions, migration does not guarantee

3.

Migration histories

It is generally difficult to examine migration histories
because that requires several questions aimed at
reconstructing previous migration paths, and the census
questions capture only one movement. Moreover,
it is assumed that there was a direct migration. The
articulation of these questions does, however, allow for
an approximation of the notion of “migration history”.
Indeed, by combining the questions about habitual
place of residence, birthplace and place of residence
five years before the census, it is possible to generate
the following typology: (i) non-migrant: a person whose
habitual place of residence, place of residence five years
ago, and birthplace are the same; (ii) former migrant:
a person whose habitual place of residence is the same
as the place of residence five years ago, but whose
birthplace is different; (iii)  recent migrant: a person
whose habitual place of residence is different from the
place of residence five years ago, and the latter is the
same as the birthplace; (iv) return migrant: a person for
whom the habitual place of residence is the same as the
birthplace but different from place of residence five years
ago; and (v) multiple migrant: a person whose habitual
place of residence, place of residence five years ago,
and birthplace are different.12
Below is a synthesis of this typology, combined
once again with the ethnic variable (see table IV.14),
which provides added value because there is very little

12

employment, and this introduces a factor of uncertainty and
risk for migrants. There is also a concern for developing
public and social policies, which must address the adaptation
process of internal migrants who do not find employment.
Given that these migrants may lack the network of contacts
and knowledge that are necessary to lead a normal life in
the place of destination, specific support might be required
to reduce the time it takes them to find a job.

empirical data on the migration histories of indigenous
people (Del Popolo et al, 2007; ECLAC, 2007a). To
capture the most information about migration and
pinpoint the nature of returns, the typology corresponds to
migration at the level of minor administrative divisions.
The principal findings are the following:
• In all countries, the proportion of migrants (all
types combined) is greater in the non-indigenous
population, which supports the hypothesis that
indigenous people have a greater territorial
fixation, associated with their attachment to the
land and the link between place, identity and
ethnic community. A recent study (Del Popolo et
al, 2007), confirms this finding, which persists
in the majority of countries even when there are
controls for the age and education composition of
indigenous and non-indigenous groups.
• Return migration is the least frequent phenomenon
in nearly every country, both among indigenous
and non-indigenous populations. This is significant
because it calls into question the hypothesis of a
massive return of indigenous migrants, which is
prevalent in the literature.
• Multiple migrants comprise a minority, suggesting
that individuals who have left their birthplace are
not very likely to migrate again (at least in the five
years preceding the census).

Operationalized in REDATAM by Rodríguez (2004a), following the proposal of Villa (1991).

Social Panorama of Latin America • 2007

229

Table IV.14
MIGRATION TYPOLOGY COMBINING LIFETIME AND RECENT MIGRATION AT THE LEVEL OF MINOR
ADMINISTRATIVE DIVISION (MIAD), ACCORDING TO ETHNICITY
Country and year

Bolivia, 2001
Chile, 2002
Costa Rica, 2000
Ecuador, 2001
Guatemala, 2002
Mexico, 2000
Honduras, 2000
Panama, 2000
Paraguay, 2002

Ethnicity

Former direct
migrants

Recent direct
migrants

Multiple
migrants

Return
migrants

Non-migrants

Total

Indigenous

19.9

5.4

2.2

1.7

70.7

100

Non-indigenous

21.7

5.3

2.3

2.0

68.7

100

Indigenous

31.8

6.3

7.2

2.3

52.4

100

Non-indigenous

38.0

5.9

8.0

2.0

46.0

100

Indigenous

16.0

3.5

2.5

1.1

76.8

100

Non-indigenous

28.7

4.5

4.3

1.5

61.0

100

Indigenous

14.5

4.3

1.5

0.7

79.0

100

Non-indigenous

28.0

4.7

3.1

1.1

63.1

100

8.9

2.5

0.9

2.2

85.5

100

Indigenous
Non-indigenous
Indigenous
Non-indigenous

21.9

4.2

2.2

1.5

70.2

100

6.3

1.8

0.4

0.7

90.9

100

17.3

2.7

0.9

1.0

78.2

100

9.5

2.0

0.6

0.5

87.3

100

Non-indigenous

21.4

3.8

1.6

0.8

72.4

100

Indigenous

15.4

9.6

1.8

0.3

72.9

100

Non-indigenous

25.2

9.4

2.4

0.8

62.2

100

Indigenous

17.4

3.8

1.7

1.7

75.5

100

Non-indigenous

28.6

5.5

4.4

1.6

59.8

100

Indigenous

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of special processing of
census microdatabases.

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Economic Commission for Latin America and the Caribbean (ECLAC)

I. Policy orientations
It is the duty of the State to guarantee the right to internal migration in the best possible
conditions. It is also the responsibility of States to tackle the territorial discriminations that
prompt outflows of population from disadvantaged areas. Any intervention aimed at either
restricting migration or pressuring people into moving would be inadmissible, since this
would be incompatible with each person’s right to freely decide when and where to move
within the country. A wide range of instruments is available to influence people’s migratory
decisions. The choice of which to use depends on various factors, including the type of
migration in question.

1.

Principles

To migrate is to exercise a human right, specifically the
right to freely move about within the national territory,
recognized in the Universal Declaration of Human Rights.
Therefore, the primary role of public policies in this realm
is to guarantee the exercise of this right under the best
possible conditions (of information, for example), and to
prevent discrimination against those who exercise it.
Although at first glance one might consider that this
approach “promotes” migration —in line with a rather
liberal political tradition prevailing in the United States
(ILPES, 2007)— in fact it does not. The right that must
be guaranteed includes the possibility of not migrating,
that is, not being forced to move because of expulsive
pressures generated by “territorial discrimination” (Diaz,
2007). Although policies cannot prevent expulsion factors
altogether, they can work to ensure that the pressure
does not infringe or undermine rights simply because of
people’s location. Policies can also combat the emergence

13

of territorial poverty traps and the erosion of the territorial
aspects of social cohesion.13
Public interest in migration does not just stem from
States’ obligation to guarantee the free exercise of human
rights or the legitimate concern for territorial equity and
for breaking cycles of poverty and population expulsion.
Because migration is a decisive factor in the ways countries
make use of their geography, and because these uses
are relevant to national authorities and stakeholders for
different reasons (economic, environmental, political,
military, and others), migratory currents —an aggregate
of myriad individual movements— require the attention
of decision makers. In other words, authorities and
other national stakeholders may have an interest in and
a need to intervene in these flows to promote changes
in population distribution patterns to make them more
compatible or functional within the country’s development
strategy or model.

These assertions are consistent with the ideas expressed recently by ILPES concerning development and regional equity (ILPES, 2007).

Social Panorama of Latin America • 2007

2.

231

History

The objective of harmonizing the image that a society
projects with the manner in which the population occupies
the territory is nothing new in the region. In fact, as
early as the era of the original civilizations, and more
recently, between 1930 and 1980, this approach could be
observed in public efforts to promote the development of
the region through a wide range of interventions (ILPES,
2007; CELADE, 1984). After a period of questioning
and a dearth of resources in the 1980s, the past 15 years
have seen renewed interventions with respect to internal
migration.
This is due to a combination of factors. One is the
strategic impetus provided by the decentralization processes
begun in the 1980s, in which subnational authorities
expanded their functions and resources, and hence
their importance. In this new scenario, there is a greater
diversity of key players whose interests are affected by
migratory flows, and the number of possible interventions
has expanded. The most recent ILPES document on
the subject asserts that “rather than a regional policy in
keeping with the formula employed in the 20th century,
a family of territorial policies [italicized in the original]
should be implemented. These would include not only
decentralization/federalism, but also local development
and territorial competitiveness, land management and
the regionalization of both comprehensive policies (on
the environment, poverty, science and technology) and
sectoral ones (on stimulating production and developing
businesses)” (ILPES, 2007, pp. 105-106).
To be sure, it is not that local and regional governments
have begun implementing specific internal migration
programmes. What is different is that local and regional
development processes are increasingly seen as the
responsibility of these same communities and governments,
whose proposals and efforts send specific signals —of
attraction or rejection— to potential migrants.
Due to asymmetries of power and resources among
the different subnational entities, this new scenario
may lead to widening territorial gaps. As has already
been demonstrated in this chapter, internal migration
can contribute to this widening of territorial disparities,
which is why programmes for the territorial redistribution
of resources and selective public investments by the
central government are needed to offset these initial
asymmetries, even if only partially. In this regard, the
increasingly important role of local stakeholders does
not at all mean that national stakeholders are irrelevant.
Furthermore, the possibility of competition between

subnational entities opens the doors to the formation of
alliances and joint efforts by weaker territories, which
should also be promoted and perhaps coordinated with
central support (ILPES, 2007).
Another important factor is the evaluation of the
results of prior interventions. At least two major types of
intervention failed in the past: colonization programmes
and policies to promote the retention of the rural population.
The former involved high financial costs, had adverse
environmental impacts, were difficult to sustain over time,
and were questioned on the grounds of human rights (both
those of the colonists and those of the native population in
colonized territories). Although some initiatives of this type
still exist, they are very limited and are governed by much
stricter human rights and environmental criteria.
On the other hand, all measures and programmes
aimed at retaining the rural population seem to have
been futile. In fact, the events of the last 20 years tend
to support an assertion that was frequently heard in the
middle of the last century: although the modernization of
the countryside can greatly increase farm productivity, it is
difficult to increase the retention of rural inhabitants. What
is more, agricultural modernization may serve to expel
the rural population and attract more skilled individuals
from cities or temporary workers —also primarily urban
in many countries— for labour-intensive activities. For
all of the above reasons, a recent study concludes that
attempts to stop migration from the countryside to the
city are futile (UNFPA, 2007).
This conclusion does not reflect a lack of concern for
the rural population, which should be given special attention
in light of their inferior socioeconomic conditions. On the
contrary, it demonstrates that even when living conditions
in the countryside are improved there is no guarantee that
the population will stay, since such improvements raise
expectations for a better life, and in fact the city offers
many more possibilities for success.
Experience shows, on the other hand, that some
trends thought to be inexorable —such as the growing
concentration of population in the principal city— have
fallen off, largely due to a shift in the direction of
migratory flows. Although this would appear to point to
the effectiveness of the numerous policies, programmes
and measures implemented since the 1960s to bring about
population deconcentration, that is a much-debated issue
and there are few suitable methodologies for arriving at
solid conclusions (UNFPA, 2007; Rodríguez, 2004a). In
any case, the fatalism of the 1980s has given way to a

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Economic Commission for Latin America and the Caribbean (ECLAC)

renewed confidence in the possibility of affecting internal
migratory flows and the feasibility of influencing tendencies
that were previously considered immutable.
A third consideration is the fact that decision makers
have gradually become more familiar with the new scenario
in terms of the distribution and movements of the region’s
population, arising out of the diversity and complexity of

3.

flows and the gradual shift from rural-to-urban migration
towards flows between and within cities. In a region where
three in four people live in urban areas and one in three
live in a city of more than 1 million inhabitants (Guzmán et
al, 2006), there is no doubt that these movements involve
the largest numbers of people and will probably become
increasingly predominant in the future.

Contemporary situation, strategies and challenges

The diversity of current internal migration increases the
range of policies, programmes and measures available to
deal with the issue. This situation also calls for greater
knowledge, precision and judgement among policymakers,
who must choose how to intervene based on the type of
migration they are attempting to influence. Any such
strategy should always adhere to the principle of combining
the exercise of the right to migrate within a country in
the best possible conditions, on the one hand, with the
struggle against territorial discrimination that leads to
poverty traps, on the other.
The four pillars of strategies for internal migration are:
incentives for individuals and companies, geographical
allocation of infrastructure and public services, use of
instruments of territorial land-use planning and economic
regeneration, and knowledge and management of the
unforeseen migratory effects of various social policies.
Highly illustrative examples of the above are urban
regeneration and resettlement programmes in central
areas. To attract immigrants into city centres, decisionmakers and technical experts have at their disposal a
huge repertoire of economic (subsidies), social (service
location) and administrative instruments (amendment of
land-use regulations). There is, however, a negative side
to this advantage, as these instruments were not designed
to influence intra-metropolitan migration, but to organize
the city and optimize its functioning (and these remain
high-priority strategic objectives). Therefore, if the
migratory forces are very strong, using these instruments to
counteract them may generate imbalances that eventually
result in costs for the city and its inhabitants (rising land
prices, overcrowding, congestion, urban sprawl, residential
segregation, etc.). As is often the case, having policy
instruments is one thing, implementing them with no
negative side-effects quite another.

While specific policies to halt advancing urbanization
or rural-to-urban migration have proved unsuccessful
(not to mention ill-advised and plain wrong according
to many experts (UNFPA, 2007)), many countries
would nonetheless like to redirect migratory flows
between cities. According to recent studies (ILPES,
2007; UNFPA, 2007; Cohen, 2006; Guzmán et al.,
2007; Davis and Henderson, 2003), the authorities
of countries that consider the population to be overly
concentrated in the main city perceive a solid, dense and
diversified urban network as being conducive to national
development. However, as mentioned previously, there
is an ongoing debate on the effectiveness of programmes
implemented to reduce such concentration. The natural
idea of promoting some cities to the detriment (if only
by omission) of others must pass several tests: to be of
benefit to national development, to be consistent with
or at least not contradict (national and global) marketbased economic buoyancy, to be acceptable to all local
stakeholders, and to respect individual rights. There are
clearly many sources of limitations on the discretionary
nature of public action in this domain.
Lastly, it is worth highlighting those public
policies that are formulated without consideration for
the mobility of the population. These include housing
and transport policies, which have direct and often
mechanical consequences on changes of residence
(particularly within cities or between cities and their
surrounding areas). These effects must be taken into
account when formulating such policies. Going one
step further, they could even be devised to have a
certain impact on migration and mobility, obviously
without neglecting their natural objectives of providing
good-quality connections and living environments for
the population.

Social Panorama of Latin America • 2007

233

Annex
Map IV.1
SOUTH AMERICA (SELECTED COUNTRIES): MAJOR ADMINISTRATIVE DIVISION BY MIGRATORY STATUS
(CENSUS ROUNDS 1990 AND 2000)

kilometers

National borders
Major divisions of net in-migration
Major administrative divisions on the decline
(changing from net in-migration to net outmigration)

Major divisions of net out-migration
Major administrative divisions on the rise
(changing from outmigration to net in-migration)
Major administrative divisions with no information available

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of reviewing census cards and
the database on Internal Migration in Latin America and the Caribbean (MIALC) [online database] http://www.eclac.cl/migracion/migracion_interna/ and
information provided by the countries.
Note: The boundaries and names shown on this map do not imply official endorsement or acceptance by the United Nations.

234

Economic Commission for Latin America and the Caribbean (ECLAC)

Map IV.2
CENTRAL AMERICA AND THE CARIBBEAN (SELECTED COUNTRIES): MAJOR ADMINISTRATIVE DIVISION BY MIGRATORY STATUS
(CENSUS ROUNDS 1990 AND 2000)

kilometers

National borders
Major administrative divisions of attraction
Declining major administrative divisions
(from net inmigration to net outmigration)

kilometers

Major administrative divisions of displacement
Rising major administrative divisions
(from net emigration to net inmigration)
Major administrative divisions with no information available

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, on the basis of reviewing census cards and
the database on Internal Migration in Latin America and the Caribbean (MIALC) [online database] http://www.eclac.cl/migracion/migracion_interna/ and
information provided by the countries.
Note: The boundaries and names shown on this map do not imply official endorsement or acceptance by the United Nations.

Social Panorama of Latin America • 2007

235

Chapter V

Social agenda
Public policies and health
programmes for indigenous peoples
in Latin America

Introduction
The emergence of an organized indigenous movement
and a human rights framework for public policy has led
to the recognition of indigenous peoples as holders of
collective rights.
The rights-based approach - as a coherent system
of principles and guidelines applicable to development
policies - establishes frameworks for defining the content
and orientation of such policies, as well as influencing
policymaking and policy implementation. Certain cultural
practices and political and legal frameworks that facilitate
or promote discrimination against given individuals or
groups (women, indigenous peoples or other ethnic groups)
have been found to act as social exclusion mechanisms by
causing or contributing to poverty (Abramovich, 2006,
p.37). Behind the supposedly universal treatment for
indigenous peoples, pre-existing inequalities have been
shown to be reproduced and expressed in marginalization,
exclusion and, in the case of health, in more precarious
conditions due to difficulties of access and the low quality
and inappropriateness of health services. There is therefore
an urgent need to incorporate the right-based approach for

1

indigenous peoples into health programmes and policies,
as well as to mainstream the dimension and make more
decisive progress towards ratifying international instruments
and developing legislation on indigenous peoples, as befits
their status as holders of collective rights.
In the light of the above, this chapter continues the
analysis of health programmes and policies in Latin
America that was started in the Social Panorama of
Latin America 2005 and the study of the new and diverse
realities of indigenous peoples in the Social Panorama of
Latin America 2006. The assessment of public policies
and health programmes targeting indigenous peoples in
Latin America is based on information provided by 16
countries in response to a survey sent out by ECLAC on
the subject. Other relevant inputs included the results
of the Workshop-Seminar “Indigenous people in Latin
America: health policies and programmes, what progress
has been made?”, held at the ECLAC headquarters on 25
and 26 June 2007. Both the assessment and the seminar
were held as part of a project funded by the Government
of France.1 Annex V.1 includes a list of countries and

A joint project by the Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC and the Government of
France: Project on Advances in Policies and Programmes for Indigenous Peoples of Latin America since the Implementation of the International
Decade for Indigenous Peoples (FRA/06/02).

236

institutions that replied to the survey and questionnaire sent
out. The Pan American Health Organization (PAHO) also
provided supplementary information from the assessment
carried out in 2004 as part of the International Decade of
the World’s Indigenous People (1995-2004).
The first section deals with the minimum standards
in terms of indigenous peoples’ rights and stresses that,
despite advances made in terms of legislation, public
policy nonetheless needs to tackle the challenge of moving
forward with the enforcement of the agreements concerned.
Indeed, there is an ongoing structural inequity that, in the
sphere of health, is reflected in less favourable morbidity
and mortality indicators for indigenous peoples. They also
have less access to health care and the care provided is
not culturally appropriate. In addition, indigenous peoples
have low levels of participation and representation in the
policies and programmes that affect them.
The second section acknowledges that health
sector reforms, combined with progress in terms of
legislation, foster conditions that are more conducive
to the incorporation of health programmes and policies

Economic Commission for Latin America and the Caribbean (ECLAC)

targeting indigenous peoples. Most countries have
therefore implemented measures in this regard, although
the situations vary considerably throughout the region.
These differing situations are then described, along
with the main achievements to date and challenges that
remain pending. The following two key aspects are
identified: indigenous participation and management in
health programmes and policies; and the availability of
information needed to design, implement and assess any
measures introduced.
The information presented is then used as a basis
for some guidelines and recommendations aimed at
improving health programmes and policies targeting
indigenous peoples and at moving forward with enforcing
their rights.
Lastly, the international social agenda provides details
of meetings and agreements on social matters within
the framework of the United Nations system, and more
specifically the tenth session of the Regional Conference
on Women in Latin America and the Caribbean, held in
Quito, Ecuador, from 6 to 9 August 2007.

Social Panorama of Latin America • 2007

237

A. Indigenous peoples and the right to health:
juridical advances and public policy implications

In Latin America, the emergence of indigenous peoples’ movements as political actors (in
democracies more conducive to the creation of pluricultural States) has resulted in progress
in terms of the recognition of their rights. International human rights instruments can be used
as a basis for a set of minimum health standards: the right to the highest level of physical
and mental health by means of appropriate, quality and non-discriminatory access; the right
to integral indigenous health, including the use, strengthening and control of traditional
medicine and the protection of territories as life spaces; and the right to participate in the
design, implementation, management, administration and assessment of health programmes
and policies, with the emphasis on the autonomy of resources. These standards generate new
State obligations in terms of legislation and public policy. Although only the constitutions
of Ecuador, Mexico and the Bolivarian Republic of Venezuela recognize the collective
health rights of indigenous peoples, some progress has been made in this area of legislation
in most countries. Despite this, there remains a gap between the official recognition of the
health rights of indigenous peoples and the effective enforcement of those rights. The
indigenous population therefore has a less favourable epidemiological profile than the
non-indigenous population.

The emergence of indigenous peoples as political actors
and their rights agenda are not exclusive to Latin America,
but rather part of a worldwide process under way since the
end of the Cold War and just one of a range of struggles
for human rights in a globalized and multicultural world
(ECLAC, 2007a). In this sense, the active participation
of indigenous organizations has resulted in a consensus
concerning two elements of human rights doctrine: (i) the
need for a special guarantee to protect generally applicable
fundamental freedoms and rights, and (ii) the recognition
and positivization of specific collective rights, leading to
the establishment of standards of rights for indigenous
peoples. In other words, this represents the equal enjoyment
of human rights and the simultaneous right to constitute

different collectives (ECLAC, 2007a). In this context, the
last 20 years have seen Latin American States gradually
recognize the rights of indigenous peoples within their
national legislations and constitutions.
A minimum standard for the rights of indigenous
peoples is enshrined in the Convention Concerning
Indigenous and Tribal Peoples in Independent Countries
of the International Labour Organization (ILO Convention
No. 169) approved in 1989 and in the United Nations
Declaration on the Rights of Indigenous Peoples, which was
approved by the General Assembly on 20 September 2007.
Article No. 3 of the Declaration states that: “Indigenous
peoples have the right of self– determination. By virtue
of that right they freely determine their political status

238

Economic Commission for Latin America and the Caribbean (ECLAC)

and freely pursue their economic, social and cultural
development” (United Nations, 2007c), and a set of
specific collective rights are recognized for indigenous
peoples on the basis of this jus cogens principle of human
rights (ECLAC, 2007a).2
The rights-based approach to public policy now
provides a conceptual framework that is accepted by the

1.


Health rights of indigenous peoples:
minimum standards and main dimensions

Human rights have resulted in a body of juridical rules
(international declarations, conventions and treaties) aimed
at promoting and protecting those rights. The following
international instruments make explicit mention of the
right to health: the Universal Declaration of Human Rights
of 1948, the International Covenant on Economic, Social
and Cultural Rights of 1966 (ICESCR) and the Additional
Protocol to the American Convention on Human Rights in
the Area of Economic, Social and Cultural Rights (Protocol
of San Salvador) that entered into force in 1999.3 Article
12 of the International Covenant on Economic, Social and
Cultural Rights (ICESCR) stipulates the right of everyone
to the enjoyment of the highest attainable standard of
physical and mental health and that the States Parties
shall take steps to achieve the full realization of this right.
Article 10 of the Protocol of San Salvador includes a series
of measures relating to primary care, coverage, extension
of the benefits of health services to all individuals subject
to the State’s jurisdiction, immunization, prevention and
treatment of disease, health education and satisfaction of
the health needs of the most vulnerable groups. This right
is also enshrined by WHO in the World Health Declaration
adopted by the World Health Assembly in 1998, which

2

3

international community as one that guides the process of
formulating, implementing and assessing policies. It also
serves as a guide for international cooperation, both in
terms of the obligations of donor governments and those
of recipient governments, and also to define the level of
participation and the local and international mechanisms
for monitoring and accountability (Abramovich, 2006).

describes health as a state of complete physical, mental
and social well-being and not merely the absence of
illness or infirmity.
These instruments form the foundation for designing
public policies aimed at ensuring that indigenous peoples
exercise their right to health as citizens. Given the new
sociopolitical context, the major challenge for health policies
is to recognize, promote, protect and guarantee health care
in keeping with the concepts and practices of the healthillness-healing process of indigenous peoples, to the extent
that this constitutes a specific collective right.
In this sense, it is vital for policies and programmes to
integrate the concept of indigenous health that transcends
the internationally accepted definition of the World Health
Organization (WHO) to holistically incorporate elements
of spirituality, collectivity and the close bond with the
ecosystem. For instance, the concept of kümelkalen (wellbeing) of the Mapuche in Chile, whereby individuals
are in balance with themselves and with their peers and
families (their “nearest and dearest”), as well as being
in equilibrium with their lof or own territorial unit, their
social, cultural, political, environmental, territorial,
religious and cosmic environment (Quidel, 2001). In this

In addition, the International Convention on the Elimination of All Forms of Racial Discrimination (1965), ratified by all countries in Latin
America, commits States to prohibiting and bringing racial discrimination to an end and guaranteeing rights to public health, medical care,
social security and social services without discrimination of race, colour or national or ethnic origin. The Convention on Biological Diversity
(1992), in article 8 (j), states that Parties shall, “subject to its national legislation, respect, preserve and maintain knowledge, innovations and
practices of indigenous and local communities embodying traditional lifestyles relevant for the conservation and sustainable use of biological
diversity and promote their wider application with the approval and involvement of the holders of such knowledge, innovations and practices
and encourage the equitable sharing of the benefits arising from the utilization of such knowledge, innovations and practices”.
The International Covenant on Economic, Social and Cultural Rights of 1966 (ICESCR) has been ratified by the following countries: Argentina,
the Bolivarian Republic of Venezuela, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Guyana, Honduras, Jamaica, Panama, Peru and
Uruguay. The following countries acceded to the Covenant: Barbados, Bolivia, Brazil, Dominica, Dominican Republic, Grenada, Mexico,
Nicaragua, Paraguay, Suriname and Trinidad and Tobago. The Protocol of San Salvador was ratified by: Argentina, Bolivia, Costa Rica, El
Salvador, Ecuador, Guatemala, Mexico, Panama, Paraguay, Peru and Uruguay, and acceded to by Brazil, Colombia and Suriname.

Social Panorama of Latin America • 2007

239

way, kutran, or illness, is a result of transgressing the ad
mapu or order that governs the universe.
The exercise by indigenous peoples of their right to
health is linked to the exercise of other rights, hence the
importance of controlling their territories and maintaining
their ecosystems. In this regard, the Special Rapporteur on
the situation of human rights and fundamental freedoms
of indigenous people points out that extractive activities,
cash crops and unsustainable consumer patterns have
generated climate change, widespread pollution and
environmental degradation. These phenomena have had a
particularly serious impact on indigenous peoples, whose
way of life is closely linked to their traditional relationship
with their lands and natural resources, and has become a
new form of forced eviction of indigenous peoples from
their ancestral territories, while increasing the levels of
poverty and disease. His most recent report presented to
the Human Rights Council states that “although sundry
governments have adopted social policies with the aim

of “closing the gap” as regards the disparities in human
development indicators between indigenous and nonindigenous peoples, the results have thus far been meagre”
(United Nations, 2007b).
The Special Rapporteur on the right of everyone to the
enjoyment of the highest attainable standard of physical
and mental health carried out missions to Latin American
countries and found situations in which indigenous peoples’
health rights had been threatened as a result of the invasion of
their territories and inequitable access to goods and services
of the State (including cultural ones) (United Nations,
2005c). His report included a series of recommendations
emphasizing, inter alia, the participation of indigenous
groups in policies and programmes and in the production
of information aimed at indigenous communities.
Notwithstanding the recognition of the interdependent
and indivisible nature of human rights, box V.1 gives details
of the articles referring to the health rights of indigenous
peoples within the various international instruments.

Box V.1
THE RIGHT TO HEALTH OF INDIGENOUS PEOPLES IN VARIOUS INTERNATIONAL INSTRUMENTS

Article 7 (2) of Convention No. 169 of
the International Labour Organization
(ILO) stipulates that: “The improvement
of the conditions of life and work and
levels of health and education of the
peoples concerned, with their participation
and co-operation, shall be a matter of
priority in plans for the overall economic
development of areas they inhabit. Special
projects for development of the areas in
question shall also be so designed as to
promote such improvement.”
There is also a special section given
over to social security and health (part
V). Article 24 states that “Social security
schemes shall be extended progressively to
cover the peoples concerned, and applied
without discrimination against them”, while
article 25 specifies “Governments shall
ensure that adequate health services are
made available to the peoples concerned,
or shall provide them with resources to allow
them to design and deliver such services
under their own responsibility and control,
so that they may enjoy the highest attainable
standard of physical and mental health;
health services shall, to the extent possible,
be community-based. These services shall

be planned and administered in co-operation
with the peoples concerned and take
into account their economic, geographic,
social and cultural conditions as well as
their traditional preventive care, healing
practices and medicines; the health care
system shall give preference to the training
and employment of local community health
workers, and focus on primary health care
while maintaining strong links with other
levels of health care services; the provision
of such health services shall be co-ordinated
with other social, economic and cultural
measures in the country.” According to article
30 “Governments shall adopt measures
appropriate to the traditions and cultures
of the peoples concerned, to make known
to them their rights and duties, especially in
regard to labour, economic opportunities,
education and health matters, social welfare
and their rights deriving from this Convention.
If necessary, this shall be done by means
of written translations and through the use
of mass communications in the languages
of these peoples.”
In 1989, the Organization of American
States (OAS) asked the Inter-American
Commission on Human Rights (IACHR)

to draft a legal instrument on the rights
of indigenous peoples. The Commission
gathered comments from governments,
indigenous organizations, intergovernmental
organizations and experts and, in 1997,
approved the draft American Declaration
on the Rights of Indigenous Peoples, which
is still in the process of being reviewed
and approved by the General Assembly
of OAS. Article XII on health and wellbeing states that “Indigenous peoples
have the right to legal recognition and
practice of their traditional medicine,
treatment, pharmacology, health practices
and promotion, including preventive and
rehabilitative practices; indigenous peoples
have the right to the protection of vital
medicinal plants, animal and mineral in their
traditional territories; indigenous peoples
shall be entitled to use, maintain, develop
and manage their own health services,
and they shall also have access, on an
equal basis, to all health institutions and
services and medical care accessible to
the general population; the states shall
provide the necessary means to enable
the indigenous peoples to eliminate such
health conditions in their communities

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Economic Commission for Latin America and the Caribbean (ECLAC)

Box V.1 (concluded)
which fall below international accepted
standards for the general population.”
The United Nations Declaration on
the Rights of Indigenous Peoples refers
to economic, social and cultural rights,
including the right to health, and article 23
establishes that “Indigenous peoples have
the right to determine and develop priorities
and strategies for exercising their right to
development. In particular, indigenous

peoples have the right to be actively involved
in developing and determining health,
housing and other economic and social
programmes affecting them and, as far as
possible, to administer such programmes
through their own institutions. According
to article 24 “Indigenous peoples have the
right to their traditional medicines and to
maintain their health practices, including
the conservation of their vital medicinal

plants, animals and minerals. Indigenous
individuals also have the right to access,
without any discrimination, to all social
and health services; indigenous individuals
have an equal right to the enjoyment of
the highest attainable standard of physical
and mental health. States shall take the
necessary steps with a view to achieving
progressively the full realization of this
right.”

Source: Economic Commission for Latin America and the Caribbean (ECLAC).

It is possible to identify specific rights in the area
of health related to each of the five dimensions of the

minimum standard for indigenous peoples’ rights (ECLAC,
2007a) (see table V.1).

Table V.1
Specific rights in the area of health related to each of the five dimensions of the minimum standard for
indigenous peoples’ rights

Five dimensions of the minimum standard
for indigenous peoples’ rights

Specific rights in the area of health

Right to non-discrimination

Right to access health care

Right to social development and well-being

Right to highest attainable level of physical and mental
health by means of adequate and quality access

Right to cultural integrity

Right to use an indigenous language; right to apply the
concept of integral health and well-being; right to the use,
strengthening and control of traditional medicine

Right of ownership, use, control and access
of land, territories and resources

Right to conserve plants, animals, minerals and territorial spaces
of vital interest for the health-illness-healing process

Right of political participation

Right to participate in the design, responsibility and social
control (resources) of health programmes and policies

The PAHO Initiative on the Health of the Indigenous
Peoples of the Americas (SAPIA) sets out the following
principles: (i) the need for a holistic approach to health
and the right to self–determination; (ii) respect for and
revitalization of indigenous cultures; (iii) reciprocity in
relations; and (iv) the right to systematic participation by
indigenous peoples.
As for traditional medicine, in recent years WHO
has been defining its role and remit through strategies for
policies, safety, effectiveness, quality, access and rational
use of traditional, complementary and alternative medicine
(Pedrero, 2003). WHO proposes to: (i) integrate this type
of medicine into national health systems through the
development and implementation of national programmes
and policies; (ii) promote the safety, effectiveness and quality
of this type of medicine by applying quality standards and
rules; (iii) increase the availability and accessibility of
this type of medicine, especially for poor people; and (iv)

therapeutically promote the appropriate use of relevant
traditional medicine by suppliers and consumers.
The public policy challenge currently facing States is
to tackle the unfavourable health situation of indigenous
peoples and the structural inequity they suffer by adopting
a rights-based approach that takes account of the standard
for indigenous peoples’ rights, which can be defined
as follows: (i) they are peoples’ rights, in other words
they are attributes of social entities that go beyond
individuals and collectivities; (ii) they are made up of
political and development rights, as the two kinds are
mutually dependent; and (iii) they exist independently
of their recognition on the part of the State (Castañeda,
2006). The new obligations of the State can therefore be
categorized as follows: obligations to respect, protect,
guarantee and promote the right in question (Abramovich,
2006), by establishing mechanisms for the enforcement
and assessment of compliance with that right.

Social Panorama of Latin America • 2007

2.


Constitutional framework and legislation
concerning the health of indigenous peoples

The emergence of indigenous movements as active political
actors and their demands for a new type of relationship
with the State, as well as the return to democracy in Latin
American countries, combined to generate a trend toward
multicultural constitutionalism (Van Cott, 2000). The
constitutional reforms initiated in the 1990s recognize
the pluriethnic and pluricultural nature of States. Most of
the region’s countries incorporated the collective rights
of indigenous peoples into these reforms (to a lesser or
greater extent) (Barié, 2003). These rights usually refer to
the ownership, protection and use of territories (and in some
cases to forms of social and political organization), and
to the recognition and protection of the use of indigenous
languages. According to the detailed analysis carried
out by Barié (2003), the most advanced constitutions in
the recognition and guarantee of the collective rights of
indigenous peoples are (in this order) Ecuador, Colombia,
the Bolivarian Republic of Venezuela and Paraguay.
Constitutional reforms tend to give international human
rights law the same status as the Constitution, or in some cases
rank it above the Constitution.4 This status of international
law at the national level determines its effectiveness and
its supremacy over domestic legislation when the relevant
courts are asked to protect human rights.
Constitutional advances have gone hand in hand with
the development of specific legislation, although the picture
is far from uniform at the regional level. According to the
Indigenous Legislation Index, constructed by IDB, the
Bolivarian Republic of Venezuela, Bolivia and Colombia
have the maximum scores (between 70% and 80%), while

4

5

241

Chile, El Salvador, Guatemala, Honduras and Uruguay score
below 50% (IDB, 2006). Practically all Latin American
constitutions recognize the right to health as part of the
social rights established by States. However, only three
countries (the Bolivarian Republic of Venezuela, Ecuador
and Mexico) explicitly acknowledge the right to health
of indigenous peoples as separate collectivities, with the
Ecuadoran Constitution being the most far-reaching in
terms of recognition, respect, promotion and guarantee of
the use of traditional medicine, knowledge systems and
protection of sacred elements and places.5
The most significant advances have been in terms
of national legislation, particularly in the last 10 years.
Out of the 16 countries examined, the following 13 have
some sort of specific legislation on health and indigenous
peoples (or population): Argentina, the Bolivarian Republic
of Venezuela, Bolivia, Brazil, Chile, Colombia, Costa Rica,
Ecuador, Guatemala, Mexico, Nicaragua, Panama and Peru.
This is mainly due to the health demands of indigenous
peoples in terms of the accessibility, equity, suitability and
comprehensiveness of culturally relevant health benefits
(Cavieres, 2006). However, this legislation is not enough
to guarantee a real exercise of health rights by indigenous
peoples, as situations range from a recognition of the
right to health as an individual good or the classification
of indigenous peoples as priority groups, to legislation
that recognizes and promotes collective rights (traditional
medicine, participation and autonomy).
These differences in legislation can be seen in more detail
in the IDB database on indigenous legislation (IDB, 2006),

According to Henderson (2004), there are four models for the integration of international law in domestic legislation: (i) the supraconstitutional
model, in which international human rights law can modify the Constitution (Bolivarian Republic of Venezuela, Guatemala, Honduras); (ii) the
constitutional model, in which international human rights law is at the same level as the Constitution (Argentina, Brazil); (iii) the supralegal
model, in which international human rights law is above national laws but cannot amend the Constitution (Colombia, El Salvador, Ecuador,
Paraguay); and (iv) the legal model, in which human rights treaties have the same status as national law (United States, Uruguay).
Although the Constitutions of Guatemala and Nicaragua do not explicitly mention indigenous peoples, the former refers to communities (which
can be interpreted as indigenous communities), while the latter refers to vulnerable sectors of society, which could include ethnic communities
(Castañeda, 2006). As for the Constitution of Ecuador (1998), article 44 stipulates that the State shall recognize, respect and promote the
development of traditional and alternative medicine, while article 84 establishes that a series of collective rights of indigenous peoples shall
be recognized and guaranteed, including their systems, knowledge and practice of traditional medicine, including the right to the protection
of ritualistic and sacred places, plants, animals, mineral and ecosystems of vital interest from that perspective. In the Constitution of Mexico
(2001), article 2 states that the authorities must ensure effective access to health services by expanding coverage of the national system,
making proper use of traditional medicine and supporting indigenous nutrition through food programmes, especially those targeting children.
The Constitution of the Bolivarian Republic of Venezuela declares that indigenous peoples have the right to integral health that takes account
of their practices and cultures, and that the State shall recognize their traditional medicine and complementary therapies, subject to bioethical
principles (article 122, 2001).

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Economic Commission for Latin America and the Caribbean (ECLAC)

which includes some aspects of the minimum standard of
indigenous health rights, such as free and preferential access,
traditional practices, protection of medicinal plants, health care
in accordance with their customs, indigenous participation
in the management and promotion of the health system and
autonomy in the management of health resources. In terms
of the regionwide picture (see table V.2), Bolivia is the only
country to have legislated on all dimensions of the standard,
while the Bolivarian Republic of Venezuela, Colombia and
Ecuador have done so on five out of six dimensions, and
they have also ratified ILO Convention No. 169, thereby
making its provisions binding. It is no coincidence that these
are the countries where national indigenous organizations
have long been gaining strength.6 At the other extreme,
Chile, El Salvador and Paraguay have practically no specific
legislation in this area, although Paraguay has ratified ILO
Convention No. 169.
Generally speaking, this legislation guarantees access
to health care for indigenous groups (see table V.2), which
ties in with the way in which health-sector reforms over the
last 20 years have sought to ensure basic universal coverage,
with the emphasis on quality care (ECLAC, 2006a). In
Bolivia in recent years, a series of laws and decrees have
been adopted to provide indigenous peoples with basic
health benefits, such as basic indigenous and native health
insurance (2002) and universal mother and child insurance
(SUMI) (2002), with article 8 of the corresponding regulations
stating the importance of ensuring that health care is in
keeping with the practices and customs of indigenous
peoples (see annex V.2). Similarly, in Colombia decree
1.811 of 1990 guarantees free health care for indigenous
communities, along with institutional adaptation and the
relevant human resources training, in a context of respect
for indigenous culture (see annex V.2).
Significant progress has been made in the recognition of
traditional indigenous medicine. As mentioned previously,
this is one of the dimensions of the collective right to
health that, along with the individual right of access,
forms the basis for intercultural dialogue (Cunningham,
2002). By the late 1990s, Bolivia was about the only
country to have made moves towards legislating in this
area, although now most countries in the region have laws
that recognize traditional health practices (see table V.2
and annex V.2). In Bolivia, ministerial resolution 0231 of
1987 establishes regulations for the practice of traditional

6

indigenous medicine; in Peru, the 1997 General Health
Act recognizes traditional indigenous medicine and a
Supreme Decree in 2003 established the National Health
Institute, which includes an Intercultural Health Centre
(CENSI) to promote, inter alia, a new appreciation of
this form of medicine. The law on indigenous peoples
and communities adopted by the Bolivarian Republic
of Venezuela in 2005 recognizes the use of traditional
indigenous medicine and therapeutic practices for
protection, development, prevention and recovery in terms
of integral health. The law also considers the incorporation
of traditional indigenous medicine and the therapeutic
practices of indigenous peoples and communities into
the services of the national health system, as well as the
relevant training of human resources. This shows that the
content of such specific legislation varies enormously:
the law in Argentina merely stipulates compliance with
the guidelines of the World Health Organization (WHO)
in terms of traditional indigenous medicine (law 23.302,
1985), while Colombia’s considerable legislation on
this matter recognizes the use and practice of traditional
medicines, calls for it to be promoted and has resulted in
regulations in this regard (IDB, 2006).
It should be pointed out that the right of indigenous
peoples to use their own medicine and to maintain and
strengthen their health practices is closely linked to
intellectual property rights. The safeguarding of traditional
medicine and each of its components (traditional indigenous
healers, traditional knowledge and natural resources) is
one of the basic demands of indigenous peoples in terms of
their intellectual rights (WHO, 2002; Huenchuán, 2004).
This is a key issue worthy of attention that goes beyond the
scope of this chapter. What should, however, be mentioned
is that the demands for a specific protection status have not
been fully met, and there are two viewpoints on the issue.
From the point of view of public health rights, traditional
medicine can be used as an input for pharmaceutical
research, but also as a source of effective treatment in
its own right. This interest is therefore based on how to
best use the potential of traditional medicine to provide
feasible treatments. From the perspective of indigenous
peoples’ intellectual property rights, traditional medicine
(as other aspects of their heritage) must be protected and
therefore requires a specific system for the protection,
control and self-management of the collective property

At present, 12 of the 16 countries examined have a national or regional organization that brings together grass-root associations and the various
indigenous peoples of the country or region. Some of the first national organizations include the Colombian National Indigenous Organization
(ONIC, 1982); the Confederation of Indigenous Nationalities of Ecuador (CONAIE, 1986); and the National Council of Venezuelan Indians
(CONIVE, 1989). Long-standing regional organization include the Confederation of Indigenous People of Bolivia) (CIDOB, 1982) and the
Confederation of the Nationalities Indigenous to the Ecuadorian Amazon (CONFENIAE).

Social Panorama of Latin America • 2007

243

Table V.2
LATIN AMERICA (16 COUNTRIES): SPECIAL LEGISLATION ON THE HEALTH OF INDIGENOUS PEOPLES
Countries

Free and
preferential
access

Traditional
practices

Protection of
medicinal plants

Health care in
keeping with
customs

Indigenous
Autonomy in the
participation in management of
the management health resources
and promotion of
the health system

ILO Convention No. 169 ratified
Argentina b

X

X

a

X

X

Bolivia

X

X

X

X

X

X

Brazil

X

X

a

X

X

---

Colombia

X

X

a

X

X

X

X

a

Xc

a

a

Costa Rica

---

Ecuador

X

X

X

a

X

X

Guatemala

X

X

a

a

a

---

Honduras

a

a

a

a

a

---

Mexico b

X

X

X

a

a

---

Paraguay

a

a

a

a

a

---

Peru

X

X

X

a

X

---

Venezuela (Bol. Rep. of) b

X

X

a

X

X

Not ratified

X
---

Chile

X

---

---

X

El Salvador

---

---

---

---

Nicaragua

X

Xc

---

Xc

Xc

X

X

Xc

X

Xc

X

Panama

X

---

-----

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Inter–American Development Bank (IDB), “Databank on
Indigenous Legislation” [online] 2004, http://www.iadb.org/sds/ind/site_3152_s.htm.
aIn application of the ILO Convention concerning Indigenous and Tribal Peoples in Independent Countries (ILO Convention No. 169).
bSome provinces and states have additional legislation.
cOnly in indigenous territories (reserve, autonomous regions, comarcas).

associated with that heritage. In other words, the aim is
to make advances in protecting traditional knowledge
relating to medicine by means of sui generis systems of
rights or other ways of protecting indigenous intellectual
rights, indigenous territories and their biological diversity,
as well as preserving indigenous cultural reproduction
systems that underlie their healing knowledge, practices
and innovations.
Tentative legislative progress is being made in terms
of participation and autonomy in health matters, which
should be part of every stage from policy and programme
design to the administration and management of resources
within a rights-based approach. The legislation of Argentina,
the Bolivarian Republic of Venezuela Bolivia, Brazil,
Colombia, Costa Rica and Peru promotes indigenous
participation in health matters (see table V.2 and annex
V.2).7 This participation is promoted by the creation of
indigenous institutions, such as the Council for Indigenous
Participation of the National Institute for Indigenous
Affairs (INAI) in Argentina (resolutions 2004 and 2006),
or the National Health Council of Indigenous Peoples

7

(CONASPI) in Costa Rica (2006). In Argentina, the aim
of the Council for Indigenous Participation is to create a
new space for dialogue and participation for the various
representatives of the country’s indigenous peoples. In
Costa Rica, the function of the National Health Council
of Indigenous Peoples is to advise the Ministry of Health
on the formulation of public health policy strategies for
indigenous peoples. In Colombia, law 691 and decree
1.416 promote and regulate the participation of ethnic
groups in the general social security system and other
health service providers. The Bolivarian Republic of
Venezuela, Bolivia, Colombia and Ecuador all have
legislation on the autonomy of health resources, while the
laws of Nicaragua and Panama make explicit reference to
autonomous regions and comarcas, respectively.
To date, there have been different levels of progress
made in the recognition of indigenous peoples’ rights in
international law and the constitutions and legislations of
Latin American countries. Behind these changes, however,
the situation is critical: there is a lack of compliance with
the rules in force and the rights of indigenous peoples

In Mexico, some specific legislation exists in individual states, such as the health act of the state of Chiapas.

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Economic Commission for Latin America and the Caribbean (ECLAC)

continue to be violated (Stavenhagen, 2002). A document
by the United Nations (2006b) pointed out that differences
in implementation of the rules were attributable to the
legislative formalities themselves, in the membership of
legislatures, in the scant representation and participation
of indigenous people in legislative work, in the lack of
consultation of indigenous peoples and in the biases

3.


and prejudices against indigenous rights. The problem
is not only one of legislating on indigenous issues, but
also of doing so with the indigenous people themselves.
It is relevant that there are no adequate mechanisms for
monitoring the effectiveness of indigenous legislation and
assessing its application in the day-to-day practice of public
administration and daily society (Castañeda, 2006).

Public institutions relating to
indigenous peoples and health

The indigenous movement, along with the strengthening
of the juridical framework, has created and opened
institutional spaces (Stavenhagen, 2004) that have in
turn encouraged the setting up of government institutions
responsible for indigenous matters. A regional overview
shows that these institutions conceal different realities
in at least two dimensions: the level of political
participation of indigenous peoples and the institutional
status achieved within the hierarchy. In the Bolivarian
Republic of Venezuela, the institution responsible for
indigenous matters has ministerial status (Ministry for
Indigenous Affairs) (see annex 3). Such institutions are
also attached to various departments, although most are
linked to a ministry. Some such institutions function as
decentralized public agencies and a few have operational,
technical, budgetary and administrative autonomy, such
as the Council for the Development of the Nationalities
and Peoples of Ecuador (CODENPE) or the National
Commission for the Development of Indigenous Peoples
(CDI) in Mexico.
The aim of these institutions is to support and strengthen
the integral development of indigenous peoples and promote
their rights. One of their main functions is coordination
between various sectors (including ministries of health),
indigenous organizations and international cooperation.
These institutions have evolved from a welfare stance
(in which indigenous people were the subject of public
policies) towards a recognition of indigenous peoples as
holders of collective rights. Nonetheless, in practice the

situation is delicate, partly because a lack of political,
economic and administrative support means that most
institutions have a limited capacity to make a real impact
on the various public sectors (Fund for the Development
of the Indigenous Peoples of Latin America and the
Caribbean, 2004).
These institutions have also expanded into health. In
14 of the 16 countries examined, the ministry of health
includes a body responsible for the health of indigenous
peoples (the two exceptions are El Salvador and Paraguay).
The status of such bodies varies, and this impacts their
scope of action. They range from indigenous health
programmes that have no institutional status but that
influence other ministerial programmes (as in Argentina
and Honduras), to an Office of the Under-Secretary of
Traditional Medicine and Interculturalism in Bolivia
(2006), which aims to promote a new appreciation of
traditional medicine intercultural health programmes (see
annex 3). The Bolivarian Republic of Venezuela, Ecuador
and Mexico have national departments of indigenous
health including traditional medicine, Panama has a
technical secretariat on the same level, while Brazil
and Chile have units responsible for indigenous health
(see annex 3). One of the main problems faced by such
institutions is the instability resulting from changes of
political regime, which depends largely on the legal
status of each institution (whether it is governed by
decisions of the executive, parliament, judiciary or
public administration).

Social Panorama of Latin America • 2007

245

B. Health programmes and policies for
 indigenous peoples: how much and
 in what way has progress been made?
Health sector reforms geared towards the equity, efficiency and quality of health services
are conducive to furthering the application of indigenous health rights, with priority given
to the active participation of the communities themselves. Countries fall into four groups
when it comes to indigenous health policies: a large number of countries have a national
indigenous peoples’ plan; a second group has begun the process to devise and implement
such a policy; a third group has an explicitly intercultural approach as part of their national
health policies; and finally there are those countries that have no specific policies for
indigenous peoples. An overview of such programmes shows a heterogeneous supply
with two main trends: programmes specially designed to improve the health of indigenous
peoples (particularly those that concentrate on specific aspects such as traditional medicine
and human resources training); and regular programmes that are part of strategic or policy
lines within health systems. Some of the achievements to date include the consolidation of
differentiated health models and the improvement of the health conditions of indigenous
peoples. There are also limitations, however, including the scarce availability of trained human
resources, low levels of financing and a lack of continuity in the allocation of resources.
Some programmes have successfully incorporated the participation of indigenous peoples
in these processes, while other programmes need to make more progress in this area. The
widespread lack of systematic information on the health situation and epidemiological
profile of indigenous peoples is one of the main obstacles to defining health goals and
assessing the results of enforcing their individual and collective rights.

Although the new juridical structure in place remains
insufficient, the foundations are considered to have been
laid for the next few years to see the battlefield shift
from the formulation of laws to their implementation and
enforcement. In other words, a new cycle should be based
on institutional practice and the effective implementation
of the legal framework (Stavenhagen, 2004). Just as
the force of the indigenous movement gave rise to the
progressive recognition of their collective rights, so it

has resulted in the incorporation into State agendas of the
need to devise special public policies in keeping with the
needs and requirements of indigenous peoples.
The common denominator of indigenous peoples is the
structural discrimination against them. Nonetheless, the fact
that there are over 670 indigenous peoples with their own
territorial, demographic and epidemiological realities means
that the particular situation and status of each group needs
to be considered individually (ECLAC, 2007a). There are

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Economic Commission for Latin America and the Caribbean (ECLAC)

many movements campaigning for indigenous rights, and
the possibility of success depends as much on the State
system and national cultural policy as it does on their
demographic weight and the geopolitical and economic
value that the economic powers attach to their territories
(ECLAC, 2007a). Generally speaking, indigenous
peoples that make up the majority of a population
and have long-standing indigenous organizations with
political clout (as in Bolivia and Ecuador) seek to
bring about transformations of the State and new plural
democracies. On the other hand, indigenous peoples

1.


that form a demographic minority tend to call for
autonomous regimes, as in countries including Chile,
Colombia, Nicaragua and Panama (ECLAC, 2007a).
As discussed below, State policies and programmes
are in response to indigenous strategies, especially
when programmes are territorially based with a wide
participation. However, some State initiatives still tend
to be designed and implemented without consideration
for the heterogeneity of indigenous peoples and therefore
continue to reproduce the welfare-based policies of the
past based on a monocultural State.

Health sector reforms:
is the outlook more favourable?

Health policies and programmes for indigenous peoples
in Latin America should be analysed in relation to the
expansion of the juridical framework of indigenous rights
and to the health system reforms initiated in most of the
region’s countries from the 1980s (ECLAC, 2006a).
Indeed, most Latin American countries are restructuring
their State health systems in terms of policies, programmes
and service networks. In this context, priority has been given
to the strategy of primary health care, based on the principles
of universal coverage and accessibility in accordance with
people’s needs; individual and community commitment,
participation and self-sustainment; intersectoral action
for health; cost-effectiveness; and the right technology
for the resources available (ECLAC, 2006a). One central
aspect of this has been to promote the participation of users
in the design of new models of care and management,
as well as the incorporation of community and family
medicine that emphasize communication between the
individual, the family and culture, on the one hand, and
scientific medicine, on the other (PAHO, 2002). These
new approaches are based on the need to adapt public
policy in order to generate cross-cutting policies geared
towards guaranteeing the rights of specific groups that
suffer from structural exclusion (including indigenous
peoples) (ECLAC, 2006a). In this sense, primary health
care is one of the fundamental strategies for achieving the
Millennium Development Goals, as it strengthens health
systems and emphasizes equity and social participation
in health matters (PAHO, 2002).

Reform processes aimed at achieving equitable, efficient
and high-quality health services have therefore generated
an environment more conducive to the development of
new models of health care based on user participation
and empowerment. In the case of indigenous peoples, this
is an opportunity for progress in terms of implementing
their collective rights, the minimum standard of which
was discussed earlier in the chapter. What is more, the
fact that Latin American countries have been hailed as
pluriethnic and multicultural has been echoed in the
health arena in the form of “medical pluralism”, which
has gradually recognized that biomedicine is just one of
many health systems and medical practices. Health systems
have their own etiological principles and diagnostic and
therapeutic categories, and the key to their effectiveness
lies within their own sociocultural context (Kleinman,
1980). This implies that no one system can meet all the
health demands of a given population. In the context
of primary health care strategies, it has been suggested
that traditional medicine be used as a valid, efficient and
cheaper medical resource to reduce the inequity suffered
by indigenous peoples.
According to a regional progress report on health
policies and programmes prepared by ECLAC in 2005,
despite the implementation of health reforms aimed at
achieving equitable, efficient and quality care, there
remain three types of problem for indigenous peoples:
(i) their health is worse than that of the non-indigenous
population; (ii) they have inequitable access to health

Social Panorama of Latin America • 2007

247

services; and (iii) there is a limited supply of specific
health services for indigenous peoples (ECLAC, 2006a).
In the light of collective rights, other issues include the
lack of cultural accessibility (or limited cultural integration
of conventional health interventions) and scarce political

2.


participation in decisions that affect them as peoples.
Solving these problems would involve developing an
intercultural approach to health policies, which is a clear
challenge for pluricultural States and new health care
models and policies (ECLAC, 2006a).

Public health policies and indigenous peoples:
concepts and regional situation

A public policy is the explicit manifestation of the
commitment of the State and its institutions to respond
to a given collective problem. With this in mind, a set
of initiatives and guidelines are proposed, along with a
juridical framework for their implementation. Aspects
of the problem include: a public problem, a diagnosis,
formulation of solutions and strategies, the necessary
resources and subsequent implementation. Part of the
process of policymaking is to establish a rule defining
who is responsible for policy implementation. As for
programmes, they are a concrete expression of pubic policy
guidelines within the established juridical framework and

include a coordinated set of concrete measures aimed at
achieving objectives that can be assessed using indicators.
Box V.2 describes the health policy for indigenous peoples
in Brazil, along with its rules and programmes.
The problems faced by a public policy dealing with
the health of indigenous peoples are threefold: (i) their
complex epidemiological profile with excess mortality
and higher levels of vulnerability and injury than the
general population; (ii) inequitable access to health care
and its limited cultural relevance; and (iii) the lack of
political participation of indigenous peoples (ECLAC,
2006a; Montenegro  Stephens, 2006).

Box V.2
NATIONAL HEALTH CARE POLICY FOR INDIGENOUS PEOPLES IN BRAZIL

In Brazil, the national health care policy
for indigenous peoples interlinks policy,
rules and a programme. The aim of the
policy is to guarantee comprehensive
health care for indigenous peoples in
accordance with the principles and
rules of the Single Health System. The
policy takes into account social, cultural,
geographic, historical and political diversity,
with a view to overcoming the factors that
make this population more vulnerable
and in worse health than the rest of the
Brazilian population. It also recognizes the
effectiveness of indigenous medicine and
these peoples’ cultural rights.
To achieve these objectives, a
series of rules were established to
formulate instruments for the planning,
implementation, assessment and control

(DSEI), the training of human resources
to work in intercultural settings, the
monitoring of health interventions geared
towards indigenous peoples (including
the creation of a Health Information
System for Indigenous Peoples in Brazil
(SIASI)) for surveillance and management
purposes, the coordination of traditional
indigenous health systems, the promotion
and appropriate use of medicine, ethics
for research and intervention, healthy
environments, indigenous health protection
and social control by the peoples
themselves.
The Special Indigenous Sanitary
Districts (DSEI) are a model of territorial
service organization for a well-defined ethnic
and cultural, geographic, demographic and
administrative area, involving technical

by means of administrative and managerial
activities needed for the provision of care
with social control. The criteria used to
define these districts are traditional territory,
social relations, demographic distribution,
operational logic, epidemiological profiles,
availability of human resources, regional
infrastructure and access for referrals
to the Single Health System. There are
currently 34 Special Indigenous Sanitary
Districts covering a total of 3,751 villages.
Every district has medical facilities in
each village. A centre has also been
set up for primary care and referrals to
Indigenous Health Centres or the Single
Health System.
In accordance with the series of rules
that derive from the policy, the various
programmes that exist include human

of health care measures for indigenous
peoples, including the organization of
health care services for indigenous peoples
into Special Indigenous Sanitary Districts

activities for the implementation of
rationalized and proven health care
measures. This model promotes and
reorganizes health networks and practices

resources training for interventions in an
intercultural context, which is considered
essential if health services are to meet the
requirements of indigenous peoples and the

248

Economic Commission for Latin America and the Caribbean (ECLAC)

Box V.2 (concluded)
new technical, political and organizational
realities. The aim of the programme is
to train indigenous individuals as health
agents, so that they can appropriate the

technical resources and knowledge of
western medicine, to be combined with
their own range of traditional and nontraditional healing and cultural practices.

This programme uses a participative
methodology to promote intercultural
communication as a way of boosting the
mutual process of gaining knowledge.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ministry of Health, Brazil, “Política nacional de
atençao à saude dos povos indígenas”, 2002.

The epidemiological profile of indigenous peoples is
linked to their stage of demographic transition. Indigenous
age structures are younger than among the non-indigenous
population, as a result of higher fertility rates (ECLAC,
2007a). Many studies have shown that indigenous peoples
have what is known as epidemiological accumulation,
in other words a morbidity and mortality profile with
ongoing and worsening diseases related to poverty and
underdevelopment, such as communicable or nutritional
diseases (including undernutrition, tuberculosis, diarrhoea
and bronchopneumonia), along with a gradual increase
in chronic and degenerative diseases associated with
modern living (such as cancer, hypertension, diabetes
and depression), as well as problems associated with
urbanization such as violence, murder and accidents (Rojas
 Shuqair, 1998). Although these characteristics are similar
to other socioeconomically disadvantaged groups, the
incidence of some diseases such as tuberculosis is even
higher among indigenous peoples and the morbidity and
mortality structure is also different (Oyarce  Pedrero,
2006; Montenegro  Stephens, 2006).
Recent data from Latin America confirms a persistent
excess mortality, especially at young ages. Although there
are considerable differences among countries, in Latin
America the average mortality rate among indigenous
children is 60% higher than among non-indigenous
children (48 per 1,000 live births compared with 30 per
1,000 live births) (ECLAC, 2007a). The gap is even
wider in terms of the probability of dying before the age
of five, with excess mortality of 70% among indigenous
peoples. The causes of death are mainly preventable, with
undernutrition being one of the main examples. What is
more, indigenous children who manage to survive are
more likely to be undernourished than those in the nonindigenous population. Data from the demographic and
health surveys show that, in Bolivia, Ecuador, Guatemala
and Peru, the incidence of global and chronic undernutrition
among children under the age of five is more than twice
as high among the indigenous population (with chronic
8

undernutrition of between 48% and 68%) than the nonindigenous population (with a rate of 23% to 37%).
Although these results are associated with poverty and a
greater indigenous presence in rural areas, there remain
inequities between the two groups even after controlling
for those factors (United Nations, 2005c).
In the case of infectious diseases, such as tuberculosis,
there are considerable gaps even in countries with low
rates of the disease such as Chile. Among the Aymara
people treated by the health service in Arica, tuberculosis
is six times more common than in the non-indigenous
population (35.1 people in 100,000 compared with 6.3
people in 100,000) (Oyarce and Pedrero, 2006). According
to survey data from Brazil, although the incidence of
tuberculosis among indigenous peoples has dropped
from 108.6 people in 100,000 in 2002 to 49.7 people in
100,000 in 2005, the nationwide average was still much
lower at 24.2 people in 100,000, even in 2003.8
Data from the survey sent to 16 countries of the
region suggest there are four groups of countries (see
table V.3). The first group is made up of countries that
have explicitly recognized that the health problems of
indigenous peoples require a different approach and that
have therefore formulated specific national policies to
tackle them. A second group of countries is in the process
of devising a specific national policy. The third group
has a national health policy that explicitly incorporates
an intercultural approach, while the fourth group has
no specific policies for indigenous peoples. As shown
in table V.3, countries with a national health policy for
indigenous peoples form the largest group.
Many countries explicitly recognize these health
policies for indigenous peoples as being part of the
conceptual framework of an intercultural health model.
Broadly speaking, interculturalism in health matters is
understood as a collective process of negotiation and
construction of meaning between social actors from
different cultures around epistemologies and models of
reality, life stages and cycles, the health-illness-healing

Data correspond to the incidence of tuberculosis with positive baciloscopy.

Social Panorama of Latin America • 2007

process, concepts of person, time and space, and the
quest for well-being by a people in a socially significant
and clinically appropriate territory (Oyarce and Pedrero,
2007). Nonetheless, this process may be associated with

249

different levels of interpretation and development within
each of the existing policies. Similarly, the heterogeneous
nature of indigenous peoples may also give rise to different
intercultural health models.

Table V.3
LATIN AMERICA (16 COUNTRIES): HEALTH POLICIES AND INDIGENOUS PEOPLES

Situation

Country

1.Countries with a national policy on health and indigenous peoples

Bolivarian Republic of Venezuela, Bolivia, Brazil, Chile,
Costa Rica, Ecuador, Mexico, Nicaragua, Panama and Peru

2.Countries in the process of formulating such a national policy

Argentina and Colombia

3. Countries with no specific policy but with a cross-cutting
intercultural approach in their national health policy

Guatemala and Honduras

4.Countries with no specific policy or approach for indigenous health

El Salvador and Paraguay

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of countries’ replies to surveys.

In Bolivia and Ecuador, these policies are explicitly
formulated in intercultural terms with a strong emphasis
on traditional medicine, with the latter also being the
case in the Bolivarian Republic of Venezuela. In Brazil
and Chile, the policies are defined in terms of health and
indigenous peoples. In Brazil, the emphasis is on health
care and services in indigenous territories (see box V.3). In
Chile, the policy is aimed at developing a health model of
indigenous peoples. In Peru, the indigenous health policy
includes intercultural coordination and implementation
by the National Intercultural Health Centre. The two main
orientations in this area are: mainstreaming policies (as in
Chile and the Bolivarian Republic of Venezuela) and territorial
policies (as in Brazil, Costa Rica and Nicaragua).
The development of such policies is a recent
phenomenon, with most dating from after the year 2000. An
exhaustive assessment of these policies from a rights-based
perspective involves reviewing an intercultural, integral
and complementary approach to construct new knowledge
that respects, promotes and protects the various meanings
of indigenous life events and cycles within their particular
worldview. This perspective forces biomedicine to break
with its hegemonic logic and be open to other forms of
knowledge in a context where indigenous cultural rights
are increasingly recognized.

3. 


In terms of policymaking at the national level as
included in the survey, the participation of indigenous
peoples has tended to take the form of consultations,
mostly at the stage of policy design (10 countries), and
less so at the stage of defining content (9 countries) and
policy implementation (7 countries). According to the
survey, indigenous participation occurred at all three
levels in the Bolivarian Republic of Venezuela, Brazil,
Costa Rica, Nicaragua and Peru. From this point of view,
interculturalism needs to be part of a broader sociopolitical
framework that recognizes that the relationship between
indigenous culture and western culture is currently one
where the former is subordinate to the latter. All actors
involved in health dialogue, negotiation and planning must
also participate in the acquisition of skills and abilities
relevant to intercultural dialogue. One fundamental
requirement is clearly the creation of democratic spaces in
which indigenous peoples’ own participatory and decisionmaking processes and dynamics are protected (PAHO/
CELADE/Universidad de la Frontera, Chile (UFRO), 2007;
Pedrero 2007; Castañeda, 2006). In practice, intercultural
and integral health policies can only be developed if the
collective rights of indigenous peoples are protected.
Otherwise, these models could become yet another means
of State domination (Boccara, 2007).

Programmes of, for and with indigenous peoples:
passive recipients or rights-holders?

Although programmes are a concrete expression of public
policy, the relationship between the two is not necessarily
linear or sequential. A concrete problem usually gives rise

to a specific programme, which is then institutionalized as a
policy as the issue takes on national significance. In Chile,
health programmes for indigenous peoples were introduced

250

Economic Commission for Latin America and the Caribbean (ECLAC)

in the early 1990s in the region of Araucanía, which
has traditionally recorded the worst health indicators in
the country. The region is the territory of the Mapuche
people, which are the country’s largest indigenous
group and a strong political and social presence. On
the basis of that regional experience, a nationwide
programme for indigenous peoples was rolled out in
the mid-1990s and subsequently extended to 22 health
services in the year 2000. Chile’s National Policy on
Health and Indigenous Peoples was devised in 2006
and was, in some way, the institutional culmination of
the activities carried out within individual territories
over the previous two decades (Pedrero, 2007). The

heterogeneous nature of policies and programmes
is shown in box V.3. In the Bolivarian Republic of
Venezuela, the policy is supported by laws that recognize,
promote and protect the health rights of indigenous
peoples, and is implemented throughout the country
by means of a series of programmes. In Colombia,
despite the fact that there is considerable legislation
on such matters, there is no national health policy for
indigenous peoples. Paradoxically, however, the way
health systems are organized has enabled programmes
to be developed on the basis of indigenous territories
that are controlled by traditional structures on the basis
of indigenous world visions.

Box V. 3
PUBLIC POLICIES AND PROGRAMMES FOR INDIGENOUS HEALTH
IN THE BOLIVARIAN REPUBLIC OF VENEZUELA AND COLOMBIA

During the constitutional reforms of 1999,
the Bolivarian Republic of Venezuela
extended the rights of indigenous peoples
and formulated laws to, inter alia, recognize
indigenous medicine, protect medicinal
resources and promote the training of
human resources. In 2004, a body for
the coordination of indigenous health
was set up within the Ministry of Health
and in 2006 became the Department for
Indigenous Health, whose mission it is to
formulate and assess health policies in the
framework of an intercultural approach and
in conjunction with indigenous peoples
and communities, so as to guarantee
compliance with the Constitution and the
Act on the Health of Indigenous Peoples
and Communities. The Department is run
by an epidemiologist who is a member of
the Wayúu people and employs around
600 indigenous health professionals,
hospital and community intercultural
brokers, health advocates and indigenous
community health representatives. The
health policy includes special programmes
for the 40 indigenous peoples spread
throughout the country. These include the
Office for Indigenous Health, indigenous
health advocates, the Mother Project, the
Yanomami Health Plan, the Delta Plan

and bilateral plans in conjunction with
Colombia. The policy also promotes an
intercultural approach throughout the
services and programmes of the national
public health system. The main results of
the policy include direct consultation with
indigenous peoples, the accreditation of
indigenous doctors, harmonization with
formal medicine and social auditing. The
success of this policy is based on solidarity
throughout all levels of government.
Interestingly, the country’s health records
include identification by ethnic group, which
means that the various programmes can
be monitored and assessed.
In Colombia, the General System of
Social Security in Health has coverage
that is subsidized, contributory or linked
to health maintenance organizations
(HMOs) that manage and give contracts to
service providers. Thanks to enforceability
mechanisms such as consultation and
negotiations concerning work in their
territories, indigenous organizations
have been able to bring about changes
in the rules so that traditional authorities
are now allowed to set up indigenous
HMOs and service providers to receive
resources from the State. These include
the indigenous service provider Dusakawi,

which is an example of the State-promoted
management model at the service of
indigenous interests and needs, as is
possible in a context of self-government
and autonomy. The Dusakawi indigenous
service provider is the result of a broad
process of consultation and comprises
the Association of the Indigenous Councils
of the departments of César and la
Guajira. It is an indigenous health tool
for the north of Colombia covering 12
indigenous peoples living in the Sierra
Nevada de Santa Marta. The principles,
values, concepts and programmes are
developed in accordance with the world
vision of these peoples and with the
principle of interculturalism, and are
based on the ancestral order for life
that values sacred sites and territory
as fundamental for integral health,
with western medicine considered as
complementary. Programmes include
the recognition of traditional medicine,
indigenous health education, food and
nutritional autonomy, rehabilitation
centres for patients and relatives from far
afield, the adaptation of western medicine,
specific programmes (for high blood
pressure, oral health and tuberculosis)
and epidemiological monitoring.

Source: Workshop-Seminar “Indigenous People in Latin America: Health Policies and Programmes, How Much and How Has Progress Been
Made?, Economic Commission for Latin America and the Caribbean (ECLAC), Santiago, Chile, 25 and 26 June 2007.

Social Panorama of Latin America • 2007

In 13 of the 14 countries surveyed, there is a specific
supply of health programmes for, of and with indigenous
peoples. These programmes fall into two main categories:
(i) special programmes, in other words specifically
designed for indigenous peoples, and (ii) programmes
specifically targeting indigenous peoples but incorporated
into traditional health service strategies or programme
areas such as primary care, sexual and reproductive health,
infectious diseases, nutrition or basic sanitation.
(a) Special programmes
This group includes general programmes, which are those
geared towards improving the health and quality of life of
indigenous peoples through access to culturally appropriate
services, the strengthening of traditional medicine, human
resource training and research (with this final aspect being
the least developed to date). Such programmes exist in the
following 10 countries: Argentina, Bolivarian Republic of
Venezuela, Bolivia, Brazil, Chile, Colombia, Costa Rica,
Ecuador, Honduras and Nicaragua (see annex 4).
One major characteristic is that, while such general
programmes tend to be designed as national schemes, in
practice they are focused on specific territories (usually
rural or urban areas with a concentration of indigenous
population). The only initiative with nationwide coverage is
the Ethnic Health Care Programme in Honduras, which aims
to coordinate health service provision, strengthen the health
services of indigenous communities, train local resources,
promote an equitable, timely and efficient intercultural
approach to health and, lastly, to set up interinstitutional
teams to define policy, promote research and evaluate the
quality of services. An example of a targeted initiative
is the Integral Indigenous Health Care Programme in
Brazil, which is aimed at providing comprehensive care
in all regular programmes of the single health system in
specific territories known as sanitary districts (see box
V.3). More specifically targeted programmes include
those for displaced individuals in the border regions of
Colombia and for indigenous immigrants entering Costa
Rica from Panama (see annex 4).
A second group of special programmes focus on specific
aspects of the health model, mainly on strengthening
traditional medicine and training human resources. In
terms of the former, these programmes aim to develop
traditional medicine and reverse the historical subordination
or even persecution of traditional healers that, along with
the degradation of ecosystems, has resulted in a significant
loss of such practices. In response to this, Bolivia, Costa
Rica and Guatemala have developed specific programmes
to recognize, value and revive traditional medicine,
especially in terms of medicinal plants and traditional
midwives. In both areas, the idea is to recognize the health
epistemologies, knowledge and practices of indigenous

251

peoples and incorporate them in the official health care
systems of western medicine. In Guatemala, the purpose
of the national programme for popular and traditional
medicine is to recognize, value and revive traditional
popular medicine and other alternative models of care at
the political, technical, normative and operational levels.
Achievements include the incorporation of traditional
treatments in primary and secondary health care. It has been
pointed out by indigenous organizations and academics
that, without social control by indigenous peoples, such
practices may lead to the alienation and loss of indigenous
medicine (Pedrero, 2007; Boccara, 2007).
In parallel, human resources training programmes are
developed in intercultural health or for work in indigenous
areas, with a view to training professionals to respect
the indigenous conception of the health-illness process
(Mexico and Peru) or training people from indigenous
communities in western medicine while maintaining their
cultural heritage (Argentina and Panama). The purpose
of this training is to technically prepare health teams to
manage biomedicine and indigenous medicine. In Mexico,
since 2002 there has been a national intercultural health
training programme covering all health teams working
in regular programmes. One common characteristic of
programmes to strengthen traditional medicine or train
human resources is their focus on rural territories with a
high indigenous population.
(b) Regular programmes
Regular programmes are those that are part of strategic
areas (such as primary care and sexual and reproductive
health) or those that are implemented as part of regular
programmes of health systems (infectious diseases, basic
sanitation and food and nutrition).
Argentina, the Bolivarian Republic of Venezuela,
Costa Rica and Ecuador have implemented primary
health care programmes aimed at improving access
while respecting cultural specificities. In Argentina, the
community doctors programme aims to train professionals
in community and intercultural health, with a view to
improving primary health care and strengthening national
and provincial management while respecting traditions and
customs. These programmes are implemented in defined
indigenous territories. In terms of sexual health and
reproductive rights, programmes in Ecuador and Panama
have implemented specific actions that combine a genderbased and intercultural approach in support of women’s
rights. Panama has two such programmes, with targets of
reducing maternal mortality and rates of abortion, child
mortality and teenage pregnancy (see annex 4).
As far as regular health programmes are concerned,
Panama is the region’s only country with specific
programmes for infectious diseases (mainly HIV/

252

Economic Commission for Latin America and the Caribbean (ECLAC)

AIDS, tuberculosis and malaria). Brazil and Panama are
implementing specific programmes for environmental
sanitation and also food and nutrition (see annex 4).9
In addition to policies and programmes, most countries
have introduced intercultural initiatives into strategies for
primary health care (nine countries), sexual health and
reproductive rights (seven countries), mother and child
(nine countries); mental health (Brazil and Costa Rica;
and infectious diseases (HIV/AIDS in Brazil, Ecuador
and Panama, tuberculosis and malaria in Panama; Chagas’
disease in Argentina and diarrhoea in Costa Rica). Argentina,
Bolivia, Brazil, Chile, Costa Rica, Ecuador, Honduras,
Mexico and Peru are developing training activities with
an intercultural approach and all except Peru also carry

4.

Main achievements and difficulties

The main achievements of programmes to date (see annex
4) include the consolidation of differentiated health care
models and the development of appropriate health care
for indigenous peoples in the Bolivarian Republic of
Venezuela, Bolivia, Brazil, Costa Rica, Colombia and
Panama. The model places special emphasis on progress in
human resource training, with Chile, Colombia, Mexico,
Panama and Peru providing illustrative examples of
intercultural awareness-raising and training of health teams.
Another important aspect is indigenous participation in
the entire process of programme design, implementation
and assessment (Argentina, Brazil and Chile).
One of the major achievements in Argentina, Brazil,
Bolivia and Peru has been the improved health conditions
of indigenous peoples, especially in the area of mother and
infant mortality and tuberculosis. Brazil has been the only
country to provide specific data on this progress. Between
2000 and 2006, infant mortality among indigenous peoples
in the sanitary districts of Brazil fell from 74.6 for every
1,000 live births to 38.5 per 1,000 live births, while the
incidence of pulmonary tuberculosis fell from 108.6 in
every 100,000 inhabitants in 2002 to 49.7 in 2005.
Mention should be made of the coordination between
various public sectors and advances in terms of public
policies and programmes in Argentina, Chile and Colombia.
Other aspects worthy of note are State recognition of the
cultural specificities of indigenous peoples, the expansion
of culturally relevant health services and the development
of particular studies, particularly epidemiological diagnoses
(Chile, Colombia and Brazil). Other progress includes
9

out State-sponsored actions to strengthen and promote
traditional medicine.
Lastly, there are various experiences where indigenous
and western medicine complement each other in specific
territories: in Ecuador there is the Indigenous Hospital
of Tungurahua, the Andean Hospital of Riobamba, the
Jambihuasi Centre for Alternative Medicine in Cañar
and the plural networks of Loreto. Chile has similar
experiences, the most well-known of which include the
Mapuche Hospital in Makewe, the Boroa-Filu Lawen
Intercultural Health centre and the Intercultural Health
Complex in Nueva Imperial (all located in the region of
Araucanía). Examples in Bolivia include the Health Centre
in Curva, which incorporates Kallawaya medicine.

the complementarity achieved between different types
of medicine and the guidelines for childbirth (Ecuador,
Panama and Peru), schemes to incorporate traditional
birth attendants into the State health system (Bolivarian
Republic of Venezuela, Guatemala, Panama and Peru) and
the use of medicinal plants in the therapeutic strategies
of regular programmes (Bolivia).
Given the importance of having suitably trained human
resources for an intercultural approach to health, the fact
that little or no progress has been made in this aspect of
the model appears to be the main obstacle to success for
the policies and programmes in question. There is a lack
of trained staff and the training itself is insufficient.
There is little information from countries on the
funding of specific programmes for the indigenous
population. Only seven countries provided the figures
for such financing (up to 2006) (Argentina, Brazil, Chile,
Honduras, Mexico, Panama and Peru). Brazil allocates
1.7% of GDP to health spending and channels 1% of that
health expenditure (US$ 173 million) to such programmes.
The country’s budget targeting the indigenous population
doubled between 2004 and 2006. However, the same
cannot be said of other countries, which cite the lack
or insufficiency of resources to cover all initiatives as a
major stumbling block.
Another aspect that must be analysed from a more
conceptual perspective is the need to develop the
“intercultural” content of health care, in what should
be a process of collective construction (Argentina
and Brazil).

In Brazil, the Food Security Programme is implemented by the Ministry of Social Development and Hunger Alleviation, while the food and
nutrition surveillance actions are carried out by the Ministry of Health.

Social Panorama of Latin America • 2007

5. 

Indigenous management and participation

As mentioned previously, participation is both a lynchpin
of health reform and a fundamental right of indigenous
peoples. It is a crucial part of policymaking to ensure that
policies are relevant to the living conditions and world
visions of indigenous peoples. Participation must be part
of every stage of reform, including the management and
use of resources. Indeed, participation and joint efforts
by planners, health providers and the representatives of
indigenous peoples are the only means of ensuring the
relevance of issues, the effectiveness of the measures
to tackle them and the suitability of health care and
management models (both epidemiologically and in terms
of their meanings in various contexts).
According to the replies provided by countries, in 13
of the 15 intercultural health programmes the Ministry
of Health coordinates its activities with indigenous
organizations. Indigenous participation is also an
achievement attained by many of these programmes.
Indigenous organizations have played a major role in
the sphere of health, especially indigenous women’s
organizations that started off working in matters related
to production and the economy. With the support of nongovernmental organizations (NGOs and international
cooperation agencies), these bodies promoted a gender
approach as the basis for their work, before gradually
extending their efforts to other areas (especially health)
and becoming more independent.
Other initiatives include the creation of community
ombudsman groups in the department of Cusco, Peru,
which constitute an efficient model for tackling domestic
violence. The ombudsmen are leading women chosen by
the community and subsequently trained to deal with and
support victims of violence. As part of their work, they
inform women that it is their right to file a complaint,
accompany them to medical examinations and police
stations and demand and monitor the authorities’ fulfilment
of their duties. The ombudsmen make domestic violence
visible within the community and provide concrete solutions
for those affected. In the process, not only are the female

10

253

ombudsmen empowered but men are also encouraged to
share responsibility as, despite the difficulties involved, they
too are an important part of the ombudsman team, given
that family violence is the problem of the community and
society as a whole, rather than just that of the women and
children affected. There are currently 38 ombudsman groups
with 380 female ombudsmen, mostly in isolated rural areas
with a mainly Quechua-speaking indigenous population
where many women do not speak Spanish.10
As was the case with policies, all stages of
programme participation in the Bolivarian Republic
of Venezuela, Bolivia, Brazil and Nicaragua take
place through indigenous organizations (including the
administration of resources). In other countries, such as
Chile, the participation there is in programme design,
content, administration and assessment takes place
on an individual level rather than through indigenous
organizations. The situation in Argentina is midway
between the two: some programmes aim for autonomy
and participation, while others where participation is
only at the programme-design stage. Lastly, Honduras,
Costa Rica and Peru are in the process of generating
conditions to guarantee participation.
As previously mentioned, one may wonder if there
can be a genuine participatory process if there is no
equality in the power and decision-making structure in
which indigenous peoples have always been subordinate
to the rest of society (Valdés, 2007). This is a complex
issue that is the subject of ongoing social debate and
that encompasses the following aspects: how to define
indigenous participation (given that not every space
with indigenous people is participatory by definition);
how do participation mechanisms provided by State
institutions fit in with the participation mechanisms of
indigenous peoples in a way that responds to community
and territorial dynamics; how and who should define
representation by an indigenous people and how can the
rights to political participation be linked to participation
in health programmes.

For further details, see Economic Commission for Latin America and the Caribbean (ECLAC) and W.K. Kellogg Foundation, Contest:
Experiences in social innovation in Latin America and the Caribbean [online] http://www.eclac.cl/dds/innovacionsocial/.

254

6.

Economic Commission for Latin America and the Caribbean (ECLAC)

Health information: how to measure the advances?

Information undoubtedly plays a crucial role in health,
both in terms of epidemiological diagnostics in public
policymaking (especially to define health objectives)
and for the follow-up and assessment of measures
implemented. In addition, research (particularly into the
health situation, determinants, risk factors and inequities
faced by indigenous peoples) requires basic data that
should also be disaggregated by ethnic group. Furthermore,
a rights-based approach and the implementation of the
above-mentioned standards of rights of indigenous peoples
require the production of public information, statistics
and systems of indicators for the purposes of monitoring
and assessment.
The demand for information on the part of States,
indigenous organizations, civil society and cooperation
agencies, among others, is therefore a central and recurring
issue at the national, regional and international levels
(ECLAC, 2006a). In Latin America, national statistical
systems have begun to respond to these requirements,
specifically in terms of identifying ethnic group in
population censuses, particularly in the 2000 round
(ECLAC, 2006a) and, to a lesser extent, in household
surveys. However, sources of health-sector data such as
vital statistics and hospital records are lagging behind in
this area. This is reflected in information provided

by the Pan American Health Organization (PAHO)
as part of an assessment of the first International
Decade of the World’s Indigenous People. Of the 16
countries under consideration, 15 reported having
information on the demographic profile of indigenous
peoples (based on censuses), while only 7 have
epidemiological profiles. However, such diagnostics
are not carried out systematically but on the basis of
information available, and are often studies limited
to certain territories or indigenous peoples.

As for the ethnic identification in health sources,
some local and territorial progress is being made in the
region. In Argentina, information on certain health districts
within provinces includes the percentage of indigenous
population. In Chile, local experiences include the health
service for the southern and northern Araucanía (populated
by the Mapuche people). The Hernán Henríquez Aravena
Hospital (the region’s main one) uses an information
system that includes membership of the Mapuche people

11

(self-definition and family names), both in the in-patient
database and the “medical agenda” system (a consultation
and referral system connected to all hospitals and health
centres in the South Araucanía Health Service). There
are also records from the Amuldungun Intercultural
Office, in which people are identified on the basis of a
community criterion used by an intercultural broker.11 In
Nicaragua, the health information systems of the North
and South Atlantic Autonomous Regions of Nicaragua
(RAAN and RAAS) and the Mayagna people are currently
being consolidated.
Brazil, the Bolivarian Republic of Venezuela and,
to a lesser extent, Chile are the countries that have made
the most progress in including ethnic identity in sources
of basic health data across the board.
In Brazil, data sources (censuses, household
surveys and records such as the Single Health System
(SUS)) tend to use the race or colour criterion, which
includes the category “indigenous”. In a major regional
initiative, since 2000 the National Health Foundation
in Brazil (FUNASA) has been implementing a Health
Information System for Indigenous Peoples (SIASI) in
the Special Indigenous Sanitary Districts. The system has
been designed for epidemiological purposes and service
delivery, as it makes it possible to monitor, plan, assess
and control the health of the indigenous population. The
system includes information on deaths, births, morbidity,
immunization and service output. The development of the
service is directly linked to the national health care policy
for indigenous peoples and there are plans to link it to the
Single Health System. The data-collection instruments
used for the Health Information System for Indigenous
Peoples (SIASI) are: family records, consultation forms,
personal records, indigenous health agents’ record books,
consolidated monthly activity reports, referral and backreferral forms and vaccination records. The data sources
are villages, indigenous health centres and public and
private health units. Although the system is still being
implemented and has had its share of operational problems,
there is a consensus that the system is easy to access,
comprehensive, with the possibility of local disaggregation
and the production and analysis of information at the
local level and with community participation (de Sousa,
Scatena  Ventura Santo, 2007).

In the Mapuche language, the term “amuldungun” means to spread the word, guide or disseminate knowledge/information.

Social Panorama of Latin America • 2007

255

The health information system of the Ministry of
People’s Power for Health in the Bolivarian Republic of
Venezuela now includes an ethnic identity variable in datacollection instruments for primary care, immunizations, and
epidemiological records (for HIV/AIDS and other chronic
diseases such as diabetes and kidney disease). The ethnic
identity variable also appears in medical consultation records.
However, the criteria used vary and include the concept of
“race”, ethnic group (34 indigenous peoples, white and mestizo)
and indigenous peoples. As for Chile, in 2007 the Ministry
of Health incorporated membership of an indigenous people
in the hospital discharge form, using the same criterion as
the population census and household surveys.
The fact that there are basic data disaggregated by
ethnic group or people does not necessarily mean that
such data are processed, analysed, used or disseminated,

let alone returned to the local area and communities of
origin. This limits indigenous use and social control of
that information. Programmes are usually devised using
nationwide averages that conceal cultural and territorial
heterogeneity. This creates health targets that do not
always fit in with the various epidemiological profiles
on the ground.
Yet health information does not come from the State
alone; information systems are also being created by
indigenous organizations, such as the Colombian National
Indigenous Organization, the Confederation of Indigenous
Nationalities of Ecuador and the Confederation of Indigenous
Peoples of Bolivia. Some studies are led by universities,
including the University of the Autonomous Regions of
the Caribbean Coast of Nicaragua (URACCAN) and the
Universidad de la Frontera (see box V.4).

Box V.4
REGIONAL OBSERVATORY FOR HEALTH EQUITY IN TERMS OF GENDER
AND THE MAPUCHE PEOPLE, REGION OF ARAUCANÍA, CHILE

The regional observatory for health equity in
terms of gender and the Mapuche people is
an interesting initiative in terms of information
collection and the development of specific
indicators for gender and the indigenous
population. The observatory is part of the
2004-2005 health reform and the 20002010 plan for equal opportunities for men
and women in Chile, and was created as a
regional space for analysis, reflection and
follow-up of the gender inequity suffered
by women in the region of Araucanía.
The observatory, which is made up
of representatives from various regional
civil-society organizations (Mapuche
and non-Mapuche) and academics from
the Universidad de la Frontera, has two
teams: a coordination team responsible
for communicating with the various civilsociety organizations; and a technical team
to coordinate contact with senior staff
and heads of services to link civil society
with public institutions, generate data for
methodologies and strategies appropriate
to the sociocultural characteristics of
the region, and produce information and

documents on the current situation of
health equity in terms of gender and the
Mapuche population.
The aims of the regional observatory
of Araucanía are to: make visible the gender
and ethnic inequalities and inequities
in terms of health, provide civil society
with the information it needs to advocate
in situations of inequity, legitimize the
observatory as a valid reference in this
area, establish networks with the Pan
American Health Organization (PAHO)
and the national observatory and produce
new regional knowledge using official
information in the fields of observation
established. The following five fields of
observation had corresponding categories
of indicators (impact or process), values
(in some cases) and their assessment
and target:
Violence: sexual, psychological and
physical domestic violence, access to
comprehensive domestic violence attention,
sexual violence outside the home, workplace
violence, extreme violence resulting in death
and institutional violence.

Sexual and reproductive health:
pregnancy and birth, access to contraceptive
methods, information, adolescent care and
education, male participation in sexual and
reproductive health, HIV/AIDS, advice,
guidance and care for women going
through the menopause.
Mental health: consultation for
mental health pathologies, addictions
and disabilities.
Quality of care: care in public health
institutions, rights of male and female health
service users, citizen participation in health,
intercultural health (establishments with
male and female intercultural brokers).
Environment: environmental pollution
by particles and pesticides, health of
female seasonal workers, traditional
Mapuche medicine (regional and national
records of medicinal herbs, surface
area of plantations with native forest,
effective ecosystem-improvement
programmes, improvement of general
living conditions of those responsible
for traditional Mapuche health) and the
legislative context.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the regional observatory for health
equity in terms of gender and the Mapuche [online] http://www.observatoriogenerosalud.cl.

256

To counter the information shortfalls in the region,
the Indigenous Peoples Fund is developing an Information
System for Indigenous Peoples. As part of the initiative,
the Latin American and Caribbean Demographic Centre
(CELADE) - Population Division of ECLAC and the
Indigenous Peoples Fund have formulated the System of
Sociodemographic Indicators for Indigenous Peoples and
Populations of Latin America (SISPPI). This includes over
50 demographic and socioeconomic indicators including
child and infant mortality (CELADE  Indigenous Peoples
Fund, 2007). The Pan American Health Organization
(PAHO), in conjunction with CELADE, is implementing
a project to include ethnic identity in vital statistics
and health records. Efforts so far have concentrated
on the Mapuche territory in Argentina and Chile, more
specifically in Araucanía (Chile) and the province of
Neuquén (Argentina).
The lack of information on the health and living
conditions of indigenous peoples remains one of the main
obstacles to defining health objectives that are relevant to
their situation and that guide and facilitate the assessment
of interventions aimed at closing gaps in the enforcement
of individual rights (increased coverage and quality of
care) and collective rights (cultural appropriateness of
services and programmes, development of traditional
medicine, and so forth).
There are at least two complementary action lines
underpinning the development of national information
systems based on integral health: first, the inclusion of
ethnic identity in traditional sources of health data to
construct indicators used for comparing the indigenous

Economic Commission for Latin America and the Caribbean (ECLAC)

and non-indigenous population; second, the development
of quantitative and qualitative indicators in keeping with
the integral health models of indigenous peoples (these
could include indicators relating to the environment,
territory and political participation).
As part of the joint PAHO and CELADE project “An
ethnic approach in sources of health data (the Mapuche
experience in the southern corridor of Argentina and Chile):
recommendations for future development in the Americas”,
a binational workshop was held at which delegates
stated that indigenous participation was essential. The
recommendations made were as follows: (i) the inclusion
of questions and the record system need to be the result
of a participatory process involving all actors, with form
and content negotiated and agreed in a collective process
covering the definition of questions and the analysis and
control of the information; (ii) participation must be at
the policymaking and decision-making levels, rather than
the merely consultative, as participation is what generates
change; (iii) the debate should take place at a territorial
level, with full participation of communities and technical
experts, in a flexible framework geared towards the local
adaptation of instruments for generating and using statistical
records, with social control on the part of indigenous
peoples; (iv) different forms of participation must be
considered for the State and Mapuche organizations and
institutions (traditional authorities); (v) the time frames
of indigenous peoples must absolutely be respected; and
(vi) institutions also require dialogue and discussion at the
senior level that will eventually lead to decision-making
and change.

Social Panorama of Latin America • 2007

257

C. Closing remarks and
 policy recommendations

The major challenge facing public policy is to continue moving forward with complying
with standards of health rights for indigenous peoples, which implies an integral concept of
indigenous health (including territorial rights and cultural integrity) and their full participation
in the definition, management and assessment of health policies and programmes. This
should form the basis of all differentiated health care models (intercultural, integral or
complementary). It is also vital to make progress in terms of training human resources to
generate an intercultural health dialogue, as well as producing knowledge to support those
models and facilitate the setting, follow-up and evaluation of health goals. Requirements
include systems of appropriate indicators, studies on sociocultural epidemiology, participatory
community health diagnoses, local research into health, illness and traditional medicine, and
an assessment of its effectiveness in each context. Continuous and adequate financing is also
essential to guarantee the autonomy of indigenous peoples as holders of collective rights.

Strengthening the rule of law is closely linked to the
effective enjoyment of citizens’ rights in their economic,
social and cultural dimensions. Although rights have gained
a legal status, there are serious shortfalls in their content,
scope and protection mechanisms. One example is the
gap between the recognition of the rights of indigenous
peoples and their actual enforcement, which in health
terms is expressed in less favourable morbidity and
mortality indicators compared with the non-indigenous
population, pointing to cumulative and more serious ill
health among the former.
The principle of rights entitlement, which should
guide public policy, is a difficult one to apply in Latin
America’s ethnically and culturally heterogeneous societies,
with their asymmetrical distribution of power. What is
needed is social consensus around indigenous peoples’
rights, as well as the institutions to enforce those rights
in response to that consensus.
The region of Latin America has made progress in
recognizing the existence of pluricultural democracies and the
contribution of the identity, world vision, roots and humanity
of the region’s indigenous peoples (ECLAC, 2006a). One

significant achievement is the creation of government
institutions responsible for indigenous affairs, despite
variations in the level of political participation among
indigenous peoples and the hierarchical status accorded to
the institution concerned. Many of the rights enshrined in
countries’ constitutions and legislations are not, however,
enjoyed by indigenous peoples. These include the right
to good health, which is one of the main factors in the
well-being of individuals, families and communities, as
well as being a necessity for human development. Health
policies for the indigenous population must therefore
consider the national and international instruments that
constitute the standard of rights and ensure that no one
is excluded from the right to access health services that
provide comprehensive and quality care for all.
Noteworthy steps in this direction include the gradual
recognition of indigenous peoples’ health rights, their
incorporation in the legislation of some Latin American
countries and their inclusion in most of the region’s health
policies and programmes. The main advances in terms of
health policies and programmes for indigenous peoples
have therefore taken the form of improving access and

258

adapting services to indigenous cultural realities. Significant
progress has been made in services, but less so in indigenous
peoples’ right to health as an integral concept including
traditional medicine and protection of the underlying
ecosystems. The participation of indigenous peoples in
these processes has also been limited, and this remains
one of the main challenges for constructing public policies
that consider them as holders of collective rights.
It is difficult to ascertain what has been achieved
in terms of improving objective health conditions and
reducing inequity, given that there are no information and
diagnosis systems for action follow-up and assessment,
and that the implementation of indigenous health
policies is a fairly recent phenomenon. There is also
a striking lack of information on the level of resources
channelled into such policies and programmes. There
is no up-to-date information on how much funding is
specifically targeting the indigenous population or the
level of continuity and increases, as such funds cannot
be distinguished from total resources used for health
programmes.
A review of the replies of governments to the ECLAC
survey on health policies and programmes for indigenous
peoples and the results of the Workshop-Seminar
“Indigenous People in Latin America: Health Policies and
Programmes, How Much and How Has Progress Been
Made?” resulted in the following recommendations.
As far as the normative framework is concerned,
progress should be made in strengthening legislation in
accordance with specific health rights for indigenous
peoples, with due consideration for the minimum standards
that can be summarized as follows:
• Right of access and preferential health care
• Right to quality and non-discriminatory health care
• Right of recognition for integral indigenous health,
including the use and control of traditional medicine
and the territorial spaces that are vital for healing
• Right to participate in the design, implementation,
management, administration and assessment of health
policies and programmes.
Complying with this normative framework requires
institutions that take responsibility for these issues and
raise the visibility of the relevant policies and programmes,
such that they become ongoing State policies that are not
affected by changes of government.
Enforcing the framework of rights for indigenous
peoples demands permanent political will on the part of
decision-makers, as well as constant vigilance by indigenous
organizations to ensure that rules are applied and that gaps
in the implementation of rights are closed.
A framework of rights is insufficient without
mechanisms for the enforcement and assessment of public
policies and rules, with a view to reducing gaps in the

Economic Commission for Latin America and the Caribbean (ECLAC)

implementation of health rights. Countries are recommended
to make creative use of institutional resources such as
peoples’ advocates, special reports on indigenous health,
new laws, accountability and lobbying of the executive. It
is also necessary to promote the protection of indigenous
rights and the legal punishment of a lack of compliance
by declaring such actions unconstitutional and producing
shadow reports on the enforcement of indigenous health
rights (in the context of, inter alia, the International Labour
Organization, and the Inter-American Commission on
Human Rights).
As for policymaking, a key element should be the
indigenous concept of integral health, which ties in with
other aspects affecting the life of indigenous communities
and peoples (such as land, territory and culture). This calls
for an intersectoral approach (environment, territory, public
works, water and sanitation), especially if the structural
causes of discrimination and poverty are to be taken to
task. What is needed is fair and equitable participation
in distributing the benefits of the exploitation of natural
resources in indigenous territories, so that living conditions
can be improved in an integral way.
Territoriality becomes a key aspect of health and
disease, and policies should therefore have a territorial
basis that is meaningful to indigenous peoples. Some
research into best health practices show that there are
clear advantages to that approach (O’Neil, Bartlett 
Mignone, 2005). What is more, there have been some
positive experiences and good governance in the sphere
of health based on indigenous cultural and community
processes within their territories.
Public policy should move forward with complementarity
in health and link traditional medicine with conventional
health systems. It is therefore vital to generate appropriate
juridical frameworks, in order to provide specific guarantees
for the practices of traditional indigenous healers and protect
the traditional knowledge and natural resources that ensure
the sustainable development of indigenous medicine. In
addition to legal harmonization, PAHO/WHO (2003)
distinguished conceptual and practical harmonization.
This implies designing and strengthening intercultural
health care models based on local research into indigenous
health practices and medicines that constitute healing
resources. Lines of research also need to be developed into
sociocultural epidemiology and participatory community
health diagnoses (Arriagada, Aranda  Miranda, 2005).
A crucial factor in the implementation of these models
is human resource training using methodologies that
respect cultural diversity and the learning processes of
each people and culture (such as oral and intergenerational
transmission).
Obviously, such processes of designing and
implementing health policies and programmes for

Social Panorama of Latin America • 2007

indigenous peoples require their active participation,
taking account of their own mechanisms and spaces,
through their organizations and authorities, so as to
guarantee genuine participation in the decision-making
around the problems that affect them. The medium- and
long-term sustainability of public policy should be
guaranteed by legal bases, participation and community
empowerment.
As far as financing is concerned, more resources are
needed to make progress in implementing public health
policies for indigenous peoples, assess the scale of public
health spending and “out-of-pocket” health spending and
establish mechanisms of accountability for the use of
resources targeting the indigenous population. New and
continuous resources are required to fund the expansion of
the system while ensuring that said resources result in a real
improvement of health services for indigenous peoples, as
well as autonomy in the management of those resources.
In terms of information, it is important to bear in mind
that shortfalls exist, especially in the area of public health.
Quality information is needed to form the basis for policies,
as well as for the implementation and assessment of their
results. Similarly, basic data are needed to carry out studies

259

into the social determinants of the health of indigenous
peoples and the distribution of medical resources, as
well as to create information, monitoring and evaluation
systems. This implies incorporating questions on ethnic
identity in conventional data sources (population censuses
and health records) and developing alternative sources
that pick up the specific characteristics and requirements
of each people. Information is also needed on access to
the supply of public health resources: services, medicine
and access to hospitals and other health centres. All of
the above is fundamental for assessing the quality of
programmes and the effects of policies and programmes
on improvements in indigenous health.
The implementation of the minimum standard of
the collective health rights of indigenous peoples, and
particularly the recent adoption of the United Nations
Declaration on the Rights of Indigenous Peoples, poses
enormous challenges for public policymaking. This is
because States must undertake a massive rethink that goes
from the conceptual framework to the design of health
targets and initiatives, while indigenous organizations and
peoples must in turn make effective progress in exercising
and protecting their right to health.

260

Economic Commission for Latin America and the Caribbean (ECLAC)

D. International agenda. Tenth session of the
 Regional Conference on Women in Latin America 
 and the Caribbean
The main aims of the Tenth session of the Regional Conference on Women in Latin America
and the Caribbean, organized by ECLAC from 6 to 9 August 2007 in Quito, Ecuador, were
to examine political participation and gender parity in decision-making processes at all
levels and analyse women’s contribution to the economy and social protection, especially
in terms of their unpaid work.

The Regional Conference is organized by ECLAC every
three years to analyse public policies from a gender
perspective. The Conference was attended by the President
of Ecuador, the President of Chile, the Vice-President of
Spain, Special Adviser to the Secretary-General on Gender
Issues and Advancement of Women and Ministers and
others in charge of gender policy in 33 Latin American
and Caribbean countries and members of ECLAC.
Three preparatory meetings had been held prior to the
Conference (Guatemala City, Guatemala, 16 and 17 May
2007; Saint John’s, Antigua and Barbuda, 22 and 23 May
2007; and Santiago, Chile, 28 and 29 May 2007), with a
view to reviewing, analysing and providing opinions on
the document Women’s contribution to equality in Latin
America and the Caribbean, produced by the Women
and Development Unit of ECLAC to facilitate dialogue
between governments and offer guidelines for devising
policies and specific measures in each of the region’s
countries. The preparatory process and the Conference
also involved side events involving social and nongovernmental organizations (NGOs) working at the
national and regional levels for the interests of women
in Latin America and the Caribbean.
In the parallel events organized by various United
Nations agencies and NGOs alongside the official
sessions of the Conference, the issues studied included
the contribution of the care economy to social protection
(ECLAC); policies for shared responsibility in terms
of productive and reproductive work (United Nations
Population Fund (UNFPA) and the World Bank); the
invisible economy and gender inequalities: the importance
of measuring and valuing unpaid work (Pan American
Health Organization, United Nations Development Fund for
Women (UNIFEM) and the Higher Council for Scientific

Research Spain); legal systems for paid domestic work
in MERCOSUR (the feminist coalition “Articulación
Feminista MARCOSUR”); gender parity policies in and
for the information society (UNESCO Regional Chair);
and the political participation of indigenous women and
those of African descent (United Nations Development
Programme (UNDP), UNIFEM, International Research
and Training Institute for the Advancement of Women
(INSTRAW), Permanent Forum on Indigenous Issues).
The Quito Consensus contains 36 resolutions,
including those referring to parity, participation and the
political representation of women and their contribution to
the economy and social protection in the form of unpaid
domestic work (see box V.1).
Countries undertook to adopt measures that
contribute to the elimination of all forms of violence and
its manifestations against women, especially the murder
of women, to develop comprehensive non-sexist public
education programmes aimed at tackling gender and racial
stereotypes and other cultural bias against women and to
promote relations of mutual support between men and
women. Countries also agreed to make efforts to sign,
ratify, implement and disseminate the Convention for
the Elimination of all Forms of Discrimination Against
Women and its Optional Protocol.
Lastly, countries requested the Presiding Officers
of the Conference to devote one of its annual meetings
to assessing the above-mentioned targets and decided
to dedicate the next Regional Conference on Women in
Latin America and the Caribbean (scheduled to be held
in 2010 in Brazil) to a general assessment of progress
made. Countries also requested ECLAC, along with
other United Nations organizations, to set up a gender
equality observatory.

