2010 Social Panorama of Latin America 2 Economic Commission for Latin America and the Caribbean (ECLAC) Alicia Bárcena Executive Secretary Antonio Prado Deputy Executive Secretary Martín Hopenhayn Director of the Social Development Division Luis Beccaria Director of the Statistics and Economic Projections Division Dirk Jaspers_Faijer Director of the Latin American and Caribbean Demographic Centre (CELADE) Population Division of ECLAC Sonia Montaño Director of the Division for Gender Affairs Ricardo Pérez Director of the Documents and Publications Division The Social Panorama of Latin America is prepared each year by the Social Development Division and the Statistics and Economic Projections Division of the Economic Commission for Latin America and the Caribbean (ECLAC), under the supervision of Martín Hopenhayn and Luis Beccaria, respectively. The Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC, directed by Dirk Jaspers_Faijer, was also involved in the preparation of the report. Work on the 2010 edition was coordinated by Juan Carlos Feres, Fernando Filgueira and Martín Hopenhayn, who, together with Simone Cecchini, Ernesto Espíndola, Diego Hernández, Mauricio Holz, Rubén Kaztman, Xavier Mancero, Ciro Martínez, Tim Miller, Paulo Saad, Daniela Trucco, Cassio Turra and Pablo Villatoro, prepared the various chapters. Andrés Espejo, Ernesto Espíndola, Fabiola Fernández, Marco Galván, Diego Hernández, Carlos Howes, Sebastián Möller, Patricio Olivera, Claudia Robles, Nora Ruedi and Luis Hernán Vargas prepared substantive inputs and processed statistical data. The preparation of chapters II and III was supported by the “Sustainability of co-responsibility transfer programmes” project (GER/001/09) being implemented by ECLAC in collaboration with the German Agency for Technical Cooperation (GTZ) and financed by the Ministry for Economic Cooperation and Development of Germany. Chapter V received support from the United Nations Population Fund. Explanatory notes Three dots (...) indicate that data are missing, are not available or are not separately reported. Two dashes and a full stop (-.-) indicate that the sample size is too small to be used as a basis for estimating the corresponding values with acceptable reliability and precision. A dash (-) indicates that the amount is nil or negligible. A blank space in a table indicates that the concept under consideration is not applicable or not comparable. A minus sign (-) indicates a deficit or decrease, except where otherwise specified. The use of a hyphen (-) between years (e.g., 1990-1998) indicates reference to the complete number of calendar years involved, including the beginning and end years. A slash (/) between years (e.g., 2003/2005) indicates that the information given corresponds to one of these two years. The world “dollars” refers to United States dollars, unless otherwise specified. Individual figures and percentages in tables may not always add up to the corresponding total because of rounding. United Nations publication ISBN: 978-92-1-121754-4 E-ISBN: 978-92-1-054537-2 ISSN: 1020-5160 LC/G.2481-P Sales No.: E.11.II.G.6 Copyright © United Nations, March 2011. All rights reserved Printed in Santiago, Chile • 2010-875 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 • 2010 3 Contents Introduction.......................................................................................................................................................... 13 Summary............................................................................................................................................................... 17 Chapter I Poverty, inequality and life cycle.................................................................................................................... 41 A. Poverty and inequality: crisis and recovery....................................................................................................... 41 . 1. Economic context..................................................................................................................................... 42 2. Recent evolution of poverty...................................................................................................................... 43 3. Factors behind the changing poverty rate................................................................................................. 46 4. Recent evolution of inequality.................................................................................................................. 48 5. Multidimensional poverty......................................................................................................................... 51 B. Fertility, early emancipation and poverty....................................................................................................... 54 1. Poverty trends among children and adolescents and some of the demographic determinants................. 54 2. Emancipation paths, poverty and inequality............................................................................................. 58 C. Subjective well-being, living conditions and life cycle: Latin America and other regions of the world......... 62 . 1. Empirical antecedents............................................................................................................................... 63 2. Life satisfaction and income indicators.................................................................................................... 64 3. Satisfaction and life cycle......................................................................................................................... 69 Appendix............................................................................................................................................................. 73 Chapter II Education and the intergenerational reproduction of inequality and exclusion: realities and challenges in Latin America.................................................................................................... A. The education agenda in the region. .............................................................................................................. . B. Gaps in attainment and in learning. ............................................................................................................... . 1. Access to early childhood and preschool education................................................................................. 2. Access to primary education and unequal completion rates. ................................................................... . 3. Unequal access to, progression in and completion of secondary education . .......................................... 4. Discrimination and lag in primary and secondary education among indigenous and Afro-descendent groups............................................................................................................................ 5. Access to and completion of post-secondary education: the bottleneck.................................................. 6. Intergenerational transmission of education inequalities......................................................................... 81 81 83 84 85 86 88 89 90 4 Economic Commission for Latin America and the Caribbean (ECLAC) 7. Learning outcome gaps within and between countries............................................................................. 8. Acquisition of digital competencies: new kinds of exclusion.................................................................. C. The transition from education to employment and the intergenerational reproduction of unequal productive opportunities and access to well-being........................................................................... 1. Minimum thresholds for well-being, credentials and educational devaluation........................................ 2. Education and quality of employment...................................................................................................... 3. Internal rates of return on education......................................................................................................... D. Key factors for fighting inequality from within the educational system: progress and challenges............... . 1. Early entry: early childhood and preschool education.............................................................................. 2. Extended school day................................................................................................................................. 3. Incorporating digital technology into education: cutting-edge competencies.......................................... 4. Support for families in order to reinforce educational progression in vulnerable sectors: conditional cash transfer programmes...................................................................................................... 5. Better training for work............................................................................................................................ 6. Support for continuing higher education ................................................................................................. Appendix............................................................................................................................................................. 91 94 109 111 113 114 Chapter III Public social spending in Latin America: general trends and investment in developing the skills of the new generations......................................................................................... A. Introduction.................................................................................................................................................... B. Public social spending in Latin America and effects of its procyclicality on economic growth. .................. . 1. The long-term trend of public social spending......................................................................................... 2. The procyclicality of social spending relative to economic growth: an ongoing debate.......................... 3. The evolution of social spending by sector.............................................................................................. 4. Expenditure trends during the financial crisis.......................................................................................... 5. Conditional cash transfer programmes: protecting the poor throughout the life cycle............................ C. Social investment at early ages: spending per student................................................................................... 1. Public-sector education spending............................................................................................................. 2. Primary and secondary education spending............................................................................................. 3. The rise in per-student spending and associated factors........................................................................... 4. Resources needed to achieve universal primary and secondary education. ............................................. . 5. The distributive impact of public-sector education spending................................................................... Appendix............................................................................................................................................................. 131 131 132 133 135 137 138 139 142 143 145 148 152 154 156 Chapter IV The generational economy, transfer systems and inequality in Latin America and the Caribbean.............................................................................................................................................. . A. The generational economy............................................................................................................................. B. National transfer accounts: Latin America in the international context......................................................... 1. The economic life cycle............................................................................................................................ 2. Financing consumption throughout the life cycle: intergenerational transfers........................................ . 3. The fiscal impact of population ageing.................................................................................................... . C. Public transfers by age and educational level in Brazil and Chile................................................................. 1. Public transfers and inequality................................................................................................................. . 2. Public transfers by age and educational level........................................................................................... 3. Net public transfers and taxation.............................................................................................................. D. Conclusions.................................................................................................................................................... 169 169 173 173 177 180 183 183 185 190 192 Chapter V Public transfers early in the life cycle: a major challenge in the effort to combat inequality across time....................................................................................................................................... . A. Social deficits associated with life-cycle stages............................................................................................. B. Poverty, inequality and cash transfers: costs and impacts.............................................................................. 1. Costing the measures................................................................................................................................ 2. Impacts. .................................................................................................................................................... . 