Social Panorama of Latin America • 2007

261

Box V.5
TENTH REGIONAL CONFERENCE ON WOMEN IN LATIN AMERICA AND THE CARIBBEAN

Place and date: Quito, Ecuador, 6 to 9
August 2007
Participants: Representatives from 33
governments of ECLAC member countries,
intergovernmental organizations and
United Nations agencies.
Organized by: ECLAC
Preparatory activities during 2007:
• Subregional preparatory meeting
for Central America and Mexico for
the tenth session of the Regional
Conference on Women in Latin America
and the Caribbean, Guatemala City,
16-17 May.
• Subregional Preparatory Meeting for the
Caribbean for the tenth session of the
Regional Conference on Women in Latin
America and the Caribbean, St. Johns,
Antigua and Barbuda, 22-23 May.
• Subregional preparatory meeting for
South America for the tenth session of
the Regional Conference on Women
in Latin America and the Caribbean,
Santiago, Chile, 28-29 May.
Some of the main agreements included
in the Quito Consensus:
With regard to political parity and gender
equity
• To adopt all necessary affirmative action
measures and mechanisms, including
the necessary legislative reforms and
budgetary allocations, to ensure the
full participation of women in public
office and in political representative
positions with a view to achieving
parity in the institutional structure of
the State (executive, legislative and
judicial branches, as well as special
and autonomous regimes) and at the
national and local levels as an objective
for Latin American and Caribbean
democracies;
• To broaden and strengthen participatory
democracy and the inclusion of
women on an egalitarian, pluralistic
and multicultural basis in the region,
guaranteeing and encouraging their
participation and valuing the function

•

•

•

•


•

they perform in social and economic
affairs and in public policymaking, and
adopting measures and strategies for
positioning them in decision-making
spheres, opinion, information and
communication;
To promote activities that will enable
the countries of the region to share
strategies, methodologies, indicators,
policies, agreements and experiences
that facilitate progress towards the
achievement of parity in public office
and political representative office;
To develop electoral policies of a
permanent character that will prompt
political parties to incorporate women’s
agendas in their diversity, the gender
perspective in their content, actions
and statutes, and the egalitarian
participation, empowerment and
leadership of women with a view to
consolidating gender parity as a policy
of State;
To seek the commitment of political
parties to implement affirmative action
and strategies for communication,
financing, training, political education,
oversight and internal organizational
reforms in order to achieve participation
by women on a basis of parity, taking into
account their diversity, both internally
and at decision-making levels;
To adopt legislative measures and
institutional reforms to prevent, punish
and eradicate political and administrative
harassment of women who reach
decision-making positions through
electoral means or by appointment at
national and local levels, as well as in
political parties and movements.
With regard to women’s contribution
to the economy and social protection,
especially in terms of unpaid work
To adopt measures in all spheres of
institutional democratic affairs and,
in particular, in economic and social
areas, including legislative measures
and institutional reforms, to ensure

Source: Economic Commission for Latin America and the Caribbean (ECLAC).

•

•

•

•

•

recognition of unpaid work and its
contribution to families’ well-being and
to countries’ economic development,
and to promote its inclusion in national
accounts;
To implement comprehensive public
social security systems, with universal
access and coverage, that are linked
to a broad spectrum of public policies
and are capable of ensuring women’s
well-being, quality of life and full
citizenship;
To formulate and apply State policies
conducive to the equitable sharing of
responsibilities by women and men
in the family, overcoming gender
stereotypes and recognizing the
importance of caregiving and domestic
work for economic reproduction and
the well-being of society as one of
the ways of overcoming the sexual
division of labour;
To equalize the labour conditions
and rights of domestic work with
those of other types of paid work in
accordance with ratified International
Labour Organization conventions and
international standards of women’s
rights, and to eradicate all forms of
exploitation of domestic work by girl
and boy children;
To develop instruments, especially
time-use surveys, for periodically
measuring unpaid work performed
by women and men in order to make
such work visible and recognize its
value, to incorporate their results into
the System of National Accounts and
to design economic and social policies
accordingly,
To adopt the necessary measures,
especially of an economic, social and
cultural nature, to ensure that States
assume social reproduction, caregiving
and the well-being of the population
as an objective for the economy and
as a public responsibility that cannot
be delegated.

262

Economic Commission for Latin America and the Caribbean (ECLAC)

Annex V.1
LATIN AMERICA AND THE CARIBBEAN (16 COUNTRIES): COUNTRIES AND INSTITUTIONS THAT REPLIED
TO THE QUESTIONNAIRE ON HEALTH POLICIES AND PROGRAMMES FOR INDIGENOUS PEOPLES
Country

Institution

Position

Name

Argentina

National Institute for Indigenous
Affairs (INAI), Ministry of Health

Technical chief, intercultural health

Inés Quilici

Coordinator, National Support
for Humanitarian Actions for
Indigenous Peoples (ANAHI)

Gabriela Martínez

 
Bolivia

Office of the Under-Secretary of Traditional
Medicine and Interculturalism

Advisor

Oscar Laguna

Brazil

National Health Foundation (FUNASA)

Advisor, Department for
Indigenous Health

Edgard Magalhaes

Chile

Ministry of Health

Chief, health and indigenous
peoples programme

Margarita Sáez

Colombia

Ministry of Social Protection

Coordinator, equity and gender group

Gina Carrioni Denyer

Costa Rica

Ministry of Health

Chief, health analysis unit

César Gamboa

Ecuador

National Department for the Health
of Indigenous Peoples

Director

Juan Naula

El Salvador

National Council for Culture and Art

Director

José Manuel Bonilla Alvarado

Guatemala

Ministry of Health

Coordinator, programme of traditional
and alternative medicine

Mynor López

Honduras

Special Prosecutor’s Office for Ethnic
Groups and Cultural Heritage

Special Prosecutor for Ethnic Groups

Jany Del Cid

Mexico

Department of Strategic Programmes
in Rural and Indigenous Areas

Assistant Director

Luciano Rangel Castillos

Nicaragua

Pan America Health Organization (PAHO) Association of Promoters and Defenders of the
Indigenous Rights of Nicaragua (APRODIN)

Focal Point for indigenous peoples
APRODIN Focal Point

Marianela Corriols
María José Mendoza

Panama

Director

Ignacio Rodríguez

Paraguay

Ministry of Public Health and Social Welfare

Expert on indigenous health

Silvio Ortega

Peru

Intercultural Health Centre

Director

Oswaldo Salaverry

Venezuela
(Bol. Rep. of)

Coordination of indigenous
health, Ministry of Health

Director

Noly Coromoto

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of countries’ responses to the ECLAC survey on health
policies and programmes for indigenous peoples.

Social Panorama of Latin America • 2007

263

Annex V. 2
LATIN AMERICA AND THE CARIBBEAN (15 COUNTRIES):
HEALTH LEGISLATION FOR INDIGENOUS PEOPLES IN FORCE IN 2006a
Country

Legislation

Date

Content

Argentina

Law 23.302

1985

Indigenist policy and support for the National Institute for Indigenous
Affairs (INAI), which formulates health and sanitation plans

Resolution Nº 152/2004 and
amendatory Resolutions Nº 301/2004;
142/2006 of the National Institute
for Indigenous Affairs (INAI)

2004
2006

Creation of the Council for Indigenous Participation

Ministerial Resolution 0231

1987

Regulation of the practice of traditional Bolivian medicine

Supreme Decree 25.265

1998

Basic health insurance

Bolivia

Supreme Decree 26.330

Basic indigenous and native health insurance

2002

Law on universal mother and child insurance (SUMI)

Supreme Decree 26.874

2002

Regulation of universal mother and child insurance (SUMI). According to article
8, benefits must be in keeping with the practices, customs and languages of
peasant, indigenous and native peoples, with respect for identity, cultural basis
and gender approach

Bill

2005

Promoting the development of a new intercultural health policy

Supreme Decree 28.631

Brazil

2001

Law 2.426

2006

Creation of the Office of the Under-Secretary for Traditional Medicine and
Interculturalism, tasked with developing intercultural health plans and increasing
the appreciation of traditional medicine

Law 9.836

1999

Creation of the subsystem of health care for the indigenous population

Decree 3.156

1999

Creating the conditions for providing assistance to indigenous peoples

Ministerial Decree Nº 852 (FUNASA)

1999

Regulation of the functioning of the Special Indigenous Sanitary Districts

Ministerial Decree Nº 254
and its annexes

2002

National health care policy for indigenous peoples

Ministerial Decree 70/GM

Creation of the permanent forum of presidents in Special Indigenous Sanitary
Districts

2006

Creation of the National Commission for Indigenist Policy

Law Decree 2.763

2004

Incorporation of the indigenous population as a priority group in the national
health plan. The Ministry of Health should be incorporating an intercultural
approach into health programmes

Prerogative Resolution
Nº 91, Ministry of Health

2006

Formulation of the policy on health and indigenous peoples

Prerogative Resolution Nº 261
Colombia

Approval of guidelines for managing indigenous health

2006

Presidential Decree, Ministry of Justice
Chile

2004

Decree Nº 644 (FUNASA)

2006

Indicating the need to consider cultural relevance, interculturalism and
complementarity in health

Decree 1.811

1990

Partial regulation of law 10 of 1990 in terms of the provision of health services
to indigenous communities

Decree 1.416

1990

Stipulating rules on the organization and establishment of arrangements for
community participation in the provision of health service delivery

Resolution Nº 005.078

1992

Adoption of technical and administrative rules on traditional medicine and
alternative therapies, and the creation of the advisory council for their preservation
and development

Law 100

1993

Introducing mechanisms to guarantee access to health coverage for the
indigenous population

Law 691

2001

Regulation of the participation of ethnic groups in the General System of
Social Security

Decree Nº 330

2001

Establishing rules for the formation and functioning of health maintenance organizations
(HMOs) comprising traditional indigenous authorities and councils

Agreement 244

2003

Prioritizing indigenous people as beneficiaries of the subsidized scheme of the
General System of Social Security in Health by producing census lists from
traditional authorities

Agreement 326

2006

Adoption of certain guidelines for the organization and functioning of the
subsidized scheme for indigenous peoples of the General System of Social
Security in Health

264

Economic Commission for Latin America and the Caribbean (ECLAC)

Annex V. 2 (continued)
Country

Legislation

Date

Content

2006

Recognition of the use of traditional medicine for the purposes of prevention
and treatment, plus a proposal to develop specific health programmes for
indigenous peoples

Decree Nº 33.121-S

2006

Creation of the National Health Council of Indigenous Peoples (CONASPI)

Decree Nº 1.642

1999

Creation of the National Department for the Health of Indigenous Peoples
(with technical, administrative and functional autonomy) within the Ministry
of Public Health

Decree Nº 2.717

2005

Development of intercultural models of health and traditional medicine in the
framework of the policy on sexual health and reproductive rights

Health Act

2006

Recognition of the need to develop traditional medicine and adopt an intercultural
approach to health policy

2001

Guarantees the right to an integral health care model, respecting the use of
traditional indigenous medicine

Costa Rica Bill on the autonomous development
of indigenous peoples

Ecuador

Guatemala Legislative Decree 42-2001
(Social Development Act)
Mexico

Establishing the Department of traditional medicine and intercultural development,
which is responsible for indigenous health care

General Health Act

(Updated as
of June 2003)

Social Security Act

(Updated as of Establishing that indigenous people shall have access to social solidarity benefits
August 2006) in the way and terms stipulated by law

Proposing to legalize traditional medicine to support natural leaders, healers
or doctors

2003

Articulating relations between the Ministry of Health and regional health councils
in autonomous regions, and establishing health commissions

Ministerial Resolution Nº 4.376

1999

Creation of the Unit of Traditional Medicine in the Ministry of Health

2003

Creation of the National Commission of Traditional Indigenous Medicine

Law 27.300

2000

Regulation and promotion of the sustainable use of medicinal plants

Supreme Decree 001-2003-SA

2003

Regulation of the organization and functions of the National Health Institute

Ministerial Resolution 771

2004

Establishing the national health strategies of the Ministry of Health, including
that concerning the health of indigenous peoples, as run by the Intercultural
Health Centre of the National Health Institute

Law 28.736

2006

Establishing the special transectorial regime protecting the rights of the
indigenous peoples of the Peruvian Amazon who are in isolation or at the early
stages of contact

Law 37.600, Social Security System Act

2002

Establishing that the social security system shall afford special protection to
indigenous people and other groups in need

Act on indigenous peoples
and communities

2005

Incorporation of traditional medicine and the healing practices of indigenous peoples
and communities into national health system services, as well as the training of
staff in charge of health care for indigenous peoples and communities

Health and national public
health system bill

Venezuela
(Bol.
Rep. of)

2007

Executive Decree Nº 117
Peru

Establishing that autonomous regions shall be able to define a health care
model in accordance with their traditions, culture, practices and customs,
within the framework of the policies, plans, programmes and projects of the
Ministry of Health

Regulation for Law Nº 28, Statute
of autonomy of the regions of the
Atlantic coast of Nicaragua
Panama

2002-2003

Bill on traditional medicine and
complementary and alternative
therapies in Nicaragua

Nicaragua

2007

Creation of the Advisory Council of the national public health system, including
representatives of indigenous communities. The right to the use and practice
of traditional medicine is recognized and health policies and programmes are
made to be culturally and linguistically relevant

General Health Act 423 and
Regulations Decree Nº 001-2003

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of countries’ replies to the ECLAC survey; Inter–American
Development Bank (IDB), “Databank on Indigenous Legislation” [online] 2006, http://www.iadb.org/sds/ind/site_3152_s.htm; Pan American Health
Organization (PAHO), “Initiative on the Health of the Indigenous Peoples of the Americas (SAPIA)”.
aEl Salvador, Honduras and Paraguay do not mention specific legislation on health and indigenous peoples. Given that the IDB database has no such
references either, these countries are assumed to have no legislation in this area.

Social Panorama of Latin America • 2007

265

Annex V.3
LATIN AMERICA AND THE CARIBBEAN (16 COUNTRIES):
MAIN GOVERNMENT INSTITUTIONS RESPONSIBLE FOR INDIGENOUS HEALTH
Country

Institutions

Argentina

National Institute for
Indigenous Affairs (INAI)

Year of
creation
1985

Institutional status

Attached to

Decentralized
administration

Secretariat for social
policies and human
development, Ministry
of Social Development

Bolivia a

Government entities responsible
for indigenous health
National Support for Humanitarian
Actions for Indigenous Peoples
(ANAHI), Ministry of Health
Office of the Under-Secretary
for Traditional Medicine and
Interculturalism, Ministry of Health

Brazil

Indian National
Foundation (FUNAI)

1967

Public foundation

Ministry of Justice

Department of Indigenous Health,
National Health Foundation
(FUNASA), Ministry of Health

Chile

National Indigenous
Development
Corporation (CONADI)

1993

Public body

Ministry of Planning
and Cooperation

Unit for indigenous peoples’
health, Ministry of Health

Colombia

Division of indigenous
affairs, Council on
Ethnic Groups

2005

National Division

Equity and Gender Group,
Ministry of Social Protection

Costa Rica

National Commission
on Indigenous
Affairs (CONAI)

1973

Public service
institution

Office of the UnderSecretary for the
Interior, Ministry of the
Interior and Justice
Ministry of National
Planning and
Economic Policy

Ecuador

Council for the
Development of the
Nationalities and Peoples
of Ecuador (CODENPE)

1998

National Council with
a ministerial rank
executive secretary

Office of the President
of the Republic

National Department for the
health of indigenous peoples,
Ministry of Public Health

El Salvador

Unit of indigenous
affairs, National
department of cultural
development spaces

1995

National department

National Council
for Culture and Art,
Ministry of Education

None

Guatemala

Guatemalan Indigenous
Development Fund
(FODIGUA)

1994

Public bipartite
entity

Office of the President
of the Republic

Honduras

Special Prosecutor’s
Office for Ethnic Groups
and Cultural Heritage

1994

Special Prosecutor’s
Office

General Department
of Prosecutors, Public
Prosecutor’s Office

National programme of popular
traditional and alternative
medicine, Ministry of Public
Health and Social Welfare
Ethnic care programme, Secretary
of Health, Ministry of Health

Mexico b

National Commission
for the Development of
Indigenous Peoples (CDI)

2003

Public body

Office of the President
of the Republic

Nicaragua c

Council for the
development of the
Caribbean coast

2007

Panama

National department
for indigenist policy

1954

Paraguay d

Paraguayan Indigenous
Institute (INDI)

1981

Peru e

National Institute for
the Development of
Andean, Amazonian
and Afro-Peruvian
Peoples (INDEPA)

Venezuela
(Rep.
Bol. of)

Ministry of
Indigenous Affairs

Costa Rican Social Security
Fund, Ministry of Health

Department of traditional medicine
and intercultural development,
Health Department
Health commissions and regional
councils of the North and South
Atlantic Autonomous Regions of
Nicaragua (RAAN and RAAS)

Ministry of Interior
and Justice

Technical department for the traditional
medicine of indigenous peoples and
the health departments of indigenous
comarcas, Ministry of Health

National Institute

Office of the Presidency
of the Republic

None

2005

Public body with
a ministerial rank
executive secretary

Presidency of the
Council of Ministers

Intercultural Health Centre
(CENSI), National Health
Institute, Ministry of Health

2007

Ministry

Office of the Presidency
of the Republic

Department of Indigenous
Health, Ministry of Health

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of countries’ replies to the ECLAC survey.
Ministry of Peasant Affairs, Indigenous and First Peoples (MACPIO) was eliminated in January 2006.
bThe National Commission for the Development of Indigenous Peoples replaced the National Indigenist Institute of Mexico created in 1950.
c The Council for the development of the Caribbean coast replaced the Technical Secretariat of the Office of the President for Indigenous Affairs created in 1991.
dThe Paraguayan Indigenous Institute replaced the National Indigenous Institute created in 1975.
eThe National Institute for the Development of Andean, Amazonian and Afro-Peruvian Peoples replaced the National Commission for the Development
of Andean, Amazonian and Afro-Peruvian Peoples created in 2001.
aThe

1.1. General

1. Special

Coverage

To improve health
Targeted: rural
and quality of life.
To promote integral
development.
To respect and
value cultural
specificities

Objectives

Intercultural health
(2005)

Targeted:
Indigenous
34 Special
population
Indigenous
Sanitary Districts
(DSEI), rural and
urban areas

To strengthen the
health care model:
management,
financing,
organization
and community
initiatives with
traditional medicine
To improve
Targeted: 22
health and the
health services
environment.
To satisfy needs in
an integral way.
To consider
sociocultural
characteristics with
the participation of
indigenous peoples

Single health
system: indigenous
health component
(2000)

Health and
indigenous
peoples (1996)

Participation of indigenous
and Afro-Bolivian
organizations

Interinstitutional articulation

Achievements

Ministry of Health

Increased coverage.
Improved geographical and
cultural access (technical
rules and procedures).
Improved quality of care and
capacity to resolve problems.
Awareness raising and
training for health teams.
Coordination between services
and indigenous organizations.
Epidemiological studies.
Intercultural facilitators.
Care for indigenous migrants.

Ministry of
Formulation of indicators
Health and other
and visibility of health
government entities in indigenous lands.
Professionalization of services.
Articulation and adoption
of strategies in the
single health system.
Increased investment

Ministry of Health,
indigenous
organizations,
NGOs and
international
agencies

Ministry of Health

Coordinating
institution

Peoples:
Ministry of Health
Aimara,
Atacaman,
Colla, Diaguita,
Rapa Nui,
Mapuche,
Yánama,
Kawésqar

Targeted:
Indigenous
34 Special
communities
Indigenous
Sanitary Districts
(DSEI), rural and
urban areas

Health care for
Integral health care
indigenous peoples for indigenous
(1999)
peoples

Indigenous
population

Targeted: by
area (Andean
and valley)

Indigenous
population
aged
5 to 45

Communities
of indigenous
peoples

Target
population

Adaptation of health
services (2005)

Targeted: rural
and by area
(Andean, valley
and the east)

Health care with
participatory
management,
empowerment
and leadership

Health for
indigenous
peoples
(1999)

Type of programme

Aspects requiring
review

National and
international
budget and
NGOs

National
budget

Funding

Low participation
of communities.
Lack of training and
human resources.
Overworked local teams.
Difficulty in achieving
consensus around
intercultural health.
Insufficient media
exposure.
The programme is not
implemented in a crosscutting way throughout
the health system

Brazil

Chile

National
budget

Brazil

Bolivia

Bolivia

Argentina

Country

National
budget,
International
Fund

National
Policy of human
resources and
budget
professionalization of
indigenous agents.
Care of indigenous people
outside their territories
and in urban areas.
Regionalization and
greater autonomy
of Indigenous
Sanitary Districts.
Intersectoral dialogue

Implementation of
real interculturalism
in health centres

Annex V.4
LATIN AMERICA (14 COUNTRIES): HEALTH PROGRAMMES AND INDIGENOUS PEOPLES

266
Economic Commission for Latin America and the Caribbean (ECLAC)

To agree and adapt Targeted:
Peoples of
collective public
municipalities
indigenous
health measures
and departments reserves
in aspects of
traditional medicine
Integral health care
and accessibility at
least equal to that
enjoyed by the rest
of the population

To provide quality
Targeted:
preventive and
Coto Brus
health care services canton
in an integral
and timely way
in the spheres of
infectious diseases,
mother and child,
older adults,
housing, drinking
water and nutrition
To develop
intercultural
health models.
To strengthen
traditional systems.
To strengthen
organization and
human resources

Integral health care
for the indigenous
population (2002)

Integral health care
for indigenous
migrants
(2002)

Intercultural health
(1999)

Targeted:
Coto Brus
canton

Indigenous
migrants

Indigenous
population

Peoples:
Nasa,
Guambiano
Yanacona,
Arhuaco,
Kogui,
Wiwa

Basic health care
plan (PAB)
(2004)

Targeted: areas
of Cauca and
Sierra Nevada
de Santa Marta

To formulate
integral and
intercultural
health models

Aimara,
Atacaman
and Mapuche
peoples

Target
population

Adapting the
compulsory health
plan (POS) for
indigenous peoples
(2007)

Coverage

To improve
Targeted: 44
the health of
rural areas
the indigenous
population.
To eliminate
cultural barriers.
To expand physical
access to services.

Objectives

Intercultural health
components
(Origins program
me) (2001)

Type of programme

Annex V.4 (continued)

Ministry of
Public Health

Ministry of Health,
other government
entities and
indigenous
organizations

Ministry of Health,
other government
entities and
indigenous
organizations

Ministry of Social
Protection and
other government
agencies

Ministry of Health,
indigenous
organizations
and international
agencies

Ministry of Planning
and Cooperation
(MIDEPLAN),
National Indigenous
Development
Corporation
(CONADI) and
other ministries
(health, education
and agriculture)

Coordinating
institution

Improvement in the social
and health conditions,
morbidity and mortality.
Reduction in the number
of hospitalizations
and emergencies.
Positive financial effect

Raising of awareness
at the national level.
Round table discussions
between indigenous peoples
and health authorities

Training of health teams
that is recognized in a
public service career.
Coordination with
municipalities.
Cultural adaptation projects
in the area of health.
Appreciation, revival
and strengthening of
indigenous medicine

Achievements
International
Fund (InterAmerican
Development
Bank)

Funding

Cultural adaptation
of health services

National
budget

National
budget

National
budget

National
budget

Lack of specific resources National
and trained staff.
budget
Relaunching indigenous
health promoters
and linking them
to the system.
Producing follow-up and
assessment instruments

Administratively complex
health services.
Implementation and
assessment of pilot
experiments:
Complementarity
of indigenous and
official medicine.

Aspects requiring
review

Ecuador

Costa Rica

Costa Rica

Colombia

Colombia

Chile

Country

Social Panorama of Latin America • 2007
267

To provide quality
and efficient care to
indigenous patients,
while promoting
intercultural
communication
To improve
communication
between the health
care team and the
users of hospitals,
primary care centres
and communities

Office for
Indigenous Health
“An intercultural
vision”
(2005)

Indigenous health
advocates (2006)
Targeted:
eight states,
rural and
urban areas

Targeted:
eight states,
rural and
urban areas

Targeted:
North and
South Atlantic
Autonomous
Regions of
Nicaragua
(RAAN and
RAAS)

To promote the
development of the
care model for the
autonomous regions
of the Caribbean
coast of Nicaragua

Health models
of the North and
South Atlantic
Autonomous
Regions of
Nicaragua (RAAN
and RAAS) (2005)

Coverage

To coordinate
Nationwide
health care with
ethnic organizations
and institutions.
To strengthen
community health
services.
To provide culturally
relevant training to
local resources and
interinstitutional
teams: to define
policies, research
and assessment.
To promote an
equitable, timely
and efficient
intercultural
approach.

Objectives

Ethnic care
programme (1996)

Type of programme

Annex V.4 (continued)

Ministry of
Health and other
government entities:
regional government
and council of North
and South Atlantic
Autonomous
Regions

Ministry of Health,
indigenous
organizations
and NGOs

Coordinating
institution

40 indigenous Ministry of Health,
peoples
other government
agencies,
indigenous
organizations

40 indigenous Ministry of Health,
peoples
other government
agencies,
indigenous
organizations
and international
agencies

620,000
people from
indigenous
and ethnic
communities

All the
country’s
indigenous
and Afrodescendent
groups (9)

Target
population

Training of 427 indigenous
health advocates in eight
states with indigenous
population

Establishment of seven offices
in hospitals in the states
of Bolívar, Delta Amacuro,
Distrito Capital and Zulia

Integrating the population
of autonomous regions
into health care.
Social participation (especially
of indigenous peoples) in
model management.
Cultural revival.
Social solidarity and
reciprocity.
Equitable care

Human resource training with
an intercultural approach in
all health programmes.
Use of methodologies
incorporated and agreed upon
with indigenous peoples.

Achievements

Country

National budget

National budget

Venezuela
(Bol.
Rep. of)

Venezuela
(Bol.
Rep. of)

Nicaragua

National budget Honduras
and International
Fund

Funding

Incorporating and
National budget
training community
indigenous health agents

Extension of Offices
for Indigenous Health
to state hospitals with
the most referrals for
indigenous patients

Insufficient funding.
Cultural adaptation
of programmes and
standards under way.
Decentralization
under way.
Progress in terms of the
model does not extend
to the Pacific, central
and northern regions.

Shortage of technical
and financial resources.
Human resources with
limited training.

Aspects requiring
review

268
Economic Commission for Latin America and the Caribbean (ECLAC)

1.2.1.
Traditional
medicine

1.2. Specific

Targeted:
Delta Amacuro
state, rural and
urban areas

Coverage

Coordinating
institution

40 indigenous Ministry of Health,
peoples
other government
entities and
indigenous
organizations

Participation in the
programme of traditional
doctors, birth attendants
and midwives from
indigenous communities

Health services need to
provide a timely response
to the needs of the
indigenous population
as well as integrating
indigenous peoples and
assessing, monitoring,
controlling and defining the
effect of the programme

Lack of funding.
No funding
Limited human resources.
Lack of political will to
implement the programme.
Programme at a standstill.

Venezuela
(Bol.
Rep. of)

Targeted:
eight states with
an indigenous
population
in urban and
rural areas

To reduce
infant mortality
in indigenous
populations

Traditional medicine guides
and standards. Vademecum
of medicinal plants.
Strengthening and revival
of the practices of
traditional healers.

National budget, Bolivia
International
Fund and NGOs

Venezuela
(Bol.
Rep. of)

Country

Mother Project
(2006)

Ministry of Public
Health and Social
Welfare, other
government
entities, indigenous
organizations
and NGOs

Lack of adequate
regulation for registering
pharmaceutical products.
Sources of funding,
training of human
resources

Funding

Guatemala

Women of
childbearing
age and
traditional
healers

Training in converting medicinal
plants into pharmaceuticals.
Preparation of guides, leaflets
and other written materials.
Participation of indigenous and
Afro-Bolivian organizations

Aspects requiring
review

Targeted:
Totonicapán,
Quetzaltenango
Huehuetenango
Chimaltenango
Quiché and
Sololá

Ministry of Health,
indigenous
organizations,
international
agencies

Achievements

Traditional, popular To recognize value
and alternative
and revive traditional
medicine (2003)
popular medicine
and other alternative
care models at the
political, technical,
normative and
operational levels

People aged
20 to 50 in
indigenous
communities

Warao people Ministry of Health
and other ministries

Target
population

Costa
Rica

To transform
Targeted:
medicinal plants into rural areas
pharmaceuticals

To treat and
accommodate
Warao patients and
their relatives.
Nutrition and
food care.
To strengthen
traditional Warao
medicine.
To provide integral
health care and
train integrated
community
health agents.
Revival and
intercultural
adaptation of health
establishments.

Objectives

Traditional birth
attendants (2000)

Artisanal
laboratories
(2005)

Delta Plan
(2007)

Type of programme

Annex V.4 (continued)

Social Panorama of Latin America • 2007
269

2.1. Primary
health care

2. Regular
To train
professionals in
intercultural and
community health
to improve primary
health care.
To strengthen
national and
provincial
management, while
respecting traditions
and customs.
To train indigenous
individuals to care
for their peoples
To set up
intercultural task
forces providing
integrated care
through mobile
unit networks and
programmes

Community
doctors
(2005)

Primary health
care by indigenous
workers
(2000)

Primary health
care in Amazonia
(2000)
Targeted:
Amazonia

Targeted:
indigenous
territories

Targeted:
indigenous
communities,
urban and
rural areas

Targeted:
geographically
isolated or
highly dispersed
communities

Amazonian
peoples

Peoples in
indigenous
territories

Indigenous
peoples and
communities

Amazonian
and Andean
indigenous
peoples

Other government
entities

Ministry of Health

Ministry of Health

Formulation and
implementation of an action
plan: diagnosis, assistance,
local participative and
intersectoral intervention

Training of all mobile
health care teams

Insufficient funding
and limited human
resources for training

Increasing promotion of
the use of condoms
and other methods
of birth control

Ecuador

Costa
Rica

National budget Argentina

National budget Peru

National budget Panama

To incorporate
interculturalism
in the provision
of health services
to the population
currently treated
by mobile teams

Ministry of Health

Training of intercultural
health instructors for
operational levels

Country

Intercultural
training for
mobile teams
(2006)

Targeted:
Indigenous
territories of the peoples
seven indigenous
peoples

Incorporation in the regular
training programmes
of health workers

Funding

To improve
development
in childhood,
adolescence and
young adults in
indigenous areas

Health Department

Aspects requiring
review

Strengthening
the health care
capacity of
communities and
their institutions
(2004)

Children and
pregnant or
breastfeeding
women

Achievements

National budget Mexico

Targeted:
rural areas with a
high indigenous
population

Coordinating
institution

To train human
resources to be
respectful of the
different concepts
of the healthdisease process

Target
population

Training for health
workers who treat
the indigenous
population
(2002)

Coverage

Bolivia

Objectives

Intercultural health
1.2.2.
Intercultural training (no other
human
information)
resources

Type of programme

Annex V.4 (continued)

270
Economic Commission for Latin America and the Caribbean (ECLAC)

To include
interculturalism in
the National plan for
sexual health and
reproductive rights
of the National
Health System

To halt the
progress of
HIV/AIDS

Care and prevention To detect outbreaks
of tuberculosis
of tuberculosis
and malaria (2004) and malaria
for eradication
(treatment and cure)

Intersectoral
and intercultural
prevention and
control of STIs/
HIV/AIDS, (2004)

Nationwide
and targeted
in indigenous
territories

Nationwide
and targeted
in indigenous
territories

General

Emphasis on
indigenous
territories and
people living
with HIV/AIDS

Targeted:
Women of
territories of
indigenous
seven indigenous communities
peoples

Peoples:
Yanomami,
Yekuana and
Arahuaco
(around 21,000
indigenous
individuals)

Target
population

3.1.
Infectious
diseases

Care services for
women during
pregnancy and
labour (2004)

Targeted: Alto
Orinoco and
Río Negro
municipalities
of the state of
Amazonas (rural)

Coverage

All indigenous
and nonindigenous
population
(with emphasis
on adolescents
and young
people)

To develop
emergency obstetric
services and reduce
maternal mortality

National plan for
sexual health
and reproductive
rights (2005)

To increase the
coverage of
culturally and
linguistically
appropriate primary
health care, with
participation
of indigenous
workers and the
implementation of
strategies adapted
to the geographical
conditions of
the area

Objectives

Strengthening
To reduce rates
Nationwide
of institutional
of abortion, child
and targeted
capacity to offer
mortality and
in indigenous
sexual health
teenage pregnancy territories
and reproductive
through the use
services with
of contraceptive
a gender and
methods
intercultural
focus (2004)
3. Particular programmes, according to regular programme areas

2.2. Sexual
health and
reproductive
rights

Yanomami
health plan
(no further
information)

Type of programme

Annex V.4 (continued)

Ministry of Health,
at the level of
regions, provinces
and comarcas

Ministry of Health,
at the level of
regions, provinces
and comarcas

Ministry of Health,
at the level of
regions, provinces
and comarcas

Ministry of Health,
at the level of
regions, provinces
and comarcas

Coordinating
institution

The low number of cases
of tuberculosis and malaria
in indigenous regions

Consolidation of the
traditional birth attendant
programme for care during
pregnancy and labour in
indigenous communities

Training of health agents
in methodology based on
demands and priorities.
Bilingual training.
Exchange of western
and traditional healing
practices and knowledge.

Achievements

Raising awareness around
the use of condoms
in indigenous areas

Ecuador

Venezuela
(Bol.
Rep. of)

Country

National budget Panama

National budget Panama

Panama

National budget Panama
and International
Fund

Funding

Increasing promotion of the National
use of condoms and other budget
methods of birth control

Lack of mechanisms
to enable significant
participation by indigenous
peoples in the design,
follow-up and control
of pubic health policies
(especially in Alto Orinoco)

Aspects requiring
review

Social Panorama of Latin America • 2007
271

Source:

3.3 Food
and
nutrition

Targeted:
rural and periurban areas

Coverage

To provide the
inhabitants
of indigenous
territories with
drinking water

Safe drinking
water and basic
sanitation in rural
and indigenous
areas (2004)

Food and nutritional To reduce chronic
security (2003)
undernutrition in
rural and indigenous
communities

To build watersupply and
sanitation systems
and control their
quality; to rebuild
indigenous health
centres and clinics

Basic sanitation in
indigenous areas

Nationwide
and targeted
in indigenous
territories

Nationwide
and targeted
in indigenous
territories

Nationwide

Improving
To improve the
the sanitation
quality of service
infrastructure of
communities (2005)

Objectives

Rural and
indigenous
communities

General and
rural and
indigenous
communities

General

Peoples:
Diaguita
Toba,
Wichi,
Pilagá

Target
population

Ministry of Health,
at the level of
regions, provinces
and comarcas,
NGOs

Ministry of Health,
at the level of
regions, provinces
and comarcas

Ministry of Health

Ministry of Health,
Ministry of Labour,
Employment and
Social Security,
indigenous
organizations
and NGOs

Coordinating
institution

Reduction in the level
of undernutrition

Participation of communities
in the formulation and
management of health
policies and programmes.
Improved service and more
dignified working conditions.

Achievements

Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of countries’ replies to the ECLAC survey.

3.2 Basic
sanitation

Type of programme

Annex V.4 (concluded)

Although indigenous
territories have
water resources, few
communities have
drinking water

Raising awareness of the
responsibilities of the health
system and communities in
maintaining infrastructure

Aspects requiring
review

National budget

National budget

National budget

Funding

Panama

Panama

Brasil

Argentina

Country

272
Economic Commission for Latin America and the Caribbean (ECLAC)

Social Panorama of Latin America • 2007

273

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Statistical appendix

Social Panorama of Latin America • 2007

283

Table contents

SOCIO-ECONOMIC CONTEXT
Table 1

Trends in selected economic indicators, 1990-2006................................................................................................ 287

Table 2

Total regional population by country or territory, 1980-2010.................................................................................. 291

Table 2.1

Estimated total population growth rates by five-year period, 1980-2010................................................................ 292

Table 2.2

Estimated global fertility rates by country and five-year period, 1980-2010.......................................................... 293

Table 2.3 

Life expectancy at birth, both sexes, by five-year period, by country, 1980-2010.................................................. 294

Table 2.4

Estimated infant mortality rates both sexes, by five-year period, 1980-2010. ........................................................ 295
.

Table 3

Trends in selected social development indicators, 1980-2010................................................................................. 296

POVERTY AND INCOME DISTRIBUTION
Table 4

Poverty and indigence levels, 1990-2006................................................................................................................ 299
.

Table 5

Indigence lines (IL) and poverty lines (PL)............................................................................................................. 302

Table 6


Breakdown of households by per capita income brackets, expressed as multiples of the
poverty line urban areas, 1990-2006........................................................................................................................ 305

Table 7

Poverty rates in selected occupational categories, urban areas, 1990-2006 . .......................................................... 308

Table 8

Poverty rates in selected occupational categories, rural areas, 1990-2006 ............................................................. 311

Table 9


Breakdown of the total employed population living in poverty by occupational category,
urban areas, 1990-2006............................................................................................................................................ 314

Table 10


Breakdown of the total employed population living in poverty by occupational category,
rural areas, 1990-2006.............................................................................................................................................. 317

Table 11


Extent and distribution of poverty and indigence in households headed by women,
urban areas, 1990-2006............................................................................................................................................ 319

Table 12

Household income distribution, national totals, 1990-2006 ................................................................................... 322

Table 13

Household income levels and distribution, urban and rural areas, 1990-2006 ....................................................... 325

Table 14

Indicators of income concentration, national totals, 1990-2006 ............................................................................. 328

Table 15

Indicators of income concentration, national totals, urban areas, 1990-2006 . ....................................................... 331

Table 16

Indicators of income concentration, rural areas, 1990-2006.................................................................................... 334

284

Economic Commission for Latin America and the Caribbean (ECLAC)

LABOUR MARKET
Table 17

Male and female economic activity rates by age group, urban areas, 1990-2006................................................... 336

Table 18

Male and female economic activity rates by years of schooling, urban areas, 1990-2006...................................... 339

Table 19


Breakdown of the employed economically active population by occupational category,
urban areas, 1990-2006............................................................................................................................................ 342

Table 19.1


Breakdown of the employed economically active male population by occupational category,
urban areas, 1990-2006............................................................................................................................................ 346

Table 19.2


Breakdown of the employed economically active female population by occupational category,
urban areas, 1990-2006............................................................................................................................................ 350

Table 20


Breakdown of the employed economically active population by occupational category,
rural areas, 1990-2006.............................................................................................................................................. 354

Table 21

Urban population employed in low-productivity sectors of the labour market, 1990-2006.................................... 357

Table 21.1

Male urban population employed in low-productivity sectors of the labour market, 1990-2006............................ 360

Table 21.2

Female urban population employed in low-productivity sectors of the labour market, 1990-2006........................ 364

Table 22


Open unemployment rates by sex and age in urban areas, around 1990, 1994, 1997, 1999, 2003,
2004. 2005 and 2006................................................................................................................................................ 368

Table 23


Open unemployment rates by sex and years of schooling, in urban areas, around 1990, 1994, 1997,
1999, 2003, 2004, 2005 and 2006............................................................................................................................ 370

WAGES
Table 24


Average income of the employed economically active population by occupational category,
urban areas, 1990-2006............................................................................................................................................ 372

Table 24.1


Average income of the employed economically active male population, by occupational category,
urban areas, 1990-2006............................................................................................................................................ 376

Table 24.2


Average income of the employed economically active female population by occupational category,
urban areas, 1990-2006............................................................................................................................................ 380

Table 25


Average income of the employed economically active population by occupational category,
rural areas, 1990-2006.............................................................................................................................................. 384

Table 26

Ratio of average female income to average male income, by age group, urban areas, 1990-2006......................... 386

Table 27


Ratio of average female income to average male income, by years of schooling, urban areas,
1990-2006................................................................................................................................................................ 389
.

Table 28


Average income of the urban population employed in low-productivity sectors of the labour
market, 1990-2006................................................................................................................................................... 392
.

Table 28.1


Average income of the urban male population employed in low-productivity sectors of the
labour market, 1990-2006........................................................................................................................................ 395

Table 28.2


Average income of the urban female population employed in low-productivity sectors of the
labour market, 1990-2006........................................................................................................................................ 398

EDUCATION
Table 29


School attendance in urban areas, both sexes, by per capita household income quintile
and age group, 1989-2006........................................................................................................................................ 401

Table 30


Population between 15 and 24 years of age, by years of schooling, urban and
rural areas, 1980-2006.............................................................................................................................................. 403

Table 30.1


Male population between 15 and 24 years of age, by years of schooling, urban
and rural areas, 1980-2006....................................................................................................................................... 406

Table 30.2


Female population between 15 and 24 years of age, by years of schooling,
urban and rural areas, 1980-2006............................................................................................................................. 408

Table 31


Population between 25 and 59 years of age, by years of schooling, urban
and rural areas, 1980-2006....................................................................................................................................... 411

Table 31.1


Male population between 25 and 59 years of age, by years of schooling,
urban and rural areas, 1980-2006............................................................................................................................. 413

Social Panorama of Latin America • 2007

285

Table 31.2


Female population between 25 and 59 years of age, by years of schooling,
urban and rural areas, 1980-2006............................................................................................................................. 416

Table 32


Economically active population aged 15 and over, by years of schooling,
urban and rural areas, 1980-2006............................................................................................................................. 418

Table 32.1


Economically active male population aged 15 and over, by years of schooling,
urban and rural areas, 1980-2006............................................................................................................................. 420

Table 32.2


Economically active female population aged 15 and over, by years of schooling,
urban and rural areas, 1980-2006............................................................................................................................. 422

Table 33


Years of schooling completed by the population between 15 and 24 years of age,
by sex, urban and rural areas, 1980-2006. ............................................................................................................... 424
.

Table 34


Years of schooling completed by the population between 25 and 59 years of age,
by sex, urban and rural areas, 1980-2006. ............................................................................................................... 426
.

Table 35


Years of schooling completed by the economically active population aged 15 and over,
by sex, urban and rural areas, 1980-2006. ............................................................................................................... 428
.

Table 36

Classification of young people aged 15 to 19 by educational status, national total, around 2006. ......................... 430
.

Table 37

Classification of young people aged 15 to 19 by educational status, urban areas, around 2006............................. 432

Table 38


Classification of young people aged 15 to 19 by educational status throughout the school cycle,
rural areas, around 2006........................................................................................................................................... 434

Table 39

Overall dropout rate among young people aged 15 to 19, 1990-2005..................................................................... 436

Table 40

Early dropout rate (during the primary cycle) among young people aged 15 to 19, 1990-2005............................. 437

Table 41

Dropout rate at the end of the primary cycle among young people aged 15 to 19, 1990-2005............................... 438

Table 42

Dropout rate during the secondary cycle among young people aged 15 to 19, 1990-2005..................................... 439

Table 43

Public social spending indicators 1990/1991-2004/2005 ....................................................................................... 440

Table 44

Indicators of public social spending on education 1990/1991-2004/2005 . ............................................................ 442

Table 45

Indicators of social spending on health 1990/1991-2004/2005............................................................................... 444
.

Table 46

Indicators of public social spending on social security 1990/1991-2004/2005....................................................... 446

Table 47

Indicators of public social spending on housing and other items 1990/1991-2004/2005........................................ 448

MILLENNIUM DEVELOPMENT GOALS
Table 48


Latin America and the Caribbean: progress towards the Millennium Development Goals
(Goal 1: Eradicate extreme poverty and hunger)..................................................................................................... 450

Table 49


Latin America and the Caribbean: progress towards the Millennium Development Goals
(Goal 2: Achieve universal primary education)....................................................................................................... 452

Table 50


Latin America and the Caribbean: progress towards the Millennium Development Goals
(Goal 3: Promote gender equality and empower women). ...................................................................................... 453
.

Table 51


Latin America and the Caribbean: progress towards the Millennium Development Goals
(Goal 4: Reduce child mortality; Goal 5: Improve maternal health)....................................................................... 455

Table 52


Latin America and the Caribbean: progress towards the Millennium Development Goals
(Goal 6: Combat HIV/AIDS, malaria and other diseases)....................................................................................... 457

Table 53


Latin America and the Caribbean: progress towards the Millennium Development Goals
(Goal 7: Ensure environmental sustainability)......................................................................................................... 458

Table 54


Latin America and the Caribbean: progress towards the Millennium Development Goals
(Goal 7: Ensure environmental sustainability)......................................................................................................... 460

Table 55


Latin America and the Caribbean: progress towards the Millennium Development Goals
(Goal 8: Develop a global partnership for development)......................................................................................... 462

Social Panorama of Latin America • 2007

287

Table 1
TRENDS IN SELECTED ECONOMIC INDICATORS, 1990-2006
Country

Argentina

Bolivia

Brazil

Chile

Colombia

Year

Per capita
GDP
(in 2000
dollars)

Per capita
Urban
Annual variation
income unemployment in consumer
(in 2000 (percentage)
prices
dollars) a

Average annual variations in the period
Period

Per capita
GDP

Per capita
income a

Mean real
remuneration

Urban
minimum
wage

1990
1999
2000
2001
2002
2003
2004
2005
2006

5 833
7 874
7 730
7 315
6 456
6 961
7 518
8 131
8 733

5 690
7 620
7 536
7 112
6 169
6 722
7 286
7 947
8 633

7.4
14.3
15.1
17.4
19.7
17.3
13.6
11.6
10.4

1 343.9
-1.8
-0.7
-1.5
41.0
3.7
6.1
12.3
9.8

1990-1999
2000
2001
2002
2003
2004
2005
2006

3.4
-1.8
-5.4
-11.7
7.8
8.0
8.1
7.4

3.3
-1.1
-5.6
-13.3
9.0
8.4
9.1
8.6

0.5
2.3
-0.8
-13.9
-1.9
10.0
6.1
8.6

15.0
0.9
1.1
-19.5
3.3
54.5
31.8
12.9

1990
1999
2000
2001
2002
2003
2004
2005
2006

870
995
996
990
992
996
1 015
1 033
1 059

901
1 016
1 016
1 005
1 038
1 076
1 114
1 151
1 272

7.3
7.2
7.5
8.5
8.7
9.2
6.2
8.2
…

18.0
3.1
3.4
0.9
2.4
3.9
4.6
4.9
4.9

1990-1999
2001
2001
2002
2003
2004
2005
2006

1.5
0.1
-0.6
0.2
0.4
1.9
1.8
2.5

1.3
-0.0
-1.0
3.3
3.6
3.5
3.3
10.5

2.1
1.4
5.8
3.3
1.6
2.9
-3.9
…

10.2
2.9
10.8
4.7
0.8
-4.2
-5.1
4.5

1990
1999
2000
2001
2002
2003
2004
2005
2006

3 349
3 589
3 689
3 682
3 727
3 715
3 872
3 930
4 021

3 274
3 481
3 595
3 570
3 619
3 610
3 776
3 841
3 973

4.3
7.6
7.1
6.2
11.7
12.3
11.5
9.8
10.1

1 583.9
8.9
6.0
7.7
12.5
9.3
7.6
5.7
3.1

1990-1999
2000
2001
2002
2003
2004
2005
2006

0.8
2.8
-0.2
1.2
-0.3
4.2
1.5
2.3

0.7
3.3
-0.7
1.4
-0.3
4.6
1.7
3.4

0.2
-1.1
-4.9
-2.1
-8.8
0.7
-0.3
3.5

3.1
2.6
9.8
4.2
2.7
3.4
5.8
13.1

1990
1999
2000
2001
2002
2003
2004
2005
2006

3 081
4 751
4 903
5 009
5 061
5 203
5 456
5 708
5 873

2 952
4 579
4 754
4 759
4 841
4 957
5 410
5 850
6 411

9.2 c
10.1 c
9.7 c
9.9 c
9.8 c
9.5 c
10.0 c
9.2 c
7.9 c

27.3
2.3
4.5
2.6
2.8
1.1
2.4
3.7
2.6

1990-1999
2000
2001
2002
2003
2004
2005
2006

4.9
3.2
2.2
1.0
2.8
4.9
4.6
2.9

5.0
3.8
0.1
1.7
2.4
9.1
8.1
9.6

4.0
1.4
1.7
2.0
0.9
1.8
1.9
1.9

5.5
7.1
3.8
2.9
1.4
2.8
1.9
2.5

1990
1999
2000
2001
2002
2003
2004
2005
2006

1 837
1 986
2 011
2 008
2 016
2 062
2 131
2 201
2 319

1 751
1 948
1 996
1 979
1 985
2 038
2 143
2 241
2 389

10.5
19.4
17.2
18.2
17.6
16.7
15.4
14.0
13.0

32.4
9.2
8.8
7.6
7.0
6.5
5.5
4.9
4.5

1990-1999
2000
2001
2002
2003
2004
2005
2006

0.9
1.3
-0.1
0.4
2.3
3.3
3.3
5.4

1.2
2.5
-0.8
0.3
2.7
5.1
4.6
6.6

2.6
3.9
-0.3
3.6
-0.2
1.3
1.2
3.2

-0.1
0.5
1.2
0.7
0.1
1.8
1.2
2.8

Socio-economic
context

Socio-economic context

288

Economic Commission for Latin America and the Caribbean (ECLAC)

Socio-economic
context

Table 1 (continued)
TRENDS IN SELECTED ECONOMIC INDICATORS, 1990-2006
Country

Costa Rica

Year

Per capita
GDP
(in 2000
dollars)

Per capita
Urban
Annual variation
income unemployment in consumer
(in 2000 (percentage)
prices
dollars) a

Average annual variations in the period
Period

Per capita
GDP

Per capita
income a

Mean real
remuneration

Urban
minimum
wage

1990

3 123

3 035

5.4

27.3

1999

4 081

3 737

6.2

10.1

1990-1999

3.0

2.3

2.2

1.1

2000

4 063

3 767

5.3

10.2

2000

-0.5

0.8

0.8

-0.6

2001

5.8

11.0

2001

-1.0

3.1

1.0

0.2

3 968

6.8

9.7

2002

0.9

2.2

4.1

-0.6

4 234

4 043

6.7

9.9

2003

4.4

1.9

0.4

-0.4

2004

4 336

4 153

6.7

13.1

2004

2.4

2.7

-2.6

-1.6

2005

4 510

4 326

6.9

14.1

2005

4.0

4.2

-1.9

0.3

2006

4 780

4 569

6.0

9.4

2006

6.0

5.6

1.6

1.7

1990

3 064

3 341

5.4 c

…

1999

2 395

2 462

6.3 c

-2.9

1990-1999

-2.7

-3.3

…

…

2000

2 534

2 529

5.4

-2.3

2000

5.8

2.7

…

…

2001

2 603

2 619

5.2

-1.5

2001

2.7

3.5

…

…

2002

2 636

2 646

3.3

7.0

2002

1.3

1.0

…

…

2003

2 708

2 746

2.3

-3.8

2003

2.7

3.8

…

…

2004

2 825

2 818

2.0

2.9

2004

4.3

2.6

…

…

2005

…

…

2.3

3.7

2005

…

…

…

…

2006

…

…

2.0

5.7

2006

…

…

…

…

1990

1 252

1 096

6.1

49.5

1999

1 279

1 214

15.1

60.7

1990-1999

0.2

1.1

38.7

2.1

2000

Ecuador

3 884

4 056

2003

Cuba b

4 022

2002

1 296

1 291

14.1

91.0

2000

1.3

6.4

-4.7

-3.6

2001

1 305

10.4

22.4

2001

3.8

1.0

11.9

11.5

1 382

1 356

8.6

9.3

2002

2.8

3.9

10.9

0.9

2003

1 412

1 381

9.8

6.1

2003

2.1

1.8

…

6.1

2004

1 502

1 459

11.0

1.9

2004

6.4

5.6

…

2.4

2005

1 551

1 614

10.7

3.1

2005

3.3

10.7

…

3.0

2006

1 591

1 732

10.1

2.9

2006

2.6

7.3

…

3.3

1990

1 639

1 704

10.0

19.3

1999

2 089

2 296

6.9

-1.0

1990-1999

2.7

3.4

…

0.1

2000

El Salvador

1 345

2002

2 093

2 339

6.5

4.3

2000

0.2

1.9

…

-2.2

2001

2 432

7.0

1.4

2001

-0.2

4.0

…

-3.6

2 098

2 380

6.2

2.8

2002

0.4

-2.1

…

-1.8

2003

2 108

2 361

6.2

2.5

2003

0.5

-0.8

…

2.1

2004

2 108

2 399

6.5

5.4

2004

0.0

1.6

…

-1.4

2005

2 129

2 428

7.3

4.3

2005

1.0

1.2

…

-4.5

2006
Guatemala

2 089

2002

2 181

2 527

5.7

4.9

2006

2.5

4.1

…

-0.7

1990

1 290

1 268

6.3 c

59.6

1999

1 514

1 572

…

4.9

1990-1999

1.8

2.4

5.4

-7.4

2000

1 532

1 591

…

5.1

2000

1.2

1.2

3.8

4.4

2001

1 530

1 610

…

8.9

2001

-0.1

1.2

0.5

8.3

2002

1 550

1 698

5.4

6.3

2002

1.3

5.4

-0.9

0.3

2003

1 551

1 722

5.2

5.9

2003

0.0

1.4

0.4

8.0

2004

1 560

1 752

4.4

9.2

2004

0.6

1.7

-2.2

0.3

2005

1 575

1 780

…

8.6

2005

0.9

1.6

-4.0

-1.4

2006

1 611

1 829

…

5.8

2006

2.3

2.8

-1.1

3.2

Social Panorama of Latin America • 2007

289

Country

Haiti

Honduras

Mexico

Nicaragua

Panama

Paraguay

Year

Per capita
GDP
(in 2000
dollars)

Per capita
Urban
Annual variation
income unemployment in consumer
(in 2000 (percentage)
prices
dollars) a

Average annual variations in the period
Period

Per capita
GDP

Per capita
income a

Mean real
remuneration

Urban
minimum
wage

1990
1999
2000
2001
2002
2003
2004
2005
2006

516
431
427
416
408
403
383
384
386

557
517
515
501
491
498
479
493
502

…
…
…
…
…
…
…
…
…

…
9.7
19.0
8.1
14.8
40.4
20.2
14.8
…

1990-1999
2000
2001
2002
2003
2004
2005
2006

-2.0
-0.8
-2.7
-1.8
-1.2
-5.0
0.2
0.7

-0.8
-0.4
-2.7
-2.1
1.5
-3.9
3.1
1.9

…
…
…
…
…
…
…
…

-7.3
-11.9
-11.6
-8.9
33.5
-14.7
-13.2
-12.0

1990
1999
2000
2001
2002
2003
2004
2005
2006

890
934
967
972
978
992
1 021
1 042
1 083

857
1 048
1 065
1 088
1 085
1 084
1 113
1 209
1 283

7.8
5.3
…
5.9
6.1
7.6
8.0
6.5
5.2

36.4
10.9
10.1
8.8
8.1
6.8
9.2
7.7
5.3

1990-1999
2000
2001
2002
2003
2004
2005
2006

0.5
3.6
0.5
0.6
1.4
3.0
2.0
3.9

2.3
1.7
2.1
-0.3
-0.1
2.7
8.6
6.1

…
…
…
…
…
…
…
…

-1.1
3.1
2.5
2.1
8.6
0.8
5.8
5.1

1990
1999
2000
2001
2002
2003
2004
2005
2006

4 914
5 541
5 826
5 761
5 756
5 791
5 986
6 099
6 323

4 756
5 455
5 746
5 674
5 701
5 778
6 058
6 222
6 486

2.7
3.7
3.4
3.6
3.9
4.6
5.3
4.7
4.6

29.9
12.3
9.0
4.4
5.7
4.0
5.2
3.3
4.1

1990-1999
2000
2001
2002
2003
2004
2005
2006

1.3
5.1
-1.1
-0.1
0.6
3.4
1.9
3.7

1.5
5.3
-1.2
0.5
1.4
4.8
2.7
4.2

0.7
6.0
6.7
1.9
1.4
0.3
-0.3
0.4

-4.1
0.7
0.4
0.7
-0.7
-1.3
-0.1
0.0

1990
1999
2000
2001
2002
2003
2004
2005
2006

681
753
771
783
778
787
819
843
863

577
799
812
807
812
826
857
887
890

13 490.2
7.2
9.9
4.7
4.0
6.6
8.9
9.6
10.2

1990-1999
2000
2001
2002
2003
2004
2005
2006

1.1
2.4
1.5
-0.6
1.2
4.0
3.0
2.3

3.7
1.6
-0.7
0.7
1.7
3.8
3.5
0.3

3.1
0.0
1.0
3.5
1.9
-2.2
0.2
1.4

0.8
-0.5
2.1
3.7
3.1
4.0
4.0
8.8

1990
1999
2000
2001
2002
2003
2004
2005
2006

2 942
3 912
3 942
3 891
3 905
3 994
4 219
4 434
4 713

3 017
3 816
3 812
3 834
3 942
3 835
3 942
4 066
4 301

20.0
13.6
15.2
17.0
16.5
15.9
14.1
12.1
10.4

0.8
1.5
0.7
0.0
1.9
1.5
1.5
3.4
2.2

1990-1999
2000
2001
2002
2003
2004
2005
2006

3.2
0.8
-1.3
0.4
2.3
5.6
5.1
6.3

2.6
-0.1
0.6
2.8
-2.7
2.8
3.1
5.8

…
…
…
…
…
0.3
1.9
2.9

1.7
3.8
7.0
-1.2
0.7
0.9
-3.0
3.5

1990
1999
2000
2001
2002
2003
2004
2005
2006

1 400
1 402
1 327
1 327
1 300
1 324
1 352
1 365
1 396

1 397
1 454
1 364
1 359
1 294
1 331
1 357
1 346
1 396

6.6
9.4
10.0
10.8
14.7
11.2
10.0
7.6
…

44.0
5.4
8.6
8.4
14.6
9.3
2.8
9.9
12.5

1990-1999
2000
2001
2002
2003
2004
2005
2006

0.0
-5.3
0.0
-2.0
1.8
2.1
0.9
2.3

0.4
-6.2
-0.4
-4.8
2.9
2.0
-0.8
3.6

1.3
1.3
1.4
-5.0
-0.8
1.7
1.1
0.6

-1.3
4.3
3.7
-0.7
2.8
-3.3
2.0
2.2

7.6 c
10.7 c
7.8
11.3
11.6
10.2
9.3
7.0
…

Socio-economic
context

Table 1 (continued)
TRENDS IN SELECTED ECONOMIC INDICATORS, 1990-2006

290

Economic Commission for Latin America and the Caribbean (ECLAC)

Socio-economic
context

Table 1 (concluded)
TRENDS IN SELECTED ECONOMIC INDICATORS, 1990-2006
Country

Peru

Year

Per capita
GDP
(in 2000
dollars)

Per capita
Urban
Annual variation
income unemployment in consumer
(in 2000 (percentage)
prices
dollars) a

1990
1999
2000
2001
2002
2003
2004
2005
2006

1 649
2 047
2 079
2 057
2 137
2 194
2 281
2 400
2 563

1 595
2 043
2 063
2 039
2 115
2 165
2 245
2 385
2 638

8.3
9.2
8.5
9.3
9.4
9.4
9.4
9.6
8.5

Dominican
Republic

1990
1999
2000
2001
2002
2003
2004
2005
2006

1 717
2 526
2 679
2 696
2 786
2 731
2 760
2 970
3 239

1 684
2 667
2 778
2 814
2 929
2 762
2 759
2 964
3 237

…
13.8 c
13.9 c
15.6 c
16.1 c
16.7 c
18.4 c
18.0 c
16.4 c

Uruguay

1990
1999
2000
2001
2002
2003
2004
2005
2006

4 802
6 174
6 061
5 845
5 200
5 317
5 949
6 341
6 770

4 852
6 144
6 051
5 853
5 247
5 163
5 743
6 071
6 483

8.5
11.3
13.6
15.3
17.0
16.9
13.1
12.2
11.6

Venezuela
(Bol. Rep. of)

1990
1999
2000
2001
2002
2003
2004
2005
2006

4 828
4 738
4 822
4 894
4 381
3 970
4 615
5 005
5 430

4 522
4 218
4 758
4 569
4 102
3 844
4 667
5 556
6 318

Latin
America d

1990
1999
2000
2001
2002
2003
2004
2005
2006

3 405
3 877
3 970
3 926
3 855
3 886
4 074
4 208
4 384

3 301
3 772
3 901
3 833
3 768
3 812
4 037
4 223
4 465

Average annual variations in the period
Period

Per capita
GDP

Per capita
income a

Mean real
remuneration

Urban
minimum
wage

7 646.8
3.7
3.7
-0.1
1.5
2.5
3.5
1.5
1.1

1990-1999
2000
2001
2002
2003
2004
2005
2006

2.4
1.6
-1.1
3.9
2.7
4.0
5.2
6.8

2.8
1.0
-1.2
3.7
2.4
3.7
6.3
10.6

0.6
0.8
-0.9
4.6
1.6
1.1
-1.9
1.2

2.3
11.1
1.2
-0.2
1.2
4.6
-1.6
6.6

79.9
7.8
9.0
4.4
10.5
42.7
28.7
7.4
5.0

1990-1999
2000
2001
2002
2003
2004
2005
2006

4.4
6.1
0.6
3.3
-2.0
1.1
7.6
9.1

5.2
4.1
1.3
4.1
-5.7
-0.1
7.4
9.2

…
…
…
…
…
-24.2
16.7
…

2.6
-0.4
5.7
-0.5
-9.2
-15.0
18.7
-7.1

128.9
4.2
5.1
3.6
25.9
10.2
7.6
4.9
6.4

1990-1999
2000
2001
2002
2003
2004
2005
2006

2.8
-1.8
-3.6
-11.0
2.2
11.9
6.6
6.8

2.7
-1.5
-3.3
-10.4
-1.6
11.2
5.7
6.8

1.4
-1.3
-0.3
-10.7
-12.5
0.0
4.6
4.3

-5.3
-1.6
-1.3
-10.1
-12.4
-0.2
70.2
16.1

10.4 c
15.0 c
13.9 c
13.3 c
15.8 c
18.0 c
15.3 c
12.4 c
9.8 c

36.5
20.0
13.4
12.3
31.2
27.1
19.2
14.4
17.0

1990-1999
2000
2001
2002
2003
2004
2005
2006

-0.2
1.8
1.5
-10.5
-9.4
16.2
8.5
8.5

-0.8
12.8
-4.0
-10.2
-6.3
21.4
19.0
13.7

-3.9
4.0
6.9
-11.0
-17.6
0.2
2.6
5.1

-0.8
3.8
-0.0
-5.4
-11.9
11.3
11.8
9.9

7.3
11.0
10.4
10.2
11.0
11.0
10.3
9.1
8.7

…
9.7
9.0
6.1
12.2
8.5
7.4
6.1
4.8

1990-1999
2000
2001
2002
2003
2004
2005
2006

1.5
2.4
-1.1
-1.8
0.8
4.8
3.3
4.2

1.5
3.4
-1.7
-1.7
1.2
5.9
4.6
5.8

1.0
1.7
0.3
-1.5
-4.1
1.4
0.4
2.8

2.2
2.2
4.5
0.2
1.4
5.3
5.6
6.8

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the relevant countries.
a Real per capita gross national income.
b The figures for per capita GDP and per capita available income are unofficial estimates calculated by ECLAC. According to information supplied by the
Government of Cuba, in 2005, the Cuban economy grew by 11.8% in per capita GDP terms. This growth rate was calculated using a new methodology
currently being studied by ECLAC and the Government of Cuba.
c Nationwide total.
d The aggregate figures for Latin America are obtained from weighted averages for all countries for which data are available in each indicator.

Social Panorama of Latin America • 2007

Table 2
TOTAL REGIONAL POPULATION BY COUNTRY OR TERRITORY, 1980-2010
(Thousands at mid-year)
Country or territory
Argentina

1980

1985

1990

1995

2000

2005

174

182

191

191

181

186

199

28 094

Netherlands Antilles

2010

30 305

32 581

34 779

36 784

38 592

40 519

Bahamas

210

233

255

280

303

323

343

Barbados

249

260

271

280

286

292

297

Belize

144

163

186

214

245

276

306

Bolivia

5 355

5 964

6 669

7 482

8 428

9 427

10 426
199 992

Brazil

121 672

136 178

149 690

162 019

174 719

187 601

Chile

11 174

12 102

13 179

14 395

15 398

16 267

17 094

Colombia

28 356

31 564

34 875

38 259

41 661

44 907

47 859

Costa Rica

2 347

2 697

3 076

3 475

3 925

4 322

4 695

Cuba

9 823

10 086

10 605

10 930

11 129

11 242

11 236

73

72

69

69

68

68

67

Ecuador

Dominica

7 961

9 099

10 272

11 396

12 297

13 211

14 200

El Salvador

4 586

4 769

5 110

5 669

6 276

6 874

7 453

89

100

96

98

100

105

105

327

355

391

406

421

438

454

7 013

7 935

8 908

10 004

11 225

12 700

14 362

761

754

731

739

734

739

731

68

88

116

139

164

187

208
10 085

Granada
Guadeloupe
Guatemala
Guyana
French Guiana
Haiti

5 691

6 388

7 108

7 836

8 576

9 292

Honduras

3 634

4 236

4 901

5 588

6 231

6 893

7 614

Jamaica

2 133

2 297

2 369

2 485

2 589

2 682

2 756

Martinique

326

341

360

375

386

396

402

69 325

76 826

84 002

91 823

99 684

104 159

110 056

Nicaragua

3 257

3 715

4 141

4 664

5 106

5 457

5 825

Panama

1 949

2 176

2 411

2 670

2 948

3 228

3 497

Mexico

Paraguay

3 198

3 702

4 248

4 799

5 346

5 899

6 451

17 325

Peru

19 523

21 762

23 857

25 650

27 254

28 861

Puerto Rico

3 197

3 378

3 528

3 696

3 834

3 947

4 056

Dominican Republic

5 935

6 609

7 296

8 014

8 740

9 465

10 169

Saint Lucia

118

127

138

146

153

161

171

Suriname

356

383

402

416

436

452

465

Trinidad and Tobago

1 082

1 179

1 224

1 270

1 301

1 324

1 348

Uruguay

2 914

3 009

3 106

3 218

3 314

3 317

3 363

15 091

17 317

19 731

22 034

24 296

26 556

28 807

364 007

404 109

443 997

483 716

522 935

558 239

594 472

Venezuela (Bol. Rep. of)
Regional total

a

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, population estimates and projections database,
2006 revision, Santiago, Chile; United Nations Population Division, World Population Prospects: The 2006 Revision (ST/ESA/SER.A/266) [CD-ROM]
a

Includes 20 countries: Argentina, Bolivarian Republic of Venezuela, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador,
El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, and Uruguay.

Socio-economic
context

291

292

Economic Commission for Latin America and the Caribbean (ECLAC)

Socio-economic
context

Table 2.1
ESTIMATED TOTAL POPULATION GROWTH RATES BY FIVE-YEAR PERIOD, 1980-2010
(Rates per thousand)
Country

1980-1985

1985-1990

1990-1995

1995-2000

2000-2005

2005-2010

9.0

9.7

0.0

-10.8

5.4

13.5

Argentina

15.2

14.5

13.1

11.2

9.6

9.7

Bahamas

20.8

18.0

18.7

15.8

12.8

12.0

Netherlands Antilles

Barbados
Belize

8.6

8.3

6.5

4.2

4.2

3.4

24.8

26.4

28.0

27.1

23.8

20.6

Bolivia

21.5

22.3

23.0

23.8

22.4

20.1

Brazil

22.5

18.9

15.8

15.1

14.2

12.8

Chile

16.0

17.1

17.7

13.5

11.0

9.9

Colombia

21.4

19.9

18.5

17.0

15.0

12.7

Costa Rica

27.8

26.3

24.4

24.4

19.3

16.6

5.3

10.0

6.0

3.6

2.0

-0.1

Dominica

-2.8

-8.5

0.0

-2.9

0.0

-3.0

Ecuador

26.7

24.3

20.8

15.2

14.4

14.4

Cuba

El Salvador

7.8

13.8

20.7

20.4

18.2

16.2

Granada

23.3

-8.2

4.1

4.0

9.8

0.0

Guadeloupe

16.5

19.2

7.7

7.3

7.9

7.2

Guatemala

24.7

23.1

23.2

23.0

24.7

24.6

-1.8

-6.2

2.2

-1.4

1.4

-2.2

French Guiana

Guyana

50.8

55.8

34.9

34.1

25.3

21.8

Haiti

23.1

21.4

19.5

18.0

16.0

16.4

Honduras

30.6

29.2

26.2

21.8

20.2

19.9

Jamaica

14.8

6.2

9.6

8.2

7.1

5.4

8.6

11.3

8.0

5.6

5.3

3.0

Martinique
Mexico

20.5

17.9

17.8

16.4

8.8

11.0

Nicaragua

26.3

21.7

23.8

18.1

13.3

13.0

Panama

22.0

20.5

20.4

19.8

18.2

16.0

Paraguay

29.3

27.5

24.4

21.6

19.7

17.9

Peru

23.9

21.7

18.4

14.5

12.1

11.5

Puerto Rico

11.0

8.7

9.3

7.3

5.8

5.4

Dominican Republic

21.5

19.8

18.8

17.3

15.9

14.3

Saint Lucia

14.7

16.6

11.3

9.4

10.2

12.1

Suriname

14.6

9.7

6.8

9.4

7.2

5.7

Trinidad and Tobago

17.2

7.5

7.4

4.8

3.5

3.6

6.4

6.3

7.1

5.9

0.2

2.7

Venezuela (Bol. Rep. of)

Uruguay

27.5

26.1

22.1

19.5

17.8

16.3

Regional total a

20.9

18.8

17.1

15.6

13.1

12.6

Source: Figures based on table 2 of the statistical appendix.
a

Includes 20 countries: Argentina, Bolivarian Republic of Venezuela, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador,
El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, and Uruguay.

Social Panorama of Latin America • 2007

Table 2.2
ESTIMATED GLOBAL FERTILITY RATES BY COUNTRY AND FIVE-YEAR PERIOD, 1980-2010
(Children per woman)
Country

1980-1985

1985-1990

1990-1995

1995-2000

2000-2005

Netherlands Antilles

2.36

2.30

2.28

2.12

2.06

2005-2010
1.85

Argentina

3.15

3.05

2.90

2.63

2.35

2.25

Bahamas

3.16

2.62

2.60

2.40

2.11

2.02

Barbados

1.92

1.75

1.60

1.50

1.50

1.50

Belize

5.40

4.70

4.35

3.85

3.35

2.94

Bolivia

5.30

5.00

4.80

4.32

3.96

3.50

Brazil

3.80

3.10

2.60

2.45

2.34

2.25

Chile

2.67

2.65

2.55

2.21

2.00

1.94

Colombia

3.69

3.17

2.93

2.70

2.47

2.22
2.10

Costa Rica

3.53

3.37

2.95

2.58

2.28

Cuba

1.85

1.85

1.65

1.61

1.63

1.49

Ecuador

4.70

4.00

3.40

3.10

2.82

2.58
2.68

El Salvador

4.50

3.90

3.52

3.17

2.88

Guadeloupe

2.55

2.45

2.10

2.10

2.06

2.11

Guatemala

6.10

5.70

5.45

5.00

4.60

4.15

Guyana

3.26

2.70

2.55

2.50

2.43

2.33

French Guiana

3.58

3.73

4.05

3.93

3.68

3.27

Haiti

6.21

5.70

5.15

4.62

4.00

3.54

Honduras

6.00

5.37

4.92

4.30

3.72

3.31
2.43

Jamaica

3.55

3.10

2.84

2.67

2.63

Martinique

2.14

2.14

1.96

1.90

1.98

1.91

Mexico

4.25

3.63

3.19

2.67

2.40

2.21

Nicaragua

5.85

5.00

4.50

3.60

3.00

2.76

Panama

3.52

3.20

2.87

2.79

2.70

2.56

Paraguay

5.20

4.77

4.31

3.88

3.48

3.08

Peru

4.65

4.10

3.70

3.10

2.70

2.51

Puerto Rico

2.46

2.26

2.18

1.99

1.84

1.83

Dominican Republic

4.00

3.47

3.20

3.05

2.95

2.81

Saint Lucia

4.20

3.65

2.99

2.36

2.24

2.18

Suriname

3.70

3.00

2.60

2.80

2.60

2.42

Trinidad and Tobago

3.22

2.80

2.10

1.73

1.61

1.64

Uruguay

2.57

2.53

2.49

2.30

2.20

2.12

Venezuela (Bol. Rep. of)

3.96

3.65

3.25

2.94

2.72

2.55

Regional total a

3.94

3.42

3.02

2.76

2.57

2.43

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, population estimates and projections database,
2006 revision, Santiago, Chile; United Nations Population Division, World Population Prospects: The 2006 Revision (ST/ESA/SER.A/266) [CD-ROM]
a

Includes 20 countries: Argentina, Bolivarian Republic of Venezuela, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador,
El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, and Uruguay.

Socio-economic
context

293

294

Economic Commission for Latin America and the Caribbean (ECLAC)

Socio-economic
context

Table 2.3
LIFE EXPECTANCY AT BIRTH, BOTH SEXES, BY FIVE-YEAR PERIOD, BY COUNTRY, 1980-2010
(Number of years)
Country

1980-1985

1985-1990

1990-1995

1995-2000

2000-2005

Netherlands Antilles

73.8

74.5

74.5

74.6

75.0

2005-2010
75.1

Argentina

70.2

71.0

72.1

73.2

74.3

75.2
73.5

Bahamas

67.9

69.5

69.2

68.5

71.1

Barbados

72.7

74.0

74.9

74.9

76.0

77.3

Belize

71.0

71.9

72.5

74.4

75.6

76.1

Bolivia

53.9

57.3

60.0

62.0

63.8

65.5

Brazil

63.6

65.5

67.5

69.4

71.0

72.4

Chile

70.7

72.7

74.3

75.7

77.7

78.5

Colombia

66.8

68.0

68.7

70.3

71.6

72.8

Costa Rica

73.8

75.2

76.2

77.3

78.1

78.8

Cuba

74.3

74.6

74.8

76.2

77.1

78.3
75.0

Ecuador

64.5

67.5

70.0

72.3

74.2

El Salvador

57.1

63.4

67.1

69.4

70.6

71.8

Guadeloupe

72.5

73.6

75.9

77.3

78.4

79.2

Guatemala

58.3

60.9

63.6

66.3

68.9

70.2

Guyana

60.9

61.8

62.5

62.1

63.6

66.8

French Guiana

69.4

71.2

72.8

74.2

75.1

75.9

Haiti

51.5

53.6

55.2

56.9

58.1

60.6

Honduras

61.6

65.4

67.7

69.8

71.0

72.0

Jamaica

71.2

71.8

71.8

72.3

72.0

72.6
79.5

Martinique

73.7

75.4

76.4

77.7

78.8

Mexico

67.7

69.8

71.8

73.6

74.8

76.1

Nicaragua

59.5

62.2

66.0

68.4

70.8

72.9
75.6

Panama

70.8

71.9

72.9

73.8

74.7

Paraguay

67.0

67.6

68.5

69.4

70.8

71.8

Peru

61.6

64.4

66.7

68.4

69.9

71.4

Puerto Rico

73.8

74.6

73.9

74.9

77.8

78.7

Dominican Republic

64.0

66.6

69.1

70.1

71.2

72.2

Saint Lucia

70.5

71.0

71.3

71.5

72.5

73.7

Suriname

67.6

68.2

68.6

69.0

69.1

70.2
69.8

Trinidad and Tobago

68.8

69.6

69.9

69.5

69.0

Uruguay

71.0

72.1

73.0

74.1

75.2

76.2

Venezuela (Bol. Rep. of)

68.8

70.5

71.5

72.2

72.8

73.8

Regional total a

65.4

67.3

69.0

70.6

71.9

73.0

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, population estimates and projections database,
2006 revision, Santiago, Chile; United Nations Population Division, World Population Prospects: The 2006 Revision (ST/ESA/SER.A/266) [CD-ROM]
a

 Includes 20 countries: Argentina, Bolivarian Republic of Venezuela, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador,
El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, and Uruguay.

Social Panorama of Latin America • 2007

Table 2.4
ESTIMATED INFANT MORTALITY RATES BOTH SEXES, BY FIVE-YEAR PERIOD, 1980-2010
(Deaths of children under the age of one year per thousand live births)
Country

1980-1985

1985-1990

1990-1995

1995-2000

2000-2005

2005-2010

Netherlands Antilles

18.0

17.0

15.1

15.5

15.0

14.8

Argentina

32.2

27.1

24.4

21.8

15.0

13.4

Bahamas

30.4

24.4

21.3

17.5

15.3

13.8

Barbados

19.3

16.1

14.0

13.6

12.3

10.1

Belize

39.3

35.9

29.3

23.3

18.5

16.4

Bolivia

109.2

90.1

75.1

66.7

55.6

45.6

Brazil

63.3

52.4

42.5

34.1

27.3

23.6

Chile

23.7

18.4

14.1

11.5

8.0

7.2

Colombia

43.0

35.3

27.6

24.0

20.5

19.1

Costa Rica

19.2

17.4

14.5

11.8

10.5

9.9

Cuba

17.4

15.9

15.3

9.6

6.1

5.1

Ecuador

68.5

55.5

44.2

33.3

24.9

21.1

El Salvador

77.0

54.0

40.2

32.0

26.4

21.5

Guadeloupe

24.7

22.0

9.2

8.3

7.3

6.8

Guatemala

79.3

67.1

54.8

45.5

38.6

30.1

Guyana

69.5

67.0

62.6

57.5

49.4

42.9

French Guiana

32.0

25.0

19.9

16.4

14.8

13.4

122.1

100.1

85.3

70.1

56.1

48.6

Honduras

65.0

53.0

43.0

35.0

31.2

27.8

Jamaica

30.5

27.0

16.8

15.7

14.9

14.1

Haiti

Martinique

14.0

10.1

9.4

8.0

7.0

6.6

Mexico

47.0

39.5

33.1

27.7

20.5

16.7

Nicaragua

79.8

65.0

48.0

33.6

26.4

21.5

Panama

31.6

29.6

27.0

23.7

20.6

18.2

Paraguay

48.9

46.7

42.9

39.2

35.5

32.0

Peru

81.6

68.0

47.6

38.8

30.3

21.2

Puerto Rico

17.2

13.8

11.6

10.9

8.1

7.2

Dominican Republic

75.2

62.9

47.6

41.3

34.9

29.6

Saint Lucia

22.7

20.1

16.8

16.7

14.6

12.6

Suriname

38.7

35.9

34.8

33.5

31.8

27.7

Trinidad and Tobago

19.2

16.6

15.1

16.1

15.1

12.4

Uruguay

33.5

22.6

20.1

15.6

14.4

13.1

Venezuela (Bol. Rep. of)

33.6

26.9

23.1

20.7

18.9

17.0

57.5

47.5

39.2

33.0

27.7

24.2

Regional total

a

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, population estimates and projections database,
2006 revision, Santiago, Chile; United Nations Population Division, World Population Prospects: The 2006 Revision (ST/ESA/SER.A/266) [CD-ROM]
a

Includes 20 countries: Argentina, Bolivarian Republic of Venezuela, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador,
El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, and Uruguay.

Socio-economic
context

295

Socio-economic
context

296

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 3
TRENDS IN SELECTED SOCIAL DEVELOPMENT INDICATORS, 1980-2010
Country

Five-year
periods

Life expectancy at birth
(years of life)

Both
sexes

Males

Females

Under-five mortality rate
(per 1 000 live births)
Both
sexes

Males

Females

Illiteracy rate in population
aged 15 and over
(percentage)

Both
sexes

Males

1980-1985

70.2

66.8

73.7

32

36

29

37

41

34

5.6

5.3

6.0

1985-1990

Argentina

Females

Infant mortality
(per 1 000 live births)

Both
sexes

Males

Females

71.0

67.6

74.6

27

30

24

32

35

29

4.3

4.1

4.4

1990-1995

68.6

75.8

24

27

22

28

31

25

3.7

3.6

3.7

73.2

69.7

77.0

22

24

19

24

27

22

3.2

3.2

3.2

2000-2005

74.3

70.6

78.1

15

17

13

18

20

15

2.8

2.8

2.7

2005-2010

75.2

71.6

79.1

13

15

12

16

17

14

2.4

2.5

2.4

1980-1985

53.9

52.0

55.9

109

116

102

163

174

153

31.3

20.4

41.7

1985-1990

Bolivia

72.1

1995-2000

57.3

55.6

59.1

90

96

84

127

134

120

21.9

13.2

30.2

1990-1995

60.0

58.3

61.8

75

79

71

99

103

95

17.9

10.4

25.2

1995-2000

62.0

60.1

64.0

67

70

63

85

89

81

14.6

8.1

20.8

2000-2005

Brazil

63.8

61.8

66.0

56

60

51

71

76

67

11.7

6.2

17.0

2005-2010

65.5

63.4

67.7

46

50

41

60

65

56

9.4

4.8

13.8
25.9

1980-1985

63.6

60.4

66.9

64

70

56

77

85

70

24.0

22.0

1985-1990

65.5

62.0

69.2

53

59

46

65

73

58

18.0

17.1

18.8

1990-1995

67.5

63.7

71.5

43

48

36

54

61

47

15.3

14.9

15.7

1995-2000

65.7

73.3

34

39

29

42

48

37

13.1

13.0

13.2

71.0

67.3

74.9

27

31

24

34

38

29

11.1

11.3

11.0

2005-2010
Chile

69.4

2000-2005

72.4

68.9

76.1

24

27

20

29

33

25

9.6

10.0

9.3

1980-1985

70.7

67.4

74.2

24

26

22

28

30

26

8.6

7.7

9.5

1985-1990

72.7

69.6

75.9

18

20

17

22

24

20

6.0

5.6

6.4

1990-1995

74.3

71.5

77.4

14

15

13

17

19

15

5.1

4.8

5.3

1995-2000

75.7

72.8

78.8

12

13

10

14

15

12

4.2

4.1

4.4

2000-2005

Colombia

77.7

74.8

80.8

8

9

7

10

11

9

3.5

3.4

3.6

2005-2010

78.5

75.5

81.5

7

8

6

9

10

8

2.9

2.8

2.9
16.8

66.8

63.6

70.2

43

47

38

60

65

54

16.0

15.1

68.0

64.5

71.7

35

39

31

48

53

44

11.6

11.2

11.9

1990-1995

68.7

64.5

73.0

28

31

24

38

42

34

9.9

9.7

10.0

1995-2000

70.3

66.5

74.2

24

27

21

33

37

29

8.4

8.4

8.4

2000-2005

71.6

68.0

75.4

21

23

17

29

32

25

7.1

7.2

6.9

2005-2010
Costa Rica

1980-1985
1985-1990

72.8

69.2

76.6

19

22

16

26

30

23

5.9

6.1

5.7

73.8

71.6

76.1

19

21

17

24

26

21

8.3

8.1

8.5

75.2

72.9

77.5

17

20

15

20

23

18

6.1

6.1

6.2

1990-1995

76.2

74.0

78.6

15

16

13

17

19

15

5.2

5.3

5.2

1995-2000

77.3

75.0

79.7

12

13

10

14

16

12

4.4

4.5

4.4

2000-2005

78.1

75.8

80.6

11

12

9

12

14

11

3.8

3.9

3.7

2005-2010
Cuba

1980-1985
1985-1990

78.8

76.5

81.2

10

11

9

12

13

10

3.2

3.3

3.0

1980-1985

74.3

72.6

76.0

17

19

16

21

23

20

7.5

7.5

7.5

1985-1990

74.6

72.8

76.6

16

18

14

19

22

17

4.9

4.8

4.9

1990-1995

74.8

72.9

76.7

15

17

13

19

21

16

4.1

4.0

4.2

1995-2000

76.2

74.2

78.2

10

11

8

12

14

10

3.3

3.2

3.4

2000-2005

77.1

75.3

79.1

6

7

5

8

8

7

2.7

2.6

2.8

2005-2010

78.3

76.2

80.4

5

6

5

6

7

6

2.1

1.9

2.2

Social Panorama of Latin America • 2007

Table 3 (continued)
TRENDS IN SELECTED SOCIAL DEVELOPMENT INDICATORS, 1980-2010
Country

Five-year
periods

Life expectancy at birth
(years of life)
Both
sexes

Ecuador

Males

Females

Infant mortality
(per 1 000 live births)
Both
sexes

Males

Under-five mortality rate
(per 1 000 live births)

Females

Both
sexes

Males

Females

Illiteracy rate in population
aged 15 and over
(percentage)
Both
sexes

Males

Females

22.0

1980-1985

64.5

62.5

66.7

69

76

61

94

102

86

18.1

14.2

1985-1990

67.5

65.3

69.9

56

62

49

74

81

67

12.4

9.8

14.9

1990-1995

70.0

67.6

72.6

44

50

39

57

63

51

10.2

8.2

12.3
10.1

1995-2000

69.7

75.1

33

37

29

41

46

36

8.4

6.8

74.2

71.3

77.2

25

29

21

30

35

25

7.0

5.6

8.3

2005-2010
El Salvador

72.3

2000-2005

75.0

72.1

78.0

21

24

18

26

29

22

5.8

4.7

6.9

1980-1985

57.1

50.8

63.8

77

83

71

118

123

113

34.2

29.4

38.7

1985-1990

63.4

59.0

68.0

54

60

48

77

82

72

27.6

23.9

30.9

1990-1995

63.3

71.0

40

44

36

51

57

45

24.1

20.9

27.1

69.4

66.5

72.5

32

35

29

41

45

37

21.3

18.5

23.9

2000-2005

70.6

67.7

73.7

26

29

24

35

38

32

18.9

16.4

21.2

2005-2010
Guatemala

67.1

1995-2000

71.8

68.8

74.9

22

23

20

29

32

27

16.6

14.4

18.6

1980-1985

58.3

56.1

60.6

79

84

75

118

121

115

47.0

39.0

55.1

1985-1990

60.9

58.3

63.7

67

72

62

96

99

92

39.0

31.2

46.8

1990-1995

63.6

60.5

66.8

55

60

50

74

78

70

35.1

27.4

42.7

1995-2000

66.3

62.9

70.0

46

51

40

59

64

53

31.5

24.0

38.9

2000-2005

Haiti

68.9

65.5

72.5

39

44

33

48

55

42

28.2

20.9

35.4

2005-2010

70.2

66.7

73.8

30

35

25

39

45

34

25.2

18.3

32.1

1980-1985

51.5

50.2

52.9

122

128

116

172

178

165

69.5

65.9

72.8

1985-1990

53.6

52.2

55.0

100

105

95

146

151

140

60.3

57.4

63.1

1990-1995

55.2

53.7

56.8

85

90

80

126

132

121

55.3

52.7

57.7

1995-2000

56.9

55.2

58.6

70

74

66

107

112

102

50.2

48.0

52.2

2000-2005

Honduras

58.1

56.4

59.9

56

61

51

93

98

87

45.2

43.5

46.8

2005-2010

60.6

59.0

62.4

49

52

45

80

85

76

41.1

39.8

42.3

1980-1985

61.6

59.4

63.8

65

72

58

101

109

92

40.1

38.1

42.0

1985-1990

65.4

63.2

67.7

53

59

47

74

81

67

31.9

31.1

32.7

1990-1995

65.4

70.1

43

48

38

60

66

54

28.3

28.0

28.6

69.8

67.5

72.3

35

40

30

50

55

44

25.0

25.1

25.0

2000-2005

71.0

68.6

73.4

31

36

27

45

50

39

22.0

22.4

21.7

2005-2010
Mexico

67.7

1995-2000

72.0

69.7

74.5

28

32

24

40

45

35

19.4

20.0

18.8
23.5

1980-1985

67.7

64.4

71.2

47

53

41

57

64

51

18.7

13.7

1985-1990

69.8

66.8

73.0

40

43

36

48

53

44

12.7

9.4

15.7

1990-1995

71.8

69.0

74.6

33

36

31

40

44

37

10.5

7.9

13.0

1995-2000

71.3

76.1

28

30

25

33

36

30

8.8

6.7

10.9

74.8

72.4

77.4

21

23

18

25

28

22

7.4

5.7

9.1

2005-2010
Nicaragua

73.6

2000-2005

76.1

73.7

78.6

17

19

15

20

23

18

6.2

4.8

7.6
41.4

1980-1985

59.5

56.5

62.6

80

88

72

117

128

106

41.2

41.0

1985-1990

62.2

59.0

65.5

65

72

58

90

98

82

37.3

37.3

37.2

1990-1995

66.0

63.5

68.7

48

54

42

62

69

54

35.4

35.5

35.2
33.3

1995-2000

68.4

65.9

71.1

34

37

30

44

48

39

33.5

33.8

2000-2005

70.8

68.0

73.8

27

30

23

32

36

28

31.9

32.2

31.6

2005-2010

72.9

69.9

76.0

22

24

19

26

29

23

30.3

30.7

29.9

Socio-economic
context

297

Socio-economic
context

298

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 3 (concluded)
TRENDS IN SELECTED SOCIAL DEVELOPMENT INDICATORS, 1980-2010
Country

Five-year
periods

Life expectancy at birth
(years of life)
Both
sexes

Panama

Males

Females

Infant mortality
(per 1 000 live births)
Both
sexes

Males

Females

Under-five mortality rate
(per 1 000 live births)
Both
sexes

Males

Females

Illiteracy rate in population
aged 15 and over
(percentage)
Both
sexes

Males

Females

1980-1985

70.8

68.4

73.3

32

36

27

43

48

38

15.1

14.4

1985-1990

71.9

69.3

74.6

30

34

25

38

43

33

11.0

10.3

15.9
11.6

1990-1995

72.9

70.2

75.7

27

31

23

34

38

29

9.4

8.8

10.1
8.8

1995-2000

71.3

76.4

24

28

20

30

34

26

8.1

7.5

74.7

72.3

77.4

21

24

17

27

31

23

7.0

6.4

7.6

2005-2010
Paraguay

73.8

2000-2005

75.6

73.0

78.2

18

21

15

24

27

20

6.0

5.4

6.6

67.0

64.9

69.3

49

55

43

64

72

56

14.1

10.5

17.6

67.6

65.4

69.9

47

52

41

61

69

53

9.7

7.6

11.7

1990-1995

68.5

66.3

70.8

43

48

37

54

62

47

8.1

6.6

9.6

1995-2000

69.4

67.2

71.7

39

44

34

48

55

42

6.7

5.6

7.8

2000-2005

70.8

68.7

72.9

36

40

30

42

49

36

5.6

4.8

6.4

2005-2010
Peru

1980-1985
1985-1990

71.8

69.7

73.9

32

37

27

38

44

33

4.7

4.1

5.3

1980-1985

61.6

59.5

63.8

82

88

75

117

124

109

20.6

11.7

29.4

1985-1990

64.4

62.1

66.8

68

75

61

94

102

86

14.5

8.0

20.9

1990-1995

64.4

69.2

48

53

42

75

83

66

12.2

6.6

17.6

68.4

66.0

70.9

39

43

34

57

63

51

10.1

5.3

14.8

2000-2005

69.9

67.5

72.5

30

34

27

40

44

37

8.4

4.4

12.3

2005-2010
Dominican
Republic

66.7

1995-2000

71.4

68.9

74.0

21

24

18

29

31

27

7.0

3.5

10.3

1980-1985

64.0

62.1

66.1

75

82

69

86

93

79

26.0

24.9

27.2

1985-1990

66.6

64.3

69.0

63

69

56

71

78

65

20.6

20.2

21.0

1990-1995

69.1

66.5

71.9

48

53

42

55

61

49

18.3

18.2

18.5

1995-2000

70.1

67.3

73.1

41

47

36

46

52

41

16.3

16.3

16.3

2000-2005

Uruguay

71.2

68.1

74.4

35

40

30

38

43

33

14.5

14.7

14.4

2005-2010

72.2

69.2

75.5

30

34

25

33

37

28

12.9

13.2

12.6

1980-1985

71.0

67.6

74.5

34

37

30

37

41

34

5.0

5.4

4.6

1985-1990

72.1

68.6

75.8

23

25

20

26

29

23

3.5

4.0

3.0

1990-1995

69.2

76.9

20

23

18

23

26

20

2.9

3.4

2.5

74.1

70.5

78.0

16

17

14

18

21

16

2.4

2.9

2.0

2000-2005

75.2

71.6

78.9

14

16

13

17

19

15

2.0

2.5

1.6

2005-2010
Venezuela
(Bol.
Rep. of)

73.0

1995-2000

76.2

72.8

79.9

13

14

12

16

17

14

1.7

2.1

1.3

1980-1985

68.8

65.8

71.8

34

38

29

43

47

38

16.1

13.9

18.3

1985-1990

70.5

67.7

73.5

27

30

23

34

38

30

11.1

9.9

12.3

1990-1995

71.5

68.7

74.5

23

26

20

29

33

26

9.1

8.3

9.9

1995-2000

72.2

69.3

75.2

21

23

18

26

29

24

7.5

7.0

8.0

2000-2005

72.8

69.9

75.8

19

21

16

24

27

21

6.0

5.8

6.2

2005-2010

73.8

70.9

76.8

17

19

15

22

25

19

4.8

4.8

4.9

Source: Latin American and Caribbean Demographic Centre (CELADE) – Population Division of ECLAC, population estimates and projections database,
2006 revision, Santiago, Chile; UNESCO Institute for Statistics (UIS) database (literacy) [online].

Social Panorama of Latin America • 2007

299

Poverty and income distribution
Table 4
POVERTY AND INDIGENCE LEVELS, 1990-2006
(Percentages)
Population below the poverty line a

Year
Country
total

Urban areas
Total

Metropolitan
Other
area
urban areas

Population below the indigence line
Rural
areas

Country
total

Urban areas
Total

Metropolitan
Other
area
urban areas

Rural
areas

Argentina

1990
1994
1997
1999
2002
2004
2005
2006

…
…
…
…
…
…
…
…

…
16.1
…
23.7
45.4
29.4
26.0
21.0

21.2
13.2
17.8
19.7
41.5
25.9
22.6
19.3

…
21.2
…
28.5
49.6
33.6
30.0
22.8

…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…

…
3.4
…
6.7
20.9
11.1
9.1
7.2

5.2
2.6
4.8
4.8
18.6
9.6
7.6
6.7

…
4.9
…
8.8
23.3
12.9
10.8
7.9

…
…
…
…
…
…
…
…

Bolivia

1989
1994
1997
1999
2002
2004

…
…
62.1
60.6
62.4
63.9

52.6
51.6
52.3
48.7
52.0
53.8

…
…
…
45.0
48.0
50.5

…
…
…
63.9
58.2
60.4

…
…
78.5
80.7
79.2
80.6

…
…
37.2
36.4
37.1
34.7

23.0
19.8
22.6
19.8
21.3
20.2

…
…
…
17.5
18.8
17.3

…
…
…
29.0
25.0
26.0

…
…
61.5
64.7
62.9
58.8

Brazil

1990
1993
1996
1999
2001
2003
2004
2005
2006

48.0
45.3
35.8
37.5
37.5
38.7
37.7
36.3
33.3

41.2
40.3
30.6
32.9
34.1
35.7
34.3
32.8
29.9

…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…

70.6
63.0
55.6
55.3
55.2
54.5
54.1
53.2
50.1

23.4
20.2
13.9
12.9
13.2
13.9
12.1
10.6
9.0

16.7
15.0
9.6
9.3
10.4
11.4
9.7
8.2
6.7

…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…

46.1
38.8
30.2
27.1
28.0
27.5
24.0
22.1
20.5

Chile

1990
1994
1996
1998
2000
2003
2006

38.6
27.6
23.2
21.7
20.2
18.7
13.7

38.5
27.0
22.0
20.7
19.7
18.5
13.9

32.1
18.4
13.4
14.6
14.4
12.4
10.4

43.5
33.4
27.8
25.0
23.4
22.7
16.0

38.8
31.1
30.4
27.5
23.7
20.0
12.3

13.0
7.6
5.7
5.6
5.6
4.7
3.2

12.5
7.1
5.1
5.1
5.1
4.4
3.2

9.3
4.2
2.4
3.3
3.9
2.8
2.3

14.9
9.3
6.9
6.4
6.0
5.6
3.7

15.6
9.9
9.4
8.6
8.4
6.2
3.5

Colombia b

1991
1994
1997
1999
2002
2004
2005

56.1
52.5
50.9
54.9
51.1
51.1
46.8

52.7
45.4
45.0
50.6
50.6
49.8
45.4

…
37.6
33.5
43.1
39.8
37.5
33.8

…
48.2
48.9
53.1
53.8
53.2
48.6

60.7
62.4
60.1
61.8
52.0
54.8
50.5

26.1
28.5
23.5
26.8
24.6
24.2
20.2

20.0
18.6
17.2
21.9
23.7
22.5
18.2

…
13.6
11.3
19.6
17.1
15.7
12.0

…
20.4
19.1
22.7
25.7
24.3
19.9

34.3
42.5
33.4
34.6
26.7
28.9
25.6

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

26.3
23.1
22.5
20.3
20.3
20.5
21.1
19.0

24.9
20.7
19.3
18.1
17.5
18.7
20.0
18.0

22.8
19.1
18.8
17.5
16.8
17.0
18.7
16.5

27.7
22.7
20.1
18.7
18.0
25.3
24.9
23.8

27.3
25.0
24.8
22.3
24.3
23.1
22.7
20.4

9.9
8.0
7.8
7.8
8.2
8.0
7.0
7.2

6.4
5.7
5.5
5.4
5.5
5.8
5.6
5.4

4.9
4.6
5.7
4.3
5.5
5.1
5.1
4.8

8.4
7.1
5.3
6.5
5.6
8.6
7.3
7.9

12.5
9.7
9.6
9.8
12.0
11.0
9.0
9.8

Poverty and income
distribution

Country

300

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 4 (continued)
POVERTY AND INDIGENCE LEVELS, 1990-2006
(Percentages)
Country

Population below the poverty line a

Year
Country
total

Urban areas
Total

Metropolitan
Other
area
urban areas

Population below the indigence line
Rural
areas

Country
total

Urban areas
Total

Metropolitan
Other
area
urban areas

Rural
areas

Poverty and income
distribution

Ecuador

1990
1994
1997
1999
2002
2004
2005
2006

…
…
…
…
…
51.2
48.3
43.0

62.1
57.9
56.2
63.5
49.0
47.5
45.2
39.9

…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…

…
…
…
…
…
58.5
54.5
49.0

…
…
…
…
…
22.3
21.2
16.1

26.2
25.5
22.2
31.3
19.4
18.2
17.1
12.8

…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…

…
…
…
…
…
30.5
29.2
22.5

El Salvador

1995
1997
1999
2001
2004

54.2
55.5
49.8
48.9
47.5

45.8
44.4
38.7
39.4
41.2

34.7
29.8
29.8
32.1
33.2

55.1
56.6
48.7
47.7
48.6

64.4
69.2
65.1
62.4
56.8

21.7
23.3
21.9
22.1
19.0

14.9
14.8
13.0
14.3
13.8

8.8
6.3
7.7
9.9
8.4

20.1
21.9
19.0
19.2
18.8

29.9
33.7
34.3
33.3
26.6

Guatemala

1989
1998
2002

69.4
61.1
60.2

53.6
49.1
45.3

…
…
…

…
…
…

77.7
69.0
68.0

42.0
31.6
30.9

26.4
16.0
18.1

…
…
…

…
…
…

50.2
41.8
37.6

Honduras

1990
1994
1997
1999
2002
2003
2006

80.8
77.9
79.1
79.7
77.3
74.8
71.5

70.4
74.5
72.6
71.7
66.7
62.7
59.4

59.9
68.7
68.0
64.4
56.9
50.3
48.7

79.5
80.4
77.2
78.8
74.4
72.5
67.8

88.1
80.5
84.2
86.3
86.1
84.8
81.5

60.9
53.9
54.4
56.8
54.4
53.9
49.3

43.6
46.0
41.5
42.9
36.5
35.1
30.0

31.0
38.3
35.5
33.7
25.1
23.3
19.9

54.5
53.7
48.6
51.9
45.3
44.5
37.9

72.9
59.8
64.0
68.0
69.5
69.4
65.3

Mexico

1989
1994
1996
1998
2000
2002
2004
2005
2006

47.7
45.1
52.9
46.9
41.1
39.4
37.0
35.5
31.7

42.1
36.8
46.1
38.9
32.3
32.2
32.6
28.5
26.8

…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…

56.7
56.5
62.8
58.5
54.7
51.2
44.1
47.5
40.1

18.7
16.8
22.0
18.5
15.2
12.6
11.7
11.7
8.7

13.1
9.0
14.3
9.7
6.6
6.9
7.0
5.8
4.4

…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…

27.9
27.5
33.0
31.1
28.5
21.9
19.3
21.7
16.1

Nicaragua

1993
1998
2001

73.6
69.9
69.3

66.3
64.0
63.8

58.3
57.0
50.8

73.0
68.9
72.1

82.7
77.0
77.0

48.4
44.6
42.4

36.8
33.9
33.4

29.5
25.8
24.5

43.0
39.5
39.1

62.8
57.5
55.1

Panama

1991
1994
1997
1999
2002
2004
2005
2006

…
…
…
…
34.0
31.8
33.0
30.8

32.7
25.3
24.7
20.8
25.3
22.4
24.4
21.7

…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…

…
…
…
…
48.5
47.9
47.8
46.6

…
…
…
…
17.4
14.8
15.7
15.2

11.5
7.8
8.0
5.9
8.9
6.8
7.7
6.4

…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…

…
…
…
…
31.5
28.6
29.4
30.4

Paraguay

1990
1994
1996
1999
2001
2004
2005

…
…
…
60.6
61.0
65.9
60.5

…
49.9
46.3
49.0
50.1
59.1
55.0

43.2
42.2
39.2
39.5
42.7
55.6
48.5

…
59.3
55.9
61.3
59.1
63.8
64.3

…
…
…
73.9
73.6
74.6
68.1

…
…
…
33.9
33.2
36.9
32.1

…
18.8
16.3
17.4
18.4
26.8
23.2

13.1
12.8
9.8
9.2
10.4
22.9
15.5

…
26.1
25.2
28.0
28.1
31.8
34.5

…
…
…
52.8
50.3
50.2
44.2

Social Panorama of Latin America • 2007

301

Table 4 (concluded)
POVERTY AND INDIGENCE LEVELS, 1990-2006
(Percentages)
Population below the poverty line a

Year
Country
total

Urban areas
Total

Metropolitan
Other
area
urban areas

Population below the indigence line
Rural
areas

Country
total

Total

Urban areas
Metropolitan
Other
area
urban areas

Rural
areas

Peru

1997
1999
2001 d
2003 d
2004 d
2005 d
2006 d

47.6
48.6
54.8
54.7
48.6
48.7
44.5

33.7
36.1
42.0
43.1
37.1
36.8
31.2

…
…
…
…
…
…
…

…
…
…
…
…
…
…

72.7
72.5
78.4
76.0
69.8
70.9
69.3

25.1
22.4
24.4
21.6
17.1
17.4
16.1

9.9
9.3
9.9
8.6
6.5
6.3
4.9

…
…
…
…
…
…
…

…
…
…
…
…
…
…

52.7
47.3
51.3
45.7
36.8
37.9
37.1

Dominican
Republic

2000
2002
2004
2005
2006

46.9
44.9
54.4
47.5
44.5

42.3
41.9
51.8
45.4
41.8

…
…
…
…
…

…
…
…
…
…

55.2
50.7
59.0
51.4
49.5

22.1
20.3
29.0
24.6
22.0

18.5
17.1
25.9
22.3
18.5

…
…
…
…
…

…
…
…
…
…

28.7
26.3
34.7
28.8
28.5

Uruguay

1990
1994
1997
1999
2002
2004
2005

…
…
…
…
…
…
…

17.9
9.7
9.5
9.4
15.4
20.9
18.8

11.3
7.5
8.6
9.8
15.1
20.8
19.7

24.3
11.8
10.3
9.0
15.8
21.0
17.9

…
…
…
…
…
…
…

…
…
…
…
…
…
…

3.4
1.9
1.7
1.8
2.5
4.7
4.1

1.8
1.5
1.5
1.9
2.7
6.1
5.8

5.0
2.2
1.8
1.6
2.2
4.3
2.4

…
…
…
…
…
…
…

Venezuela c
(Bol. Rep. of)

1990
1994
1997
1999
2002
2004
2005
2006

39.8
48.7
48.0
49.4
48.6
45.4
37.1
30.2

38.6
47.1
…
…
…
…
…
…

29.2
25.8
…
…
…
…
…
…

41.2
52.0
…
…
…
…
…
…

46.0
55.6
…
…
…
…
…
…

14.4
19.2
20.5
21.7
22.2
19.0
15.9
9.9

13.1
17.1
…
…
…
…
…
…

8.0
6.1
…
…
…
…
…
…

14.5
19.6
…
…
…
…
…
…

21.3
28.3
…
…
…
…
…
…

Latin
America e

1990
1994
1997
1999
2000
2001
2002
2003
2004
2005
2006
2007

48.3
45.7
43.5
43.9
42.5
43.2
44.0
44.2
42.0
39.8
36.5
35.1

41.4
38.7
36.5
37.2
35.9
37.0
38.4
39.0
36.9
34.1
31.1
29.8

…
…
…
…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…
…
…
…

65.4
65.1
63.0
63.7
62.5
62.3
61.8
61.1
58.7
58.8
54.4
53.6

22.5
20.8
19.0
18.7
18.1
18.5
19.4
19.1
16.9
15.4
13.4
12.7

15.3
13.6
12.3
12.1
11.7
12.2
13.5
13.7
12.0
10.3
8.6
8.1

…
…
…
…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…
…
…
…

40.4
40.8
37.6
38.2
37.8
38.0
37.8
36.4
33.1
32.5
29.4
28.7

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

 Includes persons below the indigence line or living in extreme poverty.
 As a result of a changeover to a new survey sample design in 2001, the figures for urban and rural areas are not strictly comparable with those of
previous years.
c  The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.
d  Figures from the Peruvian National Institute of Statistics and Informatics (INEI). Figures are not comparable with previous years owing to a change in
the sample framework of the household survey. According to INEI, the new framework results in estimates that are 25% higher for poverty and 10%
higher for indigence than estimates produced using the previous methodology.
e  Estimate for 19 countries in the region.
b

Poverty and income
distribution

Country

302

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 5
INDIGENCE LINES (IL) AND POVERTY LINES (PL)
(Monthly values per person)
Country

Year

Urban

Currency a

Sept.
Sept.
Sept.
Sept.
Oct.
2nd half
2nd half
2nd half

A
$
$
$
$
$
$
$

255 928
72
76
72
99
111
125
138

511 856
144
151
143
198
221
250
276

IL

PL

IL

Exchange
rate b

PL

Urban
IL

Local currency

Argentina

Poverty and income
distribution

Rural

Income
reference
period

1990 c
1994
1997 c
1999
2002
2004
2005
2006

Bolivia

1989
1994
1997
1999
2002
2004

Oct.
June-Nov.
May.
Oct.-nov.
Oct.-nov.
Nov. 03 - nov. 04

Bs
Bs
Bs
Bs
Bs
Bs

68
120
155
167
167
180

Brazil

1990
1993
1996
1999
2001
2003
2004
2005
2006

Sept.
Sept.
Sept.
Sept.
Oct.
Oct.
Oct.
Oct.
Oct.