195 195 198 198 200 97 98 100 101 105 106 107 108 Social Panorama of Latin America • 2010 C. Poverty, inequality, the education cycle and the life cycle............................................................................. 1. Costing the measures................................................................................................................................ 2. Impacts. .................................................................................................................................................... . D. Funding from an intertemporal perspective................................................................................................... 5 201 202 203 205 Bibliography......................................................................................................................................................... 209 Statistical appendix............................................................................................................................................ Table A-1 Latin America and the Caribbean: trends in selected economic indicators, 1990-2009............. . Table A-2 Latin America and the Caribbean: total population by country or territory, 1980-2020............. Table A-3 Latin America and the Caribbean: global fertility rates by country and five-year period, 1980-2020........................................................................................................ Table A-4 Latin America: poverty and indigence levels, 1990-2009........................................................... Table A-5 Latin America: poverty and indigence lines (PL and IL)............................................................ Table A-6 Latin America: male and female economic participation rates, by age group, 1990-2009......... Table A-7 Latin America: breakdown of the employed economically active population by occupational category, 1990-2009............................................................................................... Table A-8 Latin America: urban population employed in low-productivity sectors of the labour market, 1990-2009....................................................................................................................... Table A-9 Latin America: open unemployment rates by sex and age in urban areas, around 1990, 1999, 2002, 2008 and 2009............................................................................................... Table A-10 Latin America: average income of the employed economically active population by occupational category, urban areas, 1990-2009..................................................................... . Table A-11 Latin America: ratio of average female income to average male income, by years of schooling, urban areas, 1990-2009......................................................................................... . Table A-12 Latin America and the Caribbean (selected countries): indicators of public social spending, 1990-1991 and 2007-2008.......................................................................................... Table A-13 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-14 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-15 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-16 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-17 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-18 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-19 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-20 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-21 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-22 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-23 Latin America and the Caribbean: progress towards the Millennium Development Goals........ Table A-24 Latin America and the Caribbean: progress towards the Millennium Development Goals........ 217 219 222 223 224 226 228 230 232 234 236 238 240 241 242 243 244 245 246 247 248 249 250 251 252 ECLAC publications........................................................................................................................................... 253 Tables Table I.1 Table I.2 Table I.3 Table I.4 Table I.5 Table I.6 Table I.7 Table I.A-1 Latin America (20 countries): selected socio-economic indicators, 2000-2009......................... Latin America (12 countries): changes in poverty rates and contribution of growth and distribution effects, 2008-2009............................................................................................. Latin America (18 countries): changes in poverty rates and contribution of growth and distribution effects, 2002-2009............................................................................................. Latin America (17 countries): multidimensional and monetary poverty rate, 2009.................... Latin America (16 countries): changes in child and adolescent monetary poverty rate and in fertility rates, 1990 and 2009..................................................................................... Latin America (seven countries): population aged 15-29 neither studying nor working by age group, income quintile and country grouping, around 2006............................................ Latin America and the Caribbean (11 countries) and other regions: correlation between life satisfaction and happiness, 1981-2008.................................................................................. Latin America (18 countries): poverty and indigence indicators, 1990-2009............................. 42 47 47 53 56 62 68 73 6 Table I.A-2 Table I.A-3 Table I.A-4 Table II.1 Table II.2 Table II.3 Table II.A-1 Table II.A-2 Table II.A-3 Table II.A-4 Table II.A-5 Table II.A-6 Table II.A-7 Table II.A-8 Table II.A-9 Table II.A-10 Table II.A-11 Table II.A-12 Table II.A-13 Table II.A-14 Table II.A-15 Table III.1 Table III.2 Table III.3 Table III.4 Table III.5 Economic Commission for Latin America and the Caribbean (ECLAC) Latin America (18 countries): household income distribution, 1990-2008................................. Latin America (18 countries): income concentration indicators, 1990-2009.............................. Latin America (12 countries) and other regions: life satisfaction, life-cycle factors and monetary income, 1981-2008................................................................................... Latin America (nine countries): net primary and secondary school attendance ratios, primary cycle completion for young people age 15-19 and secondary cycle completion for young people age 20-24 by area of residence and ethnic background, around 2008............ Latin America (18 countries): internal rates of return on education and relevance of other factors in wage increment.............................................................................................. Latin America (18 countries): concentration of labour and wage income among workers in different age groups................................................................................................... Latin America (18 countries): net and gross primary school attendance and completion rates among young people age 15-19 by selected per capita income quintiles, area of residence and sex, around 2008.............................................................................................. . Latin America (18 countries): net and gross secondary school attendance and completion rates among population age 20-24 by selected per capita income quintiles, area of residence and sex, around 2008....................................................................... Latin America (12 countries): 13-to-19-year-old Internet users by upper and lower household per capita income quintiles and place of connection, around 2008........................... Latin America (17 countries): education-related components of conditional transfer programmes.................................................................................................................... Latin America (12 countries): assessment of the educational impact of conditional transfer programmes.................................................................................................................... Latin America (18 countries): distribution of the population age 15-29, 30-64 and 15 and over, by level of education............................................................................................... Latin America (18 countries): participation rates for the population age 15-29, 30-64 and 15 and over, by level of education.............................................................................. Latin America (18 countries): employment rates for the population age 15-29, 30-64 and 15 and over, by level of education........................................................................................ Latin America (18 countries): unemployment rates for the active population age 15-29, 30-64 and 15 and over, by level of education.................................................................. . Latin America (18 countries): distribution of employed population age 15-29, 30-64 and 15 and over, by level of education........................................................................................ Latin America (18 countries): salaried proportion of employed population age 15-29, 30-64 and 15 and over, by level of education.............................................................................. Latin America (18 countries): proportion of employed population age 15-29, 30-64 and 15 and over, working in the informal sector by level of education. ..................................... . Latin America (18 countries): social security system enrolment rates for employed population age 15-29, 30-64 and 15 and over, by level of education.......................................... Latin America (18 countries): labour income of employed population age 15-29, 30-64 and 15 and over, by level of education.............................................................................. Latin America (18 countries): results of the general regression model (with control variables) for assessing the impact of additional years of schooling per educational cycle on wages of wage-earners age 20 and older who work 20 or more hours per week, around 2008................................................................................................................ Latin America (18 countries): indicators of coverage and public spending on conditional cash transfer programmes (CCTPS), 2007-2010..................................................... . Latin America (18 countries): indicators of public-sector education spending, 1990 and 2008............................................................................................................................. Latin America and the Caribbean (41 countries and territories): compulsory education and official duration of the primary and secondary cycles, 2007-2008...................................... . Latin America (18 countries): indicators of education coverage and public education spending, 1990 and 2008............................................................................................................. Latin America (18 countries): contribution of economic and demographic factors to the rise in spending per student, 1990-2008............................................................................ 75 77 79 88 103 105 114 115 116 117 118 120 121 122 123 124 125 126 127 128 129 141 144 147 148 151 Social Panorama of Latin America • 2010 Table III.6 Table III.A-1 Table III.A-2 Table III.A-3 Table III.A-4 Table III.A-5 Table III.A-6 Table III.A-7 Table III.A-8 Table III.A-9 Table III.A-10 Table III.A-11 Table III.A-12 Table IV.1 Table IV.2 Table V.1 Table V.2 Table V.3 Table V.4 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 Latin America (15 countries): Gini concentration ratio for per capita personal income distribution and education spending by level.............................................................................. Latin America and the Caribbean (21 countries): public social spending as a percentage of gross domestic product......................................................................................... 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 total public spending............................................................................................. Latin America and the Caribbean (21 countries): public social spending on education as a percentage of gross domestic product.................................................................................. Latin America and the Caribbean (21 countries): public social spending on health as a percentage of gross domestic product.................................................................................. Latin America and the Caribbean (20 countries): public social spending on social security and assistance as a percentage of gross domestic product............................................. Latin America and the Caribbean (21 countries): public social spending on housing and other items as a percentage of gross domestic product........................................................ . Latin America and the Caribbean (21 countries): per capita public social spending on education................................................................................................................................ . Latin America and the Caribbean (21 countries): per capita public social spending on health...................................................................................................................................... Latin America and the Caribbean (20 countries): per capita public social spending on social security and assistance................................................................................................. Latin America and the Caribbean (21 countries): per capita public social spending on housing and other items.......................................................................................................... Latin America (15 countries): distribution of public spending on education, by education level and per capita income quintile, around 2008...................................................................... Countries participating in the global national transfer accounts project: age-group direction of net public transfers, around 2000............................................................................. Countries participating in the global national transfer accounts project: fiscal support ratio, 1950-2050.......................................................................................................................... Latin America: measures proposed to combat inequality early in the life cycle......................... Latin America (18 countries): poverty and indigence gaps......................................................... Latin America (16 countries): number of children and young people not attending upper secondary school (ages 15 to 17) and preschool (ages 3 to 5), by income decile and vulnerability status, around 2008............................................................................... Latin America: measures, costs and impacts of equality strategies, by fiscal capacity............... Latin America: poverty and indigence, 1980-2010..................................................................... Latin America (18 countries): accumulated variation of food CPI compared with non-food CPI, 2006-2009............................................................................................................ Latin America (18 countries): annual variation in poverty and indigence rates, 2002-2008 and 2008-2009........................................................................................................... Latin America (12 countries): annual variation in total income per person and by source in poor households, 2008-2009........................................................................................ Latin America (12 countries): annual change of labour income components per person in poor households, 2008-2009........................................................................................ Latin America (18 countries): income distribution structure, 2002, 2008 and 2009................... Latin America (18 countries): annual variation in some inequality indices, 2002-2009............. Latin America (17 countries): selected basic needs, 2000, 2008 and 2009................................. Latin America (17 countries): multidimensional poverty rate, 2000-2009................................. Latin America (15 countries): children and adolescents in poor households, 1990-2009.................................................................................................................................... Latin America (16 countries): ratio of child and adolescent poverty to the poverty rate in the rest of the population, 1999-2009............................................................................... 7 155 156 157 158 159 160 161 162 163 164 165 166 167 181 182 196 199 204 207 43 44 44 48 48 49 50 53 54 55 55 8 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 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 Economic Commission for Latin America and the Caribbean (ECLAC) Argentina, Chile and Uruguay: emancipation indicators by age and income group, around 2006................................................................................................................................. El Salvador, Guatemala, Honduras and Nicaragua: emancipation indicators by age and income group, around 2006.................................................................................................. Latin America and the Caribbean (20 countries) and other regions: life satisfaction by per capita GDP, 1981-2008.................................................................................................... . Latin America and the Caribbean (20 countries) and other regions: ordinary least squares regression residuals for life satisfaction and per capita GDP, 1981-2008...................... Latin America and the Caribbean (nine countries) and other regions: changes in life satisfaction and GDP per capita, 1981-2008............................................................................... Latin America (five countries), Eastern Europe and Asia: life satisfaction in highand low-income groups, 1990-2008............................................................................................ Latin America (11 countries) and other regions: life satisfaction by age and monetary income, 1981-2008...................................................................................................................... Latin America (11 countries) and other regions: life satisfaction by marital status and number of children in population aged 17-59, 1981-2008................................................... Latin America (19 countries): net enrolment ratio for pre-primary level (3 to 6 years); estimated enrolment ratio for early childhood education (0 to 3 years); and differences in attendance rates between the first and fifth quintiles for children one year younger than the official age for starting primary school, around 2008................................................... . Latin America and the Caribbean (36 countries and territories): net primary education enrolment ratio, 2007-2008......................................................................................................... Latin America (17 countries): educational lag among children age 9-11 and primary education completion among young people age 15-19 of the total population, by sex and income quintile, around 2007-2008. ......................................................................... . Latin America and the Caribbean (36 countries and territories): net enrolment ratio in the first and second cycles of secondary education, 2007-2008............................................. . Latin America (18 countries): population age 20-24 with complete secondary education by per capita income and sex, around 2008................................................................................ . Latin America (17 countries): post-secondary education attendance among young people age 20-29 and completion of at least five years of university education among those age 25-29 by per capita income and sex, around 2008.......................................... Latin America (selected countries): young people age 25-29 who completed varying levels of education by household educational climate, around 2006.......................................... Latin America (15 countries): average Second Regional Comparative and Explanatory Study (SERCE) reading test scores for sixth-graders by 2006 per capita GDP, 2006................ Latin America (six countries) and other participants in the Programme for International Student Assessment (PISA) (20 countries): average PISA science test scores for 15-year-old students by 2006 per capita GDP, 2006................................................................... Latin America (six countries) and OECD (30 countries): distribution of levels of performance on the PISA science assessment for 15-year-old students by index of family economic, social and cultural status, 2006.................................................................. Latin America (16 countries): average math and reading performance by sex (girls-boys), Second Regional Comparative and Explanatory Study (SERCE) score, sixth grade, 2006............................................................................................................... Latin America (11 countries): difference in the proportion of households with an Internet connection in the highest and lowest income quintiles by presence or absence of household members age 13-19, around 2008............................................................ Latin America (11 countries): difference in the proportion of Internet users in the highest and lowest income quintiles by age group, around 2008................................................ Latin America (11 countries): difference in the proportion of 13-to-19-year-old Internet users in the highest and lowest income quintiles by place of connection, around 2008................................................................................................................................. Chile, Colombia and Uruguay: proportion of 15-year-olds by type of ICT use and country of origin, 2006................................................................................................................ 59 60 65 65 65 66 70 71 85 85 86 87 87 89 90 92 92 93 94 95 96 96 96 Social Panorama of Latin America • 2010 Figure II.16 Figure II.17 Figure II.18 Figure II.19 Figure II.20 Figure II.21 Figure II.22 Figure III.1 Figure III.2 Figure III.3 Figure III.4 Figure III.5 Figure III.6 Figure III.7 Figure III.8 Figure III.9 Figure III.10 Figure III.11 Figure III.12 Figure III.13 Figure III.14 Figure III.15 Figure III.16 Figure III.17 Figure III.18 Figure III.19 Latin America (18 countries): years of schooling required to be less likely to live in poverty or to earn above-average labour income among the employed population age 20-29, around 2008............................................................................................................... Latin America (selected countries): participation and unemployment rates, ages 15-29, 30-64 and 15 and over, by level of education.............................................................................. Latin America (selected countries): informality and monthly labour income for the employed population age 15-29, 30-64 and 15 and over, by level of education......................... Latin America (selected countries): income trajectory by years of schooling, wage-earners age 20 and older working 20 or more hours per week, by sex, geographic area and labour market formality............................................................................................................... Latin America (15 countries): impact of years of preschool attendance on reading performance in third and sixth grade........................................................................................... Latin America (15 countries): sixth-graders attending educational establishments with partial or extended days (seven or more chronological hours) by type of school administration, 2006.................................................................................................................... Latin America and the Caribbean (28 countries): students enrolled in technical/vocational programmes compared with total enrolment in the upper cycle of secondary education, around 2002................................................................................................................................. Latin America (21 countries): total public spending and public social spending (weighted averages), 1990-2008. ................................................................................................ . Latin America (21 countries): evolution of social spending relative to gross domestic product and social spending per capita........................................................................................ Latin America and the Caribbean (21 countries): annual change in public social spending, total public spending and gross domestic product, 1991-2009................................... Latin America (selected countries): changes in social spending relative to economic growth......................................................................................................................... Latin America and the Caribbean (21 countries): evolution of public social spending by sector, 1990-1991 to 2007-2008............................................................................................. Latin America (seven countries): changes in public spending, social spending, non-social spending and gross domestic product during the financial crisis.............................. Latin America and the Caribbean (19 countries): coverage of conditional cash transfer programmes and public expenditure on them............................................................................. . Latin America and the Caribbean (19 countries): coverage of conditional cash transfer programmes, around 2000, 2005 and 2010................................................................................. Latin America and the Caribbean (19 countries): public spending on conditional cash transfer programmes, around 2005, 2008 and 2009.................................................................... Latin America (19 countries): rates of annual variation in gross domestic product and public-sector education spending, 1991-2009............................................................................. Latin America and the Caribbean (36 countries): public-sector education spending, 2006-2008.................................................................................................................................... Latin America: population by major age group, 1950-2050....................................................... Latin America (18 countries): public spending per primary and secondary school student, 1990 and 2008................................................................................................................ Latin America (18 countries): timing of the rise in public spending per student, 1990-2000 and 2000-2008........................................................................................................... Latin America (18 countries): groups of factors associated with changes in public spending per student.................................................................................................................... Latin America (18 countries): economic and budgetary factors associated with changes in spending per student................................................................................................................ Latin America (18 countries): increase in spending per student as determined by demographic and educational factors.......................................................................................... Latin America (18 countries): estimates of the cost of universalizing primary and secondary education.................................................................................................................... Latin America (15 countries): distribution of public education spending by income strata and comparison with per capita income............................................................................ . 9 98 99 101 104 106 108 112 133 135 136 136 137 138 139 140 140 143 145 145 148 149 149 150 151 152 154 10 Figure III.20 Figure IV.1 Figure IV.2 Figure IV.3 Figure IV.4 Figure IV.5 Figure IV.6 Figure IV.7 Figure IV.8 Figure IV.9 Figure IV.10 Figure IV.11 Figure IV.12 Figure IV.13 Figure IV.14 Figure IV.15 Figure IV.16 Figure IV.17 Figure IV.18 Figure IV.19 Figure IV.20 Figure V.1 Figure V.2 Economic Commission for Latin America and the Caribbean (ECLAC) Latin America (15 countries): access to public education........................................................... Countries participating in the global national transfer accounts project: average labour income and average per capita consumption relative to per capita labour income in the 30-49 age group, around 2000........................................................................................... Countries participating in the global national transfer accounts project: per capita consumption by age in middle- and high-income economies, relative to per capita labour income in the 30-49 age group, around 2000........................................................ Economies participating in the global national transfer accounts project: per capita consumption by older persons and the young, relative to per capita consumption in the 20-64 age group, around 2000........................................................................................... Countries participating in the global national transfer accounts project: average per capita labour income by age, relative to per capita labour income in the 30-49 age group, around 2000...................................................................................................................... Countries participating in the global national transfer accounts project: per capita labour income at age 21 and age 57, relative to per capita labour income in the 30-49 age group, around 2000..................................................................................................... Countries participating in the global national transfer accounts project: duration of economic independence, around 2000........................................................................................ . Countries participating in the global national transfer accounts project: average per capita net public transfers, by age, relative to per capita labour income in the 30-49 age group, around 2000............................................................................................... Countries participating in the global national transfer accounts project: per capita net public transfers to young people (aged 0 to 19) and older persons (65 and over), relative to per capita labour income in the 30-49 age group, around 2000................................. Countries participating in the global national transfer accounts project: sources of support for young people (aged 0 to 19) relative to per capita consumption, around 2000................................................................................................................................. Countries participating in the global national transfer accounts project: sources of support for older persons (65 and over), relative to per capita consumption, around 2000................................................................................................................................. Population by age group and years of schooling of the head of household................................ Annual per capita consumption by age group and years of schooling of the head of household relative to the group with the highest level of education....................................... Per capita public social benefits by age group and years of schooling of the head of household................................................................................................................................ Per capita public social benefits by age group and years of schooling of the head of household, relative to per capita benefits received by the group with the highest level of education. ....................................................................................................................... . Per capita public education benefits by age group and years of schooling of the head of household, relative to per capita benefits received by the group with the highest level of education. ....................................................................................................................... . Total per capita education spending, by age group and years of schooling of the head of household................................................................................................................................ Per capita public health-care benefits by age group and years of schooling of the head of household, relative to per capita benefits received by the group with the highest level of education. ....................................................................................................................... . Per capita public pension benefits by age group and years of schooling of the head of household, relative to per capita benefits received by the group with the highest level of education. ....................................................................................................................... . Rate of taxation: per capita taxes relative to per capita consumption......................................... Per capita net public transfers by age group and years of schooling of the head of household................................................................................................................................ Latin America (18 countries): cost of all cash transfers targeting the vulnerable population, by age group, around 2008....................................................................................... Latin America (18 countries): impact of transfers on poverty, around 2008............................... 155 173 174 175 176 177 177 178 178 180 180 186 186 187 187 188 189 189 190 191 191 200 201 Social Panorama of Latin America • 2010 Figure V.3 Figure V.4 Figure V.5 Figure V.6 Figure V.7 Boxes Box I.1 Box I.2 Box I.3 Box I.4 Box I.5 Box I.6 Box II.1 Box III.1 Box III.2 Box IV.1 Box IV.2 Box IV.3 Latin America (18 countries): cost of incorporating children and young people aged 0 to 17 into the education system, around 2008................................................................. . Latin America (15 countries): cost of universalizing school enrolment for children aged 6 to 11 and percentage of children in publicly funded urban schools who are not yet in all-day education, around 2008............................................................................. Latin America (18 countries): total cost of cash transfers to vulnerable populations and incorporation of children and young people aged 0 to 17 into education systems, around 2008................................................................................................................................. Latin America (18 countries): fiscal deficit or surplus available to fund the transfer system and enhanced care and education services in scenarios of growing GDP and a growing tax burden............................................................................................................ Latin America: additional costs of the transfers and educational services model, 2007-2008 . ................................................................................................................................. Method used to measure poverty................................................................................................. Methodology for analysing growth and distribution effects. ...................................................... . Indicators for measuring distributive inequality.......................................................................... Unsatisfied basic needs indicators............................................................................................... A multidimensional, rights-based approach to measuring child poverty.................................... Measuring satisfaction and happiness......................................................................................... Procedure for estimating individual returns on education........................................................... Updating social expenditure figures............................................................................................ Estimating expenditure per student............................................................................................. The National Transfer Accounts system...................................................................................... Methodological problems of national transfer accounts............................................................. . Methodological notes on estimating national transfer accounts by age group and socio-economic level............................................................................................................ 11 202 203 206 206 206 45 46 50 52 57 67 102 134 153 171 172 193 Social Panorama of Latin America • 2010 13 Introduction In 2010 the Economic Commission for Latin America and the Caribbean (ECLAC) proposed a comprehensive development strategy entitled Time for equality: closing gaps, opening trails (ECLAC, 2010). From a rights-based perspective, development is treated as an indivisible, rights-based process in which synergies are created between a macroeconomy that pushes back the frontiers of growth as an engine of employment and social inclusion; productive development that drives greater convergence between sectors and labour-market stakeholders to create a more diversified, innovation- and knowledge-intensive production matrix; a territorial matrix that links territories and narrows gaps in both production and well-being; a focus on social rights aimed at employment protection, the promotion of decent work, redistributive public transfers and the expansion of social safety nets; and a fiscal covenant that creates public policy space for promoting productive development with greater social equality by expanding and restructuring the tax burden. We talk about equality because what is at stake in the proposal is not just equal access but also equal ownership of rights. An integral approach not only seeks equal opportunities for skill development but also strives for clear public policies on employment and productive development as a way to reduce the tremendous segregation in these sphere that has marked the Latin American and Caribbean region’s recent past. The region’s structural heterogeneity (a subject often addressed by ECLAC and revisited in contemporary terms in Time for equality) generates productivity gaps that in turn open up divides in access to labour rights, well-being, fair wages, a political voice, symbolic recognition and information. This edition of Social Panorama looks at the links in the chain of inequalities identified in Time for equality that concern the education and skills development stage of the life cycle. A substantial portion of this edition, then, deals with the youth and child population and considers how differences created and consolidated during this stage of life entrench the intergenerational reproduction of poverty and inequality. The focus is on the life cycle and on the reproduction of unequal opportunities for sustainable social mobility over an individual’s lifetime. From this viewpoint, the document examines the situation of the population aged 0-29 and its internal dynamics, future prospects and ties to other age groups. Accordingly, this edition of Social Panorama pinpoints gaps in educational attainment and learning during the formative years, highlighting the need for the State to play a more significant role and for public transfers to narrow these gaps. It also examines how socio-economic background helps perpetuate inequality in education on the supply side. A structural, integral approach for achieving equality such as ECLAC is proposing as a road map for development in the region is not enough to close these gaps in skills and learning. To attain this goal, the State must play an active role in the areas of production and labour because self-regulated markets have historically proven to work against productive 14 convergence, employment and labour protection and to impede the narrowing of gaps in labour income and access to well-being. To truly close gaps in skills, learning and educational outcomes, education must be articulated with a labour market geared towards inclusion and equality, a fiscal covenant with a larger tax burden enabling the State and public policy to play a clear role in drawing on productivity gains (in which education is key) to redistribute assets and ensure universal access to social safety nets. In this context, the overarching message is that position on the social scale is more than the sum of personal circumstance, effort and decisions. There is a structure of opportunities provided by States, markets, families and communities that are largely beyond the individual’s control and that colour prospects for social mobility and access to well-being. Almost everything that the State, the market and the community provide for a child during infancy is filtered and redistributed by the family. As the child progresses in the life cycle towards adolescence and young adulthood, his or her direct ties to the State, the market and the community grow stronger. This edition of Social Panorama argues, among other things, that in Latin America the State and its transfer and regulatory mechanisms fall short of the mark in addressing inequalities of origin. In other words, the start in life for the children of Latin America depends a good deal on family circumstances. Families, in turn, depend a good deal on the market and receive little support from the State. The lack of robust transfer systems targeting families with children; limited coverage, care and protection by the State during infancy; low penetration of preschool systems; short school days; the system’s inability to retain students during secondary school; and the lack of support for young people and young adults as they become autonomous: these are all factors that dramatically limit the prospects for future social mobility for children born into lower-income sectors. The following chapters look at these dynamics from the viewpoints of poverty and inequality, spending and social policy, the educational system and its achievements and limitations, and intergenerational transfer systems —both those originating with the State and those that are provided through families. The closing chapter recaps the lessons learned from the chapters on specific areas; it sets forth public policy proposals and estimates their cost and potential coverage and impacts. The proposals should be seen as a search for a social protection and promotion system that safeguards children and adolescents from risk and offers channels for greater lifelong mobility. As in previous editions, chapter I discusses recent trends in poverty and income distribution in Latin America and the relationship between these trends and Economic Commission for Latin America and the Caribbean (ECLAC) an individual’s life cycle. The data show that despite the economic crisis and the widespread fall in GDP in 2009, there was virtually no increase in poverty rates in the region and indigence rates rose only slightly. Among the contributing factors were the maintenance of real wages thanks to low inflation and policies geared towards preventing massive job losses, along with a slight improvement in the distributive structure of income. The positive trend in access to basic services and education has held. For young people living in poverty, an early start towards emancipation is crucial. Teenage motherhood is highly concentrated in the poor population, making it far more difficult to escape poverty throughout life. In addition, the proportion of individuals who neither study nor work is higher among women than among men and among young people from lower-income strata than among those from higher-income groups. This situation calls for comprehensive policies that, together, tackle issues involving reproductive paths, school drop-out rates and vulnerability to exclusion. Subjectively, demoscopic data suggest that national life-satisfaction averages in the countries of the region are far higher than to be expected on the basis of gross domestic product (GDP) per capita. The gaps in this subjective well-being indicator are smaller than expected given the widespread distributive inequality in Latin America, where life dissatisfaction is higher among individuals over 60 years of age living in the worst socio-economic conditions, among 17-to-29-year-olds with children and among individuals without a stable partner. Chapter II highlights the role of education as one of the State’s best tools for reversing the intergenerational reproduction of inequality and decoupling an individual’s social background from future well-being outcomes. But the region has not turned the education system into a driver of equal opportunity. While there have been significant advances in education in recent decades, expanding access has also led to greater supply-side segmentation in attainment and in quality. The social and cultural disadvantages that burden lower-resource students as they enter the educational system are compounded by access to lower-quality education services than are available to students with more resources. This reinforces the inequality of their learning paths. In a context of unequal access to educational opportunities, the link between education and employment reproduces —and can even worsen— social inequalities. And there is a new factor that is ever more critical for acquiring skills: connectivity and the quality of access to and use of digital technologies. This poses the dilemma of a widening digital divide versus growing digital convergence, where there is considerable scope for action by educational systems. Education policy must dovetail with other social promotion and protection measures if inequality in the intergenerational transmission of educational opportunities is Social Panorama of Latin America • 2010 to be successfully reversed. Some key intervention factors in the field of education are: expanding early childhood education coverage; extending the primary school day; improving access to and use of digital technologies at State schools; supporting families through conditional cash transfer programmes and extending these to young people in secondary school; coordinating the job training system; and reconciling education quality at the upper level with expanding access to excluded sectors. Chapter III looks at recent trends in social spending. Over the past two decades the countries of the region have put significant effort into increasing the resources available for implementing social policies. Almost all areas of social spending have increased in absolute and relative terms alike, except for a few items and periods. Much of this effort has run concurrently with economic growth as available resources expanded. Overall budget increases, especially for the social sectors, have outpaced GDP growth, but minor GDP contractions have also led to larger than necessary budget cuts. To counteract this trend, most of the countries of the region decided to step up public spending (temporarily so far) to address the effects of the global financial crisis. Many of these measures are geared towards cushioning the impact of the crisis on the real economies and curbing rising unemployment and poverty. The social sectors seeing the largest increases in government funding were social security and assistance, followed by education. A portion of social assistance seeks to check the intergenerational reproduction of poverty and so targets the younger generations. However, spending on education primarily targets children and young people, and the resources involved are substantial. Spending per student is up sharply. Chapter IV examines the system of public and private transfers and how these are distributed between generations. These transfers centre on age groups that tend to consume more than they produce: children and young people, and older adults. This brings into play the National Transfer Accounts (NTA) system, a new approach to measuring aggregate flows of economic resources between age groups over time. These accounts include flows associated with transfers and capital accumulation, distinguishing those passing through public institutions from those in the private sphere. The assessment reveals the low level of consumption among children and young people in Latin America, associated with scanty public investment in these groups. Indeed, as a percentage of labour income, the countries of the region spend about the same on older persons as do Japan, the countries of Europe, and the United States. But their investment in children and young people is half that of the developed countries. The proportion of family transfers to children and young people is far higher in 15 Latin America, while that of public transfers is markedly lower. This calls for the public sector to be far more active in ensuring adequate investment in skills-building and in protecting children and young people from risk. Although the usual focus is on gaps between socioeconomic strata, this chapter centres on gaps between generations and in intergenerational transfers. Rethinking the intergenerational distribution of public transfers is essential, not only to check the reproduction of inequality throughout the life cycle but also to prepare for the rapid ageing of the population. In short, the high concentration of poverty in the early stages of life, the low level of public transfers targeting children and young people and the segmentation of educational attainments and learning (combined with the structural core of an unequal production matrix and labour market) are among the factors that explain, in part, the persistent inequality in our countries. To address these issues, chapter V proposes a life-cycle approach calling for measures that fall into three broad groups. One set of measures involves cash transfers to vulnerable households with children aged 0-14 to improve the odds that the family will have an appropriate environment for child socialization (nutrition, housing, clothing). Another calls for funding for policy measures covering the current cost of incorporating into the educational system those members of the early childhood, preschool, primary, lower secondary and upper secondary age groups who are not covered. The last group of measures envisions another set of cash transfers for employment and training services targeting young people in the process of becoming emancipated adults (15-24 years of age). This chapter sets out the results of simulations showing the costs and impacts of the measures proposed. Starting with the impacts, it explains how a transfer system for the population living in vulnerable households would have a decisive effect on poverty in the countries. It also spells out the significant gains in terms of incorporating into the educational system those children and young people who are currently outside it. As for costs, the chapter concludes that the additional current expense of incorporation into the educational system is viable for the vast majority of the countries of the region. Costs increase when taken together with cash transfers to vulnerable sectors. Over a 10-year horizon, in most of the countries the additional revenues from economic growth (and possible expansion of the tax burden) could cover the additional cost of such measures by 2014 or earlier. Nonetheless, there is still a group of four countries (Guatemala, Honduras, Nicaragua and the Plurinational State of Bolivia) that would not be able to achieve coverage by the end of the period. This calls for a greater effort to secure international cooperation resources in line with these clearly defined goals. Social Panorama of Latin America • 2010 17 Summary Poverty, inequality and life cycle Poverty and inequality: crisis and recovery Per capita GDP in Latin America and the Caribbean fell by 3% in 2009 in the midst of a generalized international crisis. This contraction impacted most of the countries of the region, especially the Bolivarian Republic of Venezuela, El Salvador, Honduras, Mexico and Paraguay. Unlike prior crises, though, this time public policy was paramount in dampening the impact on labour and social conditions. The poverty rate in the region stood at 33.1% in 2009, with 13.3% of the population living in extreme poverty or indigence. These figures translate into 183 million poor and 74 million living in indigence (see figure 1). Poverty worsened only slightly compared with 2008, equivalent to an increase of 0.1 percentage points. This shows that the countries are in a position to (and are inclined to) act far more decisively to contain the social impacts of the crisis than they have been during past crises. Extreme poverty posted a somewhat larger increase: 0.4 percentage points. The number of poor and indigent rose by 3 million. Figure 1 LATIN AMERICA: POVERTY AND INDIGENCE, 1980-2010 a (Percentages and millions of persons) 60 300 48.3 50 43.8 40.5 250 44.0 40 34.1 33.0 33.1 200 200 211 221 184 32.1 30 180 183 180 71 74 72 2008 2009 2010 136 150 22.5 20 18.5 18.6 19.4 12.6 12.9 13.3 12.9 10 93 100 89 97 68 62 50 0 0 1980 1990 1999 Indigent 2002 2007 2008 Non-indigent poor 2009 2010 1980 1990 1999 Indigent 2002 2007 Non-indigent poor 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 18 countries of the region, plus Haiti. The figures above the bars are the percentage and total number of poor persons (indigent plus non-indigent poor). 