Cr$
Cr$
R$
R$
R$
R$
R$
R$
R$

Chile

1990
1994
1996
1998
2000
2003
2006

Nov.
Nov.
Nov.
Nov.
Nov.
Nov.
Nov.

Colombia

1991
1994
1997
1999
2002
2004
2005

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

Rural
PL

IL

PL

US dollars

…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…

5 791.0
1.0
1.0
1.0
3.6
3.0
2.9
3.1

44.2
72.0
75.5
71.6
27.5
37.4
42.9
45.1

88.4
143.9
151.0
143.3
55.0
74.8
85.8
90.2

…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…

137
240
309
333
334
359

…
…
125
130
133
144

…
…
219
228
234
252

2.9
4.7
5.3
5.9
7.4
7.9

23.8
25.7
29.4
28.0
22.6
22.7

47.5
51.4
58.8
56.1
45.2
45.4

…
…
23.9
21.9
18.1
18.2

…
…
41.8
38.3
31.6
31.8

3 109
3 400
44
51
58
75
79
83
85

6 572
7 391
104
126
142
178
191
209
221

2 634
2 864
38
43
50
65
68
72
75

4 967
5 466
76
91
105
133
149
161
172

75.5
111.2
1.0
1.9
2.7
2.9
2.9
2.3
2.2

41.2
30.6
43.6
26.7
21.2
26.1
27.7
36.4
39.8

87.0
66.5
102.3
66.2
51.9
62.3
67.1
91.7
102.7

34.9
25.8
37.2
22.7
18.2
22.6
23.9
31.6
34.7

65.7
49.2
74.9
48.1
38.2
46.7
52.2
71.0
80.0

Ch$
Ch$
Ch$
Ch$
Ch$
Ch$
Ch$

9 297
15 050
17 136
18 944
20 281
21 856
23 549

18 594
30 100
34 272
37 889
40 562
43 712
47 099

7 164
11 597
13 204
14 598
15 628
16 842
18 146

12 538
20 295
23 108
25 546
27 349
29 473
31 756

327.4
413.1
420.0
463.3
525.1
625.5
527.4

28.4
36.4
40.8
40.9
38.6
34.9
44.6

56.8
72.9
81.6
81.8
77.2
69.9
89.3

21.9
28.1
31.4
31.5
29.8
26.9
34.4

38.3
49.1
55.0
55.1
52.1
47.1
60.2

Aug.
Aug.
Aug.
Aug.
Year
Year
Year

Col$
Col$
Col$
Col$
Col$
Col$
Col$

18 093
31 624
53 721
69 838
86 616
98 179
103 138

36 186
63 249
107 471
139 716
173 232
196 357
206 276

14 915
26 102
26 074 45 629
44 333 77 583
57 629 100 851
71 622 125 339
81 264 142 214
85 365 149 389

645.6
814.8
1 141.0
1 873.7
2 504.2
2 628.6
2 320.8

28.0
38.8
47.1
37.3
34.6
37.4
44.4

56.1
77.6
94.2
74.6
69.2
74.7
88.9

23.1
32.0
38.9
30.8
28.6
30.9
36.8

40.4
56.0
68.0
53.8
50.1
54.1
64.4

June
June
June
June
June
June
June
June

¢
¢
¢
¢
¢
¢
¢
¢

2 639
5 264
8 604
10 708
14 045
18 010
20 905
23 562

5 278
10 528
17 208
21 415
28 089
36 019
41 810
47 125

89.7
155.6
232.6
285.3
358.1
435.9
476.3
511.6

29.4
33.8
37.0
37.5
39.2
41.3
43.9
46.1

58.9
67.7
74.0
75.1
78.4
82.6
87.8
92.1

23.2
26.7
29.1
29.7
31.1
32.2
34.2
35.9

40.6
46.7
51.0
51.9
54.4
56.4
59.9
62.8

2 081
4 153
6 778
8 463
11 132
14 042
16 298
18 372

3 642
7 268
11 862
14 811
19 481
24 576
28 522
32 148

Social Panorama of Latin America • 2007

303

Table 5 (continued)
INDIGENCE LINES (IL) AND POVERTY LINES (PL)
(Monthly values per person)
Year

Income
reference
period

Urban

Currency a
IL

18 465
69 364
142 233
301 716
863 750
932 750
963 750
994 750

Rural

PL
IL
Local currency

PL

36 930
…
…
138 729
…
…
284 465
…
…
603 432
…
…
1 727 500
…
…
1 865 500 657 500 1 150 750
1 927 750 679 500 1 189 000
1 989 500 701 250 1 227 250

Exchange
rate b

Urban

Rural

IL

PL
IL
US dollars

PL

854.8
2 301.2
4 194.6
15 656.8
25 000.0
25 000.0
25 000.0
25 000.0

21.6
30.1
33.9
19.3
34.6
37.3
38.6
39.8

43.2
60.3
67.8
38.5
69.1
74.6
77.1
79.6

…
…
…
…
…
26.3
27.2
28.1

…
…
…
…
…
46.0
47.6
49.1

Ecuador

1990
1994
1997
1999
2002
2004
2005
2006

Nov.
Nov.
Oct.
Oct.
Nov.
July
Nov.
Nov.

S/.
S/.
S/.
S/.
S/.
S/.
S/.
S/.

El Salvador

1995
1997
1999
2001
2004

Jan.-Dec.
Jan.-Dec.
Jan.-Dec.
Jan.-Dec.
Year

¢
¢
¢
¢
¢

254
290
293
305
333

508
580
586
610
666

158
187
189
197
215

315
374
378
394
430

8.8
8.8
8.8
8.8
8.8

29.0
33.1
33.5
34.9
38.1

58.1
66.2
66.9
69.7
76.1

18.0
21.4
21.6
22.5
24.6

35.9
42.8
43.2
45.0
49.2

Guatemala

1989
1998
2002

Apr.
Dec. 97-Dec. 98
Oct. -Nov.

Q
Q
Q

64
260
334

127
520
669

50
197
255

88
344
446

2.7
6.4
7.7

23.6
40.7
43.6

47.1
81.5
87.2

18.7
30.8
33.3

32.7
54.0
58.2

Honduras

1990
1994
1997
1999
2002
2003
2006

Aug.
Sept.
Aug.
Aug.
Aug.
Aug.
Aug.

L
L
L
L
L
L
L

115
257
481
561
689
707
869

229
513
963
1 122
1 378
1 414
1 738

81
181
339
395
485
498
612

141
316
593
691
849
871
1 070

4.3
9.0
13.1
14.3
16.6
17.5
18.9

26.5
28.6
36.8
39.3
41.6
40.5
46.0

52.9
57.1
73.6
78.6
83.3
81.0
91.9

18.6
20.1
25.9
27.7
29.3
28.5
32.4

32.6
35.2
45.3
48.4
51.3
49.9
56.6

Mexico

1989
1994
1996
1998
2000
2002
2004
2005
2006

3rd. quarter
3rd. quarter
3rd. quarter
3rd. quarter
3rd. quarter
3rd. quarter
3rd. quarter
Aug. -Nov. 05
Aug. -Nov. 06

$
MN$
MN$
MN$
MN$
MN$
MN$
MN$
MN$

86 400
213
405
537
665
742
809
845
879

172 800
425
810
1 074
1 330
1 484
1 618
1 690
1 758

68 810
151
300
385
475
530
578
604
628

120 418
265
525
674
831
928
1 012
1 057
1 099

2 510.0
3.3
7.6
9.5
9.4
9.9
11.5
10.7
10.9

34.4
63.6
53.6
56.8
71.0
75.0
70.6
78.7
80.5

68.8
127.2
107.2
113.6
142.1
150.1
141.3
157.3
161.0

27.4
45.3
39.7
40.7
50.7
53.6
50.5
56.2
57.5

48.0
79.3
69.5
71.3
88.8
93.8
88.4
98.4
100.6

Nicaragua

1993
1997
1998
2001

21 Feb.-12 June
Oct.
15 Apr.-31 Aug.
30 Apr. - 31 July

C$
C$
C$
C$

167
247
275
369

334
493
550
739

129
…
212
284

225
…
370
498

4.6
9.8
10.4
13.4

36.6
25.3
26.3
27.6

73.3
50.5
52.7
55.2

28.2
…
20.3
21.3

49.4
…
35.5
37.2

Panama

1991
1994
1997
1999
2002
2004
2005
2006

Aug.
Aug.
Aug.
July
July
July
July
July

B
B
B
B
B
B
B
B

35.0
40.1
40.6
40.7
40.7
42.1
43.6
43.9

70.1
80.2
81.3
81.4
81.4
84.2
87.3
87.8

…
…
…
…
31.4
32.6
33.8
34.0

…
…
…
…
55.0
57.1
59.1
59.5

1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

35.0
40.1
40.6
40.7
40.7
42.1
43.6
43.9

70.1
80.2
81.3
81.4
81.4
84.2
87.3
87.8

…
…
…
…
31.4
32.6
33.8
34.0

…
…
…
…
55.0
57.1
59.1
59.5

Paraguay

1990 d June, July, Aug.
1994
Aug.-Sept.
1996
July-Nov.
1999
July-Dec.
2001
Sept. 00-Aug. 01
2004
July - Oct. 04
2005
June 05

G
G
G
G
G
G
G

43 242
87 894
108 572
138 915
155 461
212 145
224 499

86 484
175 789
217 143
277 831
310 922
424 290
448 997

…
…
…
106 608
119 404
162 786
172 013

…
…
…
186 565
208 956
284 876
301 023

1 207.8
1 916.3
2 081.2
3 311.4
3 718.3
5 915.6
6 137.9

35.8
45.9
52.2
42.0
41.8
35.9
36.6

71.6
91.7
104.3
83.9
83.6
71.7
73.2

…
…
…
32.2
32.1
27.5
28.0

…
…
…
56.3
56.2
48.2
49.0

Poverty and income
distribution

Country

304

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 5 (concluded)
INDIGENCE LINES (IL) AND POVERTY LINES (PL)
(Monthly values per person)
Country

Year

Income
reference
period

IL

Rural
PL

1997
1999
2001
2003

4th quarter
4th quarter
4th quarter
4th quarter

N$
N$
N$
N$

Dominican
Republic

2000
2002
2004
2005
2006

Sept.
Sept.
Sept.
Sept.
Sept.

Uruguay

1990
1994
1997
1999
2002
2004
2005

Venezuela
(Bol. Rep. of)

a

b
c
d
e

Exchange
rate b

PL

Urban
IL

1990
1994
1997 e
1999 e
2002 e
2004 e
2005 e
2006 e

Rural
PL

IL

PL

US dollars

103
109
117
120

192
213
230
239

83
89
102
107

128
141
159
167

2.7
3.5
3.5
3.5

42.1
31.2
34.0
34.5

84.3
61.2
66.8
68.9

31.6
25.5
29.5
30.8

55.3
40.5
46.0
48.2

RD$
RD$
RD$
RD$
RD$

713
793
1 715
1 649
1 724

1 425
1 569
3 430
3 298
3 449

641
714
1 543
1 484
1 552

1 154
1 285
2 778
2 672
2 793

16.5
18.8
37.5
31.1
33.3

43.1
42.2
45.8
53.1
51.8

86.2
83.5
91.5
106.2
103.5

38.8
38.0
41.2
47.8
46.6

69.8
68.4
74.1
86.0
83.9

2nd half
2nd half
Year
Year
Year
Year
Year

NUr$
$
$
$
$
$
$

41 972
281
528
640
793
1 027
1 073

83 944
563
1 056
1 280
1 586
2 054
2 147

…
…
…
…
…
…
…

…
…
…
…
…
…
…

1 358.0
5.4
9.4
11.3
21.3
28.7
24.5

30.9
52.1
55.9
56.4
37.3
35.8
43.8

61.8
104.1
111.9
112.9
74.6
71.6
87.7

…
…
…
…
…
…
…

…
…
…
…
…
…
…

2nd half
2nd half
2nd half
2nd half
2nd half
2nd half
2nd half
2nd half

Bs
Bs
Bs
Bs
Bs
Bs
Bs
Bs

1 924
8 025
31 711
48 737
80 276
122 936
141 699
163 503

3 848
16 050
62 316
95 876
154 813
236 597
272 689
314 700

1 503
6 356
…
…
…
…
…
…

2 630
11 124
…
…
…
…
…
…

49.4
171.3
488.6
626.3
1 161.0
1 918.0
2 147.0
2 147.0

38.9
46.9
64.9
77.8
69.1
64.1
66.0
76.2

77.9
93.7
127.5
153.1
133.4
123.4
127.0
146.6

30.4
37.1
…
…
…
…
…
…

53.2
65.0
…
…
…
…
…
…

Source: Economic Commission for Latin America and the Caribbean (ECLAC).


IL

Local currency

Peru

Poverty and income
distribution

Urban

Currency a

Local currencies:
Argentina: (A) Austral; ($) Peso
Bolivia: (Bs) Boliviano
Brazil: (Cr$) Cruzeiro; (R$) Real
Chile: (Ch$) Peso
Colombia: (Col$) Peso
Costa Rica: (¢ ) Colón
Ecuador: (S/.) Sucre
El Salvador: (¢ ) Colón
Guatemala: (Q) Quetzal
Honduras: (L) Lempira
Mexico: ($) Peso; (MN$) New Peso
Nicaragua: (C$) Córdoba
Panama: (B) Balboa
Paraguay: (G) Guaraní
Peru: (N$) Peso
Dominican Republic: (RD$) Peso
Uruguay: (Nur$) Nuevo Peso; ($) Peso
Venezuela (Bol. Rep. of): (Bs) Bolívar
International Monetary Fund rf series.
Greater Buenos Aires.
Asunción.
Nationwide total.

Social Panorama of Latin America • 2007

305

Table 6
BREAKDOWN OF HOUSEHOLDS BY PER CAPITA INCOME BRACKETS,
EXPRESSED AS MULTIPLES OF THE POVERTY LINE URBAN AREAS, 1990-2006
Per capita income bracket, in multiples of the poverty line
Country

Year

0 - 0.5
(indigents)

0.5 - 0.9

0.9 - 1.0

0.0 - 1.0
(poor)

1.0 - 1.25

1.25 - 2.0

2.0 - 3.0

More than
3.0

Argentina

1990

3.5

10.6

2.1

16.2

7.3

22.5

18.7

35.3

(Greater Buenos

1994

1.5

6.6

2.1

10.2

7.4

16.7

19.0

46.7

1997

3.3

7.0

2.8

13.1

7.2

19.0

17.5

43.2

1999

3.1

8.4

1.6

13.1

6.2

19.1

17.8

43.9

2002

12.0

15.4

4.2

31.6

8.7

19.3

15.8

24.7

2004

6.5

9.3

3.1

18.9

7.1

21.4

18.7

33.9

2005

8.6

2.6

16.1

5.6

22.6

19.2

36.6

4.6

6.8

2.2

13.6

6.4

17.7

20.4

42.0

1989

22.1

23.2

4.1

49.4

9.0

16.4

10.6

14.5

1994

Bolivia

4.9

2006

16.8

24.2

4.6

45.6

9.8

19.3

10.2

14.9
15.2

1997

22.6

5.1

46.8

9.7

17.2

11.2

16.4

20.8

5.1

42.3

10.8

18.5

11.4

17.0

2002
Brazil a

19.2

1999

17.3

23.1

4.4

44.9

9.1

18.8

10.2

17.1

1990

14.8

17.3

3.7

35.8

8.3

16.6

12.3

27.1

1993

13.5

16.0

3.8

33.3

8.5

19.0

13.3

26.0

1996

9.7

11.9

3.1

24.6

7.3

17.5

15.5

35.1

1999

9.9

13.1

3.4

26.4

8.0

18.1

15.3

32.3

2001

11.0

13.1

3.3

27.4

7.4

18.0

15.4

31.9

2003

11.5

13.5

3.4

28.4

7.7

18.4

15.5

30.1
30.6

2004

13.7

3.3

27.3

7.8

18.5

16.0

9.5

13.1

3.2

25.8

7.6

18.4

16.7

31.4

2006
Chile

10.3

2005

8.2

12.3

3.0

23.5

7.5

18.1

17.2

33.7
22.7

1990

10.2

18.6

4.5

33.3

9.5

20.3

14.3

1994

5.9

13.3

3.6

22.8

8.5

20.7

16.6

31.4

1996

4.3

11.0

3.2

18.5

8.5

20.5

17.2

34.1

1998

4.3

9.9

2.8

17.0

7.3

19.4

17.6

38.8

2000

4.3

9.1

2.9

16.3

7.5

19.2

18.0

39.1

2003

Colombia b

3.7

8.7

2.7

15.1

7.6

19.9

18.5

39.0

2006

2.7

6.4

2.4

11.4

6.5

19.5

19.7

43.0

1994

16.2

20.3

4.1

40.6

9.1

18.2

12.6

19.5

1997

14.6

20.3

4.5

39.5

9.6

18.9

12.6

19.4

1999

21.5

4.4

44.6

9.5

17.7

10.8

17.4

20.7

19.9

4.0

44.6

9.3

17.1

11.2

17.9

2004

19.8

20.1

4.0

43.9

8.7

17.1

11.5

18.8

2005
Costa Rica

18.7

2002

15.6

19.4

4.2

39.1

9.2

17.6

12.2

21.9

1990

7.8

11.2

3.7

22.2

7.9

21.9

20.2

27.9

1994

5.6

9.1

3.4

18.1

7.9

20.4

20.7

32.9

1997

5.2

9.1

2.8

17.1

8.1

20.5

20.3

34.0

1999

5.4

7.9

2.4

15.7

8.5

19.3

17.7

38.8

2002

5.5

7.7

2.7

15.9

6.1

19.2

18.3

40.6

2004

6.3

8.4

2.9

17.6

6.9

18.8

18.2

38.6

2005

5.9

9.5

2.8

18.2

7.5

20.3

17.6

36.4

2006

5.4

8.3

2.7

16.4

7.1

19.3

18.1

39.1

Poverty and income
distribution

Aires)

306

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 6 (continued)
BREAKDOWN OF HOUSEHOLDS BY PER CAPITA INCOME BRACKETS,
EXPRESSED AS MULTIPLES OF THE POVERTY LINE URBAN AREAS, 1990-2006
Per capita income bracket, in multiples of the poverty line
Country

0 - 0.5
(indigents)

0.5 - 0.9

0.9 - 1.0

0.0 - 1.0
(poor)

1.0 - 1.25

1.25 - 2.0

2.0 - 3.0

More than
3.0

1990

22.6

28.1

5.2

55.8

10.5

16.7

8.8

8.2

1994

22.4

24.7

5.2

52.3

10.1

19.1

9.1

9.4

1997

Poverty and income
distribution

Ecuador

Year

18.6

25.6

5.6

49.8

10.0

19.4

10.7

10.0

1999

27.2

25.5

5.3

58.0

7.9

16.1

7.9

10.1

2002

21.7

4.6

42.6

10.5

19.5

12.0

15.5

15.3

21.4

4.3

40.9

9.7

19.4

13.2

16.8

2005

14.3

19.7

4.8

38.8

9.0

20.1

13.8

18.3

2006

11.1

19.0

4.0

34.1

9.6

21.3

14.7

20.4

1995

12.4

22.4

5.1

40.0

12.0

22.0

12.8

13.3

1997

El Salvador

16.3

2004

12.0

21.8

4.8

38.6

11.0

21.8

13.6

15.0

1999

19.0

3.9

34.0

9.8

21.7

15.4

19.1

12.0

18.7

4.0

34.7

10.3

20.8

14.8

19.5

2004
Guatemala

11.1

2001

11.5

19.4

3.9

34.8

10.0

23.0

14.7

17.5

22.9

21.0

4.3

48.2

8.5

17.3

11.0

15.0

12.2

23.0

6.0

41.3

11.4

20.9

11.6

14.9

2002
Honduras

1989
1998

14.8

20.3

4.0

39.0

9.8

20.4

12.9

17.9

1990

38.0

22.7

3.8

64.5

8.2

12.0

6.5

8.8

1994

40.8

24.5

4.3

69.6

7.6

12.0

5.1

5.8
6.4

1997

36.8

26.0

4.2

67.0

8.2

12.5

5.9

1999

37.1

24.4

4.2

65.6

8.2

12.9

6.4

7.0

2002

31.3

24.8

4.4

60.5

8.9

14.5

7.6

8.6

2003

Mexico

30.5

22.2

3.7

56.3

10.7

15.5

7.9

9.6

2006

26.6

23.3

4.4

54.3

10.1

16.2

9.4

10.1

1989

9.3

19.8

4.8

33.9

11.0

22.3

13.1

19.8

1994

6.2

18.2

4.6

29.0

10.8

21.8

14.4

24.0

1996

10.0

22.2

5.3

37.5

10.7

21.3

12.4

18.1

1998

6.9

19.1

5.1

31.1

11.0

22.0

15.3

20.6

2000

4.7

17.3

4.5

26.5

10.9

22.7

16.3

23.6

2002

4.8

16.2

5.0

26.0

11.2

23.2

15.6

24.0

2004

16.3

4.7

26.2

10.9

23.6

15.0

24.4

4.1

14.4

4.3

22.9

10.3

24.2

16.7

26.0

2006
Nicaragua

5.2

2005

3.1

13.8

3.8

20.7

10.0

23.4

17.8

28.2

32.2

23.5

4.6

60.3

8.2

15.7

6.9

9.0

30.7

24.1

4.5

59.3

8.6

15.8

7.6

8.7

2001
Panama

1993
1998

28.3

25.2

4.2

57.7

8.3

16.4

8.4

9.2

1991

10.1

13.5

3.9

27.5

8.7

16.5

15.4

32.0

1994

6.1

11.0

3.3

20.4

7.5

18.5

18.0

35.7
38.4

1997

6.7

10.5

3.3

20.5

6.8

18.4

15.9

1999

4.9

9.3

2.8

17.0

6.8

17.6

17.6

41.1

2002

8.0

10.5

3.0

21.4

7.5

17.5

16.8

36.8
39.2

2004

6.0

9.6

3.3

18.9

7.0

18.6

16.3

2005

6.5

10.4

2.7

19.7

6.9

18.4

16.8

38.2

2006

5.4

9.4

2.8

17.7

7.0

18.8

17.5

39.0

Social Panorama of Latin America • 2007

307

Table 6 (concluded)
BREAKDOWN OF HOUSEHOLDS BY PER CAPITA INCOME BRACKETS,
EXPRESSED AS MULTIPLES OF THE POVERTY LINE URBAN AREAS, 1990-2006
Per capita income bracket, in multiples of the poverty line
Year

Paraguay
(Asunción)

1990
1994
1996
1999
2001
2004
2005

10.4
9.5
8.0
6.9
9.1
18.1
12.6

Peru

0 - 0.5
(indigents)

0.5 - 0.9
21.7
20.9
19.2
20.8
20.1
24.9
25.0

0.9 - 1.0

0.0 - 1.0
(poor)

4.7
5.0
6.4
5.2
5.9
5.3
4.0

36.8
35.4
33.5
32.9
35.0
48.3
41.5

13.6
11.6
11.3
11.9
8.9
10.8
10.8

1.0 - 1.25

1.25 - 2.0
19.6
20.4
22.2
19.9
21.4
18.7
22.0

2.0 - 3.0
14.2
13.4
13.5
16.2
13.2
10.9
11.8

More than
3.0
15.9
19.3
19.5
19.2
21.5
11.4
13.9

1997

6.5

17.1

4.4

28.0

10.3

23.8

16.2

21.8

1999

7.4

18.7

4.8

30.9

11.3

24.5

13.0

20.4

2001

10.9

20.6

4.9

36.4

12.1

22.4

13.1

16.1

2003

7.3

20.6

5.1

33.1

12.0

24.6

14.6

15.7

Dominican

2000

17.7

17.2

4.1

39.0

8.9

18.3

13.9

19.9

Republic

2002

16.0

18.1

4.3

38.4

9.1

18.3

13.9

20.4

2004

20.8

3.7

47.9

7.7

15.7

9.7

18.9

20.1

17.4

4.0

41.5

8.6

15.7

11.8

22.5

2006

17.1

18.3

3.2

38.7

8.2

16.0

12.3

24.8

1990

2.0

7.0

2.8

11.8

7.1

22.7

23.1

35.3

1994

Uruguay

23.4

2005

1.1

3.4

1.3

5.8

3.6

15.4

23.2

52.0

1997

0.9

3.5

1.4

5.7

4.0

15.2

21.4

53.8

1999

0.9

3.4

1.3

5.6

3.6

13.5

20.5

56.9
45.5

2002

9.3

5.6

18.0

21.6

2.9

13.2

6.8

20.9

22.0

37.2

2.2

7.3

2.3

11.8

6.2

20.0

23.1

38.9

10.9

17.5

5.0

33.4

10.9

21.5

14.8

19.4

1994

13.5

22.0

5.4

40.9

10.4

21.4

12.9

14.4

1997

c

1.9

7.8

1990

Venezuela

6.1

2.5

2005

(Bol. Rep. of)

1.3

2004

17.1

20.7

4.5

42.3

10.6

19.3

11.5

16.3

1999

19.4

20.5

4.1

44.0

10.3

19.5

11.5

14.8

2002

18.6

20.0

4.7

43.3

9.8

18.9

12.0

15.9

2004

15.8

19.3

4.8

39.9

9.9

20.7

13.6

15.8

2005

13.7

15.4

3.8

32.9

9.1

21.2

16.2

20.7

2006

8.5

13.8

3.9

26.2

9.7

22.0

18.2

24.0

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a

In this country, the values given for indigence (0 – 0.5 times the poverty line) and poverty (0-1.0 times the poverty line) may not coincide with the ones
given in table 14. This is because the poverty line in Brazil is calculated by multiplying the indigence line by a variable coefficient instead of a fixed one
(2.0), as in the other countries.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
c The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Poverty and income
distribution

Country

308

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 7
POVERTY RATES IN SELECTED OCCUPATIONAL CATEGORIES, URBAN AREAS, 1990-2006a
(Percentages)

Poverty and income
distribution

Country

Year

Total
population

Total
Public-sector
employed wage or salary
earners

Private-sector wage earners in non-professional
non-technical occupations
Establishments
employing
more than
5 persons

Establishments
employing
up to
5 persons b

Domestic
employees

Own-account workers in nonprofessional, non-technical occupations
Manufacturing
and
construction

Commerce
and
services

Argentina
(Greater
Buenos
Aires)

1990
1994
1997
1999
2002
2004
2005
2006

21
13
18
20
42
26
23
19

10
5
8
10
27
15
13
11

…
…
…
6
40
22
15
11

12 c
5c
8c
9
31
14
13
10

15
7
12
17
40
22
21
17

21
10
18
22
43
26
23
25

6
4
8
14
31
15
12
9

8
3
6
8
19
12
21
11

Bolivia

1989
1994
1997
1999
2002
2004

53
52
52
49
52
54

39
41
43
41
43
45

…
35
30
23
25
20

42
48
42
41
41
39

53
58
50
53
47
57

31
31
35
27
30
38

46
52
59
66
63
62

40
44
46
43
48
51

Brazil d

1990
1993
1996
1999
2001
2003
2004
2005
2006

41
40
31
33
34
36
34
33
30

32
32
22
24
24
25
25
23
21

…
20
14
14
13
13
12
12
10

30
31
22
26
26
25
23
21
19

48
39
27
32
33
33
32
30
28

49
47
35
39
40
41
41
39
36

40
43
28
33
35
33
33
32
29

36
33
22
27
27
32
31
30
27

Chile

1990
1994
1996
1998
2000
2003
2006

38
28
22
21
20
18
14

29
20
15
14
14
10
7

…
…
7
…
6
5
5

30 c
20 c
18
14 c
16
14
9

38
27
24
21
22
19
12

37
21
20
19
17
15
15

28
20
10
11
14
10
8

23
17
10
9
12
10
7

Colombia e

1991
1994
1997
1999
2002
2004
2005

52
45
40
51
51
50
45

41
34
33
38
40
39
35

27
15
15
12
11
9
8

45 f
41 f
37 f
38 f
36 f
34 f
31 f

…
…
…
…
…
…
…

38
31
34
35
44
43
39

54
42
48
60
59
62
56

53
42
42
54
56
57
52

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

25
21
23
18
18
19
20
18

15
12
10
10
9
10
11
10

…
5
4
3
1
2
2
2

15
11
10
9
8
8
11
7

22
19
17
14
12
13
15
11

28
25
23
27
18
16
27
19

28
24
21
17
19
19
20
25

24
18
18
16
18
24
21
23

Social Panorama of Latin America • 2007

309

Table 7 (continued)
POVERTY RATES IN SELECTED OCCUPATIONAL CATEGORIES, URBAN AREAS, 1990-2006a
(Percentages)
Year

Total
population

Total
Public-sector
employed wage or salary
earners

Private-sector wage earners in non-professional
non-technical occupations
Establishments
employing
more than
5 persons

Establishments
employing
up to
5 persons b

Domestic
employees

Own-account workers in nonprofessional, non-technical occupations
Manufacturing
and
construction

Commerce
and
services

Ecuador

1990
1994
1997
1999
2002
2004
2005
2006

62
58
56
64
49
48
45
40

51
46
45
53
39
37
35
31

33
31
28
30
18
14
11
9

50
49
46
55
39
37
35
28

60
58
62
70
53
50
48
44

56
56
53
61
51
45
47
40

70
60
56
68
48
52
46
38

61
56
54
62
45
46
42
40

El Salvador

1995
1997
1999
2001
2004

54
56
39
39
41

34
35
29
30
31

14
13
9
8
9

35
35
26
28
30

50
48
44
42
44

32
40
41
40
42

50
50
43
45
46

41
43
35
35
35

Guatemala

1989
1998
2002

53
49
44

42
42
34

20
20
8

47
45
33

61
58
54

42
33
42

48
50
48

35
41
33

Honduras

1990
1994
1997
1999
2002
2003
2006

70
75
73
72
67
63
59

60
66
64
64
58
54
50

29
42
44
41
28
25
19

60
71
69
64
57
44
49

76
83
83
81
75
69
66

51
56
52
58
48
52
46

81
84
84
80
80
76
71

73
77
72
72
68
69
66

Mexico

1989
1994
1996
1998
2000
2002
2004
2005
2006

42
37
45
39
32
32
33
29
27

33
29
38
31
25
25
25
21
20

…
…
19
12
11
11
…
…
…

37 g
33 g
41
36
26
27
25 c
22 c
21 c

…
…
59
49
44
40
41
37
33

60
56
63
57
38
46
45
40
39

32
27
48
39
34
27
26
25
23

28
…
41
30
24
21
23
18
17

Nicaragua

1993
1998
2001

66
64
64

52
54
54

47
…
36

54
54 c
54

64
68
67

74
74
74

60
59
65

45
52
55

Panama

1991
1994
1997
1999
2002
2004
2005
2006

33
25
25
21
25
22
24
22

19
14
14
11
14
13
15
12

9
6
6
4
5
3
4
3

22
15
15
10
12
10
11
8

31
23
26
22
15
21
24
18

25
23
23
17
22
23
25
26

35
24
29
19
27
22
25
24

33
23
23
23
29
27
27
25

Poverty and income
distribution

Country

310

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 7 (concluded)
POVERTY RATES IN SELECTED OCCUPATIONAL CATEGORIES, URBAN AREAS, 1990-2006a
(Percentages)
Country

Year

Total
population

Total
Public-sector
employed wage or salary
earners

Private-sector wage earners in non-professional
non-technical occupations
Establishments
employing
more than
5 persons

Establishments
employing
up to
5 persons b

Domestic
employees

Own-account workers in nonprofessional, non-technical occupations
Manufacturing
and
construction

Commerce
and
services

1990
1994
1996
1999
2001
2004
2005

42
42
39
40
43
56
49

32
31
29
26
32
43
37

23
14
13
11
14
26
20

40
38
27
27
37
43
37

49
44
40
40
38
54
50

29
36
33
27
36
46
39

41
42
44
42
42
55
48

31
37
37
31
47
56
51

Peru

1997
1999
2001
2003

34
36
42
43

25
28
36
38

14
14
20
21

20
21
37
37

28
32
47
49

16
23
27
30

36
52
43
44

33
36
41
44

Dominican
Republic

2000
2002
2004
2005
2006

42
42
52
45
42

27
27
38
30
28

26
27
43
32
29

29
28
49
40
38

35
37
50
44
41

55
49
65
59
52

26
29
23
18
12

26
28
26
19
21

Uruguay

Poverty and income
distribution

Paraguay
(Asunción)

1990
1994
1997
1999
2002
2004
2005

18
10
10
9
15
21
19

11
6
6
5
10
14
13

8
2
2
2
2
3
3

10
6
5
5
8
12
10

17
7
9
9
15
21
19

25
13
12
12
17
26
25

21
12
10
12
21
26
24

14
7
9
9
18
25
24

1990
1994
1997
1999
2002
2004
2005
2006

39
47
48
49
49
45
37
30

22
32
35
35
35
32
24
18

20
38
34
28
21
19
15
9

24
29
44
37
42
37
29
21

34
48
50
52
51
48
38
29

33
41
52
50
53
53
46
36

25
32
27
33
30
28
20
18

22
32
27
34
33
29
22
17

Venezuela
(Bol. Rep. of)

i

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a
b
c
d
e

f
g
h
i

Refers to the percentage of persons employed in each category who live in households with income below the poverty line.
For the Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic, El Salvador, Panama (up to 2002) and Uruguay,
establishments with up to four employees are taken into account.
Includes public-sector wage or salary earners.
For 1990, the figure given for Brazil in the column for establishments employing more than five persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to five persons includes workers who do not have such contracts.
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992 the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Includes wage earners in establishments that employ up to five persons.
Includes public-sector wage and salary earners and wage earners in establishments that employ up to five persons.
Refers to all own-account non-professional, non-technical workers.
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Social Panorama of Latin America • 2007

311

Table 8
POVERTY RATES IN SELECTED OCCUPATIONAL CATEGORIES, RURAL AREAS, 1990-2006 a
(Percentages)
Year

Total
population

Total
Public-sector
employed wage or salary
earners

Private-sector wage earners in non-professional
non-technical occupations
Establishments
employing
more than
5 persons

Establishments
employing
up to
5 persons b

Domestic
employees

Own-account workers in nonprofessional, non-technical occupations
Manufacturing
and
construction

Commerce
and
services

Bolivia

1997
1999
2002
2004

79
81
79
81

79
80
79
78

35
14
32
31

48
25
42
57

41
58
50
75

49
37
42
17

87
86
84
83

89
88
88
87

Brazil c

1990
1993
1996
1999
2001
2003
2004
2005
2006

71
63
56
55
55
55
54
53
50

64
57
49
49
48
47
47
46
43

…
56
33
39
30
29
26
25
24

45
58
46
47
47
47
43
42
39

72
53
35
40
42
35
40
38
32

61
53
40
41
42
43
41
40
36

70
59
54
54
52
51
52
52
48

74
60
56
55
53
52
53
52
48

Chile

1990
1994
1996
1998
2000
2003
2006

40
32
31
28
24
20
12

27
22
21
18
16
11
7

…
…
13
…
9
4
4

28
20
21
16 d
16
10
6

36
28
27
21
20
17
10

23
13
16
13
10
9
7

22
21
18
17
16
13
7

24
24
21
21
21
14
8

Colombia

1991
1994
1997
1999
2002
2004
2005

60
62
60
62
52
55
51

53
55
48
50
41
45
41

…
…
16
12
8
13
7

42 d e
55 d e
40 e
41 e
32 e
32 e
32 e

…
…
…
…
…
…
…

54
57
48
45
41
42
39

67
61
62
64
52
56
50

73
59
67
66
55
51
44

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

27
25
25
22
24
23
23
20

17
14
14
12
15
13
13
11

…
7
5
3
1
2
2
2

13
3
9
7
5
5
5
3

23
20
20
21
13
11
13
9

22
23
25
22
16
13
17
14

24
21
21
17
33
30
28
27

27
24
24
21
46
45
39
42

Ecuador

2004
2005
2006

59
55
49

53
47
43

18
10
8

33
31
24

51
44
40

45
31
28

61
55
52

65
59
56

El Salvador

1995
1997
1999
2001
2004

64
69
65
62
57

53
58
55
53
47

24
26
16
14
16

43
47
42
38
35

56
57
56
54
50

50
49
47
49
38

63
67
71
64
59

72
79
80
79
76

Guatemala

1989
1998
2002

78
69
68

70
63
60

42
42
27

72
62
63

76
74
62

61
53
41

71
63
65

76
67
73

Poverty and income
distribution

Country

312

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 8 (continued)
POVERTY RATES IN SELECTED OCCUPATIONAL CATEGORIES, RURAL AREAS, 1990-2006 a
(Percentages)

Poverty and income
distribution

Country

Honduras

Year

Total
population

Total
Public-sector
employed wage or salary
earners

Private-sector wage earners in non-professional
non-technical occupations
Establishments
employing
more than
5 persons

Establishments
employing
up to
5 persons b

Domestic
employees

Own-account workers in nonprofessional, non-technical occupations
Manufacturing
and
construction

Commerce
and
services

1990

88

83

…

71

90

72

88

90

1994

81

73

40

65

79

74

78

81

1997

84

79

37

75

86

74

83

85

1999

86

81

38

79

89

75

85

89

2002

86

82

34

65

89

69

86

91

2003

81

29

57

88

72

86

90

82

77

24

58

85

65

86

89

1989

57

49

…

53 f

…

50

47

54

1994

Mexico

85

2006

57

47

…

53 f

…

53

46

54

1996

62

56

23

57

67

64

59

68

1998

58

51

23

48

60

64

55

64

2000

55

46

16

44

59

64

49

61

2002

51

44

21

36

54

48

48

62

2004

44

36

…

26 d

49

39

41

55

2005

48

39

…

32 d

52

47

41

57

34

…

24 d

43

34

38

50

2006
Nicaragua

40
83

75

71

64

77

59

82

89

77

70

…

61

69

49

80

87

2001
Panama

1993
1998

77

70

46

57

67

63

80

87

1991

49

38

12

22

44

40

53

58

1994

48

37

9

20

39

43

51

61

1997

42

29

7

20

37

29

38

44

1999

40

28

5

16

35

28

37

42

2002

49

40

6

13

16

27

60

70

2004

41

4

11

26

33

61

71

48

41

4

9

26

31

59

69

2006
Paraguay

48

2005

47

40

4

9

24

26

60

68

1999

74

65

10

47

57

43

75

79

2001

74

67

13

35

68

44

75

81

2004

Peru

75

69

32

42

57

54

77

81

2005

68

62

21

38

53

55

70

72

1997

73

66

23

47

57

54

76

77

1999

73

66

33

42

54

38

73

78

2001

78

74

39

65

75

53

78

82

2003

76

72

27

58

65

63

76

79

Social Panorama of Latin America • 2007

313

Table 8 (concluded)
POVERTY RATES IN SELECTED OCCUPATIONAL CATEGORIES, RURAL AREAS, 1990-2006 a
(Percentages)
Year

Total
population

Total
Public-sector
employed wage or salary
earners

Private-sector wage earners in non-professional
non-technical occupations
Establishments
employing
more than
5 persons

Establishments
employing
up to
5 persons b

Domestic
employees

Own-account workers in nonprofessional, non-technical occupations
Manufacturing
and
construction

Commerce
and
services

Dominican

2000

55

38

33

35

44

54

39

47

Republic

2002

51

34

29

31

44

58

34

42

2004

59

45

44

53

55

59

43

60

2005

51

36

38

42

47

47

33

51

2006

50

35

33

37

45

47

35

57

Venezuela

1990

47

31

22

35

36

44

31

36

(Bol. Rep. of)

1994

56

42

27

50

50

53

42

44

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

 Refers to the percentage of persons employed in each category who live in households with income below the poverty line.
 For the Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic, El Salvador and Panama (up to 2002), includes
establishments with up to four employees only.
c For 1990, the figure given for Brazil in the column for establishments employing more than five persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to five persons includes workers who do not have such contracts.
d Includes public-sector wage earners.
e Includes wage earners in establishments employing up to 5 persons. As a result of a changeover to a new survey sample design in 2001, the figures
for rural areas are not strictly comparable with those of previous years.
f Includes public-sector wage earners and wage earners in establishments employing up to 5 persons.
b

Poverty and income
distribution

Country

314

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 9
BREAKDOWN OF THE TOTAL EMPLOYED POPULATION LIVING IN POVERTY BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages of the total employed urban population living in poverty)

Poverty and income
distribution

Country

Year

Publicsector wage
or salary
earners

Private-sector wage earners in non-professional,
non-technical occupations
In establishments
employing more
than 5 persons

In establishments
employing up
to 5 persons a

Own-account non-professional,
non-technical workers

Domestic
employees

Manufacturing
and
construction

Total b

Commerce
and
services

Argentina
(Greater
Buenos
Aires)

1990
1994
1997
1999
2002
2004
2005
2006

…
…
…
7
25
23
16
13

53
52
49
36
26
28
31
32

17
22
23
25
22
20
22
21

12
10
11
12
9
11
13
18

6
6
5
7
8
6
5
4

10
10
12
13
8
9
10
10

98
100
100
100
98
97
97
98

Bolivia

1989
1994
1997
1999
2002
2004

18
11
7
6
6
4

15
18
14
15
15
12

17
19
13
15
14
21

5
4
3
2
3
4

12
11
16
19
18
15

31
29
29
33
33
32

98
92
82
90
88
88

Brazil c

1990
1993
1996
1999
2001
2003
2004
2005
2006

…
9
8
7
7
6
6
6
6

32
32
31
28
29
30
31
30
31

26
11
12
11
12
13
12
12
22

10
12
13
14
15
14
14
14
15

5
6
7
7
7
8
8
9
8

18
17
16
18
17
16
16
16
15

91
87
87
85
87
87
87
87
97

Chile

1990
1994
1996
1998
2000
2003
2006

…
…
6
…
7
6
7

53
54
53
56
52
52
51

14
14
16
18
15
13
10

10
8
9
10
9
10
12

6
7
3
4
5
5
5

12
11
8
8
10
9
10

95
94
95
96
98
95
95

Colombia d

1991
1994
1997
1999
2002
2004
2005

…
4
4
3
2
2
2

48 e
58 e
46 e
38 e
32 e
31 e
33 e

…
…
…
…
…
…
…

5
5
5
5
6
6
6

8
8
10
12
12
12
12

26
22
30
37
39
41
40

87
97
95
95
91
92
93

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

…
11
7
6
3
3
3
4

28
28
30
28
24
24
28
21

13
18
18
17
15
14
16
12

8
9
8
15
8
5
12
10

12
10
10
8
10
8
7
11

17
18
22
20
25
32
22
28

78
94
95
94
85
87
88
87

Social Panorama of Latin America • 2007

315

Table 9 (continued)
BREAKDOWN OF THE TOTAL EMPLOYED POPULATION LIVING IN POVERTY BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages of the total employed urban population living in poverty)
Year

Publicsector wage
or salary
earners

Private-sector wage earners in non-professional,
non-technical occupations
In establishments
employing more
than 5 persons

In establishments
employing up
to 5 persons a

Own-account non-professional,
non-technical workers

Domestic
employees

Manufacturing
and
construction

Total b

Commerce
and
services

Ecuador

1990
1994
1997
1999
2002
2004
2005
2006

11
9
9
6
5
4
3
3

21
23
24
23
23
21
22
21

13
15
15
18
18
19
21
23

5
6
6
6
6
5
7
5

11
8
8
7
9
9
8
6

29
29
27
27
27
31
28
32

90
90
89
87
89
89
89
90

El Salvador

1995
1997
1999
2001
2004

5
5
4
3
3

28
25
23
24
25

15
16
21
19
19

4
5
6
6
5

12
10
10
10
10

25
27
24
27
27

89
88
88
88
88

Guatemala

1989
1998
2002

7
4
2

26
21
24

20
28
21

7
3
5

8
10
13

12
20
19

80
86
83

Honduras

1990
1994
1997
1999
2002
2003
2006

7
7
7
6
5
4
2

27
33
30
27
24
19
24

17
14
14
14
17
17
13

6
5
4
4
3
4
3

12
10
10
9
14
14
13

23
19
23
25
24
28
16

92
88
88
85
86
87
72

Mexico

1989
1994
1996
1998
2000
2002
2004
2005
2006

…
…
7
14
6
6
…
…
…

72 e
71 e
36
33
36
35
40 g
43 g
41 g

…
…
23
15
27
28
28
27
28

5
7
6
4
5
9
9
8
8

3
17 f
5
3
5
5
4
4
4

11
…
17
16
15
13
14
13
13

91
95
94
85
94
95
95
95
94

Nicaragua

1993
1998
2001

19
…
8

17
25
22

15
18
19

9
9
6

9
5
7

15
26
26

84
83
88

Panama

1991
1994
1997
1999
2002
2004
2005
2006

14
12
10
7
7
5
4
5

30
34
32
28
28
24
24
22

8
9
10
12
9
13
14
12

10
13
11
9
10
12
12
15

7
8
10
7
8
7
7
8

20
20
22
30
31
33
31
31

89
95
94
94
93
94
93
92

Poverty and income
distribution

Country

316

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 9 (concluded)
BREAKDOWN OF THE TOTAL EMPLOYED POPULATION LIVING IN POVERTY BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages of the total employed urban population living in poverty)
Country

Year

Publicsector wage
or salary
earners

Private-sector wage earners in non-professional,
non-technical occupations
In establishments
employing more
than 5 persons

In establishments
employing up
to 5 persons a

Own-account non-professional,
non-technical workers

Domestic
employees

Manufacturing
and
construction

Total b

Commerce
and
services

1990
1994
1996
1999
2001
2004
2005

8
5
5
6
5
7
7

30
30
22
26
28
19
21

24
19
19
21
13
17
18

10
14
11
10
12
12
11

7
7
10
8
7
8
7

15
19
26
20
28
29
25

94
94
93
91
93
92
89

Peru

1997
1999
2001
2003

7
5
7
6

15
12
17
16

14
15
18
16

3
5
4
4

8
9
6
6

38
38
33
34

85
84
84
82

Dominican
Republic

2000
2002
2004
2005
2006

13
14
14
14
14

33
30
38
36
35

10
9
10
9
11

8
8
9
9
9

7
8
4
5
3

20
23
14
14
16

92
91
88
87
88

Uruguay

1990
1994
1997
1999
2002
2004
2005

16
8
7
5
4
4
3

30
32
27
26
20
22
23

11
13
17
15
16
17
20

15
16
15
17
17
17
14

10
13
12
15
17
14
13

15
15
19
20
23
22
23

97
97
97
98
97
95
97

Venezuela
(Bol. Rep. of) h

Poverty and income
distribution

Paraguay
(Asunción)

1990
1994
1997
1999
2002
2004
2005
2006

19
21
17
12
8
9
10
8

33
26
32
26
28
27
28
28

10
14
15
18
16
16
16
16

10
5
7
3
4
4
4
4

5
6
5
7
6
6
5
6

15
19
15
24
25
24
22
23

92
91
91
90
87
85
85
86

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a
b
c
d

e
f
g
h

For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic, El Salvador, Panama and Uruguay (1990), includes
establishments employing up to four persons only.
In most cases, the total amounts to less than 100%, since employers, professional and technical workers and public-sector employees have not been
included.
For 1990, the figure given for Brazil in the column for establishments employing more than five persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to five persons includes workers who do not have such contracts.
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Includes wage earners in establishments employing up to 5 persons.
Refers to all non-professional, non-technical own-account workers.
Includes public-sector wage earners.
The sample design in the surveys conducted since 1997 does not distinguis between urban and rural areas and the figures therefore refer to the
nationwide total.

Social Panorama of Latin America • 2007

317

Table 10
BREAKDOWN OF THE TOTAL EMPLOYED POPULATION LIVING IN POVERTY BY OCCUPATIONAL CATEGORY,
RURAL AREAS, 1990-2006
(Percentages of the employed urban population living in poverty)
Year

Public-sector
wage and
salary earners

Private-sector wage earners in non-professional,
non-technical occupations

Own-account workers in nonprofessional, non-technical occupations

In establishments
employing more than
5 persons

In establishments
employing up to
5 persons a

Domestic
employees

Total

Total b

Agriculture

Bolivia

1997
1999
2002
2004

1
0
1
2

2
1
2
3

2
2
2
7

0
0
0
0

94
95
91
84

89
90
88
72

99
98
97
96

Brazil c

1990
1993
1996
1999
2001
2003
2004
2005
2006

…
5
3
4
3
2
2
2
3

9
23
21
20
22
22
21
21
21

26
2
2
2
2
2
2
2
2

4
3
3
3
3
4
4
4
4

57
66
70
69
69
69
70
70
69

51
61
65
64
64
63
64
61
61

96
99
99
98
99
99
99
99
99

Chile

1990
1994
1996
1998
2000
2003
2006

…
…
2
…
3
2
2

40
39
29
36
40
38
41

29
26
35
25
22
23
20

3
2
3
3
2
3
5

27
31
30
35
33
33
30

23
25
27
31
28
29
22

99
98
99
99
100
99
98

Colombia

1991
1994
1997
1999
2002
2004
2005

…
…
1
1
1
1
0

34 d
47 d
35 d
31 d
25 d
24 d
26 d

…
…
…
…
…
…
…

2
4
3
3
4
3
3

58
45
57
62
68
70
68

35
24
35
36
40
39
38

94
96
96
97
98
98
97

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

…
5
3
2
1
1
2
1

25
20
20
19
9
13
12
9

23
28
28
34
16
14
19
13

6
7
9
10
5
5
7
7

41
35
36
30
62
58
50
58

27
19
19
16
41
40
30
37

95
95
96
95
91
91
90
88

Ecuador

2004
2005
2006

1
1
0

8
8
8

17
19
17

2
1
1

70
67
71

59
60
64

97
96
98

El Salvador

1995
1997
1999
2001
2004

1
1
1
1
1

23
23
18
13
18

15
15
17
19
24

3
4
5
5
5

52
54
55
58
51

36
39
38
43
34

94
97
96
96
98

Guatemala

1989
1998
2002

2
1
1

23
22
18

12
19
15

2
1
1

61
54
63

52
37
47

100
98
97

Honduras

1990
1994
1997
1999
2002
2003
2006

2
3
2
2
1
1
1

11
14
13
12
9
8
9

17
15
16
16
21
22
20

2
2
2
2
1
2
2

68
65
65
66
67
66
61

51
49
45
45
52
49
49

100
99
98
98
99
99
92

Poverty and income
distribution

Country

318

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 10 (concluded)
BREAKDOWN OF THE TOTAL EMPLOYED POPULATION LIVING IN POVERTY BY OCCUPATIONAL CATEGORY,
RURAL AREAS, 1990-2006
(Percentages of the employed urban population living in poverty)
Country

Year

Public-sector
wage and
salary earners

Private-sector wage earners in non-professional,
non-technical occupations

Own-account workers in nonprofessional, non-technical occupations

In establishments
employing more than
5 persons

In establishments
employing up to
5 persons a

Domestic
employees

Total

Total b

Agriculture

1989
1994
1996
1998
2000
2002
2004
2005
2006

…
…
3
6
2
4
…
…
…

50 d
50 d
20
19
20
14
21 e
21 e
15 e

…
…
22
18
27
28
32
30
32

3
3
4
2
3
5
4
6
5

45
45
49
49
46
48
39
40
45

38
35
35
29
33
36
26
28
29

98
98
98
94
98
98
97
96
97

Nicaragua

1993
1998
2001

6
…
3

13
17
11

11
16
13

4
3
3

62
60
65

54
49
55

96
96
96

Panama

1991
1994
1997
1999
2002
2004
2005
2006

4
3
2
2
1
1
1
1

10
11
13
11
5
4
3
4

9
13
14
17
5
8
8
8

4
5
4
4
2
3
3
3

72
67
66
65
86
83
84
84

60
55
50
45
68
62
63
66

99
100
99
99
99
99
99
99

Paraguay

1999
2001
2004
2005

1
1
1
2

5
3
4
3

10
13
9
10

3
3
3
4

80
78
81
79

66
66
68
68

99
98
98
98

Peru

1997
1999
2001
2003

1
1
2
2

5
4
7
5

7
7
9
5

1
1
1
1

82
82
78
85

71
73
68
76

96
95
96
97

Dominican
Republic

2000
2002
2004
2005
2006

7
7
9
8
8

17
15
24
22
20

8
7
7
9
8

7
8
6
6
8

59
60
52
53
55

40
43
38
40
44

98
97
97
97
98

Venezuela
(Bol. Rep. of)

Poverty and income
distribution

Mexico

1990
1994

5
5

27
23

15
19

4
6

47
45

39
31

98
98

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a
b
c
d
e

In the case of the Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic, El Salvador and Panama (up to 2002),
this category includes establishments employing up to 4 employees only.
In most cases, the total amounts to less than 100%, since employers, professional and technical workers and public-sector employees have not been
included.
For 1990, the figure given for Brazil in the column for establishments employing more than 5 persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to five persons includes workers who do not have such contracts.
Includes wage earners in establishments employing up to 5 persons. As a result of a changeover to a new survey sample design in 2001, the figures
for rural areas are not strictly comparable with those of previous years.
Includes public-sector wage earners.

Social Panorama of Latin America • 2007

319

Table 11
EXTENT AND DISTRIBUTION OF POVERTY AND INDIGENCE IN HOUSEHOLDS HEADED BY WOMEN,
URBAN AREAS, 1990-2006
Year

Percentage of households headed by women
at each poverty level
Total
households

Indigent

Non- indigent Non-poor
poor

Distribution of households headed by women
by poverty level
Total
households

Indigent

Non- indigent Non-poor
poor

Argentina
(Greater Buenos
Aires)

1990
1994
1997
1999
2002
2004
2005
2006

21
24
26
27
27
30
31
32

26
22
32
37
20
39
40
44

12
20
24
28
25
27
29
32

22
24
26
27
28
29
31
31

100
100
100
100
100
100
100
100

4.3
1.0
4.1
4.2
8.9
8.6
6.2
6.4

7.0
7.5
9.0
10.4
18.5
11.5
10.3
9.1

88.7
91.1
86.9
85.4
72.6
79.9
83.5
84.5

Bolivia

1989
1994
1997
1999
2002
2004

17
18
21
21
24
26

23
20
24
24
24
27

16
17
22
19
19
24

15
18
19
21
26
26

100
100
100
100
100
100

30.2
18.1
22.2
19.2
17.6
16.5

25.5
27.0
30.0
23.4
22.1
28.2

44.3
54.9
47.8
57.4
60.3
55.3

Brazil

1990
1993
1996
1999
2001
2003
2004
2005
2006

20
22
24
25
26
28
29
30
31

24
23
24
24
27
28
31
33
36

23
21
22
24
25
27
28
28
31

18
22
24
26
27
28
29
31
31

100
100
100
100
100
100
100
100
100

16.0
12.3
7.7
6.7
8.2
8.7
8.1
6.7
6.0

25.1
20.9
15.9
18.3
18.3
18.7
19.1
18.3
18.0

58.9
66.8
76.4
74.9
73.5
72.6
72.8
75.1
76.0

Chile

1990
1994
1996
1998
2000
2003
2006

21
22
23
24
24
18
31

25
27
29
28
28
26
48

20
21
22
23
23
16
36

22
22
23
24
24
18
30

100
100
100
100
100
100
100

11.7
7.1
5.3
4.9
5.0
2.3
4.1

21.3
16.0
13.6
12.3
11.5
9.0
10.2

67.0
76.8
81.1
82.7
83.6
88.7
85.7

Colombia a

1991
1994
1997
1999
2002
2004
2005

24
24
27
29
30
32
33

28
24
32
31
34
38
38

22
24
28
27
29
31
31

24
24
25
29
30
31
32

100
100
100
100
100
100
100

19.8
16.1
17.5
20.4
23.1
23.6
18.1

27.6
24.0
25.9
24.0
22.8
22.8
22.0

52.6
59.9
56.6
55.6
54.1
53.6
59.9

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

23
24
27
28
28
30
31
32

36
42
51
56
48
51
54
54

25
27
36
39
34
34
35
37

21
22
24
25
27
28
29
30

100
100
100
100
100
100
100
100

10.9
9.8
9.9
10.9
9.2
10.5
10.3
9.2

16.5
14.0
15.7
14.1
12.5
12.5
13.9
12.7

72.6
76.2
74.4
75.0
78.3
77.0
75.7
78.1

Poverty and income
distribution

Country

320

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 11 (continued)
EXTENT AND DISTRIBUTION OF POVERTY AND INDIGENCE IN HOUSEHOLDS HEADED BY WOMEN,
URBAN AREAS, 1990-2006
Country

Year

Percentage of households headed by women
at each poverty level
Total
households

Indigent

Non- indigent Non-poor
poor

Distribution of households headed by women
by poverty level
Total
households

Indigent

Non- indigent Non-poor
poor

1990
1994
1997
1999
2002
2004
2005
2006

17
19
19
20
21
24
23
23

22
23
24
23
26
29
28
25

16
18
19
21
21
23
21
25

15
18
17
18
20
22
23
24

100
100
100
100
100
100
100
100

28.9
27.3
23.9
30.9
20.0
19.2
17.4
13.5

31.2
28.1
31.1
31.4
26.0
25.5
21.9
23.3

39.9
44.6
45.0
37.6
53.9
55.4
60.7
63.2

El Salvador

1995
1997
1999
2001
2004

31
30
31
35
35

38
36
36
37
35

31
33
36
40
39

29
28
29
33
34

100
100
100
100
100

15.4
14.2
12.6
12.6
11.4

28.1
29.3
25.9
25.9
25.5

56.5
56.5
61.5
61.5
63.1

Guatemala

1989
1998
2002

22
24
22

23
26
30

21
21
21

22
26
21

100
100
100

24.2
12.9
19.8

24.3
24.8
22.7

51.5
62.3
57.5

Honduras

1990
1994
1997
1999
2002
2003
2006

27
25
29
30
31
31
34

35
28
32
32
32
31
37

21
25
28
30
31
29
35

21
21
28
28
31
32
31

100
100
100
100
100
100
100

50.4
45.8
40.3
39.4
31.7
30.7
28.9

21.1
29.2
28.6
28.7
29.0
24.5
28.9

28.5
25.0
31.1
31.9
39.3
44.8
42.2

Mexico

1989
1994
1996
1998
2000
2002
2004
2005
2006

16
17
18
19
20
21
25
24
26

14
11
17
18
14
24
24
24
25

14
16
15
16
16
22
26
22
24

17
18
19
20
21
21
25
25
27

100
100
100
100
100
100
100
100
100

8.2
4.0
9.8
6.3
3.4
5.4
5.0
4.1
3.0

21.9
21.3
23.0
20.0
17.5
21.4
21.4
16.8
16.1

69.9
74.7
67.3
73.7
79.1
73.1
73.6
79.1
80.9

Nicaragua

1993
1998
2001

35
35
34

40
39
37

34
36
36

32
30
32

100
100
100

36.8
34.9
30.2

27.2
30.2
30.7

36.1
34.9
39.0

Panama

1991
1994
1997
1999
2002
2004
2005
2006

29
27
30
30
29
30
30
30

42
45
48
59
44
50
55
46

36
29
34
34
31
34
32
35

26
25
27
27
27
28
28
29

100
100
100
100
100
100
100
100

14.6
10.0
10.8
9.7
12.3
9.7
11.9
8.2

21.5
15.6
16.0
13.9
14.6
14.7
14.0
14.1

63.9
74.4
73.2
76.4
73.1
75.6
74.2
77.7

Poverty and income
distribution

Ecuador

Social Panorama of Latin America • 2007

321

Table 11 (concluded)
EXTENT AND DISTRIBUTION OF POVERTY AND INDIGENCE IN HOUSEHOLDS HEADED BY WOMEN,
URBAN AREAS, 1990-2006
Year

Percentage of households headed by women
at each poverty level
Total
households

Indigent

20
23
27
27
31
30
34

21
20
25
30
37
38
39

1997

20

21

19

21

100

8.0

18.6

73.3

1999

Paraguay
(Asunción)

21

17

21

21

100

6.3

23.9

69.7

1990
1994
1996
1999
2001
2004
2005

Peru

Non- indigent Non-poor
poor

Distribution of households headed by women
by poverty level

23
26
26
23
29
26
37

18
22
27
29
32
30
32

Total
households
100
100
100
100
100
100
100

Indigent
11.2
8.4
7.4
7.7
10.6
22.9
14.2

Non- indigent Non-poor
poor
30.5
29.3
24.7
21.9
23.7
25.8
31.1

58.3
62.3
67.9
70.4
65.7
51.3
54.6

2001

22

22

21

23

100

7.2

25.2

67.6

2003

25

30

20

26

100

7.2

24.3

68.5

Dominican

2000

31

48

33

26

100

27.2

22.3

50.5

Republic

2002

34

54

39

27

100

25.2

25.6

49.2

2004

41

35

28

100

29.5

26.4

44.1

35

48

37

30

100

27.5

22.3

50.2

2006
Uruguay

33

2005

34

50

39

28

100

25.0

24.8

50.2

1990

25

28

22

26

100

2.2

8.4

89.4

1994

27

21

23

27

100

0.8

4.0

95.1

1997

29

27

23

29

100

0.8

3.9

95.3

1999

31

29

26

31

100

0.8

4.0

95.2

2002

33

100

1.3

6.7

92.0

27

33

100

2.1

8.9

89.0

34

34

31

35

100

2.2

8.8

89.0

22

40

25

18

100

19.6

25.4

55.1

1994

25

34

28

21

100

18.7

30.8

50.5

1997

b

27

27

1990

Venezuela

31

32

2005

(Bol. Rep. of)

32

2004

26

28

29

24

100

18.6

28.4

53.0

1999

27

34

27

25

100

23.8

24.8

51.3

2002

29

35

29

26

100

24.0

24.1

51.9

2004

31

39

32

28

100

20.9

24.1

55.0

2005

32

40

33

30

100

18.2

19.3

62.5

2006

33

44

35

31

100

12.3

18.3

69.4

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992 the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
b The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Poverty and income
distribution

Country

322

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 12
HOUSEHOLD INCOME DISTRIBUTION, NATIONAL TOTALS, 1990-2006 a
(Percentages)
Country

Year

Average
income b

Share of total income of:

Ratio of average per capita
income c

40%
poorest

Next poorest
30%

20% below the
richest 10%

Richest 10%

D10/D(1 to 4)

Q5/Q1

10.6
12.4
12.5
8.1
9.4
10.0
10.8

14.9
14.9
15.4
13.4
16.0
16.7
16.9

23.6
22.3
21.6
19.3
22.3
22.2
23.6

26.7
27.1
26.1
25.3
24.5
25.4
25.4

34.8
35.8
37.0
42.1
37.3
35.7
34.1

13.5
16.0
16.4
20.0
15.5
14.6
13.8

13.5
16.4
16.5
21.8
16.6
15.5
14.9

7.7
5.8
5.7
6.1

12.1
9.4
9.2
9.5

21.9
22.0
24.0
21.3

27.9
27.9
29.6
28.3

38.2
40.7
37.2
41.0

17.1
25.9
26.7
30.3

21.4
34.6
48.1
44.2

Poverty and income
distribution

Argentina d

1990
1997
1999
2002
2004
2005
2006

Bolivia

1989 e
1997
1999
2002

Brazil

1990
1996
1999
2001
2003
2004
2005
2006

9.3
12.3
11.3
11.0
9.9
9.9
10.1
10.5

9.5
9.9
10.1
10.2
11.2
11.7
11.9
12.2

18.6
17.7
17.3
17.4
18.3
18.7
18.5
18.8

28.0
26.5
25.5
25.6
25.7
25.6
25.0
25.2

43.9
46.0
47.1
46.8
44.9
44.1
44.6
44.0

31.2
32.2
32.0
32.2
27.9
26.6
26.5
24.9

35.0
38.0
35.6
36.9
31.8
29.4
28.8
27.2

Chile

1990
1996
2000
2003
2006

9.4
12.9
13.6
13.6
14.4

13.2
13.1
13.8
13.7
14.6

20.8
20.5
20.8
20.7
21.5

25.4
26.2
25.1
25.5
26.7

40.7
40.2
40.3
40.0
37.2

18.2
18.3
18.7
18.8
15.9

18.4
18.6
19.0
18.4
15.7

Colombia f

1994
1997
1999
2002
2004
2005

8.4
7.3
6.7
6.9
6.9
7.8

10.0
12.5
12.3
12.3
12.1
12.2

21.3
21.7
21.6
22.4
22.0
21.4

26.9
25.7
26.0
26.5
26.0
25.4

41.8
40.1
40.1
38.8
39.9
41.0

26.8
21.4
22.3
24.1
25.1
25.2

35.2
24.1
25.6
28.5
29.1
27.8

Costa Rica

1990
1997
1999
2002
2004
2005
2006

9.5
10.0
11.4
11.7
10.9
10.3
11.2

16.7
16.5
15.3
14.5
14.3
15.2
14.6

27.4
26.8
25.7
25.6
26.2
26.2
25.7

30.2
29.4
29.7
29.7
30.1
29.9
29.3

25.6
27.3
29.4
30.2
29.5
28.7
30.4

10.1
10.8
12.6
13.7
13.3
12.7
13.4

13.1
13.0
15.3
16.9
16.6
15.1
16.1

Ecuador

1990 g
1997 g
1999 g
2002 g
2004
2005
2006

5.5
6.0
5.6
6.7
6.4
6.9
7.7

17.1
17.0
14.1
15.4
15.0
14.0
14.5

25.4
24.7
22.8
24.3
24.5
23.8
23.7

27.0
26.4
26.5
26.0
27.5
26.9
25.9

30.5
31.9
36.6
34.3
33.0
35.3
36.0

11.4
11.5
17.2
15.7
15.2
17.0
18.0

12.3
12.2
18.4
16.8
16.7
19.2
18.6

Social Panorama of Latin America • 2007

323

Table 12 (continued)
HOUSEHOLD INCOME DISTRIBUTION, NATIONAL TOTALS, 1990-2006 a
(Percentages)
Year

Average
income b

Share of total income of:
40%
poorest

El Salvador

Next poorest
30%

20% below the
richest 10%

Ratio of average per capita
income c
Richest 10%

D10/D(1 to 4)

Q5/Q1

1995

6.2

15.4

24.8

26.9

32.9

14.1

16.9

1997

6.1

15.3

24.5

27.3

33.0

14.8

15.9

1999

13.8

25.0

29.1

32.1

15.2

19.6

6.7

13.4

24.6

28.7

33.3

16.2

20.3

2004
Guatemala

6.6

2001

6.2

15.9

26.0

28.8

29.3

13.3

16.3

6.0

11.8

20.9

26.8

40.6

23.5

27.3

7.1

14.3

21.6

25.0

39.1

20.4

19.8

2002
Honduras

1989
1998

6.8

14.2

22.2

26.8

36.8

18.4

18.7

1990

4.3

10.1

19.7

27.0

43.1

27.4

30.7

1997

4.1

12.6

22.5

27.3

37.7

21.1

23.7

1999

11.8

22.9

28.9

36.5

22.3

26.5

4.3

11.3

21.7

27.6

39.4

23.6

26.3

2003
Mexico

3.9

2002

4.3

10.6

22.1

28.6

38.8

24.4

28.2
16.9

1989

8.6

15.8

22.5

25.1

36.6

17.2

1994

8.5

15.3

22.9

26.1

35.6

17.3

17.4

2000

8.5

14.6

22.5

26.5

36.4

17.9

18.5

2002

8.2

15.7

23.8

27.3

33.2

15.1

15.5

2004

8.3

15.8

23.3

26.3

34.6

15.9

16.0

2005

Nicaragua

8.7

15.4

23.2

26.0

35.4

16.7

17.0

2006

8.7

16.9

24.1

26.1

32.9

14.7

14.8

5.2

10.4

22.8

28.4

38.4

26.1

37.7

5.6

10.4

22.1

27.1

40.5

25.3

33.1

2001

5.9

12.2

21.5

25.7

40.6

23.6

27.2

1991 g

10.8

14.1

23.8

29.4

32.7

16.8

20.1

1994 g

12.7

14.6

23.6

25.1

36.8

17.0

18.3

1997 g

13.2

13.7

22.5

26.9

36.9

18.6

20.2

1999 g

12.6

15.6

25.2

27.8

31.5

14.0

15.9

2002

Panama

1993
1998

10.7

11.8

24.4

29.0

34.9

19.8

26.5

2004

13.0

24.6

28.0

34.4

17.3

22.6

9.6

13.2

24.8

28.9

33.1

16.9

22.4

2006

10.1

13.2

24.8

28.1

33.8

17.7

22.8

1990 h

7.7

18.6

25.7

26.9

28.9

10.2

10.6

1996 g

Paraguay

10.2

2005

7.4

16.7

24.6

25.3

33.4

13.0

13.4
22.6

1999

13.1

23.0

27.8

36.2

19.3

6.2

12.9

23.5

26.4

37.3

20.9

25.6

2004

5.2

14.6

22.9

26.5

36.1

18.6

20.1

2005
Peru

6.2

2001

5.5

15.0

23.9

26.5

34.7

16.0

18.2
20.8

1997

8.1

13.4

24.6

28.7

33.3

17.9

1999

8.2

13.4

23.1

27.1

36.5

19.5

21.6

2001

6.2

13.4

24.6

28.5

33.5

17.4

19.3

2003

6.2

14.9

23.7

27.9

33.6

15.6

16.3

Poverty and income
distribution

Country

324

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 12 (concluded)
HOUSEHOLD INCOME DISTRIBUTION, NATIONAL TOTALS, 1990-2006 a
(Percentages)
Country

Year

Average
income b

Share of total income of:
40%
poorest

Next poorest
30%

20% below the
richest 10%

Ratio of average per capita
income c
Richest 10%

D10/D(1to 4)

Q5/Q1

Dominican

2000

7.2

11.4

22.2

27.6

38.8

21.1

26.9

Republic

2002

7.2

12.0

22.6

27.0

38.3

19.3

24.9

Uruguay g

6.5

10.2

20.1

28.2

41.5

26.1

28.0

7.3

10.4

21.4

29.9

38.3

22.7

28.1

2006

Poverty and income
distribution

2004
2005

8.1

9.9

20.2

29.0

40.9

24.5

29.1

1990

9.3

20.1

24.6

24.1

31.2

9.4

9.4

1997

11.2

21.9

26.1

26.1

25.8

8.5

9.1

1999

11.9

21.6

25.5

25.9

27.0

8.8

9.5

2002

9.4

21.6

25.4

25.6

27.3

9.5

10.2

2004

8.2

21.3

24.8

25.4

28.6

10.1

10.6

2005

8.1

21.6

25.0

25.6

27.8

9.3

10.0

Venezuela

1990

8.9

16.7

25.7

28.9

28.7

12.1

13.4

(Bol. Rep. of) b

1997

7.8

14.7

23.9

28.6

32.8

14.9

16.1

1999

7.2

14.6

25.1

29.0

31.4

15.0

18.0

2002

7.1

14.3

24.9

29.5

31.3

14.5

18.1

2004

7.0

16.1

26.5

28.9

28.5

12.0

14.9

2005

8.5

14.8

26.1

28.3

30.8

13.7

17.9

2006

9.0

17.4

27.0

28.3

27.4

10.5

12.3

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a
b
c
d
e
f
g
h

Households arranged in order of per capita income. Table 13 presents disaggregated figures for urban and rural areas.
Average monthly household income in multiples of the per capita poverty line.
D(1 to 4) means the 40% of households with the lowest income, while D10 means the 10% of households with the highest income. Similar notation is
used for quintiles (Q), where each group represents 20% of total households.
Greater Buenos Aires.
Eight major cities and El Alto.
As a result of a changeover to a new survey sample design in 2001, the figures for urban areas and rural areas are not strictly comparable with those
of previous years.
Urban total.
Asunción metropolitan area.

Social Panorama of Latin America • 2007

325

Table 13
HOUSEHOLD INCOME LEVELS AND DISTRIBUTION, URBAN AND RURAL AREAS, 1990-2006 a
(Percentages)
Year

Average
income b

Share of total income of:
Poorest
40%

Next poorest 20% below
30%
richest 10%

Richest
10%

Average
income b

Share of total income of:
Poorest
40%

Urban areas

Next poorest 20% below
30%
richest 10%

Richest
10%

Rural areas, 1990-2006

Argentina

1990 c
1997 c
1999
2002
2004
2005
2006

10.6
12.4
11.6
7.3
8.9
9.6
10.8

14.9
14.9
15.9
14.3
16.3
16.5
16.9

23.6
22.3
22.1
20.4
22.5
22.7
22.9

26.7
27.1
25.4
24.6
25.2
25.4
25.2

34.8
35.8
36.7
40.6
36.0
35.4
35.0

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

Bolivia

1989 d
1997
1999
2002

7.7
7.2
7.2
7.7

12.1
13.6
15.2
13.9

21.9
22.5
24.1
21.4

27.9
26.9
28.0
26.4

38.2
37.0
32.7
38.4

…
3.6
3.1
3.5

…
9.8
6.9
8.2

…
19.4
21.3
21.6

…
28.8
33.6
30.7

…
42.0
38.3
39.5

Brazil

1990
1996
1999
2001
2003
2004
2005
2006

10.4
13.6
12.3
11.8
10.5
10.5
10.8
11.2

10.3
10.5
10.6
10.5
11.4
11.9
12.0
12.4

19.4
18.1
17.7
17.7
18.4
18.8
18.6
18.8

28.5
27.0
26.1
26.0
26.2
26.0
25.4
25.5

41.8
44.3
45.7
45.7
44.1
43.3
43.9
43.4

4.7
6.8
6.7
6.5
6.3
6.3
6.3
6.6

14.5
13.4
14.0
13.9
14.4
15.2
15.6
15.3

21.3
23.3
23.1
23.8
24.8
24.7
25.6
26.0

26.1
23.7
22.8
23.2
23.7
23.7
24.1
24.4

38.2
39.6
40.2
39.1
37.1
36.4
34.7
34.3

Chile

1990
1996
2000
2003
2006

9.4
13.5
14.1
13.9
14.6

13.4
13.4
14.0
13.9
14.8

21.2
20.9
20.9
21.0
21.8

26.2
26.4
25.4
25.6
26.8

39.2
39.4
39.7
39.4
36.5

9.7
9.4
10.6
11.1
13.1

13.8
16.8
16.9
16.5
16.3

20.4
24.3
24.5
22.6
21.7

20.6
23.4
22.4
22.2
22.6

45.1
35.6
36.1
38.8
39.3

Colombia e

1994
1997
1999
2002
2004
2005

9.0
8.4
7.3
7.2
7.4
8.3

11.6
12.9
12.6
11.9
11.7
12.0

20.4
21.4
21.9
22.2
21.8
21.1

26.1
26.1
26.6
26.8
26.4
26.0

41.9
39.5
38.8
39.1
40.1
40.9

5.7
5.3
5.6
6.4
5.4
6.2

10.0
15.4
13.9
14.7
16.3
15.2

23.3
26.3
24.7
25.2
28.4
26.0

32.2
28.2
25.9
28.0
27.6
27.2

34.6
30.1
35.5
32.1
27.7
31.6

Costa Rica

1990
1997
1999
2002
2004
2005
2006

9.6
10.5
11.9
12.3
11.4
10.7
11.5

17.8
17.3
16.1
15.5
15.0
16.1
15.4

28.7
27.6
26.8
26.2
27.0
26.5
26.1

28.9
28.4
29.9
29.3
29.4
30.1
28.9

24.6
26.8
27.2
29.0
28.6
27.3
29.6

9.3
9.6
10.9
10.8
10.1
9.8
10.6

17.6
17.3
15.8
14.4
15.0
15.9
15.1

28.0
27.9
26.7
26.6
27.4
27.6
27.6

29.9
28.9
29.3
29.2
30.0
29.2
28.9

24.5
25.9
28.2
29.8
27.6
27.3
28.4

Ecuador

1990
1997
1999
2002
2004
2005
2006

5.5
6.0
5.6
6.7
6.9
7.4
8.1

17.1
17.0
14.1
15.4
15.8
15.1
15.7

25.4
24.7
22.8
24.3
24.7
24.3
24.0

27.0
26.4
26.5
26.0
27.5
26.3
26.2

30.5
31.9
36.6
34.3
32.0
34.3
34.1

…
…
…
…
5.3
5.8
6.8

…
…
…
…
18.9
16.4
17.2

…
…
…
…
27.3
27.4
24.9

…
…
…
…
28.1
27.4
25.3

…
…
…
…
25.8
28.8
32.7

Poverty and income
distribution

Country

326

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 13 (continued)
HOUSEHOLD INCOME LEVELS AND DISTRIBUTION, URBAN AND RURAL AREAS, 1990-2006 a
(Percentages)
Country

Year

Average
income b

Share of total income of:
Poorest
40%

Next poorest 20% below
30%
richest 10%

Richest
10%

Average
income b

Share of total income of:
Poorest
40%

Urban areas

Next poorest 20% below
30%
richest 10%

Richest
10%

Rural areas, 1990-2006

Poverty and income
distribution

El Salvador

1995
1997
1999
2001
2004

6.9
7.1
7.7
7.6
6.7

17.3
17.2
16.3
15.6
17.9

25.1
24.8
25.9
25.1
26.3

25.8
26.9
28.6
28.5
28.5

31.7
31.1
29.2
30.8
27.3

5.1
4.7
4.9
5.2
5.2

17.0
19.4
15.6
14.7
16.6

29.6
28.6
28.8
27.4
29.7

27.3
27.3
29.8
30.3
27.9

26.1
24.7
25.9
27.7
25.8

Guatemala

1989
1998
2002

7.7
8.2
7.9

12.1
16.0
13.9

22.6
22.4
22.8

27.4
24.7
26.6

37.9
36.9
36.7

5.0
6.3
6.1

14.4
15.7
17.1

24.7
23.5
24.7

25.7
23.5
27.7

35.1
37.3
30.6

Honduras

1990
1997
1999
2002
2003

5.5
4.7
4.6
5.3
5.6

12.2
14.3
14.3
13.8
13.8

20.8
22.8
23.9
23.3
23.6

28.1
26.1
27.9
26.0
26.8

38.9
36.8
33.9
36.8
35.8

3.3
3.6
3.3
3.3
3.1

13.1
14.4
13.9
15.4
14.7

22.1
24.6
23.9
23.1
24.3

27.3
27.5
29.1
28.3
30.4

37.4
33.5
33.0
33.2
30.7

Mexico

1989
1994
1998
2000
2002
2004
2005
2006

9.6
9.7
8.6
9.0
8.9
8.9
9.5
9.4

16.3
16.8
17.2
16.9
17.9
17.5
17.5
18.5

22.0
22.8
22.3
23.3
24.0
23.4
23.1
24.1

24.9
26.1
25.7
26.1
26.9
26.2
24.9
26.1

36.9
34.3
34.8
33.6
31.2
33.0
34.5
31.3

6.7
6.6
6.2
7.4
6.9
7.1
7.1
7.6

18.7
20.1
17.9
15.6
18.0
18.1
18.1
19.6

26.5
25.3
23.7
21.5
23.2
24.5
24.9
25.4

27.4
27.6
26.8
24.3
26.5
26.2
26.6
25.9

27.4
27.0
31.5
38.7
32.3
31.2
30.4
29.1

Nicaragua

1993
1998
2001

6.1
6.4
6.8

12.9
12.3
13.2

23.6
22.3
21.2

26.9
26.4
24.3

36.5
39.1
41.4

3.9
4.5
4.4

12.4
10.8
14.3

24.3
24.1
26.4

30.0
27.8
28.6

33.4
37.3
30.7

Panama

1991
1994
1997
1999
2002
2004
2005
2006

10.8
12.7
13.2
12.6
11.9
11.8
11.0
11.6

14.1
14.6
13.7
15.6
14.2
15.5
15.7
15.7

23.8
23.6
22.5
25.2
24.9
24.9
25.0
24.8

29.4
25.1
26.9
27.8
28.2
27.8
28.2
27.4

32.7
36.8
36.9
31.5
32.7
31.9
31.1
32.1

…
…
…
…
8.5
7.4
7.0
7.3

…
…
…
…
11.1
14.0
14.2
14.2

…
…
…
…
23.9
26.6
26.8
26.7

…
…
…
…
30.7
29.2
29.9
30.2

…
…
…
…
34.3
30.2
29.2
28.9

Paraguay

1990 f
1996
1999
2001
2004
2005

7.7
7.4
7.1
7.4
5.5
5.9

18.6
16.7
16.5
15.9
16.4
16.4

25.7
24.6
24.9
23.4
24.2
23.6

26.9
25.3
25.8
27.5
26.4
26.4

28.9
33.4
32.8
33.1
33.0
33.6

…
…
5.0
4.6
4.8
4.9

…
…
15.1
14.6
15.0
15.6

…
…
21.2
24.9
22.6
26.2

…
…
24.3
27.7
23.5
26.2

…
…
39.4
32.9
39.0
32.0

Peru

1997
1999
2001
2003

9.2
9.2
7.6
7.7

17.3
16.2
16.9
17.9

25.4
23.6
25.4
25.2

26.7
26.6
26.9
26.8

30.6
33.6
30.8
30.1

4.4
4.4
3.7
3.4

17.8
17.4
19.2
25.0

27.1
17.9
27.6
29.7

29.4
23.8
28.0
27.5

25.7
40.9
25.2
17.7

Social Panorama of Latin America • 2007

327

Table 13 (concluded)
HOUSEHOLD INCOME LEVELS AND DISTRIBUTION, URBAN AND RURAL AREAS, 1990-2006 a
(Percentages)
Country

Year

Average
income b

Share of total income of:
Poorest
40%

Next poorest 20% below
30%
richest 10%

Richest
10%

Average
income b

Share of total income of:
Poorest
40%

Urban areas

Next poorest 20% below
30%
richest 10%

Richest
10%

Rural areas, 1990-2006

2000

8.2

11.4

22.2

28.0

38.4

5.5

14.0

25.6

27.0

33.5

2002

8.2

11.6

21.7

28.4

38.4

5.5

15.0

27.5

29.1

28.5

2004

9.8

19.5

28.1

42.5

5.0

13.6

23.5

30.3

32.7

7.9

10.4

21.5

30.0

38.1

6.2

11.6

23.0

28.9

36.5

2006
Uruguay

7.3

2005

9.0

9.7

20.3

28.3

41.7

6.4

11.6

22.9

31.1

34.4

1990

9.3

20.1

24.6

24.1

31.2

…

…

…

…

…

1997

11.2

21.9

26.1

26.1

25.8

…

…

…

…

…

1999

11.9

21.6

25.5

25.9

27.0

…

…

…

…

…

2002

9.4

21.6

25.4

25.6

27.3

…

…

…

…

…

2004

21.3

24.8

25.4

28.6

…

…

…

…

…

8.1

21.6

25.0

25.6

27.8

…

…

…

…

…

1990

Venezuela
(Bol. Rep. of)

8.2

2005

9.1

16.8

26.1

28.8

28.4

7.7

19.8

28.6

27.8

23.8

b

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
a
b
c
d
e
f

Households arranged in order of per capita income.
Average monthly household income in multiples of the per capita poverty line.
Greater Buenos Aires.
Eight major cities and El Alto.
As a result of a changeover to a new survey sample design in 2001, the figures for urban and rural areas are not strictly comparable with those of
previous years.
Asunción metropolitan area.

Poverty and income
distribution

Dominican
Republic

328

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 14
INDICATORS OF INCOME CONCENTRATION, NATIONAL TOTALS, 1990-2006 a
Country

Year

Percentage of persons with per
capita income of less than:
average

Concentration indices
Gini b

Variance of
logarithm of
income

Theil

Atkinson
(ε=1.5)

50%
of average

Poverty and income
distribution

Argentina c

1990
1997
1999
2002
2004
2005
2006

70.6
72.1
72.5
74.0
72.8
72.6
70.9

39.1
43.4
44.2
47.9
42.2
39.9
38.9

0.501
0.530
0.542
0.590
0.537
0.524
0.510

0.982
1.143
1.183
1.603
1.246
1.165
1.146

0.555
0.601
0.681
0.742
0.675
0.605
0.561

0.473
0.514
0.528
0.609
0.542
0.520
0.513

Bolivia

1989 d
1997
1999
2002

71.9
73.1
70.4
73.6

44.1
47.6
45.5
49.6

0.538
0.595
0.586
0.614

1.528
2.024
2.548
2.510

0.574
0.728
0.658
0.776

0.600
0.674
0.738
0.738

Brazil

1990
1996
1999
2001
2003
2004
2005
2006

75.2
76.3
77.1
76.9
76.2
76.0
76.5
75.9

53.9
54.4
54.8
54.4
52.5
51.6
51.4
50.7

0.627
0.638
0.640
0.639
0.621
0.612
0.613
0.602

1.938
1.962
1.913
1.925
1.802
1.707
1.690
1.646

0.816
0.871
0.914
0.914
0.838
0.826
0.840
0.807

0.664
0.668
0.663
0.665
0.647
0.632
0.629
0.621

Chile

1990
1996
2000
2003
2006

74.6
73.9
75.0
74.8
73.3

46.5
46.9
46.4
45.9
42.2

0.554
0.553
0.559
0.550
0.522

1.258
1.261
1.278
1.198
1.065

0.644
0.630
0.666
0.668
0.568

0.545
0.544
0.550
0.533
0.497

Colombia e

1994
1997
1999
2002
2004
2005

73.6
74.2
74.5
74.2
75.2
75.9

48.9
46.4
46.6
46.2
47.3
48.7

0.601
0.569
0.572
0.569
0.577
0.584

2.042
1.399
1.456
1.396
1.410
1.460

0.794
0.857
0.734
0.524
0.727
0.752

0.684
0.584
0.603
0.580
0.580
0.591

Costa Rica

1990
1997
1999
2002
2004
2005
2006

65.0
66.6
67.6
68.5
68.2
68.0
68.6

31.6
33.0
36.1
37.1
36.3
35.1
36.4

0.438
0.450
0.473
0.488
0.478
0.470
0.478

0.833
0.860
0.974
1.080
1.030
0.959
1.031

0.328
0.356
0.395
0.440
0.411
0.399
0.427

0.412
0.422
0.457
0.491
0.473
0.453
0.475

Ecuador

1990 f
1997 f
1999 f
2002 f
2004
2005
2006

69.6
68.9
72.1
72.3
71.3
71.8
72.2

33.8
34.8
42.0
39.8
41.5
42.1
42.3

0.461
0.469
0.521
0.513
0.513
0.531
0.526

0.823
0.832
1.075
1.031
1.089
1.190
1.083

0.403
0.409
0.567
0.563
0.519
0.565
0.711

0.422
0.419
0.498
0.487
0.495
0.522
0.504

Social Panorama of Latin America • 2007

329

Table 14 (continued)
INDICATORS OF INCOME CONCENTRATION, NATIONAL TOTALS, 1990-2006 a
Year

Percentage of persons with per
capita income of less than:
average

El Salvador

Concentration indices
Gini b

50%
of average

Variance of
logarithm of
income

Theil

Atkinson
(ε=1.5)

69.7

38.4

0.507

1.192

0.502

0.525

1997

69.9

40.2

0.510

1.083

0.512

0.492

1999

68.5

40.6

0.518

1.548

0.496

0.601

2001

69.1

40.8

0.525

1.559

0.528

0.602

2004
Guatemala

1995

68.1

37.5

0.493

1.325

0.449

0.552

0.736

0.590

1.182

0.760

0.534

72.8

47.9

0.543

1.142

0.589

0.515

1990

75.1

52.3

0.615

1.842

0.817

0.649

72.5

45.4

0.558

1.388

0.652

0.571

71.8

46.4

0.564

1.560

0.636

0.603

2002

72.8

49.6

0.588

1.607

0.719

0.608

2003

72.3

49.8

0.587

1.662

0.695

0.615

1989

74.2

43.5

0.536

1.096

0.680

0.509

1994

73.1

44.7

0.539

1.130

0.606

0.511

1998

72.8

43.1

0.539

1.142

0.634

0.515

2000

73.2

44.0

0.542

1.221

0.603

0.530

2002

71.7

41.2

0.514

1.045

0.521

0.485

2004

72.6

41.0

0.516

1.045

0.588

0.490

2005

72.5

41.6

0.528

1.125

0.635

0.513

2006

71.9

40.2

0.506

0.992

0.527

0.481

1993

71.5

45.9

0.582

1.598

0.671

0.619

1998

73.1

45.9

0.584

1.800

0.731

0.654

2001

74.6

46.9

0.579

1.594

0.783

0.619

1991

71.3

46.4

0.560

1.373

0.628

0.562

1994

72.5

46.1

0.567

1.440

0.706

0.579

1997

72.6

47.6

0.570

1.464

0.681

0.583

1999

70.5

44.2

0.536

1.283

0.541

0.538

2002

70.2

45.5

0.561

1.715

0.592

0.620

2004

70.7

44.0

0.548

1.562

0.554

0.592

2005

69.9

43.4

0.545

1.587

0.547

0.598

2006
Paraguay

1.477

0.560

1999

Panama

0.582

46.6

1997

Nicaragua

47.9

75.3

2002

Mexico

74.9

1998

Honduras

1989

70.3

43.3

0.548

1.639

0.571

0.609

1990 g

69.2

33.4

0.447

0.737

0.365

0.386

1996 f

72.9

37.9

0.493

0.916

0.515

0.453

1999

72.3

46.3

0.565

1.555

0.668

0.599

2001

72.9

44.4

0.570

1.705

0.702

0.631

2004

72.1

44.3

0.548

1.316

0.668

0.551

2005

71.0

42.1

0.536

1.319

0.614

0.553

Poverty and income
distribution

Country

330

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 14 (concluded)
INDICATORS OF INCOME CONCENTRATION, NATIONAL TOTALS, 1990-2006 a
Country

Year

Percentage of persons with per
capita income of less than:
average

50%
of average

Variance of
logarithm of
income

Theil

Atkinson
(ε=1.5)

0.554

1997

70.1

41.4

0.532

1.348

0.567

1999

71.7

42.7

0.545

1.358

0.599

0.560

2001

70.3

41.5

0.525

1.219

0.556

0.527

2003

…

…

0.506

1.051

0.503

0.484

2004

69.5

…

0.505

1.018

0.510

0.478

2005

70.0

…

…

…

…

…

2006

69.7

…

…

…

…

…

Dominican

2000

71.5

44.3

0.554

1.250

0.583

0.535

Republic

2002

71.6

43.0

0.544

1.216

0.570

0.529

2004

73.5

49.2

0.586

1.552

0.762

0.606

2005

72.0

46.9

0.569

1.536

0.629

0.595

2006

72.5

48.6

0.578

1.597

0.692

0.614

1990

73.2

36.8

0.492

0.812

0.699

0.441

1997

66.8

31.3

0.430

0.730

0.336

0.381

1999

67.1

32.2

0.440

0.764

0.354

0.393

2002

67.9

34.6

0.455

0.802

0.385

0.412

2004

68.5

35.8

0.464

0.824

0.412

0.414

2005

68.2

33.6

0.452

0.798

0.383

0.414

Venezuela

1990

68.0

35.5

0.471

0.930

0.416

0.446

(Bol. Rep. of)

1997

70.8

40.7

0.507

1.223

0.508

0.637

1999

69.4

38.6

0.498

1.134

0.464

0.507

2002

68.7

38.8

0.500

1.122

0.456

0.507

2004

67.5

35.4

0.470

0.935

0.389

0.453

2005

68.1

36.4

0.490

1.148

0.472

0.510

2006

Poverty and income
distribution

Peru

Concentration indices
Gini b

66.5

32.9

0.441

0.811

0.359

0.409

Uruguay f

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a
b
c
d
e
f
g

Calculated on the basis of per capita income distribution throughout the country. Tables 15 and 16 present disaggregated figures for urban and rural
areas.
Includes individuals with zero income.
Greater Buenos Aires.
Eight major cities and El Alto.
As a result of a changeover to a new survey sample design in 2001, the figures for urban areas and rural areas are not strictly comparable with those
of previous years.
Urban total.
Asunción metropolitan area.

Social Panorama of Latin America • 2007

331

Table 15
INDICATORS OF INCOME CONCENTRATION, NATIONAL TOTALS, URBAN AREAS,1990-2006 a
Year

Percentage of persons with per
capita income of less than:
average

Concentration indices
Gini b

Variance of
logarithm of
income

Theil

Atkinson
(ε=1.5)

50%
of average

Argentina

1990 c
1997 c
1999
2002
2004
2005
2006

70.6
72.1
72.1
73.1
72.0
72.4
71.2

39.1
43.4
43.3
47.2
40.9
40.5
40.0

0.501
0.530
0.539
0.578
0.531
0.526
0.519

0.982
1.143
1.194
1.510
1.225
1.190
1.173

0.555
0.601
0.667
0.724
0.633
0.602
0.626

0.473
0.514
0.530
0.593
0.534
0.525
0.522

Bolivia

1989 d
1997
1999
2002

71.9
72.5
70.4
74.7

44.1
43.0
40.1
46.6

0.538
0.531
0.504
0.554

1.528
1.772
1.131
1.286

0.574
0.573
0.487
0.633

0.600
0.521
0.511
0.549

Brazil

1990
1996
1999
2001
2003
2004
2005
2006

74.7
75.7
76.5
76.4
75.9
75.9
76.1
75.7

52.2
53.1
53.8
53.3
51.9
51.0
51.0
50.2

0.606
0.620
0.625
0.628
0.612
0.603
0.604
0.593

1.690
1.735
1.742
1.777
1.691
1.608
1.586
1.532

0.748
0.815
0.865
0.875
0.806
0.797
0.810
0.776

0.625
0.634
0.637
0.643
0.629
0.615
0.612
0.601

Chile

1990
1996
2000
2003
2006

73.8
73.5
74.7
75.0
72.8

45.1
45.7
45.9
45.1
41.8

0.542
0.544
0.553
0.547
0.517

1.204
1.206
1.246
1.184
1.048

0.600
0.604
0.643
0.661
0.553

0.531
0.532
0.542
0.529
0.492

Colombia e

1994
1997
1999
2002
2004
2005

74.6
73.8
74.2
74.0
74.8
75.7

48.1
46.5
46.1
46.7
48.2
49.3

0.579
0.577
0.564
0.576
0.582
0.587

1.491
1.571
1.312
1.418
1.425
1.435

0.749
0.714
0.707
0.716
0.728
0.749

0.597
0.545
0.559
0.580
0.581
0.583

Costa Rica

1990
1997
1999
2002
2004
2005
2006

63.6
65.3
66.3
67.3
66.8
67.2
68.2

29.6
32.2
34.5
35.2
34.3
34.8
36.2

0.419
0.429
0.454
0.465
0.462
0.459
0.469

0.727
0.779
0.881
0.916
0.924
0.895
0.961

0.295
0.323
0.356
0.398
0.384
0.379
0.404

0.376
0.394
0.427
0.443
0.443
0.434
0.454

Ecuador

1990
1997
1999
2002
2004
2005
2006

69.6
68.9
72.1
72.3
70.3
71.1
71.4

33.8
34.8
42.0
39.8
38.8
41.1
39.8

0.461
0.469
0.521
0.513
0.498
0.513
0.505

0.823
0.832
1.075
1.031
0.991
1.070
0.979

0.403
0.409
0.567
0.563
0.485
0.517
0.610

0.422
0.419
0.498
0.487
0.469
0.491
0.474

Poverty and income
distribution

Country

332

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 15 (continued)
INDICATORS OF INCOME CONCENTRATION, NATIONAL TOTALS, URBAN AREAS,1990-2006 a
Country

Year

Percentage of persons with per
capita income of less than:
average

Concentration indices
Gini b

Variance of
logarithm of
income

Theil

Atkinson
(ε=1.5)

50%
of average

Poverty and income
distribution

El Salvador

1995
1997
1999
2001
2004

69.5
70.0
68.0
68.6
67.3

34.3
34.6
35.7
36.8
34.8

0.466
0.467
0.462
0.477
0.455

0.836
0.864
1.002
1.090
0.970

0.428
0.428
0.388
0.435
0.379

0.424
0.430
0.483
0.501
0.462

Guatemala

1989
1998
2002

72.2
74.5
71.8

45.6
40.3
42.2

0.558
0.525
0.524

1.377
0.997
1.106

0.640
0.653
0.532

0.566
0.486
0.508

Honduras

1990
1997
1999
2002
2003

73.1
71.8
70.8
72.3
71.0

46.6
40.9
41.6
42.3
41.9

0.561
0.527
0.518
0.533
0.527

1.397
1.142
1.138
1.227
1.256

0.661
0.578
0.528
0.580
0.548

0.570
0.516
0.509
0.533
0.535

Mexico

1989
1994
1998
2000
2002
2004
2005
2006

75.2
73.6
73.2
72.1
71.6
72.8
73.2
72.1

42.5
41.6
41.5
38.7
31.2
39.3
39.2
37.2

0.530
0.512
0.507
0.493
0.477
0.493
0.497
0.478

1.031
0.934
0.901
0.856
0.800
0.848
0.843
0.809

0.678
0.544
0.578
0.500
0.444
0.537
0.582
0.469

0.495
0.460
0.455
0.436
0.415
0.436
0.440
0.436

Nicaragua

1993
1998
2001

71.4
72.3
73.9

42.6
43.4
44.0

0.549
0.551
0.560

1.256
1.271
1.225

0.595
0.673
0.746

0.541
0.552
0.546

Panama

1991
1994
1997
1999
2002
2004
2005
2006

70.3
72.5
72.1
68.4
70.3
69.6
68.7
69.8

44.0
42.9
44.1
39.7
41.1
40.1
40.4
40.2

0.530
0.537
0.543
0.499
0.515
0.500
0.500
0.501

1.254
1.198
1.304
1.088
1.217
1.105
1.154
1.096

0.543
0.642
0.611
0.459
0.488
0.449
0.454
0.472

0.534
0.530
0.550
0.490
0.522
0.494
0.508
0.496

Paraguay

1990 f
1996
1999
2001
2004
2005

69.2
72.9
70.0
72.0
70.5
71.1

33.4
37.9
39.1
40.2
38.9
40.8

0.447
0.493
0.497
0.511
0.496
0.504

0.737
0.916
0.997
1.081
0.971
1.000

0.365
0.515
0.490
0.549
0.518
0.545

0.386
0.453
0.472
0.501
0.468
0.477

Peru

1997
1999
2001
2003
2004
2005
2006

70.4
74.0
70.6
…
70.0
69.8
70.0

36.0
39.4
35.7
…
…
…
…

0.473
0.498
0.477
0.456
0.471
…
…

0.863
0.954
0.903
0.790
0.856
…
…

0.453
0.499
0.465
0.412
0.444
…
…

0.433
0.465
0.448
0.409
0.432
…
…

Social Panorama of Latin America • 2007

333

Table 15 (concluded)
INDICATORS OF INCOME CONCENTRATION, NATIONAL TOTALS, URBAN AREAS,1990-2006 a
Country

Year

Percentage of persons with per
capita income of less than:
average

Concentration indices
Gini b

50%
of average

Variance of
logarithm of
income

Theil

Atkinson
(ε=1.5)

2000

71.5

43.6

0.550

1.236

0.569

0.532

Republic

2002

71.8

44.4

0.548

1.232

0.569

0.532

2004

74.1

50.6

0.598

1.652

0.799

0.625

2005

71.6

47.1

0.568

1.533

0.622

0.593

2006

73.0

49.4

0.584

1.648

0.703

0.628

1990

73.2

36.8

0.492

0.812

0.699

0.441

1997

66.8

31.3

0.430

0.730

0.336

0.381

1999

67.1

32.2

0.440

0.764

0.354

0.393

2002

67.9

34.6

0.455

0.802

0.385

0.412

2004

68.5

35.8

0.464

0.824

0.412

0.414

2005

68.2

33.6

0.452

0.798

0.383

0.414

1990

67.7

34.4

0.464

0.903

0.403

0.437

Uruguay

Venezuela
(Bol. Rep. of)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a
b
c
d
e
f

Calculated on the basis of per capita income distribution in urban areas.
Includes individuals with zero income.
Greater Buenos Aires.
Eight major cities and El Alto.
As a result of a changeover to a new survey sample design in 2001, the figures for urban areas are not strictly comparable with those of earlier years.
Asunción metropolitan area.