18 Economic Commission for Latin America and the Caribbean (ECLAC) These figures point to relatively positive results over the past few years. Compared with 2002, when poverty and indigence rates were the highest since 1990, both indicators are down sharply —by 10.9 percentage points for poverty and 6.1 percentage points for indigence. There is information available for assessing poverty and indigence trends between 2008 and 2009 for nine countries. In six of them, poverty clearly dropped during the period. In the Dominican Republic and Uruguay (data for urban areas), the poverty rate fell by more than 3 percentage points; Brazil, Panama, Paraguay and Peru recorded declines between 0.9  percentage points and 2.2 percentage points. Slightly smaller poverty rate decreases were posted in Colombia and Ecuador (at the national level, but not for urban areas).1 In 2009, the indigence rate came down considerably in Colombia, the Dominican Republic, Panama, Peru and Uruguay and declined slightly in Brazil and Paraguay. Among the countries for which information is available, only Costa Rica showed an appreciable deterioration in poverty and indigence indicators in 2009, with rises of 2.5 percentage points and 1.4 percentage points, respectively. The latest figures available for Argentina, Chile and El Salvador show poverty trends over a broader period. Between 2006 and 2009, poverty and indigence rates in Argentina (urban areas) dropped at the rate of 3.2 percentage points and 1.1 percentage points per year, respectively. In Chile, poverty declined slightly between 2006 and 2009, with the indigence rate remaining basically unchanged.2 Poverty and indigence rates in El Salvador held steady between 2004 and 2009. These figures can also be used to evaluate the progress the countries are making towards achievement of target 1.A of Millennium Goal One: to halve, between 1990 and 2015, the proportion of people living in extreme poverty. Despite the setback in 2008 and 2009, Latin America is well on the way to achieving target 1.A. With 72% of the target deadline elapsed the region is 82% of the way to fulfilling it. Table 1 LATIN AMERICA (18 COUNTRIES): PERSONS LIVING IN POVERTY AND INDIGENCE, AROUND 2002, 2008 AND 2009 (Percentages) Country Around 2002 Around 2008 2009 Year Poverty Indigence Year Poverty Indigence Year Poverty Indigence Argentina a 2002 45.4 20.9 2006 21.0 7.2 2009 11.3 3.8 Bolivia (Plurinational State of) 2002 62.4 37.1 2007 54.0 31.2 … Brazil 2001 37.5 13.2 2008 25.8 7.3 Chile 2000 20.2 5.6 2006 13.7 Colombia b 2002 54.2 19.9 2008 46.1 … … 2009 24.9 7.0 3.2 2009 11.5 3.6 17.9 2009 45.7 16.5 Costa Rica 2002 20.3 8.2 2008 16.4 5.5 2009 18.9 6.9 Dominican Republic 2002 47.1 20.7 2008 44.3 22.6 2009 41.1 21.0 Ecuador a 2002 49.0 19.4 2008 39.0 14.2 2009 40.2 15.5 El Salvador 2001 48.9 22.1 2004 47.5 19.0 2009 47.9 17.3 Guatemala 2002 60.2 30.9 2006 54.8 29.1 … … … Honduras 2002 77.3 54.4 2007 68.9 45.6 … … … Mexico 2002 39.4 12.6 2008 34.8 11.2 … … … Nicaragua 2001 69.4 42.5 2005 61.9 31.9 … … … Panama 2002 36.9 18.6 2008 27.7 13.5 2009 26.4 11.1 Paraguay 2001 61.0 33.2 2008 58.2 30.8 2009 56.0 30.4 Peru c 2001 54.7 24.4 2008 36.2 12.6 2009 34.8 11.5 Uruguay a 2002 15.4 2.5 2008 14.0 3.5 2009 10.7 2.0 Venezuela (Bolivarian Republic of) 2002 48.6 22.2 2008 27.6 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. a Urban areas. b Figures from the Misión para el empalme de las series de empleo, pobreza y desigualdad (MESEP), the National Administrative Department of Statistics (DANE) and the National Planning Department (DNP) of Colombia. c Figures from the National Institute of Statistics and Informatics (INEI) of Peru. 1 For Colombia, this edition of Social Panorama is reporting a new set of official poverty estimates issued by the country for 2002 to 2009. Therefore, the figures might not coincide with those published in previous editions. 2 Estimates published herein commonly differ from official poverty figures issued by the countries because of differing methodological approaches. For Chile, the figures shown diverge for the first time from the country’s official estimates. With the change in methodology introduced by ECLAC in 2007, the indigence line was adjusted to reflect changes in the food component of the consumer price index (CPI). The part of the line that corresponds to non-food spending was adjusted to reflect changes in the CPI for all other goods and services instead of using the same deflator for both lines as in the past. Social Panorama of Latin America • 2010 19 The variations in poverty and indigence rates are due to the interaction of rising average individual income (growth effect) with changes in how that income is distributed (distribution effect). The growth effect was predominant in five of the countries in which poverty declined in 2009 (Argentina, Chile, Dominican Republic, Peru and Uruguay). In another five (Brazil, Colombia, Ecuador, Panama and Paraguay) the decline was due mainly to the distribution effect. A clear worsening of distribution was behind the increasing poverty rate in Costa Rica, while the slight increase in the poverty rate in El Salvador was caused above all by falling average income (see table 2). A look at the period from 2002 to 2009 shows that poverty reduction was due to complementarity between growth effects and distribution effects. Both effects contributed to the outcome in countries where the poverty rate came down by 7 percentage points or more, with the growth effect accounting for 41% to 80% and the distribution effect accounting for 20% to 59%. Table 2 LATIN AMERICA (12 COUNTRIES): CHANGES IN POVERTY RATES AND CONTRIBUTION OF GROWTH AND DISTRIBUTION EFFECTS, 2008-2009 a (Percentages) Year Poverty Effect Contribution to total variation Beginning Ending Beginning Ending Variation Growth Distribution Growth Argentina b 2006 2009 21.0 11.3 -9.7 -9.7 0.0 100 Distribution 0 Uruguay 2008 2009 13.7 10.4 -3.3 -2.1 -1.2 65 35 Dominican Republic Chile 2008 2006 2009 2009 44.3 13.7 41.1 11.5 -3.2 -2.2 -5.7 -1.5 2.5 -0.7 >100 70 <0 30 >100 Paraguay 2008 2009 58.2 56.0 -2.2 0.1 -2.3 <0 Peru 2008 2009 36.2 34.8 -1.4 -2.1 0.7 65 35 Panama 2008 2009 27.7 26.4 -1.3 -0.5 -0.8 44 56 Brazil 2008 2009 25.8 24.9 -0.9 0.6 -1.5 <0 >100 Ecuador 2008 2009 42.7 42.2 -0.5 0.6 -1.1 <0 >100 >100 Colombia 2008 2009 46.1 45.7 -0.4 0.8 -1.2 <0 El Salvador 2004 2009 47.5 47.9 0.4 0.7 -0.3 >100 <0 Costa Rica 2008 2009 16.4 18.9 2.5 -1.3 3.8 <0 >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 Countries in order of total variation in poverty rate, expressed in percentage points. The period 2008 refers to the latest survey available between 2006 and 2008. b Urban area. Figure 2 LATIN AMERICA (12 COUNTRIES): ANNUAL VARIATION IN TOTAL PER CAPITA INCOME AND IN INCOME COMPONENTS, POOR HOUSEHOLDS, 2008-2009 a (Percentages) 16 25 8 15 4 5 0 -5 -4 -15 Labour income Transfers Other income Total income Costa Rica El Salvador Ecuador Colombia Brazil Peru Paraguay Panama Chile Dominican Rep. Argentina b -12 Uruguay -8 Variation in poverty rate 12 Variation in income In 2009, changes in poor household income were triggered mainly by rising or falling labour income. In most of the countries reviewed, average labour income in poor households increased in real terms, except in Chile, Costa Rica and Ecuador. While some countries posted no significant worsening of the employment rate, this was the variable most affected by the crisis. Falling employment rates were a relevant factor in declining labour income in Chile and Costa Rica and also affected labour income trends in Brazil and the Dominican Republic. In some cases, worsening employment rates were offset by a rise in labour income per employed person and, in other cases, by an increase in the proportion of active persons in the household. Four of the countries with the sharpest increase in labour income in poor households were Argentina, the Dominican Republic, Panama and Peru. In Colombia, Paraguay and Uruguay, an increase in the number of active persons was the key factor (see figure 2). -25 Poverty rate Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the relevant countries. a Countries in order of annual variation in poverty rate. The period 2008 refers to the latest survey available between 2006 and 2008. The percentage of population analysed is the same for both periods and refers to the poverty rate in 2008. YL = labour income; E =  number of employed; EAP = economically active population; WAP = working-age population; N = total population. b Urban areas. 20 Economic Commission for Latin America and the Caribbean (ECLAC) The distribution of income in the countries of Latin America is known as one of the most unequal in the world; this has not changed over the past four decades. Broadly, the income share of the four poorest deciles averages less than 15% of total income, with the wealthiest decile accounting for about one third of the total. The income received by the wealthiest 20% of the population is, on average, 19.3 times more than for the poorest quintile. In most of the countries the concentration of wealth has started to trend down in recent years. Between 2002 and the latest estimate available, the gap between extreme distribution quintiles narrowed in 14 of 18 countries; the Gini coefficient fell at least 5% in 11 countries. Only in the Dominican Republic and Guatemala (to 2006, the date of the latest data available) did distribution worsen during the period (see figure 3). the outcomes from a monetary measure of poverty. The countries with the highest multidimensional poverty rates (Guatemala, Honduras, Nicaragua and the Plurinational State of Bolivia) are also those with the highest monetary poverty rates. At the other extreme, Chile, Costa Rica and Uruguay (urban areas) are the countries with the lowest multidimensional poverty rates and the lowest monetary poverty rates. Over the past decade, practically all of the countries of the region recorded lower multidimensional poverty rates, with drops of more than 10 percentage points in six cases (see figure 4). The decline in multidimensional poverty was not confined to some countries where rates were below 10% (which is to be expected because some of the indicators used are probably at the minimum threshold level). Figure 3 LATIN AMERICA (18 COUNTRIES): GINI COEFFICIENT OF INCOME DISTRIBUTION, 2002-2009 a Figure 4 LATIN AMERICA (17 COUNTRIES): MULTIDIMENSIONAL POVERTY RATE, 2000-2009 a (Percentages) 0.70 70 0.65 60 0.60 50 0.55 40 30 0.50 20 0.45 10 Most recent year 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 year of the survey used differs from country to country. The period 2002 corresponds to the latest survey available between 2000 and 2002, and the period 2009 represents surveys available between 2006 and 2009. b Urban area. Latin America has habitually issued figures that may be equated to the multidimensional poverty index, applying the unmet basic needs method. This method scores basic deprivation among the population for such factors as housing, access to potable water and sanitation and education. In line with the need for a complementary way to measure poverty, the trend in living conditions is evaluated using an approach similar to the unmet basic needs method. Persons with two or more deprivations in the subject fields are considered poor. The results show a wide range of multidimensional poverty indicators that is, broadly speaking, similar to 2000 Chile Uruguay c Ecuador c Costa Rica Venezuela (Bol. Rep. of) b Argentina c Brazil Mexico Paraguay Colombia b El Salvador Peru Bolivia (Plur. State of) Honduras Nicaragua Guatemala Honduras Guatemala Brazil Colombia Bolivia (Plur. State of) Dominican Rep. Chile Nicaragua Mexico Panama Paraguay 0 Dominican Rep. 2002 Argentina b Ecuador b Costa Rica Peru El Salvador Uruguay b Venezuela (Bol. Rep. of) 0.40 Most recent year 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 year of the survey used differs from country to country. The period 2000 corresponds to the latest survey available in 2000, and the period 2009 represents the latest surveys available between 2006 and 2009. b The surveys available around the year 2000 do not support a comparable estimate of multidimensional poverty. c Urban areas. The evidence confirms the trend towards improving living conditions. However, it should be borne in mind that this assessment of multidimensional poverty is bound by the specific material deprivation indicators that household surveys conducted in the region can quantify. To make better use of the multidimensional approach requires combining the evaluation of material deprivations with an assessment of deprivation in other components of well-being. To do so requires improving the sources of information currently available. Social Panorama of Latin America • 2010 21 Fertility rates, early emancipation and poverty In monetary terms, child poverty in Latin America declined significantly between 2000 and 2009. But poverty still affects a higher proportion of children and adolescents, calling for a better understanding of the factors behind child poverty. Early fertility can be a key factor in the reproduction of poverty among children. Earlier fertility and higher lifetime fertility place a heavy childraising burden on households, forcing them to distribute scarce resources among a large number of children and making it harder for mothers to participate in the labour market. Poor children develop at a disadvantage in terms of health and access to the education system. This erodes their human capital and contributes to the reproduction of poverty in the long run. In Chile and Uruguay (two of the four countries where the poverty rate among children aged 0-5 has come down the most), the fertility rate for poor mothers aged 15-24 decreased more than for all mothers in the same age group. On the other hand, Argentina (the second most successful in reducing child poverty) saw the fertility rate for the youngest poor mothers decline less than for all mothers. In Panama, which ranks fourth in reducing child poverty, the fertility rate for poor mothers aged 15-24 increased. Table 3 LATIN AMERICA (16 COUNTRIES): TRENDS IN CHILD AND ADOLESCENT MONETARY POVERTY RATE AND CHANGES IN FERTILITY RATE, 1990 AND 2009 a (Percentages) Poor children aged 0-15 Fertility rate, poor mothers aged 15-24 b Fertility rate, all mothers aged 15-24 b Poor children aged 0-15 Fertility rate, all poor mothers b Fertility rate, all mothers b Argentina -54 -26 -33 -48 -7 -54 Bolivia (Plurinational State of) -14 -23 -30 -9 -17 -14 Brazil -25 -27 -53 -28 -19 -25 Chile -74 -63 -57 -74 -57 -74 Colombia Costa Rica -7 -19 -24 -6 -13 -7 -15 -46 -54 -15 -33 -15 Ecuador -21 -37 -51 -21 -25 -21 El Salvador -11 -39 -39 -7 -23 -11 Guatemala -7 -10 -16 -6 -4 -7 Honduras -8 -46 -49 -8 -29 -8 -9 -37 -49 -16 -34 -9 Nicaragua Mexico -10 -43 -48 -8 -25 -10 -28 Panama -28 13 -19 -37 -7 Paraguay 17 -23 -27 11 -22 17 Uruguay -45 -33 -31 -45 -41 -45 Venezuela (Bolivarian Republic of) -11 -38 -53 -16 -29 -11 Latin America c -20 -31 -40 -21 -24 -33 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. a Changes in fertility rates for poor and non-poor mothers were calculated considering a constant overall poverty rate at the value for 1990. The results were very similar to those shown in table 1. b The term “mothers” refers to all women identified as female heads of household or spouses of the head of household. c Simple averages. In four of the five countries with the largest drops in the poverty rate for children aged 0-5 (Argentina, Brazil, Chile and Uruguay) the simple average decline in the fertility rate for poor mothers aged 15-24 