Poverty and income
distribution

Dominican

334

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 16
INDICATORS OF INCOME CONCENTRATION, RURAL AREAS, 1990-2006 a
Country

Year

Percentage of persons with per
capita income of less than:
average

Concentration indices
Gini b

Variance
of logarithm
of income

Theil

Atkinson
(ε=1.5)

50%
of average

Poverty and income
distribution

Bolivia

1997
1999
2002

75.4
71.3
73.4

53.6
52.9
51.1

0.637
0.640
0.632

2.133
2.772
2.662

0.951
0.809
0.799

0. 692
0.752
0.746

Brazil

1990
1996
1999
2001
2003
2004
2005
2006

72.5
73.1
73.8
73.0
72.1
72.4
71.6
70.9

45.5
47.6
47.4
47.1
46.2
45.0
43.8
43.6

0.548
0.578
0.577
0.581
0.564
0.552
0.542
0.538

1.266
1.424
1.357
1.451
1.401
1.286
1.239
1.282

0.627
0.727
0.773
0.790
0.734
0.675
0.658
0.664

0.545
0.578
0.569
0.587
0.576
0.550
0.539
0.546

Chile

1990
1996
2000
2003
2006

79.0
73.9
74.5
75.5
75.7

47.9
36.2
38.7
38.1
38.7

0.578
0.492
0.511
0.507
0.506

1.269
0.887
0.956
0.909
0.904

0.854
0.542
0.669
0.622
0.614

0.563
0.452
0.478
0.464
0.463

Colombia c

1994
1997
1999
2002
2004
2005

69.8
73.8
72.1
70.4
67.3
70.5

45.5
46.5
39.5
37.0
33.0
35.6

0.570
0.554
0.525
0.499
0.465
0.495

2.047
1.571
1.291
1.133
0.982
1.124

0.621
0.714
0.626
0.524
0.443
0.511

0.674
0.509
0.582
0.525
0.469
0.512

Costa Rica

1990
1997
1999
2002
2004
2005
2006

63.3
65.7
66.8
67.5
65.7
66.0
65.8

27.9
30.4
33.0
34.6
32.4
32.3
32.3

0.419
0.426
0.457
0.481
0.453
0.444
0.449

0.771
0.757
0.895
1.056
0.936
0.860
0.930

0.301
0.316
0.377
0.436
0.360
0.352
0.385

0.390
0.387
0.434
0.487
0.444
0.422
0.445

Ecuador

2004
2005
2006

66.0
67.6
71.0

31.7
34.8
35.3

0.431
0.469
0.479

0.755
0.885
0.795

0.333
0.466
0.872

0.388
0.439
0.433

El Salvador

1995
1997
1999
2001
2004

64.4
66.3
64.8
65.2
64.9

29.9
30.9
34.0
35.5
32.4

0.442
0.423
0.462
0.477
0.456

0.961
0.670
1.302
1.329
1.231

0.352
0.343
0.382
0.414
0.385

0.457
0.361
0.540
0.549
0.525

Guatemala

1989
1998
2002

72.6
75.0
72.5

37.6
40.6
36.1

0.513
0.510
0.470

1.076
0.882
0.794

0.593
0.697
0.420

0.500
0.461
0.416

Honduras

1990
1997
1999
2002
2003

73.9
70.9
69.8
71.8
70.9

45.6
38.7
39.8
42.6
40.2

0.558
0.504
0.512
0.519
0.508

1.326
1.083
1.244
1.072
1.060

0.692
0.520
0.516
0.567
0.501

0.559
0.498
0.537
0.495
0.486

Social Panorama of Latin America • 2007

335

Table 16 (concluded)
INDICATORS OF INCOME CONCENTRATION, RURAL AREAS, 1990-2006 a
Year

Percentage of persons with per
capita income of less than:
average

Mexico

Concentration indices
Gini b

50%
of average

Variance
of logarithm
of income

Theil

Atkinson
(ε=1.5)

1989

68.8

33.5

0.453

0.769

0.401

0.401

1994

69.5

34.9

0.451

0.720

0.385

0.384
0.430

1998

0.846

0.467

0.553

1.125

0.682

0.517

72.7

39.7

0.498

0.879

0.528

0.444

69.9

36.7

0.480

0.886

0.518

0.443

2005

70.9

37.6

0.486

0.932

0.493

0.455

2006

70.1

34.5

0.466

0.784

0.470

0.413

1993

69.2

41.6

0.536

1.348

0.553

0.573

1998

68.2

42.4

0.558

1.765

0.598

0.644

2001

67.6

37.9

0.506

1.367

0.503

0.562

1991

70.2

40.4

0.514

0.999

0.579

0.477

1994

68.3

39.0

0.491

0.983

0.459

0.463

1997

71.6

40.2

0.511

1.031

0.563

0.486

1999

69.8

36.5

0.481

0.882

0.461

0.439

2002

70.3

41.1

0.515

1.217

0.488

0.623

2004

69.6

43.7

0.542

1.390

0.580

0.561

2005

68.5

42.5

0.536

1.432

0.540

0.548

2006
Paraguay

0.486

46.1

2004

Panama

41.5

75.3

2002

Nicaragua

70.2

2000

68.9

43.0

0.546

1.568

0.568

0.593

1999

74.1

47.1

0.570

1.389

0.839

0.578

2001

70.6

42.4

0.548

1.483

0.752

0.595

2004

75.1

45.0

0.570

1.282

0.878

0.562

2005

70.3

40.5

0.523

1.258

0.597

0.538

1997

66.5

33.9

0.451

0.868

0.383

0.424

1999

65.8

31.1

0.427

0.803

0.320

0.400

2001

66.9

31.8

0.439

0.745

0.380

0.390

2003

…

…

0.358

0.473

0.222

0.276

2004

67.5

…

0.398

0.562

0.309

0.323

2005

67.6

…

…

…

…

…

2006

66.9

…

…

…

…

…

Dominican

2000

70.2

37.0

0.501

0.969

0.456

0.460

Republic

2002

67.0

34.4

0.473

0.919

0.403

0.443

2004

67.9

40.1

0.503

1.133

0.460

0.503

2005

71.1

42.9

0.542

1.369

0.568

0.564

2006

68.3

42.4

0.520

1.261

0.513

0.532

1990

67.0

31.3

0.431

0.724

0.348

0.379

Peru

Venezuela
(Bol. Rep. of)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Calculated on the basis of per capita income distribution in rural areas.
Includes individuals with zero income.
c As a result of the changeover to a new survey sample design in 2001, the figures for rural areas are not strictly comparable with those of earlier years.
b

Poverty and income
distribution

Country

336

Economic Commission for Latin America and the Caribbean (ECLAC)

Labour market
Table 17
MALE AND FEMALE ECONOMIC ACTIVITY RATES BY AGE GROUP,
URBAN AREAS, 1990-2006
Country

Year

Age
Males

Females

Total

15 - 24

25 - 34

35 - 49

50
and over

Total

15 - 24

25 - 34

35 - 49

50
and over

1990
1994
1997
1999
2000
2002
2004
2005
2006

76
76
76
76
76
75
78
78
77

62
65
61
58
57
52
61
61
58

97
98
97
96
96
96
96
96
96

97
97
97
97
97
98
97
97
97

55
54
59
62
62
63
65
65
65

38
41
45
47
46
48
52
51
52

41
43
44
42
43
40
45
41
46

53
59
61
66
63
66
71
69
69

52
56
60
63
62
70
70
71
70

19
21
27
29
29
28
34
35
35

(Urban)

Labour market

Argentina
(Greater Buenos
Aires)

1999
2000
2002
2004
2005
2006

74
74
72
75
75
75

53
52
48
55
55
54

94
94
93
94
94
94

97
96
96
96
96
96

59
60
60
63
64
64

44
45
46
50
50
50

36
36
35
39
37
38

62
62
64
69
68
67

61
62
67
70
70
69

27
28
27
33
34
34

Bolivia

1989
1994
1997
1999
2000
2002
2004

73
75
75
75
77
77
79

47
50
48
49
51
51
58

90
92
92
93
92
93
93

97
98
98
98
98
98
97

64
65
73
72
74
75
76

47
51
51
54
54
57
58

35
37
35
40
36
39
41

57
62
61
64
68
71
68

61
68
68
71
74
75
76

34
37
42
46
42
49
55

Brazil

1990
1993
1996
1999
2001
2003
2004
2005
2006

82
83
80
80
79
79
79
80
79

78
77
72
72
70
70
71
72
71

96
96
94
95
94
94
95
95
94

95
95
94
93
93
93
93
93
93

59
60
59
59
59
59
59
59
60

45
50
50
53
53
55
56
57
57

48
51
50
51
52
53
55
57
56

56
60
63
67
67
70
72
73
73

53
60
61
64
65
68
69
70
71

21
27
26
28
29
30
30
32
33

Chile

1990
1994
1996
1998
2000
2003
2006

72
75
74
74
73
73
73

47
49
44
44
39
40
43

94
94
94
93
92
92
92

95
96
96
97
96
96
96

56
62
62
64
64
64
65

35
38
39
41
42
45
45

29
32
29
30
28
31
31

47
50
53
57
57
60
64

46
50
51
54
56
59
61

20
23
23
26
26
29
31

Colombia a

1991
1994
1997
1999
2002
2004
2005

81
79
78
79
79
78
78

62
58
55
59
61
59
57

97
96
96
96
96
96
95

97
97
97
96
96
96
96

69
65
65
64
65
66
64

48
48
50
55
57
56
55

44
43
42
48
51
48
46

63
65
68
73
76
74
75

56
59
63
69
72
71
71

22
21
24
27
32
33
32

Costa Rica

1990
1994
1997
1999
2000
2002
2004
2005
2006

78
76
77
79
77
77
78
78
78

62
59
60
61
59
57
59
56
57

96
94
96
95
96
97
96
97
96

95
96
96
96
96
97
97
98
96

61
57
58
65
60
61
62
67
66

39
40
42
45
43
46
45
48
48

39
35
33
40
38
37
35
39
40

53
54
61
58
59
63
61
65
66

49
52
54
58
54
60
61
63
64

14
17
21
23
49
25
23
27
27

Social Panorama of Latin America • 2007

337

Table 17 (continued)
MALE AND FEMALE ECONOMIC ACTIVITY RATES BY AGE GROUP,
URBAN AREAS, 1990-2006
Country

Year

Age
Males

Females

Total

15 - 24

25 - 34

35 - 49

50
and over

Total

15 - 24

25 - 34

35 - 49

50
and over

2000
2001
2002
2003
2004
2005
2006

71
71
69
68
68
68
67

48
45
40
38
38
38
38

91
90
90
89
88
88
88

94
94
93
93
93
93
92

50
51
50
50
50
49
49

44
44
47
46
43
42
43

28
26
23
25
25
27
29

63
63
61
61
60
60
61

67
65
66
66
66
65
66

20
20
24
25
21
21
20

Ecuador

1990
1994
1997
1999
2000
2002
2004
2005
2006

80
81
81
82
80
81
81
81
82

56
59
58
64
59
60
59
60
62

95
96
97
97
95
96
96
97
96

98
98
98
98
97
98
99
98
98

78
76
75
76
74
74
76
76
77

43
47
49
54
51
53
54
54
55

33
39
38
45
41
40
44
40
40

54
58
61
65
63
65
68
68
70

56
58
62
67
63
67
67
68
70

31
34
35
36
36
41
40
42
42

El Salvador

1990
1995
1997
1999
2000
2001
2002
2004

80
78
75
75
75
75
73
74

64
61
54
58
56
57
52
55

95
95
95
93
93
93
92
92

96
96
97
94
96
95
94
95

72
68
66
63
66
64
61
61

51
49
48
52
51
51
51
51

41
36
33
38
35
35
35
36

66
65
65
68
68
68
67
67

66
69
68
69
70
70
70
69

36
34
34
37
37
36
35
35

Guatemala

1989
1998
2002

84
82
85

69
66
75

97
95
95

97
97
97

78
77
78

43
54
58

42
47
54

50
60
65

49
68
72

29
44
41

Honduras

1990
1994
1997
1999
2002
2003
2006

81
80
83
82
79
78
76

66
64
70
67
63
63
56

95
93
96
97
94
93
94

97
96
98
96
96
94
96

73
74
74
78
74
73
72

43
43
51
54
47
50
48

35
35
43
45
38
40
37

54
54
63
64
58
63
62

57
51
63
69
62
66
64

30
31
35
37
36
37
35

Mexico

1989
1994
1996
1998
2000
2002
2004
2005
2006

77
81
80
81
82
79
80
80
81

58
63
60
61
62
59
61
60
61

96
97
97
96
97
95
97
96
96

97
97
97
98
97
96
97
97
97

68
69
68
71
71
70
69
69
71

33
38
41
43
42
45
47
47
51

31
34
36
39
36
36
37
36
40

45
49
50
51
52
55
58
59
62

39
46
50
51
53
57
60
60
64

18
21
24
28
26
29
30
33
36

Nicaragua

1993
1998
2001

71
81
83

50
66
72

86
95
96

89
95
95

66
74
73

44
51
52

26
36
40

57
66
62

62
67
68

32
38
39

Panama

1991
1994
1997
1999
2002
2004
2005
2006

72
77
78
77
79
78
78
77

52
59
60
61
58
60
58
55

95
97
96
97
98
96
97
96

96
97
97
96
98
97
97
97

48
54
59
58
65
62
61
60

48
49
50
50
54
51
51
50

39
40
40
42
39
39
39
37

66
66
66
67
71
68
67
67

65
66
69
68
69
70
70
68

20
21
26
26
34
29
30
31

Labour market

Cuba b

338

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 17 (concluded)
MALE AND FEMALE ECONOMIC ACTIVITY RATES BY AGE GROUP,
URBAN AREAS, 1990-2006
Country

Year

Age
Males

Females

Total

15 - 24

25 - 34

35 - 49

50
and over

Total

15 - 24

25 - 34

35 - 49

50
and over

1990
1994
1996
1999
2001
2004
2005

84
82
86
83
81
83
81

69
69
76
68
67
69
62

97
99
97
97
95
96
96

99
98
97
95
96
97
97

75
66
75
73
69
74
69

50
58
59
54
57
59
60

51
58
54
46
52
51
51

63
74
69
65
76
74
73

58
76
71
66
68
72
72

27
31
40
39
38
43
48

(Urban)

1994
1996
1999
2001
2004
2005

86
86
83
81
83
81

75
78
64
68
66
65

98
98
97
95
96
96

98
97
95
96
98
97

71
73
76
70
72
70

53
58
55
57
59
59

53
54
47
51
50
50

62
65
66
72
75
72

62
69
67
67
73
71

32
40
42
40
42
46

Peru

1997
1999
2001
2003

83
73
74
74

66
53
56
56

96
87
88
88

98
91
92
93

77
68
66
66

62
55
54
54

54
49
46
45

74
66
67
62

76
66
69
72

45
39
38
34

Dominican
Republic

1992
1995
1997
2000
2002
2003
2004
2005
2006

86
78
83
78
78
80
79
78
78

77
62
70
61
62
62
64
62
61

96
95
96
93
95
96
95
95
95

98
98
97
95
97
96
97
96
96

76
68
71
68
65
68
64
61
66

53
44
49
51
53
51
56
53
54

57
40
44
41
45
43
49
46
46

66
64
65
66
73
69
73
71
73

57
57
61
70
71
66
72
72
72

25
20
22
26
25
27
29
24
29

Uruguay

1990
1994
1997
1999
2000
2002
2004
2005

75
75
73
73
74
72
71
71

68
72
71
67
68
63
61
60

98
97
96
96
96
96
96
95

97
97
97
97
98
96
97
96

54
52
49
50
50
51
51
50

44
47
47
50
50
50
49
50

47
52
51
50
52
47
44
46

69
74
74
75
75
76
75
76

64
70
71
74
75
76
75
77

21
23
23
26
26
28
29
29

Venezuela
(Bol. Rep. of) c

Labour market

Paraguay
(Asunción)

1990
1994
1997
1999
2000
2002
2004
2005
2006

78
79
83
84
82
84
82
81
81

55
58
66
67
64
67
63
60
59

93
94
96
97
96
97
96
96
96

96
97
97
97
97
97
97
97
97

71
68
73
75
72
74
76
74
73

38
38
46
48
47
55
54
52
51

25
26
34
36
34
42
39
35
33

51
52
59
61
60
69
69
66
65

52
53
61
64
63
71
71
69
69

21
20
28
30
32
37
37
37
37

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992 the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
b National Statistical Office (ONE), Cuba, on the basis of tabulations of data from the National Occupation Survey, 2006.
c The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Social Panorama of Latin America • 2007

339

Table 18
MALE AND FEMALE ECONOMIC ACTIVITY RATES BY YEARS OF SCHOOLING,
URBAN AREAS, 1990-2006
Country

Year

Years of schooling
Males

Females

Total

0-3

4-6

7-9

10 - 12

13 and
over

Total

0-3

4-6

7-9

10 - 12

13 and
over

1990
1994
1997
1999
2000
2002
2004
2005
2006

76
76
76
76
76
75
78
78
77

...
...
63
60
56
61
65
61
64

...
...
68
73
63
70
72
74
67

74
74
73
73
74
73
75
74
72

86
85
77
79
79
74
81
80
81

84
83
88
86
87
86
85
88
87

38
41
45
47
46
48
52
51
52

...
...
27
28
27
32
30
30
30

...
...
29
32
32
32
37
38
40

31
33
35
35
36
36
41
38
39

50
53
48
50
51
50
53
51
55

66
70
74
76
72
74
77
77
76

(Urban)

1999
2000
2002
2004
2005
2006

74
70
72
75
75
75

58
57
60
62
59
62

71
71
69
69
71
68

72
70
71
74
72
71

76
72
73
77
77
79

80
74
79
81
82
82

44
42
46
50
50
50

25
24
27
29
28
27

30
31
33
35
37
37

34
34
36
41
38
37

47
44
48
51
50
52

70
63
68
71
71
71

Bolivia

1989
1994
1997
1999
2000
2002
2004

73
75
75
75
77
77
79

78
80
83
78
79
81
82

87
87
88
86
92
89
89

68
69
67
76
75
72
73

71
71
72
71
73
73
78

68
75
72
73
74
77
76

47
51
51
54
54
57
58

50
54
55
57
53
62
62

51
56
57
57
63
61
62

41
43
41
53
52
52
50

40
45
45
47
47
51
53

53
57
58
61
58
63
66

Brazil

1990
1993
1996
1999
2001
2003
2004
2005
2006

82
83
80
80
79
79
79
80
79

76
77
73
72
71
70
69
68
67

84
84
80
80
79
78
78
78
77

83
83
80
79
78
77
77
78
77

88
88
86
86
86
86
87
87
87

91
90
89
88
88
88
88
88
88

45
50
50
53
53
55
56
57
57

33
38
36
37
36
36
36
36
35

41
47
46
47
47
48
48
49
49

45
50
50
52
51
52
53
54
53

61
65
64
67
67
68
69
71
70

77
79
80
79
80
80
80
81
80

Chile

1990
1994
1996
1998
2000
2003
2006

72
75
74
74
73
73
73

59
59
61
60
57
55
52

74
74
74
72
70
66
65

66
67
67
66
65
64
62

74
79
78
78
76
78
78

80
80
79
81
80
80
81

35
38
39
41
42
45
45

20
21
20
23
20
21
21

28
28
26
29
28
29
28

26
29
31
31
32
33
33

35
40
41
43
44
47
49

62
58
62
64
64
66
67

Colombia b

1991
1994
1997
1999
2002
2004
2005

81
79
78
79
79
78
78

80
75
73
74
73
73
70

85
84
82
83
82
81
80

76
71
69
70
72
69
69

81
80
79
79
84
84
83

83
86
84
85
80
79
79

48
48
50
55
57
56
56

37
35
34
38
40
38
36

42
43
43
49
51
49
48

42
39
42
48
50
48
47

56
56
57
61
65
62
62

70
76
76
78
74
73
73

Costa Rica

1990
1994
1997
1999
2000
2002
2004
2005
2006

78
76
77
79
77
77
78
78
78

66
62
59
61
58
58
58
60
58

84
83
82
84
83
82
82
84
83

73
70
72
75
73
70
70
71
71

77
77
77
80
76
75
81
78
78

82
81
83
84
85
86
85
86
86

39
40
42
45
43
46
45
48
48

21
22
19
28
20
23
20
24
23

33
33
37
39
37
40
35
42
42

35
34
35
38
36
40
39
41
41

47
46
44
49
49
49
50
49
49

62
64
68
67
68
70
69
70
70

Cuba c

2006

67

16

34

68

73

81

43

3

9

30

55

75

Labour market

Argentina a
(Greater Buenos
Aires)

340

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 18 (continued)
MALE AND FEMALE ECONOMIC ACTIVITY RATES BY YEARS OF SCHOOLING,
URBAN AREAS, 1990-2006
Country

Year

Years of schooling
Males

Females

Total

0-3

4-6

7-9

10 - 12

13 and
over

Total

0-3

4-6

7-9

10 - 12

13 and
over

1990
1994
1997
1999
2000
2002
2004
2005
2006

80
81
81
82
80
81
81
81
82

82
79
81
81
74
76
73
74
74

90
90
88
89
87
87
89
87
88

69
70
71
74
75
75
74
77
76

73
76
76
78
73
76
77
77
80

81
84
86
86
84
85
85
86
85

43
47
49
54
51
53
54
54
55

39
41
43
45
43
45
41
41
41

39
45
45
50
46
52
51
50
48

34
37
37
44
43
46
47
48
49

44
47
46
53
49
51
51
50
52

65
66
70
72
70
67
73
74
75

El Salvador

Labour market

Ecuador

1990
1995
1997
1999
2000
2001
2002
2004

80
78
75
75
75
75
73
74

80
77
76
72
72
72
68
69

86
84
80
80
78
80
76
78

75
71
71
73
71
70
68
71

78
77
74
75
77
77
75
77

80
79
76
78
78
78
77
76

51
49
48
52
51
51
51
51

45
43
44
43
46
43
43
41

56
52
49
53
52
51
50
50

45
43
40
46
44
46
44
44

56
53
53
57
55
56
56
59

68
67
65
69
65
65
66
68

Guatemala

1989
1998
2002

84
82
85

90
85
86

89
88
93

65
68
78

81
81
80

87
82
87

43
54
58

38
53
54

41
54
57

37
45
56

57
58
62

77
74
75

Honduras

1990
1994
1997
1999
2002
2003
2006

81
80
83
82
79
78
76

84
81
83
85
81
78
77

88
88
90
87
87
86
86

61
59
72
64
63
65
62

80
82
80
81
75
76
70

76
79
82
84
80
79
78

43
43
51
54
47
50
48

39
37
43
48
41
42
38

43
45
53
56
48
51
50

31
29
38
41
38
42
39

59
50
59
61
53
56
53

53
63
67
65
65
66
69

Mexico

1989
1994
1996
1998
2000
2002
2004
2005
2006

77
81
80
81
82
79
80
80
81

79
80
75
71
72
73
72
69
71

87
88
87
83
85
83
84
85
85

74
81
81
85
87
84
83
82
83

65
69
71
79
80
79
76
76
77

80
83
82
81
83
79
83
83
82

33
38
41
43
42
45
47
47
51

21
29
32
33
32
29
34
34
36

33
32
36
39
35
38
40
42
44

37
41
42
38
36
40
45
45
49

42
40
41
43
45
47
49
48
53

55
58
62
63
55
63
65
65
68

Nicaragua

1993
1998
2001

71
81
83

70
83
84

74
87
89

66
79
77

70
75
78

83
90
86

44
51
52

39
46
43

43
49
50

40
46
52

51
54
58

67
76
72

Panama

1991
1994
1997
1999
2002
2004
2005
2006

72
77
78
77
79
78
78
77

56
61
64
57
75
60
65
60

70
76
76
74
81
77
76
76

69
73
72
75
75
76
71
74

72
77
80
77
77
78
80
78

81
88
85
85
86
86
85
83

48
49
50
50
54
51
51
50

24
20
23
19
45
21
24
23

37
37
39
39
43
37
38
35

39
41
41
41
41
42
42
41

50
53
52
50
54
50
51
49

71
73
73
73
73
74
73
72

Paraguay
(Asunción)

1990
1994
1996
1999
2001
2004
2005

84
82
86
83
81
83
81

75
64
76
73
69
74
69

88
83
91
88
83
86
86

82
78
82
79
80
81
75

83
82
86
81
79
80
82

87
89
91
91
88
88
87

50
58
59
54
57
59
60

29
39
43
40
39
44
45

53
57
57
51
56
57
61

45
51
53
49
51
57
48

50
57
63
57
58
58
61

71
74
81
79
79
75
78

Social Panorama of Latin America • 2007

341

Table 18 (concluded)
MALE AND FEMALE ECONOMIC ACTIVITY RATES BY YEARS OF SCHOOLING,
URBAN AREAS, 1990-2006
Country

Year

Years of schooling
Males

Females

Total

0-3

4-6

7-9

10 - 12

13 and
over

Total

0-3

4-6

7-9

10 - 12

13 and
over

1994
1996
1999
2001
2004
2005

86
86
83
81
83
81

76
77
70
72
76
71

92
92
87
86
88
86

83
82
80
80
80
75

84
87
81
79
81
81

91
92
91
87
89
89

53
58
55
57
59
59

38
44
43
41
44
45

53
57
49
58
59
57

47
53
50
50
56
49

58
63
57
57
58
60

78
81
78
79
77
80

Peru

1997
1999
2001
2003

83
73
74
74

77
70
72
68

82
71
78
77

71
65
69
71

85
78
79
80

92
83
82
81

62
55
54
54

58
54
50
55

61
58
57
53

51
51
50
51

62
53
55
56

77
70
65
67

Dominican
Republic

1992
1995
1997
2000
2002
2003
2004
2005
2006

86
78
83
78
78
80
79
78
78

87
74
77
70
74
74
70
69
70

91
81
84
81
80
80
80
78
79

85
76
84
77
77
77
77
78
77

85
74
82
77
77
80
82
78
80

88
86
90
90
87
89
87
86
88

53
44
49
51
53
51
46
53
54

38
28
34
30
32
33
37
32
33

43
37
41
44
45
41
47
45
45

48
39
42
46
48
45
53
49
47

61
47
56
55
57
55
58
57
58

80
72
80
78
79
79
79
75
77

Uruguay

1990
1994
1997
1999
2000
2002
2004
2005

75
75
73
73
74
72
71
71

50
41
40
39
39
38
34
33

74
74
70
69
71
67
66
64

79
84
82
83
82
77
75
77

84
82
80
78
77
78
78
76

83
83
84
83
80
83
83
83

44
47
47
50
50
50
49
50

18
17
16
17
18
15
14
13

36
36
35
38
37
36
36
35

48
56
57
57
58
51
51
54

57
61
59
59
59
61
58
59

72
74
71
74
73
74
72
74

1990
1994
1997
1999
2000
2002
2004
2005
2006

78
79
83
84
82
84
82
81
81

73
73
80
80
79
80
80
78
77

84
86
87
88
87
88
88
87
87

74
78
81
81
81
81
80
79
79

77
76
82
82
80
83
80
79
79

76
76
82
83
81
84
82
80
79

38
38
46
48
47
55
54
52
51

23
22
28
28
28
35
34
33
31

34
34
40
41
43
50
50
47
45

34
36
43
46
44
52
50
47
45

47
45
53
55
53
59
58
54
51

58
58
69
70
69
75
74
70
69

Venezuela
(Bol. Rep. of)

d

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a

For 1990 and 1994, the following categories of schooling were considered: complete primary but incomplete secondary education; complete secondary
education; and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992 the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
c National Statistical Office (ONE), Cuba, on the basis of tabulations by the National Occupation Survey, 2006.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Labour market

(Urban)

342

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 19
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid
family workers
Total c

Private sector
Total a

Professional
and
technical

Nonprofessional
nontechnical

22.9

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to 5 persons

Domestic
employment

Argentina

1990

5.4

69.0

…

69.0

6.9

44.8

11.6

5.7

25.5

(Greater

1994

4.8

70.2

…

70.2

17.1

34.9

13.4

4.8

25.0

19.7

Buenos Aires) 1997

5.3

73.2

…

73.2

17.8

35.8

14.5

5.1

21.5

16.7

Labour market

1999

73.2

11.6

61.6

10.7

32.1

13.6

5.2

21.8

17.3

4.7

73.4

11.8

61.6

10.5

31.3

14.6

5.2

22.0

17.0

2002

4.2

73.5

17.6

55.9

12.4

22.9

15.0

5.6

22.3

17.5

2004

3.8

74.7

15.6

59.1

9.5

29.5

14.0

6.1

21.5

16.4

2005

3.8

75.5

13.2

62.3

11.6

30.5

13.1

7.1

20.8

15.8

2006
(Urban)

4.6

2000

3.8

76.7

12.4

64.3

10.9

32.5

13.4

7.5

19.5

15.4

72.7

15.6

57.1

9.1

28.5

13.7

5.8

23.0

18.6

72.0

15.9

56.1

8.9

27.3

14.1

5.8

23.4

19.0

4.0

73.1

21.7

51.4

10.3

21.1

14.0

6.0

23.0

18.4

2004

4.1

74.2

19.3

54.9

8.6

25.8

14.0

6.5

21.8

17.2

2005

4.1

74.7

16.8

57.9

10.0

27.5

13.2

7.2

21.1

16.7

2006

4.1

75.7

16.2

59.5

9.4

29.3

13.4

7.4

20.1

16.2

1989

2.2

53.9

17.9

36.0

4.3

16.3

9.6

5.8

43.8

41.0

1994

7.6

54.1

12.8

41.3

6.8

15.5

13.8

5.2

38.4

36.8

1997

7.0

46.1

10.5

35.6

6.7

14.3

11.0

3.6

46.8

44.9

1999

4.2

47.6

10.3

37.3

7.3

15.1

11.8

3.1

48.2

45.9

2000

3.0

48.2

10.7

37.5

5.9

17.2

10.2

4.2

48.8

46.4

2002

4.3

47.6

10.4

37.2

4.6

15.5

13.2

3.9

48.1

45.7

2004
Brazil d

4.4
4.6

2002

Bolivia

1999
2000

4.9

49.2

8.7

40.5

4.7

14.5

16.7

4.6

45.8

44.1

34.2

1990

5.2

72.0

…

72.0

14.3

1993

4.1

67.2

14.4

52.8

4.6

17.3

6.2

22.8

21.5

31.5 e

8.5

8.2

27.8

26.4

1996

4.2

68.5

13.7

54.8

1999

4.7

66.6

13.0

53.6

4.8

31.7 e

9.9

8.4

27.3

25.7

11.0

25.7

8.4

8.5

28.6

2001

4.6

68.8

12.7

56.1

11.6

26.5

26.8

8.9

8.8

26.6

24.4
23.6

2003

68.6

12.6

56.0

6.7

31.0

9.8

8.5

26.7

4.6

69.9

12.5

57.4

6.7

32.6

9.6

8.5

25.5

22.5

2005

4.7

69.6

12.4

57.2

6.9

32.4

9.4

8.5

25.7

22.6

2006
Chile f

4.7

2004

5.0

70.3

12.5

57.8

7.1

33.0

9.3

8.4

24.8

21.6

1990

2.5

75.0

…

75.0

12.9

45.7

9.4

7.0

22.5

20.6

1994

3.3

75.0

…

75.0

15.4

44.9

8.6

6.1

21.8

17.4

1996

3.9

76.4

10.9

65.5

11.6

38.7

9.1

6.1

19.7

16.1

1998

4.2

76.0

…

76.0

17.0

43.4

9.7

5.9

19.8

15.2

2000

4.4

75.7

13.1

62.6

11.2

37.5

7.7

6.2

19.9

14.8

2003
2006

4.1
3.2

75.5
76.5

11.4
10.5

64.1
66.0

12.2
11.3

38.3
42.4

7.1
6.5

6.5
5.8

20.4
20.4

14.9
15.9

Social Panorama of Latin America • 2007

343

Table 19 (continued)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Year

Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid
family workers
Total c

Private sector
Total a

Professional
and
technical

Nonprofessional
nontechnical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to 5 persons

Domestic
employment

Colombia g

1991
1994
1997
1999
2002
2004
2005

4.2
4.8
4.4
4.3
5.1
5.5
5.3

66.2
68.2
62.2
57.4
53.6
52.4
54.2

11.6
8.6
9.9
8.7
7.6
7.6
7.5

54.6
59.6
52.3
48.7
46.0
44.8
46.7

4.9
6.0
6.4
5.7
4.3
4.4
4.4

44.1
48.3
41.4
37.8
35.8
35.2
37.2

…
…
…
…
…
…
…

5.6
5.3
4.5
5.2
5.9
5.2
5.1

29.6
27.1
33.4
38.3
41.4
42.2
40.4

27.3
25.0
30.7
35.7
38.5
39.4
37.5

Costa Rica

1990
1994
1997
1999
2000
2002
2004
2005
2006

5.5
6.6
7.7
8.0
5.7
8.1
8.3
7.3
7.5

74.8
75.3
72.4
72.7
74.6
71.3
70.5
73.6
72.6

25.0
21.8
20.5
17.2
18.7
17.3
17.0
17.2
17.2

49.7
53.5
51.9
55.5
55.9
54.0
53.5
56.4
55.4

6.1
7.5
7.3
8.9
8.4
11.9
11.6
11.9
12.2

29.5
31.0
29.9
29.7
31.2
27.2
28.6
28.2
27.9

9.7
11.2
11.2
11.8
11.8
10.9
9.9
11.4
10.3

4.4
3.8
3.5
5.1
4.5
4.0
3.4
4.9
5.0

19.7
18.2
19.8
19.2
19.8
20.6
21.2
19.1
19.9

17.6
16.5
17.7
17.2
17.5
17.8
18.1
16.1
17.0

Ecuador

1990
1994
1997
1999
2000
2002
2004
2005
2006

5.0
7.9
7.8
8.8
4.6
6.9
6.5
6.4
6.5

58.9
58.0
59.1
59.0
59.4
58.3
57.7
60.1
59.5

17.5
13.7
13.8
10.7
11.0
11.5
10.6
10.0
9.7

41.4
44.3
45.3
48.3
48.4
46.8
47.1
50.1
49.8

4.5
5.6
6.3
7.0
6.0
6.4
7.4
7.6
7.0

21.1
21.8
23.0
22.5
23.9
22.6
21.5
22.2
23.0

11.3
12.2
11.0
13.4
13.8
13.3
14.0
15.1
15.7

4.5
4.7
5.0
5.4
5.4
4.5
4.2
5.2
4.1

36.1
34.1
33.1
32.1
35.9
34.8
35.8
33.6
34.0

34.5
32.1
31.1
31.5
33.8
32.9
34.2
31.6
32.2

El Salvador h

1990
1995
1997
1999
2001
2002
2004

3.4
6.2
5.7
4.6
5.0
5.0
4.9

62.9
61.8
61.7
65.2
62.1
60.8
61.2

13.8
12.5
13.3
12.3
11.3
11.2
10.6

49.1
49.3
48.4
52.9
50.8
49.6
50.6

3.4
7.2
7.8
9.1
7.5
8.9
7.7

26.3
27.2
25.0
25.7
25.7
24.5
25.8

13.3
10.5
11.2
13.8
13.4
12.5
13.2

6.1
4.4
4.4
4.3
4.2
3.7
3.9

33.7
32.1
32.6
30.3
32.8
34.1
33.8

33.3
31.1
31.5
29.2
31.6
33.0
32.5

Guatemala

1989
1998
2002

2.8
4.7
6.8

64.2
59.0
57.1

14.4
8.2
6.9

49.8
50.8
50.2

6.2
7.3
8.4

22.8
19.5
24.7

13.8
20.1
13.1

7.0
3.9
4.0

33.0
36.3
36.1

30.9
34.5
34.5

Honduras

1990
1994
1997
1999
2002
2003
2006

1.5
4.2
6.3
6.2
4.3
5.1
3.9

65.5
65.0
60.4
60.2
58.7
56.9
59.2

14.4
11.3
10.1
9.7
9.7
9.6
10.6

51.1
53.7
50.3
50.5
49.0
47.3
48.6

4.9
6.8
6.5
7.5
7.2
5.9
10.9

26.3
30.5
27.7
27.0
24.9
23.9
24.1

13.2
11.0
11.0
11.2
12.9
13.4
9.9

6.7
5.4
5.1
4.8
4.0
4.1
3.7

33.0
30.8
33.4
33.6
36.8
38.0
37.0

31.7
29.5
32.3
33.1
34.9
36.8
25.2

Labour market

Country

344

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 19 (continued)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Employers

Wage or salary earners

Total

Mexico i

Public
sector

Own-account
and unpaid
family workers
Total c

Private sector
Total a

Professional
and
technical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to 5 persons

Domestic
employment

Nonprofessional
nontechnical

3.3

76.4

…

76.4

9.0

64.7

…

2.7

20.3

18.9

3.7

74.5

16.1

58.4

6.6

48.1

…

3.7

21.7

20.4

1996

4.5

73.5

15.1

58.4

7.1

33.1

14.6

3.6

22.1

20.5

1998

4.8

72.9

14.2

58.7

6.6

33.1

14.9

4.1

22.4

20.5

2000

Labour market

1989
1994

4.5

74.2

13.6

60.6

8.1

34.6

14.9

3.0

21.3

19.6

2002

4.3

73.1

13.2

59.9

6.3

32.0

17.0

4.6

22.7

20.9

2004

75.7

…

75.7

13.6

39.7

17.5

4.9

21.1

19.0

3.6

75.4

…

75.4

13.7

41.7

15.5

4.5

21.0

18.8

2006
Nicaragua

3.2

2005

3.9

73.5

…

73.5

13.9

38.8

16.9

3.9

22.6

20.2

0.7

60.8

20.3

40.5

6.6

16.0

11.7

6.2

38.5

29.3

3.8

59.8

…

59.8

13.5

25.4

14.5

6.4

36.5

35.1

2001
Panama

1993
1998

4.7

58.5

11.9

46.6

4.1

22.3

15.8

4.4

36.9

35.3

1991

3.0

78.6

30.1

48.5

9.0

27.0

5.1

7.4

18.4

17.2

1994

2.8

79.6

27.6

52.0

8.3

30.8

5.4

7.5

17.6

16.8
18.4

1997

3.3

77.1

24.5

52.6

11.4

29.2

5.5

6.5

19.7

1999

3.2

76.7

21.1

55.6

12.1

31.2

6.2

6.1

20.2

18.9

2002

3.4

74.3

20.4

53.9

6.7

32.4

8.1

6.7

22.1

20.6
20.9

2004

3.4

73.7

19.6

54.1

6.1

32.9

8.2

6.9

22.9

2005

3.6

73.2

18.3

54.9

6.8

32.6

8.7

6.8

23.2

21.5

2006

3.7

73.6

17.8

55.8

8.6

32.3

8.0

6.9

22.7

21.1

Paraguay

1990

8.9

68.4

11.9

56.5

5.5

24.9

15.6

10.5

22.7

21.2

(Asunción)

1994

9.4

67.0

11.6

55.4

6.3

24.3

13.3

11.5

23.6

23.1

1996

7.0

62.3

11.3

51.0

5.0

22.9

13.8

9.3

30.7

28.6

1999

6.4

67.7

12.7

55.0

6.9

25.4

13.6

9.1

25.8

23.2

2001

7.3

65.8

11.5

54.3

7.8

23.9

11.3

11.3

35.4

24.4

2004

5.3

61.3

11.4

49.9

6.1

18.9

13.7

11.2

33.4

31.2

2005

6.9

63.9

13.4

50.5

5.9

20.6

13.3

10.7

29.3

25.9

(Urban)

9.2

62.0

10.5

51.5

4.5

21.5

15.0

10.5

28.9

28.6

6.8

57.9

10.0

47.9

3.8

20.4

14.4

9.3

35.3

33.7

1999

6.6

62.1

11.8

50.3

5.1

21.1

14.9

9.2

31.2

29.1

2001

7.6

59.9

11.1

48.8

5.5

19.6

13.3

10.4

32.5

30.1

2004

5.3

57.9

11.0

46.9

4.8

16.6

15.0

10.5

36.7

34.6

2005
Peru

1994
1996

6.0

61.9

12.7

49.2

4.9

18.0

15.2

11.1

32.0

29.4

1997

5.8

53.7

11.3

42.4

7.4

18.7

11.9

4.4

40.5

38.2

1999

5.6

52.9

11.0

41.9

7.0

16.1

13.0

5.8

41.5

38.1

2001
2003

4.8
4.6

53.0
51.1

12.0
10.7

41.0
40.4

6.5
6.6

15.9
15.8

13.4
12.4

5.2
5.6

42.1
44.4

39.6
42.0

Social Panorama of Latin America • 2007

345

Table 19 (concluded)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Year

Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid
family workers
Total c

Private sector
Total a

Professional
and
technical

Nonprofessional
nontechnical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to 5 persons

Domestic
employment

Dominican
Republic

1992
1995
1997
2000
2002
2003
2004
2005
2006

2.8
4.2
3.7
2.9
3.9
3.9
5.5
4.9
4.5

61.9
62.8
62.5
64.2
61.3
60.8
61.5
58.9
58.8

14.3
13.1
11.9
13.8
13.8
13.7
11.9
13.1
13.2

47.6
49.7
50.6
50.4
47.5
47.1
49.6
45.8
45.6

8.7
9.0
6.7
7.5
8.0
8.3
8.0
7.7
7.5

35.7
36.9
31.1
31.0
28.8
28.1
29.2
26.9
26.0

…
…
8.4
7.8
6.4
6.6
7.1
6.4
7.2

3.2
3.8
4.4
4.1
4.3
4.1
5.3
4.8
4.9

35.3
33.2
33.9
32.9
34.8
35.2
32.9
36.3
36.7

32.8
30.6
31.4
30.7
32.7
32.7
30.6
34.1
34.2

Uruguay

1990
1994
1997
1999
2000
2002
2004
2005

4.6
4.8
4.3
4.0
3.7
3.7
3.5
3.9

74.2
72.3
72.2
72.4
73.3
70.5
70.6
71.7

21.8
18.7
17.7
16.2
17.2
17.3
17.0
16.3

52.4
53.6
54.5
56.2
56.1
53.2
53.6
55.4

5.1
5.4
5.9
6.5
6.3
5.9
6.2
6.2

30.1
31.8
30.5
31.8
29.6
26.4
26.6
28.3

10.3
9.4
11.0
10.4
11.1
11.0
11.4
13.7

6.9
7.0
7.1
7.5
9.1
9.9
9.4
7.2

21.3
22.9
23.6
23.6
23.2
25.8
25.9
24.4

19.0
20.1
20.8
20.6
19.4
21.8
21.8
20.3

Venezuela
1990
(Bol. Rep. of) j 1994
1997
1999
2000
2002
2004
2005
2006

7.5
6.1
5.0
5.1
5.0
5.4
4.7
4.8
4.5

70.0
64.5
62.8
57.9
56.3
54.6
55.4
57.4
58.3

21.4
18.1
16.8
14.9
14.6
13.8
15.4
15.8
16.6

48.6
46.4
46.0
43.0
41.7
40.8
40.0
41.6
41.7

5.8
6.1
5.5
4.9
4.6
3.9
4.7
6.1
5.3

30.0
27.1
25.4
24.0
23.8
23.2
22.5
23.4
24.2

6.5
9.2
10.8
12.1
11.2
11.1
10.3
10.2
10.1

6.3
4.0
4.3
2.0
2.1
2.6
2.5
1.9
2.1

22.5
29.3
32.3
36.9
38.6
39.9
39.8
37.7
37.3

21.4
27.4
30.3
35.3
37.1
38.2
38.0
35.3
35.3

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a
b

c
d

e
f
g

h
i
j

For Argentina (except 1999 and 2000), Brazil (except 1993, 1996 and 1999), Chile (except 1996 and 2000), Mexico (1998 and 2004) and Nicaragua
(1998), this includes public-sector wage or salary earners.
For Colombia, Dominican Republic (1992, 1995 and 1998) and Mexico (1989 and 1994), no information was available on the size of business
establishments. In those cases, wage earners in non-professional, non-technical occupations in establishments employing up to 5 persons were
included in the figures for establishments employing more than 5 persons. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996),
Dominican Republic, El Salvador, Panamá (up to 2002) and Uruguay (1990), establishments employing up to 4 persons are taken into account.
Includes professional and technical workers.
Brazil’s National Household Survey (PNAD) does not provide information on the size of business establishments, except in 1993, 1996 and 1999.
Therefore, the figure given for Brazil in the column for establishments employing more than five persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to 5 persons includes workers who do not have such contracts.
Includes private-sector employees engaged in non-professional, non-technical occupations in business establishments of undeclared size.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
The figures for 1990 are not strictly comparable with those for 1997 owing to changes made in the classification of professional and technical workers.
Information from national household income and expenditure surveys (ENIGH).
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Labour market

Country

346

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 19.1
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE MALE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid family
workers
Total c

Private sector
Total a

Professional
and
technical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to
5 persons

Domestic
employment

Nonprofessional
non-technical

Argentina

1990

6.9

68.3

…

68.3

6.3

47.8

12.4

1.8

24.7

23.1

(Greater

1994

6.2

69.0

…

69.0

14.6

39.5

14.5

0.4

24.7

20.8
16.2

1997

6.4

72.5

…

72.5

14.3

40.3

17.5

0.4

21.1

1999

6.0

71.3

8.7

62.6

9.4

37.1

15.9

0.2

22.5

18.1

2000

Labour market

Buenos
Aires)

5.8

71.1

8.7

62.4

10.4

35.5

16.4

0.1

23.1

18.6

2002

5.4

67.7

11.6

56.1

11.9

26.6

17.5

0.1

26.9

21.9

2004

5.0

71.9

11.5

60.4

8.7

34.9

16.7

0.1

23.2

18.4

2005

(Urban)

4.9

72.9

9.8

63.1

10.9

35.0

16.3

0.9

22.3

17.8

2006

4.9

73.6

9.0

64.6

10.3

38.8

15.4

0.1

21.4

17.9

1999

5.8

70.1

12.3

57.8

8.2

33.6

15.8

0.2

24.1

19.7

2000

5.8

69.1

12.5

56.6

8.6

31.7

16.1

0.2

25.1

20.6
23.2

2002

67.0

15.5

51.5

9.8

25.0

16.6

0.1

28.0

5.4

70.8

14.3

56.5

8.1

31.0

17.2

0.2

23.7

19.3

2005

5.4

71.5

12.8

58.7

9.5

32.1

16.4

0.7

23.2

19.0

2006
Bolivia

5.2

2004

5.3

72.5

12.3

60.2

8.9

35.3

15.9

0.1

22.2

18.6

1989

3.2

60.4

20.0

40.4

4.8

22.1

12.9

0.6

36.4

32.8

1994

10.7

62.0

13.9

48.1

7.8

21.5

18.3

0.5

27.4

25.4
35.5

1997

52.0

10.0

42.0

7.8

19.6

14.1

0.5

37.9

5.8

55.5

10.3

45.2

9.1

20.2

15.6

0.3

38.7

35.5

2000

4.1

54.2

11.2

43.0

6.7

21.8

14.3

0.2

41.7

38.7

2002

6.1

54.8

10.2

44.6

5.5

21.8

17.1

0.2

39.1

36.3

2004
Brazil d

10.1

1999

7.0

57.3

8.1

49.2

5.6

20.0

23.4

0.2

35.6

33.5

6.9

71.0

…

71.0

10.4

39.1

21.1

0.4

22.1

20.9

5.6

66.5

11.8

54.7

4.5

39.3 e

10.1

0.8

27.9

26.7

1996

5.4

65.8

10.9

54.9

4.4

38.3 e

11.4

0.8

28.7

27.2

1999

6.2

63.4

10.2

53.2

9.1

32.8

10.5

0.8

30.4

28.5

2001

5.9

65.8

9.9

55.9

9.6

34.4

11.1

0.8

28.3

26.4

2003

6.0

65.8

9.9

55.9

6.4

37.5

11.2

0.8

28.3

25.0

2004

5.8

67.0

9.9

57.1

6.6

38.8

10.9

0.8

27.2

24.0

2005

5.9

67.1

9.6

57.5

6.9

39.1

10.7

0.8

27.0

23.8

2006
Chile f

1990
1993

5.9

67.6

9.9

57.7

7.0

39.3

10.6

0.8

26.1

22.7

1990

3.1

73.0

…

73.0

9.9

52.9

10.0

0.2

23.9

22.0

1994

3.9

73.7

…

73.7

13.4

51.1

9.1

0.1

22.5

18.3

1996

4.5

75.0

9.6

65.4

11.4

44.1

9.7

0.2

20.5

17.0

1998

5.0

74.2

…

74.2

14.9

49.5

9.7

0.1

20.7

16.4

2000

5.5

74.1

11.8

62.3

11.0

43.3

7.9

0.1

20.5

15.8

2003

4.8

72.6

8.3

64.3

11.8

44.7

7.6

0.2

22.6

17.8

2006

3.7

75.9

9.2

66.7

10.5

49.4

6.7

0.1

20.3

16.2

Social Panorama of Latin America • 2007

347

Table 19.1 (continued)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE MALE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Year

Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid family
workers
Total c

Private sector
Total a

Professional
and
technical

Nonprofessional
non-technical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to
5 persons

Domestic
employment

Colombia g

1991
1994
1997
1999
2002
2004
2005

5.6
6.3
5.6
5.4
6.9
7.2
7.0

63.1
65.3
58.8
54.4
50.6
49.6
51.6

10.8
8.0
8.7
7.9
6.5
6.6
6.7

52.3
57.3
50.1
46.5
44.1
43.0
44.9

4.4
5.2
5.9
5.1
3.8
4.0
4.0

47.6
51.9
44.0
40.9
39.9
38.6
40.6

…
…
…
…
…
…
…

0.3
0.2
0.2
0.5
0.4
0.4
0.3

31.3
28.4
35.6
40.2
42.4
43.2
41.3

28.5
26.1
32.5
37.4
39.3
40.2
38.1

Costa Rica

1990
1994
1997
1999
2000
2002
2004
2005
2006

7.2
8.1
9.9
10.2
7.1
10.3
10.7
9.2
9.4

72.1
73.2
70.7
71.2
71.8
70.4
69.5
72.4
70.7

23.0
20.1
16.5
14.6
15.7
13.6
13.2
13.8
13.9

49.1
53.1
54.2
56.6
56.1
56.8
56.3
58.6
56.8

7.0
7.7
7.7
9.6
8.7
13.6
12.4
12.7
12.6

31.6
33.5
33.9
33.3
34.7
31.5
33.1
32.9
32.5

10.3
11.6
12.4
13.3
12.4
11.4
10.5
12.6
11.2

0.2
0.3
0.2
0.4
0.3
0.3
0.3
0.4
0.5

20.6
18.7
19.4
18.5
21.0
19.4
19.8
18.3
19.7

18.1
16.7
17.1
16.7
18.5
16.1
16.6
15.0
16.3

Ecuador

1990
1994
1997
1999
2000
2002
2004
2005
2006

6.3
9.7
9.8
10.2
5.9
8.4
8.3
7.7
7.8

60.3
59.6
59.6
60.7
60.5
60.5
61.1
62.2
62.9

17.4
13.0
12.8
10.4
9.8
10.6
9.9
9.3
8.9

42.9
46.6
46.8
50.3
50.7
49.9
51.2
52.9
54.0

4.0
5.3
5.7
5.8
5.4
5.6
6.3
6.5
5.9

24.5
26.0
27.3
27.3
27.8
27.6
26.7
26.9
28.0

13.8
15.0
13.1
16.6
16.8
16.0
17.7
18.6
19.7

0.6
0.3
0.7
0.6
0.7
0.7
0.5
0.9
0.4

33.5
30.7
30.6
28.2
33.5
31.2
30.7
30.1
29.2

31.7
28.5
28.3
27.7
31.1
28.9
28.9
27.8
27.3

El Salvador h

1990
1995
1997
1999
2000
2001
2002
2004

4.8
8.6
7.6
6.2
8.0
6.4
7.0
6.5

71.4
68.7
68.1
72.4
68.4
69.5
67.5
68.6

15.5
13.0
14.1
12.9
12.9
11.2
11.3
10.9

55.9
55.7
54.0
59.5
55.5
58.3
56.2
57.7

4.2
8.3
8.8
10.3
10.0
8.7
10.2
8.6

33.1
32.6
30.3
30.0
28.3
30.7
28.6
31.0

18.2
14.3
14.6
18.6
16.8
18.4
16.9
17.6

0.4
0.5
0.3
0.6
0.4
0.5
0.5
0.5

23.8
22.7
24.4
21.5
23.6
24.0
25.5
24.9

23.2
21.3
22.9
20.0
22.0
22.1
23.9
23.1

Guatemala

1989
1998
2002

3.6
6.2
9.4

66.1
64.4
61.1

15.0
8.4
7.0

51.1
56.0
54.1

6.2
7.5
8.1

27.3
23.8
29.6

17.4
24.4
16.3

0.2
0.3
0.1

30.3
29.5
29.5

28.6
27.2
27.6

Honduras

1990
1994
1997
1999
2002
2003
2006

1.9
5.7
8.8
8.4
5.4
6.7
4.9

69.8
65.9
62.5
63.3
60.1
59.0
60.7

13.6
10.3
8.3
8.0
7.7
7.6
8.2

56.2
55.6
54.2
55.3
52.4
51.4
52.5

5.4
6.9
6.1
6.6
7.2
6.0
11.2

33.0
34.5
31.5
31.9
27.6
26.9
27.4

17.4
14.2
15.8
16.2
17.2
18.0
13.3

0.4
0.0
0.8
0.6
0.4
0.5
0.6

28.3
28.4
28.9
28.4
34.6
34.4
34.4

26.8
26.9
27.8
28.0
32.6
33.1
25.2

Labour market

Country

348

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 19.1 (continued)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE MALE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Employers

Wage or salary earners

Total

Mexico i

Public
sector

Own-account
and unpaid family
workers
Total c

Private sector
Total a

Professional
and
technical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to
5 persons

Domestic
employment

Nonprofessional
non-technical

1989

4.3

76.4

…

76.4

9.3

66.5

…

0.6

19.2

17.4

1994

4.9

75.5

13.9

61.6

6.9

54.1

…

0.6

19.6

18.0

1996

5.8

75.2

13.7

61.5

7.2

36.1

17.3

0.9

19.0

17.4

1998

6.3

75.0

12.9

62.1

6.8

36.7

17.4

1.2

18.9

16.6

Labour market

2000

76.9

11.3

65.6

8.9

37.4

18.4

0.9

17.3

15.3

5.8

74.2

11.9

62.3

6.2

35.3

19.4

1.4

20.0

18.2

2004

4.3

77.6

…

77.6

11.5

44.3

20.8

1.0

18.1

15.8

2005

4.5

77.1

…

77.1

12.1

46.4

17.9

0.7

18.5

15.9

2006
Nicaragua

6.0

2002

5.1

76.0

…

76.0

12.7

43.0

19.7

0.6

18.9

16.3

0.9

64.3

18.8

45.5

6.6

22.4

16.2

0.3

34.9

27.5

5.6

63.1

…

63.1

11.7

31.5

18.7

1.2

31.3

30.0

2001
Panama

1993
1998

6.3

63.6

9.8

53.8

4.0

28.2

21.5

0.1

30.1

28.6
22.0

1991

4.0

72.5

26.9

45.6

10.2

28.9

5.7

0.8

23.5

1994

3.7

74.1

24.7

49.4

8.9

33.4

6.1

1.0

22.2

21.2

1997

4.6

72.3

21.9

50.4

12.2

31.4

5.8

1.0

23.2

21.4

1999

4.2

73.2

19.0

54.2

13.1

33.4

6.8

0.9

22.5

20.9

2002

4.6

70.0

17.7

52.3

6.2

35.5

9.6

1.0

25.4

23.6

2004

4.7

69.2

16.7

52.5

5.1

37.1

9.2

1.1

26.1

23.7

2005

4.9

69.3

15.1

54.2

6.0

37.1

9.9

1.2

25.7

23.4

2006

4.9

70.2

14.8

55.4

6.1

38.6

9.9

0.8

24.8

23.0

Paraguay

1990

13.5

69.2

12.3

56.9

4.9

31.4

20.6

0.0

17.4

16.4

(Asunción)

1994

12.3

68.1

11.7

56.4

6.5

30.2

18.1

1.6

19.5

19.1
24.6

1996

9.3

64.3

10.3

54.0

5.1

29.5

18.4

1.0

26.3

1999

8.5

69.4

13.4

56.0

7.4

33.3

14.5

0.8

22.1

19.5

2001

9.5

66.4

10.5

55.9

7.7

32.2

13.7

2.3

24.0

20.3

2004

61.9

10.9

51.0

5.8

25.0

17.7

2.5

30.6

28.3

9.7

64.9

13.3

51.6

5.4

26.0

18.7

1.5

25.4

21.4

1994

11.9

63.4

10.2

53.2

4.6

27.0

20.2

1.4

24.7

24.5

1996

(Urban)

7.3

2005

9.1

60.3

9.0

51.3

4.0

27.1

19.3

0.9

30.6

29.2

1999

64.0

11.9

52.1

5.3

28.0

17.9

0.9

27.0

25.1

10.3

60.7

9.9

50.8

5.4

25.8

18.0

1.6

29.1

26.1

2004

7.2

59.0

10.0

49.0

4.5

22.6

20.0

1.9

33.7

31.5

2005
Peru

9.0

2001

8.3

62.5

11.6

50.9

4.8

23.0

21.6

1.5

29.3

26.3

1997

8.5

58.8

11.6

47.2

7.3

23.8

15.9

0.2

32.6

29.5

1999

8.0

55.8

11.4

44.4

7.6

20.3

16.1

0.4

36.1

32.0

2001

6.7

58.0

12.6

45.4

7.0

20.4

17.5

0.5

35.4

32.2

2003

6.3

55.1

11.6

43.5

6.2

20.6

15.9

0.8

38.7

35.8

Social Panorama of Latin America • 2007

349

Table 19.1 (concluded)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE MALE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Year

Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid family
workers
Total c

Private sector
Total a

Professional
and
technical

Nonprofessional
non-technical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to
5 persons

Domestic
employment

Dominican
Republic

1992
1995
1997
2000
2002
2003
2004
2005
2006

3.9
5.3
4.9
3.5
4.8
5.1
6.6
5.9
5.4

57.1
56.7
58.1
58.6
55.2
53.8
54.9
53.0
52.1

13.8
11.0
11.4
11.4
12.5
11.1
9.9
10.7
10.7

43.3
45.7
46.7
47.2
42.7
42.7
45.0
42.3
41.4

6.9
8.0
5.6
6.3
6.7
6.7
6.2
6.4
6.2

36.2
37.5
31.3
32.6
29.1
29.5
30.6
28.2
27.6

…
…
9.4
7.7
6.1
6.1
7.1
6.8
6.9

0.2
0.2
0.4
0.6
0.8
0.4
1.1
0.9
0.7

39.0
37.9
37.0
38.0
39.9
41.1
38.5
41.1
42.6

36.1
35.2
34.5
35.6
37.8
38.3
36.0
38.9
40.0

Uruguay

1990
1994
1997
1999
2000
2002
2004
2005

6.4
6.3
5.8
5.2
4.9
4.9
4.6
5.3

73.0
70.8
69.2
69.1
69.7
65.6
66.7
67.4

22.8
18.6
17.3
15.6
16.5
16.8
16.3
15.0

50.2
52.2
51.9
53.5
53.2
48.8
50.4
52.4

4.4
4.8
4.9
5.4
5.3
4.9
5.5
5.6

33.9
36.7
34.8
36.2
35.2
30.3
31.2
32.4

11.8
10.6
12.0
11.7
11.4
12.2
12.3
13.3

0.1
0.1
0.2
0.2
1.3
1.4
1.4
1.1

20.5
23.0
24.9
25.6
25.2
29.5
28.6
27.3

18.9
20.7
22.6
23.2
21.9
25.7
24.6
23.0

Venezuela
1990
(Bol. Rep. of) j 1994
1997
1999
2000
2002
2004
2005
2006

10.2
8.4
6.7
6.9
6.8
7.3
6.3
6.4
6.0

66.1
60.6
61.2
57.5
55.6
54.4
54.2
56.9
57.0

16.8
13.0
12.1
10.6
10.4
9.9
10.9
11.1
11.5

49.3
47.6
49.1
46.9
45.2
44.5
43.3
45.8
45.5

5.5
5.2
5.0
4.0
3.7
3.2
4.0
5.4
4.5

33.9
30.0
29.2
27.9
27.7
27.4
26.4
27.5
28.5

8.0
10.9
13.4
14.9
13.7
13.8
12.8
12.8
12.4

1.9
1.5
1.5
0.1
0.1
0.1
0.1
0.1
0.1

23.6
31.1
32.0
35.6
37.6
38.3
39.5
36.8
36.9

22.5
29.2
30.3
34.1
36.3
36.8
37.8
34.5
35.0

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a
b

c
d

e
f
g

h
i
j

For Argentina (except 1999 and 2000), Brazil (except 1993, 1996 and 1999), Chile (except 1996 and 2000), Mexico (1998 and 2004) and Nicaragua
(1998), this includes public-sector wage or salary earners
For Colombia, Dominican Republic (1992, 1995 and 1998) and Mexico (1989 and 1994), no information was available on the size of business
establishments. In those cases, wage earners in non-professional, non-technical occupations in establishments employing up to 5 persons were included
in the figures for establishments employing more than 5 persons. In the case of the Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile
(1996), Dominican Republic, El Salvador, Panama (up to 2002) and Uruguay (1990), establishments employing up to 4 persons are taken into account.
Includes professional and technical workers.
Brazil’s National Household Survey (PNAD) does not provide information on the size of business establishments, except in 1993, 1996 and 1999.
Therefore, the figure given for Brazil in the column for establishments employing more than five persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to 5 persons includes workers who do not have such contracts.
Includes private-sector employees engaged in non-professional, non-technical occupations in business establishments of undeclared size.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
The figures for 1990 are not strictly comparable with those for 1997 owing to changes made in the classification of professional and technical workers.
Information from national household income and expenditure surveys (ENIGH).
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Labour market

Country

350

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 19.2
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE FEMALE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid family
workers
Total c

Private sector
Total a

Professional
and
technical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to
5 persons

Nonprofessional
non-technical

Domestic
employment

Argentina

1990

2.8

70.3

…

70.3

8.0

39.6

10.2

12.5

27.1

22.7

(Greater

1994

2.4

72.2

…

72.2

21.4

27.0

11.5

12.3

25.4

18.7

Buenos Aires) 1997

3.5

74.2

…

74.2

23.6

28.3

9.6

12.7

22.2

17.5

1999

2.6

76.3

15.9

60.4

12.6

24.8

10.3

12.7

20.7

15.3
15.7

Labour market

2000

3.0

76.8

16.4

60.4

10.7

24.8

12.0

12.9

20.1

2002

2.5

81.3

25.9

55.4

13.0

17.6

11.6

13.2

16.2

11.5

2004

2.2

78.6

21.2

57.4

10.6

22.0

10.3

14.5

19.1

13.6

2005

79.1

17.8

61.3

12.5

24.4

8.7

15.7

18.7

13.0

2.3

80.8

17.0

63.8

11.7

24.1

10.7

17.3

16.8

12.0

1999

2.5

76.2

20.4

55.8

10.4

20.7

10.5

14.2

21.3

16.9

2000

(Urban)

2.3

2006

2.8

76.5

21.1

55.4

9.4

20.7

11.1

14.2

20.7

16.5

2002

81.6

30.3

51.3

11.0

15.9

10.4

14.0

16.1

11.8

2.4

78.6

26.0

52.6

9.3

18.6

9.5

15.2

19.0

14.2

2005

2.4

79.0

22.0

57.0

10.7

21.3

8.9

16.1

18.4

13.6

2006
Bolivia

2.3

2004

2.5

80.3

21.6

58.7

10.1

21.2

10.2

17.2

17.3

13.0

0.8

45.3

15.0

30.3

3.6

8.6

5.2

12.9

54.0

52.2

3.5

43.7

11.4

32.3

5.4

7.8

7.9

11.2

52.9

51.7

1997

2.8

38.5

11.1

27.4

5.4

7.3

7.0

7.7

58.7

57.4

1999

2.2

37.4

10.2

27.2

5.0

8.6

6.9

6.7

60.6

59.3

2000

1.6

40.7

10.0

30.7

4.9

11.5

4.9

9.4

57.8

56.3

2002

2.2

39.0

10.7

28.3

3.6

7.8

8.6

8.3

58.7

56.9

2004
Brazil d

1989
1994

2.3

39.5

9.4

30.1

3.7

7.8

8.6

10.0

58.2

57.0
22.4

2.5

73.6

…

73.6

20.7

26.1

11.2

15.6

24.0

1.8

70.7

18.3

52.4

4.7

21.9 e

6.0

19.8

27.4

25.8

1996

2.5

72.3

17.9

54.4

5.4

21.7 e

7.6

19.7

25.2

23.4

1999

2.7

71.2

16.9

54.3

13.8

15.5

5.3

19.7

26.1

23.6

2001

2.8

73.0

16.5

56.5

14.5

16.1

5.9

20.0

24.3

21.6

2003

2.9

72.6

16.4

56.2

7.1

22.2

7.8

19.1

24.5

21.7

2004

2.9

73.8

16.1

57.7

6.8

24.2

7.8

18.9

23.3

20.5

2005

3.1

73.1

16.1

57.0

7.0

23.6

7.7

18.7

23.9

20.9

2006
Chile f

1990
1993

3.2

73.8

15.9

57.9

7.2

24.8

7.6

18.3

23.1

20.1

1990

1.4

78.6

…

78.6

18.4

32.6

8.2

19.4

20.1

18.2

1994

2.2

77.4

…

77.4

19.1

33.8

7.7

16.8

20.6

15.8

1996

2.8

78.9

13.2

65.7

12.0

29.2

8.2

16.3

18.4

14.5

1998

3.0

78.8

…

78.8

20.6

33.3

9.7

15.2

18.1

13.2

2000

2.5

78.4

15.3

63.1

11.5

28.2

7.4

16.0

19.1

13.3

2003

3.0

80.0

16.2

63.8

12.8

28.3

6.4

16.3

17.0

10.5

2006

2.3

77.2

12.5

64.7

12.4

31.8

6.2

14.3

20.4

15.4

Social Panorama of Latin America • 2007

351

Table 19.2 (continued)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE FEMALE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Year

Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid family
workers
Total c

Private sector
Total a

Professional
and
technical

Nonprofessional
non-technical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to
5 persons

Domestic
employment

Colombia g

1991
1994
1997
1999
2002
2004
2005

2.2
2.7
2.8
2.7
2.9
3.4
3.3

70.7
72.3
66.9
61.7
57.1
55.8
57.4

12.8
9.4
11.6
9.9
8.9
8.8
8.4

57.9
62.9
55.3
51.8
48.2
47.0
49.0

5.5
7.2
6.9
6.6
4.9
4.9
5.0

38.8
43.0
38.0
33.7
30.6
30.9
32.9

…
…
…
…
…
…
…

13.6
12.7
10.4
11.5
12.7
11.2
11.1

27.1
25.2
30.3
35.6
40.0
40.8
39.3

25.5
23.4
28.2
33.4
37.5
38.3
36.8

Costa Rica

1990
1994
1997
1999
2000
2002
2004
2005
2006

2.3
4.0
4.0
4.4
3.2
4.7
4.4
4.3
4.6

79.6
78.6
75.7
75.0
79.1
72.8
72.3
75.3
75.5

28.7
24.7
27.5
21.5
23.6
23.0
23.2
22.4
22.2

50.9
53.9
48.2
53.5
55.5
49.8
49.1
52.9
53.3

4.5
7.1
6.6
7.5
7.8
9.3
10.3
10.7
11.6

25.8
26.4
23.2
24.0
25.4
20.6
21.4
20.8
21.0

8.6
10.3
9.2
9.4
10.9
10.1
9.0
9.4
9.0

12.0
10.1
9.2
12.6
11.4
9.8
8.4
12.0
11.7

18.1
17.3
20.4
20.4
17.5
22.6
23.4
20.5
19.9

16.6
16.1
18.7
18.1
15.7
20.4
20.5
17.9
17.9

Ecuador

1990
1994
1997
1999
2000
2002
2004
2005
2006

2.7
5.0
4.5
5.0
2.5
4.5
3.7
4.4
4.5

56.4
55.5
57.5
56.7
57.7
55.0
52.9
56.8
54.4

17.7
14.8
15.5
11.3
12.8
12.8
11.7
10.9
10.9

38.7
40.7
42.0
45.4
44.9
42.2
41.2
45.9
43.5

5.5
6.2
7.3
8.9
7.0
7.6
9.1
9.3
8.6

14.9
15.0
15.8
15.0
17.8
14.7
13.9
15.1
15.5

6.7
7.7
8.0
8.4
9.0
9.1
8.5
10.0
9.6

11.6
11.8
10.9
13.1
11.1
10.8
9.7
11.5
9.8

40.8
39.5
37.1
38.3
39.8
40.5
43.4
38.8
41.1

39.5
37.8
35.7
37.4
38.1
39.3
42.1
37.3
39.4

El Salvador h

1990
1995
1997
1999
2000
2001
2002
2004

1.6
3.3
3.3
2.7
3.4
3.4
3.0
3.1

52.5
53.4
53.9
57.0
54.5
53.9
53.6
53.3

11.7
11.8
12.2
11.5
12.0
11.5
11.1
10.3

40.8
41.6
41.7
45.5
42.5
42.4
42.5
43.0

2.5
5.9
6.5
7.6
6.6
6.2
7.5
6.8

18.0
20.8
18.7
20.9
20.0
20.0
20.2
20.1

7.2
5.8
7.1
8.4
7.7
7.8
7.8
8.4

13.1
9.1
9.4
8.6
8.2
8.4
7.0
7.7

45.9
43.3
42.8
40.2
42.1
42.7
43.4
43.6

45.8
42.8
42.0
39.6
41.5
42.3
42.8
43.0

Guatemala

1989
1998
2002

1.5
2.7
3.3

61.2
52.0
51.5

13.4
7.8
6.8

47.8
44.2
44.7

6.1
7.1
8.6

15.7
14.1
18.1

7.9
14.6
8.8

18.1
8.4
9.2

37.3
45.2
45.1

34.6
43.9
43.9

Honduras

1990
1994
1997
1999
2002
2003
2006

0.9
1.8
3.1
3.6
2.9
3.0
2.7

59.0
63.6
57.4
56.6
57.2
54.2
56.9

15.5
12.9
12.4
11.8
12.4
12.1
13.5

43.5
50.7
45.0
44.8
44.8
42.1
43.4

4.1
6.7
7.0
8.6
7.2
5.8
10.5

16.5
24.3
22.6
21.2
21.4
20.1
19.8

6.9
6.0
4.7
5.1
7.3
7.5
5.4

16.0
13.7
10.7
9.9
8.9
8.7
7.7

40.0
34.6
39.4
39.8
39.9
42.8
40.3

39.0
33.6
38.3
39.2
38.0
41.6
25.2

Labour market

Country

352

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 19.2 (continued)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE FEMALE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Employers

Wage or salary earners

Total

Mexico i

Public
sector

Own-account
and unpaid family
workers
Total c

Private sector
Total a

Professional
and
technical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to
5 persons

Nonprofessional
non-technical

Domestic
employment

1989

1.3

76.3

…

76.3

8.4

60.8

…

7.1

22.4

21.9

1994

1.5

72.8

20.3

52.5

6.1

36.8

…

9.6

25.8

25.0
25.9

70.4

17.5

52.9

7.0

27.7

9.9

8.3

27.5

69.5

16.5

53.0

6.5

26.8

10.7

9.0

28.4

27.1

1.9

70.2

17.5

52.7

6.6

30.0

9.6

6.5

27.9

26.8

2002

1.9

71.1

15.2

55.9

6.4

26.7

13.1

9.7

27.0

25.3

2004

1.6

73.0

…

73.0

16.7

32.9

12.8

10.6

25.5

23.7

2005

2.1

72.8

…

72.8

16.0

34.7

12.0

10.1

25.1

23.3

2006
Nicaragua

2.1
2.2

2000

Labour market

1996
1998

2.1

70.2

…

70.2

15.6

33.1

12.9

8.6

27.8

25.6
31.7

0.5

56.2

22.4

33.8

6.6

7.5

5.6

14.1

43.4

1.3

55.4

…

55.4

15.8

17.2

8.9

13.5

43.3

41.9

2001
Panama

1993
1998

2.5

51.2

14.7

36.5

4.2

14.0

8.0

10.3

46.2

44.5

1991

1.6

87.2

34.6

52.6

7.4

24.4

4.4

16.4

11.3

10.6

1994

1.5

88.1

32.0

56.1

7.3

26.9

4.2

17.7

10.4

10.0

1997

1.4

83.9

28.2

55.7

10.2

25.9

5.1

14.5

14.8

14.2

1999

1.6

81.8

24.2

57.6

10.7

28.0

5.2

13.7

16.6

15.9

2002

1.8

81.2

24.6

56.6

7.6

27.8

5.9

15.3

17.1

16.1

2004

1.4

80.5

23.8

56.7

7.7

26.7

6.6

15.7

18.1

16.7

2005

1.8

78.8

22.9

55.9

7.9

26.2

6.9

14.9

19.6

18.8

2006

1.8

78.4

22.2

56.2

12.2

23.0

5.0

16.0

19.6

18.3

Paraguay

1990

2.4

67.5

11.3

56.2

6.5

15.5

8.6

25.6

30.2

28.1

(Asunción)

1994

5.7

65.5

11.5

54.0

6.1

16.6

7.0

24.3

28.8

28.2

1996

4.0

59.5

12.5

47.0

4.9

14.3

7.8

20.0

36.5

33.9

1999

3.7

65.4

11.7

53.7

6.3

14.9

12.4

20.1

30.8

28.2

2001

64.3

12.7

51.6

7.8

14.3

8.4

21.1

30.9

29.0

2.7

60.2

12.0

48.2

6.5

11.0

8.6

22.1

37.1

34.9

2005
(Urban)

4.8

2004

3.7

62.5

13.5

49.0

6.4

14.3

6.9

21.4

33.8

31.2

1994

5.3

59.7

10.9

48.8

4.3

13.7

7.5

23.3

34.9

34.5

1996

3.5

54.7

11.4

43.3

3.5

11.3

7.7

20.8

41.8

39.9

1999

59.7

11.6

48.1

5.0

11.6

10.8

20.7

36.9

34.6

4.2

59.0

12.6

46.4

5.6

11.8

7.5

21.5

36.8

35.2

2004

2.9

56.5

12.2

44.3

5.2

8.8

8.5

21.8

40.6

38.6

2005
Peru

3.4

2001

3.3

61.3

14.1

47.2

5.1

11.9

7.2

23.0

35.4

33.3

1997

2.3

47.3

10.9

36.4

7.6

12.1

6.9

9.8

50.5

49.1

1999

2.5

49.3

10.5

38.8

6.3

11.0

9.1

12.4

48.2

45.7

2001

2.4

46.9

11.3

35.6

5.8

10.2

8.3

11.3

50.7

49.0

2003

2.4

46.1

9.4

36.7

7.1

10.0

8.1

11.5

51.5

49.7

Social Panorama of Latin America • 2007

353

Table 19.2 (concluded)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE FEMALE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(Percentages)
Year

Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid family
workers
Total c

Private sector
Total a

Professional
and
technical

Nonprofessional
non-technical

Non-professional, non-technical
Establishments
employing
more than
5 persons b

Establishments
employing
up to
5 persons

Domestic
employment

Dominican
Republic

1992
1995
1997
2000
2002
2003
2004
2005
2006

0.9
2.0
1.5
2.0
2.4
1.8
3.7
3.1
3.1

70.9
73.7
70.1
73.3
71.0
72.4
72.6
68.6
69.7

15.1
16.9
12.6
17.7
15.9
17.9
15.2
17.0
17.2

55.8
56.8
57.5
55.6
55.1
54.5
57.4
51.6
52.5

12.1
10.7
8.6
9.4
10.0
11.1
11.1
9.8
9.7

35.0
35.6
30.6
28.4
28.4
25.8
26.9
24.8
23.6

…
…
6.7
8.1
6.7
7.4
7.2
5.6
7.7

8.7
10.5
11.6
9.7
10.0
10.2
12.2
11.4
11.5

28.3
24.3
28.4
24.8
26.6
25.7
23.6
28.2
27.0

26.7
21.9
25.8
22.8
24.6
23.5
21.7
26.1
24.8

Uruguay

1990
1994
1997
1999
2000
2002
2004
2005

1.9
2.8
2.3
2.3
2.2
2.1
2.0
2.3

75.9
74.4
75.9
76.7
77.7
77.1
75.9
76.9

20.2
18.9
18.1
17.0
18.0
18.0
17.9
17.9

55.7
55.5
57.8
59.7
59.7
59.1
58.0
59.0

6.1
6.2
7.2
7.9
7.6
7.2
7.2
6.9

24.4
24.9
24.4
25.8
22.0
20.9
20.4
23.2

8.1
7.6
9.5
8.6
10.6
9.5
10.1
14.1

17.1
16.8
16.7
17.4
19.5
21.5
20.3
14.8

22.3
22.8
21.8
21.1
20.3
20.9
22.1
20.8

19.1
19.2
18.3
17.1
15.9
16.6
18.0
16.8

Venezuela
1990
(Bol. Rep. of) j 1994
1997
1999
2000
2002
2004
2005
2006

2.3
1.7
1.9
1.9
1.9
2.4
2.2
2.3
1.9

77.5
72.3
65.7
58.9
57.6
55.0
57.4
58.7
60.3

30.4
28.1
25.7
22.7
22.1
20.0
22.7
23.5
25.0

47.1
44.2
40.0
36.2
35.5
35.0
34.7
35.2
35.3

6.4
8.0
6.4
6.5
6.3
5.1
5.8
7.3
6.7

22.3
21.3
18.1
17.1
16.7
16.6
16.2
16.8
17.1

3.4
5.9
5.8
7.0
6.9
6.7
6.4
6.1
6.2

15.0
9.0
9.7
5.6
5.6
6.6
6.3
5.0
5.3

20.2
26.0
32.5
39.2
40.4
42.6
40.5
39.1
37.8

19.1
23.9
30.1
37.4
38.4
40.6
38.4
36.6
35.6

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a

For Argentina (except 1999 and 2000), Brazil (except 1993, 1996 and 1999), Chile (except 1996 and 2000), Mexico (1989 and 2004) and Nicaragua
(1998), this includes public-sector wage or salary earners.
b For Colombia, Dominican Republic (1992, 1995 and 1998) and Mexico (1989 and 1994), no information was available on the size of business
establishments. In those cases, wage earners in non-professional, non-technical occupations in establishments employing up to 5 persons were included
in the figures for establishments employing more than 5 persons. In the case of the Bolivarian Republic of Venezuela, Chile (1996), Dominican Republic,
El Salvador, Panama and Uruguay (1990), establishments employing up to 4 persons are taken into account.
c Includes professional and technical workers.
d Brazil’s National Household Survey (PNAD) does not provide information on the size of business establishments, except in 1993, 1996 and 1999.
Therefore, the figure given for Brazil in the column for establishments employing more than five persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to 5 persons includes workers who do not have such contracts.
e Includes private-sector employees engaged in non-professional, non-technical occupations in business establishments of undeclared size.
f Information from national socio-economic surveys (CASEN).
g In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result ot a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
h  The figures for 1990 are not strictly comparable with those for 1997 owing to changes made in the classification of professional and technical workers.
i  Information from national household income and expenditure surveys (ENIGH).
j  The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas. and the figures therefore refer to the
nationwide total.

Labour market

Country

354

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 20
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
RURAL AREAS, 1990-2006
(Percentages)
Country

Year

Total

Employers

Wage or salary earners
Total

Total

Bolivia

Own-account
and unpaid
family workers

Private sector a

Public
sector

Agriculture

Other

Total

Agriculture

1997

100.0

3.3

8.9

2.4

6.5

2.7

3.8

87.8

79.9

1999

100.0

1.2

9.2

2.3

6.9

2.7

4.2

89.6

82.1

2000

0.5

8.6

2.8

5.8

2.1

3.7

90.9

83.0

100.0

4.2

9.8

2.3

7.5

4.2

3.3

86.0

79.0

2004

100.0

4.4

16.4

4.4

12.0

5.4

6.6

79.2

64.2

1990

100.0

3.0

44.3

…

44.3

22.7

21.6

52.7

44.3

1993

Brazil

100.0

2002

100.0

1.9

33.6

5.1

28.5

20.8

7.7

64.5

58.4

1996

100.0

1.8

34.3

4.4

29.9

20.6

9.3

63.8

57.2

1999

100.0

2.0

34.3

5.2

29.1

15.6

13.5

63.7

56.4

Labour market

2001

100.0

2.5

33.7

4.3

29.4

17.4

12.0

63.8

57.3

2003

100.0

2.2

33.1

3.8

29.3

17.2

12.1

64.7

57.8

2004

2.2

34.2

4.3

29.9

16.7

13.2

63.7

56.6

100.0

2.4

35.0

4.2

30.8

16.8

14.0

62.5

54.0

2006
Chile b

100.0

2005

100.0

2.3

35.3

4.4

30.9

16.3

14.6

62.4

53.8
25.0

1990

100.0

2.8

64.9

…

64.9

45.4

19.5

32.3

1994

100.0

2.6

66.6

…

66.6

42.2

24.4

30.8

21.5

1996

100.0

2.4

64.2

3.6

60.6

39.9

20.7

33.3

26.6

1998

100.0

2.8

64.5

…

64.5

39.8

24.7

32.7

24.4

2000

100.0

2.5

65.1

4.9

60.2

38.7

21.5

32.5

24.3

2003

Colombia c

100.0

2.5

65.6

4.0

61.6

38.9

22.7

32.0

23.4

2006

100.0

2.4

69.3

4.1

65.2

39.0

26.2

28.3

18.6

1991

100.0

6.3

48.6

…

48.6

28.8

19.8

45.0

25.5

1994

100.0

4.5

54.2

…

54.2

28.6

25.6

41.3

22.4
25.0

1997

100.0

4.2

50.6

…

50.6

27.7

22.9

45.1

1999

100.0

3.7

47.2

3.7

43.5

25.9

17.6

49.2

27.9

2002

100.0

4.6

40.6

3.5

37.1

21.3

15.8

54.8

30.2

2004

Costa Rica

100.0

4.0

39.2

2.0

37.2

22.7

14.5

56.7

34.7

2005

100.0

5.0

39.1

2.2

36.9

24.5

12.4

56.0

35.7
16.8

1990

100.0

5.1

66.2

10.5

55.7

24.1

31.6

28.7

1994

100.0

6.8

69.0

9.6

59.4

22.5

36.9

24.2

11.1

1997

100.0

7.1

67.8

9.0

58.8

20.7

38.1

25.2

11.3

1999

100.0

8.2

69.2

8.9

60.3

21.3

39.0

22.7

9.5

2000

100.0

5.8

66.9

9.6

57.3

22.7

34.6

27.3

12.3

2002

7.5

63.5

8.8

54.8

19.4

35.4

29.0

13.2

100.0

7.8

65.8

9.2

56.6

19.2

37.4

26.4

11.5

2005

100.0

7.8

67.9

9.3

58.6

20.4

38.2

24.3

9.7

2006
Ecuador

100.0

2004

99.9

8.0

67.4

9.9

57.5

18.5

39.0

24.5

9.5

2000

100.0

3.2

42.4

3.9

38.5

23.1

15.3

54.3

40.7

2004

100.0

4.2

35.4

3.1

32.3

19.4

12.9

60.4

48.2

2005

100.0

5.5

37.7

2.4

35.3

21.6

13.7

56.8

47.6

2006

100.0

4.3

36.9

2.3

34.6

20.0

14.6

58.7

49.0

Social Panorama of Latin America • 2007

355

Table 20 (continued)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
RURAL AREAS, 1990-2006
(Percentages)
Country

Year

Total

Employers

Wage or salary earners
Total

Public
sector

Private sector

Own-account
and unpaid
family workers

a

Total
Total

Agriculture

Agriculture

Other

1995
1997
1999
2000
2001
2002
2004

100.0
100.0
100.0
100.0
100.0
100.0
100.0

6.0
4.0
4.1
4.6
3.8
3.9
3.2

49.6
50.9
50.8
47.2
47.0
45.9
56.3

3.2
3.1
3.9
3.9
3.8
3.8
3.4

46.4
47.8
46.9
43.3
43.2
42.1
52.9

24.9
24.8
20.2
18.0
17.8
14.7
21.2

21.2
23.0
26.7
25.3
25.4
27.4
31.7

44.3
45.1
45.2
48.1
49.2
50.3
40.5

26.8
28.1
26.3
26.7
28.9
27.6
20.9

Guatemala

1989
1998
2002

100.0
100.0
100.0

0.6
2.0
6.3

38.7
42.9
35.3

2.9
1.7
1.6

35.8
41.2
33.7

23.6
26.6
17.4

12.2
14.6
16.3

60.7
55.1
58.4

47.5
34.8
38.8

Honduras

1990
1994
1997
1999
2002
2003
2006

100.0
100.0
100.0
100.0
100.0
100.0
100.0

0.6
1.7
2.6
3.1
1.3
1.4
1.6

34.9
37.0
34.8
33.4
35.0
35.6
36.4

4.0
4.8
3.4
3.7
1.8
1.9
2.3

30.9
32.2
31.4
29.7
33.2
33.7
34.1

21.0
17.5
19.2
16.4
19.8
20.1
19.3

9.9
14.7
21.2
13.3
13.4
13.6
14.8

64.6
61.4
62.6
63.5
63.7
63.0
62.0

47.6
43.5
41.6
41.3
46.9
43.6
42.6

Mexico d

1989
1994
1996
1998
2000
2002
2004
2005
2006

100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0

2.5
4.0
5.1
4.5
5.0
3.3
3.4
4.1
4.2

50.2
48.6
48.1
45.6
51.0
52.4
61.1
56.8
55.2

…
5.5
6.4
6.0
6.6
7.8
…
…
…

50.2
43.1
41.7
39.6
44.4
44.6
61.1
56.8
55.2

21.9
18.8
16.9
16.0
18.1
15.7
16.4
16.0
14.6

28.3
24.3
24.8
23.6
26.3
28.9
44.7
40.8
40.6

47.3
47.4
46.7
49.9
44.0
44.3
35.4
39.1
40.6

34.6
30.8
28.6
29.2
25.1
25.4
16.8
19.0
19.5

Nicaragua

1993
1998
2001

100.0
100.0
100.0

0.2
3.3
5.4

38.4
43.7
37.4

6.6
…
4.9

31.8
43.7
32.5

17.4
23.8
17.8

14.4
19.9
14.7

61.3
53.0
57.2

45.8
39.7
44.5

Panama

1991
1994
1997
1999
2002
2004
2005
2006

100.0
100.0
100.0
100.0
100.0
100.0
100.0
99.8

3.6
2.5
2.2
2.4
2.0
2.8
2.0
1.9

43.4
49.1
46.2
48.1
40.1
40.9
39.4
41.3

12.8
10.5
10.1
9.5
8.3
8.5
8.1
8.3

30.6
38.6
36.1
38.6
31.8
32.3
31.3
33.0

12.1
15.7
13.1
14.3
14.3
13.3
12.5
13.2

18.5
22.9
23.0
24.3
17.5
19.0
18.8
19.8

53.0
48.5
51.6
49.5
57.9
56.3
58.7
56.7

39.3
33.1
33.4
29.7
39.1
35.5
37.3
38.6

Paraguay

1997
1999
2001
2004
2005

100.0
100.0
100.0
100.0
100.0

2.3
3.4
3.6
2.7
2.4

24.8
27.0
27.1
24.5
26.8

3.2
3.4
2.5
2.4
4.5

21.6
23.6
24.6
22.1
22.3

10.1
7.2
8.8
7.4
7.5

11.5
16.4
15.8
14.7
14.8

72.8
69.7
69.4
72.9
70.9

57.3
54.0
53.7
58.2
58.5

Labour market

El Salvador

356

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 20 (concluded)
BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
RURAL AREAS, 1990-2006
(Percentages)
Country

Year

Total

Employers

Wage or salary earners
Total

Public
sector

Private sector

Own-account
and unpaid
family workers

a

Total
Total

Peru

Agriculture

Agriculture

Other

1997

100.0

5.3

19.8

4.4

15.4

9.9

5.5

74.8

61.0

1999

100.0

6.3

19.9

3.7

16.2

10.9

5.3

73.9

61.9

2001

100.0

5.4

20.6

4.1

16.5

12.0

4.5

74.0

61.2

2003

100.0

5.0

14.6

3.5

11.1

8.2

2.9

80.5

69.5

Dominican

1992

100.0

4.0

52.4

13.2

39.2

14.8

24.4

43.7

21.6

Republic

1995

100.0

2.1

56.1

11.5

44.6

10.3

33.3

41.9

15.7

1997

100.0

3.4

45.6

10.3

35.3

7.3

28.0

51.0

28.5

2000

100.0

1.8

40.3

8.1

32.2

7.2

25.0

57.8

32.6

Labour market

2002

100.0

1.7

36.6

8.3

28.3

5.5

22.8

61.7

34.9

2003

100.0

2.7

42.4

8.9

33.5

4.5

29.0

54.9

25.3
28.0

2004

100.0

2.9

42.0

8.7

33.3

4.7

28.6

55.1

2005

100.0

3.3

39.4

7.8

31.6

4.1

27.5

57.2

27.9

2006

100.0

2.5

41.9

7.9

34.0

4.8

29.2

55.5

27.4

Venezuela

1990

100.0

6.9

46.6

8.3

38.3

22.9

15.4

46.5

33.3

(Bol. Rep. of)

1994

100.0

7.6

47.6

7.4

40.2

19.4

20.8

44.8

29.7

1997

100.0

5.4

49.6

5.4

44.2

34.6

9.6

44.9

33.1

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a

Includes domestic employees. For Brazil (1990), Chile (1990, 1994 and 1998), Mexico (1989, 2004 - 2006) and Nicaragua (1998), public-sector wage
or salary earners are included.
b Information from national socio-economic surveys (CASEN).
c As a result of a changeover to a new survey sample design in 2001, the figures for rural areas are not strictly comparable with those of previous years.
d Information from national household income and expenditure surveys (ENIGH).

Social Panorama of Latin America • 2007

357

Table 21
URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Domestic
employment

Wage or salary earners
Total

Professional and
Nontechnical
professional,
non-technical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and construction and services

1990
1994
1997
1999
2000
2002
2004
2005
2006

44.4
42.7
41.4
40.4
42.2
42.1
44.6
39.8
39.9

3.8
3.4
3.7
3.2
3.4
2.9
2.5
2.5
2.7

12.0
14.8
15.9
14.9
16.0
16.1
15.0
14.5
14.4

0.4
1.4
1.4
1.3
1.4
1.1
1.0
1.4
1.0

11.6
13.4
14.5
13.6
14.6
15.0
14.0
13.1
13.4

5.7
4.8
5.1
5.3
5.3
5.6
6.1
7.1
7.5

22.9
19.7
16.7
17.0
17.5
17.5
21.0
15.7
15.3

6.9
6.0
4.6
5.1
5.1
6.8
10.3
5.5
5.0

16.0
13.6
12.1
11.9
12.4
10.7
10.7
10.1
10.3

(Urban)

1999
2000
2002
2004
2005
2006

42.2
43.5
42.5
40.9
41.2
41.0

3.2
3.3
2.9
2.8
2.8
2.9

14.9
15.4
15.2
15.2
14.5
14.4

1.4
1.3
1.2
1.2
1.3
1.0

13.5
14.1
14.0
14.0
13.2
13.4

5.8
5.9
6.0
5.9
7.2
7.4

18.3
18.9
18.4
17.0
16.7
16.3

5.4
5.6
6.4
5.9
5.6
5.2

12.7
13.2
11.8
11.1
10.9
10.9

Bolivia

1989
1994
1997
1999
2000
2002
2004

58.5
63.0
65.5
64.3
63.1
66.7
70.9

1.1
6.2
5.0
2.5
1.7
3.2
4.1

10.5
14.8
12.0
12.8
10.8
13.9
18.1

0.9
1.0
1.0
1.0
0.6
0.7
1.4

9.6
13.8
11.0
11.8
10.2
13.2
16.7

5.8
5.2
3.6
3.1
4.2
3.9
4.6

41.1
36.8
44.9
45.9
46.4
45.7
44.1

9.8
9.1
11.9
12.1
12.1
12.3
10.8

30.0
27.1
27.7
31.1
30.9
29.4
28.9

Brazil d

1990
1993
1996
1999
2001
2003
2004
2005
2006

49.2
45.5
46.7
47.3
46.2
45.0
43.7
43.6
42.4

…
1.9
2.0
2.2
2.2
2.2
2.2
2.2
2.3

21.6
9.0
10.6
10.1
10.8
10.7
10.5
10.3
10.1

4.3
0.5
0.7
1.7
1.9
0.9
0.9
0.9
0.8

17.3
8.5
9.9
8.4
8.9
9.8
9.6
9.4
9.3

6.2
8.2
8.4
8.5
8.8
8.5
8.5
8.5
8.4

21.4
26.4
25.7
26.5
24.4
23.6
22.5
22.6
21.6

3.5
4.7
5.0
5.2
4.8
6.5
6.0
6.3
5.9

15.8
16.0
15.9
16.4
15.4
12.6
12.3
12.0
11.7

Chile e

1990
1994
1996
1998
2000
2003
2006

38.8
34.6
34.3
34.4
32.5
31.8
30.6

0.8
1.8
2.0
2.6
2.4
2.4
1.7

10.3
9.4
10.1
10.7
9.0
7.9
7.3

0.9
0.8
1.0
1.0
1.0
0.8
0.8

9.4
8.6
9.1
9.7
8.0
7.1
6.5

7.0
6.1
6.1
5.9
6.2
6.5
5.8

20.7
17.3
16.1
15.2
14.9
15.0
15.8

5.7
5.4
4.2
4.1
4.3
4.9
4.8

14.0
11.2
10.7
10.2
9.6
9.2
10.1

Colombia f

1991
1994
1997
1999
2002
2004
2005

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

5.6
5.3
4.5
5.2
5.9
5.2
5.3

27.3
25.0
30.8
35.7
38.5
39.5
37.6

6.4
6.2
7.1
7.5
8.0
7.9
7.6

20.0
18.4
22.9
26.7
27.8
28.1
27.2

Costa Rica

1990
1994
1997
1999
2000
2002
2004
2005
2006

36.9
38.0
39.6
41.6
39.1
40.2
38.9
39.9
39.7

4.4
5.0
6.1
6.0
4.1
6.2
6.2
5.9
6.2

10.5
12.6
12.2
13.2
13.0
12.3
11.2
13.0
11.6

0.8
1.4
1.0
1.4
1.2
1.4
1.3
1.6
1.3

9.7
11.2
11.2
11.8
11.8
10.9
9.9
11.4
10.3

4.4
3.8
3.5
5.1
4.5
4.0
3.4
4.9
5.0

17.6
16.6
17.8
17.3
17.5
17.7
18.1
16.1
16.9

6.4
4.6
4.8
4.5
4.5
4.7
4.3
3.8
4.2

10.1
11.1
12.4
11.9
11.9
12.2
12.9
11.5
11.8

Labour market

Argentina
(Greater Buenos
Aires)

358

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 21 (continued)
URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Domestic
employment

Wage or salary earners
Total

Professional and
Nontechnical
professional,
non-technical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and construction and services

1990
1994
1997
1999
2000
2002
2004
2005
2006

54.5
56.5
56.6
58.9
56.5
56.3
58.6
57.9
57.8

3.6
6.5
6.2
7.0
3.0
4.8
5.1
4.8
4.9

11.9
13.2
12.6
15.0
15.0
14.2
15.1
16.3
16.7

0.6
1.0
0.8
1.6
1.2
0.9
1.1
1.2
1.0

11.3
12.2
11.8
13.4
13.8
13.3
14.0
15.1
15.7

4.5
4.7
5.0
5.4
4.7
4.5
4.2
5.2
4.1

34.5
32.1
32.8
31.5
33.8
32.8
34.2
31.6
32.1

7.8
6.0
6.9
5.6
7.1
6.9
6.5
5.8
5.1

24.4
24.1
23.6
23.8
24.1
23.6
25.2
23.3
24.5

El Salvador

Labour market

Ecuador

1990
1995
1997
1999
2000
2001
2002
2004

55.6
51.0
52.5
52.2
53.8
54.4
54.8
54.6

2.7
4.9
4.8
4.1
5.0
4.4
4.6
4.4

13.6
10.7
11.8
14.6
13.5
14.1
13.5
13.9

0.3
0.2
0.6
0.8
1.0
0.7
1.0
0.7

13.3
10.5
11.2
13.8
12.5
13.4
12.5
13.2

6.1
4.4
4.4
4.3
4.1
4.2
3.7
3.9

33.2
31.0
31.5
29.2
31.2
31.7
33.0
32.4

8.7
8.1
7.1
6.7
7.0
6.7
6.8
6.5

21.8
20.2
21.5
20.0
21.7
22.8
23.9
23.9

Guatemala

1989
1998
2002

54.6
64.4
57.6

2.1
3.6
5.2

14.6
22.4
13.9

0.8
2.3
0.8

13.8
20.1
13.1

7.0
3.9
4.0

30.9
34.5
34.5

7.4
8.2
8.9

14.9
20.7
19.8

Honduras

1990
1994
1997
1999
2002
2003
2006

53.3
49.9
54.3
55.2
56.5
59.4
43.2

1.0
3.0
5.3
5.1
3.6
4.3
3.2

13.9
11.9
11.6
12.2
14.0
14.3
11.1

0.7
0.9
0.6
1.0
1.1
0.9
1.2

13.2
11.0
11.0
11.2
12.9
13.4
9.9

6.7
5.4
5.1
4.8
4.0
4.1
3.7

31.7
29.5
32.3
33.1
34.9
36.7
25.2

8.9
8.1
7.6
7.4
9.8
10.0
9.2

18.7
16.1
20.4
22.0
20.1
22.0
11.7

Mexico g

1989
1994
1996
1998
2000
2002
2004
2005
2006

…
…
43.6
44.3
42.5
47.2
45.7
42.9
45.7

2.8
3.3
3.8
3.9
3.9
3.4
2.3
2.4
2.8

…
…
15.8
15.9
16.0
18.3
19.5
17.1
18.8

…
…
1.2
1.0
1.1
1.3
2.0
1.6
1.9

…
…
14.6
14.9
14.9
17.0
17.5
15.5
16.9

2.7
3.7
3.6
4.1
3.0
4.6
4.9
4.5
3.9

18.9
20.4
20.4
20.4
19.6
20.9
19.0
18.9
20.2

3.0
4.2
3.8
3.2
3.6
4.2
3.5
3.2
3.8

12.5
14.9
15.7
16.4
15.1
16.1
14.7
15.1
15.9

Nicaragua

1993
1998
2001

49.2
60.6
59.9

0.5
3.0
3.6

13.3
16.2
16.5

1.6
1.7
0.7

11.7
14.5
15.8

6.2
6.4
4.4

29.2
35.0
35.4

7.7
4.3
5.5

17.5
26.4
25.7

Panama

1991
1994
1997
1999
2002
2004
2005
2006

32.3
32.0
33.6
34.2
38.4
39.3
40.5
40.1

1.8
1.9
2.2
2.2
2.3
2.5
2.8
2.8

5.9
5.8
6.4
7.0
8.8
8.9
9.4
9.3

0.8
0.4
0.9
0.8
0.7
0.7
0.7
1.3

5.1
5.4
5.5
6.2
8.1
8.2
8.7
8.0

7.4
7.5
6.5
6.1
6.7
6.9
6.8
6.9

17.2
16.8
18.5
18.9
20.6
21.0
21.5
21.1

3.9
4.4
4.6
4.3
4.4
4.2
4.0
4.1

11.5
11.6
12.8
13.8
15.2
15.9
16.4
16.0

Paraguay
(Asunción)

1990
1994
1996
1999
2001
2004
2005

55.5
54.6
57.1
51.9
54.5
61.1
56.0

6.8
7.1
4.7
4.7
6.1
3.9
5.2

17.0
14.6
14.6
14.9
13.0
14.8
14.2

1.1
1.3
0.8
1.3
1.7
1.1
0.9

15.9
13.3
13.8
13.6
11.3
13.7
13.3

10.5
11.5
9.3
9.1
11.0
11.2
10.7

21.2
21.4
28.5
23.2
24.4
31.2
25.9

5.2
5.3
6.4
5.2
5.1
6.4
5.4

15.5
15.9
19.9
17.1
19.0
22.9
18.1

Social Panorama of Latin America • 2007

359

Table 21 (concluded)
URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Domestic
employment

Wage or salary earners
Total

Professional and
Nontechnical
professional,
non-technical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and construction and services

1994
1996
1999
2001
2004
2005

61.2
62.9
59.1
61.6
65.4
61.3

7.2
4.9
5.0
6.4
4.2
4.6

16.0
15.0
15.8
14.7
16.1
16.1

1.0
0.6
0.9
1.4
1.1
0.9

15.0
14.4
14.9
13.3
15.0
15.2

10.5
9.3
9.2
10.4
10.5
11.1

27.5
33.7
29.1
30.1
34.6
29.5

5.4
5.6
5.2
5.3
6.2
5.7

20.2
24.3
21.3
21.9
23.8
19.3

Peru

1997
1999
2001
2003

60.6
63.3
63.1
64.6

4.9
4.5
4.0
3.7

13.1
14.9
14.4
13.3

1.2
1.9
1.0
0.9

11.9
13.0
13.4
12.4

4.4
5.8
5.2
5.6

38.2
38.1
39.5
42.0

5.4
4.9
5.0
5.3

28.6
29.4
28.8
29.7

Dominican
Republic

1992
1995
1997
2000
2002
2003
2004
2005
2006

…
…
47.0
45.1
46.3
46.9
48.1
49.3
50.0

…
…
2.1
1.8
2.3
2.7
4.3
3.5
3.1

…
…
9.1
8.5
7.0
7.4
7.9
6.9
7.8

…
…
0.7
0.7
0.6
0.8
0.8
0.5
0.6

…
…
8.4
7.8
6.4
6.6
7.1
6.4
7.2

3.2
3.8
4.4
4.1
4.3
4.1
5.3
4.8
4.9

32.8
30.6
31.4
30.7
32.7
32.7
30.6
34.1
34.2

5.6
4.9
6.8
7.3
7.4
7.8
6.8
7.9
8.1

23.0
22.1
21.3
20.6
22.0
21.4
20.2
22.3
22.0

Uruguay

1990
1994
1997
1999
2000
2002
2004
2005

39.2
40.3
42.2
41.5
42.6
45.7
45.3
44.3

2.7
3.3
2.8
2.4
2.4
2.4
2.1
2.5

10.6
9.9
11.5
11.0
11.8
11.6
12.0
14.3

0.3
0.5
0.5
0.6
0.7
0.6
0.6
0.6

10.3
9.4
11.0
10.4
11.1
11.0
11.4
13.7

6.9
7.0
7.1
7.5
9.1
9.9
9.4
7.2

19.0
20.1
20.8
20.6
19.3
21.8
21.8
20.3

5.6
6.4
6.8
7.0
7.3
8.1
7.4
6.9

12.0
12.7
12.7
12.7
10.9
12.5
13.0
12.3

1990
1994
1997
1999
2000
2002
2004
2005
2006

39.2
45.3
49.4
53.7
54.6
56.5
54.9
52.0
51.4

4.9
4.2
3.6
3.9
3.8
4.2
3.6
3.7
3.4

6.7
9.7
11.3
12.6
11.6
11.5
10.8
11.2
10.6

0.2
0.5
0.5
0.5
0.4
0.4
0.5
1.0
0.5

6.5
9.2
10.8
12.1
11.2
11.1
10.3
10.2
10.1

6.3
4.0
4.3
2.0
2.1
2.6
2.5
1.9
2.1

21.3
27.4
30.2
35.2
37.1
38.2
38.0
35.2
35.3

4.1
5.9
6.1
6.7
7.4
6.5
6.5
6.0
6.5

15.3
19.0
19.9
23.7
24.7
26.4
25.8
24.4
24.0

Venezuela
(Bol. Rep. of)

h

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a
b
c
d
e
f

g
h

Refers to establishments employing up to 5 persons. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic,
El Salvador, Panama (up to 2002) and Uruguay (1990), includes establishments employing up to four persons.
Refers to own-account and unpaid family workers without professional or technical skills.
Includes persons employed in agriculture, forestry, hunting and fishing.
Until 1990, the “microenterprises” category included wage earners without an employment contract. In 1993 and from 1996 to 1999, this category Included
wage earners in establishments employing up to 5 persons, so that the figures for these years are not comparable with those of previous years.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Information from national household income and expenditure surveys (ENIGH). In the 1994 survey, no Information was given on the size of the
establishments employing wage or salary earners.
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Labour market

(Urban)

360

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 21.1
MALE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS
OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Domestic
employment

Wage or salary earners
Total

Professional
Nonand
professional,
technical
nontechnical

Unskilled
self-employed workers b
Total c

Manufacturing Commerce
and
and
construction
services

Labour market

Argentina
(Greater Buenos
Aires)

1990
1994
1997
1999
2000
2002
2004
2005
2006

42.2
41.3
39.8
39.4
40.8
43.9
39.4
39.2
37.7

4.6
4.4
4.5
4.2
4.1
3.4
3.2
2.9
3.4

12.7
15.7
18.7
16.9
17.9
18.4
17.7
17.6
16.3

0.3
1.2
1.2
1.0
1.5
0.9
1.0
1.3
0.9

12.4
14.5
17.5
15.9
16.4
17.5
16.7
16.3
15.4

1.8
0.4
0.4
0.2
0.2
0.1
0.1
0.9
0.1

23.1
20.8
16.2
18.1
18.6
22.0
18.4
17.8
17.9

8.5
8.4
6.0
7.2
7.2
9.5
7.5
7.5
6.9

14.6
12.3
10.2
10.8
11.4
12.5
10.9
10.1
10.9

(Urban)

1999
2000
2002
2004
2005
2006

40.9
42.5
44.6
41.5
40.9
39.3

4.1
4.1
3.5
3.7
3.5
3.7

16.8
17.6
17.7
18.3
17.7
16.9

1.2
1.5
1.1
1.1
1.3
1.0

15.6
16.1
16.6
17.2
16.4
15.9

0.2
0.2
0.1
0.2
0.7
0.1

19.8
20.6
23.3
19.3
19.0
18.6

7.6
8.0
9.2
7.5
7.6
7.0

11.9
12.4
13.8
11.6
11.1
11.4

Bolivia

1989
1994
1997
1999
2000
2002
2004

48.8
53.7
58.4
57.2
56.2
58.5
64.4

1.5
8.6
7.1
3.0
2.2
4.2
5.7

13.8
19.2
15.2
16.7
15.1
17.8
25.0

0.9
0.9
1.1
1.1
0.8
0.7
1.6

12.9
18.3
14.1
15.6
14.3
17.1
23.4

0.6
0.5
0.5
0.3
0.2
0.2
0.2

32.9
25.4
35.6
37.2
38.7
36.3
33.5

11.5
9.1
12.6
12.7
15.3
13.1
12.5

19.9
15.6
17.1
19.5
19.2
18.4
17.2

Brazil d

1990
1993
1996
1999
2001
2003
2004
2005
2006

44.7
40.6
42.6
43.7
42.3
40.7
39.3
39.0
37.8

…
2.5
2.5
2.9
2.8
2.8
2.7
2.8
2.9

23.4
10.6
12.0
11.6
12.3
12.1
11.8
11.6
11.4

2.3
0.5
0.6
1.1
1.2
0.9
0.9
0.9
0.8

21.1
10.1
11.4
10.5
11.1
11.2
10.9
10.7
10.6

0.4
0.8
0.8
0.8
0.8
0.8
0.8
0.8
0.8

20.9
26.7
27.3
28.4
26.4
25.0
24.0
23.8
22.7

5.1
6.7
7.4
7.5
7.1
7.8
7.2
7.6
7.2

12.9
14.8
15.1
15.9
14.9
12.5
12.2
11.7
11.3

Chile e

1990
1994
1996
1998
2000
2003
2006

33.8
30.1
30.2
30.0
27.9
27.8
25.7

0.9
2.0
2.3
2.9
2.9
2.7
2.0

10.7
9.8
10.7
10.5
9.1
8.3
7.3

0.7
0.7
1.0
0.8
0.9
0.7
0.6

10.0
9.1
9.7
9.7
8.2
7.6
6.7

0.2
0.1
0.2
0.1
0.1
0.2
0.1

22.0
18.2
17.0
16.5
15.8
16.6
16.3

6.3
6.2
4.8
5.0
5.2
6.1
5.7

14.3
10.9
10.6
10.2
9.2
9.1
9.2

Colombia f

1991
1994
1997
1999
2002
2004
2005

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

0.3
0.2
0.2
0.5
0.4
0.4
0.3

28.4
26.0
32.6
37.3
39.3
40.2
38.0

6.2
6.7
8.4
8.4
8.2
8.0
8.0

20.9
18.7
22.9
26.5
26.7
26.7
25.5

Social Panorama of Latin America • 2007

361

Table 21.1 (continued)
MALE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS
OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Wage or salary earners
Total

Domestic
employment

Professional
Nonand
professional,
technical
nontechnical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and
and
construction
services

1990
1994
1997
1999
2000
2002
2004
2005
2006

35.1
36.2
38.5
39.5
37.4
37.3
36.7
36.6
36.8

5.7
6.1
7.8
7.7
5.1
7.9
7.9
7.3
7.5

11.1
13.1
13.4
14.7
13.5
13.0
11.9
13.9
12.4

0.8
1.5
1.0
1.4
1.1
1.6
1.4
1.3
1.2

10.3
11.6
12.4
13.3
12.4
11.4
10.5
12.6
11.2

0.2
0.3
0.2
0.4
0.3
0.3
0.3
0.4
0.5

18.1
16.7
17.1
16.7
18.5
16.1
16.6
15.0
16.4

5.7
4.4
5.2
4.4
5.3
5.1
4.5
4.0
4.8

10.8
10.9
11.0
10.9
11.6
9.8
10.6
9.8
10.2

Ecuador

1990
1994
1997
1999
2000
2002
2004
2005
2006

50.7
52.5
52.2
54.9
53.6
52.1
54.5
54.0
54.1

4.3
7.8
7.6
8.6
3.8
5.7
6.4
5.7
5.6

14.2
15.9
14.8
18.0
18.0
16.8
18.7
19.7
20.7

0.4
0.9
0.6
1.4
1.2
0.8
1.0
1.1
1.0

13.8
15.0
14.2
16.6
16.8
16.0
17.7
18.6
19.7

0.6
0.3
0.7
0.6
0.7
0.7
0.5
0.9
0.4

31.6
28.5
29.1
27.7
31.1
28.9
28.9
27.7
27.4

8.0
5.8
6.5
5.4
7.5
6.9
7.0
6.3
5.4

20.7
20.2
19.5
19.6
20.6
19.4
19.4
18.6
19.2

El Salvador

1990
1995
1997
1999
2000
2001
2002
2004

45.9
43.0
44.7
45.7
47.1
47.5
48.4
47.8

3.8
6.7
6.3
5.5
6.6
5.5
6.1
5.8

18.6
14.5
15.2
19.6
18.1
19.3
18.0
18.3

0.4
0.2
0.6
1.0
1.3
0.9
1.1
0.7

18.2
14.3
14.6
18.6
16.8
18.4
16.9
17.6

0.4
0.5
0.3
0.6
0.4
0.5
0.5
0.5

23.1
21.3
22.9
20.0
22.0
22.2
23.8
23.2

6.0
5.2
5.6
4.2
5.0
4.4
4.8
5.0

12.8
11.5
12.2
11.3
12.5
13.9
14.9
14.5

Guatemala

1989
1998
2002

49.5
59.1
51.5

2.5
4.7
6.9

18.2
26.9
16.9

0.8
2.5
0.6

17.4
24.4
16.3

0.2
0.3
0.1

28.6
27.2
27.6

5.7
5.6
7.6

10.1
13.3
11.3

Honduras

1990
1994
1997
1999
2002
2003
2006

46.6
43.0
52.1
52.4
55.7
57.9
44.2

1.2
4.1
7.3
6.7
4.5
5.6
3.9

18.2
12.0
16.2
17.1
18.2
18.8
14.6

0.8
0.9
0.4
0.9
1.0
0.8
1.3

17.4
14.2
15.8
16.2
17.2
18.0
13.3

0.4
0.0
0.8
0.6
0.4
0.5
0.6

26.8
26.9
27.8
28.0
32.6
33.0
25.1

6.6
5.6
4.7
4.1
8.4
8.0
8.2

13.5
12.6
15.7
17.6
15.9
17.1
9.7

Mexico g

1989
1994
1996
1998
2000
2002
2004
2005
2006

…
…
41.7
41.3
40.7
44.9
42.2
38.9
42.0

3.5
4.4
5.1
5.1
5.1
4.6
3.0
3.0
3.6

…
…
18.3
18.4
19.3
20.7
22.5
19.4
21.5

…
…
1.0
1.0
1.2
1.3
1.7
1.5
1.8

…
…
17.3
17.4
18.1
19.4
20.8
17.9
19.7

0.6
0.6
0.9
1.2
0.9
1.4
1.0
0.7
0.6

17.5
17.9
17.4
16.6
15.4
18.2
15.7
15.8
16.3

2.5
4.0
3.6
2.6
3.6
3.9
3.7
3.5
4.0

10.5
12.6
12.9
13.2
10.7
13.5
11.0
11.6
11.7

Labour market

Costa Rica

362

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 21.1 (continued)
MALE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS
OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Total

Nicaragua

Domestic
employment

Wage or salary earners
Professional
Nonand
professional,
technical
nontechnical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and
and
construction
services

45.8

0.6

17.4

1.2

16.2

0.3

27.5

6.8

14.2

55.8

4.2

20.4

1.7

18.7

1.2

30.0

4.9

18.2

2001
Panama

1993
1998

55.7

4.9

22.1

0.6

21.5

0.1

28.6

4.6

17.3

1991

31.8

2.4

6.6

0.9

5.7

0.8

22.0

5.4

13.5

1994

31.2

2.5

6.5

0.4

6.1

1.0

21.2

5.8

14.0

1997

31.9

2.9

6.6

0.8

5.8

1.0

21.4

6.1

13.5

1999

32.2

2.8

7.6

0.8

6.8

0.9

20.9

5.4

14.3

Labour market

2002

37.8

2.9

10.3

0.7

9.6

1.0

23.6

5.9

16.2

2004

38.1

3.4

9.8

0.6

9.2

1.1

23.8

5.4

17.0

2005

38.9

3.7

10.6

0.7

9.9

1.2

23.4

4.9

16.7

2006

38.1

3.6

10.7

0.8

9.9

0.8

23.0

5.1

16.3

Paraguay

1990

48.0

10.2

21.4

0.8

20.6

0.0

16.4

4.3

11.5

(Asunción)

1994

47.9

8.8

19.3

1.2

18.1

1.6

18.2

5.4

11.9

1996

51.1

6.2

19.3

0.9

18.4

1.0

24.6

6.6

15.0

1999

43.8

6.1

16.4

1.9

14.5

0.8

20.5

4.9

14.5

2001

7.8

15.3

1.6

13.7

2.3

20.3

4.2

15.8

55.3

5.6

18.9

1.2

17.7

2.5

28.3

6.6

20.1

2005
(Urban)

45.7

2004

50.4

7.6

19.9

1.2

18.7

1.5

21.4

5.9

13.7

1994

55.1

9.0

21.2

1.0

20.2

1.4

23.5

5.3

15.4

1996

56.7

6.6

20.1

0.8

19.3

0.9

29.1

6.0

18.4

1999

6.8

19.1

1.2

17.9

0.9

25.1

4.9

16.8

55.6

8.6

19.3

1.3

18.0

1.6

26.1

4.8

18.0

2004

60.2

5.7

21.1

1.1

20.0

1.9

31.5

6.2

20.9

2005
Peru

51.9

2001

57.0

6.4

22.7

1.1

21.6

1.5

26.4

6.0

15.8
19.2

1997

53.7

7.0

17.0

1.1

15.9

0.2

29.5

5.3

1999

56.5

6.2

18.0

1.9

16.1

0.4

31.9

5.0

21.7

2001

56.7

5.5

18.5

1.0

17.5

0.5

32.2

5.4

20.4

2003

58.1

4.8

16.7

0.8

15.9

0.8

35.8

5.1

23.5

Dominican

1992

…

…

…

…

…

0.2

36.2

5.8

24.0

Republic

1995

…

…

…

…

…

0.2

35.1

5.3

24.4

1997

47.5

2.7

9.9

0.5

9.4

0.4

34.5

8.7

20.8

2000

46.6

1.9

8.5

0.8

7.7

0.6

35.6

10.1

21.3

2002

48.1

2.7

6.7

0.6

6.1

0.8

37.9

10.3

22.5

2003

48.9

3.4

6.8

0.7

6.1

0.4

38.3

10.8

22.0
20.6

2004

49.6

5.0

7.5

0.4

7.1

1.1

36.0

9.7

2005

51.1

4.0

7.3

0.5

6.8

0.9

38.9

11.1

21.8

2006

51.7

3.5

7.5

0.6

6.9

0.7

40.0

11.7

21.8

Social Panorama of Latin America • 2007

363

Table 21.1 (concluded)
MALE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS
OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Total

Uruguay

Domestic
employment

Wage or salary earners
Professional
Nonand
professional,
technical
nontechnical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and
and
construction
services

1990

34.8

3.7

12.1

0.3

11.8

0.1

18.9

5.4

11.7

1994

36.0

4.2

11.0

0.4

10.6

0.1

20.7

6.9

12.4

1997

38.2

3.6

12.3

0.3

12.0

0.2

22.1

8.1

12.8

1999

38.6

3.1

12.1

0.4

11.7

0.2

23.2

9.0

13.0

2000

38.3

3.1

12.0

0.6

11.4

1.3

21.9

9.6

10.7

2002

43.0

3.2

12.8

0.6

12.2

1.4

25.6

10.7

13.3

41.6

2.7

12.9

0.6

12.3

1.4

24.6

9.3

13.4

41.4

3.3

13.9

0.6

13.3

1.1

23.1

8.8

12.8

Venezuela

1990

39.1

6.5

8.2

0.2

8.0

1.9

22.5

4.0

15.7

(Bol. Rep. of) h

1994

47.8

5.8

11.3

0.4

10.9

1.5

29.2

6.5

19.0

1997

50.4

4.8

13.8

0.4

13.4

1.5

30.3

6.8

17.4

1999

54.6

5.2

15.2

0.3

14.9

0.1

34.1

7.2

19.9
20.6

2000

55.6

5.1

14.0

0.3

13.7

0.1

36.4

8.4

2002

56.4

5.6

14.0

0.2

13.8

0.1

36.7

7.1

21.9

2004

55.7

4.7

13.2

0.4

12.8

0.1

37.7

7.4

21.9

2005

52.9

4.8

13.6

0.8

12.8

0.1

34.4

6.7

20.7

2006

52.6

4.6

12.8

0.4

12.4

0.1

35.1

7.7

20.4

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a
b
c
d
e
f

g
h

Refers to establishments employing up to 5 persons. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic,
El Salvador, Panama (up to 2002), and Uruguay (1990), includes establishments employing up to four persons.
Refers to own-account and unpaid family workers without professional or technical skills.
Includes persons employed in agriculture, forestry, hunting and fishing.
Until 1990, the “microenterprises” category included wage earners without an employment contract. In 1993 and from 1996 to 1999, this category included
wage earners in establishments employing up to 5 persons, so that the figures for these years are not comparable with those of previous years.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Information from national household income and expenditure surveys (ENIGH). In the 1994 survey, no information was given on the size of the
establishments employing wage or salary earners.
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Labour market

2004
2005

364

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 21.2
FEMALE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS
OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Domestic
employment

Wage or salary earners
Total

Professional
Non
and technical professional,
non-technical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and construction and services

Labour market

Argentina
(Greater Buenos
Aires)

1990
1994
1997
1999
2000
2002
2004
2005
2006

48.0
45.6
43.9
41.9
44.1
40.0
41.1
40.7
42.9

2.3
1.6
2.5
1.7
2.2
2.3
1.6
1.8
1.8

10.6
13.0
11.2
12.2
13.2
13.0
11.4
10.2
11.8

0.4
1.5
1.6
1.9
1.2
1.4
1.1
1.5
1.1

10.2
11.5
9.6
10.3
12.0
11.6
10.3
8.7
10.7

12.5
12.3
12.7
12.7
13.0
13.2
14.5
15.7
17.3

22.6
18.7
17.5
15.3
15.7
11.5
13.6
13.0
12.0

4.0
1.8
2.3
1.9
2.0
3.1
4.1
2.8
2.5

18.6
16.8
15.2
13.4
13.7
8.4
9.5
10.2
9.5

(Urban)

1999
2000
2002
2004
2005
2006

44.0
45.2
39.5
41.8
41.7
43.4

1.7
2.2
2.0
1.7
1.8
1.9

11.8
12.2
11.8
10.7
10.3
11.3

1.6
1.1
1.4
1.2
1.4
1.1

10.2
11.1
10.4
9.5
8.9
10.2

14.2
14.3
14.0
15.2
16.1
17.2

16.3
16.5
11.7
14.2
13.5
13.0

2.1
2.1
2.6
3.7
2.8
2.7

14.1
14.3
9.1
10.4
10.7
10.3

Bolivia

1989
1994
1997
1999
2000
2002
2004

71.5
75.0
75.2
75.3
71.9
76.7
78.7

0.4
3.1
2.1
1.7
1.1
2.1
2.0

6.1
9.0
7.9
7.6
5.2
9.4
9.7

0.9
1.1
0.9
0.7
0.3
0.8
1.1

5.2
7.9
7.0
6.9
4.9
8.6
8.6

12.9
11.2
7.7
6.7
9.4
8.3
10.0

52.1
51.7
57.5
59.3
56.2
56.9
57.0

7.5
9.1
11.1
11.3
8.1
11.3
8.7

43.6
42.1
41.8
45.9
45.7
42.6
43.2

Brazil d

1990
1993
1996
1999
2001
2003
2004
2005
2006

56.8
53.2
52.7
53.1
51.6
51.1
49.7
49.7
47.8

…
1.0
1.3
1.3
1.3
1.4
1.5
1.5
1.5

18.8
6.6
8.3
8.0
8.8
8.8
8.7
8.6
8.4

7.6
0.6
0.7
2.7
2.9
1.0
0.9
0.9
0.8

11.2
6.0
7.6
5.3
5.9
7.8
7.8
7.7
7.6

15.6
19.8
19.7
20.3
20.0
19.1
18.9
18.7
18.3

22.4
25.8
23.4
23.5
21.5
21.8
20.6
20.9
19.6

0.9
1.6
1.6
1.7
1.6
4.6
4.4
4.5
4.3

20.7
17.8
17.1
17.1
16.1
12.9
12.5
12.3
12.2

Chile e

1990
1994
1996
1998
2000
2003
2006

47.5
42.7
41.5
41.7
39.8
38.0
38.2

0.5
1.5
1.5
2.1
1.6
1.9
1.4

9.5
8.6
9.2
11.1
8.9
7.3
7.1

1.3
0.9
1.0
1.4
1.1
0.9
0.9

8.2
7.7
8.2
9.7
7.8
6.4
6.2

19.4
16.8
16.3
15.2
16.0
16.3
14.3

18.1
15.8
14.5
13.3
13.3
12.5
15.4

4.6
4.0
3.2
2.8
2.8
3.0
3.5

13.3
11.7
10.9
10.3
10.2
9.3
11.6

Colombia f

1991
1994
1997
1999
2002
2004
2005

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

13.6
12.7
10.4
11.5
12.7
11.2
11.1

25.5
23.4
28.2
33.4
37.4
38.3
36.8

6.8
5.4
5.2
6.3
7.7
7.6
7.0

18.6
17.9
22.9
26.8
29.2
29.8
29.2

Social Panorama of Latin America • 2007

365

Table 21.2 (continued)
FEMALE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS
OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Domestic
employment

Wage or salary earners
Total

Professional
Non
and technical professional,
non-technical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and construction and services

1990
1994
1997
1999
2000
2002
2004
2005
2006

40.1
40.9
41.3
45.1
41.7
45.1
42.4
44.9
44.4

1.9
3.1
3.3
3.3
2.3
3.7
3.4
3.7
4.2

9.5
11.5
10.1
11.0
12.3
11.2
10.1
11.4
10.5

0.9
1.2
0.9
1.6
1.4
1.1
1.1
2.0
1.5

8.6
10.3
9.2
9.4
10.9
10.1
9.0
9.4
9.0

12.0
10.1
9.2
12.6
11.4
9.8
8.4
12.0
11.7

16.7
16.2
18.7
18.2
15.7
20.4
20.5
17.8
18.0

7.7
4.9
4.0
4.6
3.2
4.2
3.8
3.5
3.4

8.9
11.3
14.7
13.5
12.4
16.0
16.6
14.2
14.4

Ecuador

1990
1994
1997
1999
2000
2002
2004
2005
2006

61.1
62.8
62.8
65.1
61.0
64.1
64.6
63.8
63.4

2.3
4.4
4.0
4.4
1.7
3.3
3.1
3.4
3.7

7.6
8.8
9.2
10.3
10.1
10.0
9.7
11.5
10.5

0.9
1.1
1.2
1.9
1.1
0.9
1.2
1.5
0.9

6.7
7.7
8.0
8.4
9.0
9.1
8.5
10.0
9.6

11.6
11.8
10.9
13.1
11.1
10.8
9.7
11.5
9.8

39.6
37.8
38.7
37.3
38.1
40.0
42.1
37.4
39.4

7.5
6.2
7.5
5.8
6.5
7.8
5.9
5.1
4.7

31.0
30.5
30.2
30.5
29.6
30.3
33.8
30.2
32.5

El Salvador

1990
1995
1997
1999
2000
2001
2002
2004

67.9
60.8
62.0
59.6
61.1
62.3
61.0
62.5

1.4
2.8
3.0
2.6
3.1
3.1
2.9
2.8

7.5
6.1
7.6
8.9
8.3
8.4
8.6
9.0

0.3
0.3
0.5
0.5
0.6
0.6
0.8
0.6

7.2
5.8
7.1
8.4
7.7
7.8
7.8
8.4

13.1
9.1
9.4
8.6
8.2
8.4
7.0
7.7

45.9
42.8
42.0
39.5
41.5
42.4
42.5
43.0

12.1
11.6
8.9
9.5
9.3
9.3
8.9
8.3

33.0
30.7
32.8
29.7
32.0
32.8
33.6
34.5

Guatemala

1989
1998
2002

62.7
71.2
65.7

1.3
2.2
2.9

8.7
16.7
9.8

0.8
2.1
1.0

7.9
14.6
8.8

18.1
8.4
9.2

34.6
43.9
43.8

10.1
11.6
10.6

22.7
30.2
31.2

Honduras

1990
1994
1997
1999
2002
2003
2006

63.3
55.6
57.3
58.5
57.9
61.5
41.7

0.8
1.5
2.7
3.2
2.4
2.6
2.3

7.5
6.8
5.5
6.3
8.6
8.6
6.5

0.6
0.8
0.8
1.2
1.3
1.1
1.1

6.9
6.0
4.7
5.1
7.3
7.5
5.4

16.0
13.7
10.7
9.9
8.9
8.7
7.7

39.0
33.6
38.4
39.1
38.0
41.6
25.2

12.3
12.0
11.4
11.3
11.7
12.6
10.5

26.5
21.4
26.7
27.2
25.6
28.3
14.2

Mexico g

1989
1994
1996
1998
2000
2002
2004
2005
2006

…
…
47.6
49.6
45.7
51.0
50.7
48.7
50.8

1.2
1.1
2.0
1.9
1.8
1.6
1.3
1.6
1.6

…
…
11.4
11.6
10.6
14.4
15.2
13.7
15.0

…
…
1.5
0.9
1.0
1.3
2.4
1.7
2.1

…
…
9.9
10.7
9.6
13.1
12.8
12.0
12.9

7.1
9.6
8.3
9.0
6.5
9.7
10.6
10.1
8.6

21.9
25.0
25.9
27.1
26.8
25.3
23.6
23.3
25.6

4.0
4.6
4.2
4.4
3.7
4.6
3.1
2.8
3.4

16.7
19.1
20.7
22.0
22.4
20.3
20.1
20.2
21.8

Labour market

Costa Rica

366

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 21.2 (continued)
FEMALE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS
OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Country

Year

Microenterprises a

Total
Employers

Total

Nicaragua

Domestic
employment

Wage or salary earners
Professional
Non
and technical professional,
non-technical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and construction and services

54.2

0.5

7.9

2.2

5.7

14.1

31.7

9.0

1998

67.4

1.3

10.7

1.8

8.9

13.5

41.9

3.6

37.4

2001
Panama

1993

22.0

65.5

1.9

8.7

0.7

8.0

10.3

44.6

6.7

37.2

1991

32.9

1.0

5.0

0.6

4.4

16.4

10.5

1.8

8.7

1994

33.4

1.0

4.7

0.5

4.2

17.7

10.0

2.1

7.9

1997

35.8

1.0

6.1

1.0

5.1

14.5

14.2

2.4

11.7

37.0

1.4

6.0

0.8

5.2

13.7

15.9

2.6

13.1

39.2

1.3

6.5

0.6

5.9

15.3

16.1

2.2

13.8

2004

41.1

1.2

7.4

0.8

6.6

15.7

16.8

2.4

14.3

2005

42.8

1.6

7.6

0.7

6.9

14.9

18.7

2.7

15.9

2006

42.9

1.6

7.0

2.0

5.0

16.0

18.3

2.6

15.5

Paraguay

1990

65.9

2.0

10.2

1.6

8.6

25.6

28.1

6.5

21.1

(Asunción)

1994

65.0

4.9

9.0

1.5

7.5

24.3

26.8

5.3

21.1

1996

65.1

2.8

8.4

0.6

7.8

20.0

33.9

6.3

26.4

1999

64.3

2.9

13.0

0.6

12.4

20.1

28.3

5.7

22.1
22.7

Labour market

1999
2002

2001

4.2

10.3

1.9

8.4

21.1

29.0

6.1

68.6

1.9

9.6

1.0

8.6

22.1

35.0

6.2

26.4

2005

62.6

2.5

7.5

0.6

6.9

21.4

31.2

4.8

23.3

1994

69.9

4.7

8.5

1.0

7.5

23.3

33.4

5.6

27.0

1996

71.4

2.5

8.1

0.4

7.7

20.8

40.0

5.1

32.4

1999

69.1

2.5

11.3

0.5

10.8

20.7

34.6

5.6

27.5

2001

(Urban)

64.6

2004

71.9

3.7

9.0

1.5

7.5

21.5

37.7

6.0

26.7

2004

Peru

72.2

2.3

9.5

1.0

8.5

21.8

38.6

6.3

27.6

2005

66.4

2.4

7.8

0.6

7.2

23.0

33.2

5.3

23.6

1997

69.3

2.2

8.2

1.3

6.9

9.8

49.1

5.4

40.4

1999

71.5

2.5

10.9

1.8

9.1

12.4

45.7

4.8

38.8

2001

71.7

2.2

9.3

1.0

8.3

11.3

48.9

4.5

39.6

2003

72.5

2.3

9.0

0.9

8.1

11.5

49.7

5.5

37.5

Dominican

1992

…

…

…

…

…

8.7

26.7

5.2

21.4

Republic

1995

…

…

…

…

…

10.5

21.9

4.0

17.8

1997

46.0

1.1

7.6

0.9

6.7

11.6

25.7

3.6

22.0
19.4

2000

42.8

1.6

8.7

0.6

8.1

9.7

22.8

2.9

2002

43.7

1.8

7.3

0.6

6.7

10.0

24.6

2.8

21.3

2003

43.6

1.6

8.3

0.9

7.4

10.2

23.5

2.8

20.5

2004

45.9

3.3

8.6

1.4

7.2

12.2

21.8

2.1

19.4

2005

46.3

2.6

6.1

0.5

5.6

11.4

26.2

2.7

23.1

2006

47.2

2.5

8.3

0.6

7.7

11.5

24.9

2.3

22.4

Social Panorama of Latin America • 2007

367

Table 21.2 (concluded)
FEMALE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS
OF THE LABOUR MARKET, 1990-2006
(Percentages of the total employed urban population)
Year

Microenterprises a

Total
Employers

Total

Uruguay

Domestic
employment

Wage or salary earners
Professional
Non
and technical professional,
non-technical

Unskilled
self-employed workers b

Total c

Manufacturing Commerce
and construction and services

1990

46.1

1.4

8.5

0.4

8.1

17.1

19.1

6.0

12.3

1994

46.3

2.0

8.2

0.6

7.6

16.8

19.3

5.7

13.0

1997

46.8

1.6

10.2

0.7

9.5

16.7

18.3

5.0

12.6

1999

45.4

1.6

9.3

0.7

8.6

17.4

17.1

4.4

12.2

2000

48.2

1.4

11.4

0.8

10.6

19.5

15.9

4.2

11.3

2002

49.6

1.4

10.1

0.6

9.5

21.5

16.6

4.6

11.5

2004

50.3

1.3

10.7

0.6

10.1

20.3

18.0

4.8

12.5

2005

48.0

1.6

14.8

0.7

14.1

14.8

16.8

4.6

11.7

Venezuela

1990

39.6

1.7

3.7

0.3

3.4

15.0

19.2

4.4

14.6

(Bol. Rep. of) h

1994

40.7

1.2

6.6

0.7

5.9

9.0

23.9

4.7

19.0

1997

47.9

1.4

6.6

0.8

5.8

9.7

30.2

5.0

24.6

1999

52.2

1.5

7.7

0.7

7.0

5.6

37.4

5.9

30.6

2000

52.9

1.5

7.4

0.5

6.9

5.6

38.4

5.6

32.0

2002

56.6

2.0

7.4

0.7

6.7

6.6

40.6

5.4

33.8

2004

53.6

1.8

7.1

0.7

6.4

6.3

38.4

5.0

32.0

2005

50.2

1.3

7.4

1.3

6.1

5.0

36.5

4.8

30.4

2006

49.3

1.5

6.9

0.7

6.2

5.3

35.6

4.5

29.9

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a
b
c
d
e
f

g

h

Refers to establishments employing up to 5 persons. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic,
El Salvador, Panama (up to 2002), and Uruguay (1990), includes establishments employing up to four persons.
Refers to own-account and unpaid family workers without professional or technical skills.
Includes persons employed in agriculture, forestry, hunting and fishing.
Until 1990, the “microenterprises” category included wage earners without an employment contract. In 1993 and from 1996 to 1999, this category included
wage earners in establishments employing up to 5 persons, so that the figures for these years are not comparable with those of previous years.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Information from national household income and expenditure surveys (ENIGH). In the 1994 survey, no information was given on the size of the
establishments employing wage or salary earners.
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Labour market

Country

2003

1999

1997

1994

1990

6.4

8.5

6.0

7.1
7.9

5.2

6.4
7.3

4.9

6.0
…

…

…

6.7

9.4

9.0

8.0

8.3

8.0 11.4 11.1 10.2 10.7

3.7

3.7

3.7

8.5
…

…

5.4

5.7

4.2

Males

4.5

3.4

7.6

Males

Females 5.9

…

4.1

6.9

Females 3.8

Total

…

3.3

Males

…

4.9

3.5

Females 9.7

Guatemala Total

Males

6.8

8.3

9.9

10.0

El Salvador Total

Honduras

1990

7.4

9.5

2004

2003

1999

1997

1994

6.9 10.5

9.2 14.2

9.6

4.3

6.3

7.4

5.3

6.1

5.8

9.1

2.9

1.9

2.3

7.7

6.2

6.8

7.5

9.9

2.1

1.9

2.0

8.1

5.7

6.7

5.6

7.7

2.3

2.2

2.3

8.8

5.6

6.9

5.2

6.3

5.8
9.2 10.1

7.1 18.5 13.4 14.5

5.8 12.5

6.4 15.3 11.2 12.0
…

…

…

…

…

2.0

8.6 11.4 14.8 14.7 13.2 13.2 12.2

9.7 13.0 14.8 16.4 15.0 15.9 15.5

…
…

…

…
…

…

…
…

…

…
…

…

6.4
6.8

6.1

5.3
5.5

5.1

5.1
4.6

5.3

3.7
3.4

3.9

5.3 11.2 12.7 15.1 20.0 12.0 16.8 12.2 12.2

7.7 13.5 14.9 18.9 25.9 17.4 20.5 15.5 16.3

2.1

2.0

7.3

4.3

5.9

5.2

…

…

…

5.5

8.8

6.9

4.0

6.2

5.3

1.9

3.6

2.8

4.6

8.9

6.2

7.8

7.2

7.5

7.0

5.2

6.0

3.5

8.6

6.5

…

…

…

…

…

…

3.8

8.8

…

…

…

…

…

…

…

…

…

… 19.3 14.0 14.6 13.9 11.7 12.7

7.0

7.2

7.1

5.1 10.7

4.3 11.5

4.7 11.2

…

…

…

6.6

7.5

7.1

…

…

…

8.4
8.2

9.0 12.0

3.4 14.6

6.0

4.8 11.1

8.5

7.4 13.4

9.2 10.3 10.9

8.9

…

…

…

… 21.3 11.9 12.4 10.6

…

…

…

…

…

…

9.6

… 17.7 15.4 16.1 16.2 14.2 14.9

…

…

…

…

…

…

…

…

…

2004

1994

8.8 10.1 11.3 15.3

9.3

8.4

…

5.5

8.3

9.8

7.5

8.3

3.8

4.7

4.4

9.9

7.5

8.5

3.2

6.4

…

…

…

6.2

4.1

4.9

9.2
8.4

9.0

6.7

7.7

…

…

…

7.6

6.6

7.0

3.4

2.6

2.9

… 10.0

…

5.9

8.0

2006

8.2

4.8

6.3
9.7

4.8

7.1

8.0

7.5

6.4

9.3

7.5

3.3

5.2

6.7

9.7

…

…

…

4.4

9.3

9.0

9.9 10.2

7.4 10.9 12.0

5.0

5.9
…

…

…

8.6 14.0 13.4 11.3 10.4

…

…

…

7.4

3.8

5.3

6.4

8.0

9.7 13.6

…

…

…

5.6

3.6

4.4

4.7

9.2

4.2

2.8

3.4

6.0

4.4

5.1

6.1

9.5

3.2

2.7

2.9

7.1

4.0

5.2

6.3

8.1

5.1

8.3

3.3

3.3

3.3

7.2

3.2

4.8

4.3

7.5

3.3

3.1

3.2

7.9

3.0

5.1

…

…

…

… 10.7

…

…

3.6

3.7

3.6

…

…

…

6.0

7.5

6.8

5.2

5.6

5.4

…

…

…

7.2

8.1

7.7

7.8

8.9

4.6

3.3

3.8

4.3

7.3

5.9

4.1 10.2

5.3

4.7

2.8

4.5

3.8

5.1

6.0

6.1

…

…

…

…

…

…

4.1

8.4

6.4

…

…

…

…

…

…

…

…

…

6.3

4.2

5.1

…

…

…

…

…

…

9.8 14.3 21.3 15.3 14.0 12.5 11.7

4.4

6.6

…

…

…

4.0

3.7

3.8

6.3

9.1

…

…

…

9.8 13.8 13.8 12.9 13.4 12.4

5.6

7.4 10.5 10.4

4.2

3.4

3.7

7.6 11.8 17.8 17.0 15.4 13.7

8.4

5.5

6.5

8.8

5.5

6.9

3.2

2.5

2.8

4.9 11.9 16.8 13.0 15.7 14.1 14.4 10.6

5.0

… 11.8 11.6 15.6 22.1 20.9 19.8 17.2

…

8.2 11.6 11.6 16.2 14.9 19.0 18.0 20.0 20.2

9.8

6.0 10.5

… 24.8 21.0 28.3 41.6 35.6 34.3 31.6

… 15.3 11.9 20.7 32.0 28.7 25.6 23.7

…

… 21.6

… 15.8

… 18.2

… 19.7 16.2 24.3 36.6 32.0 29.7 27.4

9.5 19.1 19.3 17.1 23.7 26.3

6.3 17.0 14.0 10.7 20.4 19.0

…

7.7 17.0 18.2 26.2 26.9 25.6 27.4 24.7

8.7 12.4 12.8 18.4 17.7 17.1 18.1 16.2

7.6 17.9 16.1 13.2 21.8 22.1

4.5

…

…

…

8.3 14.3 15.1 21.7 21.7 20.9 22.2 20.1

… 16.5

… 18.2

… 17.4

1999

25 - 34
2005

4.9 10.0 12.7 12.0 15.4 11.4 11.0

1990

9.2 12.6 19.5 13.9 13.4 10.8 11.0 17.2 17.8 24.5 33.9 25.5 25.7 20.6 22.9 11.3

7.1

6.1

Females 9.2

4.7

7.1

6.7

5.3

5.8

9.7 16.2 14.8 12.6 11.0

8.7 11.2

5.3

Total

Females 8.5

3.6

Males

6.5

3.7

5.1

4.9

Males

Females 6.2

Total

4.2

5.3

Costa Rica Total

5.4

13 11.6 14.7 23.0 20.0 18.1 16.0

…

…

…

Females

7.3 11.2 12.4

9.4

…

6.7

8.4

Females 9.7

5.1

6.0 10.1 10.1

8.0 11.8 19.2 17.2 15.1 13.3

5.9

8.1

Males

6.8

8.7

Total

Males

Ecuador

2006

8.9 10.0 14.1 13.8 13.0 13.7 12.1

4.8

Males

Females 3.9

7.4

2.9

4.5

Females 9.1

Total

3.4

9.5

Males

3.2

9.4

Total

9.3

Cuba c

2005

8.2 11.5 20.3 21.1 22.8 31.7 26.9 23.2 20.0

2006

Females 6.4 15.5 17.2 16.5 19.5 15.8 13.7 13.4 15.6 26.7 28.9 26.3 36.3 32.9 29.4 32.9

2004

Colombia b Total

Chile

Brazil

Bolivia

5.7 11.5 12.4 13.4 18.5 11.9

Males

2005

9.9

5.9 13.0 14.3 14.7 19.0 13.5 11.5 10.5 13.0 22.8 24.2 24.3 33.8 29.4 25.8 26.0

Total

Argentina
(Greater
Buenos
Aires)

1997

Age group
2003

15 - 24

35 - 44
1997

1994

1990

7.3

8.6

8.0 14.8

6.3

8.5

2004

2.0

6.0

4.3

1.8

1.5

1.6

4.3

7.0

5.7

4.5

1.7

2.7

…

…

…

2.8

2.3

2.5

6.2

2.8

4.2

5.8

4.8

5.1

1.7

2.8

2.4

4.6

5.5

5.1

1.3

4.1

3.1

…

…

…

1.5

3.7

2.6

5.2

3.1

3.9

…

…

…

3.5

1.5

2.3

6.3

3.4

4.7

4.9

3.0

3.7

5.0

3.8

4.3

1.9

2.1

2.0

5.6

7.4

8.6

5.8

7.1

6.1

3.2

4.6

8.9 10.0

6.4

7.4

9.0

5.5

7.0

5.5

2.3

3.8

9.2

7.7

10

…

…

…

8.4

4.5

6.3

4.8

2.0

3.3

6.3

8.7

…

…

…

8.7

4.3

6.3

…

…

…

7.8

4.8

6.2

2005

5.5

9.0

…

…

…

4.2

2.1

3.0

0.8

4.5

2.9

…

…

…

2.5

6.1

4.4

2.2

3.6

2.9

1.0

2.4

1.8

2.6

6.0

4.4

6.3 13.6

3.6

4.7

…

…

…

4.0

3.9

3.9

3.8

5.0

4.4

3.8

2.7

3.2

2.0

6.9

4.5

9.8

3.1

5.9

2.3

1.3

1.7

4.6

3.0

3.7

…

…

…

…

…

…

2.3

6.6

4.5

9.9

3.6

6.3

1.5

1.6

1.6

6.5

3.1

4.6

…

…

…

…

…

…

…

…

…

8.4

3.6

5.8

2.3

1.9

2.1

6.0

4.0

4.9

7.9 16.4 13.8 12.5 11.2

5.4 10.5

6.5 13.2 11.4

5.0

3.6

4.1

6.2

4.2

5.0

2.5

3.1

2.9

4.3 15.4 13.8 16.1 22.1 11.4

3.9

4.1 10.5 10.6 11.6 18.1

1999

Total

Sex

Country
2003

Table 22

2006

3.1

2.9

3.0

…

…

…

…

…

…

7.2

2.2

4.5

2.2

1.7

1.9

4.4

1.4

2.7

…

…

…

7.2

4.2

5.4

7.7

3.7

5.6

…

…

…

8.7

3.5

5.9

45 and over
1997

1994

1990

9.2

9.9

2004

0.7

5.3

3.7

0.9

1.4

1.2

1.3

6.5

4.3

1.4

1.3

1.3

…

…

…

2.3

3.1

2.9

3.9

3.7

3.8

4.7

5.6

5.3

0.6

2.0

1.5

3.8

8.5

6.6

0.1

2.0

1.3

…

…

…

0.6

5.4

3.4

2.2

2.9

2.7

…

…

…

1.5

1.6

1.6

4.2

2.9

3.3

3.4

3.9

3.7

2.5

2.7

2.6

0.9

2.9

2.1

5.6

6.7

6.3

5.8

5.3

5.5

1.9

4.9

3.7

7.6

6.0

6.6

5.6

5.2

5.4

2.4

4.0

3.3

0.7

3.4

2.3

…

…

…

0.8

5.4

3.5

4.6

3.4

3.8

…

…

…

2.8

3.1

3.0

5.1

1.1

4.3

3.0

0.4

1.3

0.9

1.0

6.1

3.8

7.7

8.6

8.3

…

…

…

3.2

1.9

2.3

9.7

2.7

4.2

3.6

0.9

5.1

3.4

0.8

6.7

3.9

6.7

4.3

5.2

1.1

0.6

0.8

3.3

3.4

3.3

9.7

6.1 10.6 10.4

5.8 10.3 10.1

2.9

3.7

3.4

4.0

3.7

3.8

1.2

2.8

2.1

…

…

…

…

…

…

0.8

6.2

3.8

6.3

4.9

5.4

0.7

0.6

0.6

3.1

3.8

3.6

8.0

8.6

8.3

…

…

…

5.2

4.2

4.6

2.7

3.9

3.3

3.0 10.0 12.4 13.2 10.3 10.8

4.2 10.5 11.1 12.7 16.7

3.8 10.3 11.6 12.9 14.1

1999

OPEN UNEMPLOYMENT RATES BY SEX AND AGE IN URBAN AREAS,
AROUND 1990, 1994, 1997, 1999, 2003, 2004. 2005 AND 2006 a

2003

Labour market

2005

7.2

2006

…

…

…

7.7

…
…

…

…

…

…

…

…

…

… 1.5

… 3.3

… 2.6

…

…

…

…

…

…

4.5 5.7

2.9 3.5

3.5 4.4

0.7 0.7

0.9 0.9

0.8 0.8

4.2 2.8

3.5 2.6

3.8 2.7

6.9

7.1

7.1

… 5.0

… 3.8

… 4.3

5.5 4.6

4.1 4.0

4.7 4.2

…

…

…

9.4

7.2 6.8

8.1

368
Economic Commission for Latin America and the Caribbean (ECLAC)

3.6 3.9

Total

Males

Females 3.1

Mexico

1997

1994

3.2

1999

3.4

6.2

(Asunción) Males

9.0

5.4

… 19.7 23.8 25.8 20.9

… 20.3 18.9 17.9 21.8
…

…

…

8.3

…

…

…

7.4

…

…

…

7.0

2.4

1990

2.7

3.0

2.9

1994

3.2
2.9

3.4

2.8
2.3

3.1

3.5
2.9

3.9

… 10.6 14.3 11.7

9.6

… 17.3 13.2 10.3 10.7

… 14.5 13.7 11.0 10.2

2.0

2.5

3.6

…

…

…

2.7

4.2

3.7

…

…

…

3.4

3.9

3.3

…

…

…

3.3

3.2

11.5 10.0

8.8

7.0

… 8.1

…

…

Males

Females

9.3

7.9

…

…

…
…

…

…
…

…

…
…

…

…

… 16.5

… 14.7

… 15.5

… 21.3 15.2 12.1

… 15.3 15.3 18.0

… 18.2 15.3 15.4
…

…

…
…

…

…

6.5 18.2 17.1 21.8 24.2 18.0

9.9 17.4 21.6 21.0 16.1 16.8

8.3 17.8 19.5 21.4 20.0 17.4

…

…

…

…

…

…

…

…

…

4.7

5.0

4.8

4.8

7.4

6.5

4.2

5.2

… 10.3

…

…

3.0

3.4

3.2
9.5

6.3

4.7

5.5
4.1

3.8

3.9

8.8 14.3

5.2

6.7 11.8

…

…

…

8.3

7.5

7.8

…

…

…

9.9

2.3

6.0

…

…

…

…

…

…

1.2

1.5
0.8

1.8

9.2 12.3

1.0

2.1

1.7

1997

…

7.9

8.4

7.5

9.7

7.2

1.5

9.8

9.6

9.7

1.3

1.6

6.5

8.3

8.4 11.3

9.9

… 13.5 11.2 14.3

… 11.1

0.2

2.3
2.8

2.0

2004

6.3

9.3

…

…

…

1.6

2.4

1.9

5.1

7.8

…

…

…

1.0

2.6

8.8 12.0 12.6 12.1 10.6 22.3 24.0 20.0 12.9 24.8 26.6 26.6 24.1

9.2 10.4

8.0

8.0 10.2

8.7 11.5 10.3

…

…

…

2.6

3.1

2.9

9.7

2.6

6.0

5.1

1.9

3.4

4.5

3.8

4.1

5.5

6.2

5.9

2.9

2.6

2.8

6.2

3.0

4.5

…

…

…

8.8

3.0

5.5

…

…

…

5.5

3.1

4.1

…

…

…

…

…

…

9.2

5.4

7.0

…

…

…

1.4

5.0

6.3

6.9

7.5

7.0

6.8

6.5

6.4

9.2 10.0 10.2 13.3 13.6 15.0 14.1 11.9

…

…

…

1.1

3.2

2.3

1.5

2006

1.7

1990

0.4

4.2

3.1

1994

2.8

8.9

Males

(Bolivarian

9.1 9.0 13.6 14.4 12..3 10.3

6.0

8.2
4.9

7.5

7.2 12.7

9.0

8.7

8.4 10.5 10.0 16.4 12.9 12.8

…

4.0

7.4

…

…

…

0.0

2.0

1.4

6.4

9.1

8.1

6.3

3.9

3.4

7.6

5.8

6.0

7.4

6.9

9.0

5.8

7.4

6.1

8.7

… 13.0

…

… 10.5

0.7

3.9

2.6

6.3

6.1

6.2

8.3 12.8 13.4 11.5

9.6

7.8
9.6 14.3 17.7 23.3 18.4 15.1 13.2

8.8

9.1 10.6 14.7 17.6 14.3 11.8 10.0

…

…

…

4.0

6.9

5.9

6.4

2.5

4.3

4.4

7.1

3.7

7.8

7.2 12.1

4.6

8.0

5.1

8.2

4.2

5.9

5.3

8.4

9.9
8.5 10.4 14.4 12.0

5.7 10.1 10.1

6.8 10.2 11.9

8.9

7.4

8.0

7.8 10.2 11.1 16.8 12.0 11.4

3.4

5.5

7.7

5.8

6.6

…

…

…

1.7

5.5

4.5

4.4

3.0

3.5

2.5

4.9

4.2

4.5

3.4

3.8

5.3

5.6

5.5

6.7

4.4

5.3

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted In the relevant countries.

9.6

8.2 19.9 17.2 16.4 22.2 23.7 19.6 17.3 14.3 12.3

9.3 19.3 17.1 19.8 25.7 28.0 23.0 19.8 17.0 11.3

… 11.0 12.8 14.3 13.5 20.9 17.6 17.5

…

…

8.3 13.6 16.1 20.3 16.4 13.0 11.1 18.0 17.0 26.6 32.6 34.8 28.6 24.1 22.0

11.2

Republic of) d Females 8.4

8.9 10.6 14.5 16.8 13.9 11.4

10.2

… 27.5 31.5 32.7 31.9 46.1 40.2 34.7

Total

Females 11.1 13.0 14.7 14.5 21.1 16.6 15.3

7.3 8.9

… 24.4 24.7 26.3 25.8 37.9 33.0 29.2
… 22.2 19.8 21.8 21.4 32.0 27.9 25.1

Males

9.7 11.4 11.2 16.9 13.0 12.1

8.6 13.4 10.2 9.5

7.3

Total

Venezuela

0.4

1.0

5.8

6.6

6.3

7.1

9.4

3.7

5.0

4.5

7.7

8.8

8.4

8.5

7.7

9.6

9.9

8.6

4.7

9.8

8.7

9.4 11.2 10.6

7.8 10.7

5.4

6.8

9.8 19.7

6.9

7.7 12.1

4.9

6.1

…

…

…

7.9

8.7

8.3

7.8

6.5

7.0

…

…

…

3.1

2.7

2.0

2004

7.9 12.7

6.1

5.1

5.5

3.9

8.5

6.4

4.5 21.1

6.8 14.3

5.9 17.1

7.0

1.8
2.2

2005

…
…

…

…

…

…

…

…

…

…
…

…

6.5 4.8

8.2 6.2

7.6 5.6

7.9

4.8

6.2

8.0 11.9

4.2 3.4

5.6 6.5

…

…

…

3.3

6.9

5.2

6.6 3.7

6.2 5.4

6.4 4.7

…

…

…

0.6 0.7

3.1 3.0

2.2 2.1

2006

b

Labour market

For the exact years of the surveys in each country, see table 21.
As a result of a changeover to a new survey sample design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
c National Statistical Office (ONE), Cuba; 1990-1999, total unemployment (urban and rural), 2003-2006, urban unemployment; on the basis of tabulations of data from the National Occupation Survey,
1990-1999.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas. and the figures therefore refer to the nationwide total.

a

1.1
1.5
7.4 10.5

0.5

3.9

45 and over

… 13.9 10.1 12.9

… 10.6

0.1

1.0

0.8

1997

Females 31.5 24.8 26.0 20.7 25.8 30.5 27.4 25.1 47.3 39.9 38.2 27.1 41.5 49.4 44.9 42.6 27.7 23.4 25.5 20.4 27.1 28.3 30.7 26.8 15.8 15.5 15.0 20.0 21.9 24.4 23.5 18.2 15.4 11.5 14.8 14.0

Males

11.3 12.1 10.9

6.2

7.3

6.8

9.6

19.7 17.0 17.0 13.8 17.8 20.4 18.6 16.8 34.1 30.6 27.8 18.8 31.8 36.3 34.2 32.2 17.3 16.1 15.7 13.7 18.0 18.0 20.0 17.7

7.7

7.0

7.3

9.7 14.1

Dominican Total

… 13.8

… 10.7

3.5 8.7 10.1 12.1 12.5 9.2

5.1 8.2 10.2 11.0

8.6 37.0 28.9 29.2 24.3 31.7 26.8 23.1 19.4 17.8 10.5 10.9

Republic

Uruguay

0.7
0.9

35 - 44
2005

17.6 15.0 13.0 41.0 34.4 34.6 33.6 40.3 34.8 30.9 29.1 26.5 22.5 20.1 19.0 22.0 19.1 15.9 15.3 12.7 12.9 12.2 10.5 15.3 13.0 11.2

4.4 8.4 10.1 11.5 10.5 8.0

…

Total

Females 6.5

6.3

Peru

6.2

2005

9.8

1999

7.1

Females 22.8 19.7 18.2 16.7 23.5

Total

Paraguay

8.3 10.3

2004

9.7

2006

8.2 10.6 11.3 10.2

7.2

2003

… 20.1 20.9 20.9 21.5

7.6

7.4

1999

8.1

2004

17.9 13.0 13.3 11.4 16.5

…

…

…

2.8

1994

9.4 12.5

2005

Males

…

…

…

1990

8.1

1997

8.4 10.0 13.8

2006

9.6

…

…

…

3.1 2.9

3.7

2006

4.3

1990

20.0 15.8 15.4 13.6 19.4 14.0 12.1 10.4 38.8 31.1 31.5 28.3 35.1 30.0 26.3 23.4 21.7 15.8 14.9 13.5 17.6 13.8 12.2 11.0 10.4

… 10.8 12.6 13.6 11.7

2004

4.1 4.1

2005

4.7 4.9

2003

25 - 34
1994

Total

Females

Panama

… 16.5 13.6 14.0 13.1

2.6

3.9

Males

1990

… 14.1 13.1 13.8 12.5

2.6

3.6

1997

Age group
1999

15 - 24
2003

Total
2003

Nicaragua Total

4.5 5.1

5.1 5.8

3.3

3.4

Sex

Country
1999

Table 22 (concluded)

2003

OPEN UNEMPLOYMENT RATES BY SEX AND AGE IN URBAN AREAS,
AROUND 1990, 1994, 1997, 1999, 2003, 2004. 2005 AND 2006 a

Social Panorama of Latin America • 2007
369

1999

1997

1994

1990

9.4

9.0

8.0

8.3

…
7.4

9.5

9.4

8.5

7.3 11.2 12.4

5.1

6.0 10.1 10.1
…

…

…
…

…

…

…

9.5

6.3

7.6

5.4

5.3

4.7

7.1

6.7

6.9 10.5

9.2 14.2

9.6

4.3

6.3

7.4

5.3

6.1

5.8

9.1

2.9

1.9

2.3

7.7

6.2

6.8

7.5

9.9

2.1

1.9

2.0

8.1

5.7

6.7

5.6

7.7

2.3

2.2

2.3

8.8

5.6

6.9

5.3

7.7

2.1

2.0

2.0

8.2

4.5

6.0

4.5

3.4

7.6

5.9

Males

Females

…

…

…

4.9

8.3

6.8

4.3

5.9

5.2

…

…

…

5.5

8.8

7.3

4.0

6.2

5.3

1.9

3.6

2.8

4.6

8.9

6.9

7.8

7.2

7.5

7.0

5.2

6.0

3.5

8.6

6.2

…

…

…

…

…

…

3.8

8.8

6.5

…

…

…

…

…

…

…

…

…
…

5.1

4.3

4.7

…

…

…

2004

2003

1999

1997

1994

9.7

2005

8.1

2.0

3.0

2.6

…

…

…

5.2

6.9

6.4

9.0

5.1

6.6

9.2

9.3

9.3

3.1

4.8

4.2

5.4

9.0

7.1

5.2

1.7

7.3

5.1

2.3

2.3

2.3

8.5

9.9

3.9

2.8

3.4

6.5 13.8

7.8

9.2
6.5

8.3

4.4 14.5

4.0 10.1

4.2 12.0

…

…

…

8.7 13.8 11.4

9.7

9.3 15.3 13.1 11.0

6.6 10.7 11.4

6.8 14.0 10.5

6.7 12.8 10.8

1.7

3.8

3.0

…

…

…

2.6

9.2

6.0

5.0

4.9

5.0

…

…

…

6.6

4.3

5.0

…

2.2

6.6

4.8

…

…

…

1.6

8.8

5.3

5.9

6.0

5.9

…

…

9.7

…

2.0

7.0

4.8

0.3

3.0

1.7

1.9

7.8

4.9

9.5

8.5

9.0

…

…

6.0

8.8

8.6

8.7

…

…

…

8.6

7.4

7.8

5.1

5.8

5.5

2.6

1.5

2.0

1.3

…

…

…

…

…

…

1.3

9.8 10.8

5.4

9.4

6.1

7.5

…

…

…

7.1

6.8 11.1

9.2

7.2 13.3

4.8

5.5

8.9

9.5

2006

6.6

8.3

…

…

…

8.0

9.1

…

…

…

…

…

…

…

…

…

…

…

…

9.5

1994

4.9

7.3

3.1

2.1

2.3

9.7

6.5

7.6

9.1

9.9

8.0

3.3

4.8

…

…

…

7.3

5.4

6.0

2.9

3.0

3.0

…

…

…

6.9

8.1

7.7

4.7

4.1

4.3

… 11.2

…

…

9.8

2.4

3.1

2.8
2.6

1.8

2.1
9.2

7.0

7.9
9.2

5.9

7.3
7.5

3.3

5.2
…

…

…

8.8

9.0 12.7 12.3 10.5 11.4

9.6

8.1 12.5 12.3

5.9 12.1

6.7 12.2 10.6
…

…

…

6.3 11.5 19.2 16.9 12.9 11.5

7.3

8.4

…

…

…

6.4 10.9

5.7

6.8

8.5

…
…

…

7.4

…

4.9

7.0

…

…

1997

9.8 12.2 18.5 13.8

9.9

7.9

6.5

7.8

8.8

5.9

7.3

3.4

3.9

3.7
7.5
9.8

6.0

7.5
4.8

2.0

3.3
…

…

…

8.1

5.1

7.4

2.8

9.5

9.3

8.9

8.7

8.7

8.9

9.1 12.5 14.7

5.2

6.6 10.2 11.2

…

…

…

6.5 11.4 18.6 17.6 15.1 13.8

…
…

…

…

…

…

3.9

4.3

4.1

4.6

6.8

7.8

8.0

…

…

…

7.1

5.4

6.1

…

…

…

6.1

3.6

4.7

5.8

7.6

…

…

…

…

…

…

8.3 10.2

4.6

6.2

9.2 12.8

6.6

8.8

6.7

8.5

…

…

…

9.9

5.4

7.3

7.4

6.6

9.5

2.1

2.0

2.1

8.0

5.0

6.3

…

…

…

… 11.1

…

…

6.7 10.3 10.2 12.9 19.0 11.1 12.4 10.2

3.9

2.3

7.2

4.6

5.7

…

…

…

9.3 14.9 15.7 14.8 15.6 14.0

5.8

… 17.6 14.6 18.4 28.2 24.9 22.4 20.5

…

8.5

7.5 12.2 12.4 11.8 12.0 10.9

6.8 15.7

4.6

5.4 10.5

… 12.4 10.2 14.7 23.2 21.1 18.6 17.0

9.9 11.6 11.4

6.6

7.7

9.4 10.3

…

…

…

9.3 10.4

7.1

7.8

7.8 13.8

…

…

…

8.9

6.4

7.3

2004

3.5

5.9

5.0

…

…

…

4.8

8.1

6.8

4.5

6.0

5.4

…

…

…

5.8

9.4

8.0

5.5

6.9

6.3

1.1

4.1

2.9

4.7

9.4

7.4

6.3

8.0

7.3

8.8

5.8

7.0

2.2

8.6

5.9

…

…

…

…

…

…

3.6

9.0

6.9

…

…

…

…

…

…

…

…

…

8.0

9.3

6.5

5.3

5.9

4.8 10.6

3.9

4.3

…

…

…

… 17.8

… 11.8

… 14.6

5.3

3.8

4.4

…

…

…

8.7

9.6

9.2

9.3

6.7

5.9

6.3

…

…

…

9.3

8.2

9.1

6.6

9.6

8.2

7.6

9.6
3.8 11.4

4.9

4.3

5.8 10.3

5.1

5.4

7.3

9.8 11.0

9.6

…

…

…

…

…

…

5.5

8.2

7.0

…

…

…

…

…

…

…

…

…

7.2

6.4

6.8

…

…

…

…

…

…

7.3 10.5 18.8 15.8 15.2 10.4 10.3 14.9 13.6 18.3 27.0 17.2 17.3 14.3 13.9

4.9

5.7

…

…

…

7.5

3.7

5

6.0

9.2

4.5

4.6

4.5

… 14.1

7.6

2005

2.5 19.7 21.3 17.8 25.2 19.3 17.0 18.4

… 10.2 11.7 10.2

…

…

9.7 14.5 23.2 19.3 16.2 13.9

9.6

7.4

8.1

1994

3.4 12.1

… 12.5

9.8

10 - 12
2006

3.0 15.0 14.4 14.5 21.5 16.0 12.8 12.8

1990

… 13.1

… 18.4 20.5 20.9 19.6 14.2 15.2

… 15.7 15.8 20.6 12.7 10.6

… 16.3 14.9 18.6 28.2 22.2 20.5 17.0

8.2

… 11.3
…

2004

… 16.6 17.4 20.7 15.3 12.0 11.8

2005

6.2 14.4 14.8 20.1 19.1 17.8 19.2 16.5

6.2

6.7 10.3
7.6

6-9
2006

6.2 11.0 11.3 15.6 15.0 13.5 14.6 12.5

7.0 10.1

9.7

6.2

7.6

9.4 10.2

3.4

5.9

…

…

…

9.3

7.4

8.0

8.2

9.3

7.4

4.7

5.9

1990

… 11.1

…

…

8.7 10.3

9.2 12.1 11.6 11.1 11.1

6.5

7.5

2.3

3.2

2.7

8.5 10.4 17.4 15.4 12.8 10.7

4.7

6.2

6.2

5.8

5.9

7.4

5.9

6.5

1.7

3.1

2.4

8.5 15.8 18.7 13.5

6.1 13.1 15.6 19.4 23.5 15.9 10.2

6.8 14.0 16.8 17.0 17.1 15.1

1990

… 11.0

…

9.2 12.6 19.5 13.9 13.4 10.8 11.0

5.7

7.1

8.7 11.2

4.1

3.8

6.5

5.3

6.9

Females

Total

3.3

Males

9.7

3.5

Females

Guatemala Total

10.0

9.2

Females

Males

4.2

Males

8.5

Females

6.1

Males

Total

3.6

Total

3.7

5.1

4.9

6.2

Males

Females

5.8

…

5.4

4.2

9.9

Honduras

6.7

8.0 11.8 19.2 17.2 15.1 13.3

5.3

El Salvador Total

Ecuador

…

Females 13.0 11.6 14.7 23.0 20.0 18.1 16.0

Costa Rica Total

Cuba d

7.3

…

…

6.7

Males

7.9

…

…

9.7 16.2 14.8 12.6 11.0

9.3

5.9

8.1

9.7

Males

Females

8.4

6.8

8.7

Total

Colombia c Total

Chile

6.4

4.8

3.9

Males

Females

8.5

4.9

8.0 11.4 11.1 10.2 10.7

3.7

5.2

…

8.9 10.0 14.1 13.8 13.0 13.7 12.1

7.4

2.9

6.0

6.0

9.1

4.5

Total

3.7

6.4

Females

Brazil

3.4

7.1

9.5

3.7

Males

3.2

6.4 15.5 17.2 16.5 19.5 15.8 12.5 13.4

9.4

Total

8.2

Buenos Aires)Females

9.2

Bolivia

Males

5.9 13.0 14.3 14.7 19.0 13.5 10.6 10.5

2003

5.7 11.5 12.4 13.4 18.5 11.9

2005

Argentina b Total

2006

(Greater

1997

Years of schooling
1999

0-5
2003

Total
1999

Sex
2003

Country
2004

Table 23

…

1990

7.8

5.3

6.3

2.3

2.3

2.3

8.6

6.9

7.6

8.7

4.2

6.1

…

…

…

3.9

2.3

3.0

9.1

0.6

7.4

8.0

4.9

6.3

2.1

1.6

1.8

8.4

7.9

8.1

…

…

7.7

1994

7.6

8.1 13.4

9.4 10.2 14.3

1997

4.6

7.0

8.8

5.7

7.1

6.4

4.0

5.2

9.4

6.2

7.5

5.9

4.5

5.2

6.7 10.0

5.5

6.0

9.4

…

…

…

5.5

4.0

4.8

2.7

3.9

3.3

3.6

2.3

2.8

…

…

…

5.2

4.7

4.9

…

…

…

5.9

4.7

5.4

…

…

…

7.5

5.8

6.7

2005

…

…

…

3.6

2.1

2.8

5.4

7.7

8.1 11.5

…

…

…

3.6

3.2

3.4

5.0

7.3

…

…

…

4.1

2.7

3.4

5.6

7.5

…

…

…

4.3

3.4

3.8

4.0

3.3

3.6

…

…

…

7.4

5.5

6.4

7.1

9.0

8.8

5.8

6.9

4.5

5.2

4.9

5.0 11.2

3.3

4.0

3.3

0.8

1.7

5.7

6.5

6.1

…

…

…

…

…

…

5.8

6.4

6.1

…

…

…

…

…

…

…

…

…

8.3

5.4

6.8

…

…

…

4.5

2.5

3.5

9.6 16.0 17.6 17.0 14.9

5.9 12.4 14.5 13.3 11.2

7.6 14.1 16.1 15.2 13.1

4.8

3.4

4.0

4.2

2.6

3.4

3.1

4.7

4.1

6.5

8.0

2004

9.0 11.7 16.1 10.3 13.4

4.9

6.7

…

…

…

2.6

2.7

2.7

7.3

3.4

5.2

6.0

3.3

4.4

4.2

2.4

3.3

5.0

3.1

3.8

9.5 11.3 12.0 15.1

5.9

13 and over
1999

OPEN UNEMPLOYMENT RATES BY SEX AND YEARS OF SCHOOLING, IN URBAN AREAS,
AROUND 1990, 1994, 1997, 1999, 2003, 2004, 2005 AND 2006 a

2003

Labour market

6.9

2006

5.5

5.7

5.6

…

…

…

…

…

…

9.2

5.2

7.1

0.6

0.8

0.7

4.4

1.9

3.1

…

…

…

7.1

5.5

6.2

6.0

3.7

4.9

…

…

…

8.2

5.3

370
Economic Commission for Latin America and the Caribbean (ECLAC)

2.6

1.2

0.5

2.1
3.2

9.0

8.0

7.0

7.3

…

…
…

…

…

…

…
…

…

…

4.7

…

…

…

2.5

7.6

9.2

11

7.5

9.4
4.1

5.8

4.9
3.3

3.4

3.3

5.9 12.0 11.0

9.5

7.8 16.3 10.3
9.3 19.8

7.7

…

…

…

7.2

5.2

9.0 10.5

8.2

6.9
4.8

2006

4.3

1.9

2.6
3.0
1.7

2.8
3.5

… 12.0 13.8 16.2 12.5

… 16.8 14.7 13.0 15.4

… 15.0 14.3 14.2 14.3

3.7

5.8
6.7

2004

…

…

…

3.1

4.3
4.9

2005

…

…

…

2.8

4.3
5.1

2006

…

…

…

2.3

3.8
4.7

1990

1994

4.2

4.9
5.3
4.2

5.2
5.7

1997

3.2

3.7
4.0
3.1

3.7
4.1

… 10.2 14.7 17.8 14.1

… 14.8 15.1 19.2 19.5

… 12.6 14.9 18.5 16.6

2.7

3.8
4.4

…

…

…

4.3

4.9
5.4

2004

9.8 21.0 14.4 14.4 11.8 16.2 12.8

…

…

…
…

…

…

… 6.0

… 6.7

… 6.4

9.4
9.8

9.0

… 12.9

9.8

8.7

… 10.4 10.1 10.7

9.8
…

…

…

9.7 13.7 12.7

8.6

9.8 12.5 10.4
9.8 13.9

… 11.5 10.0

3.8

6.2

5.2
5.6

9.7

9.2

…

…

…

…

…

…

…

…

…

9.1

7.9

8.4
8.8

9.9 13.9 10.0

2005

8.9
… 18.2

…

… 12.8

7.3

7.0

7.1

8.5

7.4

7.8

…

…

…

1990

5.2

2.6
2.8

5.5

4.6
4.2

3.9

3.9
3.9

4.1

4.4
4.6

…

9.8

8.2

7.2

9.9

8.9

…
…

…

8.1 6.3

11.3 8.9

…

…

…

4.3 3.8

4.3 3.4
4.2 3.1

5.1 …

8.2 …

…

…

…

…

…

…

4.8

2.9

3.7

3.4

7.1

5.3

7.8
4.9

7.6
6.8

5.6

8.1

5.8

7.7

4.8

7.5

6.3

…

…

…

3.5 12.0 10.8 12.5

3.4

… 11.4 10.2

…

…

1.5

1.1

1.3

8.3

3.8

6.1

…

…

…

…

…

…

18.6 18.3 16.8 14.5 14.2 12.2 16.1 15.6 14.2 11.2

11.9 9.7 13.5 10.0

…

…

…

3.4

3.7
4.0

9.7 13.2 12.5

4.8 12.7 14.0 13.6

… 19.2 10.7 10.8

… 13.6 11.6 12.4 11.5

3.3

2.4
2.1

1994

14.7 13.2 15.2 12.2 11.3

… …

… …

… …

2.9 2.9

4.0 3.8
4.9 4.6

2006

4.9 12.9 12.8 13.7 18.4 12.46 …

4.1

4.5 10.6 11.1 13.8 13.5

3.8 22.4 19.1 18.4 17.9 23.4 16.0 13.3 10.8 30.4 27.0 23.5 21.6 25.5 22.7

4.7 18.2 13.5 15.6 14.2 16.9 12.4 10.2

4.4 19.8 15.5 16.6 15.5 19.1 13.6 11.3 10.1 25.3 19.8 18.2 16.0 20.2 16.9

…

…

…

2.2 4.0

1994

5.0
5.7

1997

7.0 10.2 10.4

8.5

9.6

9.9

9.0

6.3 11.1 12.8 11.2

8.3 12.8 11.4 11.8 10.9 15.5 14.3 11.5

9.1 14.5 16.5

…

8.4

Republic of) e Females

5.6
9.7
5.4

8.2 11.4

13 11.1

9.0 13.6 14.4 12.3 10.3

8.3 13.6 16.1 20.3 16.4

9.1

9.3

5.6
5.6

5.7

8.1
6.7

7.4 10.6

8.3

7.6

8.9 13.2 10.9 10.3

7.9 12.2 12.1 11.2

9.4 11.7 13.4 12.0
8.7

9.3

7.1 13.4 10.6 16.2 13.9 10.5

8.2

7.9

6.5 10.7 11.9 18.3 15.6 15.3

5.2

9.8 15.1 10.8 10.6

8.3 10.1

8.9

8.6 13.3 11.3

9.5 11.8 11.4 17.8 14.3
6.1

8.4

9.1

8.7

9.7

9.3

9.2 15.5 19.7 22.3 18.3

9.0 10.6 13.7 16.0 13.0

9.1 12.7 16.2 18.8 15.3

… 12.8 13.3 14.9 14.5 22.7 17.8

7.5

… 10.0
…

8.5 14.3 17.0 21.6 17.1 12.5 10.7

9.5 14.8 14.8 12.7 10.7

9.8 11.0 15.5 17.3 14.2 11.4

7.3 12.9 10.4

7.5 12.1

… 13.0 17.5 18.1 18.2 25.3 20.8 18.9

9.1 10.1

… 10.2 12.4 13.2 13.1 19.1 14.7 13.9
… 8.4

14.9 13.3

11.2 9.3

12.7 11

16.3 …

9.6 …

12.8 …

5.9

6.7

5.6

6.1

7.2

4.4

4.9

6.8

6.3 12.2
7.8 13.8

4.3 10.2

9.8

7.7

8.8

6.6 11.2 14.3 11.8

8.4 12.7 16.6 13.3

8.3

4.8

…
…

…

9.7

7.3

11.3 9.0

9.4

7.2

8.5

7.8 10.4 14.0 18.6 14.6 12.7 10.5

5.9

6.7

5.6

4.0

b

Labour market

For the exact years of the surveys in each country, see table 21.
 For 1990, the levels of schooling for which figures are given are 0 to 6 years, 7 to 9 years and 10 or more years, respectively. For 1994, however, the 0 to 5 category actually refers to between 0 and 9 years
of schooling.
c As a result of a changeover to a new survey sample design in 2001, the figures for urban and rural areas are not strictly comparable with those of previous years.
d  National Statistical Office (ONE), Cuba; 1990-1999, total unemployment (urban and rural), 2003-2006, urban unemployment; on the basis of tabulations of data from the National Occupation Survey.
e  The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas. and the figures therefore refer to the nationwide total.

a

9.8 10.5 12.5 12.2 9.3
34.2 31.9 21.8 16.1 19.5 15.8 18.8 20.0 18.33 18.3

15.0 14.6 11.2 10.9 10.0

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted In the relevant countries.

11.2

(Bolivarian Males

8.9 10.6 14.5 16.8 13.9 11.4

8.6 13.4 10.2
…

10.2

8.9

Females 11.1 13.0 14.7 14.5 21.1 16.6 15.3

7.3

9.7 11.4 11.2 16.9 13.0 12.1
…

7.3

9.5

8.9

Total

Males

Venezuela Total

Uruguay

8.8 12.0 12.6 12.1 10.6

Females 31.5 24.8 26.0 20.7 25.8 30.5 27.4 25.1 30.5 21.3 24.8 18.7 24.7 31.9 24.8 20.4 34.7 29.8 32.7 22.4 29.8 35.3 30.9 28.8 37.2 30.5 26.2 25.1 30.3 36.1

Males

11.3 12.1 10.9

…

…

9.2

7.0
4.2

9.3
8.8

6.2

…

…

…

0.6

1990

3.7 4.3
4.8 4.4

13 and over
2004

19.7 17.0 17.0 13.8 17.8 20.4 18.6 16.8 15.6 13.6 15.3 12.0 15.0 18.1 14.6 11.33 19.6 18.7 18.9 13.5 18.8 20.7 19.0 17.4 25.2 21.4 18.1 16.4 21.5 25.3 23.47 22.3 16.6 13.4 15.1 12.9 14.9 16.5 15.4 14.3

6.2

…

…
…

9.1 49.7

9.1

…

…

…

0.8

2005

3.2
5.0

10 - 12

2005

Republic

7.7

6.8

7.0

8.0

9.1

2004

2.9
4.2

6-9

2006

Dominican Total

… 13.8

8.1

…

…

…

Males

7.3

8.7 10.1 12.1 12.5

Females

3.5

8.8

8.4 10.1 11.5 10.5

8.2 10.2 11.0

… 10.7

6.5

4.4

5.1

…

Total

Females

6.3

7.8

9.4 34.1

9.0

9.1

8.7

0.5

1.9
2.8

8.6 16.3 13.3 13.6

… 11.1

… 16.4 12.5 13.8

Females 22.8 19.7 18.2 16.7 23.5 17.6 15.0 13.0 14.1

6.2

Peru

1.2

3.5
4.8

… 14.1 10.9 11.8

0.4

3.9
5.4

17.9 13.0 13.3 11.4 16.5 11.5 10.0

…

…

…

2.8

1990

1.3
1.6

1994

Males

…

…

…

2.9

2006

3.7
4.3

1997

9.3 40.3

…

…

…

3.1

2005

4.1
4.9

1999

20.0 15.8 15.4 13.6 19.4 14.0 12.1 10.4 15.5 11.5 12.1

Total

Paraguay

2004

4.1
4.7

2003

Total

(Asunción) Males

Panama

… 10.8 12.6 13.6 11.7

2.6

3.4
3.9

Females

3.9

3.2
3.6

… 16.5 13.6 14.0 13.1

3.6

5.1
5.8

1997

Males

3.1

Females

1994

4.5
5.1

1999

… 14.1 13.1 13.8 12.5

3.3
3.4

1990

Total
Males

2003

Nicaragua Total

Mexico

1997

Years of schooling
1999

0-5
2003

Total
1999

Sex
2003

Country
1999

Table 23 (concluded)

2003

OPEN UNEMPLOYMENT RATES BY SEX AND YEARS OF SCHOOLING, IN URBAN AREAS,
AROUND 1990, 1994, 1997, 1999, 2003, 2004, 2005 AND 2006 a

Social Panorama of Latin America • 2007
371

372

Economic Commission for Latin America and the Caribbean (ECLAC)

Wages
Table 24
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Argentina
(Greater
Buenos
Aires)

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
non-technical

1990

6.4

20.6

4.7

…

4.7

9.4

4.5

3.6

2.5

7.9

7.2

1994

8.6

28.3

6.4

…

6.4

10.2

5.7

4.7

3.3

10.8

9.1

7.2

24.2

5.6

…

5.6

9.4

4.8

3.7

2.6

8.6

6.5

6.4

22.0

5.1

6.2

4.8

8.5

4.9

3.5

2.4

7.3

8.1

2002

4.7

20.9

3.5

3.3

3.5

6.7

3.1

2.1

1.7

5.6

4.1

2004

5.0

17.1

4.0

4.0

4.0

6.8

4.0

2.9

1.7

6.6

5.1

2005

5.7

24.6

4.4

5.1

4.2

6.9

4.2

3.1

1.8

7.0

5.8

2006

5.9

21.0

4.8

5.7

4.6

7.4

4.9

3.4

1.7

7.4

6.2

1989

4.2

16.2

3.9

4.1

3.5

7.7

3.5

2.6

1.6

4.1

3.8

1994

3.5

10.3

3.2

3.9

3.0

7.3

2.7

2.0

1.0

2.5

2.2

1997

3.6

10.1

3.9

4.6

3.6

8.8

3.2

2.2

1.1

2.5

2.3

1999

Bolivia

1997
1999

3.4

8.2

4.1

4.7

3.7

7.4

3.8

2.4

1.8

2.3

2.2

Wages

2002

Brazil c

3.2

7.3

4.0

5.2

3.7

7.7

4.0

2.4

2.0

2.0

1.9

2004

2.9

7.6

3.4

5.0

3.1

7.4

3.6

1.9

1.4

1.7

1.6

4.7

16.1

4.1

…

4.1

8.2

3.8

2.6

1.0

3.8

3.4

4.3

15.6

4.2

6.4

3.6

10.9

3.5

d

2.0

1.1

3.1

2.7

1996

5.0

19.1

4.5

7.0

3.9

10.7

3.9

d

2.5

1.5

4.2

3.7

1999

4.4

14.7

4.1

6.6

3.5

6.9

3.2

d

2.1

1.4

3.2

2.8

2001

4.3

14.8

4.1

6.7

3.5

6.9

3.1

d

2.1

1.4

3.2

2.8

2003

4.0

13.4

3.8

6.2

3.3

6.9

3.4

d

2.0

1.3

2.8

2.2

2004

4.0

13.3

3.7

6.2

3.2

6.7

3.3

d

2.0

1.3

7.9

2.3

2005

4.0

13.2

3.8

6.3

3.3

6.7

3.4

d

2.1

1.4

2.8

2.2

2006
Chile e

1990
1993

4.2

13.9

4.2

6.8

3.3

6.7

3.4

d

2.2

1.4

2.9

2.2

1990

4.7

24.8

3.8

…

3.8

7.4

3.5

2.4

1.4

5.4

5.0

1994

6.2

34.2

4.9

…

4.9

9.6

4.0

2.9

2.0

6.3

4.9

1996

6.8

33.7

5.1

6.5

4.8

11.2

3.8

2.9

2.0

8.3

6.4

1998

7.4

33.8

5.6

…

5.6

11.7

4.3

3.0

2.2

8.6

6.5
5.2

2000

32.7

5.8

7.4

5.5

13.3

4.1

3.0

2.4

7.1

7.4

36.7

5.7

7.7

5.3

12.4

4.0

2.9

2.4

7.8

5.8

2006
Colombia f

7.2

2003

6.6

26.9

5.5

7.7

5.1

11.5

4.1

3.1

2.3

7.5

5.6

1991

2.9

7.4

2.7

3.9

2.5

5.3

2.4

…

1.3

2.4

2.2

1994

3.8

13.1

3.4

5.5

3.1

7.9

2.6

…

1.7

3.4

3.0
2.9

1997

3.8

10.9

3.6

5.7

3.2

6.9

2.7

…

1.6

3.2

1999

3.3

9.5

3.7

6.3

3.2

6.8

2.8

…

2.1

2.2

1.9

2002

3.0

7.2

3.6

6.4

3.1

6.3

3.0

…

1.7

1.8

1.5

2004

3.1

7.6

3.7

6.1

3.3

7.0

3.0

…

1.8

1.8

1.6

2005

3.3

8.6

3.8

6.6

3.4

6.8

3.2

…

1.9

1.9

1.7

Social Panorama of Latin America • 2007

373

Table 24 (continued)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
non-technical

1990
1994
1997
1999
2002
2004
2005
2006

5.2
5.7
5.6
6.0
6.5
6.3
5.5
6.1

6.8
10.8
8.4
10.4
10.2
8.2
7.3
9.1

5.4
5.5
5.8
5.9
6.8
7.1
6.0
6.7

7.3
7.8
8.2
8.8
9.5
9.8
8.8
10.3

4.4
4.6
4.8
5.1
6.0
6.2
5.1
5.6

9.0
8.4
9.0
9.7
9.7
10.0
8.1
8.8

4.3
4.4
4.8
4.8
5.9
5.9
5.1
5.6

3.2
3.6
3.2
3.6
3.7
3.9
3.3
3.6

1.5
1.6
1.8
1.7
2.0
2.2
1.6
2.0

3.7
4.4
3.8
4.4
3.7
3.1
3.2
3.0

3.4
4.0
3.6
4.0
3.1
2.6
2.6
2.5

Ecuador

1990
1994
1997
1999
2002
2004
2005
2006

2.8
2.9
3.0
2.9
3.5
3.3
3.6
3.6

4.8
6.6
6.0
7.6
8.7
7.2
8.6
8.8

3.2
2.8
3.0
2.8
3.4
3.7
3.6
3.8

4.1
3.5
3.9
3.8
4.7
5.5
5.8
5.8

2.8
2.5
2.7
2.6
3.1
3.3
3.2
3.4

6.0
5.2
5.7
4.5
5.0
5.6
5.5
5.6

2.9
2.6
2.9
2.9
3.4
3.5
3.5
3.7

2.3
1.9
1.8
1.7
2.1
2.2
2.2
2.3

0.8
0.9
0.9
0.9
1.5
1.7
1.7
2.0

1.9
2.2
2.2
1.8
2.6
2.0
2.4
2.4

1.9
2.0
2.1
1.8
2.4
1.9
2.2
2.2

El Salvador

1995
1997
1999
2001
2004

3.4
3.8
4.2
3.9
3.4

8.6
9.9
9.9
9.2
7.1

3.5
4.5
4.6
4.2
3.7

5.3
5.9
6.9
6.6
6.1

3.0
3.8
4.0
3.7
3.2

6.9
7.8
8.2
7.4
5.3

2.8
3.2
3.7
3.6
3.2

2.0
2.3
2.4
2.3
2.3

1.0
1.9
2.1
2.0
2.1

2.1
2.2
2.5
2.4
2.3

2.0
2.1
2.3
2.2
2.2

Guatemala

1989
1998
2002

3.5
3.4
2.9

17.7
15.7
7.4

3.0
3.1
3.3

4.8
4.5
5.6

2.5
2.9
3.0

5.2
5.2
5.4

2.6
3.4
3.2

1.7
2.0
1.6

1.4
0.6
1.6

3.2
2.2
1.4

2.9
2.1
1.2

Honduras

1990
1994
1997
1999
2002
2003
2006

2.8
2.3
2.0
2.0
2.3
2.3
2.4

16.4
7.3
6.5
5.1
5.1
4.7
4.6

3.1
2.2
2.1
2.1
2.7
3.0
2.9

4.9
3.4
2.9
2.9
4.3
4.9
4.9

2.5
2.0
1.9
1.9
2.4
2.6
2.5

6.5
4.5
4.2
3.0
5.3
6.6
4.6

2.7
1.9
1.8
2.1
2.3
2.5
2.3

1.6
1.3
1.1
1.1
1.4
1.5
1.4

0.8
0.5
0.5
0.5
0.8
1.2
1.2

1.6
1.7
1.3
1.2
1.3
1.0
1.3

1.5
1.6
1.2
1.2
1.2
1.0
0.9

Mexico g

1989
1994
1996
1998
2000
2002
2004
2005
2006

4.4
4.4
3.7
4.1
4.3
4.1
4.1
4.4
4.1

21.7
18.3
15.2
18.2
16.5
16.1
16.5
21.3
15.2

3.5
3.9
3.3
3.5
3.9
3.6
3.6
3.7
3.7

…
5.0
4.9
5.3
5.2
5.4
…
…
…

3.5
3.6
2.9
3.1
3.6
3.2
3.6
3.7
3.7

6.9
9.5
6.4
6.9
7.7
7.1
6.7
6.9
6.9

3.1
3.0
2.8
3.1
3.4
3.3
3.5
3.4
3.5

…
…
1.7
1.9
2.1
2.1
2.2
2.1
2.1

1.4
1.2
1.2
1.3
1.3
1.4
1.4
1.6
1.4

4.8
3.7
2.5
3.0
3.4
3.5
4.0
4.0
3.4

4.4
3.3
2.3
2.6
3.0
3.2
3.3
3.4
2.9

Wages

Costa Rica

374

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 24 (continued)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Nicaragua

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
non-technical

3.5

8.5

3.3

3.4

3.2

6.1

3.1

2.3

2.1

3.6

2.9

3.1

11.1

3.2

…

3.2

6.3

2.6

1.9

1.7

2.1

2.0

2001

3.2

14.3

3.1

4.5

2.7

5.4

3.0

1.8

1.4

1.9

1.8

1991

5.6

14.9

5.8

7.8

4.6

9.8

4.2

2.7

1.3

3.1

2.8

1994

Panama

1993
1998

5.5

17.8

5.4

7.5

4.3

9.6

3.9

2.4

1.3

4.2

4.0

1997

6.0

16.0

6.0

8.3

5.0

10.3

4.2

2.6

1.4

4.4

3.9

1999

6.2

11.9

6.7

9.0

5.8

11.3

4.9

2.8

2.1

3.6

3.3

2002

6.4

13.0

7.1

9.1

6.3

9.7

6.5

5.9

2.5

3.0

2.8

2004

5.5

11.5

6.0

8.9

5.0

9.5

5.4

3.1

1.6

2.9

2.5

2005

5.2

11.0

5.8

8.6

4.8

8.7

5.2

2.9

1.7

2.6

2.3

2006

5.4

10.8

5.9

8.4

5.1

8.0

5.6

3.0

1.5

2.9

2.5

1990

3.4

10.3

2.5

3.4

2.2

4.7

2.6

1.8

0.8

3.8

3.6

1994

3.6

10.0

3.0

4.4

2.7

6.7

2.7

2.0

1.3

2.9

2.9

1996

3.6

10.6

3.3

5.1

2.9

6.5

3.1

2.3

1.2

2.8

2.5
2.3

Wages

Paraguay
(Asunción)

1999

8.9

3.5

4.6

3.2

6.5

3.4

2.3

1.7

2.7

3.4

8.1

3.4

5.2

3.0

4.5

3.6

2.2

1.6

2.2

1.7

2004

2.6

8.3

2.6

3.7

2.4

4.2

2.8

1.8

1.5

1.6

1.4

2005
(Urban)

3.6

2001

2.9

9.6

2.9

4.4

2.5

3.9

3.0

1.7

1.6

1.6

1.3

1994

3.3

9.6

2.8

4.3

2.5

6.6

2.6

1.9

1.2

2.5

2.5
2.3

1996

3.3

9.7

3.1

5.1

2.6

6.3

3.0

2.1

1.1

2.5

1999

3.3

8.8

3.3

4.8

2.9

6.7

3.1

2.1

1.6

2.2

1.9

2001

3.1

8.6

3.1

5.2

2.6

4.5

3.3

1.9

1.4

1.8

1.5

2004

Peru

2.5

7.7

2.4

3.5

2.2

4.1

2.7

1.7

1.4

1.7

1.5

2005

2.7

8.8

2.7

4.1

2.3

4.2

2.9

1.7

1.4

1.5

1.3

1997

3.3

7.9

3.8

4.1

3.7

6.1

3.9

2.3

2.3

1.9

1.7

1999

3.2

7.0

3.9

4.6

3.8

6.9

4.2

2.0

2.9

1.8

1.6

2001

2.8

6.7

3.3

3.9

3.1

5.9

3.4

1.9

2.0

1.8

1.7

2003

2.7

7.9

3.2

4.1

3.0

5.5

3.3

1.8

2.0

1.6

1.5

Dominican

1997

4.4

13.5

3.9

4.7

3.7

7.5

3.5

2.4

1.4

4.3

4.0

Republic

2000

4.6

18.5

3.9

4.8

3.6

7.7

3.3

2.3

1.2

4.7

4.3

2002

4.7

19.8

3.9

4.7

3.7

7.0

3.5

2.3

1.3

4.4

4.1

2004

3.9

16.8

2.3

2.7

2.2

4.3

2.1

1.4

0.9

4.7

4.4

2005

3.1

7.8

3.0

3.5

2.9

5.6

2.7

1.6

1.3

2.6

2.4

2006

3.3

8.7

3.2

3.9

3.0

4.9

3.1

1.6

1.4

2.8

2.6

Social Panorama of Latin America • 2007

375

Table 24 (concluded)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY,
URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Uruguay

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
non-technical

1990

4.3

12.0

3.7

4.0

3.6

7.6

3.7

2.5

1.5

5.1

5.1

1994

4.8

12.3

4.6

5.3

4.2

9.6

4.5

2.9

1.7

3.9

3.5

1997

4.9

11.5

4.8

5.9

4.5

9.8

4.6

3.0

1.8

4.0

3.5

1999

5.4

14.1

5.3

6.7

4.9

11.2

4.9

3.2

2.1

4.1

3.6

2002

10.6

4.4

5.8

3.9

7.9

4.3

2.6

2.0

3.1

2.4

3.7

10.2

3.7

5.2

3.2

6.3

3.6

2.0

1.7

2.7

2.1

2005

3.7

9.7

3.8

5.4

3.3

6.6

3.6

2.0

1.7

2.7

2.0
4.3

1990

4.5

11.9

3.7

4.0

3.6

6.6

3.6

2.5

2.1

4.5

(Bol. Rep. of) h 1994

3.8

8.9

3.2

2.7

3.4

6.7

3.4

2.0

1.9

4.1

3.8

1997

3.6

11.2

2.6

2.9

2.5

5.8

2.4

1.7

1.4

4.2

3.9

1999

3.5

9.2

3.2

3.7

2.9

6.4

2.9

2.0

1.4

3.2

3.0

2002

3.3

9.9

2.9

4.5

2.4

4.8

2.5

1.7

1.2

2.9

2.8

2004

3.2

9.3

2.9

4.1

2.5

4.1

2.6

1.7

1.2

2.8

2.7

2005

3.9

11.8

3.4

4.8

2.9

4.5

3.0

2.0

1.4

3.6

3.5

2006

4.0

9.7

4.0

5.6

3.3

5.4

3.4

2.4

1.7

3.3

3.2

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a

b
c

d
e
f

g
h

For Argentina (except 1999), Brazil (1990), Chile (1990, 1994 and 1998), Mexico (1989 and 2004) and Nicaragua (1998), this includes public-sector
wage or salary earners. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic, El Salvador, Panama (up to
2002) and Uruguay (1990), in the case of non-professional, non-technical workers, this includes establishments employing up to 4 persons. Where no
information was available on the size of the establishments, no figures are given for the population employed in low-productivity sectors. 
Includes own-account professional and technical workers.
Brazil’s National Household Survey (PNAD) does not provide information on the size of business establishments, except in 1993, 1996 and 1999.
Therefore, the figure given for Brazil in the column for establishments employing more than five persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to five persons includes workers who do not have such contracts.
Includes private-sector employees engaged in non-professional, non-technical occupations in business establishments of undeclared size.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Information from national household income and expenditure surveys (ENIGH).
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Wages

Venezuela

4.3

2004

376

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 24.1
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE MALE POPULATION,
BY OCCUPATIONAL CATEGORY, URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
nontechnical

Argentina

1990

7.3

22.2

5.1

…

5.1

11.4

4.7

3.7

4.4

9.4

8.8

(Great

1994

9.7

28.0

7.1

…

7.1

12.3

6.0

4.9

4.5

12.3

10.6

Buenos

1997

8.2

25.7

6.0

…

6.0

11.5

5.1

3.8

2.7

10.2

7.6

Aires)

1999

7.4

24.0

5.7

7.1

5.3

9.9

5.1

3.8

2.6

8.5

7.1

2002

5.7

23.8

4.0

3.9

4.0

8.2

3.3

2.2

3.6

6.3

4.7

2004

18.6

4.6

5.0

4.5

8.3

4.2

3.1

3.7

7.7

6.1

6.6

22.3

5.1

6.2

4.9

8.5

4.6

3.2

3.4

8.3

7.0

2006

7.0

22.7

5.6

6.7

5.4

8.9

5.2

3.6

1.0

8.3

7.3

17.1

4.3

4.8

4.0

9.6

3.6

2.7

4.0

5.4

4.9

4.4

10.8

4.4

4.7

3.5

8.3

2.8

2.2

1.7

3.6

3.2

4.5

10.5

4.4

5.4

4.2

9.8

3.3

2.4

1.8

3.1

2.9

1999

4.1

7.9

4.5

5.2

4.4

8.0

4.1

2.6

1.9

3.0

2.8

2002

4.0

7.7

4.5

5.9

4.2

8.8

4.4

2.5

2.6

2.7

2.5

2004

3.5

7.8

3.8

5.7

3.5

8.3

3.7

2.1

1.3

2.3

2.2

1990

5.7

17.2

4.8

…

4.8

11.3

4.2

2.8

1.3

4.9

4.4

1993

5.3

16.6

4.9

7.9

4.2

14.5

3.7

d

2.0

1.5

4.0

3.6

1996

6.0

20.1

5.2

8.4

4.6

13.8

4.2

d

2.6

2.0

5.2

4.7

1999

5.2

15.5

4.7

7.9

4.1

8.9

3.4

d

2.2

2.1

4.1

3.6

2001

5.1

15.8

4.7

8.0

4.1

8.8

3.4

d

2.2

2.0

4.0

3.5

2003

4.7

14.6

4.3

7.4

3.8

8.0

3.6

d

2.1

1.9

3.6

2.9

2004

4.7

14.6

4.3

7.4

3.8

7.8

3.6

d

2.1

1.8

3.5

2.8

2005

4.7

14.3

4.3

7.6

3.8

7.5

3.6

d

2.1

1.8

3.4

2.7

2006

4.9

15.0

4.5

8.0

3.9

7.7

3.7

d

2.2

1.9

3.6

2.8

1990

5.4

27.4

4.4

…

4.4

10.4

3.6

2.5

1.9

5.8

5.3

1994

7.0

37.6

5.4

…

5.4

12.0

4.1

3.1

2.2

6.7

5.4

1996

7.7

36.3

5.7

7.2

5.5

13.3

4.0

3.0

2.4

9.2

7.2

1998

8.4

37.0

6.3

…

6.3

14.1

4.5

3.2

3.3

9.5

7.1

2000

Chile e

5.1

1997

Brazil c

1989
1994

Wages

Bolivia

6.0

2005

8.5

36.9

6.6

8.3

6.2

15.8

4.3

3.1

3.0

7.9

5.8

2003

Colombia f

8.6

41.0

6.3

8.6

6.0

14.7

4.2

3.0

3.4

8.9

6.5

2006

7.5

29.8

6.0

8.4

5.7

13.5

4.4

3.3

3.1

8.9

6.8

1991

3.3

7.8

3.1

4.2

2.8

6.5

2.5

…

1.5

3.0

2.7

1994

4.4

14.5

3.6

6.1

3.3

9.8

2.6

…

1.7

4.0

3.5

1997

4.4

11.8

4.0

6.4

3.5

8.4

2.9

…

1.6

3.9

3.4

1999

3.8

10.2

4.0

7.1

3.4

7.9

2.9

…

2.7

2.6

2.3

2002

3.4

7.6

3.7

6.7

3.3

6.9

3.0

…

2.2

2.2

1.9

2004

3.5

8.0

3.9

6.5

3.5

8.0

3.1

…

2.1

2.2

2.0

2005

3.8

9.5

4.1

7.1

3.7

7.8

3.3

…

2.8

2.3

2.1

Social Panorama of Latin America • 2007

377

Table 24.1 (continued)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE MALE POPULATION,
BY OCCUPATIONAL CATEGORY, URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
nontechnical