was 37%, compared with 27% for the countries that were least successful at decreasing the child poverty rate (Colombia, Guatemala, Honduras, Mexico and Paraguay). These calculations did not include Panama among the countries with the largest drops in the child poverty rate. In short, reproductive outcomes can have a long —and lasting— impact in terms of poverty for mothers and their children. This calls for policies targeting current and future mothers and their children. Among such policy instruments are (a) postponing the age at which motherhood is initiated; (b)  improving access to information on reproduction control; (c)  retaining women in the education system; (d) improving the quality of education; and (e) making institutions available to provide care for young children, 22 Economic Commission for Latin America and the Caribbean (ECLAC) thus giving mothers more time for their own education or for participating in the labour market. Early initiation of the emancipation process, that is, the process of leaving the family of origin, entering the labour market and forming one’s own household, is a crucial milestone in the lives of poor young people.3 In countries with less education coverage and less advanced demographic transition, there are marked differences in school attendance rates for 15-year-olds by income quintile. For the highest-income quintile the rate is 95%; for the poorest quintile it is only 75%. In none of the age groups between 15-29 does labour participation for women in the poorest quintile reach 50%. Conversely, some 80% of the 29-year-old women in the wealthiest quintile participate in the labour market (see figure 5). The data on young people who neither study nor work raise a red flag for the risk of poverty and social exclusion. Disaffiliation from key institutions is more frequent among women than among men and for young people from lower-income strata than for their peers at the other extreme of the distribution. In the less developed countries of the region, young women in the higher strata who neither study nor work but surely perform traditional domestic tasks outnumber their peers in more developed countries by more than three to one. Figure 5 EL SALVADOR, GUATEMALA, HONDURAS AND NICARAGUA (SIMPLE AVERAGES): EMANCIPATION INDICATORS BY AGE AND INCOME GROUP, AROUND 2006 a (Percentages) B. Men, quintile V A. Men, quintile I 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 0 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 24 25 26 27 28 29 Age Age D. Women, quintile V C. Women, quintile I 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 14 15 16 17 18 19 20 21 22 23 Age Age Attendance, quintile I No conjugal union, quintile I Inactivity, quintile I Single, quintile I Attendance, quintile V No conjugal union, quintile V Inactivity, quintile V Single, quintile V 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. a El Salvador 2004, Guatemala 2006, Honduras 2007 and Nicaragua 2005. 3 Emancipation is the path from dependency to autonomy, or the transition from youth to the shouldering of the roles and responsibilities of adulthood. Social Panorama of Latin America • 2010 Subjective well-being, living conditions and life cycle: Latin America and the Caribbean and other regions of the world Figure 6 shows the findings of a study linking national average life satisfaction and GDP per capita in countries of Latin America and in other regions for the period from 1981 to 2008. National life satisfaction averages in our region are far higher than what would be expected on the basis of per capita GDP; they are comparable with national averages for countries in Western Europe, North America and Oceania. In Latin America, the life satisfaction gap by income bracket is greater for individuals aged 60 and older, where middle- and lower-income groups report a level of satisfaction that is far lower than for higher-income groups. This pattern is similar to the one found in Eastern Europe and unlike that of the more developed countries, where individuals in lower-income households show a U curve for degree of life satisfaction over their entire life cycle (see figure 7), life satisfaction increases after age 60 and the satisfaction gap between groups with different income levels narrows substantially at that stage of the life cycle. This difference between regions probably has to do with the fact that the more developed countries have more universal systems to protect older persons (greater pension and health care coverage for lower-income sectors). It is not the same thing to age with protection (thanks to either self-funded pensions or a welfare state) than to age in a precarious economic situation without social protection. Figure 6 LATIN AMERICA AND THE CARIBBEAN (20 COUNTRIES) AND OTHER REGIONS OF THE WORLD: LIFE SATISFACTION BY PER CAPITA GDP, 1981-2008 a 9 8 Life satisfaction 23 7 6 5 4 3 2.0 2.5 2.0 3.5 Log of per capita GDP 4.0 Western Europe North America and Oceania Eastern Europe Asia 4.5 5.0 Africa Latin America Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the E basis of special tabulations of data from the database of the World Values Survey [online] http://www.worldvaluessurvey.org and Latinobarómetro, 2007 for satisfaction level; and World Bank, World Development Indicators (WDI) [online] http://data.worldbank.org/indicator, for GDP per capita. a Average values on a life satisfaction scale from 1 to 10 where 1 is very unsatisfied and 10 is very satisfied, and in per capita GDP logarithms). North America, Oceania and Western Europe: Andorra, Australia, Canada, Cyprus, Finland, Germany, Great Britain, Italy, Netherlands, New Zealand, Norway, Spain, Sweden, Switzerland and United States. Eastern Europe: Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, Russian Federation, Serbia, Slovakia, Slovenia, Ukraine and former Yugoslav Republic of Macedonia. Asia: Armenia, Azerbaijan, Bangladesh, China, Georgia, Hong Kong (Special Administrative Region of China), India, Indonesia, Iran, Iraq, Israel, Japan, Jordan, Kyrgyzstan, Malaysia, Pakistan, Philippines, Republic of Korea, Saudi Arabia, Singapore, Thailand, Turkey and Viet Nam. Africa: Algeria, Burkina Faso, Egypt, Ethiopia, Ghana, Mali, Morocco, Nigeria, Rwanda, South Africa, Uganda, United Republic of Tanzania, Zambia and Zimbabwe. Latin America and the Caribbean: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Costa Rica, Colombia, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Trinidad and Tobago and Uruguay. Figure 7 LATIN AMERICA (11 COUNTRIES) AND OTHER REGIONS OF THE WORLD: LIFE SATISFACTION BY AGE AND INCOME, 1981-2008 a Eastern Europe Latin America 8.0 6.5 7.9 7.8 7.7 7.6 7.5 7.8 7.8 7.2 7.8 6.2 6.0 5.8 5.5 7.6 5.0 7.6 7.4 7.3 7.3 7.4 4.5 7.3 7.1 7.1 5.7 Aged 30-44 Aged 45-59 60 and older 5.0 4.9 5.1 4.8 4.0 3.5 7.0 Aged 17-29 5.6 5.5 7.4 7.3 7.9 4.1 Aged 17-29 Aged 30-44 4.2 Aged 45-59 4.0 60 and older 24 Economic Commission for Latin America and the Caribbean (ECLAC) Figure 7 (concluded) Nordic countries Continental Europe 8.5 8.0 7.8 8.0 8.1 7.5 7.8 7.6 8.1 8.1 7.9 7.6 7.9 7.3 7.3 7.1 7.0 6.8 6.9 6.6 6.7 7.5 7.4 7.4 7.2 7.0 6.5 7.7 7.4 7.5 7.5 7.8 7.8 7.6 7.6 6.6 6.6 6.4 6.2 6.0 Aged 17-29 Aged 30-44 Aged 45-59 6.0 60 and older Lowest income group Aged 17-29 Aged 30-44 Aged 45-59 60 and older Highest income group Middle group Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from the World Values Survey [online] http://www. E worldvaluessurvey.org. a Average values on a scale from 1 to 10 where 1 is very unsatisfied and 10 is very satisfied. Latin America: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Dominican Republic, El Salvador, Guatemala, Mexico, Peru and Uruguay. Eastern Europe: Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Czech Republic, Hungary, Poland, Republic of Moldova, Romania, Russian Federation and Ukraine. Continental Europe: France, Germany, Netherlands and Switzerland. English-speaking countries: Australia, Great Britain, United States and New Zealand. Nordic countries: Finland, Norway and Sweden. In the region, being married, being in a shared living arrangement and having a partner are associated with higher levels of life satisfaction. In Latin America, childless 17to-29-year olds report the highest level of life satisfaction, similar to their counterparts in industrialized countries. But young people who have one or more children or are single parents have far lower levels of life satisfaction than their counterparts in developed countries, as do married couples in the same age bracket with one or more children (see figure 8). As figure 8 shows, Nordic countries report the highest levels of life satisfaction among young couples with children. Tellingly, these are countries with the supports and incentives for maternity and paternity that are characteristic of a welfare state. Figure 8 LATIN AMERICA (12 COUNTRIES) AND OTHER WORLD REGIONS: LIFE SATISFACTION BY MARITAL STATUS AND NUMBER OF CHILDREN, AGES 17-59, 1981-2008 a Latin America Eastern Europe 8.2 8.0 6.5 8.0 6.2 6.0 6.0 7.8 5.6 7.6 7.5 7.5 7.5 7.4 7.1 7.1 7.0 6.8 0 children 1 or more 0 children Married, shared living arrangements, partner 5.2 5.0 5.0 7.2 7.2 5.3 5.5 7.5 1 or more 4.6 4.5 4.0 0 children Separated, widowed, single, never married 1 or more 7.8 7.7 7.7 7.8 8.3 8.1 7.6 7.9 7.4 7.4 7.7 7.2 8.3 8.1 8.0 7.7 7.5 7.5 6.9 7.0 1 or more Separated, widowed, single, never married Nordic countries 8.5 7.9 0 children Married, shared living arrangements, partner English-speaking countries 8.0 5.0 6.9 6.7 6.8 7.2 7.3 7.1 7.1 7.0 6.9 6.6 6.7 6.4 6.5 0 children 1 or more Married, shared living arrangements, partner 0 children 1 or more Separated, widowed, single, never married Aged 17-29 years 0 children 1 or more Married, shared living arrangements, partner 0 children 1 or more Separated, widowed, single, never married Aged 30-59 years Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from the World Values Survey 1981-2008 [online] http:// E www.worldvalueswurvey.org/. a Average values on a scale from 1 to 10 where 1 is very unsatisfied and 10 is very satisfied. Latin America: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Dominican Republic, El Salvador, Guatemala, Mexico, Peru and Uruguay. Eastern Europe: Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Czech Republic, Hungary, Poland, Republic of Moldova, Romania, Russian Federation and Ukraine. English-speaking countries: Australia, New Zealand, United Kingdom and United States. Nordic countries: Finland, Norway and Sweden. Social Panorama of Latin America • 2010 25 Education and the intergenerational reproduction of inequality and exclusion: realities and challenges in Latin America Education is at the core of all the developmental stages of the life cycle discussed in this edition of Social Panorama. It is the main tool at the disposal of States to dissociate an individual’s social background from the well-being he or she can attain throughout life. But the region has not harnessed the education system as a driver of equal opportunity. Advances in coverage, access and progression through education cycles in recent decades have caused stratification in learning and attainment within educational systems. Any look at the life cycle must take into account education cycles, too, so preschool education is coming to the forefront of public policy in the region because of its positive impact on subsequent stages. Access to preschool is uneven in the region; some countries have nearly universal enrolment while in others enrolment is in the area of 30%. While socio-economic inequalities do not seem to affect attendance rates towards the end of the preschool cycle (three to five years of age), household surveys provide some evidence that inequalities are greater at younger ages. Moreover, there are marked differences in access between A. Educational lag urban and rural areas and for indigenous groups. Guatemala 26 Access to primary education is virtually universal, but Nicaragua 25 efforts should focus on timely progression and completion Paraguay 22 Colombia of this cycle for the most neglected social 21 groups, as Dominican Rep. 20 shown in figures 9A and 9B. Honduras 17 Bolivia (Plur.ratios for access to and timely progression through 14 The State of) 13 El Salvador the secondary cycle are markedly lower than for primary 12 Ecuador 11 education and vary more widely from country to country. The Brazil 10 Panama net attendance rate for the secondary level is 88%, versus 10 Peru 97% for the primary level. Young people approaching the 10 Uruguay 9 Chile upper secondary cycle already have opportunities to enter 6 Argentina the labour market. This 5acts as a disincentive to staying Costa Rica 3 in school, Mexico especially if students face adverse economic 0 10 30 or academic conditions or problems with 20 integration or identity formation. In addition to heterogeneity among countries, there are ever more pronounced differences within countries: between rural and urban areas, poor and non-poor students, different socioeconomic strata and indigenous and non-indigenous groups, as well as other discriminating factors (see figure 10). Figure 9 LATIN AMERICA (17 COUNTRIES): SCHOOL LAG AMONG CHILDREN AGED 9-11 AND PRIMARY EDUCATION COMPLETION, YOUNG PEOPLE AGED 15-19, TOTAL POPULATION, BY SEX AND INCOME QUINTILE, AROUND 2007-2008 a (Percentages) A. Educational lag Guatemala Nicaragua Paraguay Colombia Dominican Rep. Honduras Bolivia (Plur. State of) El Salvador Ecuador Brazil Panama Peru Uruguay Chile Argentina Costa Rica Mexico 26 25 100 80 70 17 14 13 60 12 11 10 10 10 50 40 30 9 20 6 10 5 3 0 10 20 30 B. Completion rate 100 92 94 86 90 91 90 93 96 97 94 96 98 98 Quintile IV Quintile V 80 70 60 50 40 30 20 10 0 Total Quintile I Quintile II Men 92 94 90 22 21 20 Quintile III Women Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of the Information System on Educational Trends in Latin America (SITEAL), Statistical Summary I, National Totals, October 2008, and special tabulations of data from household surveys conducted in the respective countries. a Children who are two