1990
1994
1997
1999
2002
2004
2005
2006

5.8
6.4
6.1
6.8
7.2
7.0
6.2
6.8

7.0
11.9
8.9
11.1
10.2
8.5
7.9
10.3

6.0
6.0
6.1
6.5
7.5
7.6
6.5
7.2

7.9
8.2
8.7
9.5
10.3
10.7
9.7
11.4

5.1
5.2
5.3
5.7
6.8
6.9
5.7
6.2

9.9
9.6
9.7
10.7
10.6
11.1
8.9
9.5

4.6
4.7
5.0
5.1
6.3
6.3
5.4
5.8

3.3
3.9
3.5
3.8
3.9
4.1
3.5
3.7

1.5
2.1
2.3
2.3
2.3
2.9
1.9
3.0

4.8
5.3
5.0
5.6
4.6
3.9
4.0
3.9

4.3
4.9
4.6
5.2
4.1
3.3
3.4
3.3

Ecuador

1990
1994
1997
1999
2002
2004
2005
2006

3.3
3.4
3.4
3.4
4.0
3.9
4.1
4.2

4.9
7.2
6.3
8.2
9.6
7.9
9.2
9.8

3.6
3.1
3.3
3.0
3.7
4.0
3.9
3.9

4.6
3.8
4.1
4.2
5.3
6.4
6.2
6.5

3.2
2.9
3.1
2.7
3.3
3.5
3.5
3.5

8.0
6.7
6.9
4.9
6.1
7.0
6.8
6.3

3.0
2.6
2.9
2.9
3.5
3.5
3.5
3.8

2.4
2.0
1.8
1.7
2.1
2.2
2.3
2.3

1.1
1.1
1.3
1.4
1.9
2.8
2.1
2.0

2.4
2.9
2.7
2.3
3.2
2.6
3.1
3.1

2.3
2.6
2.6
2.3
3.0
2.5
2.7
2.8

El Salvador

1995
1997
1999
2001
2004

4.1
4.4
4.8
4.4
3.8

9.4
10.5
10.3
10.4
7.9

3.9
4.3
4.8
4.4
3.9

5.5
5.9
6.9
6.6
5.9

3.5
3.9
4.4
4.0
3.5

7.6
8.5
9.1
7.7
5.8

3.0
3.3
3.9
3.9
3.4

2.2
2.4
2.5
2.4
2.5

1.7
2.8
2.9
2.3
2.8

2.1
2.9
3.2
3.0
2.6

2.8
2.7
2.9
2.6
2.5

Guatemala

1989
1998
2002

4.0
4.3
3.6

18.6
17.2
8.3

3.3
3.6
3.7

4.8
4.9
6.1

2.8
3.4
3.4

6.2
6.3
6.6

2.7
3.7
3.5

1.8
2.2
1.7

2.6
1.2
1.7

3.9
3.1
1.8

3.6
2.9
1.5

Honduras

1990
1994
1997
1999
2002
2003
2006

3.4
2.7
2.5
2.4
2.6
2.6
2.7

20.3
7.8
7.1
6.7
5.3
5.0
5.1

3.3
2.5
2.2
2.3
2.9
3.0
3.1

5.1
3.8
3.3
3.1
4.9
5.2
5.3

2.9
2.2
2.0
2.1
2.6
2.7
2.7

7.3
5.2
5.3
3.8
6.1
7.1
5.0

2.8
2.0
1.9
2.3
2.5
2.6
2.4

1.7
1.3
1.1
1.2
1.4
1.5
1.5

1.6
1.6
0.8
0.8
1.2
1.4
1.8

2.4
2.1
1.8
1.7
1.6
1.3
1.7

2.2
2.0
1.7
1.6
1.5
1.2
1.2

Mexico g

1989
1994
1996
1998
2000
2002
2004
2005
2006

5.1
5.2
4.3
4.9
5.2
4.9
4.9
5.3
4.9

23.4
19.4
16.0
19.2
17.1
16.5
17.9
24.9
16.7

3.8
4.4
3.6
3.9
4.3
4.0
4.0
4.1
4.1

…
5.6
5.3
5.9
5.6
5.8
…
…
…

3.8
4.1
3.3
3.5
4.1
3.6
4.0
4.1
4.1

7.8
11.5
7.7
8.2
9.3
8.3
8.2
8.4
8.3

3.3
3.2
3.1
3.4
3.7
3.6
3.7
3.7
3.8

…
…
1.8
2.1
2.3
2.3
2.3
2.3
2.2

2.1
2.0
1.9
1.9
2.1
2.0
2.3
3.3
2.7

6.1
5.0
3.4
4.3
5.2
4.9
5.6
5.7
4.7

5.6
4.4
3.1
3.6
4.7
4.5
4.6
4.9
4.1

Wages

Costa Rica

378

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 24.1 (continued)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE MALE POPULATION,
BY OCCUPATIONAL CATEGORY, URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Nicaragua

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
nontechnical

1993

3.8

9.4

3.6

3.9

3.5

7.4

3.1

2.4

1.3

4.1

3.2

1998

3.7

12.0

3.5

…

3.5

7.9

2.8

2.0

3.3

2.5

2.4

2001

3.7

14.1

3.3

5.8

2.8

6.9

3.0

1.8

1.0

2.4

2.2

1991

6.2

15.4

6.6

8.5

5.5

10.6

4.3

2.7

1.3

3.4

3.1

1994

6.3

19.4

6.1

8.5

4.9

10.8

3.9

2.4

2.2

4.7

4.5

1997

6.9

17.2

6.8

9.4

5.7

11.3

4.2

2.6

2.0

5.1

4.5

1999

6.8

12.7

7.3

10.0

6.4

12.1

5.0

2.7

2.4

4.2

3.9

2002

7.1

13.3

7.9

10.3

7.1

11.1

6.7

6.6

2.4

3.5

3.3

2004

6.1

12.4

6.6

10.3

5.4

11.1

5.3

3.0

2.2

3.5

3.1

2005

5.8

11.6

6.3

9.9

5.3

10.2

5.2

3.0

2.1

3.2

2.9

2006

5.9

11.7

6.4

9.5

5.6

9.7

5.6

3.1

2.4

3.4

3.1

Paraguay

1990

4.2

10.4

2.9

4.0

2.6

5.8

2.6

1.9

…

4.8

4.6

(Asunción)

1994

4.4

10.6

3.5

5.1

3.2

8.5

2.7

2.1

2.1

3.5

3.5

Panama

3.6

5.5

3.3

7.3

3.2

2.4

2.0

3.5

3.2

8.9

3.8

4.7

3.6

7.0

3.4

2.3

1.9

3.1

2.6

3.9

7.6

3.7

5.3

3.4

5.5

3.6

2.2

1.9

3.0

2.1

3.1

9.0

2.8

3.9

2.6

3.9

2.9

1.8

2.0

2.2

1.8

2005

3.7

11.2

3.2

4.9

2.7

4.5

3.1

1.7

2.2

2.2

1.8

1994

4.0

10.0

3.2

5.0

2.9

8.2

2.7

2.0

1.9

3.0

3.0

1996

3.9

10.3

3.4

5.5

3.0

6.9

3.1

2.2

1.7

3.1

2.9

1999

3.8

8.7

3.6

5.2

3.2

7.5

3.2

2.0

1.7

2.6

2.3

2001

3.7

8.8

3.4

5.5

3.0

5.4

3.3

1.9

1.8

2.4

1.9

2004

2.9

8.2

2.6

3.8

2.4

4.1

2.8

1.7

1.9

2.3

2.0

2005
Peru

11.7

2004

(Urban)

4.3
4.1

2001

Wages

1996
1999

3.3

10.1

3.0

4.7

2.6

4.8

3.0

1.7

1.8

1.9

1.7

1997

4.0

8.5

4.2

4.6

4.1

7.0

4.3

2.5

2.7

2.5

2.3

1999

3.9

7.9

4.3

5.4

4.1

7.0

4.5

2.1

1.8

2.3

2.1

2001

3.4

7.1

3.7

4.3

3.5

6.8

3.6

2.0

1.8

2.2

2.0

2003

3.4

9.0

3.7

4.6

3.4

7.2

3.4

1.9

3.6

2.0

1.9

Dominican

1997

4.8

14.5

4.0

4.6

3.9

8.0

3.6

2.6

2.2

4.8

4.5

Republic

2000

5.2

20.1

4.4

5.0

4.2

9.2

3.7

2.4

2.0

5.2

4.9

2002

5.4

21.7

4.3

4.9

4.1

7.9

3.6

2.3

2.5

4.9

4.6

2004

4.6

17.4

2.6

2.9

2.5

5.2

2.3

1.5

1.2

5.2

4.9

2005

3.4

8.6

3.2

3.6

3.1

5.9

2.8

1.8

1.8

2.9

2.7

2006

3.7

9.3

3.5

4.1

3.4

6.0

3.2

1.8

2.1

3.2

2.9

Social Panorama of Latin America • 2007

379

Table 24.1 (concluded)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE MALE POPULATION,
BY OCCUPATIONAL CATEGORY, URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Uruguay

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
nontechnical

5.5

13.0

4.3

4.4

4.2

10.1

4.0

2.7

1.5

7.3

7.3

1994

5.8

13.1

5.5

6.0

5.3

12.5

5.0

3.1

3.0

4.9

4.4

1997

5.8

12.3

5.6

6.6

5.3

12.9

5.0

3.2

2.0

4.8

4.2

1999

6.3

14.9

6.2

7.5

5.8

14.6

5.3

3.4

2.7

4.8

4.2

2002

4.9

11.0

5.0

6.3

4.6

9.9

4.6

2.8

3.3

3.4

2.7

2004

4.3

11.1

4.3

5.7

3.9

7.7

3.9

2.2

2.6

3.1

2.4

2005

4.3

10.7

4.3

5.8

3.9

8.0

3.9

2.3

2.7

3.0

2.3

1990

5.1

12.0

4.0

4.4

3.9

7.6

3.7

2.5

3.4

5.1

4.9

(Bol. Rep. of) h 1994

4.3

9.1

3.4

3.1

3.5

7.6

3.4

2.0

2.9

4.6

4.3

1997

4.0

11.4

2.8

3.2

2.7

6.7

2.5

1.7

2.2

4.6

4.3

1999

3.8

9.4

3.3

4.1

3.2

7.4

3.0

2.0

2.0

3.7

3.5

2002

3.6

10.2

2.9

4.8

2.5

5.6

2.6

1.7

1.6

3.3

3.2

2004

3.5

9.6

3.0

4.5

2.6

4.7

2.7

1.7

1.7

3.2

3.1

2005

4.2

12.2

3.4

5.1

3.0

4.8

3.1

2.1

1.7

4.1

4.0

2006

4.3

9.8

4.1

6.3

3.5

5.9

3.6

2.5

1.8

3.7

3.6

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a

b
c

d
e
f

g
h

For Argentina (except 1999), Brazil (1990), Chile (1990, 1994 and 1998), Mexico (1989 and 2004) and Nicaragua (1998), this includes public-sector
wage or salary earners. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic, El Salvador, Panama (up to
2002) and Uruguay (1990), in the case of non-professional, non-technical workers, this includes establishments employing up to 4 persons. Where no
information was available on the size of the establishments, no figures are given for the population employed in low-productivity sectors.
Includes own-account professional and technical workers.
Brazil’s National Household Survey (PNAD) does not provide information on the size of business establishments, except in 1993, 1996 and 1999.
Therefore, the figure given for Brazil in the column for establishments employing more than five persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to five persons includes workers who do not have such contracts.
Includes private-sector employees engaged in non-professional, non-technical occupations in business establishments of undeclared size.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Information from national household income and expenditure surveys (ENIGH).
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Wages

Venezuela

1990

380

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 24.2
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE FEMALE POPULATION
BY OCCUPATIONAL CATEGORY, URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
non-technical

Argentina

1990

4.7

13.6

3.9

…

3.9

6.6

4.0

3.4

2.0

5.8

4.5

(Greater

1994

6.7

29.4

5.4

…

5.4

7.8

6.2

4.2

3.2

8.3

6.4

Buenos

1997

5.6

19.6

4.8

…

4.8

7.3

5.8

3.4

2.5

6.2

4.7

Aires)

1999

4.8

15.0

4.4

5.5

4.0

6.8

4.3

3.0

2.1

5.3

4.3

2002

3.3

12.4

2.8

3.0

2.7

4.8

2.6

1.8

1.7

4.2

2.7

2004

3.6

12.4

3.1

3.2

3.1

5.1

3.4

2.4

1.6

4.7

3.3

2005

Bolivia

4.4

31.0

3.5

4.2

3.3

5.0

3.6

2.6

1.7

5.0

3.7

2006

4.5

16.3

3.9

5.0

3.6

5.6

4.2

3.0

1.7

5.9

4.2
2.9

1989

2.9

10.7

3.6

2.9

3.4

4.1

3.1

2.2

1.6

4.1

1994

2.2

8.4

2.3

2.7

2.1

5.3

2.2

1.5

0.9

2.5

1.6

1997

2.5

8.1

3.0

3.5

2.8

6.8

2.6

1.8

1.0

1.8

1.7

Brazil c

2.4

9.0

3.2

4.1

2.9

5.8

2.9

1.8

1.8

1.7

1.7

2.3

5.9

3.1

4.3

2.7

5.7

2.9

2.0

2.0

1.5

1.4

2004

Wages

1999
2002

2.1

6.5

2.9

4.3

2.4

5.6

3.2

1.5

1.4

1.4

1.3

3.1

11.1

3.1

…

3.1

5.6

2.9

2.0

0.9

2.2

1.9

2.8

11.1

3.0

4.9

2.3

5.7

2.8

d

1.8

1.1

1.7

1.4

1996

3.6

15.4

3.6

5.7

3.1

7.0

3.2

d

2.3

1.5

2.5

2.0

1999

3.2

12.4

3.3

5.4

2.6

5.0

2.4

d

1.8

1.4

2.0

1.6

2001

3.2

11.7

3.4

5.6

2.7

5.0

2.4

d

1.8

1.4

2.0

1.6

2003

3.0

10.2

3.1

5.2

2.5

5.4

2.8

d

2.0

1.3

1.8

1.3

2004

3.0

9.9

3.1

5.3

2.5

5.3

2.8

d

1.9

1.3

1.8

1.3

2005

3.1

10.3

3.1

5.3

2.5

5.6

2.8

d

2.0

1.3

1.8

1.3

2006
Chile e

1990
1993

3.2

11.3

3.3

5.8

2.6

5.3

2.9

d

2.1

1.4

1.9

1.4

1990

3.4

14.3

3.0

…

3.0

4.5

3.2

2.2

1.4

4.4

4.2

1994

4.7

26.4

3.8

…

3.8

6.5

3.5

2.6

2.0

5.8

3.8

1996

5.1

26.4

4.1

5.5

3.9

7.8

3.6

2.8

2.0

6.4

4.4

1998

24.9

4.7

…

4.7

8.8

3.8

2.7

2.2

6.8

5.0

5.2

18.1

4.7

6.3

4.3

9.4

3.6

2.8

2.4

5.6

3.9

2003

5.5

25.5

4.7

6.7

4.3

9.0

3.6

2.8

2.4

5.6

4.0

2006
Colombia f

5.6

2000

5.1

19.7

4.6

6.9

4.2

9.0

3.5

2.7

2.3

5.3

3.8

1991

2.2

5.9

2.3

3.5

2.1

3.9

2.1

…

1.2

1.6

1.4

1994

3.0

8.4

3.0

4.8

2.7

5.9

2.5

…

1.7

2.3

2.0
2.0

1997

2.9

8.4

3.0

5.0

2.6

5.2

2.4

…

1.6

2.3

1999

2.8

7.7

3.4

5.5

2.9

5.7

2.7

…

2.1

1.5

1.3

2002

2.5

6.1

3.3

6.0

2.8

5.7

2.8

…

1.7

1.1

0.9

2004

2.6

6.5

3.4

5.8

2.9

6.0

2.8

…

1.8

1.1

1.0

2005

2.7

6.3

3.5

6.1

3.1

5.8

3.1

…

1.9

1.2

1.0

Social Panorama of Latin America • 2007

381

Table 24.2 (continued)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE FEMALE POPULATION
BY OCCUPATIONAL CATEGORY, URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
non-technical

1990
1994
1997
1999
2002
2004
2005
2006

4.0
4.4
4.7
4.7
5.3
5.3
4.5
5.1

5.4
6.9
6.2
7.9
10.0
6.8
5.4
5.3

4.4
4.6
5.3
5.1
5.8
6.2
5.1
6.0

6.5
7.1
7.7
8.0
8.7
8.9
8.0
9.2

3.3
3.5
3.9
3.9
4.5
4.9
3.9
4.6

6.5
6.1
7.6
7.7
7.6
8.0
6.7
7.5

3.7
3.7
4.2
4.1
4.9
5.0
4.4
5.1

2.9
2.9
2.8
3.3
3.4
3.5
2.8
3.3

1.5
1.6
1.8
1.7
2.0
2.2
1.6
1.9

1.9
2.7
2.2
2.5
2.6
2.1
1.9
1.7

1.7
2.5
2.1
2.1
2.0
1.7
1.4
1.5

Ecuador

1990
1994
1997
1999
2002
2004
2005
2006

2.0
2.1
2.4
2.1
2.5
2.5
2.8
2.9

4.5
4.8
5.2
5.3
5.9
5.0
6.9
6.3

2.5
2.3
2.7
2.5
2.9
3.2
3.3
3.5

3.4
3.1
3.6
3.2
3.9
4.5
5.3
5.1

2.0
2.1
2.4
2.3
2.6
2.8
2.8
3.1

3.5
3.2
4.2
4.1
3.8
4.1
4.2
4.7

2.6
2.7
3.1
2.9
3.1
3.3
3.3
3.4

1.9
1.7
1.7
1.4
2.1
1.9
2.1
2.1

0.7
0.9
0.9
0.9
1.5
1.6
1.6
2.0

1.2
1.5
1.5
1.2
1.7
1.4
1.7
1.6

1.2
1.4
1.4
1.2
1.6
1.3
1.6
1.5

El Salvador

1995
1997
1999
2001
2004

2.5
3.1
3.5
3.2
3.0

5.8
8.1
8.8
6.8
5.1

3.0
4.0
4.2
4.0
3.5

4.9
6.0
6.9
6.6
6.3

2.5
3.6
3.5
3.3
2.8

5.7
6.6
6.8
7.0
4.6

2.5
3.1
3.5
3.2
2.9

1.5
2.0
2.1
2.1
2.0

0.9
1.8
2.0
1.9
2.0

1.6
1.8
2.0
2.0
2.1

1.6
1.7
2.0
2.0
2.1

Guatemala

1989
1998
2002

2.6
2.2
2.0

14.4
11.2
3.8

2.7
2.3
2.7

5.0
3.9
4.8

2.0
2.0
2.4

3.5
3.6
4.0

2.4
2.7
2.6

1.5
1.4
1.3

1.4
0.6
1.6

2.1
1.5
1.0

1.9
1.5
1.0

Honduras

1990
1994
1997
1999
2002
2003
2006

2.0
1.6
1.4
1.5
1.9
2.1
2.1

4.3
5.1
4.6
3.8
4.5
4.0
3.6

2.2
1.8
1.7
1.8
2.5
3.0
2.8

4.7
2.9
2.5
2.7
3.9
4.7
4.6

1.9
1.5
1.5
1.5
2.1
2.5
2.3

4.8
3.3
2.9
2.4
4.4
6.1
4.0

2.5
1.7
1.6
1.8
2.1
2.3
2.1

1.2
1.1
0.9
1.0
1.2
1.5
1.4

0.8
0.5
0.5
0.5
0.8
1.2
1.2

1.0
1.2
1.3
0.8
0.9
0.8
0.9

0.9
1.1
0.8
0.8
0.9
0.8
0.6

Mexico g

1989
1994
1996
1998
2000
2002
2004
2005
2006

2.8
2.9
2.5
2.7
2.8
2.9
2.9
3.0
3.0

9.4
11.6
11.8
13.2
13.4
14.1
10.7
10.0
9.8

2.9
3.0
2.7
2.8
3.0
3.0
3.0
3.1
3.1

…
4.2
4.2
4.4
4.8
4.7
…
…
…

2.9
2.6
2.2
2.3
2.5
2.5
3.0
3.1
3.1

4.8
5.3
4.1
4.5
4.0
5.2
5.2
5.3
5.3

2.8
2.5
2.3
2.5
2.7
2.7
3.0
2.9
3.1

…
…
1.4
1.5
1.6
1.7
1.8
1.8
1.8

1.3
1.1
1.1
1.1
1.1
1.3
1.3
1.5
1.3

2.3
2.0
1.4
1.7
1.6
1.8
2.1
2.2
2.1

2.3
1.8
1.3
1.6
1.5
1.7
1.9
1.9
1.8

Wages

Costa Rica

382

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 24.2 (continued)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE FEMALE POPULATION
BY OCCUPATIONAL CATEGORY, URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Nicaragua

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
non-technical

2.9

6.6

2.8

2.9

2.7

4.4

2.8

2.3

2.1

3.0

2.3

6.0

2.7

…

2.7

4.7

2.4

1.6

1.5

1.7

1.6

2001
Panama

1993
1998

2.6

2.5

14.8

2.7

3.3

2.4

3.4

3.1

1.9

1.4

1.7

1.6

1991

4.8

13.1

5.0

7.0

3.7

8.2

4.2

2.7

1.3

2.2

1.8

1994

4.3

11.8

4.4

6.2

3.3

7.3

3.8

2.4

1.2

2.7

2.6

1997

4.8

10.3

5.1

7.1

4.1

8.5

4.1

2.7

1.4

2.9

2.6
2.1

1999

5.3

8.9

5.8

7.7

5.0

10.1

4.9

2.9

2.0

2.3

2002

5.3

11.7

6.0

7.8

5.2

8.1

6.1

4.2

2.5

1.6

1.5

2004

4.7

6.9

5.4

7.5

4.5

7.9

5.5

3.1

1.6

1.6

1.3

2005

4.5

8.4

5.1

7.3

4.2

7.1

5.2

2.7

1.7

1.5

1.3

2006

4.6

7.1

5.2

7.3

4.4

6.8

5.5

2.5

1.5

1.9

1.4

1990

2.3

9.0

1.8

2.4

1.6

3.4

2.4

1.5

0.8

3.0

2.9

1994

2.6

8.6

2.3

3.4

2.0

4.3

2.5

1.8

1.2

2.3

2.3

1996

2.7

7.2

2.8

4.7

2.3

5.5

2.8

2.0

1.2

2.2

1.9

Wages

Paraguay
(Asunción)

1999

3.0

8.9

3.0

4.4

2.7

5.5

3.1

2.4

1.7

2.2

1.9

2001

2.8

9.1

2.9

5.1

2.4

3.4

3.4

2.1

1.5

4.7

1.3

2004

(Urban)

2.0

5.7

2.3

3.3

2.1

4.5

2.4

1.7

1.5

1.0

0.9

2005

2.1

4.8

2.4

3.7

2.1

3.4

2.7

1.7

1.5

1.0

0.9
2.0

1994

2.4

8.5

2.2

3.4

1.9

4.2

2.4

1.7

1.2

2.0

1996

2.4

7.5

2.6

4.6

2.0

5.3

2.7

2.0

1.1

1.9

1.7

1999

2.7

9.3

2.8

4.3

2.5

5.6

3.0

2.2

1.6

1.8

1.6

2001

8.2

2.8

4.8

2.2

3.4

3.3

1.9

1.4

1.3

1.2

1.9

6.1

1.9

3.2

1.7

4.1

2.4

1.6

1.3

1.1

1.0

2005
Peru

2.4

2004

1.9

5.0

2.3

3.5

1.9

3.3

2.7

1.7

1.3

1.0

0.9

1997

2.3

5.1

3.0

3.5

2.9

5.0

2.8

1.6

2.3

1.4

1.3

1999

2.4

3.4

3.4

3.5

3.3

6.7

3.3

1.7

2.9

1.3

1.2

2001

2.1

5.0

2.7

3.3

2.5

4.4

2.8

1.5

2.0

1.4

1.4

2003

1.9

4.1

2.6

3.3

2.4

3.6

2.8

1.6

1.9

1.1

1.1
2.9

Dominican

1997

3.6

7.7

3.7

4.7

3.4

7.0

3.5

2.0

1.4

3.3

Republic

2000

3.6

14.4

3.3

4.6

2.9

6.1

2.7

2.1

1.1

3.5

2.9

2002

3.7

13.9

3.5

4.4

3.2

6.0

3.2

2.2

1.1

3.2

2.9
3.0

2004

2.8

13.1

2.0

2.5

1.9

3.6

1.9

1.1

0.8

3.4

2005

2.6

5.3

2.7

3.3

2.5

5.2

2.4

1.3

1.2

1.9

1.6

2006

2.6

7.0

2.7

3.6

2.4

3.9

2.7

1.3

1.3

1.9

1.7

Social Panorama of Latin America • 2007

383

Table 24.2 (concluded)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE FEMALE POPULATION
BY OCCUPATIONAL CATEGORY, URBAN AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total Employers

Wage or salary earners

Total

Uruguay

Public
sector

Own-account
and unpaid
family workers
Total b

Private sector
Total a

Professional
and technical

Non-professional, non-technical
Establishments Establishments Domestic
employing more employing up to employment
than 5 persons
5 persons

Nonprofessional,
non-technical

1990

2.7

6.9

2.7

3.4

2.5

4.8

2.8

1.9

1.5

2.1

1.8

1994

3.4

9.9

3.4

4.4

3.1

6.4

3.4

2.5

1.7

2.7

2.2

1997

3.7

8.3

3.8

5.0

3.4

6.7

3.8

2.6

1.8

2.9

2.3

1999

4.1

11.5

4.2

5.6

3.8

8.0

4.0

2.8

2.1

3.1

2.4

2002

9.2

3.6

5.1

3.1

6.2

3.7

2.2

1.9

2.5

1.8

2.9

7.4

3.0

4.6

2.5

4.9

2.9

1.7

1.6

2.1

1.6

2005

3.0

6.7

3.1

4.9

2.6

5.3

3.1

1.7

1.6

2.1

1.5
2.7

1990

3.3

10.8

3.2

3.6

2.9

4.9

3.3

2.4

1.7

2.9

(Bol. Rep. of) h 1994

3.0

7.5

2.8

2.3

3.2

5.6

3.3

2.0

1.5

3.1

2.6

1997

2.8

9.4

2.4

2.6

2.2

4.5

2.2

1.6

1.2

3.4

3.0

1999

2.9

7.9

3.0

3.3

2.8

5.4

2.6

1.9

1.3

2.5

2.3

2002

2.8

8.6

3.0

4.3

2.2

4.0

2.3

1.6

1.2

2.3

2.2

2004

2.7

8.0

2.8

3.9

2.1

3.4

2.3

1.5

1.2

2.2

2.1

2005

3.3

9.6

2.6

4.5

2.6

4.1

2.7

1.8

1.4

2.8

2.7

2006

3.5

9.1

3.9

5.1

3.0

4.7

3.0

2.1

1.7

2.5

2.4

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a

b
c

d
e
f

g
h

For Argentina (except 1999), Brazil (1990), Chile (1990, 1994 and 1998), Mexico (1989 and 2004) and Nicaragua (1998), this includes public-sector
wage or salary earners. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic, El Salvador, Panama (up to
2002) and Uruguay (1990), in the case of non-professional, non-technical workers, this includes establishments employing up to 4 persons. Where no
information was available on the size of the establishments, no figures are given for the population employed in low-productivity sectors.
Includes own-account professional and technical workers.
Brazil’s National Household Survey (PNAD) does not provide information on the size of business establishments, except in 1993, 1996 and 1999.
Therefore, the figure given for Brazil in the column for establishments employing more than five persons includes wage earners who have an employment
contract (“carteira”), while the column for establishments employing up to five persons includes workers who do not have such contracts.
Includes private-sector employees engaged in non-professional, non-technical occupations in business establishments of undeclared size.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Information from national household income and expenditure surveys (ENIGH).
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Wages

Venezuela

3.5

2004

384

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 25
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION
BY OCCUPATIONAL CATEGORY, RURAL AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Employers

Wage or salary earners
Total a

Own-account and
unpaid family workers
Total b

Public
sector

Total

Private sector
Agriculture

Agriculture

Other

1997
1999
2000
2002
2004

1.3
0.8
1.2
1.2
1.1

10.5
3.9
5.9
4.1
3.3

3.5
3.4
3.2
3.4
2.3

3.7
4.2
3.6
4.2
3.7

3.4
3.1
3.0
3.2
1.8

3.1
2.9
2.7
3.1
1.5

3.6
3.2
3.2
3.4
2.0

0.8
0.6
1.0
0.8
0.7

0.6
0.4
0.8
0.6
0.5

Brazil

1990
1993
1996
1999
2001
2003
2004
2005
2006

2.0
1.8
2.0
1.8
1.7
1.7
1.8
1.7
1.8

9.3
11.6
13.5
12.4
10.6
12.7
10.7
10.1
11.0

2.2
2.2
2.8
2.6
2.3
2.3
2.4
2.4
2.6

…
2.9
4.0
3.8
2.8
3.3
3.5
3.5
3.8

2.2
2.1
2.6
2.4
2.2
2.2
2.2
2.3
2.4

1.4
1.7
2.0
2.1
2.1
2.0
2.1
2.1
2.2

2.9
3.4
3.8
2.8
2.4
2.5
2.4
2.5
2.7

1.5
1.3
1.3
1.0
1.0
1.0
1.1
1.0
1.1

1.3
1.2
1.1
0.8
0.9
0.9
1.0
0.9
0.9

Chile c

1990
1994
1996
1998
2000
2003
2006

4.9
4.6
4.2
5.3
5.3
5.7
6.0

39.3
28.9
24.0
32.8
36.8
33.6
38.9

3.2
3.8
3.5
3.9
4.2
4.5
4.9

…
…
5.3
…
7.0
7.9
8.4

3.2
3.8
3.4
3.9
3.9
4.3
4.7

2.8
3.1
2.9
3.2
3.5
3.6
4.0

4.3
5.1
4.3
4.9
4.5
5.5
5.8

5.2
4.2
4.0
6.3
5.6
6.3
5.9

5.2
3.7
3.5
5.3
4.8
5.3
4.2

Colombia d

1991
1994
1997
1999
2002
2004
2005

3.1
2.5
2.7
2.9
2.9
2.6
2.8

10.7
5.8
7.0
5.6
7.9
6.6
6.6

2.9
2.8
3.1
3.9
3.8
3.3
3.5

…
…
5.0
6.4
7.6
6.0
6.9

2.9
2.8
3.0
3.7
3.4
3.2
3.3

3.1
2.9
3.2
3.5
3.8
3.5
3.5

2.6
2.6
3.0
3.9
2.9
2.6
2.8

2.3
1.9
1.8
1.8
1.8
3.1
2.0

1.7
2.3
1.8
1.9
1.9
2.3
2.5

Costa Rica

1990
1994
1997
1999
2000
2002
2004
2005
2006

5.1
5.8
5.6
6.3
6.1
6.2
6.3
5.7
6.4

9.9
11.7
9.3
11.3
8.5
9.0
7.7
7.4
8.1

5.2
5.4
5.5
6.0
6.8
7.2
7.5
6.5
7.2

8.4
8.4
9.4
10.2
10.5
11.9
12.6
10.0
11.5

4.6
4.9
4.9
5.4
6.2
6.5
6.7
5.9
6.5

4.1
4.8
4.3
4.5
6.1
7.1
7.4
6.5
7.2

4.9
5.0
5.2
5.8
6.2
6.2
6.3
5.6
6.1

4.0
5.4
4.7
5.3
3.9
3.2
3.1
3.1
3.5

3.9
6.3
4.9
5.5
2.9
2.2
2.1
2.4
2.4

Ecuador

2000
2004
2005
2006

2.5
2.1
2.4
2.4

8.4
5.6
5.5
7.1

2.7
3.0
3.1
3.4

4.6
5.6
6.2
6.8

2.5
2.7
2.9
3.2

2.2
2.3
2.4
2.6

2.9
3.4
3.6
4.0

2.0
1.2
1.6
1.5

1.8
1.0
1.4
1.3

El Salvador

1995
1997
1999
2000
2001
2004

2.4
2.4
3.4
3.5
2.4
2.7

5.5
4.3
10.2
9.3
3.8
7.6

2.7
3.1
3.3
3.5
3.3
3.2

5.4
5.7
6.8
7.3
6.8
6.6

2.6
2.9
3.0
3.2
3.0
3.0

2.0
2.2
2.2
2.2
2.0
2.0

3.2
3.6
3.7
3.9
3.7
3.6

1.7
1.5
2.8
2.9
1.4
1.6

1.4
1.1
3.1
3.1
0.5
0.6

Guatemala

1989
1998
2002

2.5
2.6
1.7

21.1
25.3
5.7

2.3
2.3
2.3

4.9
3.9
4.4

2.1
2.2
2.2

1.8
2.0
1.8

2.7
2.5
2.6

2.4
2.1
1.0

2.1
2.1
0.8

Wages

Bolivia

Social Panorama of Latin America • 2007

385

Table 25 (concluded)
AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION
BY OCCUPATIONAL CATEGORY, RURAL AREAS, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Employers

Wage or salary earners

Total a

Public
sector

Own-account and
unpaid family workers
Total b

Private sector

Agriculture

Agriculture

Other

1990
1994
1997
1999
2002
2003
2006

1.7
2.0
1.7
1.8
1.4
1.2
1.3

14.7
8.6
9.0
6.1
6.3
3.6
3.5

2.2
2.1
1.6
2.0
1.9
1.8
2.1

4.9
4.1
3.4
4.4
4.7
5.3
5.4

1.8
1.8
1.4
1.7
1.7
1.6
1.9

1.4
1.6
1.3
1.4
0.9
0.8
0.9

2.7
2.1
1.7
2.0
2.9
2.8
3.1

1.3
1.8
1.4
1.4
1.1
0.9
0.8

1.3
1.8
1.5
1.4
1.0
0.8
0.6

Mexico e

1989
1994
1996
1998
2000
2002
2004
2005
2006

3.0
2.7
2.3
2.6
3.2
3.0
3.3
3.1
3.2

9.3
9.7
7.1
8.7
14.9
10.1
9.2
9.0
11.9

2.7
2.6
2.4
2.9
2.9
3.2
3.4
3.2
3.3

…
5.1
4.9
5.2
5.8
5.8
…
…
…

2.7
2.3
2.0
2.5
2.5
2.7
3.4
3.2
3.3

1.8
1.7
1.5
1.8
1.8
1.8
1.9
1.9
2.1

3.5
2.7
2.3
2.9
3.0
3.2
4.0
3.7
3.7

3.0
2.2
1.6
1.8
2.3
2.2
2.6
2.4
2.1

2.6
1.8
1.3
1.6
1.5
1.5
1.7
1.6
1.5

Nicaragua

1993
1998
2001

2.2
2.1
1.9

4.8
8.8
4.6

2.7
2.8
2.6

3.0
…
3.3

2.6
2.8
2.5

2.1
2.1
2.0

3.2
3.5
3.2

1.9
1.1
1.1

1.4
0.8
0.8

Panama

1991
1994
1997
1999
2002
2004
2005
2006

3.6
3.5
4.0
4.2
4.5
3.4
3.1
3.2

9.2
13.6
15.4
13.5
12.8
11.0
7.7
11.0

5.1
4.1
4.4
5.2
8.1
5.4
5.2
5.2

7.4
6.3
6.9
9.1
8.8
8.8
8.4
8.2

4.2
3.5
3.7
4.2
7.9
4.5
4.4
4.5

4.4
3.2
3.1
3.2
9.4
5.0
4.9
4.9

4.1
3.7
4.0
4.8
6.7
4.1
4.1
4.2

2.0
2.4
3.1
2.8
1.8
1.6
1.5
1.4

1.5
1.6
2.3
2.2
1.5
1.2
1.2
1.2

Paraguay

1999
2001
2004
2005

2.2
1.8
1.9
1.9

17.2
9.4
12.2
5.9

2.9
2.8
2.5
2.7

5.3
5.3
3.3
3.9

2.5
2.6
2.4
2.4

1.8
1.9
2.4
2.4

2.7
3.0
2.4
2.4

1.3
1.0
1.3
1.5

1.1
0.8
1.3
1.4

Peru

1997
1999
2001
2003

1.6
1.4
1.2
1.0

4.3
3.3
2.8
2.0

2.8
2.2
2.4
2.3

3.8
3.8
3.8
3.1

2.5
1.9
2.0
2.0

2.1
1.9
1.8
1.8

3.3
3.3
2.4
2.4

1.0
0.9
0.8
0.7

0.9
0.8
0.6
0.6

Dominican
Republic

1997
2000
2002
2004
2005
2006

4.3
3.7
3.5
3.0
2.6
2.6

6.6
13.0
13.3
8.6
7.7
6.0

4.3
3.0
2.9
2.0
2.6
2.7

6.2
4.0
3.5
2.2
3.1
3.1

3.8
2.7
2.7
1.9
2.5
2.6

3.2
2.2
2.2
1.5
1.9
2.3

4.0
2.9
2.8
2.0
2.6
2.7

4.2
3.8
3.6
3.5
2.4
2.4

3.4
3.3
3.3
1.9
1.7
1.6

Venezuela
(Bol. Rep. of)

1990
1994

3.8
3.4

9.5
7.2

3.3
2.9

4.3
4.3

3.1
2.6

2.6
2.1

3.9
3.1

3.5
3.4

2.9
3.2

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted In the relevant countries.
a

Includes domestic employees. For Brazil (1990), Chile (1990, 1994 and 1998), Colombia (1991 and 1994) Mexico (1989 and 2004) and Nicaragua
(1998), includes public-sector wage earners.
b Includes wages earners in all branches of activity. Information from national socio-economic surveys (CASEN).
d As a result of a changeover to a new survey sample design in 2001, the figures for rural areas are not strictly comparable with those of previous years.
e Information from national household income and expenditure surveys (ENIGH).

Wages

Total

Honduras

386

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 26
RATIO OF AVERAGE FEMALE INCOME TO AVERAGE MALE INCOME, BY AGE GROUP, URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Wage disparity by age group b

Disparity in labour income
by age group a
Total

15- 24
years

25 - 34
years

35 - 44
years

45 - 54
years

55 and
over

Total

15 - 24
years

25 - 34
years

35 - 44
years

45 - 54
years

55 and
over

1990
1994
1997
1999
2002
2004
2005
2006

65
71
70
65
59
61
67
65

87
87
95
94
89
86
86
78

77
88
83
76
73
69
75
76

61
64
66
64
60
62
80
62

59
72
67
58
54
57
58
62

51
50
49
54
43
48
47
52

76
76
79
79
71
68
69
70

94
94
98
95
82
86
87
78

82
80
92
84
79
72
80
80

72
69
77
69
71
66
62
63

72
73
63
78
61
67
63
59

54
61
66
73
54
50
50
64

Bolivia

1989
1994
1997
1999
2002
2004

59
54
60
63
61
63

71
61
60
72
80
70

65
61
67
70
68
70

54
58
72
55
56
53

54
44
47
67
53
62

62
40
40
54
44
57

60
61
69
72
77
90

74
60
65
81
83
83

68
71
74
85
90
97

60
68
85
63
69
69

54
56
64
72
66
102

44
40
39
63
43
101

Brazil

1990
1993
1996
1999
2001
2003
2004
2005
2006

56
56
62
64
66
66
66
67
67

73
74
77
80
84
86
83
85
82

64
66
67
71
74
76
73
74
75

54
53
62
62
64
63
64
65
67

47
43
51
57
59
58
58
61
61

35
48
54
54
52
51
55
55
52

65
61
68
70
86
87
86
87
86

77
77
80
83
100
100
97
99
96

71
68
72
75
91
92
89
88
90

63
56
65
66
81
79
83
84
85

57
46
56
58
79
78
76
80
81

52
54
60
59
79
80
83
76
75

Chile

1990
1994
1996
1998
2000
2003
2006

61
67
67
66
61
64
70

81
81
86
90
87
90
88

67
84
82
77
79
79
81

60
71
60
69
59
65
67

56
56
64
59
50
55
64

52
54
57
54
56
55
63

66
70
73
74
72
83
86

86
84
93
93
91
99
93

72
78
82
83
82
92
93

63
67
67
69
68
82
79

54
64
62
67
64
74
84

61
56
67
69
67
92
100

Colombia c

1991
1994
1997
1999
2002
2004
2005

68
68
79
75
77
76
75

88
97
90
101
99
96
93

77
80
95
86
83
88
87

64
69
83
69
73
72
73

56
52
60
68
73
70
70

55
48
58
55
58
53
53

77
83
77
83
99
95
95

87
104
92
101
108
106
104

79
90
85
94
101
101
100

73
82
73
76
90
88
91

75
67
64
75
97
92
91

74
57
60
66
104
85
90

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

72
69
78
70
75
76
73
75

86
82
99
87
86
96
86
91

75
76
79
75
78
75
83
84

66
64
73
67
69
72
68
65

60
60
74
64
68
76
71
75

61
55
51
59
70
55
48
61

74
75
87
78
85
88
89
92

87
84
102
89
98
102
99
98

78
79
87
79
85
85
98
99

66
70
79
75
79
81
82
82

62
65
87
72
86
95
84
91

81
77
55
70
95
65
69
98

Wages

Argentina
(Greater Buenos
Aires)

Social Panorama of Latin America • 2007

387

Table 26 (continued)
RATIO OF AVERAGE FEMALE INCOME TO AVERAGE MALE INCOME, BY AGE GROUP, URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Wage disparity by age group b

Disparity in labour income
by age group a
Total

15- 24
years

25 - 34
years

35 - 44
years

45 - 54
years

55 and
over

Total

15 - 24
years

25 - 34
years

35 - 44
years

45 - 54
years

55 and
over

1990
1994
1997
1999
2002
2004
2005
2006

66
67
75
67
67
68
74
73

80
77
90
99
83
101
93
105

70
73
84
82
77
74
83
78

61
65
70
61
66
63
70
65

60
57
64
51
55
59
62
70

64
58
67
55
50
63
67
61

67
76
83
83
87
89
102
95

78
81
94
99
95
107
99
111

73
82
90
93
96
91
99
97

63
76
77
78
89
85
79
85

63
65
75
69
69
80
90
93

60
72
62
52
70
94
94
93

El Salvador

1995
1997
1999
2001
2004

63
72
75
73
77

76
97
84
87
80

70
74
79
79
78

58
69
71
73
78

52
64
67
62
76

47
53
60
51
52

79
88
88
100
98

80
100
87
95
85

81
85
93
100
96

72
85
84
92
99

85
91
86
104
112

61
73
70
100
81

Guatemala

1998
2002

55
58

87
78

74
62

51
54

34
42

39
45

70
80

85
88

73
81

67
79

71
65

48
73

Honduras

1990
1994
1997
1999
2002
2003
2006

59
63
60
65
76
83
81

77
80
81
78
86
98
94

68
72
72
65
78
81
85

51
69
58
68
70
77
77

56
47
47
51
71
89
76

43
43
37
52
63
64
69

78
73
77
78
95
107
101

81
82
86
80
102
110
107

80
80
78
76
90
98
98

70
82
74
82
86
101
96

89
67
70
69
98
111
103

103
32
72
86
103
117
120

Mexico

1989
1994
1996
1998
2000
2002
2004
2005
2006

55
57
59
57
58
63
63
58
63

71
83
83
84
79
83
89
83
83

63
65
61
71
76
67
72
70
69

52
57
62
51
53
63
61
55
59

46
45
45
54
42
59
59
50
58

48
46
52
40
58
43
42
47
54

73
68
73
72
72
76
78
76
76

86
91
90
89
83
87
92
88
90

78
74
73
79
92
78
84
80
82

69
78
66
68
65
74
71
69
69

59
49
72
63
83
72
84
78
70

82
49
84
72
82
64
56
69
77

Nicaragua

1993
1998
2001

77
65
69

107
92
87

87
73
85

62
60
72

64
47
34

67
43
85

77
77
82

90
103
94

88
77
91

54
73
74

64
56
66

95
47
67

Panama

1991
1994
1997
1999
2002
2004
2005
2006

78
69
70
78
76
78
79
78

73
80
81
98
76
89
96
84

89
76
78
87
86
92
89
85

81
71
68
74
77
72
72
78

68
56
68
73
70
79
81
76

78
58
46
57
57
50
60
60

89
84
85
89
85
94
93
95

95
107
104
120
83
109
108
100

95
95
92
92
92
107
103
97

90
77
80
81
80
85
84
91

75
68
79
83
79
87
91
92

77
62
64
75
83
71
72
90

Wages

Ecuador

388

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 26 (concluded)
RATIO OF AVERAGE FEMALE INCOME TO AVERAGE MALE INCOME, BY AGE GROUP, URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Wage disparity by age group b

Disparity in labour income
by age group a
Total

15 - 24
years

25 - 34
years

35 - 44
years

45 - 54
years

55 and
over

Total

15 - 24
years

25 - 34
years

35 - 44
years

45 - 54
years

55 and
over

Paraguay

1990

55

63

68

52

50

60

63

66

72

58

63

77

(Asunción)

1994

60

73

71

58

68

33

64

77

71

58

70

47

1996

64

76

66

71

48

56

76

76

74

82

72

93

1999

71

96

84

67

69

44

79

102

92

70

62

69

2001

86

76

70

55

71

95

102

104

101

81

44

65

102

65

64

53

57

101

106

88

113

111

99

2005
Peru

70

2004

58

90

81

70

33

39

93

101

100

87

86

60

1997

60

80

67

58

49

41

73

89

79

79

67

48

1999

63

95

83

63

47

32

78

99

94

86

61

40

2001

67

91

75

59

59

56

80

92

90

74

63

72

2003

61

93

76

65

41

33

78

92

91

87

46

52

Dominican

1997

75

95

77

76

51

69

90

97

87

90

84

67

Republic

2000

69

84

76

67

58

53

84

106

90

71

85

52

2002

68

87

70

66

60

59

89

101

84

93

71

111

2004

59

62

59

63

45

77

85

96

79

78

81

122

2005

88

75

64

59

93

98

106

82

85

82

82

72

75

67

61

84

91

75

92

87

72

1990

Wages

91

72
45

63

60

46

37

30

64

79

73

61

59

49

1994

Uruguay

77

2006

61

76

65

58

56

51

63

76

66

59

60

51

1997

65

79

72

63

59

55

67

79

71

64

60

55

1999

67

79

77

63

65

55

68

79

75

61

66

53

2002

68

69

61

71

85

78

67

64

62

80

63

66

58

70

84

77

64

67

58

71

85

79

70

68

59

74

83

80

69

68

67

66

80

72

64

57

48

79

86

82

74

68

66

1994

70

96

77

64

56

57

83

106

84

75

67

69

1997

d

79

88

1990

Venezuela

87

69

2005

(Bol. Rep. of)

72

2004

69

84

77

62

60

55

83

92

87

77

73

65

1999

74

92

76

71

65

57

91

99

91

85

79

91

2002

76

86

80

74

70

58

99

96

97

97

94

90
100

2004

77

90

78

74

71

66

96

97

92

95

89

2005

76

88

78

78

71

56

98

97

95

99

91

90

2006

79

86

84

74

73

68

95

95

96

87

93

100

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Refers to the income differential in the total employed population. This differential is calculated as the quotient of average female income and average
male income, multiplied by 100.
Refers to total income differentials between wage earners. This differential is calculated as the quotient of average female income and average male
income, multiplied by 100.
c In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.
b

Social Panorama of Latin America • 2007

389

Table 27
RATIO OF AVERAGE FEMALE INCOME TO AVERAGE MALE INCOME,
BY YEARS OF SCHOOLING, URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Differential in labour income
Years of schooling a
Total

Argentina c
(Geater Buenos
Aires)

0-3

4-6

7-9

10 - 12

Wage differential
Years of schooling b
13 and
over

Total

0-3

4-6

7-9

10 - 12

13 and
over

65

...

66

...

63

51

76

...

73

...

68

62

71

...

62

65

65

63

76

...

...

...

...

...

1997
1999
2002
2004
2005
2006

70
65
59
61
67
65

73
64
62
52
44
63

66
82
81
52
39
49

67
58
55
48
53
48

69
63
61
60
55
57

55
51
46
56
66
63

79
79
71
68
69
70

60
63
76
51
42
49

57
72
68
53
43
51

69
58
55
50
55
50

76
77
67
69
65
67

64
66
60
65
65
69

Bolivia

1989
1994
1997
1999
2002
2004

59
54
60
63
61
63

62
60
59
63
61
61

67
58
66
64
67
73

76
67
53
66
75
62

77
65
75
71
66
69

46
54
57
66
60
64

60
61
69
72
77
90

40
44
61
55
39
53

49
48
46
59
83
69

69
56
48
42
95
67

85
70
79
82
74
78

49
60
60
65
60
67

Brazil

1990
1993
1996
1999
2001
2003
2004
2005
2006

56
56
62
64
66
66
66
67
67

46
49
57
58
58
59
61
61
63

46
46
52
51
54
54
53
55
55

50
49
53
55
55
55
57
57
58

49
51
53
55
56
57
57
60
59

49
46
53
56
54
55
56
56
57

65
61
68
70
86
87
86
87
86

56
56
65
65
76
78
79
79
81

51
51
57
58
71
71
70
71
73

57
56
57
59
70
70
71
71
72

53
55
57
60
64
67
67
67
68

52
45
56
57
57
57
59
60
60

Chile

1990
1994
1996
1998
2000
2003
2006

61
67
67
66
61
64
70

56
93
83
71
75
68
71

58
70
65
63
71
68
73

69
69
70
65
68
64
65

62
69
70
71
68
69
67

49
54
53
54
48
53
62

66
70
73
74
72
83
86

64
83
74
72
82
77
79

49
68
68
64
73
80
76

66
66
74
71
73
73
76

69
72
73
75
74
81
76

55
58
60
63
60
64
71

Colombia d

1991
1994
1997
1999
2002
2004
2005

68
68
79
75
77
76
75

57
59
69
66
61
51
57

60
68
65
71
68
56
63

70
65
108
75
70
67
66

72
71
88
73
72
72
71

64
57
61
70
73
73
71

77
83
77
83
99
95
95

71
80
74
79
83
75
80

70
81
74
86
88
85
85

78
83
71
84
87
83
86

78
86
78
81
84
86
84

68
66
67
74
79
77
77

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

72
69
78
70
75
76
73
75

53
61
61
49
62
62
53
54

62
55
58
62
56
57
54
58

65
58
61
57
60
68
62
63

73
64
77
65
72
72
67
66

67
70
75
68
72
70
70
70

74
75
87
78
85
88
89
92

58
61
66
59
74
83
74
75

66
63
67
68
71
73
75
81

67
68
70
66
74
78
79
73

76
67
83
73
79
80
77
76

66
75
77
71
69
68
71
73

Wages

1990
1994

390

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 27 (continued)
RATIO OF AVERAGE FEMALE INCOME TO AVERAGE MALE INCOME,
BY YEARS OF SCHOOLING, URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Differential in labour income
Years of schooling a

Wage differential
Years of schooling b

Total

0-3

4-6

7-9

10 - 12

13 and
over

Total

0-3

4-6

7-9

10 - 12

13 and
over

1990
1994
1997
1999
2002
2004
2005
2006

66
67
75
67
67
68
74
73

49
60
57
63
73
67
79
78

57
61
60
62
69
62
64
72

68
70
61
62
66
68
70
74

79
72
87
71
70
75
76
71

57
59
70
60
57
57
65
62

67
76
83
83
87
89
94
95

42
56
64
55
96
92
76
87

47
59
61
60
90
78
77
80

70
68
63
68
78
83
83
80

77
83
92
87
80
85
84
88

56
66
72
71
64
61
70
69

El Salvador

1995
1997
1999
2001
2004

63
72
75
73
77

61
77
73
80
83

56
67
75
69
79

63
76
78
69
77

69
80
80
82
73

65
66
71
69
77

79
88
88
100
98

59
80
79
82
93

56
73
79
78
79

67
85
81
81
76

83
92
88
92
82

72
71
73
78
83

Guatemala

1998
2002

55
58

61
57

52
61

59
65

56
62

53
58

70
80

56
82

58
71

66
81

71
71

61
68

Honduras

1990
1994
1997
1999
2002
2003
2006

59
63
60
65
76
83
81

47
60
52
60
66
71
72

50
65
56
62
69
71
69

58
66
58
59
67
72
73

69
67
66
66
77
86
83

54
56
54
66
65
79
71

78
73
77
78
95
107
101

55
57
60
67
87
97
106

55
70
69
68
84
87
84

66
80
76
60
81
88
86

82
74
76
76
83
92
88

63
63
59
74
64
78
75

1989
1994
1996
1998
2000
2002
2004
2005
2006

55
57
59
57
58
63
63
58
63

61
...
56
72
67
57
59
59
48

50
58
67
56
59
59
59
60
59

70
65
71
65
55
61
69
64
68

62
70
63
63
72
64
74
69
72

46
48
49
47
49
62
52
47
56

73
68
73
72
72
76
78
76
76

71
...
67
61
67
63
66
70
61

68
59
69
65
61
70
67
66
69

83
78
81
75
63
68
80
70
74

78
76
76
78
84
79
81
81
82

63
56
63
56
60
70
64
64
66

Nicaragua

1993
1998
2001

77
65
69

95
68
85

73
80
76

71
67
60

91
52
80

58
53
52

77
77
82

86
72
76

76
75
82

72
64
66

77
57
75

65
67
62

Panama

1991
1994
1997
1999
2002
2004
2005
2006

78
69
70
78
76
78
79
78

47
54
52
61
65
46
61
49

55
51
48
56
48
50
57
46

69
58
60
63
55
57
58
55

82
68
68
75
80
71
74
75

69
62
62
71
67
67
70
68

89
84
85
89
85
94
93
95

60
92
73
80
64
76
62
81

72
73
77
75
52
68
73
65

82
80
78
75
67
73
76
76

86
83
80
81
83
88
88
85

73
63
64
71
68
69
70
72

Wages

Ecuador

Mexico

e

Social Panorama of Latin America • 2007

391

Table 27 (concluded)
RATIO OF AVERAGE FEMALE INCOME TO AVERAGE MALE INCOME,
BY YEARS OF SCHOOLING, URBAN AREAS, 1990-2006
(Percentages)
Country

Year

Differential in labour income
Years of schooling a
Total

0-3

4-6

7-9

10 - 12

Wage differential
Years of schooling b
13 and
over

Total

0-3

4-6

7-9

10 - 12

13 and
over

Paraguay

1990

55

69

55

60

65

42

63

51

50

58

72

58

(Asunción)

1994

60

64

59

66

67

52

64

64

59

66

75

51

1996

64

69

62

55

67

58

76

56

61

60

81

70

1999

71

62

76

62

74

63

79

72

75

61

86

67

2001

59

63

78

74

69

95

59

66

97

97

68

65

50

61

71

75

53

101

120

84

91

94

75

2005
Peru

70

2004

58

60

68

68

46

59

93

103

81

104

75

66

1997

60

69

66

61

71

53

73

79

69

62

80

65

1999

63

65

65

…

67

62

78

78

80

…

69

72

2001

67

80

82

72

71

63

80

52

75

74

75

67

2003

61

63

68

72

65

56

78

73

66

59

72

65

Dominican

1997

75

57

60

60

75

66

90

67

71

67

95

75

Republic

2000

69

56

53

65

61

60

84

77

74

76

70

65

2002

68

53

54

60

66

62

89

79

64

73

82

78

2004

59

41

54

55

54

51

85

64

67

75

64

68

2005

60

54

60

66

75

93

71

64

73

71

82

72

59

54

62

62

62

84

79

65

64

74

64

1990

45

50

41

40

42

37

64

52

57

63

59

57

1994

61

59

55

55

56

50

63

57

54

59

59

51

1997

65

54

57

60

58

56

67

51

57

62

62

57

1999

67

61

58

61

62

56

68

54

56

63

65

58

2002

62

66

60

71

61

60

62

68

61

64

59

64

57

70

53

60

59

69

60

71

66

61

61

63

62

74

55

58

61

68

67

66

62

58

68

61

62

79

73

68

77

78

71

1994

70

68

62

70

63

67

84

83

75

90

71

76

1997

f

65

63

1990

Venezuela

76

69

2005

(Bol. Rep. of)

72

2004

69

71

61

64

60

63

83

74

73

71

75

70

1999

74

71

65

66

63

66

91

83

73

75

77

74

2002

76

67

67

65

70

69

99

84

80

80

79

85

2004

77

72

69

67

69

70

96

81

83

80

83

81

2005

76

74

65

68

65

73

98

75

78

82

80

88

2006

79

63

66

68

69

75

95

72

78

79

81

84

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a
b
c
d

e
f

Refers to the income differential in the total employed population. This differential is calculated as the quotient of average female income and average
male income multiplied by 100.
Refers to total income differentials between wage earners. This differential is calculated as the quotient of average female income and average male
income multiplied by 100.
The levels of schooling in Argentina are 0 – 6; 7 – 9; 10 and over.
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Except in 1990, the levels of schooling in Mexico are 0 – 5; 6 – 9; 10 – 12; and 13 and over.
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Wages

Uruguay

77

2006

392

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 28
AVERAGE INCOME OF THE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY
SECTORS OF THE LABOUR MARKET, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Microenterprises
Employers

a

Unskilled self-employed
workers b

Wage or salary earners
Total

Professional
Nonand technical professional
non-technical

Total c

Domestic
employment

Manufacturing Commerce
and
and
construction
services

1990
1994
1997
1999
2002
2004
2005
2006

6.6
8.3
6.5
5.7
4.0
4.4
4.9
5.2

18.4
24.8
23.1
19.7
15.1
16.0
17.5
19.4

3.7
5.0
3.9
3.8
2.4
3.0
3.0
3.5

7.6
7.7
6.0
6.1
6.4
4.2
5.0
4.5

3.6
4.7
3.7
3.5
2.1
2.9
3.1
3.4

7.2
9.1
6.5
8.1
4.1
5.2
5.8
6.2

7.0
8.8
6.6
5.7
3.7
4.4
5.5
5.8

7.4
9.2
6.4
6.2
4.4
5.6
5.9
6.4

2.5
3.3
2.6
2.4
1.7
1.7
1.8
1.7

Bolivia

1989
1994
1997
1999
2002
2004

3.6
2.7
2.6
2.5
2.2
2.0

11.8
8.1
7.1
7.1
5.4
5.8

2.8
2.4
2.5
2.6
2.4
2.1

4.5
3.6
5.7
5.0
3.3
4.5

2.6
2.0
2.2
2.4
2.4
1.9

3.9
2.2
2.2
2.2
1.8
1.6

3.3
2.0
2.1
1.9
1.6
1.9

4.0
2.3
2.6
2.4
2.1
1.7

1.6
1.0
1.1
1.8
2.0
1.4

Brazil d

1990
1993
1996
1999
2001
2003
2004
2005
2006

4.1
2.6
3.4
3.0
2.8
2.4
2.4
2.4
2.6

…
11.3
14.0
10.3
10.6
9.5
9.4
8.8
9.5

3.6
2.2
2.7
2.4
2.4
2.1
2.0
2.2
2.3

7.6
5.1
5.9
3.6
3.6
3.7
3.8
3.8
4.0

2.6
2.0
2.5
2.1
2.1
2.0
2.0
2.1
2.2

3.4
2.7
3.7
2.8
2.8
2.3
2.3
2.1
2.2

3.3
2.6
3.5
2.7
2.6
2.4
2.2
2.2
2.3

3.6
3.4
4.5
3.5
3.4
2.7
2.8
2.6
2.7

1.0
1.1
1.5
1.4
1.4
1.3
1.3
1.4
1.4

Chile e

1990
1994
1996
1998
2000
2003
2006

3.8
4.3
5.6
5.9
5.3
5.8
5.5

18.8
17.4
22.3
24.0
21.8
24.2
19.4

2.6
3.2
3.4
3.4
3.6
3.3
3.4

4.8
6.8
7.9
7.1
8.2
7.3
6.6

2.4
2.9
2.9
3.0
3.0
2.9
3.1

4.7
4.6
6.0
5.9
5.2
5.8
5.6

3.9
4.6
5.5
5.5
5.1
5.6
5.7

5.1
4.6
6.1
6.2
5.4
5.9
5.7

1.4
2.0
2.0
2.2
2.4
2.4
2.3

Colombia f

1991
1994
1997
1999
2002
2004
2005

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

2.2
2.9
2.8
1.9
1.4
1.6
1.7

2.0
2.6
2.4
1.6
1.2
1.2
1.3

2.3
2.9
2.8
1.9
1.5
1.5
1.6

1.3
1.7
1.6
2.1
1.7
1.8
1.9

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

3.7
4.3
3.9
4.5
4.3
3.6
3.2
3.5

6.5
9.2
7.4
9.3
6.5
6.9
6.4
7.5

3.5
3.8
3.3
4.0
4.1
4.3
3.6
3.9

6.7
6.3
4.9
7.0
6.9
7.3
5.9
6.2

3.2
3.5
3.2
3.6
3.7
3.9
3.3
3.6

3.4
4.0
3.6
4.0
3.1
2.6
2.5
2.5

2.9
2.9
3.3
3.6
3.2
2.8
2.5
2.4

3.6
4.2
3.7
4.1
3.1
2.6
2.6
2.6

1.5
1.6
1.8
1.7
2.0
2.2
1.6
2.0

Wages

Argentina
(Greater Buenos
Aires)

Social Panorama of Latin America • 2007

393

Table 28 (continued)
AVERAGE INCOME OF THE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY
SECTORS OF THE LABOUR MARKET, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Microenterprises
Employers

a

Unskilled self-employed
workers b

Wage or salary earners
Total

Professional
Nonand technical professional
non-technical

Total c

Domestic
employment

Manufacturing Commerce
and
and
construction
services

1990
1994
1997
1999
2002
2004
2005
2006

2.0
2.4
2.3
1.9
2.6
2.3
2.7
2.5

4.0
6.1
5.5
6.0
6.2
6.0
6.7
6.7

2.3
2.0
2.0
1.8
2.2
2.3
2.4
2.4

3.4
3.9
5.0
2.6
3.4
3.4
4.4
4.6

2.3
1.9
1.8
1.7
2.1
2.2
2.2
2.3

1.8
2.0
2.1
1.8
2.4
1.9
2.2
2.1

1.7
1.8
1.8
1.6
2.2
1.8
2.2
2.2

1.9
2.1
2.2
1.9
2.5
2.0
2.3
2.2

0.8
0.9
0.9
0.9
1.5
1.7
1.7
2.0

El Salvador

1995
1997
1999
2001
2004

2.4
2.6
2.9
2.7
2.7

6.8
7.3
8.8
7.4
7.0

2.0
2.5
2.5
2.4
2.3

3.1
6.4
4.4
3.4
2.9

2.0
2.3
2.4
2.3
2.3

2.0
2.1
2.4
2.2
2.2

1.6
2.0
1.7
1.6
1.8

2.4
2.4
2.6
2.6
2.5

1.0
1.9
2.1
2.0
2.1

Guatemala

1989
1998
2002

2.8
2.5
1.7

13.1
9.9
5.4

1.8
2.2
1.7

3.9
3.5
3.9

1.7
2.0
1.6

2.8
2.1
1.2

2.4
1.6
1.1

3.5
2.4
1.4

1.4
0.6
1.6

Honduras

1990
1994
1997
1999
2002
2003
2006

1.6
1.6
1.5
1.5
1.5
1.3
1.2

7.6
4.8
4.7
4.4
4.4
4.2
3.8

1.7
1.4
1.2
1.1
1.6
1.6
1.6

3.9
2.5
2.6
1.7
3.5
3.8
3.0

1.6
1.3
1.1
1.1
1.4
1.5
1.4

1.5
1.6
1.2
1.2
1.2
1.0
0.9

1.1
1.1
1.0
1.1
1.0
0.9
1.1

1.6
1.7
1.3
1.3
1.4
1.1
0.9

0.8
0.5
0.5
0.5
0.8
1.2
1.2

Mexico g

1989
1994
1996
1998
2000
2002
2004
2005
2006

…
…
3.2
3.1
3.5
3.3
3.1
3.3
3.0

15.5
13.8
13.7
11.7
12.9
12.6
12.7
11.3
10.5

…
…
1.8
2.1
2.2
2.3
2.5
2.3
2.3

…
…
2.9
4.7
3.5
5.3
4.7
4.4
4.5

…
…
1.7
1.9
2.1
2.1
2.2
2.1
2.1

3.8
3.3
2.3
2.6
3.0
3.2
3.2
3.5
2.9

3.5
2.7
1.9
2.1
2.7
2.9
3.2
3.3
2.8

5.2
3.6
2.4
2.7
3.2
3.3
3.3
3.5
3.0

1.4
1.2
1.2
1.3
1.3
1.4
1.4
1.6
1.4

Nicaragua

1993
1998
2001

3.0
2.3
2.1

8.8
6.9
6.1

2.6
2.2
1.9

4.8
5.2
3.4

2.3
1.9
1.8

2.9
2.0
1.8

2.7
2.1
1.5

3.3
2.1
2.1

2.1
1.7
1.4

Panama

1991
1994
1997
1999
2002
2004
2005
2006

2.9
3.6
3.6
3.5
4.0
2.9
2.8
3.0

9.7
11.6
11.7
10.9
9.7
9.3
9.7
8.2

3.1
2.6
3.0
3.4
6.1
3.3
3.3
3.4

7.4
6.0
5.4
7.9
8.2
5.9
7.4
6.2

2.7
2.4
2.6
2.8
5.9
3.1
2.7
3.0

2.3
4.0
3.9
3.3
2.8
2.5
2.8
2.5

2.7
3.7
3.8
3.1
2.7
2.9
2.7
2.8

3.0
4.3
4.1
3.4
2.8
2.5
3.0
2.5

1.3
1.3
1.4
2.1
2.5
1.6
1.3
1.5

Paraguay
(Asunción)

1990
1994
1996
1999
2001
2004
2005

3.1
3.0
2.5
2.6
2.3
1.9
1.7

8.2
8.7
7.2
6.2
6.4
7.5
4.8

1.9
2.3
2.3
2.5
2.3
1.8
1.8

3.8
4.9
3.3
4.1
3.1
2.4
3.2

1.8
2.0
2.3
2.3
2.2
1.8
1.7

3.6
2.4
2.5
2.2
1.7
1.4
1.3

2.4
2.0
2.1
2.2
1.6
1.4
1.5

4.1
2.6
2.7
2.3
1.7
1.5
1.3

0.8
1.3
1.2
1.7
1.6
1.5
1.6

Wages

Ecuador

394

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 28 (concluded)
AVERAGE INCOME OF THE URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY
SECTORS OF THE LABOUR MARKET, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Microenterprises
Employers

a

Unskilled self-employed
workers b

Wage or salary earners
Total

Professional
Nonand technical professional
non-technical

Total c

Domestic
employment

Manufacturing Commerce
and
and
construction
services

1994
1996
1999
2001
2004
2005

2.7
2.4
2.3
2.1
2.0
1.8

8.3
6.8
5.7
6.2
7.0
5.5

2.1
2.2
2.2
2.0
1.7
1.8

4.7
3.7
3.8
3.1
2.3
3.1

1.9
2.1
2.1
1.9
1.7
1.7

2.3
2.3
2.0
1.5
1.5
1.4

1.9
2.2
1.9
1.4
1.4
1.3

2.4
2.5
2.1
1.6
1.5
1.5

1.2
1.1
1.6
1.4
1.4
1.4

Peru

1997
1999
2001
2003

2.4
2.1
2.0
1.8

6.5
4.5
5.5
5.4

2.4
2.2
2.0
1.8

3.6
3.9
3.0
2.1

2.3
2.0
1.9
1.8

1.8
1.6
1.7
1.5

1.6
1.4
1.6
1.6

1.9
1.7
1.9
1.7

2.3
2.9
2.0
2.0

Dominican
Republic

1997
2000
2002
2004
2005
2006

3.8
4.1
4.0
4.5
2.5
2.7

9.9
14.3
14.5
15.2
6.8
7.7

2.6
2.8
2.4
1.5
1.7
1.7

5.1
8.5
4.0
2.4
2.8
3.3

2.4
2.3
2.3
1.4
1.6
1.6

4.0
4.3
4.1
4.4
2.4
2.6

4.2
4.6
4.4
5.3
2.7
2.9

4.1
4.3
4.2
4.5
2.4
2.6

1.4
1.2
1.3
0.9
1.3
1.4

Uruguay

1990
1994
1997
1999
2002
2004
2005

3.8
3.5
3.5
3.7
2.4
2.3
2.2

8.9
10.5
9.8
11.6
8.8
8.0
7.9

2.6
3.0
3.1
3.3
2.7
2.1
2.1

4.8
4.6
4.2
5.4
4.2
3.1
4.1

2.5
2.9
3.0
3.2
2.6
2.0
2.0

5.1
3.5
3.5
3.6
2.4
2.1
2.0

2.1
2.8
2.8
3.1
2.1
1.9
1.8

3.0
3.9
3.8
3.9
2.5
2.2
2.1

1.5
1.7
1.8
2.1
2.0
1.7
1.7

Venezuela h
(Bol. Rep. of)

1990
1994
1997
1999
2002
2004
2005
2006

4.2
3.6
3.6
3.1
2.9
2.9
3.6
3.3

9.5
7.5
9.4
7.6
8.7
8.3
10.3
8.6

2.5
2.2
1.8
2.1
1.7
1.7
2.0
2.5

3.5
6.0
2.9
4.0
2.6
2.7
2.5
3.8

2.5
2.0
1.7
2.0
1.7
1.7
2.0
2.4

4.3
3.8
3.8
3.1
2.8
2.7
3.5
3.2

4.0
3.5
4.0
3.3
3.3
3.1
3.8
3.6

4.5
4.0
4.2
3.1
2.9
2.9
3.6
3.3

2.1
1.9
1.4
1.4
1.2
1.2
1.4
1.7

Wages

(Urban)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

b
c
d
e
f

g
h

Refers to establishments employing up to 5 persons. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic,
El Salvador, Panama (up to 2002) and Uruguay (1990), includes establishments employing up to four persons. Where no information was available on
the size of the establishments, no figures are given for the population employed in low-productivity sectors.
Refers to own-account and unpaid family workers without professional or technical skills.
Includes persons employed in agriculture, forestry, hunting and fishing.
Until 1990, the “microenterprises” category included wage earners without an employment contract.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992,the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Information from national household income and expenditure surveys (ENIGH).
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Social Panorama of Latin America • 2007

395

Table 28.1
AVERAGE INCOME OF THE URBAN MALE POPULATION EMPLOYED IN LOW-PRODUCTIVITY
SECTORS OF THE LABOUR MARKET
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Microenterprises
Employers

a

Unskilled self-employed
workers b

Wage or salary earners
Total

Professional
Nonand technical professional
nontechnical

Total c

Domestic
employment

Manufacturing Commerce
and
and
construction
services

1990
1994
1997
1999
2002
2004
2005
2006

8.3
10.1
7.7
7.3
4.8
5.7
6.1
6.8

19.9
25.2
23.8
21.7
16.7
16.9
18.6
21.0

3.8
5.2
4.0
4.0
2.6
3.2
3.4
3.7

8.9
9.4
6.5
7.9
10.0
4.9
5.6
4.9

3.7
4.9
3.8
3.8
2.2
3.1
3.2
3.6

8.8
10.6
7.6
7.1
4.7
6.1
7.0
7.3

7.3
9.3
7.3
6.1
4.1
5.2
6.1
6.6

9.6
11.4
7.8
7.8
5.1
6.8
7.5
7.6

4.4
4.5
2.7
3.1
3.6
3.7
3.4
1.0

Bolivia

1989
1994
1997
1999
2002
2004

4.6
3.6
3.3
2.9
2.7
2.4

12.9
8.2
7.3
6.0
5.4
5.6

2.9
2.3
2.6
2.8
2.5
2.3

5.4
4.3
5.3
5.0
3.7
5.1

2.7
2.2
2.4
2.6
2.5
2.1

4.9
3.2
2.9
2.8
2.5
2.1

3.6
2.5
2.6
2.6
2.0
2.4

5.6
3.6
3.8
3.2
3.2
2.2

4.0
1.7
1.8
1.9
2.6
1.3

Brazil d

1990
1993
1996
1999
2002
2003
2004
2005
2006

4.0
3.7
4.7
3.8
3.6
3.1
3.1
3.1
3.1

…
12.0
14.4
10.4
11.0
9.9
10.0
9.4
10.0

3.7
2.2
2.8
2.5
2.4
2.3
2.3
2.3
2.3

11.6
6.6
7.3
5.0
4.3
4.3
4.1
4.2
4.2

2.8
2.0
2.6
2.2
2.2
2.1
2.1
2.1
2.2

4.4
3.5
4.7
3.6
3.5
2.8
2.8
2.8
2.8

3.5
2.8
3.8
3.0
2.8
2.8
2.6
2.7
2.7

5.2
4.6
6.0
4.5
4.5
3.5
3.6
3.4
3.5

1.3
1.5
2.0
2.1
2.0
1.9
1.8
1.8
1.9

Chile e

1990
1994
1996
1998
2000
2003
2006

5.0
5.2
7.0
7.6
7.2
7.5
6.9

21.5
17.5
23.1
27.1
24.5
26.8
21.6

2.8
3.4
3.6
3.6
3.7
3.6
3.7

6.7
8.9
9.1
8.1
9.4
9.6
7.7

2.5
3.0
3.0
3.2
3.1
3.0
3.3

5.2
5.2
7.0
7.0
5.8
6.5
6.8

4.3
5.1
6.4
6.2
5.6
6.2
6.6

5.7
5.4
7.3
7.4
6.2
6.8
7.2

1.9
2.2
2.1
3.0
3.0
3.4
3.1

Colombia f

1991
1994
1997
1999
2002
2004
2005

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

2.8
3.5
3.4
2.4
1.9
2.0
2.1

2.4
3.0
2.6
1.9
1.5
1.5
1.6

2.9
3.5
3.5
2.4
2.0
1.9
2.0

1.5
1.7
1.6
2.7
2.2
2.1
2.8

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

4.5
5.4
4.7
5.7
5.2
4.6
4.3
4.4

6.8
9.9
7.9
10.1
8.6
7.0
6.8
8.5

3.6
4.3
3.7
4.2
4.4
4.6
3.7
3.9

8.0
7.4
5.7
8.0
7.7
8.0
6.0
6.0

3.3
3.9
3.5
3.8
3.9
4.1
3.5
3.7

4.3
4.8
4.5
5.2
4.0
3.3
3.5
3.3

3.9
3.7
3.9
4.6
3.7
3.2
3.1
2.9

4.5
4.9
4.9
5.5
4.4
3.5
3.8
3.6

1.5
2.1
2.3
2.3
2.3
2.9
1.9
3.0

Wages

Argentina
(Greater
Buenos Aires)

396

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 28.1 (continued)
AVERAGE INCOME OF THE URBAN MALE POPULATION EMPLOYED IN LOW-PRODUCTIVITY
SECTORS OF THE LABOUR MARKET
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Microenterprises
Employers

a

Unskilled self-employed
workers b

Wage or salary earners
Total

Professional
Nonand technical professional
nontechnical

Total c

Domestic
employment

Manufacturing Commerce
and
and
construction
services

1990
1994
1997
1999
2002
2004
2005
2006

2.5
3.0
2.9
2.8
3.1
3.0
3.2
3.2

3.9
6.6
5.6
6.4
6.5
6.5
7.4
7.4

2.4
2.2
2.0
1.8
2.2
2.3
2.5
2.4

4.0
5.3
7.9
2.9
3.8
4.2
5.3
4.9

2.4
2.0
1.8
1.7
2.1
2.2
2.3
2.3

2.3
2.6
2.6
2.3
3.0
2.5
2.6
2.8

1.9
2.2
2.3
2.1
2.7
2.3
2.7
2.7

2.5
2.8
2.8
2.5
3.2
2.7
2.9
3.0

1.1
1.1
1.3
1.4
1.9
2.8
2.1
2.0

El Salvador

1995
1997
1999
2001
2004

3.2
3.3
3.5
3.1
3.1

7.4
7.9
9.3
7.9
7.9

2.2
2.5
2.6
2.5
2.5

3.4
5.8
4.5
3.9
2.9

2.2
2.4
2.5
2.4
2.5

2.8
3.2
2.9
2.6
2.8

2.2
2.7
2.4
2.2
2.5

3.8
3.5
3.4
3.4
2.9

1.7
2.8
2.9
2.3
2.8

Guatemala

1989
1998
2002

3.5
3.3
3.1

13.7
11.3
6.0

1.9
2.4
1.8

4.9
4.0
3.9

1.8
2.2
1.7

3.6
2.8
1.5

3.4
2.5
1.6

5.4
3.7
2.0

2.6
1.2
1.7

Honduras

1990
1994
1997
1999
2002
2003
2006

2.2
2.1
1.9
1.9
1.8
1.7
1.7

9.4
5.1
5.0
4.7
4.6
4.4
4.2

1.8
1.4
1.1
1.2
1.6
1.6
1.7

4.1
2.5
2.2
1.4
4.4
3.6
3.3

1.7
1.3
1.1
1.2
1.4
1.5
1.5

2.2
2.0
1.7
1.6
1.5
1.2
1.2

1.7
1.6
1.6
2.1
1.5
1.3
1.6

2.4
2.3
1.8
1.8
1.8
1.4
1.4

1.6
1.6
0.8
0.8
1.2
1.4
1.8

Mexico g

1989
1994
1996
1998
2000
2002
2004
2005
2006

…
…
3.9
3.8
4.6
4.4
4.1
4.2
3.8

16.5
14.2
14.2
11.6
13.5
13.1
13.7
11.7
11.0

…
…
1.9
2.3
2.4
2.5
2.6
2.5
2.7

…
…
3.1
5.6
3.9
5.5
5.7
5.4
5.0

…
…
1.8
2.1
2.3
2.3
2.3
2.3
2.2

5.5
4.4
3.1
3.6
4.7
4.5
4.6
4.9
4.1

4.8
3.7
2.5
2.8
3.5
3.8
4.3
4.4
3.6

7.2
4.9
3.4
3.8
5.4
4.9
4.9
5.1
4.3

2.1
2.0
1.8
1.9
2.1
2.0
2.3
3.3
2.7

Nicaragua

1993
1998
2001

3.0
2.8
2.3

9.9
7.1
5.5

2.7
2.3
1.9

7.4
5.1
4.6

2.4
2.0
1.8

3.2
2.4
2.2

2.8
2.5
1.9

4.0
2.8
2.8

1.3
3.3
1.0

Panama

1991
1994
1997
1999
2002
2004
2005
2006

3.6
4.8
4.8
4.3
4.8
3.8
3.8
3.6

9.5
12.1
12.3
11.6
10.0
10.1
9.5
8.8

3.4
2.6
2.9
3.3
6.8
3.2
3.2
3.6

7.9
6.1
5.1
8.5
9.5
6.4
6.1
9.4

2.7
2.4
2.6
2.7
6.6
3.0
3.0
3.1

3.1
4.5
4.5
3.9
3.3
3.1
2.9
3.1

3.1
4.1
4.3
3.6
3.0
3.4
3.0
3.2

3.5
4.9
4.9
4.2
3.5
3.2
3.0
3.2

1.3
2.2
2.0
2.4
2.4
2.2
2.1
2.4

Wages

Ecuador

Social Panorama of Latin America • 2007

397
Table 28.1 (concluded)

AVERAGE INCOME OF THE URBAN MALE POPULATION EMPLOYED IN LOW-PRODUCTIVITY
SECTORS OF THE LABOUR MARKET
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Microenterprises
Employers

a

Unskilled self-employed
workers b

Wage or salary earners
Total

Professional
Nonand technical professional
nontechnical

Total c

Domestic
employment

Manufacturing Commerce
and
and
construction
services

1990
1994
1996
1999
2001
2004
2005

4.2
3.9
3.3
3.0
2.9
2.5
2.3

8.2
9.0
7.6
6.4
7.0
8.2
5.2

2.0
2.3
2.5
2.5
2.4
1.8
1.8

4.8
5.8
3.5
3.9
3.7
2.3
2.8

1.9
2.1
2.4
2.3
2.2
1.8
1.7

4.5
2.9
3.1
2.6
2.1
1.8
1.8

2.9
2.5
2.6
2.4
2.1
1.8
1.9

5.2
3.2
3.6
2.8
2.1
1.9
1.9

…
2.1
2.0
1.9
1.9
2.0
2.2

(Urban)

1994
1996
1999
2001
2004
2005

3.5
3.1
2.8
2.7
2.4
2.3

8.4
7.0
5.8
6.5
7.6
5.9

2.2
2.3
2.1
2.0
1.7
1.8

5.3
4.0
3.7
3.6
2.5
3.0

2.0
2.2
2.0
1.9
1.7
1.7

2.8
2.9
2.3
1.9
1.9
1.8

2.5
2.7
2.1
1.8
1.8
1.6

3.0
3.3
2.6
2.1
2.0
2.0

1.9
1.7
1.7
1.8
1.9
1.8

Peru

1997
1999
2001
2003

3.0
2.4
2.5
2.3

6.9
4.9
5.9
5.9

2.6
2.3
2.1
1.9

4.3
4.3
3.5
2.5

2.5
2.1
2.0
1.9

2.3
2.1
2.0
2.0

2.2
2.0
2.2
2.0

2.5
2.3
2.3
2.3

2.7
1.8
1.8
3.6

Dominican
Republic

1997
2000
2002
2004
2005
2006

4.4
4.9
4.9
5.5
2.9
3.1

10.8
15.0
14.8
16.4
7.4
7.8

2.7
3.0
2.4
1.5
1.9
1.9

4.8
8.6
3.2
2.4
3.1
3.6

2.6
2.4
2.3
1.5
1.8
1.8

4.7
4.9
4.6
4.9
2.6
3.0

4.6
5.0
4.6
5.6
2.8
3.1

4.8
5.0
5.0
5.3
2.8
3.2

2.2
2.0
2.5
1.2
1.8
2.1

Uruguay

1990
1994
1997
1999
2002
2004
2005

6.1
4.7
4.5
4.7
3.3
2.8
2.9

9.6
10.8
10.5
12.1
9.0
8.7
8.4

2.8
3.2
3.3
3.5
2.9
2.2
2.4

6.3
7.0
6.0
7.1
4.7
2.9
4.7

2.7
3.1
3.2
3.4
2.8
2.2
2.3

7.3
4.4
4.1
4.2
2.6
2.4
2.4

2.7
3.5
3.3
3.5
2.3
2.2
2.1

3.8
5.0
4.6
4.7
2.8
2.5
2.5

1.5
3.0
2.0
2.7
3.3
2.6
2.7

1990
1994
1997
1999
2002
2004
2005
2006

5.1
4.2
4.1
3.4
3.4
3.3
4.0
3.8

9.5
7.6
9.5
7.7
8.9
8.5
10.6
8.6

2.5
2.2
1.7
2.1
3.3
1.7
2.1
2.5

3.9
6.4
2.8
4.3
3.3
2.9
2.9
3.7

2.5
2.0
1.7
2.0
1.7
1.7
2.1
2.5

4.9
4.2
4.3
3.3
1.7
3.1
4.0
3.7

4.8
3.9
4.6
3.8
3.9
3.6
4.5
4.1

5.4
4.7
5.0
3.8
3.6
3.5
4.4
4.1

3.4
2.9
2.2
2.0
1.9
1.7
1.7
1.8

Venezuela
(Bol. Rep. of)

h

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

b
c
d
e
f

g
h

Refers to establishments employing up to 5 persons. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic,
El Salvador, Panama (up to 2002) and Uruguay (1990), includes establishments employing up to four persons. Where no information was available on
the size of the establishments, no figures are given for the population employed in low-productivity sectors.
Refers to own-account and unpaid family workers without professional or technical skills.
Includes persons employed in agriculture, forestry, hunting and fishing.
Until 1990, the “microenterprises” category included wage earners without an employment contract.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Information from national household income and expenditure surveys (ENIGH).
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Wages

Paraguay
(Asunción)

398

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 28.2
AVERAGE INCOME OF THE URBAN FEMALE POPULATION EMPLOYED IN LOW-PRODUCTIVITY
SECTORS OF THE LABOUR MARKET, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Microenterprises
Employers

a

Unskilled self-employed
workers b
Total c

Wage or salary earners
Total

Professional
Nonand technical professional
non-technical

Domestic
employment

Manufacturing Commerce
and
and
construction services

1990
1994
1997
1999
2002
2004
2005
2006

4.2
5.5
4.9
3.7
2.7
2.7
3.2
3.3

13.2
23.0
21.1
12.6
11.9
13.3
15.3
15.4

3.5
4.4
3.7
3.2
2.0
2.5
2.8
3.1

5.8
5.5
5.3
4.6
3.3
3.4
4.2
4.1

3.4
4.2
3.4
3.0
1.8
2.4
2.6
3.0

4.5
6.4
4.7
4.3
2.7
3.3
3.7
4.2

5.7
4.2
3.4
3.4
2.1
2.5
3.3
2.7

4.2
6.5
4.9
4.4
2.9
3.6
3.8
4.6

2.0
3.2
2.5
2.4
1.7
1.6
1.7
1.7

Bolivia

1989
1994
1997
1999
2002
2004

2.7
1.8
1.9
1.9
1.7
1.5

6.1
7.5
6.6
9.7
5.4
6.5

2.4
1.7
2.3
2.1
2.1
1.7

3.4
2.8
6.3
5.1
2.9
3.4

2.2
1.5
1.8
1.8
2.0
1.5

2.9
1.6
1.7
1.6
1.4
1.2

2.7
1.4
1.3
0.9
1.1
1.0

3.0
1.7
2.0
1.9
1.6
1.4

1.4
0.9
1.0
1.8
2.0
1.4

Brazil d

1990
1993
1996
1999
2001
2003
2004
2005
2006

2.2
1.5
2.2
1.9
1.8
1.7
1.7
1.7
1.7

…
8.4
12.6
10.1
9.5
8.4
8.1
7.3
8.5

3.5
2.1
2.5
2.2
2.3
2.1
2.1
2.1
2.3

5.6
3.3
4.1
2.9
3.2
3.1
3.4
3.3
3.7

2.1
1.8
2.3
1.8
1.8
2.0
1.9
2.0
2.1

1.9
1.4
2.0
1.6
1.6
1.3
1.3
1.3
1.4

1.1
1.1
1.5
1.2
1.3
1.4
1.4
1.3
1.4

2.0
1.9
2.6
2.0
2.0
1.6
1.7
1.7
1.8

0.9
1.1
1.5
1.4
1.4
1.4
1.3
1.3
1.4

Chile e

1990
1994
1996
1998
2000
2003
2006

2.6
3.2
3.6
3.7
3.5
3.8
3.3

10.2
17.2
20.4
16.8
14.0
18.3
14.7

2.3
2.7
3.1
3.2
3.3
3.0
3.1

3.1
3.8
5.6
6.2
6.6
4.6
5.5

2.2
2.6
2.8
2.6
2.8
2.8
2.7

2.9
3.3
3.9
4.2
3.9
4.0
3.8

2.9
3.2
3.3
3.6
3.6
3.4
3.3

3.9
3.3
4.1
4.4
4.0
4.2
4.0

1.4
2.0
2.0
2.2
2.4
2.4
2.3

Colombia f

1991
1994
1997
1999
2002
2004
2005

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

2.2
2.0
2.0
1.3
1.0
1.0
1.0

1.9
1.9
1.9
1.1
0.8
0.8
0.8

2.3
2.0
2.0
1.3
1.0
1.0
1.1

1.2
1.7
1.6
2.1
1.7
1.8
1.9

Costa Rica

1990
1994
1997
1999
2002
2004
2005
2006

2.1
2.8
2.4
2.7
3.0
2.7
2.3
2.6

5.0
6.5
5.3
6.1
9.2
6.7
5.1
5.1

3.1
2.9
2.9
3.6
3.6
3.7
3.3
3.7

4.5
4.0
3.7
5.6
5.2
5.6
5.9
6.3

2.9
2.8
2.8
3.3
3.4
3.5
2.8
3.3

1.7
2.5
2.1
2.1
2.0
1.7
1.4
1.5

1.6
1.7
2.1
2.0
2.3
1.9
1.5
1.4

1.8
2.9
2.1
2.1
1.9
1.6
1.4
1.5

1.5
1.6
1.8
1.7
2.0
2.2
1.6
1.9

Wages

Argentina
(Greater Buenos
Aires)

Social Panorama of Latin America • 2007

399

Table 28.2 (continued)
AVERAGE INCOME OF THE URBAN FEMALE POPULATION EMPLOYED IN LOW-PRODUCTIVITY
SECTORS OF THE LABOUR MARKET, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Microenterprises
Employers

a

Unskilled self-employed
workers b

Wage or salary earners
Total

Total c

Professional
Nonand technical professional
non-technical

Domestic
employment

Manufacturing Commerce
and
and
construction services

1990
1994
1997
1999
2002
2004
2005
2006

1.3
1.6
1.7
1.4
1.8
1.6
1.9
2.0

4.2
4.4
4.9
4.7
5.2
4.4
5.1
5.1

2.0
1.7
1.9
1.6
2.2
2.0
2.3
2.3

2.8
1.9
2.9
2.2
2.8
2.5
3.5
4.0

1.9
1.7
1.7
1.4
2.1
1.9
2.1
2.1

1.3
1.4
1.5
1.2
1.7
1.3
1.6
1.5

1.2
1.3
1.0
0.8
1.4
0.9
1.2
1.3

1.3
1.4
1.6
1.3
1.8
1.4
1.7
1.6

0.7
0.9
0.9
0.9
1.5
1.6
1.6
2.0

El Salvador

1995
1997
1999
2001
2004

1.7
2.1
2.4
2.2
2.3

5.2
5.9
7.6
6.3
4.8

1.6
2.3
2.2
2.1
1.4

2.9
7.2
4.2
2.4
2.8

1.5
2.0
2.1
2.1
2.0

1.6
1.7
2.0
2.0
2.1

1.3
1.5
1.4
1.3
1.4

1.7
1.8
2.2
2.2
2.3

0.9
1.8
2.0
1.9
2.0

Guatemala

1989
1998
2002

1.6
1.6
1.3

11.1
6.2
3.5

1.8
1.6
1.6

2.5
2.8
4.0

1.5
1.4
1.3

1.9
1.5
1.0

1.6
1.0
0.7

2.1
1.7
1.1

1.4
0.6
1.6

Honduras

1990
1994
1997
1999
2002
2003
2006

1.0
1.0
0.9
1.0
1.1
1.2
1.0

4.0
3.5
3.5
3.5
4.0
3.7
3.0

1.4
1.3
1.2
1.2
1.4
1.8
1.6

3.5
2.6
2.9
1.9
2.7
3.9
2.5

1.2
1.1
0.9
1.0
1.2
1.5
1.4

0.9
1.1
0.8
0.8
0.9
0.8
0.6

0.7
0.7
0.6
0.7
0.6
0.5
0.7

0.9
1.2
0.9
0.9
1.0
0.9
0.6

0.8
0.5
0.5
0.5
0.8
1.2
1.2

Mexico g

1989
1994
1996
1998
2000
2002
2004
2005
2006

…
…
1.7
1.9
1.7
2.0
1.9
2.2
2.0

9.4
11.6
11.3
12.5
9.7
10.3
9.5
10.0
8.8

…
…
1.6
1.6
1.7
2.0
2.1
2.0
2.1

…
…
2.6
3.2
2.7
5.0
3.7
3.2
3.8

…
…
1.4
1.5
1.6
1.7
1.8
1.8
1.8

2.3
1.8
1.3
1.6
1.4
1.7
1.9
1.9
1.8

1.7
1.1
1.1
1.5
1.3
1.9
1.3
1.4
1.4

2.6
2.1
1.4
1.6
1.5
1.7
2.0
2.0
1.9

1.3
1.1
1.1
1.1
1.1
1.3
1.3
1.5
1.3

Nicaragua

1993
1998
2001

2.5
1.8
1.8

7.0
6.0
8.0

2.4
2.2
1.9

2.8
5.4
2.0

2.3
1.6
1.9

2.6
1.6
1.6

2.6
1.3
1.2

2.7
1.7
1.7

2.1
1.5
1.4

Panama

1991
1994
1997
1999
2002
2004
2005
2006

2.0
1.9
2.3
2.6
2.5
2.0
2.0
1.9

10.3
9.4
9.6
8.8
8.8
5.8
6.0
6.4

3.1
2.8
3.2
3.4
4.4
3.3
2.9
3.0

6.3
5.8
5.7
7.0
5.9
5.3
5.1
4.4

2.7
2.4
2.7
2.9
4.2
3.1
2.7
2.5

1.8
2.6
2.5
2.1
1.6
1.3
1.3
1.4

1.3
2.2
2.2
1.9
1.5
1.2
1.2
1.5

1.9
2.7
2.6
2.2
1.6
1.3
1.3
1.4

1.3
1.2
1.4
2.0
2.5
1.6
1.7
1.5

Wages

Ecuador

400

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 28.2 (concluded)
AVERAGE INCOME OF THE URBAN FEMALE POPULATION EMPLOYED IN LOW-PRODUCTIVITY
SECTORS OF THE LABOUR MARKET, 1990-2006
(In multiples of the relevant per capita poverty line)
Country

Year

Total

Microenterprises
Employers

a

Unskilled self-employed
workers b

Wage or salary earners
Total

Total c

Professional
Nonand technical professional
non-technical

Domestic
employment

Manufacturing Commerce
and
and
construction services

1990
1994
1996
1999
2001
2004
2005

2.0
2.1
1.8
2.2
1.8
1.4
1.4

8.2
8.0
6.1
5.7
5.2
5.1
3.7

1.8
2.2
2.1
2.5
2.2
1.8
1.9

3.1
4.0
2.8
5.1
2.4
2.4
4.1

1.5
1.8
2.0
2.4
2.1
1.7
1.7

2.9
1.9
1.9
2.1
1.3
1.0
0.9

1.9
1.3
1.4
1.9
1.2
0.9
0.9

3.2
2.1
2.1
2.0
1.3
1.0
1.0

0.8
1.2
1.2
1.7
1.5
1.5
1.5

(Urban)

1994
1996
1999
2001
2004
2005

2.0
1.7
1.9
1.5
1.4
1.2

7.9
6.1
5.4
5.6
5.3
4.1

2.0
2.0
2.3
2.0
1.7
1.8

3.9
2.8
4.0
2.5
2.2
3.3

1.7
2.0
2.0
1.9
1.6
1.7

1.8
1.7
1.6
1.2
0.9
1.0

1.1
1.3
1.6
1.0
0.9
0.8

2.0
1.9
1.7
1.3
1.1
1.1

1.2
1.1
1.6
1.4
1.3
1.3

Peru

1997
1999
2001
2003

1.7
1.7
1.6
1.4

5.0
3.2
4.4
4.1

1.8
2.0
1.6
1.6

2.7
3.5
2.4
1.6

1.6
1.7
1.5
1.6

1.3
1.2
1.4
1.1

0.8
0.6
0.7
1.2

1.5
1.3
1.6
1.3

2.3
2.9
2.0
1.9

Dominican
Republic

1997
2000
2002
2004
2005
2006

2.5
2.9
2.9
2.8
1.7
1.8

5.8
12.9
13.6
12.0
5.1
7.5

2.4
2.5
2.5
1.3
1.4
1.4

5.6
8.3
5.4
2.4
2.2
2.8

2.0
2.1
2.2
1.1
1.3
1.3

2.9
2.9
2.9
3.0
1.6
1.7

2.5
2.3
3.3
2.9
1.5
1.7

3.0
3.0
2.9
3.0
1.6
1.7

1.4
1.1
1.1
0.8
1.2
1.3

Uruguay

Wages

Paraguay
(Asunción)

1990
1994
1997
1999
2002
2004
2005

1.9
2.2
2.4
2.5
2.2
1.8
1.7

6.3
9.4
7.4
10.4
7.9
6.2
6.6

2.0
2.5
2.6
2.9
2.3
1.8
1.8

3.1
2.5
2.9
4.1
3.4
3.2
3.5

1.9
2.5
2.6
2.8
2.2
1.7
1.7

1.8
2.2
2.3
2.5
1.8
1.6
1.5

1.2
1.5
1.6
1.9
1.4
1.2
1.1

1.9
2.5
2.6
2.7
2.0
1.7
1.7

1.5
1.7
1.8
2.1
1.9
1.6
1.6

1990
1994
1997
1999
2002
2004
2005
2006

2.5
2.6
2.6
2.4
2.2
2.1
2.7
2.6

9.8
6.7
8.3
6.7
7.7
7.4
8.9
8.4

2.5
2.4
1.2
2.1
1.7
1.6
1.9
2.3

3.1
5.6
3.0
3.7
2.2
2.5
2.2
3.8

2.4
2.0
1.6
1.9
1.6
1.5
1.8
2.1

2.7
2.6
3.1
2.3
2.2
2.1
2.7
2.4

2.6
2.4
2.5
2.1
2.0
2.0
2.3
2.2

2.8
2.6
3.2
2.4
2.3
2.2
2.8
2.5

1.7
1.5
1.2
1.3
1.2
1.2
1.4
1.7

Venezuela
(Bol. Rep. of)

h

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

b
c
d
e
f

g
h

Refers to establishments employing up to 5 persons. For Bolivarian Republic of Venezuela, Bolivia (1999 and 2002), Chile (1996), Dominican Republic,
El Salvador, Panama (up to 2002), and Uruguay (1990), includes establishments employing up to four persons. Where no information was available on
the size of the establishments, no figures are given for the population employed in low-productivity sectors.
Refers to own-account and unpaid family workers without professional or technical skills.
Includes persons employed in agriculture, forestry, hunting and fishing.
Until 1990, the “microenterprises” category included wage earners without an employment contract.
Information from national socio-economic surveys (CASEN).
In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. As a result of a changeover to a new survey sample
design in 2001, the figures for urban areas are not strictly comparable with those of previous years.
Information from national household income and expenditure surveys (ENIGH).
The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Social Panorama of Latin America • 2007

401

Education
Table 29
SCHOOL ATTENDANCE IN URBAN AREAS, BOTH SEXES, BY PER CAPITA HOUSEHOLD
INCOME QUINTILE AND AGE GROUP, 1989-2006

(In percentages of the population of the same age group)
Country

Year

7 - 12

13 - 19

20 - 24

Total

Poorest
20%

Richest
20%

Total

Poorest
20%

Richest
20%

Total

Poorest
20%

Richest
20%

1990 a
2002 b
2004
2005
2006

98.4
99.4
98.9
99.0
99.2

97.9
99.1
98.7
98.7
99.1

100.0
100.0
99.4
99.8
99.6

68.8
83.2
78.7
79.8
78.4

62.6
76.3
73.9
75.1
73.6

79.3
96.4
88.8
90.0
89.3

23.6
40.5
38.2
38.1
38.9

12.4
21.7
22.9
22.4
24.0

39.8
61.6
60.7
62.7
62.2

Bolivia

1989 c
2002
2004

97.3
96.9
97.8

95.9
95.6
96.6

96.3
98.3
99.8

85.0
84.6
82.5

84.4
84.2
83.5

87.5
88.2
90.6

44.3
43.3
38.9

45.6
32.9
28.2

52.7
74.3
64.8

Brazil

1990
2001
2003
2004
2005
2006

91.4
97.6
98.2
98.0
98.3
98.7

83.6
95.8
96.8
96.7
97.4
97.9

98.5
99.6
99.7
99.8
99.6
99.6

64.6
77.5
78.4
77.4
76.9
76.8

56.1
72.6
74.5
73.9
73.6
74.0

86.7
90.6
90.5
89.4
89.8
90.0

19.8
27.5
28.1
26.8
26.3
26.9

11.6
18.7
19.5
18.5
17.4
16.9

39.8
52.9
55.3
54.0
53.9
56.0

Chile

1990
1998
2003
2006

98.8
99.2
99.5
99.2

97.9
98.7
99.2
98.9

99.4
99.9
99.6
99.9

78.6
81.5
85.3
82.7

74.3
75.1
81.4
81.6

89.6
92.2
94.1
89.0

18.7
30.0
35.3
36.4

8.2
12.8
18.9
19.1

41.5
62.0
67.8
64.1

Colombia

1990 d
2002
2004
2005

96.0
96.3
96.9
97.4

92.6
94.0
94.9
95.8

99.1
99.4
98.1
99.6

74.9
68.2
71.0
73.0

66.3
64.3
68.4
70.1

92.8
85.1
86.3
89.2

28.1
23.5
25.0
25.0

15.3
12.7
12.6
11.6

48.9
52.2
53.0
56.6

Costa Rica

1990
2002
2004
2005
2006

96.8
98.5
99.5
99.4
99.2

95.3
97.2
99
99
97.8

98.4
99.4
100.0
100.0
100.0

68.6
76.9
77.9
80.2
78.6

57.9
72.9
74.5
78.2
71.3

86.2
90.2
89.1
93.4
94.9

28.5
43.3
44.1
41.3
43.0

20.0
29.7
22.9
26.4
23.2

52.1
60.6
65.2
67.5
65.7

Ecuador

1990
2002
2004
2005
2006

97.8
95.9
96.8
96.4
97.1

97.1
92.6
95.3
93.1
94.0

98.6
98.6
99.1
99.7
100.0

77.2
73.3
75.6
75.3
75.9

78.1
68.1
66.4
70.2
67.4

84.5
87.3
91.7
88.9
92.0

35.4
30.2
33.6
32.6
33.0

32.5
17.1
17.2
21.4
15.6

42.0
50.4
55.2
52.0
58.1

El Salvador

1995
2001
2004

92.2
92.6
94.7

85.8
85.9
91.6

99.6
100.0
99.0

70.5
73.4
75.1

64.2
66.0
67.5

87.0
87.0
90.2

27.2
25.5
24.3

13.1
11.3
14.5

49.6
49.5
43.6

Guatemala

1990
2002

...
90.4

...
84.2

…
94.3

...
66.9

...
63.3

…
78.3

...
25.5

...
11.1

...
43.9

Honduras

1990
2002
2003
2006

89.5
92.3
94.7
95.5

85.1
86.2
89.9
92.4

98.3
98.1
99.2
98.6

57.7
63.8
66.7
70.8

51.2
50.0
55.8
63.5

79.2
85.8
83.6
85.1

22.2
26.9
28.7
32.4

13.4
9.8
13.3
18.7

41.1
51.1
53.0
52.6

Education

Argentina

402

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 29 (concluded)
SCHOOL ATTENDANCE IN URBAN AREAS, BOTH SEXES, BY PER CAPITA HOUSEHOLD
INCOME QUINTILE AND AGE GROUP, 1989-2006

(In percentages of the population of the same age group)
Country

Year

7 - 12
Total

Mexico

Poorest
20%

13 - 19
Richest
20%

Total

Poorest
20%

20 - 24
Richest
20%

Total

Poorest
20%

Richest
20%

1992

97.4

95.8

99.5

62.7

55.6

80.7

23.9

7.1

47.3

2002

98.1

96.3

99.6

68.9

57.6

92.8

30.7

16.4

55.1

2004

97.1

100.0

68.0

62.2

86.2

27.7

12.3

50.2

97.9

96.3

99.1

70.0

60.5

87.1

27.4

14.4

48.7

2006
Nicaragua

98.6

2005

98.7

97.2

99.7

70.4

61.0

88.6

28.7

13.1

51.4

Panama

1993

88.7

82.5

97.3

69.5

56.7

80.4

24.4

17.1

34.0

2001

93.1

88.1

96.3

69.9

61.5

79.2

31.5

15.4

52.1

1991

98.7

98.4

99.5

81.3

76.1

91.1

37.6

25.8

57.0

2002

98.9

98.4

99.3

81.4

78.0

89.1

35.6

22.6

55.0

2004

97.8

100.0

82.7

77.9

94.5

34.6

21.6

58.8

99.1

98.4

100.0

81.4

76.4

94.4

34.4

20.8

52.5

2006
Paraguay

99.0

2005

99.1

98.7

100.0

81.7

79.5

94.1

36.5

20.0

58.9
43.0

96.0

94.5

99.2

71.2

62.0

85.3

23.6

12.0

97.7

97.4

99.9

74.1

63.8

86.8

31.9

13.7

61.5

2004

98.0

95.8

99.3

77.6

73.3

82.7

27.9

11.0

53.0

2005
Peru

1994
2001

99.4

99.1

100.0

78.8

70.7

88.2

29.6

10.4

57.2

1997

97.6

96.2

99.5

72.4

73.1

84.1

29.8

20.7

44.6

2001

98.6

97.7

98.9

72.9

72.2

74.8

27.7

18.9

40.6

2003

98.2

97.6

100.0

73.0

74.3

77.0

33.5

24.4

61.0

Dominican

2000

97.6

95.3

99.5

82.6

84.6

87.6

43.2

38.6

56.3

Republic

2002

97.7

95.9

99.2

83.7

83.3

89.3

44.3

34.4

60.5
48.3

Uruguay

98.0

96.9

99.5

83.2

82.9

84.2

42.1

34.3

97.6

97.2

98.1

83.3

83.0

84.2

40.9

30.7

57.9

2006

Education

2004
2005

97.9

97.3

99.1

82.6

82.2

85.0

42.5

38.2

55.8

1990

99.1

98.9

100.0

70.6

60.5

89.4

26.7

8.6

54.2

2002

98.2

98.2

98.8

76.5

64.2

94.9

34.8

12.7

73.0

2004

98.5

98.2

99.0

77.8

67.5

96.1

37.0

15.7

73.4

2005

98.6

98.6

99.6

76.6

66.4

96.2

37.4

14.1

72.5

Venezuela

1990

95.4

94.3

97.9

68.7

68.8

78.3

27.3

27.0

39.3

(Bol. Rep. of)

2002 e

96.7

94.6

98.6

67.2

62.7

77.8

33.6

20.8

54.7

2004 e

96.6

95.0

97.8

74.6

72.6

80.6

40.7

33.5

58.0

2005 e

97.5

96.1

98.9

75.4

74.4

80.6

43.2

34.3

60.4

2006 e

97.8

96.5

99.5

76.4

74.6

85.2

45.9

36.7

63.4

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Metropolitan area.
Twenty-eight urban agglomerates.
c Cochabamba, El Alto, La Paz, Oruro, Potosí, Santa Cruz, Sucre, Tarija and Trinidad.
d Barranquilla, Bogotá, Bucaramanga, Cali, Cartagena, Manizales, Medellín and Pasto.
e Nationwide total.
b

Social Panorama of Latin America • 2007

403

Table 30
POPULATION BETWEEN 15 AND 24 YEARS OF AGE, BY YEARS OF SCHOOLING, URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1980
1990
1994
1999
2002
2004
2006

7.6
3.3
3.9
2.5
2.9
2.8
1.5

77.3
78.6
77.2
40.6
35.2
34.0
39.9

...
...
...
41.5
44.5
47.5
42.0

15.0
18.2
18.9
15.5
17.4
15.6
16.6

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

Bolivia

1997
2002
2004

11.9
8.8
8.6

31.1
29.5
31.3

44.4
45.8
43.8

12.6
15.9
16.3

48.3
44.3
27.2

34.9
34.1
39.3

15.3
20.5
31.0

1.5
1.2
2.6

Brazil

1979
1990
1993
1999
2001
2003
2006

48.2
41.0
40.7
27.0
23.1
18.2
13.6

34.6
37.5
38.9
42.7
41.1
40.8
39.0

14.1
18.2
17.6
26.7
31.6
35.9
41.0

3.1
3.3
2.8
3.7
4.1
5.1
6.4

86.8
79.0
77.9
62.8
58.6
48.2
39.2

9.7
16.9
17.4
27.2
30.7
37.9
41.3

1.9
3.7
4.3
9.5
10.3
13.2
18.7

1.6
0.3
0.3
0.5
0.4
0.7
0.7

Chile

1990
1994
2000
2003
2006

5.7
4.2
2.6
1.6
1.3

33.2
31.3
29.9
28.3
26.5

45.4
46.4
51.1
51.8
53.0

15.8
18.1
16.5
18.4
19.2

16.6
14.3
8.4
5.4
3.3

57.1
54.8
49.8
45.4
38.3

22.4
26.2
37.1
44.2
51.8

3.9
4.8
4.6
5.1
6.5

Colombia b

1980
1990
1991
1994
1999
2002
2005

31.2
19.6
21.8
17.7
14.6
13.5
10.9

40.9
40.4
37.9
37.9
32.4
29.5
28.2

21.1
31.0
29.7
35.9
43.2
37.1
37.8

6.8
9.0
10.6
8.4
9.8
19.9
23.2

...
...
60.1
55.8
46.2
…
...

...
...
25.7
29.5
30.7
…
...

...
...
13.6
14.0
21.8
…
...

...
...
0.5
0.7
1.3
…
...

Costa Rica

1981
1990
1994
1999
2002
2006

7.3
9.1
8.6
8.5
7.3
5.6

50.5
50.1
49.6
50.8
49.4
48.8

33.9
29.8
30.9
28.3
30.4
31.8

8.2
10.9
10.9
12.4
12.8
13.8

19.8
20.0
21.2
18.5
19.1
14.3

64.7
64.5
64.3
61.9
61.4
60.0

13.8
13.6
12.3
15.9
15.5
20.2

1.7
2.0
2.2
3.7
4.0
5.5

Cuba c

2002
2006

1.4
0.8

36.2
23.9

39.3
49.3

23.1
26.0

3.9
1.9

54.1
32.6

26.8
49.4

12.2
16.0

Ecuador

1990
1994
1999
2002
2006

5.8
4.8
6.0
6.5
4.0

45.9
42.3
41.0
39.4
35.6

37.0
39.5
39.5
37.6
42.3

11.4
13.4
13.6
16.5
18.1

...
...
...
...
11.4

...
...
...
...
58.9

...
...
...
...
25.6

...
...
...
...
4.1

Education

Argentina a
(Greater Buenos
Aires)

404

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 30 (continued)
POPULATION BETWEEN 15 AND 24 YEARS OF AGE, BY YEARS OF SCHOOLING, URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas
0-5

El Salvador

Rural areas

Years of schooling

Years of schooling

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1995

20.6

41.4

28.8

9.2

60.4

31.2

7.3

1.1

1999

15.6

38.7

33.5

12.2

49.7

38.5

10.0

1.9

2001

Guatemala

13.8

39.5

33.7

13.0

43.9

41.8

12.3

2.0

2004

14.8

40.5

32.4

12.3

38.9

44.9

14.8

1.4

33.9

42.6

19.2

4.3

75.9

21.8

2.1

0.2

25.3

43.5

24.3

6.9

67.3

29.1

3.4

0.2

2004
Honduras

1989
1998

25.0

43.2

24.8

7.0

58.4

35.5

5.9

0.2

1990

24.1

55.7

15.3

5.0

57.6

39.8

2.3

0.3

1994

20.5

56.1

17.3

6.0

45.9

49.3

4.4

0.4

1999

57.7

19.9

6.2

45.5

49.1

5.2

0.3

16.1

52.4

23.8

7.7

45.4

49.9

4.1

0.6

2006

12.5

51.5

28.2

7.8

37.3

54.2

7.8

0.6

1989

8.3

60.5

22.1

9.1

31.4

59.2

7.7

1.7

1994

Mexico a

16.3

2003

7.5

57.5

24.4

10.6

25.8

65.1

8.0

1.1

1998

6.0

55.2

24.3

12.3

21.6

62.3

12.7

3.0

2002

6.3

42.2

37.2

14.3

15.2

59.7

20.2

4.9

2004

Nicaragua

4.5

46.6

32.2

16.7

14.1

56.8

23.1

6.0

2006

3.5

45.2

34.1

17.2

11.5

57.6

27.0

3.9

24.6

53.8

19.5

2.1

68.9

26.5

4.3

0.3

21.7

50.5

22.2

5.5

61.2

32.6

5.3

0.9

2001
Panama

1993
1998

19.8

46.4

26.1

7.7

60.5

33.2

5.5

0.7

1979

6.3

49.1

35.5

9.1

20.5

61.3

16.2

1.9

1991

6.3

42.7

39.5

11.5

15.6

57.3

23.6

3.5

Education

1994

5.0

45.9

36.4

12.6

16.4

56.3

23.3

4.0

1999

3.9

40.8

39.1

16.2

12.9

55.4

26.3

5.4

2002

3.5

38.6

41.8

16.1

20.2

53.6

21.2

5.1

2006

2.3

33.8

43.7

20.2

14.1

52.9

27.3

5.7

Paraguay

1986

10.6

50.9

31.1

7.5

...

...

...

...

(Asunción)

1990

7.3

46.7

36.8

9.3

...

...

...

...

1994

7.9

49.0

34.8

8.3

...

...

...

...

1997

6.2

48.1

37.1

8.6

...

...

...

...

2001

7.3

39.0

40.7

12.9

...

...

...

...

2005

3.6

38.8

45.2

12.4

...

...

...

...

1999

3.4

32.9

49.6

14.1

25.1

49.0

22.7

3.2

2001

5.6

31.6

44.0

18.8

22.1

48.7

23.5

5.7

2003

3.9

25.8

47.8

22.5

19.9

47.5

26.5

6.1

Dominican

2000

13.1

35.5

37.1

14.3

37.4

38.7

20.4

3.5

Republic

2002

11.7

35.1

37.3

15.9

31.3

41.6

23.4

3.7

2006

10.1

33.7

40.4

15.8

20.4

39.3

34.3

6.0

Peru

Social Panorama of Latin America • 2007

405

Table 30 (concluded)
POPULATION BETWEEN 15 AND 24 YEARS OF AGE, BY YEARS OF SCHOOLING, URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas
0-5

Uruguay

Rural areas

Years of schooling

Years of schooling

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1981

7.4

55.5

31.8

5.3

...

...

...

...

1990

3.7

52.6

35.4

8.3

...

...

...

...

1994

3.5

51.1

37.6

7.8

...

...

...

...

1999

2.8

48.6

39.4

9.2

...

...

...

...

2002

3.3

47.4

35.5

13.8

...

...

...

...

2005

3.2

45.5

36.7

14.6

...

...

...

...

Venezuela

1981

13.5

58.5

20.4

7.7

46.1

46.4

6.8

0.7

(Bol. Rep. of) d

1990

10.3

56.5

23.6

9.6

39.0

51.3

8.5

1.2

1994

10.2

48.2

28.8

12.8

38.2

48.4

10.9

2.5

1999

10.7

48.2

27.3

13.8

...

...

...

...

2002

9.9

46.3

29.0

14.8

...

...

...

...

2006

7.7

38.3

34.0

20.0

...

...

...

...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Education

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997.The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary
education, complete secondary education and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of 2002 population and housing censuses and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

406

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 30.1
MALE POPULATION BETWEEN 15 AND 24 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1980
1990
1994
1999
2002
2004
2006

7.6
3.1
4.8
2.5
3.7
3.6
1.7

78.9
81.6
80.1
46.0
39.2
35.8
43.1

...
...
...
39.9
41.6
47.8
41.6

13.5
15.3
15.0
11.7
15.4
12.7
13.5

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

Bolivia

1997
2002
2004

9.2
6.8
5.6

31.3
29.1
31.6

46.6
48.6
46.3

12.9
15.5
16.5

40.0
37.5
20.9

39.1
36.1
40.2

19.8
24.9
35.1

1.1
1.5
3.8

Brazil

1979
1990
1993
1999
2001
2003
2006

49.2
44.4
44.8
30.7
26.2
21.1
16.3

34.6
37.0
37.4
42.9
42.3
42.0
40.5

13.1
15.8
15.5
23.4
28.3
32.7
37.8

3.1
2.9
2.2
3.0
3.2
4.1
5.4

87.0
81.7
81.0
68.1
63.0
53.2
44.2

9.5
15.6
15.6
23.7
28.1
35.3
39.6

1.6
2.6
3.2
7.8
8.5
11.1
15.6

2.0
0.2
0.2
0.4
0.3
0.5
0.5

Chile

1990
1994
2000
2003
2006

6.1
4.6
2.7
2.0
1.6

33.7
32.3
30.8
29.3
27.6

45.4
45.5
49.6
50.9
52.3

14.8
17.7
16.8
17.9
18.5

18.7
16.2
9.5
6.2
3.7

57.6
55.5
52.7
46.5
40.4

20.5
24.2
34.3
43.3
50.9

3.1
4.2
3.5
3.9
5.1

Colombia b

1980
1990
1991
1994
1999
2002
2005

29.5
18.2
22.1
18.1
15.0
14.3
12.0

42.7
42.5
39.8
39.0
34.0
30.8
30.1

21.3
30.7
28.4
35.1
42.2
36.1
36.1

6.6
8.6
9.7
7.8
8.9
18.8
21.8

...
...
64.3
60.3
50.2
...
...

...
...
23.5
28.3
29.7
...
...

...
...
11.6
10.9
19.1
...
...

...
...
0.5
0.5
1.0
...
...

Costa Rica

1981
1990
1994
1999
2002
2006

7.8
10.5
9.4
9.5
8.0
6.4

52.4
50.1
47.9
52.0
50.5
51.8

31.6
28.6
31.5
26.8
29.8
29.9

8.2
10.8
11.2
11.6
11.7
11.9

19.6
22.3
22.4
19.3
20.9
15.8

65.8
63.7
64.7
63.3
61.9
60.8

12.7
12.2
11.0
13.6
13.4
18.7

1.9
1.8
1.9
3.7
3.7
4.7

Cuba c

2002
2006

1.8
1.0

40.0
26.7

36.5
48.5

21.7
23.8

4.8
2.7

59.0
33.9

24.0
48.1

12.2
15.3

Ecuador

1990
1994
1999
2002
2006

6.7
4.9
6.0
7.1
3.5

48.9
42.9
43.7
40.5
37.4

33.9
39.9
39.2
37.2
42.9

10.6
12.3
11.0
15.2
16.2

...
...
...
...
11.5

...
...
...
...
59.4

...
...
...
...
25.5

...
...
...
...
3.5

El Salvador

1995
1999
2001
2004

20.7
16.0
13.0
15.0

43.5
38.7
41.6
39.9

26.7
32.8
33.4
32.9

9.1
12.4
11.9
12.1

61.1
48.6
42.4
38.9

31.5
40.6
43.6
45.8

6.7
9.0
12.0
14.2

0.7
1.8
2.0
1.2

Guatemala

1989
1998
2004

27.6
24.3
19.9

47.5
45.8
46.9

18.6
21.8
26.2

6.2
8.1
6.9

70.8
61.1
52.0

26.5
34.8
41.4

2.5
3.9
6.3

0.2
0.1
0.4

Education

Argentina a
(Greater Buenos
Aires)

Social Panorama of Latin America • 2007

407

Table 30.1 (concluded)
MALE POPULATION BETWEEN 15 AND 24 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1990
1994
1999
2003
2006

23.8
21.4
17.7
18.1
13.7

57.3
56.2
58.8
53.4
53.2

14.6
15.9
18.5
21.5
25.5

4.3
6.5
5.0
7.0
7.6

60.2
48.2
46.7
48.6
41.9

38.2
47.9
49.0
47.4
51.8

1.6
3.5
4.2
3.6
5.7

0.1
0.4
0.1
0.5
0.6

Mexico a

1989
1994
1998
2002
2004
2006

7.6
7.1
6.2
5.3
4.9
3.7

58.1
56.1
55.5
44.3
47.5
47.2

23.8
25.2
25.3
35.9
32.1
32.9

10.5
11.5
12.4
14.5
15.5
16.1

31.4
27.4
19.9
14.9
14.4
11.3

58.6
63.5
62.6
61.2
58.3
58.4

8.4
7.9
13.6
19.7
21.1
25.7

1.5
1.2
3.4
4.3
6.2
4.6

Nicaragua

1993
1998
2001

26.0
24.0
23.5

54.2
50.7
49.0

17.7
20.6
21.3

2.1
4.7
6.2

72.1
65.7
64.2

23.3
30.1
30.7

4.4
3.5
4.7

0.2
0.8
0.4

Panama

1979
1991
1994
1999
2002
2006

6.5
7.2
5.6
4.3
4.1
2.4

52.6
47.1
49.5
43.9
42.3
38.0

32.3
36.0
34.8
37.9
40.0
42.3

8.6
9.7
10.1
13.8
13.6
17.3

20.3
17.8
18.2
14.8
19.0
13.3

63.5
58.2
59.1
59.4
58.1
54.9

14.6
21.2
19.9
21.9
19.5
27.0

1.6
2.8
2.8
3.9
3.4
4.8

Paraguay
(Asunción)

1986
1990
1994
1997
2001
2005

7.7
5.6
7.4
5.3
6.5
3.4

52.3
46.6
47.5
45.8
41.9
39.1

31.2
38.8
37.2
40.1
40.3
46.5

8.8
9.1
7.8
8.7
11.3
11.0

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Peru

1999
2001
2003

3.1
4.4
3.5

33.3
31.5
26.7

50.0
46.5
49.1

13.7
17.6
20.8

20.3
16.9
14.4

50.6
51.9
48.7

27.5
26.2
31.4

1.6
5.0
5.5

Dominican
Republic

2000
2002
2006

15.6
14.1
12.7

39.4
36.9
37.6

33.9
35.6
37.9

11.0
13.3
11.7

41.9
36.0
24.8

38.1
44.1
41.6

17.3
17.7
29.1

2.8
2.2
4.4

Uruguay

1981
1990
1994
1999
2002
2005

8.8
4.0
4.1
3.3
4.0
4.0

57.4
57.3
56.5
55.4
52.4
48.9

28.7
31.8
33.2
34.2
32.8
34.6

5.1
6.9
6.2
7.2
10.7
12.4

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Venezuela
(Bol. Rep. of) d

1981
1990
1994
1999
2002
2006

15.3
11.9
12.2
13.5
12.3
10.0

59.0
58.4
51.0
51.4
49.8
42.2

18.6
21.1
26.0
24.7
26.2
31.9

7.1
8.6
10.8
10.4
11.7
15.9

49.0
44.4
43.5
...
...
...

44.5
48.8
45.2
...
...
...

6.0
6.0
9.7
...
...
...

0.5
0.8
1.6
...
...
...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Education

Honduras

408

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 30.2
FEMALE POPULATION BETWEEN 15 AND 24 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1980
1990
1994
1999
2002
2004
2006

7.7
3.4
3.0
2.4
2.1
2.1
1.3

75.9
75.2
74.1
35.4
31.4
32.2
37.0

...
...
...
43.0
47.3
47.3
42.3

16.5
21.3
22.9
19.1
19.2
18.5
19.5

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

Bolivia

1997
2002
2004

14.5
10.5
11.4

30.9
29.9
31.1

42.3
43.4
41.5

12.4
16.3
16.0

56.9
52.0
33.6

30.5
31.7
38.3

10.8
15.4
26.7

1.8
0.8
1.4

Brazil

1979
1990
1993
1999
2001
2003
2006

47.3
37.9
36.8
23.4
20.2
15.4
11.0

34.5
38.0
40.3
42.4
40.0
39.6
37.5

15.0
20.4
19.5
29.9
34.7
39.0
44.2

3.2
3.7
3.4
4.3
5.0
6.0
7.4

86.6
76.1
74.3
56.7
53.5
42.4
33.6

9.9
18.5
19.5
31.1
33.8
40.9
43.3

2.2
5.0
5.7
11.5
12.2
15.7
22.3

1.3
0.4
0.4
0.7
0.4
0.9
0.8

Chile

1990
1994
2000
2003
2006

5.3
3.9
2.4
1.1
1.0

32.7
30.4
28.9
27.2
25.4

45.3
47.2
52.6
52.7
53.7

16.7
18.5
16.1
19.0
19.8

14.3
12.4
7.3
4.5
3.0

56.5
54.1
46.8
44.0
36.1

24.5
28.2
40.2
45.2
52.9

4.8
5.4
5.7
6.3
8.0

Colombia b

1980
1990
1991
1994
1999
2002
2005

32.5
20.8
21.5
17.4
14.3
12.9
9.8

39.5
38.7
36.3
37.1
31.1
28.3
26.5

21.0
31.2
30.8
36.6
44.0
38.0
39.3

7.0
9.3
11.4
8.9
10.6
20.8
24.4

...
...
55.9
50.9
41.8
…
...

...
...
28.0
30.8
31.8
…
...

...
...
15.6
17.4
24.8
…
...

...
...
0.5
0.8
1.7
…
...

Costa Rica

1981
1990
1994
1999
2002
2006

6.9
7.7
7.7
7.5
6.6
4.8

48.7
50.1
51.4
49.7
48.2
45.8

36.2
31.1
30.3
29.7
31.1
33.7

8.2
11.1
10.6
13.1
14.0
15.7

19.9
17.4
19.8
17.8
17.2
12.8

63.7
65.4
63.9
60.5
60.8
59.1

14.8
15.0
13.8
18.1
17.8
21.7

1.6
2.2
2.5
3.6
4.2
6.4

Cuba c

2002
2006

1.0
0.5

32.4
20.9

42.1
50.2

24.5
28.4

2.8
1.1

55.2
31.2

29.8
50.9

12.1
16.7

Ecuador

1990
1994
1999
2002
2006

5.0
4.8
5.9
5.9
4.5

43.1
41.8
38.3
38.3
33.8

39.8
39.2
39.8
38.0
41.7

12.1
14.3
16.0
17.8
20.0

...
...
...
...
11.3

...
...
...
...
58.3

...
...
...
...
25.6

...
...
...
...
4.7

Education

Argentina a
(Greater Buenos
Aires)

Social Panorama of Latin America • 2007

409

Table 30.2 (continued)
FEMALE POPULATION BETWEEN 15 AND 24 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Year

Urban areas
0-5

El Salvador

Rural areas

Years of schooling

Years of schooling

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1995

20.5

39.6

30.6

9.3

59.7

30.9

7.8

1.5

1999

15.3

38.7

34.1

12.0

50.8

36.4

11.0

1.9

2001

Guatemala

14.6

37.6

33.9

13.9

45.5

40.0

12.6

1.9

2004

14.6

41.1

31.9

12.4

38.9

44.0

15.4

1.6

38.9

38.7

19.6

2.8

80.8

17.4

1.7

0.2

26.2

41.5

26.6

5.8

73.2

23.7

2.8

0.3

2004

29.8

39.7

23.4

7.1

64.2

30.1

5.6

0.1

1990

24.2

54.4

15.9

5.5

55.0

41.5

3.1

0.4

1994

Honduras

1989
1998

19.8

56.0

18.5

5.6

43.4

50.8

5.3

0.4

1999

56.7

21.1

7.1

44.2

49.2

6.3

0.4

14.3

51.6

25.7

8.3

42.0

52.6

4.8

0.6

2006
Mexico a

15.2

2003

11.5

50.2

30.5

7.9

32.6

56.7

10.0

0.7

1989

8.9

62.7

20.5

7.8

31.4

59.8

6.9

1.9

1994

7.8

58.8

23.6

9.8

24.3

66.7

8.1

0.9

1998

5.8

54.9

23.4

12.3

23.2

62.0

11.7

2.6

2002

7.3

40.0

38.5

14.2

15.5

58.3

20.6

5.6

2004

Nicaragua

4.1

45.7

32.3

17.9

13.9

55.4

24.9

5.8

2006

3.2

43.2

35.3

18.3

11.7

56.9

28.2

3.2
0.3

23.4

53.4

21.1

2.1

65.7

29.8

4.3

19.7

50.3

23.7

6.3

56.4

35.4

7.2

1.0

2001
Panama

1993
1998

16.4

44.0

30.5

9.1

56.4

36.0

6.5

1.0

1979

6.1

46.1

38.2

9.6

20.8

58.6

18.2

2.3

1991

5.4

38.4

42.9

13.3

12.9

56.2

26.5

4.4
5.4

1994

4.5

42.3

38.0

15.2

14.4

53.0

27.2

1999

3.5

37.7

40.3

18.5

10.8

51.1

31.2

7.0

2002

3.0

34.6

43.6

18.8

21.5

48.5

23.0

7.0

2006

2.1

29.9

45.0

22.9

15.0

50.6

27.5

6.8

Paraguay

1986

12.4

49.9

31.0

6.7

...

...

...

...

(Asunción)

1990

8.7

46.7

35.1

9.4

...

...

...

...

1994

8.3

50.2

32.8

8.7

...

...

...

...

1997

6.9

50.1

34.5

8.5

...

...

...

...

2001

8.0

36.6

41.1

14.3

...

...

...

...

2005

3.7

38.6

44.1

13.6

...

...

...

...

1999

3.6

32.6

49.3

14.5

30.3

47.2

17.4

5.1

2001

6.8

31.7

41.5

20.0

27.8

45.3

20.5

6.5

2003

4.2

25.0

46.5

24.3

26.1

46.2

20.9

6.8

Dominican

2000

10.6

31.8

40.2

17.4

32.5

39.4

23.9

4.2

Republic

2002
2006

9.3
7.5

33.3
29.9

39.0
42.8

18.4
19.7

25.0
15.2

38.5
36.5

30.7
40.4

5.7
7.9

Peru

Education

Country

410

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 30.2 (concluded)
FEMALE POPULATION BETWEEN 15 AND 24 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas
0-5

Uruguay

Rural areas

Years of schooling

Years of schooling

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1981

6.1

53.9

34.6

5.5

...

...

...

...

1990

3.3

48.0

38.9

9.7

...

...

...

...

1994

2.8

45.8

42.0

9.4

...

...

...

...

1999

2.3

41.6

44.8

11.3

...

...

...

...

2002

2.7

42.3

38.2

16.9

...

...

...

...

2005

2.4

42.0

38.8

16.7

...

...

...

...

Venezuela

1981

11.8

58.0

22.0

8.2

42.2

48.8

7.9

1.0

(Bol. Rep. of) d

1990

8.7

54.5

26.2

10.6

32.5

54.3

11.5

1.7

1994

8.3

45.3

31.6

14.8

32.0

52.1

12.4

3.5

1999

7.7

44.9

30.0

17.4

...

...

...

...

2002

7.5

42.6

31.9

18.0

...

...

...

...

2006

5.3

34.2

36.2

24.2

...

...

...

...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Education

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Social Panorama of Latin America • 2007

411

Table 31
POPULATION BETWEEN 25 AND 59 YEARS OF AGE, BY YEARS OF SCHOOLING, URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1980
1990
1994
1999
2002
2004
2006

21.6
12.4
10.3
8.5
7.6
6.6
6.5

67.4
69.6
70.7
38.2
37.0
36.9
33.3

...
...
...
30.6
29.7
29.9
31.1

11.1
18.0
19.0
22.7
25.7
26.6
29.1

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

Bolivia

1997
2002
2004

34.1
31.0
33.0

17.3
18.6
18.1

28.4
25.7
25.7

20.3
24.6
23.3

78.3
74.6
67.3

12.2
16.5
17.3

5.8
6.4
9.1

3.8
2.5
6.3

Brazil

1979
1990
1993
1999
2001
2003
2006

70.0
55.5
53.4
45.3
43.1
39.8
34.7

12.6
17.1
19.0
21.6
21.9
21.7
21.1

10.0
16.8
17.7
21.8
23.4
25.9
30.0

7.3
10.7
10.0
11.3
11.5
12.5
14.2

96.0
89.2
88.3
82.6
83.7
79.9
74.5

1.9
6.3
6.8
10.2
9.9
11.8
13.9

1.0
3.7
3.9
5.8
5.3
7.1
9.8

1.0
0.8
1.0
1.4
1.1
1.2
1.8

Chile

1990
1994
2000
2003
2006

15.8
14.1
9.6
8.6
8.3

29.4
24.2
22.8
21.5
21.2

34.5
38.9
40.6
42.0
43.8

20.3
22.8
27.1
27.9
26.7

43.8
39.5
34.9
29.6
24.6

37.3
38.7
43.4
45.4
43.6

13.2
15.8
17.0
19.5
25.1

5.7
6.0
4.7
5.5
6.7

Colombia b

1980
1990
1991
1994
1999
2002
2005

52.4
37.4
39.9
35.9
33.3
33.2
30.7

22.3
23.4
23.0
22.9
21.5
19.0
18.1

13.7
23.1
21.3
25.3
27.6
26.8
27.6

11.6
16.1
15.8
15.9
17.6
21.0
23.7

...
...
78.2
76.2
72.8
...
...

...
...
12.4
12.0
12.5
...
...

...
...
7.3
9.5
10.9
...
...

...
...
2.1
2.4
3.9
...
...

Costa Rica

1981
1990
1994
1999
2002
2006

27.2
16.7
14.1
12.7
11.0
10.6

41.5
40.5
39.5
41.1
42.4
40.9

17.8
22.1
24.9
22.5
21.7
21.6

13.5
20.7
21.5
23.7
24.9
26.9

58.1
40.0
34.8
28.8
28.8
25.1

33.5
44.8
49.2
52.0
53.0
53.8

5.8
10.6
10.7
11.7
10.3
11.6

2.6
4.5
5.3
7.5
7.9
9.5

Cuba c

2002
2006

4.5
2.8

33.3
30.9

24.7
31.3

37.5
35.0

13.4
8.1

54.2
52.8

17.0
24.6

15.4
14.5

Ecuador

1990
1994
1999
2002
2006

16.1
11.7
11.5
11.4
10.1

43.0
39.8
37.2
36.5
34.4

21.9
24.6
27.1
25.5
27.7

19.0
24.0
24.2
26.5
27.8

...
...
...
...
36.0

...
...
...
...
49.1

...
...
...
...
10.1

...
...
...
...
4.7

El Salvador

1995
1999
2001
2004

35.8
30.6
29.7
27.6

30.2
29.8
29.9
30.5

19.7
22.0
22.9
23.6

14.3
17.7
17.5
18.3

80.2
75.2
72.2
68.7

16.3
19.6
21.0
23.4

2.6
3.7
5.1
6.1

0.9
1.5
1.8
1.8

Guatemala

1989
1998
2004

51.5
42.4
41.5

26.6
29.9
29.9

13.8
17.5
19.4

8.1
10.2
9.2

90.7
87.1
81.9

7.3
10.2
14.4

1.5
2.3
2.9

0.5
0.5
0.8

Honduras

1990
1994
1999
2003
2006

42.7
35.1
31.4
29.7
26.6

31.0
34.4
36.6
37.8
38.9

18.2
22.0
21.0
20.0
20.9

8.1
8.5
11.0
12.5
13.7

81.4
69.9
69.3
68.5
64.5

15.9
25.1
24.8
27.4
30.4

2.5
4.5
5.0
3.2
3.7

0.2
0.5
0.9
0.9
1.3

Education

Argentina a
(Greater Buenos
Aires)

412

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 31 (concluded)
POPULATION BETWEEN 25 AND 59 YEARS OF AGE, BY YEARS OF SCHOOLING, URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1989
1994
1998
2002
2004
2006

29.5
23.0
19.7
17.2
15.7
12.9

47.2
48.4
49.0
43.3
43.8
43.0

9.6
11.8
13.1
21.3
18.9
20.9

13.7
16.8
16.8
18.1
21.6
23.2

70.0
63.3
51.9
50.3
41.0
39.4

25.1
31.4
38.0
36.9
43.3
46.3

2.3
3.4
4.6
7.6
9.1
8.9

2.6
1.9
2.9
5.2
6.5
5.4

Nicaragua

1993
1998
2001

41.4
36.5
37.6

34.1
35.2
33.8

15.9
14.0
17.3

8.7
14.4
11.4

81.7
75.9
76.8

15.0
16.6
18.0

2.1
4.1
3.6

1.1
3.4
1.5

Panama

1979
1991
1994
1999
2002
2006

18.2
13.8
11.2
8.0
6.6
5.7

47.8
39.6
39.9
38.7
36.3
34.4

20.5
25.1
26.6
27.8
29.1
29.8

13.5
21.6
22.3
25.4
28.0
30.1

57.4
37.6
35.0
27.2
32.5
26.2

36.6
43.9
44.8
48.4
47.7
48.5

4.4
12.3
13.2
16.1
13.3
16.4

1.7
6.1
6.9
8.3
6.6
8.9

Paraguay
(Asunción)

1986
1990
1994
1997
2001
2005

21.6
16.9
17.9
17.0
17.5
11.3

37.5
40.5
42.1
39.0
34.6
35.5

23.3
28.1
22.9
25.5
26.7
28.6

17.6
14.6
17.1
18.5
21.3
24.5

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Peru

1999
2001
2003

21.3
22.3
20.4

13.8
15.5
13.9

35.3
31.5
31.8

29.6
30.6
33.9

69.3
63.4
61.2

15.7
18.8
19.4

10.9
12.3
13.7

4.2
5.5
5.8

Dominican
Republic

2000
2002
2006

26.4
24.7
23.0

29.0
27.7
27.6

23.5
25.7
25.9

21.1
21.9
23.6

58.6
55.8
45.2

26.6
26.8
29.1

10.4
11.7
16.2

4.3
5.7
9.5

Uruguay

1981
1990
1994
1999
2002
2005

26.6
17.2
14.5
9.2
8.0
7.0

46.4
46.3
46.3
47.8
43.7
43.2

18.2
23.6
25.3
27.4
27.2
26.6

8.8
12.8
13.8
15.6
21.1
23.1

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Venezuela
(Bol. Rep. of) d

Education

Mexico a

1981
1990
1994
1999
2002
2006

29.9
19.4
18.5
18.6
17.8
14.7

49.4
48.3
45.8
45.2
43.5
39.6

11.9
17.8
20.2
20.0
20.5
24.3

8.7
14.5
15.5
16.3
18.1
21.5

73.5
61.0
54.0
...
...
...

22.8
32.4
36.3
...
...
...

2.8
5.2
7.0
...
...
...

0.9
1.4
2.8
...
...
...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Social Panorama of Latin America • 2007

413

Table 31.1
MALE POPULATION BETWEEN 25 AND 59 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1980
1990
1994
1999
2002
2004
2006

20.9
11.2
9.1
8.1
8.5
6.6
6.8

66.1
70.1
71.9
39.8
39.0
38.5
35.7

...
...
...
31.4
28.9
30.5
31.8

13.1
18.7
19.1
20.7
23.6
24.4
25.7

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

Bolivia

1997
2002
2004

25.1
22.9
23.7

18.4
19.5
19.4

32.3
30.2
30.7

24.2
27.3
26.2

71.3
64.5
55.9

15.6
22.3
23.3

7.9
9.8
13.2

5.2
3.3
7.6

Brazil

1979
1990
1993
1999
2001
2003
2006

67.9
54.6
52.8
45.7
43.7
40.4
35.6

13.7
17.8
19.7
22.6
22.6
22.7
22.0

9.7
16.6
17.4
20.6
22.7
25.3
29.4

8.6
11.0
10.1
11.1
11.0
11.6
13.0

95.9
89.0
88.4
83.5
85.4
81.5
76.9

2.0
6.6
6.9
10.3
9.5
11.8
13.3

1.0
3.4
3.7
5.0
4.3
5.8
8.4

1.1
0.9
1.0
1.3
0.9
0.9
1.4

Chile

1990
1994
2000
2003
2006

13.9
13.0
9.0
7.9
7.8

28.6
23.6
21.8
21.0
20.2

35.2
39.4
40.5
41.9
44.3

22.3
23.9
28.7
29.2
27.7

42.8
38.3
35.1
28.7
24.4

38.7
40.4
44.2
47.0
45.1

12.9
15.0
16.2
19.0
24.1

5.6
6.3
4.5
5.3
6.4

Colombia b

1980
1990
1991
1994
1999
2002
2005

48.8
34.6
36.9
33.8
31.8
32.5
30.4

21.0
22.8
23.0
22.8
21.2
18.9
17.8

13.8
23.3
21.6
25.4
27.4
26.7
27.2

16.4
19.2
18.5
18.0
19.6
22.0
24.6

...
...
78.0
76.9
73.9
...
...

...
...
12.4
11.4
12.1
...
...

...
...
7.3
9.2
10.3
...
...

...
...
2.2
2.6
3.7
...
...

Costa Rica

1981
1990
1994
1999
2002
2006

25.4
15.0
13.4
11.7
10.3
10.8

40.3
40.1
38.3
41.8
43.2
41.5

18.4
22.1
24.5
22.0
20.9
21.7

15.8
22.9
23.7
24.5
25.7
26.1

55.5
38.1
34.3
28.2
28.0
25.0

35.9
46.6
49.9
53.2
54.4
55.1

5.9
10.7
10.3
11.3
9.4
10.8

2.7
4.7
5.5
7.3
8.2
9.2

Cuba c

2002
2006

4.2
2.8

33.6
30.9

25.5
32.9

36.7
33.5

12.1
7.2

53.2
51.4

17.6
26.1

16.9
15.3

Ecuador

1990
1994
1999
2002
2006

14.0
10.1
10.1
10.1
8.8

43.4
39.7
37.8
37.4
35.0

20.6
23.7
25.8
24.5
28.0

22.1
26.5
26.3
28.0
28.3

...
...
...
...
31.6

...
...
...
...
52.5

...
...
...
...
11.1

...
...
...
...
4.8

Education

Argentina a
(Greater Buenos
Aires)

414

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 31.1 (continued)
MALE POPULATION BETWEEN 25 AND 59 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5
El Salvador

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

29.4

32.8

20.4

17.3

75.0

20.6

3.4

1.0

25.4

31.8

22.5

20.3

70.2

24.0

4.3

1.5

2001

24.2

32.3

23.9

19.6

67.0

24.8

6.5

1.7

2004
Guatemala

1995
1999

21.0

33.3

25.4

20.2

63.2

27.5

7.5

1.8

45.3

29.9

13.9

10.9

87.9

9.9

1.6

0.6

34.2

34.6

17.9

13.3

82.2

14.1

3.1

0.6

2004
Honduras

1989
1998

34.2

33.4

21.1

11.3

76.9

19.0

3.3

0.8

1990

39.7

32.9

17.2

10.2

81.0

16.5

2.2

0.3

1994

32.3

34.3

21.9

11.5

69.0

26.8

3.6

0.6

1999

38.2

18.7

13.8

71.2

23.1

4.7

1.0

29.7

38.5

18.0

13.8

69.5

26.8

2.7

1.0

2006

26.0

39.8

19.3

14.9

65.8

29.3

3.5

1.3

1989

25.3

43.9

10.7

20.1

66.8

25.7

3.6

3.9

1994

Mexico a

29.3

2003

19.8

45.5

12.3

22.4

59.7

33.0

4.4

2.9

1998

44.3

15.7

20.9

47.5

38.2

5.4

3.6

15.5

42.2

19.9

22.4

47.4

38.9

7.4

6.2

2004

13.5

43.7

18.6

24.2

37.6

45.6

9.9

6.9

2006
Nicaragua

17.2

2002

11.1

42.5

20.3

26.2

35.6

48.7

9.2

6.4

36.6

37.4

15.3

10.6

80.3

15.9

2.1

1.6

32.3

38.0

13.9

15.8

75.8

17.5

3.4

3.3

2001
Panama

1993
1998

35.9

35.7

15.0

13.3

76.3

17.9

3.7

2.2

1979

17.6

46.8

20.4

15.1

56.5

37.3

4.5

1.7

1991

13.9

40.3

24.5

21.3

37.3

45.0

12.1

5.5
6.4

11.4

40.4

26.4

21.7

35.4

46.5

11.7

7.8

40.3

27.7

24.3

27.4

50.8

14.6

7.1

2002

6.5

38.8

29.4

25.4

31.4

51.4

12.5

4.7

2006

Education

1994
1999

5.5

37.1

30.4

26.9

24.7

51.2

16.5

7.7

Paraguay

1986

17.4

37.6

23.7

21.3

...

...

...

...

(Asunción)

1990

15.1

40.6

28.3

16.0

...

...

...

...

1994

42.2

23.3

18.8

...

...

...

...

13.3

39.4

28.5

18.9

...

...

...

...

2001

14.3

34.9

28.2

22.6

...

...

...

...

2005
Peru

15.7

1997

9.9

35.3

31.5

23.4

...

...

...

...
4.8

1999

14.6

14.2

37.7

33.5

59.3

19.9

16.0

2001

16.4

15.8

33.8

34.0

53.6

21.9

17.3

7.2

2003

14.7

13.3

34.8

37.2

52.1

22.7

18.2

6.9

Dominican

2000

25.9

30.1

23.2

20.8

56.9

28.2

9.9

5.0

Republic

2002
2006

24.8
22.9

28.5
29.7

24.9
26.9

21.8
20.5

56.8
45.6

26.4
31.3

11.7
15.1

5.1
8.0

Social Panorama of Latin America • 2007

415

Table 31.1 (concluded)
MALE POPULATION BETWEEN 25 AND 59 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas
0-5

Uruguay

Rural areas

Years of schooling

Years of schooling

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1981

26.6

47.4

18.3

7.7

...

...

...

...

1990

17.5

47.4

23.4

11.7

...

...

...

...

1994

14.7

47.7

25.7

11.9

...

...

...

...

1999

9.8

50.2

26.6

13.4

...

...

...

...

2002

Venezuela
(Bol. Rep. of) d

8.5

46.1

26.7

18.7

...

...

...

...

2005

7.7

46.1

26.3

19.9

...

...

...

...

1981

26.0

50.9

12.1

11.1

70.9

25.0

2.9

1.2

1990

17.5

49.6

17.4

15.5

58.9

34.5

5.1

1.6
2.8

1994

17.3

46.5

19.7

16.4

53.6

37.4

6.2

1999

18.4

47.1

19.7

14.8

...

...

...

...

2002

18.5

45.0

20.3

16.2

...

...

...

...

2006

16.1

41.9

23.8

18.2

...

...

...

...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Education

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

416

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 31.2
FEMALE POPULATION BETWEEN 25 AND 59 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1980
1990
1994
1999
2002
2004
2006

22.3
13.5
11.4
8.8
6.8
6.6
6.2

68.3
69.1
69.7
36.8
35.1
35.4
31.2

...
...
...
29.9
30.4
29.3
30.5

9.4
17.4
19.0
24.6
27.7
28.7
32.2

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

...
...
...
...
...
...
...

Bolivia

1997
2002
2004

42.0
38.3
41.0

16.3
17.8
16.9

24.9
21.7
21.3

16.8
22.2
20.8

85.3
85.0
78.7

8.8
10.5
11.3

3.6
2.9
5.0

2.3
1.6
5.1

Brazil

1979
1990
1993
1999
2001
2003
2006

72.0
56.2
53.9
45.0
42.7
39.3
33.9

11.6
16.4
18.4
20.6
21.3
20.9
20.3

10.3
17.0
17.9
22.9
24.1
26.5
30.6

6.1
10.3
9.8
11.5
11.9
13.3
15.3

96.2
89.4
88.1
81.7
81.8
78.2
71.8

1.8
5.9
6.7
10.2
10.3
11.7
14.5

1.1
3.9
4.2
6.6
6.5
8.5
11.3

0.9
0.8
1.0
1.6
1.3
1.6
2.4

Chile

1990
1994
2000
2003
2006

17.5
15.0
10.0
9.3
8.7

30.1
24.7
23.7
21.9
22.1

33.9
38.5
40.6
42.0
43.4

18.5
21.8
25.7
26.7
25.8

45.0
40.7
34.7
30.5
24.9

35.7
37.0
42.5
43.7
42.0

13.5
16.6
17.8
20.0
26.1

5.8
5.6
5.0
5.8
7.1

Colombia b

1980
1990
1991
1994
1999
2002
2005

55.5
39.9
42.3
37.6
34.6
33.8
30.9

23.5
23.9
23.0
23.0
21.8
19.1
18.3

13.7
22.9
21.1
25.3
27.7
26.9
27.9

7.4
13.3
13.6
14.2
16.0
20.1
23.0

...
...
78.4
75.5
71.5
...
...

...
...
12.4
12.6
12.9
...
...

...
...
7.3
9.7
11.5
...
...

...
...
2.0
2.2
4.1
...
...

Costa Rica

Education

Argentina a
(Greater Buenos
Aires)

1981
1990
1994
1999
2002
2006

28.7
18.2
14.8
13.6
11.6
10.5

42.6
40.9
40.4
40.4
41.7
40.3

17.3
22.1
25.3
22.9
22.5
21.4

11.4
18.9
19.5
23.0
24.3
27.7

60.9
42.0
35.3
29.5
29.5
25.2

31.1
43.0
48.5
50.8
51.7
52.6

5.6
10.6
11.1
12.1
11.3
12.5

2.5
4.4
5.1
7.7
7.5
9.8

Cuba c

2002
2006

4.8
2.8

33.1
31.0

23.9
29.7

38.2
36.5

14.8
9.0

55.2
54.4

16.2
22.9

13.8
13.7

Ecuador

1990
1994
1999
2002
2006

18.0
13.1
12.8
12.7
11.4

42.7
39.8
36.6
35.6
33.8

23.1
25.4
28.3
26.5
27.4

16.2
21.7
22.3
25.1
27.4

...
...
...
...
40.3

...
...
...
...
45.8

...
...
...
...
9.1

...
...
...
...
4.7

El Salvador

1995
1999
2001
2004

40.7
34.7
33.9
32.9

28.2
28.2
28.0
28.2

19.1
21.5
22.2
22.2

12.0
15.6
15.9
16.7

84.7
79.5
76.6
73.3

12.6
15.9
17.8
19.9

1.9
3.1
3.8
4.9

0.7
1.5
1.8
1.9

Guatemala

1989
1998
2004

56.7
49.0
47.4

23.9
26.2
26.9

13.7
17.1
18.0

5.8
7.6
7.6

93.4
91.3
86.5

4.9
6.8
10.3

1.3
1.5
2.4

0.3
0.4
0.9

Honduras

1990
1994
1999
2003
2006

45.1
37.4
33.1
29.7
27.1

29.6
34.5
35.4
37.2
38.1

18.9
22.1
22.8
21.6
22.1

6.4
6.0
8.7
11.5
12.7

81.8
70.8
67.6
67.6
63.3

15.4
23.5
26.3
28.0
31.4

2.7
5.3
5.3
3.7
4.0

...
0.5
0.9
0.7
1.3

Social Panorama of Latin America • 2007

417

Table 31.2 (concluded)
FEMALE POPULATION BETWEEN 25 AND 59 YEARS OF AGE, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

Mexico a

1989
1994
1998
2002
2004
2006

33.3
25.9
22.0
18.7
17.6
14.4

50.1
51.0
53.1
44.2
43.8
43.5

8.6
11.3
10.7
22.6
19.2
21.4

8.1
11.9
13.1
14.5
19.3
20.7

72.9
66.6
55.9
52.8
44.0
42.6

24.6
29.9
37.8
35.2
41.3
44.4

1.1
2.5
3.9
7.6
8.4
8.6

1.4
1.1
2.2
4.4
6.2
4.5

Nicaragua

1993
1998
2001

45.5
39.9
38.9

31.1
32.9
32.2

16.3
14.0
19.2

7.0
13.3
9.7

83.1
76.0
77.4

14.1
15.7
18.2

2.1
4.8
3.6

0.6
3.5
0.8

Panama

1979
1991
1994
1999
2002
2006

18.6
13.7
10.9
8.3
6.7
5.9

48.6
39.0
39.5
37.3
34.0
31.9

20.6
25.6
26.8
27.9
28.9
29.2

12.1
21.8
22.8
26.5
30.4
33.0

58.3
37.9
34.6
26.9
33.7
27.8

35.9
42.7
43.1
45.9
43.6
45.7

4.2
12.6
14.7
17.6
14.1
16.3

1.6
6.7
7.5
9.5
8.6
10.2

Paraguay
(Asunción)

1986
1990
1994
1997
2001
2005

25.4
18.4
19.8
20.3
20.1
12.7

37.5
40.3
42.0
38.7
34.3
35.8

22.9
27.9
22.6
22.9
25.5
26.0

14.3
13.3
15.6
18.1
20.1
25.6

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Peru

1999
2001
2003

27.2
27.5
25.6

13.6
15.3
14.5

33.1
29.6
29.1

26.2
27.7
30.8

78.5
72.8
70.1

11.8
15.8
16.1

6.1
7.5
9.2

3.6
3.9
4.7

Dominican
Republic

2000
2002
2006

26.8
24.7
23.1

28.2
27.1
25.6

23.7
26.4
24.9

21.4
21.9
26.3

60.4
54.9
44.8

25.0
27.1
26.7

10.9
11.7
17.4

3.6
6.3
11.1

1981

26.6

45.6

18.1

9.7

...

...

...

...

1990

17.0

45.4

23.9

13.7

...

...

...

...

1994

14.4

45.2

25.0

15.4

...

...

...

...

1999

8.7

45.6

28.2

17.6

...

...

...

...

2002

7.6

41.4

27.7

23.3

...

...

...

...

2005

6.5

40.8

26.8

25.9

...

...

...

...

Venezuela

1981

33.6

48.1

11.7

6.6

76.5

20.1

2.7

0.6

(Bol. Rep. of) d

1990

21.3

46.9

18.1

13.6

63.5

30.0

5.4

1.1

1994

19.6

45.1

20.7

14.6

54.4

35.0

7.9

2.8

1999

18.7

43.3

20.2

17.7

...

...

...

...

2002

17.2

42.1

20.8

20.0

...

...

...

...

2006

13.3

37.2

24.7

24.7

...

...

...

...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education,incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Education

Uruguay

418

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 32
ECONOMICALLY ACTIVE POPULATION AGED 15 AND OVER, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1980
1990
1994
1999
2002
2006

17.8
13.1
8.1
7.3
7.2
6.1

67.2
69.0
70.2
35.9
34.1
31.9

...
...
...
32.7
31.9
33.1

15.0
17.9
21.7
24.2
26.8
29.0

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Bolivia

1997
2002
2004

31.7
27.3
28.5

19.7
21.2
20.8

30.8
29.3
29.7

17.8
22.2
21.0

74.5
69.1
62.0

15.9
19.5
20.6

6.7
9.4
12.6

2.8
2.0
4.8

Brazil

1979
1990
1993
1999
2001
2003
2006

60.9
47.5
53.6
39.5
36.7
33.2
28.5

19.2
24.3
23.0
25.4
24.8
24.3
23.1

12.4
18.4
16.2
24.5
27.4
30.3
34.5

7.6
9.8
7.2
10.6
11.1
12.1
13.9

93.2
85.0
86.5
79.3
79.1
74.1
68.5

4.0
10.3
9.2
13.1
13.7
16.5
18.4

1.3
3.9
3.6
6.5
6.4
8.2
11.6

1.4
0.8
0.7
1.1
0.9
1.1
1.6

Chile

1990
1994
2000
2003
2006

13.0
11.7
8.4
7.5
7.6

26.9
22.8
21.4
19.9
19.2

36.4
40.1
42.3
44.0
45.5

23.7
25.3
27.9
28.5
27.7

36.8
34.2
32.1
26.6
22.5

40.9
40.9
42.3
42.7
39.6

15.2
17.7
20.1
24.7
30.5

7.0
7.2
5.5
6.0
7.5

Colombia b

1980
1990
1991
1994
1999
2002
2005

47.1
28.4
35.3
32.0
29.3
29.6
27.4

25.3
28.2
24.4
23.1
21.5
19.1
17.6

16.1
26.9
24.2
28.7
31.7
29.9
30.2

11.5
16.5
16.0
16.2
17.5
21.4
24.8

...
...
75.9
73.1
68.4
...
...

...
...
13.5
13.3
14.0
...
...

...
...
8.8
11.2
13.8
...
...

...
...
1.8
2.4
3.7
...
...

Costa Rica

Education

Argentina a
(Greater Buenos
Aires)

1981
1990
1994
1999
2002
2006

20.4
14.1
12.7
11.6
10.1
9.8

43.4
41.1
39.7
41.9
42.0
40.6

23.0
24.1
25.8
23.2
22.7
23.1

13.3
20.7
21.7
23.3
25.2
26.6

42.0
32.9
31.1
26.3
26.2
23.0

47.3
50.7
52.6
54.0
54.2
53.2

8.2
11.7
11.2
12.2
11.2
13.5

2.5
4.6
5.0
7.5
8.4
10.3

Cuba c

2002
2006

2.8
1.4

28.7
25.5

24.7
32.1

43.8
41.0

11.2
5.8

50.9
46.4

17.9
27.9

20.0
19.9

Ecuador

1990
1994
1999
2002
2006

14.5
11.1
11.3
12.0
10.4

43.1
39.5
38.0
37.4
34.1

24.1
27.0
28.4
25.9
29.0

18.2
22.4
22.3
24.7
26.5

...
...
...
...
35.5

...
...
...
...
48.1

...
...
...
...
12.3

...
...
...
...
4.1

El Salvador

1995
1999
2001
2004

33.7
28.9
27.6
26.1

31.5
30.3
30.6
30.8

21.3
24.2
25.5
25.9

13.5
16.5
16.3
17.3

74.2
68.0
64.2
60.1

20.9
25.0
26.9
28.8

4.0
5.4
7.1
9.2

1.0
1.6
1.8
1.8

Guatemala

1989
1998
2004

45.5
39.5
36.2

29.9
31.8
33.1

16.2
19.0
21.5

8.4
9.7
9.3

84.1
80.2
72.9

13.5
16.8
22.2

1.9
2.6
4.2

0.5
0.4
0.7

Honduras

1990
1994
1999
2003
2006

38.2
32.0
29.3
28.6
24.4

36.7
38.9
41.0
39.7
40.8

18.2
20.5
20.3
20.3
21.9

7.0
8.7
9.4
11.3
12.8

74.8
62.3
63.1
63.6
59.5

22.2
32.2
30.9
32.1
34.8

2.8
4.9
5.2
3.3
4.4

0.2
0.6
0.9
1.0
1.3

Social Panorama of Latin America • 2007

419

Table 32 (concluded)
ECONOMICALLY ACTIVE POPULATION AGED 15 AND OVER, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas
Years of schooling

Rural areas
Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1989
1994
1998
2002
2004
2006

21.7
19.0
17.3
14.7
14.3
11.8

50.4
50.0
49.7
42.9
42.8
42.2

13.2
14.0
15.2
23.5
20.8
22.6

14.6
16.9
17.8
18.9
22.1
23.4

59.8
54.6
47.1
45.2
37.1
37.3

34.1
39.4
43.7
40.1
45.4
45.5

3.5
4.0
6.3
9.7
10.6
11.9

2.6
2.0
3.0
5.0
6.9
5.3

Nicaragua

1993
1998
2001

33.5
33.8
33.6

41.0
38.0
36.7

18.1
15.3
18.8

7.4
12.9
10.9

74.1
70.9
71.8

21.4
21.8
22.6

3.5
4.4
4.4

1.1
2.9
1.2

Panama

1979
1991
1994
1999
2002
2006

14.0
11.7
9.3
7.2
7.6
5.2

46.3
37.6
38.7
36.7
34.4
32.6

25.3
29.1
29.2
29.8
30.7
31.5

14.4
21.6
22.8
26.3
27.3
30.7

47.8
34.0
32.4
26.9
34.8
28.0

42.3
45.2
45.8
48.0
45.7
46.6

7.8
14.9
15.2
16.8
13.2
16.9

2.1
5.8
6.6
8.3
6.3
8.5

Paraguay
(Asunción)

1986
1990
1994
1997
2001
2005

18.7
14.7
15.7
15.0
15.3
10.8

40.8
41.6
42.1
39.8
34.4
34.3

24.8
29.3
25.8
27.9
29.1
32.0

15.7
14.4
16.4
17.3
21.2
22.9

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Peru

1999
2001
2003

19.7
20.9
19.0

17.3
18.2
15.7

36.8
33.6
34.5

26.2
27.4
30.8

62.9
57.8
56.2

21.7
23.8
24.0

12.3
13.8
15.1

3.0
4.5
4.6

Dominican
Republic

2000
2002
2006

22.7
22.0
21.6

29.0
27.9
26.7

26.2
27.3
27.8

22.1
22.9
24.0

54.6
51.5
42.2

27.7
28.1
29.6

12.6
14.2
18.4

5.0
6.2
9.8

Uruguay

1981
1990
1994
1999
2002
2005

21.3
14.2
12.2
8.4
7.1
6.4

47.4
46.3
46.9
47.5
43.2
42.7

21.8
26.2
27.6
28.7
28.5
27.9

9.5
13.3
13.4
15.3
21.2
23.0

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Venezuela
(Bol. Rep. of) d

1981
1990
1994
1999
2002
2006

24.3
16.6
16.3
17.3
17.1
14.6

52.3
49.6
45.9
44.6
42.9
38.6

14.7
19.7
22.1
21.5
22.0
25.1

8.7
14.1
15.7
16.6
18.0
21.7

67.0
56.7
51.4
...
...
...

28.8
36.1
37.8
...
...
...

3.5
5.8
7.9
...
...
...

0.8
1.4
2.9
...
...
...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Education

Mexico a

420

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 32.1
ECONOMICALLY ACTIVE MALE POPULATION AGED 15 AND OVER, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1980
1990
1994
1999
2002
2006

18.6
12.5
8.3
7.4
7.7
6.5

68.1
71.1
73.7
40.7
38.8
35.8

...
...
...
32.7
30.7
33.9

13.3
16.3
18.0
19.2
22.7
23.8

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Bolivia

1997
2002
2004

25.7
22.0
21.9

21.0
22.0
22.5

34.3
33.0
34.2

18.9
23.0
21.4

68.2
61.6
52.7

19.1
23.5
25.1

9.0
12.6
16.5

3.6
2.4
5.7

Brazil

1979
1990
1993
1999
2001
2003
2006

63.5
51.4
53.7
43.0
40.1
36.4
31.7

19.2
23.8
23.4
26.5
26.0
25.8
24.6

10.4
16.2
15.5
21.4
24.5
27.7
32.1

7.0
8.6
7.4
9.1
9.3
10.0
11.7

93.7
87.3
87.5
81.0
80.8
75.6
70.8

3.9
9.2
8.8
12.8
13.4
16.9
18.4

1.0
2.9
3.1
5.3
5.1
6.8
9.8

1.4
0.6
0.7
0.9
0.6
0.7
1.0

Chile

1990
1994
2000
2003
2006

13.4
12.3
9.1
7.8
8.2

28.8
24.2
22.7
21.6
20.4

37.1
40.6
42.3
44.3
46.0

20.7
22.8
25.9
26.3
25.4

39.1
36.4
34.9
28.9
24.9

42.2
42.0
43.2
44.4
41.9

13.8
16.0
17.8
22.1
27.5

4.9
5.6
4.1
4.6
5.7

Colombia b

1980
1990
1991
1994
1999
2002
2005

46.8
29.8
36.8
33.8
31.1
31.8
29.9

25.3
28.6
25.5
24.1
22.0
19.7
18.4

15.3
25.4
22.5
27.0
30.1
28.7
29.1

12.7
16.1
15.2
15.1
16.7
19.7
22.6

...
...
78.4
77.0
73.3
...
...

...
...
13.0
12.8
13.2
...
...

...
...
7.2
8.4
10.9
...
...

...
...
1.4
1.8
2.6
...
...

Costa Rica

Education

Argentina a
(Greater Buenos
Aires)

1981
1990
1994
1999
2002
2006

21.7
15.7
13.9
12.2
11.0
10.9

45.6
43.1
41.7
44.9
44.9
43.8

20.5
22.4
24.7
22.1
21.6
22.5

12.2
18.8
19.7
20.7
22.4
22.8

44.9
35.7
33.9
29.1
28.9
25.7

46.3
50.9
52.7
54.7
55.2
55.0

6.9
10.0
9.5
10.6
9.4
11.7

2.0
3.4
3.9
5.7
6.4
7.6

Cuba c

2002
2006

3.5
1.8

33.8
30.3

25.1
33.2

37.5
34.8

12.6
6.8

54.0
50.5

16.8
26.8

16.7
15.9

Ecuador

1990
1994
1999
2002
2006

14.2
10.8
11.2
11.6
9.8

46.9
41.9
40.8
39.6
36.8

21.9
26.2
27.2
25.2
29.8

17.1
21.2
20.8
23.6
23.6

...
...
...
...
32.8

...
...
...
...
50.8

...
...
...
...
12.8

...
...
...
...
3.6

El Salvador

1995
1999
2001
2004

31.7
27.0
25.3
23.5

34.4
32.9
33.5
34.0

20.6
23.7
25.3
26.1

13.3
16.4
15.9
16.4

74.6
68.2
64.3
61.0

21.1
25.9
27.6
28.9

3.6
4.7
6.9
8.7

0.7
1.2
1.3
1.4

Guatemala

1989
1998
2004

45.0
36.6
33.9

32.1
35.2
35.7

14.1
17.7
21.0

8.8
10.6
9.3

84.2
78.0
71.8

14.0
19.1
24.4

1.4
2.6
3.3

0.4
0.4
0.5

Honduras

1990
1994
1999
2003
2006

39.1
32.7
30.0
30.5
26.4

38.7
39.3
42.8
41.4
43.1

15.1
19.0
17.5
17.4
18.8

7.1
9.1
9.8
10.7
11.8

76.0
64.9
65.8
66.0
62.5

22.1
31.7
29.7
30.8
33.4

1.7
2.9
3.9
2.4
3.2

0.2
0.5
0.7
0.7
0.9

Social Panorama of Latin America • 2007

421

Table 32.1 (concluded)
ECONOMICALLY ACTIVE MALE POPULATION AGED 15 AND OVER, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1989
1994
1998
2002
2004
2006

23.3
19.1
17.0
15.0
14.4
11.6

48.5
49.6
49.0
44.8
44.8
44.3

12.3
13.4
16.2
21.2
19.8
21.4

15.9
17.8
17.8
18.9
20.9
22.7

59.8
54.5
46.5
44.1
38.2
36.4

34.1
39.9
44.1
42.4
45.8
47.4

3.5
3.7
6.4
8.8
10.5
11.0

2.5
1.9
3.0
4.6
5.5
5.2

Nicaragua

1993
1998
2001

33.3
33.9
35.9

42.2
40.6
38.6

16.6
14.0
15.3

7.8
11.5
10.2

78.0
74.3
74.7

18.2
20.5
20.6

2.7
3.0
3.5

1.1
2.1
1.2

Panama

1979
1991
1994
1999
2002
2006

16.2
14.2
11.5
8.8
7.9
5.9

48.3
42.0
42.2
40.9
39.3
37.2

22.8
26.4
27.5
28.8
30.3
32.2

12.8
17.5
18.7
21.5
22.5
24.7

50.6
38.3
36.5
30.6
35.7
28.6

42.3
46.0
47.2
50.2
49.2
49.4

5.8
11.9
11.8
13.6
11.5
16.1

1.3
3.8
4.4
5.5
3.6
5.9

Paraguay
(Asunción)

1986
1990
1994
1997
2001
2005

17.5
14.6
14.9
13.1
13.9
9.2

40.8
41.5
43.3
39.6
36.4
35.6

24.3
30.0
26.2
30.8
29.8
34.5

17.4
13.8
15.6
16.5
20.0
20.6

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Peru

1999
2001
2003

15.7
17.2
15.8

17.3
18.6
16.1

40.1
36.3
36.8

26.9
27.9
31.3

54.4
50.6
48.9

25.9
27.1
26.9

16.5
17.2
19.1

3.1
5.2
5.2

Dominican
Republic

2000
2002
2006

25.6
25.1
24.2

31.6
29.7
29.9

24.4
25.6
27.4

18.4
19.6
18.4

58.1
56.9
46.6

27.5
27.7
30.6

10.1
11.4
16.2

4.4
4.0
6.6

Uruguay

1981
1990
1994
1999
2002
2005

22.9
16.0
13.8
9.8
8.4
7.7

49.6
49.4
50.5
51.8
47.8
47.1

20.4
24.3
25.7
26.6
26.9
27.0

7.2
10.3
10.0
11.8
16.8
18.3

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Venezuela
(Bol. Rep. of) d

1981
1990
1994
1999
2002
2006

25.6
17.8
18.1
19.7
19.6
17.2

53.8
52.5
48.8
48.0
45.8
42.4

12.5
17.4
19.8
19.7
20.6
24.1

8.1
12.3
13.4
12.7
14.0
16.2

68.7
58.7
55.2
...
...
...

28.0
35.8
36.8
...
...
...

2.6
4.6
6.1
...
...
...

0.6
1.0
1.9
...
...
...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Education

Mexico a

422

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 32.2
ECONOMICALLY ACTIVE FEMALE POPULATION AGED 15 AND OVER, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1980
1990
1994
1999
2002
2006

16.2
14.0
7.7
7.1
6.5
5.5

65.6
65.7
64.5
29.1
27.5
27.0

...
...
...
32.6
33.7
32.1

18.2
20.3
27.7
31.2
32.4
35.4

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Bolivia

1997
2002
2004

39.6
33.7
36.4

17.9
20.2
18.7

26.3
24.8
24.4

16.2
21.3
20.5

82.4
79.7
72.9

12.0
14.0
15.3

3.8
4.9
8.1

1.9
1.4
3.8

Brazil

1979
1990
1993
1999
2001
2003
2006

55.7
41.6
53.4
34.9
32.0
29.0
24.6

19.1
25.0
22.7
23.8
23.2
22.4
21.2

16.3
21.7
16.7
28.6
31.2
33.7
37.5

9.0
11.7
7.1
12.7
13.6
14.8
16.7

91.8
80.0
85.4
76.7
76.2
71.9
65.0

4.5
12.7
9.7
13.5
14.2
16.0
18.3

2.0
6.3
4.2
8.3
8.4
10.5
14.4

1.6
1.1
0.7
1.4
1.2
1.6
2.4

Chile

1990
1994
2000
2003
2006

12.3
10.7
7.2
6.9
6.7

23.4
20.4
19.4
17.5
17.4

35.0
39.3
42.3
43.7
44.9

29.2
29.7
31.0
31.9
31.0

25.1
25.1
22.0
19.3
16.2

34.8
36.0
39.2
37.4
33.5

22.4
25.0
28.4
32.9
38.3

17.8
13.9
10.5
10.4
12.0

Colombia b

1980
1990
1991
1994
1999
2002
2005

47.6
26.5
33.2
29.4
27.1
27.0
24.4

25.4
27.6
22.8
21.7
20.8
18.4
16.7

17.4
29.0
26.8
31.1
33.6
31.2
31.5

9.6
16.9
17.2
17.8
18.5
23.4
27.4

...
...
69.9
63.4
57.5
...
...

...
...
14.8
14.7
15.9
...
...

...
...
12.5
18.2
20.5
...
...

...
...
2.8
3.7
6.2
...
...

Costa Rica

Education

Argentina a
(Greater Buenos
Aires)

1981
1990
1994
1999
2002
2006

17.5
11.4
10.6
10.6
8.7
8.2

38.8
37.5
36.4
37.3
37.7
35.9

28.0
27.1
27.7
24.9
24.2
23.9

15.7
24.0
25.3
27.2
29.4
32.0

31.1
23.5
22.5
18.8
19.0
17.0

51.3
50.2
52.5
52.3
51.8
49.2

13.3
17.6
16.6
16.6
15.8
17.6

4.3
8.7
8.4
12.2
13.5
16.2

Cuba c

2002
2006

1.7
0.7

20.8
18.5

24.0
30.6

53.6
50.2

6.4
3.0

40.4
35.3

21.9
31.0

31.2
30.6

Ecuador

1990
1994
1999
2002
2006

15.1
11.6
11.5
12.7
11.2

36.6
35.8
34.0
34.1
30.3

28.0
28.3
30.0
26.8
27.9

20.2
24.3
24.5
26.3
30.6

...
...
...
...
39.8

...
...
...
...
43.7

...
...
...
...
11.4

...
...
...
...
5.0

El Salvador

1995
1999
2001
2004

36.2
31.3
30.4
29.2

28.0
27.3
27.2
27.0

22.0
24.8
25.6
25.6

13.8
16.7
16.8
18.2

73.0
67.7
63.9
58.0

20.3
22.7
25.3
28.5

5.0
7.0
7.7
10.4

1.7
2.7
3.1
3.0

Guatemala

1989
1998
2004

46.3
43.3
39.3

26.3
27.6
29.3

19.8
20.6
22.1

7.6
8.5
9.2

83.8
85.0
75.8

11.2
11.6
16.6

4.0
2.8
6.3

1.0
0.6
1.3

Honduras

1990
1994
1999
2003
2006

36.8
31.0
28.4
26.2
21.9

33.7
38.2
38.8
37.4
38.0

22.7
22.8
23.8
24.1
25.9

6.8
8.0
9.0
12.2
14.2

69.6
53.6
56.3
56.1
51.1

22.7
33.9
33.8
36.1
38.7

7.3
11.4
8.6
6.1
7.9

0.4
1.1
1.4
1.6
2.3

Social Panorama of Latin America • 2007

423

Table 32.2 (concluded)
ECONOMICALLY ACTIVE FEMALE POPULATION AGED 15 AND OVER, BY YEARS OF SCHOOLING,
URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

0-5

6-9

10 - 12

13 and
over

0-5

6-9

10 - 12

13 and
over

1989
1994
1998
2002
2004
2006

18.5
18.9
17.7
14.1
14.2
12.1

54.4
50.6
50.9
39.8
39.7
39.2

15.0
15.1
13.6
27.2
22.3
24.2

12.0
15.3
17.8
18.9
23.8
24.4

60.0
54.9
48.2
47.1
34.7
38.8

33.8
38.4
42.9
35.6
44.8
42.3

3.2
4.5
5.9
11.5
10.8
13.4

2.9
2.2
3.0
5.7
9.7
5.5

Nicaragua

1993
1998
2001

33.6
33.6
30.4

39.5
34.6
34.1

20.0
17.0
23.5

6.9
14.8
11.9

62.3
60.5
63.9

30.8
25.6
27.8

5.7
8.5
6.9

1.2
5.3
1.4

Panama

1979
1991
1994
1999
2002
2006

10.6
7.9
5.7
4.7
7.2
4.2

43.3
30.7
33.0
30.4
27.7
26.1

29.1
33.4
31.9
31.3
31.2
30.6

16.9
28.0
29.4
33.6
33.9
39.1

32.1
17.5
18.2
15.1
32.0
26.4

42.2
42.2
40.8
40.8
35.8
39.4

19.2
26.5
26.8
27.1
18.0
19.0

6.5
13.8
14.2
17.0
14.1
15.2

Paraguay
(Asunción)

1986
1990
1994
1997
2001
2005

20.2
14.7
16.8
17.3
17.0
12.7

40.9
41.8
40.4
40.1
32.1
32.7

25.4
28.3
25.3
24.5
28.4
29.2

13.5
15.2
17.5
18.1
22.5
25.5

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Peru

1999
2001
2003

24.6
25.5
23.0

17.3
17.6
15.2

32.9
30.2
31.6

25.2
26.7
30.2

74.6
67.6
65.6

16.1
19.5
20.5

6.6
9.3
10.0

2.8
3.7
3.9

Dominican
Republic

2000
2002
2006

18.7
17.7
17.6

25.3
25.4
21.7

28.7
29.5
28.3

27.3
27.4
32.5

45.3
38.5
30.9

28.4
29.1
26.8

19.5
21.0
24.2

6.8
11.4
18.1

Uruguay

1981
1990
1994
1999
2002
2005

18.6
11.6
10.0
6.6
5.4
4.8

43.7
42.0
42.2
42.1
37.6
37.5

24.2
29.0
30.0
31.5
30.6
29.0

13.4
17.4
17.8
19.8
26.5
28.6

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

...
...
...
...
...
...

Venezuela
(Bol. Rep. of) d

1981
1990
1994
1999
2002
2006

21.2
14.0
12.8
13.1
13.4
10.5

48.9
43.9
40.2
38.9
38.4
32.5

19.9
24.3
26.6
24.7
24.2
26.5

9.9
17.8
20.4
23.3
24.0
30.5

56.9
46.7
37.1
...
...
...

33.5
38.0
41.6
...
...
...

8.2
12.1
14.7
...
...
...

1.5
3.2
6.6
...
...
...

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Education

Mexico a

424

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 33
YEARS OF SCHOOLING COMPLETED BY THE POPULATION
BETWEEN 15 AND 24 YEARS OF AGE, BY SEX, URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

Both sexes

Males

Females

Both sexes

Males

Females

1980
1990
1994
1999
2002
2004
2006

7.8
9.0
9.1
10.1
10.4
10.5
10.6

7.8
8.9
8.8
9.8
10.2
10.3
10.3

7.7
9.2
9.4
10.5
10.6
10.7
10.8

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

Bolivia

1989
1994
2002
2004

10.2
10.0
10.1
10.0

10.6
10.3
10.2
10.2

9.9
9.7
9.9
9.8

…
…
6.6
7.8

…
…
7.2
8.4

…
…
6.0
7.3

Brazil

1979
1990
1993
1999
2001
2003
2006

6.4
6.6
6.5
7.5
7.9
8.4
8.8

6.4
6.3
6.2
7.2
7.6
8.0
8.5

6.4
6.8
6.8
7.9
8.2
8.7
9.1

4.2
3.6
3.7
4.9
5.1
5.8
6.5

4.4
3.3
3.4
4.4
4.7
5.4
6.1

4.1
4.0
4.2
5.4
5.5
6.2
6.9

Chile

1987
1990
1994
2000
2003
2006

9.9
10.1
10.4
10.6
10.9
11.0

9.9
10.0
10.3
10.6
10.8
10.9

10.0
10.2
10.5
10.7
11.0
11.1

7.4
7.9
8.2
9.0
9.4
10.0

7.1
7.6
8.0
8.7
9.3
9.8

7.6
8.1
8.4
9.2
9.6
10.1

Colombia b

1980
1990
1991
1994
1999
2002
2005

7.5
8.5
8.5
8.7
9.2
9.8
10.2

7.6
8.5
8.4
8.6
9.0
9.6
9.9

7.5
8.5
8.7
8.8
9.3
10.0
10.4

…
…
5.5
5.8
6.5
…
…

…
…
5.2
5.5
6.2
…
…

…
…
5.8
6.2
6.8
…
…

Costa Rica

1981
1990
1994
1999
2002
2006

8.8
9.1
8.8
8.8
9.0
9.2

8.7
8.9
8.8
8.6
8.8
8.9

8.9
9.3
8.8
9.0
9.1
9.5

6.7
6.9
6.6
7.0
7.1
7.7

6.6
6.7
6.5
6.8
6.9
7.4

6.8
7.2
6.7
7.1
7.3
7.9

Cuba c

2002
2006

10.4
11.0

10.1
10.8

10.7
11.3

9.2
10.3

9.0
10.2

9.4
10.5

Ecuador

1990
1994
1999
2002
2006

9.4
9.7
9.6
9.7
10.2

9.1
9.6
9.4
9.5
10.1

9.6
9.8
9.8
9.8
10.3

…
…
…
…
8.0

…
…
…
…
7.9

…
…
…
…
8.0

El Salvador

1997
1999
2001
2004

8.8
9.0
9.2
9.1

8.7
8.9
9.2
9.1

8.9
9.0
9.2
9.1

5.2
5.5
6.0
6.3

5.2
5.5
6.0
6.3

5.1
5.5
5.9
6.4

Guatemala

1989
1998
2004

6.7
7.5
7.6

7.3
7.6
8.0

6.2
7.5
7.3

2.9
3.6
4.3

3.4
4.1
4.8

2.4
3.1
3.9

Argentina a

Education

(Greater Buenos Aires)

Social Panorama of Latin America • 2007

425

Table 33 (concluded)
YEARS OF SCHOOLING COMPLETED BY THE POPULATION
BETWEEN 15 AND 24 YEARS OF AGE, BY SEX, URBAN AND RURAL AREAS, 1980-2006
(Percentages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

Males

Females

Both sexes

Males

Females

1990
1994
1999
2003
2006

7.0
7.3
7.6
7.9
8.3

6.9
7.2
7.3
7.6
8.1

7.0
7.4
7.8
8.1
8.5

4.1
4.8
4.9
4.9
5.5

3.9
4.7
4.7
4.7
5.1

4.3
5.0
5.1
5.1
5.9

Mexico a

1984
1989
1994
2002
2004
2006

9.7
8.7
8.9
9.8
10.0
10.1

9.9
8.9
9.0
9.9
9.8
10.0

9.5
8.6
8.8
9.8
10.1
10.3

8.3
6.8
7.0
7.9
8.2
8.5

8.5
6.8
6.9
7.9
8.2
8.5

8.1
6.7
7.1
7.9
8.2
8.5

Nicaragua

1993
1998
2001

7.0
7.5
7.9

6.8
7.2
7.4

7.2
7.8
8.3

3.6
4.2
4.3

3.3
3.8
4.0

4.0
4.6
4.6

Panama

1979
1991
1994
1999
2002
2006

9.2
9.6
9.6
10.0
10.2
10.6

9.0
9.2
9.3
9.8
9.9
10.4

9.3
9.9
9.9
10.3
10.5
10.9

6.9
7.6
7.6
8.0
7.4
8.1

6.8
7.3
7.3
7.6
7.3
8.0

7.0
8.0
8.1
8.4
7.5
8.1

Paraguay
(Asunción)

1986
1990
1994
2001
2005

8.7
9.3
9.1
9.6
10.0

9.0
9.5
9.1
9.6
10.0

8.5
9.1
9.0
9.6
10.0

…
…
…
…
…

…
…
…
…
…

…
…
…
…
…

Peru

1997
2001
2003

9.0
10.1
10.6

9.0
10.2
10.5

9.0
10.1
10.6

6.1
7.6
7.8

6.4
7.9
8.2

5.7
7.2
7.2

Dominican
Republic

2000
2002
2006

9.4
9.5
9.7

8.8
9.1
9.2

9.9
9.9
10.2

6.7
7.1
8.3

6.3
6.5
7.7

7.2
7.9
9.0

Uruguay

1981
1990
1994
1999
2002
2005

8.6
9.2
9.2
9.5
9.6
9.7

8.4
8.9
8.9
9.1
9.2
9.4

8.7
9.4
9.5
9.8
10.0
10.0

…
…
…
…
…
…

…
…
…
…
…
…

…
…
…
…
…
…

Venezuela
(Rep. Bol.de) d

1981
1990
1994
1999
2002
2006

8.0
8.4
8.7
8.8
8.9
9.6

7.7
8.2
8.4
8.2
8.5
9.1

8.2
8.7
9.1
9.3
9.4
10.2

5.1
5.7
6.0
…
…
…

4.9
5.2
5.7
…
…
…

5.4
6.2
6.4
…
…
…

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Education

Both sexes
Honduras

426

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 34
YEARS OF SCHOOLING COMPLETED BY THE POPULATION
BETWEEN 25 AND 59 YEARS OF AGE, BY SEX, URBAN AND RURAL AREAS, 1980-2006
(Averages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

Both sexes

Males

Females

Both sexes

Males

Females

1980
1990
1994
1999
2002
2004
2006

7.4
8.8
9.0
10.2
10.5
10.5
10.9

7.0
8.9
9.0
10.1
10.2
10.4
10.6

7.7
8.8
9.0
10.3
10.7
10.7
11.2

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

Bolivia

1989
1994
2002
2004

8.8
9.3
9.2
8.9

9.9
10.3
10.1
9.9

7.8
8.3
8.3
8.0

…
…
4.0
4.9

…
…
5.1
6.1

…
…
3.0
3.7

Brazil

1979
1990
1993
1999
2001
2003
2006

5.1
6.2
6.3
7.0
7.2
7.5
8.0

5.3
6.3
6.4
6.9
7.1
7.4
7.9

4.9
6.1
6.2
7.1
7.2
7.6
8.2

2.4
2.6
2.7
3.3
3.2
3.6
4.0

2.5
2.6
2.7
3.2
3.0
3.3
3.8

2.3
2.6
2.8
3.4
3.4
3.8
4.4

Chile

1987
1990
1994
2000
2003
2006

9.3
9.7
10.2
10.9
11.1
11.1

9.7
10.1
10.4
11.1
11.3
11.3

9.0
9.4
10.0
10.7
10.9
11.0

5.5
6.2
6.6
6.8
7.3
7.9

5.6
6.2
6.7
6.8
7.3
7.8

5.5
6.1
6.5
6.9
7.3
7.9

Colombia b

1980
1990
1991
1994
1999
2002
2005

6.8
8.2
8.1
8.3
8.6
9.3
9.7

7.4
8.6
8.5
8.6
8.9
9.4
9.8

6.2
7.8
7.8
8.1
8.4
9.2
9.6

…
…
4.1
4.4
4.8
…
…

…
…
4.1
4.3
4.7
…
…

…
…
4.1
4.4
4.9
…
…

Costa Rica

1981
1990
1994
1999
2002
2006

7.5
9.6
9.1
9.3
9.4
9.7

7.9
10.0
9.3
9.4
9.5
9.6

7.3
9.3
8.9
9.1
9.3
9.7

4.6
6.3
6.0
6.5
6.5
6.9

4.7
6.6
6.0
6.5
6.5
6.8

4.5
6.0
6.0
6.5
6.5
7.0

Cuba c

2002
2006

10.9
11.3

10.9
11.2

10.9
11.3

8.6
9.2

8.8
9.4

8.4
9.0

Ecuador

1990
1994
1999
2002
2006

8.9
9.7
9.9
10.1
10.3

9.2
10.0
10.1
10.3
10.5

8.6
9.5
9.7
9.9
10.2

…
…
…
…
5.8

…
…
…
…
6.1

…
…
…
…
5.5

El Salvador

1997
1999
2001
2004

7.9
8.2
8.3
8.6

8.7
8.8
8.9
9.3

7.4
7.7
7.9
8.0

2.9
3.2
3.5
3.8

3.3
3.6
3.9
4.3

2.6
2.9
3.2
3.5

Guatemala

1989
1998
2004

5.6
6.5
6.5

6.4
7.2
7.3

4.9
5.8
5.8

1.5
1.9
2.4

1.9
2.4
2.9

1.1
1.4
1.9

Education

Argentina a
(Greater Buenos Aires)

Social Panorama of Latin America • 2007

427

Table 34 (concluded)
YEARS OF SCHOOLING COMPLETED BY THE POPULATION
BETWEEN 25 AND 59 YEARS OF AGE, BY SEX, URBAN AND RURAL AREAS, 1980-2006
(Averages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

Both sexes

Males

Females

Both sexes

Males

Females

1990
1994
1999
2003
2006

6.4
7.0
7.3
7.5
7.8

6.8
7.5
7.6
7.5
7.9

6.1
6.6
7.1
7.4
7.7

2.5
3.4
3.5
3.5
3.8

2.6
3.4
3.5
3.4
3.7

2.4
3.4
3.6
3.6
3.8

Mexico a

1984
1989
1994
2002
2004
2006

8.4
7.5
8.0
9.1
9.4
9.8

8.8
8.1
8.5
9.6
9.8
10.2

8.1
7.0
7.6
8.7
9.0
9.5

6.9
4.7
5.0
5.3
6.2
6.1

7.1
5.0
5.3
5.5
6.5
6.5

6.7
4.5
4.8
5.1
5.9
5.8

Nicaragua

1993
1998
2001

6.4
7.0
6.9

6.8
7.4
7.1

6.0
6.6
6.7

2.4
3.2
3.1

2.4
3.2
3.2

2.3
3.2
3.0

Panama

1979
1991
1994
1999
2002
2006

8.5
9.6
9.9
10.4
10.8
11.1

8.6
9.6
9.9
10.4
10.6
10.9

8.3
9.7
10.0
10.5
11.0
11.3

4.4
6.1
6.4
7.1
6.4
7.1

4.4
6.1
6.3
6.9
6.3
7.1

4.3
6.2
6.6
7.2
6.5
7.1

Paraguay
(Asunción)

1986
1990
1994
2001
2005

8.8
9.0
8.9
9.6
10.1

9.4
9.3
9.2
9.9
10.3

8.3
8.8
8.6
9.3
10.0

…
…
…
…
…

…
…
…
…
…

…
…
…
…
…

Peru

1999
2001
2003

10.1
10.2
10.6

10.9
10.9
11.3

9.5
9.6
10.0

4.6
5.1
5.3

5.7
6.3
6.4

3.6
3.9
4.3

Dominican
Republic

2000
2002
2006

8.9
9.1
9.4

8.9
9.1
9.2

8.9
9.1
9.5

5.1
5.4
6.5

5.2
5.2
6.2

5.0
5.6
6.7

Uruguay

1981
1990
1994
1999
2002
2005

7.3
8.3
8.6
9.2
9.7
9.9

7.3
8.3
8.6
9.0
9.5
9.6

7.3
8.4
8.7
9.3
9.9
10.2

…
…
…
…
…
…

…
…
…
…
…
…

…
…
…
…
…
…

Venezuela
(Bol. Rep. of) d

1981
1990
1994
1999
2002
2006

6.8
8.2
8.3
8.3
8.6
9.2

7.3
8.4
8.4
8.2
8.3
8.8

6.4
8.0
8.1
8.5
8.8
9.5

3.1
4.0
4.7
…
…
…

3.3
4.2
4.7
…
…
…

2.7
3.8
4.6
…
…
…

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Education

Honduras

428

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 35
YEARS OF SCHOOLING COMPLETED BY THE ECONOMICALLY ACTIVE POPULATION AGED 15 AND OVER,
BY SEX, URBAN AND RURAL AREAS, 1980-2006
(Averages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

Both sexes

Males

Females

Both sexes

Males

Females

1980
1990
1994
1999
2002
2004
2006

7.4
8.7
9.3
10.4
10.7
10.7
11.0

7.0
8.6
9.0
10.0
10.2
10.3
10.6

8.2
8.9
9.7
11.1
11.2
11.1
11.7

…
…
…
…
…
…
…

…
…
…
…
…
…
…

…
…
…
…
…
…
…

Bolivia

1989
1994
2002
2004

9.0
9.3
9.2
9.0

9.7
10.0
9.8
9.7

8.2
8.5
8.6
8.3

…
…
4.5
5.1

…
…
5.3
6.1

…
…
3.3
3.9

Brazil

1979
1990
1993
1999
2001
2003
2006

5.9
6.7
6.0
7.3
7.6
8.0
8.5

5.6
6.3
6.0
6.9
7.2
7.5
8.1

6.4
7.2
6.0
7.9
8.1
8.5
9.0

3.1
3.0
2.8
3.5
3.5
3.9
4.4

3.0
2.7
2.7
3.3
3.3
3.7
4.1

3.4
3.5
2.9
3.8
3.8
4.3
4.8

Chile

1987
1990
1994
2000
2003
2006

9.9
10.2
10.6
11.1
11.3
11.3

9.7
10.0
10.4
10.9
11.2
11.1

10.3
10.6
10.9
11.4
11.6
11.6

6.2
6.7
7.1
7.2
7.7
8.3

5.9
6.4
6.8
6.8
7.4
7.9

7.6
8.5
8.4
8.4
8.8
9.3

Colombia b

1980
1990
1991
1994
1999
2002
2005

7.1
8.7
8.4
8.6
8.9
9.5
9.9

7.2
8.6
8.2
8.4
8.7
9.2
9.6

6.9
8.8
8.6
8.9
9.1
9.8
10.3

…
…
4.3
4.7
5.1
…
…

…
…
4.1
4.3
4.7
…
…

…
…
4.9
5.6
6.1
…
…

Costa Rica

1981
1990
1994
1999
2002
2006

8.1
10.1
9.2
9.3
9.5
9.8

7.8
9.7
9.0
9.1
9.2
9.4

8.6
10.6
9.7
9.7
10.0
10.3

5.4
6.7
6.2
6.6
6.7
7.1

5.2
6.4
5.9
6.3
6.3
6.7

6.3
7.8
7.1
7.5
7.7
8.1

Cuba c

2006

11.7

11.4

12.5

9.8

9.5

10.8

Ecuador

1990
1994
1999
2002
2006

9.0
9.7
9.8
9.9
10.3

8.8
9.6
9.6
9.8
10.1

9.3
10.0
10.0
10.0
10.5

…
…
…
…
5.9

…
…
…
…
6.0

…
…
…
…
5.7

El Salvador

1997
1999
2001
2004

8.1
8.3
8.5
8.7

8.2
8.5
8.6
8.8

7.9
8.2
8.3
8.5

3.5
3.9
4.2
4.6

3.5
3.8
4.1
4.5

3.6
4.0
4.4
4.9

Guatemala

1989
1998
2004

6.1
6.7
6.9

6.2
6.9
7.1

6.0
6.4
6.6

2.2
2.5
3.1

2.2
2.7
3.2

2.2
2.1
3.1

Education

Argentina a
(Greater Buenos Aires)

Social Panorama of Latin America • 2007

429

Table 35 (concluded)
YEARS OF SCHOOLING COMPLETED BY THE ECONOMICALLY ACTIVE POPULATION AGED 15 AND OVER,
BY SEX, URBAN AND RURAL AREAS, 1980-2006
(Averages)
Country

Year

Urban areas

Rural areas

Years of schooling

Years of schooling

Both sexes

Males

Females

Both sexes

Males

Females

1990
1994
1999
2003
2006

6.5
7.1
7.2
7.4
7.9

6.4
7.1
7.1
7.2
7.6

6.8
7.2
7.4
7.8
8.3

2.9
3.8
3.8
3.8
4.0

2.8
3.6
3.6
3.5
3.8

3.4
4.7
4.4
4.4
4.8

Mexico a

1984
1989
1994
2002
2004
2006

8.9
8.0
8.3
9.4
9.6
10.0

8.8
8.0
8.3
9.4
9.5
9.9

9.0
8.1
8.3
9.6
9.8
10.0

7.2
5.2
5.5
5.6
6.4
6.4

7.2
5.2
5.5
5.6
6.3
6.4

7.3
5.2
5.5
5.6
6.7
6.3

Nicaragua

1993
1998
2001

6.8
7.1
7.1

6.8
7.0
6.8

6.9
7.3
7.5

3.0
3.5
3.4

2.7
3.2
3.2

4.1
4.6
4.1

Panama

1979
1991
1994
1999
2002
2006

8.9
9.9
10.2
10.6
10.7
11.2

8.6
9.2
9.6
10.1
10.3
10.7

9.5
10.8
11.0
11.5
11.3
12.0

5.0
6.4
6.6
7.1
6.3
7.0

4.7
5.8
6.0
6.5
5.9
6.7

6.8
8.6
8.6
9.0
7.3
7.7

Paraguay
(Asunción)

1986
1990
1994
2001
2005

8.9
9.2
9.1
9.7
10.1

9.1
9.2
9.1
9.8
10.2

8.6
9.1
9.1
9.7
10.1

…
…
…
…
…

…
…
…
…
…

…
…
…
…
…

Peru

1999
2001
2003

10.0
10.0
10.4

10.4
10.4
10.8

9.4
9.6
10.0

4.8
5.3
5.4

5.6
6.1
6.3

3.7
4.1
4.3

Dominican
Republic

2000
2002
2006

9.3
9.4
9.5

8.8
8.9
8.9

10.0
10.0
10.4

5.5
5.8
6.7

5.1
5.1
6.1

6.5
7.2
8.4

Uruguay

1981
1990
1994
1999
2002
2005

7.8
8.6
8.8
9.3
9.8
10.0

7.5
8.2
8.4
8.9
9.3
9.5

8.2
9.2
9.3
9.8
10.4
10.6

…
…
…
…
…
…

…
…
…
…
…
…

…
…
…
…
…
…

Venezuela
(Bol. Rep. of) d

1981
1990
1994
1999
2002
2006

7.2
8.4
8.5
8.5
8.6
9.2

7.0
8.1
8.1
7.9
8.1
8.6

7.7
9.2
9.3
9.5
9.4
10.3

3.5
4.3
4.9
…
…
…

3.4
4.1
4.6
…
…
…

4.3
5.3
6.3
…
…
…

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

Information from which the number of years of schooling could be calculated became available for Mexico in 1996 and for Argentina in 1997. The
figures for previous years are estimates based on the categories of incomplete primary education, complete primary education, incomplete secondary,
complete secondary and higher education.
b In 1993, the survey’s geographical coverage was extended to include nearly the entire urban population of the country. Up to 1992, the survey covered
approximately half the urban population, except in 1991, when a nationwide survey was conducted. The figures for 1980 and 1990 therefore refer to
eight major cities only.
c Figures supplied by the National Statistical Office (ONE) of Cuba, on the basis of the 2002 population and housing census and the 2006 National
Employment Survey.
d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas and the figures therefore refer to the
nationwide total.

Education

Honduras

430

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 36
CLASSIFICATION OF YOUNG PEOPLE AGED 15 TO 19 BY EDUCATIONAL STATUS, NATIONAL TOTAL, AROUND 2006 a
(Percentages)
Country

Year

Sex

Educational status

Total

Dropouts

Students and graduates

Did not
Early
Dropouts Dropouts Dropouts at Dropout Students Students Up-to- Graduates Subtotal
enter
dropouts at end of in lower
end of lower subtotal who who are date
students
educational (during
primary secondary secondary or
are far slightly students
and
system
primary
cycle
cycle
during upper
behind behind
graduates
cycle)
secondary
cycle

Bolivia

21.9

36.9

9.7

9.8

29.5

13.5

62.5

100.0

3.4

22.1

35.3

11.0

9.5

30.6

12.9

64.0

100.0

0.8

10.1

3.3

3.4

21.7

38.5

8.4

10.0

28.3

14.1

60.8

100.0

2006 Both sexes

1.3

2.2

2.5

9.0

7.6

21.3

18.1

10.5

33.6

15.1

77.3

100.0

1.6

3.0

2.9

9.7

7.6

23.2

21.7

11.0

30.2

12.4

75.3

100.0

0.9

1.5

2.2

8.4

7.6

19.7

14.5

9.9

37.1

17.9

79.4

100.0

2006 Both sexes

0.2

0.8

0.7

0.9

9.7

12.1

4.7

12.1

51.1

19.7

87.6

100.0

Males

0.3

1.0

0.7

1.1

10.3

13.1

6.1

12.5

49.2

18.8

86.6

100.0

Females

0.2

0.6

0.7

0.8

9.1

11.2

3.3

11.6

53.1

20.5

88.5

100.0

2005 Both sexes

1.6

5.9

7.4

6.4

6.0

25.7

13.6

10.0

24.0

25.3

72.9

100.0

Males

2.0

7.2

8.0

6.5

5.7

27.4

16.0

10.4

22.4

21.8

70.6

100.0

Females

1.1

4.5

6.8

6.3

6.2

23.8

11.2

9.5

25.5

28.7

74.9

100.0

2006 Both sexes

0.7

5.6

16.4

4.8

3.1

29.9

20.9

12.0

23.3

13.2

69.4

100.0

Males

0.9

6.3

17.9

4.5

3.4

32.1

22.2

11.8

21.5

11.5

67.0

100.0

Females
Ecuador

3.4

2.7

Females

Costa Rica

3.0

7.1

Males

Colombia

8.6

0.6

Females

Chile

0.7

Males

Brazil

2004 Both sexes

0.5

4.9

14.8

5.1

2.8

27.6

19.6

12.1

25.2

14.9

71.8

100.0

Education

3.6

7.8

12.1

7.3

30.8

7.0

6.7

38.0

16.6

68.3

100.0

1.1

3.7

7.9

12.5

6.9

31.0

7.9

7.2

37.5

15.3

67.9

100.0

Females

0.9

3.4

7.7

11.6

7.8

30.5

6.0

6.2

38.4

17.9

68.5

100.0

2004 Both sexes

4.2

14.6

5.8

6.0

8.3

34.7

10.8

8.1

33.3

9.0

61.2

100.0

Males

4.5

14.9

5.4

4.6

8.0

32.9

13.2

8.6

32.4

8.4

62.6

100.0

Females

3.8

14.3

6.2

7.5

8.6

36.6

8.3

7.6

34.2

9.5

59.6

100.0

2004 Both sexes

11.5

23.1

15.9

3.8

4.1

46.9

12.7

6.5

19.9

2.5

41.6

100.0

Males

7.7

19.6

17.0

4.8

4.3

45.7

15.6

7.9

20.0

3.0

46.5

100.0

15.1

26.4

14.9

2.8

3.8

47.9

9.9

5.2

19.8

2.1

37.0

100.0

2006 Both sexes

4.9

14.0

24.9

3.8

4.2

46.9

10.6

6.8

26.2

4.6

48.2

100.0

Males

6.0

15.2

26.4

3.9

4.1

49.6

10.4

6.8

23.3

4.0

44.5

100.0

Females

3.8

12.9

23.4

3.7

4.3

44.3

10.9

6.8

29.0

5.2

51.9

100.0

2006 Both sexes

1.2

3.3

7.6

5.8

20.8

37.5

4.7

6.6

35.8

14.3

61.4

100.0

Males

1.3

3.5

7.7

6.1

21.2

38.5

5.2

8.1

34.5

12.3

60.1

100.0

Females

Guatemala

1.0

Males

El Salvador

2006 Both sexes

1.1

3.0

7.5

5.4

20.3

36.2

4.2

5.0

37.2

16.4

62.8

100.0

Females
Honduras

Mexico

Nicaragua

2001 Both sexes

10.6

17.6

10.2

6.8

2.1

36.7

14.9

8.8

18.6

10.2

52.5

100.0

Males

12.9

20.8

10.5

6.8

2.2

40.3

15.7

9.5

14.7

7.1

47.0

100.0

8.2

14.3

10.0

6.9

2.1

33.3

14.2

8.1

22.7

13.5

58.5

100.0

Females

Social Panorama of Latin America • 2007

431

Table 36 (concluded)
CLASSIFICATION OF YOUNG PEOPLE AGED 15 TO 19 BY EDUCATIONAL STATUS, NATIONAL TOTAL, AROUND 2006 a
(Percentages)
Country

Year

Sex

Educational status

Total

Dropouts

Students and graduates

Did not
Early
Dropouts Dropouts Dropouts at Dropout Students Students Up-to- Graduates Subtotal
enter
dropouts at end of in lower
end of lower subtotal who who are date
students
educational (during
primary secondary secondary or
are far slightly students
and
system
primary
cycle
cycle
during upper
behind behind
graduates
cycle)
secondary
cycle

Panama

1.6

2.9

9.8

6.4

6.0

25.1

8.2

8.3

40.5

16.2

73.2

100.0

Males

0.8

3.6

10.1

7.6

6.6

27.9

10.3

9.5

37.9

13.5

71.2

100.0

Females
Paraguay

2006 Both sexes

2.5

2.3

9.4

5.3

5.3

22.3

6.0

7.2

43.2

18.9

75.3

100.0

7.1

32.2

12.1

12.6

33.0

9.3

67.0

100.0

5.4

6.8

33.3

13.2

14.5

29.3

8.8

65.8

100.0

0.6

5.8

10.8

6.9

7.4

30.9

11.0

10.7

36.8

9.9

68.4

100.0

2003 Both sexes

0.9

6.1

7.5

6.1

11.4

31.1

8.9

6.2

20.6

32.2

67.9

100.0

0.6

4.9

6.4

6.4

11.3

29.0

10.0

7.2

21.1

32.0

70.3

100.0

1.1

7.5

8.6

5.8

11.5

33.4

7.7

5.1

20.2

32.5

65.5

100.0

2006 Both sexes

1.9

5.2

1.7

1.9

6.7

15.5

13.8

9.8

45.2

13.8

82.6

100.0

Males

2.6

7.0

1.6

2.1

6.9

17.6

16.9

10.7

41.4

10.9

79.9

100.0

Females

1.2

3.3

1.9

1.7

6.6

13.5

10.4

8.8

49.3

16.8

85.3

100.0

2006 Both sexes

1.5

4.3

6.8

5.9

3.7

20.7

11.5

8.2

27.2

30.9

77.8

100.0

Males

1.8

5.8

8.4

6.6

3.5

24.3

13.6

9.5

24.6

26.1

73.8

100.0

Females

(Bol. Rep. of)

6.2

10.8

Females

Venezuela

10.8

10.3

Males

Republic

8.1

0.9

Females

Dominican

0.7

Males

Peru

2005 Both sexes

1.2

2.8

5.2

5.1

3.8

16.9

9.3

6.9

29.8

35.9

81.9

100.0

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
The methodology for calculating dropout rates is described in ECLAC, Social Panorama of Latin America 2001-2002 (LC/G.2183-P), Santiago, Chile,
October 2002, box III.1, except that the division into cycles is based strictly on the International Standard Classification of Education (ISCED) 1997.

Education

a

432

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 37
CLASSIFICATION OF YOUNG PEOPLE AGED 15 TO 19 BY EDUCATIONAL STATUS, URBAN AREAS, AROUND 2006 a
(Percentages)
Country

Year

Sex

Educational status

Total

Dropouts
Did not
Early
enter
dropouts
educational (during
system
primary
cycle)

Argentina

Students and graduates

Dropouts Dropouts Dropouts at Subtotal Students Students Up-to- Graduates Subtotal
at end of in lower
end of lower dropouts who who are date
students
primary secondary secondary or
are far slightly students
and
cycle
cycle
during upper
behind behind
graduates
secondary
cycle

0.2

0.8

1.0

11.5

4.5

17.8

14.5

14.7

21.1

31.8

82.1

100.0

Males

0.3

1.1

1.1

13.1

4.4

19.7

15.0

14.9

19.8

30.2

79.9

100.0

Females
Bolivia

2006 Both sexes

0.1

0.5

0.9

9.9

4.6

15.9

13.9

14.5

22.2

33.5

84.1

100.0

0.6

5.1

2.3

3.1

20.9

31.4

8.7

10.5

32.2

16.5

67.9

100.0

Males

0.6

3.6

1.9

2.9

21.6

30.0

9.8

11.2

32.9

15.6

69.5

100.0

Females
Brazil

2004 Both sexes

0.6

6.5

2.6

3.3

20.3

32.7

7.7

10.0

31.6

17.4

66.7

100.0

1.6

1.9

8.1

7.8

19.4

15.5

10.5

36.4

17.2

79.6

100.0

1.3

2.1

2.2

8.8

8.0

21.1

18.9

11.4

33.1

14.2

77.6

100.0

Females

0.7

1.1

1.5

7.5

7.6

17.7

12.2

9.7

39.7

20.1

81.7

100.0

2006 Both sexes

0.2

0.8

0.6

0.8

9.1

11.3

4.5

12.0

51.7

20.3

88.5

100.0

Males

0.3

0.9

0.6

0.9

9.7

12.1

5.9

12.3

50.1

19.3

87.6

100.0

Females
Colombia

1.0

Males

Chile

2006 Both sexes

0.1

0.6

0.6

0.7

8.5

10.4

3.1

11.8

53.3

21.4

89.6

100.0

1.0

3.0

4.0

5.4

5.9

18.3

11.7

10.4

27.7

30.8

80.6

100.0

Males

1.2

3.5

4.3

5.7

5.7

19.2

14.2

11.6

26.6

27.2

79.6

100.0

Females
Costa Rica

2005 Both sexes

0.8

2.4

3.8

5.2

6.0

17.4

9.5

9.3

28.8

34.2

81.8

100.0

3.3

11.3

5.1

2.9

22.6

21.8

12.3

26.9

16.1

77.1

100.0

0.2

3.8

12.8

3.9

3.0

23.5

23.4

13.0

25.7

14.2

76.3

100.0

Females

0.3

2.8

9.8

6.4

2.7

21.7

20.2

11.6

28.2

18.0

78.0

100.0

2006 Both sexes

0.6

2.1

4.6

8.3

7.7

22.7

6.1

6.1

43.3

21.2

76.7

100.0

Males

Education

0.2

Males

0.7

1.8

4.6

9.1

7.5

23.0

6.8

6.6

43.0

19.8

76.2

100.0

Females

Ecuador

2006 Both sexes

0.4

2.3

4.6

7.4

7.9

22.2

5.4

5.6

43.7

22.6

77.3

100.0

El Salvador 2004 Both sexes

8.3

3.7

5.0

7.6

24.6

8.7

8.7

42.7

13.2

73.3

100.0

2.2

8.7

3.3

3.6

7.3

22.9

10.5

8.0

43.9

12.7

75.1

100.0

Females
Guatemala

2.2

Males

2.2

7.9

4.0

6.4

7.8

26.1

6.9

9.4

41.6

13.6

71.5

100.0
100.0

15.9

13.3

5.2

6.3

40.7

9.3

7.7

31.8

5.2

54.0

3.6

13.2

13.2

6.0

6.9

39.3

11.8

8.0

31.3

6.0

57.1

100.0

Females

6.8

18.5

13.3

4.5

5.7

42.0

7.0

7.5

32.3

4.4

51.2

100.0

2006 Both sexes

2.1

6.6

15.7

4.7

4.6

31.6

10.9

8.4

38.6

8.4

66.3

100.0

Males

2.5

7.1

17.7

4.9

4.7

34.4

10.8

8.7

35.7

7.9

63.1

100.0

Females
Mexico

5.3

Males

Honduras

2004 Both sexes

1.8

6.1

13.9

4.6

4.6

29.2

11.0

8.0

41.1

8.8

68.9

100.0

2006 Both sexes

0.6

1.9

5.7

6.0

19.0

32.6

4.5

6.7

38.8

16.8

66.8

100.0

Males

0.6

2.3

5.6

7.0

18.7

33.6

5.0

8.4

37.9

14.5

65.8

100.0

Females

0.5

1.5

5.8

5.0

19.3

31.6

3.9

4.9

39.8

19.3

67.9

100.0

Social Panorama of Latin America • 2007

433

Table 37 (concluded)
CLASSIFICATION OF YOUNG PEOPLE AGED 15 TO 19 BY EDUCATIONAL STATUS, URBAN AREAS, AROUND 2006 a
(Percentages)
Country

Year

Sex

Educational status

Total

Dropouts
Did not
Early
enter
dropouts
educational (during
system
primary
cycle)

Nicaragua

Students and graduates

Dropouts Dropouts Dropouts at Subtotal Students Students Up-to- Graduates Subtotal
at end of in lower
end of lower dropouts who who are date
students
primary secondary secondary or
are far slightly students
and
cycle
cycle
during upper
behind behind
graduates
secondary
cycle

9.5

8.8

8.2

2.5

29.0

13.7

11.3

25.5

15.6

66.1

100.0

6.2

11.9

10.0

9.1

3.0

34.0

15.0

13.5

20.6

10.9

60.0

100.0

Females

3.7

7.3

7.6

7.3

2.1

24.3

12.5

9.2

30.2

20.1

72.0

100.0

2006 Both sexes

0.4

1.1

4.6

6.1

5.6

17.4

6.9

9.0

45.8

20.4

82.1

100.0

Males

0.3

1.5

4.8

7.6

6.8

20.7

8.8

10.4

42.9

17.0

79.1

100.0

Females
Paraguay

4.9

Males

Panama

2001 Both sexes

0.5

0.8

4.4

4.6

4.5

14.3

5.0

7.7

48.6

23.7

85.0

100.0

0.5

3.9

6.2

4.4

7.4

21.9

12.0

14.2

38.2

13.2

77.6

100.0

Males

0.2

4.7

6.0

3.4

7.0

21.1

11.8

18.4

36.1

12.5

78.8

100.0

Females
Peru

2005 Both sexes

0.7

3.3

6.3

5.4

7.8

22.8

12.2

10.4

40.2

13.8

76.6

100.0

0.5

2.6

3.2

4.8

11.3

21.9

6.8

5.5

23.9

41.3

77.5

100.0

Males

0.5

2.5

3.2

4.7

11.0

21.4

6.8

6.5

24.3

40.5

78.1

100.0

Females
Dominican

2003 Both sexes

0.5

2.6

3.3

4.8

11.7

22.4

6.8

4.5

23.6

42.2

77.1

100.0
100.0

1.4

4.3

1.6

1.8

7.0

14.7

11.6

9.5

47.3

15.4

83.8

Males

1.9

5.3

1.3

2.2

8.0

16.8

13.8

10.5

44.4

12.6

81.3

100.0

0.9

3.3

1.8

1.4

6.1

12.6

9.5

8.6

50.2

18.1

86.4

100.0

2005 Both sexes

0.2

2.4

8.9

8.5

9.5

29.3

10.3

10.5

39.6

10.0

70.4

100.0

Males

0.4

3.2

10.8

8.9

9.1

32.0

12.1

11.2

36.1

8.1

67.5

100.0

Females

Uruguay

2006 Both sexes
Females

Republic

0.0

1.6

6.9

8.1

9.9

26.5

8.3

9.9

43.2

12.1

73.5

100.0

a

The methodology for calculating dropout rates is described in ECLAC, Social Panorama of Latin America 2001-2002 (LC/G.2183-P), Santiago, Chile,
October 2002, box III.1, except that the division into cycles is based strictly on the International Standard Classification of Education (ISCED) 1997.

Education

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.

434

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 38
CLASSIFICATION OF YOUNG PEOPLE AGED 15 TO 19 BY EDUCATIONAL STATUS THROUGHOUT THE SCHOOL CYCLE,
RURAL AREAS, AROUND 2006 a
(Percentages)
Country

Year

Sex

Educational status

Total

Dropouts
Did not
Early
enter
dropouts
educational (during
system
primary
cycle)

Bolivia

Dropouts Dropouts Dropouts at Subtotal Students Students Up-to- Graduates Subtotal
at end of in lower
end of lower dropouts who who are date
students
primary secondary secondary or
are far slightly students
and
cycle
cycle
during upper
behind behind
graduates
secondary
cycle

1.0

15.7

4.5

3.9

23.8

47.9

11.8

8.2

23.9

7.3

51.2

100.0

Males

0.8

13.5

4.1

4.2

22.9

44.7

13.3

6.5

26.5

8.1

54.4

100.0

Females
Brazil

2004 Both sexes

Students and graduates

1.2

18.2

4.9

3.6

24.8

51.5

10.0

10.1

20.8

6.4

47.3

100.0

2.5

5.1

5.4

13.2

7.0

30.7

29.7

10.1

21.0

5.8

66.6

100.0

Males

3.0

6.5

5.6

13.6

6.1

31.8

33.6

9.2

17.7

4.6

65.1

100.0

Females
Chile

2006 Both sexes

2.0

3.6

5.3

12.7

8.0

29.6

25.3

11.2

24.7

7.2

68.4

100.0

0.4

1.2

1.5

1.6

14.2

18.5

6.2

12.5

47.3

15.0

81.0

100.0

Males

0.3

1.4

1.6

1.9

14.7

19.6

7.6

14.2

42.9

15.5

80.2

100.0

Females
Colombia

2006 Both sexes

0.5

0.9

1.3

1.3

13.8

17.3

4.7

10.7

52.1

14.6

82.1

100.0

3.1

13.4

16.2

8.9

6.1

44.6

18.3

8.8

14.2

11.0

52.3

100.0

Males

4.0

16.0

16.7

8.4

5.5

46.6

20.2

7.7

12.5

9.0

49.4

100.0

Females
Costa Rica

2005 Both sexes

2.2

10.5

15.6

9.4

6.8

42.3

16.2

10.1

16.2

13.2

55.7

100.0

1.3

8.8

23.5

4.4

3.4

40.1

19.6

11.5

18.4

9.2

58.7

100.0

Males

1.8

9.6

24.8

5.4

3.9

43.7

20.4

10.3

15.8

7.9

54.4

100.0

Females
Ecuador

2006 Both sexes

0.8

7.9

22.1

3.4

2.8

36.2

18.6

12.8

21.0

10.5

62.9

100.0

6.4

13.9

19.4

6.6

46.3

8.7

7.9

27.6

7.6

51.8

100.0

1.8

7.2

13.9

18.6

5.7

45.4

9.9

8.3

27.6

7.0

52.8

100.0

Females

Education

1.9

Males

El Salvador

2006 Both sexes

1.9

5.6

14.0

20.3

7.5

47.4

7.2

7.4

27.7

8.4

50.7

100.0

6.7

22.4

8.4

7.2

9.2

47.2

13.5

7.4

21.5

3.8

46.2

100.0

Males

7.2

22.0

7.7

5.8

8.8

44.3

16.4

9.2

19.3

3.6

48.5

100.0

Females
Guatemala

2004 Both sexes

6.1

22.9

9.2

8.9

9.6

50.6

10.2

5.2

24.0

3.9

43.3

100.0
100.0

16.4

28.7

18.1

2.6

2.3

51.7

15.5

5.5

10.4

0.5

31.9

Males

10.9

24.7

20.0

3.8

2.3

50.8

18.7

7.8

11.1

0.7

38.3

100.0

Females
Honduras

2004 Both sexes

21.9

32.7

16.2

1.4

2.3

52.6

12.3

3.3

9.7

0.2

25.5

100.0

7.4

20.6

33.1

3.0

3.8

60.5

10.4

5.4

15.2

1.1

32.1

100.0

Males

8.9

21.8

33.4

3.0

3.6

61.8

10.1

5.2

13.2

0.7

29.2

100.0

Females
Mexico

2006 Both sexes

5.8

19.5

32.7

2.9

4.1

59.2

10.7

5.5

17.2

1.6

35.0

100.0

2.2

5.4

10.6

5.4

23.7

45.1

5.0

6.4

31.0

10.3

52.7

100.0

Males

2.3

5.4

11.1

4.8

25.4

46.7

5.4

7.6

29.1

8.9

51.0

100.0

Females
Nicaragua

2006 Both sexes

2.1

5.3

10.2

6.0

22.0

43.5

4.5

5.1

33.0

11.8

54.4

100.0

2001 Both sexes

19.0

29.4

12.4

4.8

1.6

48.2

16.7

5.2

8.5

2.4

32.8

100.0

Males

21.8

32.4

11.1

3.8

1.2

48.5

16.6

4.2

6.9

2.1

29.8

100.0

Females

15.7

25.8

14.0

6.2

2.1

48.1

16.9

6.3

10.4

2.7

36.3

100.0

Social Panorama of Latin America • 2007

435

Table 38 (concluded)
CLASSIFICATION OF YOUNG PEOPLE AGED 15 TO 19 BY EDUCATIONAL STATUS THROUGHOUT THE SCHOOL CYCLE,
RURAL AREAS, AROUND 2006 a
(Percentages)
Country

Year

Sex

Educational status

Total

Dropouts
Did not
Early
enter
dropouts
educational (during
system
primary
cycle)

Panama

Dropouts Dropouts Dropouts at Subtotal Students Students Up-to- Graduates Subtotal
at end of in lower
end of lower dropouts who who are date
students
primary secondary secondary or
are far slightly students
and
cycle
cycle
during upper
behind behind
graduates
secondary
cycle

3.7

6.0

18.6

7.0

6.6

38.2

10.3

7.2

31.5

9.1

58.1

100.0

Males

1.6

7.2

19.1

7.6

6.4

40.3

12.8

8.0

29.5

7.7

58.0

100.0

Females
Paraguay

2006 Both sexes

Students and graduates

5.9

4.8

18.1

6.4

6.8

36.1

7.7

6.3

33.5

10.5

58.0

100.0
100.0

1.1

13.7

17.0

8.5

6.7

45.9

12.4

10.6

25.9

4.2

53.1

Males

1.6

16.5

16.2

7.8

6.6

47.1

14.7

10.1

21.8

4.6

51.2

100.0

Females
Peru

2005 Both sexes

0.4

9.9

18.2

9.5

6.8

44.4

9.2

11.2

31.3

3.6

55.3

100.0

1.5

12.9

15.6

8.7

11.6

48.8

12.7

7.5

14.4

15.1

49.7

100.0

Males

0.8

9.1

11.9

9.4

12.0

42.4

15.5

8.5

15.6

17.2

56.8

100.0

Females
Dominican

2003 Both sexes

2.4

17.5

19.8

7.8

11.1

56.2

9.4

6.4

13.0

12.5

41.3

100.0
100.0

2.8

6.8

2.1

2.2

6.1

17.2

17.6

10.3

41.4

10.8

80.1

Males

3.6

9.7

2.1

2.0

5.0

18.8

21.9

11.0

36.6

8.1

77.6

100.0

Females

Republic

2006 Both sexes

1.8

3.1

2.0

2.4

7.5

15.0

12.3

9.4

47.5

14.1

83.3

100.0

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
The methodology for calculating dropout rates is described in ECLAC, Social Panorama of Latin America 2001-2002 (LC/G.2183-P), Santiago, Chile,
October 2002, box III.1, except that the division into cycles is based strictly on the International Standard Classification of Education (ISCED) 1997.

Education

a

436

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 39
OVERALL DROPOUT RATE AMONG YOUNG PEOPLE 15 TO 19, 1990-2005 a
(Percentages)
Country

National
Both
sexes

Males

Urban
Females

Rural

Both
sexes

Males

Females

Ambos
sexos

Males

Females

1990
2006

…
…

…
…

…
…

35.6
17.8

37.6
19.8

33.2
15.8

…
…

…
…

…
…

Argentina

2006

…

…

…

17.5

20.2

14.9

…

…

…

Bolivia

2004

37.2

35.5

38.8

31.7

30.2

33.0

48.4

45.1

52.1

Brazil

1990
2006

45.9
21.7

49.0
23.5

43.0
19.9

39.7
19.6

42.7
21.4

36.9
17.8

64.5
31.6

67.3
32.9

61.7
30.2

Chile

1990
2006

26.8
12.2

26.6
13.1

27.1
11.3

20.7
11.3

20.1
12.1

21.3
10.4

57.3
18.6

58.4
19.6

56.3
17.5

Colombia

1991
2005

42.5
26.0

45.0
28.0

40.1
24.1

29.7
18.5

29.8
19.5

29.7
17.6

59.1
46.0

62.7
48.5

55.2
43.1

Costa Rica

1990
2006

53.2
30.1

53.2
32.4

53.1
27.8

32.9
22.7

32.2
23.6

33.7
21.7

68.8
40.6

69.3
44.5

68.3
36.5

Ecuador

1990
2006

…
31.1

…
31.3

…
30.8

24.3
22.8

28.3
23.3

20.5
22.3

…
47.2

…
46.3

…
48.3

El Salvador

1995
2004

45.1
36.2

44.1
34.4

46.1
38.0

32.4
25.1

30.8
23.3

33.7
26.8

62.9
50.6

60.8
47.7

65.0
53.8

Guatemala

2004

52.9

49.6

56.3

43.0

40.8

45.1

61.9

57.1

67.2

Honduras

1990
2006

66.1
49.3

69.6
52.7

62.9
46.1

49.1
32.3

51.9
35.3

46.7
29.7

81.5
65.4

83.8
67.9

79.0
62.9

Mexico

2006

37.9

39.1

36.6

32.8

33.8

31.7

46.2

47.8

44.5

Nicaragua

1993
2001

44.3
41.2

43.2
46.2

45.3
36.3

32.0
30.5

31.4
36.2

32.7
25.2

65.1
59.6

62.8
61.9

67.3
57.0

Panama

1991
2006

35.3
25.5

38.8
28.2

31.6
22.8

28.0
17.6

30.5
20.7

25.5
14.5

53.4
39.7

58.4
41.0

47.6
38.4

Paraguay

2005

32.4

33.7

31.1

22.1

21.2

22.9

46.5

47.9

44.6

Peru

1997
2003

40.3
31.4

40.6
29.2

39.9
33.8

36.3
22.0

36.2
21.5

36.3
22.5

48.4
49.5

48.5
42.8

48.4
57.7

Dominican
Republic

1997
2006

22.9
15.9

25.1
18.1

21.0
13.6

19.3
14.9

22.7
17.2

16.8
12.8

28.1
17.6

28.0
19.6

28.2
15.3

Uruguay

1990
2005

…
…

…
…

…
…

36.5
29.4

41.1
32.2

31.9
26.5

…
…

…
…

…
…

Venezuela
(Bol. Rep. of)

Education

Argentina b

1990
2006

39.6
21.0

43.2
24.8

35.8
17.1

35.5
…

38.7
…

32.3
…

63.2
…

67.4
…

58.1
…

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a
b

The methodology for calculating dropout rates is described in ECLAC, Social Panorama of Latin America 2001-2002 (LC/G.2183-P), Santiago, Chile,
October 2002, box III.1, except that the division into cycles is based strictly on the International Standard Classification of Education (ISCED) 2002.
Greater Buenos Aires.

Social Panorama of Latin America • 2007

437

Table 40
EARLY DROPOUT RATE (DURING THE PRIMARY CYCLE) AMONG YOUNG PEOPLE AGED 15 TO 19,1990-2005 a
Country

National
Both
sexes

Males

Urban
Females

Both
sexes

Males

Rural
Females

Both
sexes

Males

Females

1990
2006

…
…

…
…

…
…

2.4
0.8

2.4
1.1

2.4
0.5

…
…

…
…

…
…

Argentina

2006

…

…

…

1.2

1.5

0.8

…

…

…

Bolivia

2004

8.7

7.2

10.1

5.2

3.6

6.6

15.9

13.6

18.5

Brazil

1990
2006

13.3
2.3

15.3
3.0

11.4
1.5

9.2
1.6

10.5
2.2

7.9
1.1

25.7
5.3

29.1
6.7

22.2
3.7

Chile

1990
2006

4.3
0.8

4.7
1.0

3.9
0.6

2.9
0.8

3.1
0.9

2.7
0.6

11.3
1.2

12.5
1.4

10.1
0.9

Colombia

1991
2005

15.5
6.0

17.8
7.4

13.4
4.6

7.3
3.0

7.6
3.6

7.1
2.5

26.1
13.8

29.5
16.6

22.4
10.7

Costa Rica

1990
2006

12.1
5.6

13.2
6.3

10.9
4.9

4.6
3.3

5.2
3.8

4.1
2.8

17.9
8.9

19.3
9.8

16.4
8.0

Ecuador

1990
2006

…
3.6

…
3.8

…
3.4

3.5
2.1

4.4
1.9

2.7
2.3

…
6.6

…
7.3

…
5.7

El Salvador

1995
2004

24.6
15.2

24.4
15.6

24.8
14.8

12.6
8.5

10.9
8.9

14.1
8.1

41.3
24.0

41.4
23.8

41.1
24.4

Guatemala

2004

26.1

21.3

31.1

16.8

13.7

19.9

34.4

27.7

41.8

Honduras

1990
2006

27.3
14.7

30.0
16.1

24.8
13.4

15.2
6.7

15.5
7.3

14.9
6.2

38.2
22.3

41.8
23.9

34.6
20.7

Mexico

2006

3.3

3.6

3.0

1.9

2.3

1.5

5.5

5.6

5.4

Nicaragua

1993
2001

23.6
19.7

25.4
23.9

21.8
15.6

11.8
10.0

13.7
12.7

10.0
7.5

43.7
36.3

45.0
41.4

42.5
30.6

Panama

1991
2006

5.8
3.0

6.9
3.6

4.6
2.3

3.9
1.1

4.5
1.5

3.2
0.8

10.7
6.2

12.6
7.3

8.5
5.1

Paraguay

2005

8.2

10.4

5.8

4.0

4.7

3.3

13.9

16.8

10.0

Peru

1997
2003

16.3
6.2

16.3
4.9

16.3
7.5

8.2
2.6

8.4
2.5

7.9
2.6

32.9
13.1

30.4
9.2

36.0
17.9

Dominican
Republic

1997
2006

9.9
5.3

11.9
7.2

8.1
3.3

6.8
4.4

8.0
5.5

5.8
3.4

14.3
7.0

16.5
10.1

11.8
3.2

Uruguay

1990
2005

…
…

…
…

…
…

2.2
2.4

2.9
3.2

1.5
1.6

…
…

…
…

…
…

Venezuela
(Bol. Rep. of)

1990
2006

9.9
4.4

12.1
5.9

7.6
2.8

7.0
…

8.6
…

5.4
…

26.8
…

31.1
…

21.6
…

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

The methodology for calculating dropout rates is described in ECLAC, Social Panorama of Latin America 2001-2002 (LC/G.2183-P), Santiago, Chile,
October 2002, box III.1, except that the division into cycles is based strictly on the International Standard Classification of Education (ISCED) 1997.
b Greater Buenos Aires.

Education

Argentina b

438

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 41
DROPOUT RATE AT THE END OF THE PRIMARY CYCLE AMONG YOUNG PEOPLE AGED 15 TO 19, 1990-2005 a
(Percentages)
Country

National
Both
sexes

Males

Urban
Females

Both
sexes

Males

Rural
Females

Ambos
sexos

Males

Females

2006

…

…

…

1.0

1.1

0.9

…

…

…

Argentina

2006

…

…

…

1.3

1.7

0.9

…

…

…

Bolivia

2004

3.3

2.9

3.7

2.4

2.0

2.8

5.4

4.8

6.1

Brazil

1990
2006

14.1
2.6

14.9
3.0

13.4
2.2

9.4
1.9

9.9
2.3

8.9
1.6

31.3
5.9

33.0
6.2

29.7
5.6

Chile

1990
2006

3.9
0.7

4.0
0.7

3.8
0.7

2.1
0.6

2.1
0.6

2.1
0.6

13.6
1.5

14.0
1.6

13.2
1.4

Colombia

1991
2005

18.0
8.0

19.2
8.8

16.8
7.3

9.5
4.2

9.4
4.5

9.7
3.9

31.6
19.4

34.2
20.9

29.1
17.9

Costa Rica

1990
2006

35.8
17.5

35.6
19.3

36.0
15.7

18.7
11.7

17.1
13.3

20.3
10.1

51.1
26.1

52.0
28.0

50.2
24.2

Ecuador

1990
2006

…
8.2

…
8.3

…
8.0

12.1
4.7

13.8
4.7

10.6
4.8

…
15.2

…
15.3

…
15.1

El Salvador

1995
2004

9.1
7.1

8.5
6.7

9.6
7.6

6.1
4.1

6.0
3.7

6.3
4.5

15.1
11.8

13.4
10.8

16.9
12.9

Guatemala

2004

24.4

23.4

25.4

16.8

15.9

17.8

33.0

31.1

35.6

Honduras

1990
2006

46.4
30.7

49.4
33.4

43.8
28.1

31.3
17.2

34.8
19.5

28.4
15.1

65.1
46.0

66.5
48.2

63.8
43.8

Mexico

2006

8.0

8.1

7.8

5.9

5.8

5.9

11.5

12.0

11.0

Nicaragua

1993
2001

16.0
14.3

17.2
15.8

14.9
12.9

12.4
10.2

14.2
12.2

10.8
8.6

25.5
24.1

24.9
24.3

26.0
23.9

Panama

1991
2006

18.7
10.2

22.0
10.6

15.3
9.9

12.3
4.7

14.7
4.9

9.9
4.5

36.0
20.6

41.0
20.9

30.6
20.3

Paraguay

2005

11.9

12.2

11.5

6.5

6.3

6.6

20.0

19.8

20.3

Peru

1997
2003

2.8
8.1

2.2
6.8

3.3
9.5

2.5
3.3

2.0
3.3

2.9
3.4

3.5
18.2

2.7
13.3

4.6
24.8

Dominican
Republic

1997
2006

4.3
1.9

4.5
1.8

4.1
2.0

3.0
1.7

3.0
1.4

3.0
1.9

6.2
2.3

6.4
2.4

6.0
2.1

Uruguay

1990
2005

…
…

…
…

…
…

13.1
9.1

13.7
11.2

12.5
7.0

…
…

…
…

…
…

Venezuela
(Bol. Rep. of)

Education

Argentina b

1990
2006

17.8
7.3

20.5
9.1

15.1
5.4

15.6
…

17.9
…

13.4
…

34.3
…

39.5
…

28.7
…

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries.
a

The methodology for calculating dropout rates is described in ECLAC, Social Panorama of Latin America 2001-2002 (LC/G.2183-P), Santiago, Chile,
October 2002, box III.1, except that the division into cycles is based strictly on the International Standard Classification of Education (ISCED) 1997.
b Greater Buenos Aires.

Social Panorama of Latin America • 2007

439

Table 42
DROPOUT RATE DURING THE SECONDARY CYCLE AMONG YOUNG PEOPLE AGED 15 TO 19 1990-2005 a
(Percentages)
Country

National
Both
sexes

Males

Urban
Females

Rural

Both
sexes

Males

Females

Both
sexes

Males

Females

1990 c
2006

…
…

…
…

…
…

34.0
16.3

36.1
18.0

31.5
14.7

…
…

…
…

…
…

Argentina

2006

…

…

…

15.5

17.6

13.5

…

…

…

Bolivia

2004

28.8

28.4

29.2

26.2

26.1

26.2

35.2

33.3

37.5

Brazil

1990
2006

27.4
17.8

29.3
18.7

25.7
16.8

26.8
16.6

28.9
17.8

24.8
15.6

30.5
23.3

31.2
23.3

29.9
23.3

Chile

1990
2006

20.4
10.9

19.8
11.6

21.1
10.1

16.6
10.1

15.7
10.8

17.4
9.3

44.3
16.4

44.7
17.1

44.0
15.6

Colombia

1991
2005

17.1
14.5

17.3
14.7

16.9
14.3

16.2
12.3

16.1
12.6

16.2
12.1

19.0
22.2

19.6
22.0

18.5
22.5

Costa Rica

1990
2006

17.0
10.2

16.5
10.6

17.6
9.9

13.5
9.4

13.7
8.4

13.3
10.4

22.3
11.7

20.7
14.5

23.9
9.0

Ecuador

1990
2006

…
22.1

…
22.2

…
22.1

10.8
17.3

13.1
17.9

8.7
16.5

…
33.4

…
31.6

…
35.4

El Salvador

1995
2004

20.0
19.0

19.1
16.8

20.8
21.2

17.5
14.7

17.4
12.6

17.7
16.6

25.6
26.3

22.8
23.1

28.5
29.9

Guatemala

2004

15.8

16.4

15.1

17.6

18.5

16.6

13.3

13.9

12.4

Honduras

1990
2006

13.0
14.2

14.0
15.2

12.3
13.4

12.6
12.4

12.7
13.2

12.6
11.7

14.0
17.5

16.9
18.4

11.5
16.6

Mexico

2006

30.2

31.3

29.1

27.2

28.0

26.3

35.6

37.2

34.0

Nicaragua

1993
2001

13.2
14.6

8.0
16.1

17.8
13.3

12.0
14.0

7.4
16.8

16.1
11.6

16.8
16.4

10.0
14.2

23.2
18.6

Panama

1991
2006

15.5
14.5

15.7
16.6

15.3
12.3

14.6
12.5

14.7
15.4

14.6
9.7

18.5
19.0

19.5
19.5

17.6
18.5

Paraguay

2005

16.5

15.8

17.3

13.3

11.7

14.7

22.3

21.9

22.8

Peru

1997
2003

26.6
20.5

27.4
20.2

25.8
20.9

28.8
17.2

28.9
16.7

28.8
17.6

20.3
28.9

23.8
27.4

15.5
31.4

Dominican
Republic

1997
2006

10.7
9.5

11.0
10.1

10.4
8.8

10.8
9.5

13.4
11.1

8.9
8.0

10.5
9.4

7.8
8.3

13.3
10.6

Uruguay

1990
2005

…
…

…
…

…
…

25.3
20.4

29.7
21.1

21.0
19.7

…
…

…
…

…
…

Venezuela
(Bol. Rep. of)

1990
2006

18.4
10.9

18.7
12.0

18.1
9.9

17.9
…

18.4
…

17.4
…

23.4
…

21.8
…

24.9
…

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys
conducted in the relevant countries
a

The methodology for calculating dropout rates is described in ECLAC, Social Panorama of Latin America 2001-2002 (LC/G.2183-P), Santiago, Chile,
October 2002, box III.1, except that the division into cycles is based strictly on the International Standard Classification of Education (ISCED) 1997.
b Greater Buenos Aires.
c Includes dropouts at the end of the primary cycle.

Education

Argentina b

440

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 43
PUBLIC SOCIAL SPENDING INDICATORS a
1990/1991-2004/2005 b
Country

Institutional coverage

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Argentina d

695

825

824

752

11.4

11.2

11.0

9.6

60.3

66.6

61.3

63.1

National Government and
provincial governments

1103

1444

1516

1410

18.1

19.7

20.2

18.0

62.7

66.7

63.2

64.6

National Government,
provincial governments and
local governments

1179

1553

1640

1521

19.3

21.1

21.8

19.4

62.2

65.6

62.7

64.1

47

68

120

...

5.2

7.2

12.0

...

34.4

27.5

35.4

...

...

118

179

190

...

12.4

18.0

18.6

...

36.3

54.4

63.0

Union (Federal Government)

337

420

445

501

10.1

11.8

12.1

12.8

…

…

…

…

Federal, state and municipal f

604

725

776

860

18.1

20.4

21.1

22.0

48.9

58.6

61.6

72.0

Chile

Central government

403

508

746

729

12.7

12.4

15.1

13.1

61.2

64.2

67.5

66.9

Colombia

Non-financial public sector

123

237

266

291

6.6

11.5

13.2

13.4

28.8

39.9

33.2

...

Costa Rica

Total public sector

486

566

728

772

15.6

15.8

18.0

17.4

38.9

38.2

40.5

35.8

Cuba

Central government

…

…

570

870

27.6

28.5

22.2

28.7

35.6

39.4

47.0

53.0

Ecuador

Central government

94

81

65

96

7.4

6.1

4.9

6.3

42.8

33.7

20.9

28.5

El Salvador

Central government

...

90

113

120

...

4.6

5.4

5.6

...

31.6

34.9

31.2

Guatemala

Central government

44

57

93

100

3.3

4.1

6.1

6.3

29.9

41.3

47.3

53.8

Honduras

Central government

67

61

97

120

7.5

6.6

10.0

11.6

40.7

40.6

45.4

52.8

Jamaica g

Central government

243

245

273

289

8.4

8.2

9.5

9.9

26.8

20.6

17.1

16.3

Mexico

Budgetary central government

324

449

564

618

6.5

8.9

9.7

10.2

41.3

53.1

61.3

58.6

Nicaragua

Budgetary central government

45

46

63

90

6.6

7.2

8.1

10.8

34.0

39.9

38.4

47.9

Panama

Central government

229

287

371

344

7.5

8.3

9.5

8.0

38.1

48.6

42.5

39.3

Non-financial public sector g

496

578

680

724

16.2

16.6

17.4

17.2

40.0

41.5

44.3

40.0

Bolivia

National government - federal

Central government
Non-financial public sector e

Education

Brazil

Paraguay

Budgetary central government

45

115

107

108

3.2

7.8

8.0

7.9

39.9

43.3

38.3

40.2

Peru

Budgetary central government

64

125

160

...

3.9

6.5

7.7

...

33.0

39.4

45.0

...

...

...

173

208

...

...

8.3

8.9

...

...

49.7

50.8

Total public sector

Social Panorama of Latin America • 2007

441

Table 43 (concluded)
INDICADORES DEL GASTO PÚBLICO SOCIAL a
1990/1991-2004/2005 b
Country

Institutional coverage

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Dominican
Republic

Central government

74

133

209

204

4.3

6.7

7.7

7.1

38.4

45.4

47.5

34.5

Trinidad and
Tobago

Central government

303

294

588

845

6.9

6.6

9.1

9.4

40.6

42.8

70.8

76.4

Uruguay

Consolidated central
government h

820

1150

1322

1087

16.8

20.2

22.2

17.7

62.3

70.8

66.6

57.4

General government

...

...

1405

...

...

...

23.6

...

...

...

62.8

...

Non-financial public sector

...

...

1506

...

...

...

25.3

...

...

...

64.4

...

441

396

563

562

8.8

7.8

11.6

11.7

32.8

35.3

37.8

41.0

...

...

494

...

...

...

10.2

...

...

...

43.5

...

Venezuela
(Bol. Rep. of)

Budgetary central
government – approved
Budgetary central
government - executed

i

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the Commission’s social expenditure
database.
b
c
d
e
f

g
h
i

Includes public spending on education, health and nutrition, social security, labour, social welfare, housing, water and sewerage systems.
The figures are simple averages for the relevant bienniums.
The implicit figures in total public spending may differ from other published figures owing to methodological differences in accounting for expenditure in
economic, administrative and functional classifications.
At all levels of government, includes non-financial public corporations.
The figure under the heading 1994/1995 relates to 1995.
From 1990 to 1999, the figure for consolidated social spending – which includes federal, state and municipal spending – is an estimate. At all levels of
government, includes non-financial public corporations.
The figure under the heading 2004/2005 relates to 2004.
Includes social security transfers to social security organizations.
Relates to the budgetary law and includes the modifications made yearly on 31 December.

Education

a

442

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 44
INDICATORS OF PUBLIC SOCIAL SPENDING ON EDUCATION a
1990/1991-2004/2005 b
Country

Institutional coverage

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Argentina d

72

74

70

1.3

1.0

1.0

0.9

7.0

5.8

5.5

5.8

216

303

372

341

3.5

4.1

4.9

4.3

12.3

14.0

15.5

15.5

National Government,
provincial governments and
local governments

220

312

383

350

3.6

4.2

5.1

4.5

11.6

13.2

14.7

14.7

29

46

55

...

3.3

4.9

5.5

...

21.7

18.7

16.3

...

Non-financial public sector e

...

50

67

75

...

5.3

6.7

7.3

...

15.5

20.1

24.6

Union (Federal Government)

46

53

39

36

1.4

1.5

1.1

0.9

…

…

…

…

Federal, state and municipal f

Brazil

80

National Government and
provincial governments

Bolivia

National government - federal

125

190

183

178

3.7

5.3

5.0

4.6

9.9

15.4

14.5

14.9

Central government

Central government

77

107

195

198

2.4

2.6

3.9

3.5

11.6

13.5

17.6

18.1

Colombia

Non-financial public sector

49

69

82

82

2.6

3.3

4.1

3.7

11.4

11.6

10.3

...

Costa Rica

Total public sector

123

151

206

242

3.9

4.2

5.1

5.5

9.9

10.2

11.5

11.2

Cuba

Central government

…

…

218

375

10.8

9.0

8.5

12.4

13.9

12.4

18.0

22.9

Ecuador

Central government

36

35

27

40

2.8

2.6

2.1

2.6

16.0

14.6

8.7

11.8

El Salvador

Central government

...

40

62

63

...

2.0

3.0

2.9

...

14.0

19.3

16.3

Guatemala

Education

Chile

Central government

21

24

39

39

1.6

1.7

2.6

2.5

14.3

17.6

19.9

21.2

Honduras

Central government

39

34

61

79

4.3

3.7

6.2

7.7

23.2

22.9

28.4

35.0

Jamaica g

Central government

119

121

166

158

4.1

4.1

5.8

5.4

13.1

10.1

10.4

8.9

Mexico

Budgetary central government

129

200

227

229

2.6

3.9

3.9

3.8

16.4

23.6

24.6

21.7

Nicaragua

Budgetary central government

17

19

30

39

2.6

2.8

3.7

4.7

13.0

15.8

17.6

20.8

Panama

Central government

109

122

164

165

3.6

3.5

4.2

3.8

18.3

20.7

18.8

18.8

125

150

192

181

4.1

4.3

4.9

4.3

10.1

10.8

12.5

10.0

Non-financial public sector

g

Paraguay

Budgetary central government

18

53

57

52

1.3

3.6

4.3

3.8

15.7

20.0

20.6

19.5

Peru

Budgetary central government

27

51

51

...

1.6

2.7

2.5

...

13.8

16.1

14.4

...

...

...

60

73

...

...

2.9

3.1

...

...

17.2

17.7

Total public sector

Social Panorama of Latin America • 2007

443

Table 44 (concluded)
INDICATORS OF PUBLIC SOCIAL SPENDING ON EDUCATION a
1990/1991-2004/2005 b
Country

Institutional coverage

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Dominican
Republic

Central government

20

41

77

56

1.2

2.1

2.9

2.0

10.5

14.0

17.6

9.4

Trinidad and
Tobago

Central government

139

134

264

407

3.2

3.0

4.1

4.5

18.6

19.5

31.7

36.7

Uruguay

Consolidated central
government

120

140

201

201

2.5

2.5

3.4

3.3

9.1

8.6

10.1

10.6

General government

...

...

209

...

...

...

3.5

...

...

...

9.4

...

Non-financial public sector

...

...

209

...

...

...

3.5

...

...

...

9.0

...

177

192

249

240

3.5

3.8

5.1

5.0

13.2

17.1

16.8

17.5

...

...

258

...

...

...

5.3

...

...

...

22.6

...

Venezuela
(Bol. Rep. of)

Budgetary central
government – approved
Budgetary central
government - executed

h

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the Commission’s social expenditure
database.
b
c
d
e
f
g
h

Includes public spending on primary, secondary and tertiary education. In some countries, includes feeding programmes (school cantines).
The figures are simple averages for the relevant bienniums.
The implicit figures in total public spending may differ from other published figures owing to methodological differences in accounting for expenditure in
economic, administrative and functional classifications.
At all levels of government, includes non-financial public corporations.
The figure under the heading 1994/1995 relates to 1995.
From 1990 to 1999, the figure for consolidated social spending — which includes federal, state and municipal spending – is an estimate. At all levels of
government, includes non-financial public corporations.
The figure under the heading 2004/2005 relates to 2004.
Relates to the budgetary law and includes the modifications made yearly on 31 December.

Education

a

444

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 45
INDICATORS OF SOCIAL SPENDING ON HEALTH a
1990/1991-2004/2005 b
Country

Institutional coverage

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Argentina d

155

190

184

172

2.5

2.6

2.5

2.2

13.4

15.3

13.7

14.4

National Government and
provincial governments

251

341

353

325

4.1

4.6

4.7

4.2

14.3

15.7

14.7

14.9

National Government,
provincial governments and
local governments
Bolivia

National government - federal

264

363

378

347

4.3

4.9

5.0

4.4

14.0

15.3

14.5

14.6

9

12

13

...

1.0

1.2

1.3

...

6.9

4.9

3.8

...

e

...

30

36

36

...

3.1

3.6

3.5

...

9.2

10.9

12.0

Union (Federal Government)

38

76

66

67

1.1

2.1

1.8

1.7

…

…

…

…

119

150

150

180

3.6

4.2

4.1

4.6

9.6

12.1

11.9

15.0

Central government
Non-financial public sector

Brazil

Federal, state and municipal

f

Central government

62

97

144

156

2.0

2.4

2.9

2.8

9.4

12.2

13.0

14.3

Colombia

Non-financial public sector

18

60

61

50

1.0

2.9

3.0

2.3

4.2

10.1

7.5

...

Costa Rica

Total public sector

153

168

210

220

4.9

4.7

5.2

5.0

12.3

11.3

11.7

10.2

Cuba

Central government

…

…

135

182

5.0

5.6

5.2

6.0

6.4

7.8

11.1

11.0

Ecuador

Central government

18

11

10

19

1.4

0.8

0.8

1.2

8.1

4.5

3.3

5.5

El Salvador

Central government

...

26

28

33

...

1.3

1.3

1.5

...

9.1

8.9

8.5

Guatemala

Education

Chile

Central government

12

12

16

15

0.9

0.9

1.1

1.0

8.1

8.8

8.2

8.1

Honduras

Central government

26

24

32

37

2.9

2.6

3.3

3.5

15.5

15.9

15.2

16.0

Jamaica g

Central government

63

65

64

81

2.2

2.2

2.2

2.8

7.0

5.4

4.0

4.6

Mexico

Budgetary central government

147

118

132

153

2.9

2.3

2.3

2.5

18.6

13.9

14.4

14.4

Nicaragua

Budgetary central government

19

18

23

28

2.8

2.8

2.9

3.3

14.5

15.6

13.9

14.8

Panama

Central government

49

63

90

98

1.6

1.8

2.3

2.3

8.0

10.5

10.3

11.2

164

202

232

240

5.4

5.8

5.9

5.7

13.3

14.4

15.1

13.3

Non-financial public sector g
Paraguay

Budgetary central government

4

18

16

16

0.3

1.2

1.2

1.1

3.8

6.7

5.7

5.7

Peru

Budgetary central government

15

25

36

...

0.9

1.3

1.7

...

7.4

7.6

10.2

...

...

...

32

37

...

...

1.5

1.6

...

...

9.0

8.9

Total public sector

Social Panorama of Latin America • 2007

445

Table 45 (concluded)
INDICATORS OF SOCIAL SPENDING ON HEALTH a
1990/1991-2004/2005 b
Country

Institutional coverage

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Dominican
Republic

Central government

17

25

50

40

1.0

1.2

1.8

1.4

8.6

8.4

11.3

6.6

Trinidad and
Tobago

Central government

115

99

136

199

2.6

2.2

2.1

2.2

15.4

14.4

16.3

18.0

Uruguay

Consolidated central
government

142

196

153

107

2.9

3.4

2.6

1.7

10.8

12.0

7.7

5.6

General government

...

...

166

...

...

...

2.8

...

...

...

7.4

...

Non-financial public sector

...

...

190

...

...

...

3.2

...

...

...

8.1

...

79

56

71

77

1.6

1.1

1.5

1.6

5.9

5.0

4.7

5.6

...

...

67

...

...

...

1.4

...

...

...

5.8

...

Venezuela
(Bol. Rep. of)

Budgetary central
government - approved h
Budgetary central
government - executed

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the Commission’s social expenditure
database.
b
c
d
e
f
g
h

Includes public spending on health and nutrition.
The figures are simple averages for the relevant bienniums.
The implicit figures in total public spending may differ from other published figures owing to methodological differences in accounting for expenditure in
economic, administrative and functional classifications.
At all levels of government, includes non-financial public corporations.
The figure under the heading 1994/1995 relates to 1995.
From 1990 to 1999, the figure for consolidated social spending — which includes federal, state and municipal spending – is an estimate. At all levels of
government, includes non-financial public corporations.
The figure under the heading 2004/2005 relates to 2004.
Relates to the budgetary law and includes the modifications made yearly on 31 December.

Education

a

446

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 46
INDICATORS OF PUBLIC SOCIAL SPENDING ON SOCIAL SECURITY
1990/1991-2004/2005 b
Country

Institutional coverage

a

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Argentina d

National government - federal

456

560

565

508

7.5

7.6

7.5

6.5

39.5

45.3

42.0

42.7

National Government and
provincial governments

581

740

745

685

9.5

10.1

9.9

8.8

33.0

34.1

31.1

31.5

National Government,
provincial governments and
local governments

592

759

775

718

9.7

10.3

10.3

9.2

31.2

32.1

29.7

30.3

Central government

6.5

8.5

50

...

0.7

0.9

5.0

...

4.5

3.4

14.6

...

...

14

45

46

...

1.4

4.5

4.5

...

4.2

13.6

15.1

Union (Federal Government)

252

291

337

394

7.6

8.2

9.1

10.1

…

…

…

…

Federal, state and municipal f

308

371

410

467

9.2

10.4

11.1

12.0

25.0

30.0

32.6

39.1

Chile

Central government

259

296

393

364

8.1

7.2

7.9

6.5

39.3

37.5

35.5

33.4

Colombia

Non-financial public sector

47

93

97

148

2.5

4.5

4.8

6.8

10.9

15.6

12.0

...

Costa Rica

Total public sector

152

187

248

234

4.9

5.2

6.1

5.3

12.2

12.6

13.8

10.9

Cuba

Central government

…

…

156

231

7.0

8.6

6.1

7.6

8.9

11.9

12.9

14.0

Ecuador

Central government

41

29

23

34

3.2

2.2

1.7

2.2

18.5

12.1

7.3

10.1

El Salvador

Central government

...

1

1

1

...

0.0

0.1

0.0

...

0.2

0.3

0.2

Guatemala

Central government

10

11

16

16

0.7

0.7

1.0

1.0

6.6

7.6

8.1

8.7

Honduras

Central government

3

3

2

3

0.4

0.3

0.2

0.3

1.9

1.8

1.0

1.2

Jamaica g

Central government

17

12

11

13

0.6

0.4

0.4

0.5

1.9

1.0

0.7

0.8

Mexico

Budgetary central government

6

65

132

130

0.1

1.3

2.3

2.2

0.8

7.6

14.4

12.3

Panama

Central government

37

54

64

47

1.2

1.5

1.6

1.1

6.1

9.1

7.3

5.3

155

175

205

254

5.1

5.0

5.2

6.0

12.6

12.5

13.4

14.0

Bolivia

Non-financial public sector e

Education

Brazil

Non-financial public sector g
Paraguay

Budgetary central government

17

36

27

33

1.2

2.4

2.1

2.4

14.6

13.3

9.6

12.1

Peru

Budgetary central government

23

48

68

...

1.3

2.5

3.3

...

11.4

14.9

19.2

...

Total public sector

...

...

81

98

...

...

3.9

4.2

...

...

23.2

23.9

Central government

7

9

28

42

0.4

0.4

1.1

1.5

3.4

2.8

6.5

7.3

Dominican
Republic

Social Panorama of Latin America • 2007

447

Table 46 (concluded)
INDICATORS OF PUBLIC SOCIAL SPENDING ON SOCIAL SECURITY
1990/1991-2004/2005 b
Country

Institutional coverage

a

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Trinidad and
Tobago

4

90

128

0.1

0.1

1.4

1.4

0.4

0.5

11.0

11.5

Consolidated central
government h

544

787

939

759

11.2

13.9

15.8

12.3

41.3

48.4

47.3

40.1

...

...

948

...

...

...

15.9

...

...

...

42.4

...

Non-financial public sector
Venezuela
(Bol. Rep. of)

3

General government

Uruguay

Central government

...

...

948

...

...

...

15.9

...

...

...

40.6

...

101

115

179

198

2.0

2.3

3.7

4.1

7.5

10.3

12.0

14.4

...

...

100

...

...

...

2.0

...

...

...

8.8

...

Budgetary central
government - approved i
Budgetary central government
- executed

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the Commission’s social expenditure
database.
a

Includes public spending on social security, employment and social welfare.
The figures are simple averages for the relevant bienniums.
c The implicit figures in total public spending may differ from other published figures owing to methodological differences in accounting for expenditure in
economic, administrative and functional classifications.
d At all levels of government, includes non-financial public corporations.
e The figure under the heading 1994/1995 relates to 1995.
f From 1990 to 1999, the figure for consolidated social spending — which includes federal, state and municipal spending – is an estimate. At all levels of
government, includes non-financial public corporations.
g The figure under the heading 2004/2005 relates to 2004.
h Includes social security transfers to social security organizations (recorded in general government accounts); these amounted to approximately 6% of
GDP in 2000/2001.
i Relates to the budgetary law and includes the modifications made yearly on 31 December.

Education

b

448

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 47
INDICATORS OF PUBLIC SOCIAL SPENDING ON HOUSING AND OTHER ITEMS a
1990/1991-2004/2005 b
Country

Institutional coverage

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Argentina d

National government - federal

4

3

1

2

0.1

0.0

0.0

0.0

0.4

0.2

0.1

0.2

56

62

46

61

0.9

0.8

0.6

0.8

3.2

2.9

1.9

2.7

102

121

103

108

1.7

1.6

1.4

1.4

5.4

5.1

3.9

4.5

Central government

2

2

3

...

0.2

0.1

0.3

...

1.4

0.6

0.7

...

Non-financial public sector e

...

24

32

34

...

2.5

3.2

3.3

...

7.4

9.7

11.3

Union (Federal Government)

2

1

4

4

0.0

0.0

0.1

0.1

…

…

…

…

Federal, state and municipal f

52

15

34

37

1.5

0.4

0.9

0.9

4.4

1.1

2.7

3.1

National Government and
provincial governments
National Government,
provincial governments and
local governments
Bolivia

Brazil

Central government

6

8

15

12

0.2

0.2

0.3

0.2

0.9

1.0

1.3

1.1

Colombia

Non-financial public secto

9

16

27

13

0.5

0.8

1.3

0.6

2.2

2.6

3.4

...

Costa Rica

Total public sector

58

61

64

77

1.9

1.7

1.6

1.7

4.6

4.1

3.6

3.5

Cuba

Central government

…

…

62

83

4.8

5.3

2.4

2.8

6.4

7.3

5.1

5.1

Ecuador

Central government

0

6

6

4

0.0

0.4

0.4

0.2

0.1

2.5

1.5

1.1

El Salvador

Central government

...

24

22

24

...

1.2

1.0

1.1

...

8.3

6.4

6.1

Guatemala

Education

Chile

Central government

2

11

22

30

0.1

0.7

1.4

1.9

0.9

7.4

11.1

15.8

Honduras

Central government

0

0

2

1

0.0

0.0

0.2

0.1

0.1

0.0

0.9

0.6

Jamaica g

Central government

44

48

33

36

1.5

1.6

1.1

1.2

4.9

4.1

2.0

2.0

Mexico

Budgetary central government

43

68

73

106

0.9

1.3

1.3

1.8

5.4

8.0

7.9

10.0

Nicaragua

Budgetary central government

8

10

12

23

1.2

1.5

1.5

2.8

6.6

8.5

6.9

12.2

Panama

Central government

35

49

52

36

1.1

1.4

1.3

0.8

5.6

8.3

6.0

4.0

Non-financial public sector g

53

52

52

50

1.7

1.5

1.3

1.2

4.0

3.8

3.4

2.7

Paraguay

Budgetary central government

6

9

7

8

0.5

0.6

0.5

0.6

5.8

3.4

2.4

2.9

Peru

Budgetary central government

1

3

5

...

0.1

0.1

0.2

...

0.4

0.9

1.3

...

Total public sector

...

...

2

1

...

...

0.1

0.1

...

...

0.4

0.3

Social Panorama of Latin America • 2007

449

Table 47 (concluded)
INDICATORS OF PUBLIC SOCIAL SPENDING ON HOUSING AND OTHER ITEMS a
1990/1991-2004/2005 b
Country

Institutional coverage

Public social spending
Per capita
(2000 dollars)

As a percentage of gross
domestic product

As a percentage of total
public spending c

1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/ 1990/ 1994/ 2000/ 2004/
1991 1995 2001 2005 1991 1995 2001 2005 1991 1995 2001 2005
Dominican
Republic

Central government

31

59

54

66

1.8

3.0

2.0

2.3

15.9

20.2

12.2

11.2

Trinidad and
Tobago

Central government

46

58

98

112

1.0

1.3

1.5

1.2

6.1

8.5

11.7

10.1

Uruguay

Consolidated central
government

15

28

30

21

0.3

0.5

0.5

0.3

1.1

1.7

1.5

1.1

Gobierno general

...

...

82

...

...

...

1.4

...

...

...

3.7

...

Non-financial public sector

...

...

158

...

...

...

2.7

...

...

...

6.8

...

85

33

64

48

1.7

0.6

1.3

1.0

6.2

2.9

4.4

3.4

...

...

71

...

...

...

1.5

...

...

...

6.2

...

Venezuela
(Bol. Rep. of)

Budgetary central
government - approved h
Budgetary central
government - executed

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the Commission’s social expenditure
database.

b
c
d
e
f
g
h

Includes public spending on housing, water and sewerage systems and other items not listed in the remaining functions. In some countries, includes
social welfare.
The figures are simple averages for the relevant bienniums.
The implicit figures in total public spending may differ from other published figures owing to methodological differences in accounting for expenditure in
economic, administrative and functional classifications.
At all levels of government, includes non-financial public corporations.
The figure under the heading 1994/1995 relates to 1995.
From 1990 to 1999, the figure for consolidated social spending — which includes federal, state and municipal spending – is an estimate. At all levels of
government, includes non-financial public corporations.
The figure under the heading 2004/2005 relates to 2004.
Relates to the budgetary law and includes the modifications made yearly on 31 December.

Education

a

450

Economic Commission for Latin America and the Caribbean (ECLAC)

Millennium Development Goals
Table 48
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 1: Eradicate extreme poverty and hunger
Target 1: Halve, between 1990 and 2015, the proportion of
people whose income is less than one dollar a day
Indicator 1
Population living in
extreme poverty,
measured by
national poverty
lines

Indicator 2
Poverty gap ratio

Indicator 3 Share
of poorest quintile in
national consumption

Level

Level

Level

Level

Level

1990

2006

1990

2006

2006

Target 2: Halve, between 1990 and 2015, the
proportion of people who suffer from hunger
Indicator 4
Prevalence of
underweight children
under five years of age

Level

Level

Indicator 5
Proportion of
population below
minimum level of
dietary energy
consumption
Level

Level

1981/1993 1995/2006 1990/1992 2001/2003

Latin America and
the Caribbean
Latin America

…

…

9.8

6.7

3.1

10.3

7.2

13

10

22.5

12.7

9.8

6.7

3.1

10.4

7.2

13

10

Argentina b
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Ecuador b
El Salvador
Guatemala
Haiti
Honduras
Mexico
Nicaragua
Panama b
Paraguay
Peru
Dominican Republic
Uruguay b
Venezuela (Bol. Rep. of)

8.2
39.5
23.4
12.9
26.1
9.8
…
26.2
27.7
41.8
…
60.6
18.8
51.4
11.5
35.0
25.0
…
3.4
14.4

7.2
34.7 c
9.0
3.2
20.2 c
7.2
…
12.8
19.0 c
30.9
…
49.3
8.7
42.4 c
6.4
32.1 c
16.1
22.0
4.1 c
9.9

1.6
9.7
9.7
4.4
9.8
4.8
…
9.2
9.1
18.5
…
31.5
5.9
24.3
7.3
3.6
…
…
0.9
5.0

2.8
15.0 c
3.7
1.1 c
8.3 c
3.1
…
5.4
8.1 c
10.7 c
…
26.3 c
2.4
19.0 c
6.6
13.1 c
9.2 c
9.1
0.7
3.8

3.6
1.5 c
2.5
4.1
2.9 c
3.9
…
4.1
3.4 c
3.7 c
…
1.6
4.2
2.5 c
3.9
3.2
3.8 c
2.5
4.8 c
4.6

1.9
13.2
7.0
0.9
10.1
2.8
…
16.5
16.1
33.2
26.8
20.6
13.9
11.9
7.0
3.7
10.7
10.4
7.4
7.7

5.4
7.5
5.7
0.7
6.7
5.1
4.0
11.6
10.3
22.7
17.3
16.6
7.5
9.6
6.8
4.6
7.1
5.3
4.5
4.4

2
28
12
8
17
6
8
8
12
16
65
23
5
30
21
18
42
27
7
11

2
23
8
4
14
4
2
5
11
23
47
22
5
27
25
15
12
27
3
18

Millennium Development
Goals

Caribbean countries

…

…

…

…

…

9.0

5.9

14

10

Anguila
Antigua and Barbuda
Netherlands Antilles
Aruba
Bahamas
Barbados
Belize
Dominica
Grenada
Guadeloupe
French Guiana
Guyana
Cayman Islands
Turks and Caicos Islands
British Virgin Islands
United States
Virgin Islands
Jamaica
Martinique

…
…
…
…
…
…
…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…
…
…
…
…
…
…

…
…
…
…
…
…
…
…
…
…
…
…
…
…
…

…
9.5
…
…
…
5.9
6.2
…
…
…
…
18.3
…
…
…

…
1.6
…
…
…
…
…
5.9
0.1
…
…
13.6
…
…
…

…
…
14
…
9
…
7
4
9
…
…
21
…
…
…

…
…
12
…
7
…
5
8
7
…
…
9
…
…
…

…

…

…

…

…

…

…

…

…

…
…

…
…

…
…

…
…

…
…

7.2
…

3.6
…

14
…

10
…

Social Panorama of Latin America • 2007

451

Table 48 (concluded)
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 1: Eradicate extreme poverty and hunger
Target 1: Halve, between 1990 and 2015, the proportion of
people whose income is less than one dollar a day
Indicator 1
Population living in
extreme poverty,
measured by
national poverty
lines

Indicator 2
Poverty gap ratio

Indicator 3 Share
of poorest quintile in
national consumption

Level

Level

Level

Level

Level

1990

2006

1990

2006

2006

Target 2: Halve, between 1990 and 2015, the
proportion of people who suffer from hunger
Indicator 4
Prevalence of
underweight children
under five years of age

Level

Level

Indicator 5
Proportion of
population below
minimum level of
dietary energy
consumption
Level

Level

1981/1993 1995/2006 1990/1992 2001/2003

Montserrat

…

…

…

…

…

…

…

…

…

Puerto Rico

…

…

…

…

…

…

…

…

…

Saint Kitts and Nevis
Saint Vincent and the
Grenadines
Saint Lucia

…

…

…

…

…

…

…

13

11

…

…

…

…

…

…

19.5

22

12

…

…

…

…

…

13.8

…

8

5

Suriname

…

…

…

…

…

…

13.3

13

10

Trinidad and Tobago

…

…

…

…

6.7

5.9

13

11

…

Source: United Nations, Millennium Development Goals: a Latin America and Caribbean perspective (LC/G.2331-P), J.L. Machinea, A. Bárcena and A.
León (coords.), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), June 2005; United Nations, Millennium Indicators
Database [online] http://mdgs.un.org/unsd/mdg/Default.aspx.
a

Millennium Development
Goals

The indicators appear in the order in which they are listed officially; the absence of any indicator is due to lack of information. Figures are percentages
unless otherwise indicated. For indicators recorded at two different times, the regional and subregional averages take into account only those countries
for which information is available at both times.
b The figures for indicators 1, 2 and 3 relate to urban areas.
c Figures relate to the most recent year for which information was available (as distinct from the year in the heading of the column).

452

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 49
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS
Country or territory

a

Goal 2: Achieve universal primary education
Target 3: Ensure that, by 2015, children everywhere, boys and girls alike,
will be able to complete a full course of primary schooling
Indicator 6
Net enrolment ratio in
primary education

Indicator 7
Pupils completing primary education according
to the International Standard Classification of
Education (ISCED) 1997

Indicator 8
Literacy rate of 15-24
year-olds

Level

Millennium Development
Goals

Latin America and the Caribbean
Latin America
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Ecuador
El Salvador
Guatemala
Haiti
Honduras
Mexico
Nicaragua
Panama
Paraguay
Peru
Dominican Republic
Uruguay
Venezuela (Bol. Rep. of)
Caribbean countries
Anguila
Antigua and Barbuda
Netherland Antilles
Aruba
Bahamas
Barbados
Belize
Dominica
Grenada
Guadeloupe
French Guiana
Guyana
Cayman Islands
Turks and Caicos Islands
British Virgin Islands
United States Virgin Islands
Jamaica
Martinique
Montserrat
Puerto Rico
Saint Kitts and Nevis
Saint Vincent and the Grenadines
Saint Lucia
Suriname
Trinidad and Tobago

Level

Level

Level

Level

Level

1990

2005

1992

2005

1990

2000/2005

87.5

96.3

87.5
93.8
90.8
85.6
87.7
68.1
87.3
98.6
97.8
72.8
64.0
22.1
89.9
100.0
72.2
91.5
92.8
87.8
58.2
91.9
88.1
91.5
…
…
…
…
89.6
80.1
94.0
…
…
…
…
88.9
…
…
…
95.7
…
…
…
…
…
95.1
78.4
90.9

96.3
99.5 b
96.5 b
96.4 b
94.1
89.9
90.4 b
99.4
97.7 b
94.8
95.6
…
93.7
99.8
93.7
99.1
88.2 b
99.2
89.5
96.2 b
92.8
93.7
92.4
…
88.4 b
99.5
91.4
97.6
97.5
88.5
86.5
…
…
99.2 b
87.2 b
80.7
97.6
…
90.7
…
98.2
…
95.6
92.4
97.9
95.7
94.8

…
83.8
97.1
67.1
82.2
95.5
85.6
84.6
96.0
89.8
69.0
52.2
…
61.7
86.7
60.2
89.3
78.3
85.4
76.3
96.2
88.3
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…

…

92.6

95.8

90.9
97.1
88.7 b
92.6
98.3 b
91.1
92.3
97.9
92.8
76.1 b
58.3 b
…
70.6 b
93.9
64.5 b
95.0
89.5
91.6 b
86.1
96.4
91.5
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…

92.6
98.2
92.6
91.8
98.1
94.9
97.4
96.2 c
95.5
83.8
73.4
54.8
79.7
95.2
68.2
95.3
95.6
94.5
87.5
98.7
96.0
95.1
…
…
97.5
…
96.5
99.8
96.0
…
…
…
…
99.8
…
…
…
…
91.2
…
…
96.1
…
…
…
…
99.6

95.8
98.6
97.3
96.8
99.0
98.0
98.4
100.0
96.4
88.9
80.1
66.2
88.9
96.6
86.2
97.0
96.3
97.1
91.7
99.1
98.2
96.6
…
…
98.3
…
…
99.8
84.2
…
…
…
…
…
…
…
…
…
94.5
99.8
…
97.7
…
…
…
94.9
99.8

Source: United Nations, Millennium Development Goals: a Latin America and Caribbean perspective (LC/G.2331-P), J.L. Machinea, A. Bárcena and A.
León (coords.), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), June 2005; United Nations Millennium Indicators
Database [online] http://mdgs.un.org/unsd/mdg/Default.aspx.
a

The indicators appear in the order in which they are listed officially; the absence of any indicator is due to lack of information. Figures are percentages
unless otherwise indicated. For indicators recorded at two different times, the regional and subregional averages take into account only those countries
for which information is available at both times.
b Figures relate to the most recent year for which information was available (as distinct from the year appearing in the heading of the column).
c The information provided is from the 1981 population and housing census.

Social Panorama of Latin America • 2007

453

Table 50
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 3: Promote gender equality and empower women
Target 4: Eliminate gender disparity in primary and secondary education, preferably by 2005
and in all levels of education no later than 2015
Indicator 9
Ratio of girls to boys in:
Primary

Secondary

Indicator 9
Ratio of women to men
completing primary
education according
to the International
Standard Classification
of Education (ISCED)
1997

Tertiary

Indicator 10
Literacy gender
parity index

Level

Level

Level

Level

Level

Level

Level

Level

Level

1990

2005

1990

2005

1990

2005

1992

2005

1990 2000/2004

Latin America and
the Caribbean

1.98

0.96

1.08

1.07

0.97

1.22

…

…

1.06

1.01

37.8

43.2

8

17

Latin America

0.98

0.96

1.08

1.07

0.97

1.21

1.01

1.02

1.07

1.01

37.7

43.2

8

17

Argentina

1.04

0.99 b

Bolivia

0.91

1.00 b

Brazil

0.94

Chile

…

1.07 b

0.85

0.97 b

0.93 b

…

0.98

0.95 b

1.08

Colombia

1.15

0.98

1.13

1.11

Costa Rica

0.99

0.99

1.05

1.06

Cuba

0.93

0.95

1.10

Ecuador

0.99

1.00

…

El Salvador

1.01

0.96

Guatemala

0.88

0.92

Haiti

0.94

Honduras

1.05

Mexico

0.98

Nicaragua

1.06

Panama

0.96

Paraguay

Level

Indicator 11
Indicator 12
Share of women in Proportion
wage employment of seats held
in the nonby women
agricultural sector
in national
parliament
Level

Level

Level

Level

1990

2005

1990

2007

…

1.41 b

1.01

1.01

0.81

1.00

37.3

45.1

6

35

…

0.55 b

0.89

0.96 b

2.88

0.98

35.2

36.5 b

9

17

1.10 b

1.06

1.32 b

1.05

1.04

0.72

1.03

40.2

46.7 b

5

9

1.01 b

…

0.95 b

1.01

1.01 b

0.80

1.00

36.2

37.9

…

15

1.07

1.09

1.03

1.05

0.78

1.01

39.9

48.3 b

5

8

…

1.26

1.00

1.03

0.80

1.01

37.2

39.6

11

39

0.96

1.34

1.80

…

1.01 b

1.09

1.00

39.6

43.1

34

1.10

…

…

0.99

1.02

1.28

1.00

37.3

42.0

5

25

1.06

1.03

0.71

1.23

0.96

1.05 b

1.17

0.98

32.3

34.8 b

12

17

…

0.91

…

0.72 b

0.72

0.82 b

1.73

0.86

36.8

38.8 b

7

8

…

0.96

…

…

…

…

1.05

1.01

…

…

…

4

1.00

…

1.24

0.77

1.46 b

1.06

1.11 b

0.89

1.05

48.1

45.3

10

23

0.98

1.01

1.07

0.74

0.99

0.97

0.99

1.38

1.00

35.3

39.1

12

23

0.97

1.37

1.15

1.06

1.11 b

1.09

1.21 b

0.97

1.06

…

…

15

19

0.97

1.07

1.07

…

1.63

1.01

1.00

1.21

0.99

44.3

43.4

8

17

0.97

0.97 b

1.04

1.02 b

1.34 b

0.96

1.06

1.17

1.00

40.5

43.9 b

6

10

Peru

0.97

1.00

…

1.01

…

1.03

0.90

0.97 b

2.53

0.98

28.9

37.5

6

29

Dominican Republic

1.02

0.95

…

1.21

…

1.64 b

1.09

1.08

0.90

1.02

35.5

38.3

8

20

0.99

0.98 b

…

1.15 b

…

2.04 b

1.01

1.02

0.53

1.01

41.9

48.0

6

11

1.03

0.98

1.38

1.13

…

1.08

1.05

1.05

0.74

1.01

35.2

41.5 b

10

18

Caribbean countries 0.99

0.99

1.08

1.06

0.81

2.00

…

…

0.56

1.03

45.3

43.0

12

17

Anguila
Antigua and
Barbuda
Netherland Antilles

…

1.06

…

0.97

…

3.11

…

…

…

…

…

46.9 b

…

…

Aruba
Bahamas
Barbados
Belize
Dominica
Grenada
Guadeloupe
French Guiana
Guyana
Cayman Islands
Turks and Caicos
Islands
British Virgin
Islands

…

…

…

…

…

…

…

…

…

…

…

…

…

11

…

0.98 b

…

1.09 b

…

1.48 b

…

…

0.85

1.00

43.1

48.8 b

…

…

…

0.97

…

1.03

…

1.49

…

…

…

…

…

44.4 b

…

…

1.03

1.00

…

1.00

…

…

…

…

0.54

…

49.2

50.0

4

20
13

1.00

1.00

…

1.00

1.26

2.47 b

…

…

1.00

1.00

45.5

48.7 b

4

0.98

0.96

1.15

1.02

…

2.43 b

…

…

0.73

1.01

37.4

41.3 b

…

7

…

0.99

…

0.97

…

…

…

…

…

…

…

45.8 b

10

13

…

0.96

…

1.03

…

…

…

…

…

…

…

42.7 b

…

27

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

41.6 b

…

…

0.98

0.98

1.06

1.02

…

2.13

…

…

1.00

…

…

39.9 b

37

29

…

0.89

…

0.92

…

…

…

…

…

…

…

50.6 b

…

…

…

1.04

…

0.94

…

0.44

…

…

…

…

…

…

…

…

…

0.96

…

1.18

…

2.28

…

…

…

…

…

…

…

…

Millennium Development
Goals

Uruguay
Venezuela
(Bol. Rep. of)

0.88

…

36 b

454

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 50 (concluded)
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 3: Promote gender equality and empower women
Target 4: Eliminate gender disparity in primary and secondary education, preferably by 2005
and in all levels of education no later than 2015
Indicator 9
Ratio of women to men
completing primary
education according
to the International
Standard Classification
of Education (ISCED)
1997

Indicator 9
Ratio of girls to boys in:
Primary

Secondary

Tertiary

Indicator 10
Literacy gender
parity index

Level

Level

Level

Level

Level

Level

Level

Level

Level

1990
United States Virgin
Islands

Level

Indicator 11
Indicator 12
Share of women in Proportion
wage employment of seats held
in the nonby women
agricultural sector
in national
parliament

2005

1990

2005

1990

2005

1992

2005

1990 2000/2004

Level

Level

Level

Level

1990

2005

1990

2007

…

…

…

…

…

…

…

…

…

…

…

2.29 b

…

…

…

0.99

1.00

1.06

1.03

0.73

…

…

0.37

1.07

49.6

47.4

5

12

Martinique

…

…

…

…

…

…

…

…

0.55

1.00

…

48.1 b

…

…

Montserrat

…

1.04

…

1.10

…

…

…

…

…

…

…

…

…

…

Puerto Rico

…

…

…

…

…

…

…

…

0.65

1.01

46.5

39.3 b

…

…

Saint Kitts
and Nevis

…

1.06

…

0.98

…

…

…

…

…

…

…

…

7

0

Saint Vincent and
the Grenadines

0.99

0.90

1.24

1.24

…

…

…

…

…

…

…

…

10

18

Saint Lucia

0.94

0.97

1.45

1.21

1.38

2.80

…

…

…

…

…

48.0

…

6

Suriname

1.00

1.00

1.15

1.33

…

1.69 b

…

…

…

…

39.1

33.1 b

8

26

Trinidad and Tobago 0.99

0.97

1.05

1.04

0.79

1.27

…

…

…

1.00

35.6

43.6

17

19

Jamaica

Source: United Nations, Millennium Development Goals: a Latin America and Caribbean perspective (LC/G.2331-P), J.L. Machinea, A. Bárcena and A.
León (coords.), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), June 2005; United Nations Millennium Indicators
Database [online] http://mdgs.un.org/unsd/mdg/Default.aspx.
a

Millennium Development
Goals

The indicators appear in the order in which they are listed officially; the absence of any indicator is due to lack of information. Figures are percentages
unless otherwise indicated. For indicators recorded at two different times, the regional and subregional averages take into account only those countries
for which information is available at both times.
b Figures relate to the most recent year for which information was available (as distinct from the year appearing in the heading of the column).

Social Panorama of Latin America • 2007

455

Table 51
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 4: Reduce child mortality

Goal 5: Improve maternal health

Target 5: Reduce by two thirds, between 1990 and 2015,
the under-five mortality rate

Target 6: Reduce by three quarters,
between 1990 and 2015, the maternal
mortality ratio

Indicator 13 Under-five
Indicator 14 Infant
mortality rate
mortality rate
(per 1 000 live births) (per 1 000 live births)

Indicator 15
Children immunized
against measles

Indicator 16
Indicator 17
Maternal mortality Proportion of births
ratio (per 100 000 attended by skilled
live births)
health personnel

Level
Latin America and the
Caribbean
Latin America
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Ecuador
El Salvador
Guatemala
Haiti
Honduras
Mexico
Nicaragua
Panama
Paraguay
Peru
Dominican Republic
Uruguay
Venezuela (Bol. Rep. of)

Level

Level

Level

Level

Level

Level

Level

1990

2007

1990

2007

1990

2007

2005

2000

…

…

41.9

21.4

76

92

126

85

55.6

27.8

42.3

21.6

76

92

127

85

30.0
113.0
59.6
19.3
52.3
18.6
13.2
65.3
64.1
85.0
133.5
66.8
44.3
75.8
35.8
55.8
85.7
70.7
25.0
30.3

16.1
62.1
29.5
9.1
26.2
11.1
7.1 b
26.4
29.6
39.9
73.0
42.4
20.5
26.6
24.3
38.4
30.2
33.6
16.2
24.0

25.8
81.9
47.5
16.3
31.1
16.0
10.7
49.9
47.1
60.4
92.1
47.7
36.3
55.7
28.3
45.0
56.9
54.6
21.4
25.0

13.6
46.6
24.0
7.3
19.2
10.0
5.3 b
21.5
22.0
31.0
49.6
28.5
17.1
22.0
18.4
32.4
22.1
30.1
13.2
17.2

93
53
78
82
82
90
94
60
98
68
31
90
75
82
73
69
64
96
97
61

99
64
99
90
89
89
96 b
93
99
77
54
92
96
96
99
90
80
99
95
76

77
290
110
16
120
30
51
110
170
290
670
280
60
170
83
150
240
77 b
20
57

99
65
97 b
100
86 b
98
100 b
69 b
69
41
24 b
56
85 b
67
90 b
86 b
59 b
99
100 b
94 b

…

21.8

22.3

14.6

75

89

70

94

…
…
…
…
…
…
…
…
…
…
…
…
…
…
…

…
12.0 b
17.0
20.2
17.2
11.3
20.3
15.0 b
41.6
9.1
15.2
58.1
…
…
…

…
…
16.6
16.9
21.5
14.6
32.3
…
44.1
15.6
22.4
64.6
…
…
…

…
11.0 b
14.8
17.2
14.0
10.3
16.6
13.0 b
34.2
6.9
13.5
43.6
…
…
…

…
89
…
…
86
87
86
88
85
…
…
73
…
…
…

…
99
…
…
85
93
95
98
99
…
…
92
…
…
95 b

…
65 b
…
…
16
16
52
…
…
…
…
470
…
…
…

…
100 b
…
99 b
99 b
98 b
100 b
100 b
100 b
…
…
90 b
…
88 b
…

…

10.1

15.6

8.7

…

…

…

…

…
…
…
…

17.2
8.1
…
9.1

21.9
9.8
…
12.7

13.7
6.6
…
7.3

74
…
…
…

84
…
…
…

26
…
…
18

95 b
…
…
…

Millennium Development
Goals

Caribbean countries
Anguila
Antigua and Barbuda
Netherland Antilles
Aruba
Bahamas
Barbados
Belize
Dominica
Grenada
Guadeloupe
French Guiana
Guyana
Cayman Islands
Turks and Caicos Islands
British Virgin Islands
United States Virgin
Islands
Jamaica
Martinique
Montserrat
Puerto Rico

456

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 51 (concluded)
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 4: Reduce child mortality

Goal 5: Improve maternal health

Target 5: Reduce by two thirds, between 1990 and 2015,
the under-five mortality rate

Target 6: Reduce by three quarters,
between 1990 and 2015, the maternal
mortality ratio

Indicator 13 Under-five
Indicator 14 Infant
mortality rate
mortality rate
(per 1 000 live births) (per 1 000 live births)

Indicator 15
Children immunized
against measles

Indicator 16
Indicator 17
Maternal mortality Proportion of births
ratio (per 100 000 attended by skilled
live births)
health personnel

Level

Level

Level

Level

Level

Level

Level

Level

1990

2007

1990

2007

1990

2007

2005

2000

Saint Kitts and Nevis
Saint Vincent and the
Grenadines
Saint Lucia

…

…

…

…

28.4

32.3

…

16.3

18.4

12.0 b

Suriname

…

35.4

34.9

28.1

Trinidad and Tobago

…

18.2

15.8

12.7

70

18.0 b

99

99

…

99

23.6

96

97

…

100 b

82

94

35 b

100 b

65

91

72

91 b

93

45

96 b

Source: United Nations, Millennium Development Goals: a Latin America and Caribbean perspective (LC/G.2331-P), J.L. Machinea, A. Bárcena and A.
León (coords.), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), June 2005; United Nations Millennium Indicators
Database [online] http://mdgs.un.org/unsd/mdg/Default.aspx.
a

Millennium Development
Goals

The indicators appear in the order in which they are listed officially; the absence of any indicator is due to lack of information. Figures are percentages
unless otherwise indicated. For indicators recorded at two different times, the regional and subregional averages take into account only those countries
for which information is available at both times.
b Figures relate to the most recent year for which information was available (as distinct from the year appearing in the heading of the column).

Social Panorama of Latin America • 2007

457

Table 52
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 6: Combat HIV/AIDS, malaria and other diseases
Target 7: Have halted by
2015 and begun to reverse
the spread of HIV/AIDS

Target 8: Have halted by 2015 and begun to reverse the incidence
of malaria and other major diseases

Indicator 18a
Indicator 21a
Indicator 23a
HIV/AIDS prevalence among
Incidence of
Incidence of tuberculosis per
the population aged 15-49 malaria per 100 000
100 000 population
population

Indicator 23b
Tuberculosis death rate per
100 000 population

Level

Level

Level

Level

Level

Level

2005

2000

1990

2005

1990

2005

0.63

0.57

217

155

78

14

9

0.61
0.7
0.1
0.6
0.3
0.5
0.6
0.1
0.3
0.6
1.1
5.5
1.6
0.3
0.2
0.7
0.4
0.4
1.8
0.3
0.6
1.73
…
…
…
…
3.0
1.5
2.1
…
…
…
…
2.5
…
…
…

0.55
0.6
0.1
0.5
0.3
0.6
0.3
0.1
0.3
0.9
0.9
3.8
1.5
0.3
0.2
0.9
0.4
0.6
1.1
0.5
0.7
2.02
…
…
…
…
3.3
1.5
2.5
…
…
…
…
2.4
…
…
…

210
1
378
344
…
250
42
0
728
11
386
15
541
8
402
36
124
258
6
…
94
1 421
…
…
…
…
…
…
657
…
…
…
2 073
3 074
…
…
…

157
113
454
146
90
90
34
4
315
155
154
604
181
76
241
110
118
618
214
54
68
34
49
13
18
…
84
27
64
30
10
…
…
61
…
…
29

79
51
280
76
16
66
17
5
202
68
110
405
99
27
74
46
100
206
116
33
52
29
39
9
18
…
49
12
55
24
8
…
…
194
6
31
24

15
10
42
14
8
8
3
0.5
29
14
14
56
17
7
22
10
11
57
20
5
6
3
5
1
2
…
8
3
6
3
1
…
…
6
…
…
3

9
6
31
8
1
7
1
0.3
27
8
13
58
12
2
8
4
12
20
14
3
6
4
4
1
2
…
6
1
5
3
1
…
…
25
1
3
3

…

…

…

26

17

2

2

0.8
…
…
…
…

1.5
…
…
…
…

…
…
…
…
…

13
…
18
30
21

10
…
12
6
17

1
…
2
3
2

1
…
1
1
2

…

…

…

56

42

5

5

…
1.3
3.0

…
1.9
2.6

…
2 954
1

32
152
21

22
99
13

3
14
2

2
13
1

Source: United Nations, Millennium Development Goals: a Latin America and Caribbean perspective (LC/G.2331-P), J.L. Machinea, A. Bárcena and A.
León (coords.),Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), June 2005; United Nations Millennium Indicators
Database [online] http://mdgs.un.org/unsd/mdg/Default.aspx.
a

The indicators appear in the order in which they are listed officially; the absence of any indicator is due to lack of information. Figures are percentages
unless otherwise indicated. For indicators recorded at two different times, the regional and subregional averages take into account only those countries
for which information is available at both times.

Millennium Development
Goals

Latin America
and the Caribbean
Latin America
Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Ecuador
El Salvador
Guatemala
Haiti
Honduras
Mexico
Nicaragua
Panama
Paraguay
Peru
Dominican Republic
Uruguay
Venezuela (Bol. Rep. of)
Caribbean countries
Anguila
Antigua and Barbuda
Netherland Antilles
Aruba
Bahamas
Barbados
Belize
Dominica
Grenada
Guadeloupe
French Guiana
Guyana
Cayman Islands
Turks and Caicos Islands
British Virgin Islands
United States Virgin
Islands
Jamaica
Martinique
Montserrat
Puerto Rico
Saint Kitts and Nevis
Saint Vincent and the
Grenadines
Saint Lucia
Suriname
Trinidad and Tobago

Level

2001

458

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 53
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 7: Ensure environmental sustainability
Target 9: Integrate the principles of sustainable development into country policies and programmes
and reverse the loss of environmental resources
Indicator 25
Proportion
of land area
covered by
forest

Indicator 28b
Indicator 29
Indicator 26
Indicator 27 Energy
Indicator 28a
Ozone-depleting
Per capita
Ratio of area use (kg oil equivalent)
Carbon dioxide
protected
per US$ 1 000 GDP
(CO2) emissions, chlorofluorocarbons, consumption of
consumption in
biomass fuels
to maintain PPP (purchasing power metric tons per
1 000 population ozone-depleting
(fuelwood+cane
biological
parity)
potential (ODP)
residues+other
diversity to
metric tons
primary fuels)
surface area

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

1990

2005

1990

2005

1990

2004

1990

2004

1990

2003

1990

2001

Latin America and the
Caribbean
Latin America

49.2

45.8

12.9

18.4

170

170

2.5

2.6

34 480

8 611

0.07

0.06

48.4

44.9

13.3

18.9

166

167

2.4

2.5

33 331

8 521

0.08

0.07

Argentina

12.9

12.1

5.0

6.2

161

141

3.4

3.7

2 138

1 676

…

…

Bolivia

57.9

54.2

8.8

19.8

202

225

0.8

0.8

23

27

0.09

0.02
0.04

Brazil

61.5

56.5

15.7

18.7

138

148

1.4

1.8

8 539

967

0.05

Chile

20.4

21.5

13.4

20.8

186

171

2.7

3.9

662

222

0.14

0.18

Colombia

59.1

58.5

31.5

31.6

129

99

1.7

1.2

2 026

557

0.10

0.04
0.01

Costa Rica

50.2

46.8

18.9

23.3

105

100

0.9

1.5

342

96

0.16

Cuba

18.7

24.5

…

15.7

…

270

3.3

2.3

778

209

…

…

Ecuador

49.9

39.2

16.3

53.5

184

207

1.6

2.3

604

133

0.05

0.03

El Salvador

18.1

14.4

0.9

0.9

138

143

0.5

0.9

384

119

0.17

0.16

Guatemala

43.8

36.3

25.9

30.8

148

153

0.6

1.0

357

58

0.30

0.27

Haiti
Honduras

4.2

3.8

0.1

0.1

108

180

0.1

0.2

0

81

0.11

0.11

66.0

41.5

14.6

20.0

181

183

0.5

1.1

0

123

0.25

0.16

Mexico

36.2

33.7

2.5

8.7

194

173

4.9

4.2

12 037

1 604

0.07

0.06

Nicaragua

53.9

42.7

8.1

18.2

192

191

0.6

0.7

87

36

0.22

0.22

Panama

58.8

57.7

18.9

24.6

137

124

1.3

1.8

252

93

0.13

0.13

Paraguay

53.3

46.5

2.9

5.8

165

164

0.5

0.7

171

251

0.27

0.18

Peru

54.8

53.7

4.8

13.3

120

93

1.0

1.2

801

128

0.11

0.07

Dominican Republic

28.4

28.4

11.5

32.6

132

126

1.3

2.1

256

204

0.08

0.06
0.09

5.2

8.6

0.3

0.4

104

100

1.3

1.6

531

98

0.10

Venezuela (Bol. Rep. of)

Uruguay

59.0

54.1

39.8

62.9

386

390

6.0

6.6

3 343

1 842

…

…

Caribbean countries

81.7

81.6

2.0

5.5

552

565

5.5

7.9

1 149

91

0.09

0.10

214

10

…

…

4.9

5.1

421

1

…

…
…

Anguila

75.0

75.0

…

0.1

…

…

Antigua and Barbuda

20.5

20.5

0.9

0.9

…

…

Netherlands Antilles

1.3

1.3

…

1.1

…

…

6.3

22.2

…

Aruba

2.2

2.2

…

0.1

…

…

28.9

21.3

…

…

51.4

51.4

0.4

0.9

…

…

7.6

6.3

51

…

…

Millennium Development
Goals

Bahamas
Barbados

13

4.7

4.7

0.1

0.1

…

…

4.0

4.4

21

7

…

…

Belize

72.5

72.5

14.9

30.4

…

…

1.7

2.9

15

10

…

…

1

…

…

4

1

0.04

0.05
…

Dominica

66.7

61.3

3.7

4.5

…

…

0.9

1.6

Grenada

11.8

11.8

0.1

0.1

…

…

1.3

2.1

Guadeloupe

49.7

47.3

…

3.1

…

…

3.3

4.0

…

French Guiana

91.8

91.5

…

5.4

…

…

6.9

5.4

…

…

Guyana

76.7

76.7

…

2.2

…

…

1.6

2.0

0.28

0.29

19

24

Cayman Islands

46.2

46.2

…

92.7

…

…

9.5

7.0

…

…

Turks and Caicos Islands

79.1

79.1

…

…

…

…

…

…

…

…

British Virgin Islands

26.7

26.7

…

34.6

…

…

2.9

3.9

…

…

United States Virgin
Islands

35.3

29.4

…

3.0

…

…

…

…

…

…

Social Panorama of Latin America • 2007

459

Table 53 (concluded)
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 7: Ensure environmental sustainability
Target 9: Integrate the principles of sustainable development into country policies and programmes
and reverse the loss of environmental resources
Indicator 25
Proportion
of land area
covered by
forest

Indicator 28b
Indicator 29
Indicator 26 Indicator 27 Energy use Indicator 28a
Ozone-depleting
Per capita
Ratio of area (kg oil equivalent) per
Carbon dioxide
protected
US$ 1 000 GDP PPP (CO2) emissions, chlorofluorocarbons, consumption of
metric tons per
consumption in
biomass fuels
to maintain
(purchasing
1 000 population ozone-depleting
(fuelwood+cane
biological
power parity)
potential (ODP)
residues+other
diversity to
metric tons
primary fuels)
surface area

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

1990

2005

1990

2005

1990

2004

1990

2004

1990

2003

1990

2001

5

0.03

0.04

Jamaica

31.9

31.3

3.6

13.5

383

409

3.4

4.0

Martinique

43.4

43.4

…

10.5

…

…

5.7

3.3

424

…

…

Montserrat

40.0

40.0

…

10.7

…

…

3.1

11.6

…

…

Puerto Rico

45.5

46.0

…

2.5

…

…

…

…

…

…

Saint Kitts and Nevis

13.9

13.9

9.6

9.6

…

…

1.6

2.6

6

2

…

…

Saint Vincent and the
Grenadines

23.1

28.2

1.3

1.3

…

…

0.7

1.7

3

1

…

…

Saint Lucia

27.9

27.9

2.2

2.4

…

…

1.2

2.3

8

2

…

…

Suriname

94.7

94.7

2.2

11.5

…

…

4.5

5.1

40

8

0.08

0.09

Trinidad and Tobago

45.8

44.1

1.7

1.8

706

712

13.8

24.7

138

18

…

…

Source: United Nations, Millennium Development Goals: a Latin America and Caribbean perspective (LC/G.2331-P), J.L. Machinea, A. Bárcena and A.
León (coords.), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), June 2005; United Nations Millennium Indicators
Database [online] http://mdgs.un.org/unsd/mdg/Default.aspx.
The indicators appear in the order in which they are listed officially; the absence of any indicator is due to lack of information. Figures are percentages
unless otherwise indicated. For indicators recorded at two different times, the regional and subregional averages take into account only those countries
for which information is available at both times.

Millennium Development
Goals

a

460

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 54
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 7: Ensure environmental sustainability
Target 10. Halve, by 2015, the proportion of people without sustainable access to
safe drinking water and sanitation

Indicator 30
Indicator 30
Sustainable
Sustainable
access to
access to
improved water improved water
sources National sources Urban
total
areas

Indicator
Indicator 30
Indicator 31
31 Access
Sustainable
Access to
to improved
access to
improved
sanitation
improved water
sanitation
sources Rural National totall Urban areas
areas

Target 11: By
2020, to have
achieved a
significant
improvement in
the lives of at least
100 million
slum-dwellers

Indicator 31 Indicator 32 Slum
Access to dwellers in urban
improved
areas
sanitation
Rural areas

Level

Level

Level

Level

Level

Level

Level Level Level Level Level Level

Level

Level

1990

2004

1990

2004

1990

2004

1990

2004

1990

2004

1990

2004

1990

2001

Latin America and the
Caribbean

83

91

93

96

60

73

68

77

81

86

36

49

35

32

Latin America

84

92

92

78

60

72

68

78

81

87

34

48

36

33

Argentina

94

96

97

98

72

80

81

91

86

92

45

83

31

33

Bolivia

72

85

91

95

49

68

33

46

49

60

14

22

70

61

Brazil

83

90

93

96

55

57

71

75

82

83

37

37

45

37

Chile

90

95

98

100

49

58

84

91

91

95

52

62

4

9

Colombia

92

93

98

99

78

71

82

86

95

96

52

54

26

22

Costa Rica

…

97

100

100

…

92

…

92

…

89

97

97

12

13

Cuba

…

…

84

98

78

87

…

…

96

98

68

86

…

…

Ecuador

73

94

82

97

61

89

63

89

77

94

45

82

28

26

El Salvador

67

84

87

94

48

70

51

62

70

77

33

39

45

35

Guatemala

79

95

89

99

72

92

58

86

73

90

47

82

66

62

Haiti

47

54

60

52

42

56

24

30

25

57

23

14

85

86

Honduras

84

87

92

95

79

81

50

69

77

87

31

54

24

18

Mexico

82

97

89

10

64

87

58

79

75

91

13

41

23

20

Nicaragua

70

79

91

90

46

63

45

47

64

56

24

34

81

81

Panama

90

90

99

99

79

79

71

73

89

89

51

51

31

31

Paraguay

62

86

81

99

44

68

58

80

72

94

45

61

37

25

Peru

74

83

89

89

41

65

52

63

69

74

15

32

60

68

Dominican Republic

84

95

98

97

66

91

52

78

60

81

43

73

56

38

100

100

100

100

100

100

100

100

100

100

99

99

7

7

Venezuela (Bol. Rep. of)

…

83

…

85

…

70

…

68

…

71

…

48

41

41

Caribbean countries

93

93

96

96

89

90

88

90

93

96

77

80

13

10

Anguila

…

60

…

60

…

…

99

99

99

99

…

…

40

41

Antigua and Barbuda

…

91

95

95

…

89

…

95

98

98

…

94

7

7

Netherlands Antilles

…

…

…

…

…

…

…

…

…

…

…

…

1

1

100

100

100

100

100

100

…

…

…

…

…

…

2

2

Bahamas

…

97

98

98

…

86

100

100

100

100

100

100

2

2

Barbados

100

100

100

100

100

100

100

100

99

99

100

100

1

1

Belize

…

91

100

100

…

82

…

47

…

71

…

25

54

62

Dominica

…

97

100

100

…

90

…

84

…

86

…

75

17

14

Grenada

…

95

97

97

…

93

97

96

96

96

97

97

7

7

Guadeloupe

…

98

98

98

…

93

…

64

…

64

…

61

7

7

French Guiana

…

84

88

…

71

…

78

…

85

…

57

…

13

13

Guyana

…

83

…

83

…

83

…

70

…

86

…

60

5

5

Cayman Islands
Turks and Caicos
Islands

…

…

…

…

…

…

…

…

…

…

…

…

2

2

100

100

100

100

100

100

…

96

98

98

…

94

2

3

Millennium Development
Goals

Uruguay

Aruba

Social Panorama of Latin America • 2007

461

Table 54 (concluded)
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a
Country or territory

Goal 7: Ensure environmental sustainability
Target 10. Halve, by 2015, the proportion of people without sustainable access to
safe drinking water and sanitation

Indicator 30
Indicator 30
Sustainable
Sustainable
access to
access to
improved water improved water
sources National sources Urban
total
areas

Indicator
Indicator 30
Indicator 31
31 Access
Sustainable
Access to
to improved
access to
improved
sanitation
improved water
sanitation
sources Rural National totall Urban areas
areas

Target 11: By
2020, to have
achieved a
significant
improvement in
the lives of at least
100 million
slum-dwellers

Indicator 31 Indicator 32 Slum
Access to dwellers in urban
improved
areas
sanitation
Rural areas

Level

Level

Level

Level

Level

Level

Level Level Level Level Level Level

Level

Level

1990

2004

1990

2004

1990

2004

1990

2004

1990

2004

1990

2004

1990

2001

British Virgin Islands

100

100

98

98

98

98

100

100

100

100

100

100

3

3

United States Virgin
Islands
Jamaica

…

…

…

…

…

…

…

…

…

…

…

…

2

2

92

93

98

98

86

88

75

80

86

91

64

69

29

36

Martinique

…

…

…

…

…

…

…

…

…

…

…

…

2

2

Montserrat

100

100

100

100

100

100

100

100

96

96

96

96

11

9

…

…

…

…

…

…

…

…

…

…

…

…

2

2

100

100

99

99

99

99

95

95

96

96

96

96

5

5

…

…

…

…

…

93

…

…

…

…

96

96

5

5
12

Puerto Rico
Saint Kitts and Nevis
Saint Vincent and the
Grenadines
Saint Lucia

98

98

98

98

98

98

…

89

…

89

…

89

12

Suriname

…

92

98

98

…

73

…

94

99

99

…

76

7

7

Trinidad and Tobago

92

91

93

92

89

88

100

100

100

100

100

100

35

32

Source: United Nations, Millennium Development Goals: a Latin America and Caribbean perspective (LC/G.2331-P), J.L. Machinea, A. Bárcena and A.
León (coords.), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), June 2005; United Nations Millennium Indicators
Database [online] http://mdgs.un.org/unsd/mdg/Default.aspx. The figures for indicators relating to Cuba were supplied directly by the National Statistical
Office (ONE).
The indicators appear in the order in which they are listed officially; the absence of any indicator is due to lack of information. Figures are percentages
unless otherwise indicated. For indicators recorded at two different times, the regional and subregional averages take into account only those countries
for which information is available at both times.

Millennium Development
Goals

a

462

Economic Commission for Latin America and the Caribbean (ECLAC)

Table 55
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS
Country or territory

a

Goal 8: Develop a global partnership for development
Target 16: In cooperation with developing countries,
develop and implement strategies for decent and
productive work for youth

Target 18: In cooperation with the private sector, make
available the benefits of new technologies, especially
information and communications

Indicator 45a
Unemployment
rate among
young people
aged 15-24
Both sexes

Indicator 45c
Unemployment
rate among
young people
aged 15-24
Females

Indicator 47b
Telephone lines
and cellular
subscribers
per 100
population

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

1990
Latin America
and the Caribbean

Indicator 45b
Unemployment
rate among
young people
aged 15-24
Males

Indicator 48b
Personal
computers in
use per 100
population

Indicator 48d
Internet users
per 100
population

2005

1990

2005

1990

2005

1990

2004

1998

2004

1996

2006

12.5

20.0

11.6

16.6

13.9

24.7

6.4

50.2

3.4

9.2

0.3

16.3

Latin America

12.2

19.9

11.2

16.5

13.5

24.7

6.1

49.3

3.3

9.2

0.3

16.0

Argentina
Bolivia
Brazil
Chile
Colombia
Costa Rica
Cuba
Ecuador
El Salvador
Guatemala
Haiti
Honduras
Mexico
Nicaragua
Panama
Paraguay
Peru
Dominican Republic
Uruguay
Venezuela (Bol. Rep. of)

13.0
4.5
6.7
13.1
27.1
8.3
…
13.5
…
…
…
…
…
11.1
…
15.7
15.8
…
24.9
19.4

24.2
8.5 b
18.1 b
17.3
25.0 b
15.0
3.7 b
15.5
11.5 b
…
17.9 b
7.0
6.6
12.5 b
22.5
13.8 b
20.9
23.1 b
29.5
28.0

11.5
3.1
6.7
13.4
23.4
7.6
…
11.1
…
…
…
…
…
8.6
…
15.0
12.6
…
22.6
20.0

21.6
7.0 b
14.2 b
15.2 b
20.2 b
11.3
3.9 b
12.2
12.7
…
…
5.2
6.1
10.8 b
18.5
11.7 b
21.0
…
25.4
23.7 b

15.6
8.7
6.8
12.4
31.4
10.0
…
17.3
…
…
…
…
…
16.7
…
16.5
19.7
…
28.1
17.9

28.0
10.4 b
23.3 b
21.0
31.7 b
21.5
3.4 b
20.6
9.4 b
…
21.1 b
11.2
7.4
15.8 b
29.6
17.3 b
20.7
34.3 b
34.9
34.8 b

9.3
2.8
6.5
6.7
6.9
10.1
3.1
4.8
2.4
2.1
0.7
1.7
6.6
1.3
9.3
2.7
2.6
4.8
13.4
7.7

58.1
27.0
59.8
83.6
40.1
53.4
10.0 b
39.1
41.1
34.0
6.6
15.7
53.9
16.8
38.8
34.6 b
22.1
39.5
49.4
45.0

5.5
0.8
3.0
6.3
3.2
7.8
1.4 c
1.9
…
0.8
…
0.8
3.7
1.9
2.7
1.0
3.0
…
9.1
3.9

8.2 b
2.3 b
10.7
13.9
5.5
21.9
3.8 b
5.5
4.5
1.8
…
1.6
10.7
3.5
4.1
5.9
9.7
…
13.3
8.2

0.2
0.2
0.5
0.7
0.3
0.9
0.5 c
0.1
0.1
0.0
0.0
0.0
0.2
0.1
0.2
0.0
0.3
0.1
1.9
0.3

20.9
6.2
17.2 b
25.5
14.5
27.6
2.3
11.5
9.3 b
10.2
7.5
4.6
16.9 b
2.8
6.7
4.1
21.5
13.7
20.6 b
15.2

Caribbean countries

32.9

23.8

32.0

22.8

34.5

28.1

18.2

87.8

6.3

9.5

0.4

27.0

69.0 b

…

…

…

30.7 b

…

…

2.9

35.6 b

…

…

0.2

0.9 b
24.1 b

Anguila

…

13.3 b

…

10.3 b

…

16.6 b

Antigua and Barbuda

…

…

…

…

…

…

…

27.2 b

…

24.9 b

…

30.0 b

24.7

50.8 b

Aruba

…

20.4 b

…

16.8 b

…

24.5 b

28.2

85.0 b

…

…

2.7

Bahamas

…

20.2

…

16.9

…

24.1

28.1

102.8

…

…

1.8

31.9 b

Barbados

30.7

26.2 b

21.8

21.3 b

40.5

26.0 b

28.1

123.9

7.5

12.6

0.4

59.5 b

…

22.5 b

…

15.4 b

…

34.7 b

9.2

48.0

8.8

13.8 b

0.9

12.4

Dominica

…

40.6 b

…

36.4 b

…

46.3 b

16.4

88.1

…

18.2

1.1

28.8 b

Grenada

…

31.5 b

…

25.4 b

…

39.4 b

17.8

73.8

10.8

15.5

0.3

16.9 b

Millennium Development
Goals

Netherlands Antilles

Belize

…
25.3

119.5

29.5

…

21.1

…

40.4

…

30.6

116.6 b

19.1

20.3

0.0

19.0 b

French Guiana

…

…

…

…

…

…

26.5

74.9 b

13.2

18.0

0.4

22.5 b

Guyana

…

20.0 b

…

17.5 b

…

24.4 b

2.0

27.0

2.4

3.5

0.1

21.3 b

Cayman Islands
Turks and Caicos
Islands
British Virgin Islands

…

9.5 b

…

…

…

…

47.0

122.9 b

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

…

41.8

89.6 b

…

…

…

18.2 b

…

…

…

…

…

…

…

…

…

…

26.8 b

Guadeloupe

United States
Virgin Islands

121.7

Social Panorama of Latin America • 2007

463

Table 55 (concluded)
LATIN AMERICA AND THE CARIBBEAN: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS
Country or territory

a

Goal 8: Develop a global partnership for development
Target 16: In cooperation with developing countries,
develop and implement strategies for decent and
productive work for youth

Target 18: In cooperation with the private sector, make
available the benefits of new technologies, especially
information and communications

Indicator 45a
Unemployment
rate among
young people
aged 15-24
Both sexes

Montserrat
Puerto Rico
Saint Kitts and Nevis
Saint Vincent
and the Grenadines
Saint Lucia
Suriname
Trinidad and Tobago

Indicator 47b
Telephone lines
and cellular
subscribers
per 100
population

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

Level

1990

Martinique

Indicator 45c
Unemployment
rate among
young people
aged 15-24
Females

Level

Jamaica

Indicator 45b
Unemployment
rate among
young people
aged 15-24
Males

2005

1990

2005

1990

2005

1990

2004

1998

2004

1996

2006

36.3 b

4.5

96.8

3.9

6.2

0.6

46.5 b

33.9

118.4 b

10.6

20.8

…

32.8 b

…
…

28.1 b
…

…
…

22.0 b
…

…
…

…

Indicator 48b
Personal
computers in
use per 100
population

Indicator 48d
Internet users
per 100
population

…

…

…

…

…

…

32.7

…

…

…

…

…

31.3

23.3

33.3

24.8

27.6

20.9

28.5

97.4

…

…

0.3

23.2 b

…

…

…

…

…

…

23.8

70.0

11.3

22.0

2.0

21.4 b

…

…

…

…

…

…

12.4

75.2

8.9

13.2

0.5

8.4 b

13.3

17.3

…

40.0 b

…

31.8 b

…

49.2 b

12.9

40.9 b

36.6

34.1 b

29.0

23.9 b

46.2

58.2 b

9.2

67.1

36.4

21.1 b

33.1

17.4 b

42.5

26.4 b

14.1

74.4

0.7

36.7 b

…

4.6 b

0.2

7.1 b

4.7

8.0 b

0.4

12.5 b

Source: United Nations, Millennium Development Goals: a Latin America and Caribbean perspective (LC/G.2331-P), J.L. Machinea, A. Bárcena and A.
León (coords.), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), June 2005; United Nations Millennium Indicators
Database [online] http://mdgs.un.org/unsd/mdg/Default.aspx.
a

Millennium Development
Goals

The indicators appear in the order in which they are listed officially; the absence of any indicator is due to lack of information. Figures are percentages
unless otherwise indicated. For indicators recorded at two different times, the regional and subregional averages take into account only those countries
for which information is available at both times.
b Figures relate to the most recent year for which information was available (as distinct from the year appearing in the heading of the column).
c Indicator 48b relates to the year 2000 and indicator 48d to 2002.


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