or more years behind the grade they should be in for their age. 0 Total 26 Economic Commission for Latin America and the Caribbean (ECLAC) Figure 10 LATIN AMERICA (SELECTED COUNTRIES): POPULATION AGED 20-TO-24 WITH COMPLETE SECONDARY EDUCATION, BY PER CAPITA INCOME AND SEX, AROUND 2008 a (Percentages) 100 90 81 80 72 70 59 60 50 86 49 55 62 49 44 40 35 30 23 26 22 20 20 26 31 10 0 Total Quintile I Quintile II Quintile III Quintile IV Quintile V Income quintile Men Indigenous Nonindigenous Rural areas educational system for traditionally excluded sectors has come with greater segmentation of supply and a sharp increase in out-of-pocket expenses and the number of private schools. Segmentation, then, is not just in years of schooling but also in effective learning. Figure 11 shows the distribution of academic performance for 15-year-old students in science, by economic, social and cultural status. Most students in the first and second income quartiles in the countries of Latin America perform below level 2, meaning that they have not developed the basic competencies for performance in this area. By way of contrast, learning outcomes also differ among students from different quartiles in OECD countries, but the vast majority achieve the basic expected level of competency (level 2 and higher). Women 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. a The data for indigenous and non-indigenous young people refer to eight countries and correspond to 2007. Access to the final cycle of post-secondary education is generally reserved for a relatively small portion of the region’s young people. Only 8.3% of young people aged 25-29 have completed at least five years of post-secondary education (typical length of time for a university degree programme). There is marked stratification by per capita income quintile: for every 27 young persons from highincome strata (fifth quintile) who complete five years of post-secondary studies only one lower-income (first quintile) one does. Among the factors of inequality, household socioeconomic status and the head of the household’s level of formal education underlie disparate results in learning outcomes and progression through the education system. This shows that the educational system is not performing one of its principal functions: that of decoupling children’s and young people’s attainments from the dissimilar backgrounds they carry into the system. This situation is compounded by access to education services that vary widely in quality. Social patterns are not reproduced by any single institution alone but rather by the institutional structure as a whole, where the education system combines, above all, with family life and the immediate community environment. Household attributes are still the basic cause of differences in learning outcomes. The social and cultural disadvantages that burden lower-resource students as they enter the educational system are compounded by access to lower-quality education services than are available to students with more resources. This reinforces the inequality of their learning paths. Over the past few decades, expanding access to the Figure 11 LATIN AMERICA (SIX COUNTRIES): PERFORMANCE ON THE PISA SCIENCE ASSESSMENT FOR 15-YEAR-OLD STUDENTS, BY FAMILY ECONOMIC, SOCIAL AND CULTURAL STATUS (EsCs INDEX), 2006 a (Percentages) 100 80 60 40 20 0 -20 -40 -60 -80 -100 Lowest ESCS quartile Lower-mid Higher-mid ESCS ESCS quartile quartile Highest ESCS quartile Lowest ESCS quartile Lower-mid Higher-mid Highest ESCS ESCS ESCS quartile quartile quartile Latin America (6 countries) Below level 1 Level 1 Level 2 OECD Level 3 Level 4 Level 5 Level 6 Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of microdata from the PISA 2006 survey. a The distribution of performance levels in Latin America and in the Organisation for Economic Cooperation and Development (OECD) refers to the simple average of average weighted national achievement levels of the countries participating in the Programme for International Student Assessment (PISA) 2006 (Argentina, Brazil, Chile, Colombia, Mexico and Uruguay). While attainment and learning in the formal educational system are very (and increasingly) important for full participation in the economy, society and political life, full access to and use of information and telecommunications technologies (ICT) is becoming a requisite for social inclusion. The digital divide exacerbates gaps in learning, in broadened communication, in social networks, in access to productive employment and in having a voice in society; digital convergence clearly helps narrow them. The school system is key for achieving mass access and providing training in and access to new digital technologies. But efforts to Social Panorama of Latin America • 2010 work through the schools to counteract the marketdriven digital divide (reflected in the gap between households in high and low socio-economic strata) have not closed those gaps nor achieved much in the area of digital convergence. The disparity in skills development is linked not only to educational attainment but also, later on, to self-regulated labour markets that are true factories of segmentation in terms of productivity, access to welfare and full enjoyment of social entitlements. Hence, structural inequality (which is reproduced through the production structure, markets and institutions) combines with intergenerational inequality where gaps are reinforced throughout life and are passed from one generation to the next. This calls for an integral approach that encompasses structures, institutions and the life cycle. And it highlights the importance of education to prepare individuals for fuller participation in all spheres of society throughout their adult lives. One of these spheres, although not the only one, is labour market. ECLAC has conclusively documented that in most of the countries of the region, individuals who do not complete secondary education are exposed to a high degree of social vulnerability because they will tend to receive a poor labour income in exchange for their educational credentials, and they will be at high risk for living in poverty and becoming “dispensable” (excluded) if they must engage with self-regulated labour markets in the absence of minimum guarantees or labour rights. Only a complete secondary education will, according to the “rates of return approach”, keep an individual at a “prudent distance” from the poverty line. Figure 12 shows how important it is to extend higher education coverage to young people who historically have had no access to it, in order to reduce the gaps in life prospects that are cemented during youth.4 4 We do not argue here that the role of education is exclusively or even primarily that of ensuring that competitive labour markets yield a rate of return for years of schooling. We merely seek to illustrate the importance of democratizing educational opportunities in order to enable individuals to exercise their positive freedom, that is, to carry out their life projects thanks to having, among other things, the timely opportunity to develop their skills. Such skill development is necessary, but it is not enough. The labour markets take in young people on the other side of the door (not in the world of education but in the world of work), so these markets should be subject to regulatory policies and receive guidance for ensuring the full force of labour rights and social protections. The State has an essential role to play in keeping differences in education attainment from dooming those without them to exclusion. Productivity gains, then, should not be seen as a return on learning but rather as a way for society to work through the State and the tax system to redistribute resources and extend social protections to the most disadvantaged sectors. 27 Figure 12 LATIN AMERICA (SELECTED COUNTRIES): MONTHLY LABOUR INCOME FOR THE EMPLOYED POPULATION AGED 15-29, 30-64, AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages and 2000 purchasing power parity dollars) 2 500 1 964 2 000 1 500 1 086 1 000 500 0 424 500 548 666 686 307 Incomplete Complete primary primary Incomplete Incomplete Complete lower upper secondary secondary secondary Age 15 to 29 Age 30 to 64 Incomplete Complete tertiary university Total 15 and older 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 length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). Education policy must mesh with other social promotion and protection efforts if the intergenerational reproduction of educational opportunities is to be reversed. Key intervention factors within the education system are: (i) Extending early childhood education coverage. Publicly-funded institutional care for children under six has well-documented benefits. Such care facilitates the integration of women into the labour market, fosters their autonomy and increases household resources. For the young cohort, it provides an opportunity for young mothers, giving them more free time to continue studying and avoid breaking their own education cycle. In-school meals and health care, as well as early stimulation, offset deficiencies at home. Such care also has a positive effect on a child’s future development: it is essential for cognitive, psychomotor and attention-span development and activity levels and has a substantial impact on the child’s prospects in subsequent education cycles. (ii) Extending the primary school day. Advances in current pedagogical models and the education needs of the modern world are making longer school days increasingly important. An extended school day would be expected to change the ratio between time spent on working and time for rest, increasing pedagogical work for pupils at school and decreasing the time spent on homework. This is especially important for students who lack an educational climate at home and whose environment does not provide appropriate stimulus or support for learning. A full school day also has positive externalities for families, easing concerns about out-of-school care (including meals) and preventing risky behaviour. 28 Economic Commission for Latin America and the Caribbean (ECLAC) (iii) Incorporating digital technologies into education as a critical opportunity in the battle for equity. Defining the criteria for choosing the models for incorporating information and communication technologies into teaching practices should be subordinated to State goals for education in each country. One of the priorities for the States of Latin America (and for those in charge of their educational systems) is to make universal access to computer skills a key tool in the effort to dissociate social background from learning attainments. This is seen as an essential step in reducing poverty and inequality and in enhancing social integration. (iv) Providing support for families through conditional cash transfer programmes. It is important to test instruments and strategies that help keep students in the system during this cycle of schooling, that is, that foster sustained, timely school progression. Conditional cash transfer programmes are one of the pillars that the countries have built over the past two decades in order to encourage lower-income families to buy into keeping their children in the educational system. Such programmes have the virtue of improving, however marginally, the monetary resources available to poor households, preventing drop-outs for opportunity cost reasons (staying in school is part of the transfer programme contract). However, primary education is approaching universal coverage and the drop-out rate for young people in vulnerable families is higher at the secondary level (at this age the opportunity cost of lower family income is higher). This makes it essential to extend benefits for school-age children throughout the secondary cycle. (v) Coordinating the job training system. The path leading young people to the world of work is, as we have seen, highly segmented by educational attainment levels. The formation of competencies in the 15-20 age group is essential for successful entry into the labour market with meaningful opportunities for the future. Government action is therefore required to target this area of education and link this supply of education services to the production sector. (vi) Reconciling higher education quality with expanding access to excluded sectors. The higher education system in Latin America and the Caribbean has expanded and grown substantially over the past few decades. Coverage is still very limited, though, and it is concentrated in the medium- and high-income levels. Ensuring greater equality of opportunities at this level calls for policies that offset the lack of monetary resources and of time among young people graduating from secondary school who need to work to survive or help their families. Public social spending in Latin America: general trends and investment in capacity-building for new generations Progressive recognition of the importance of public social spending as an instrument for channelling resources to the poorest population segment and of the importance of social development as a driver of economic development has led the region’s countries to gradually increase this category of spending. Thus, social spending rose from 12.2% of GDP in 1990-1991 to 18.0% in 20072008, substantially increasing its budget share in the process from just under 45% to about 65% of overall public spending. There are clear differences between countries, however, in the macroeconomic priority they give to social spending, which ranges from less than 8% of GDP in Ecuador, Guatemala and Peru (central government) to over a fifth of GDP in Argentina, Brazil, Cuba and Uruguay. The differences between countries are also due to their respective levels of wealth. Differences in countries’ development levels and tax burdens and thence in their general and specifically social public budgets are the source of large disparities in funding levels (see figure 13). Social Panorama of Latin America • 2010 29 Figure 13 LATIN AMERICA (21 COUNTRIES): EVOLUTION OF SOCIAL SPENDING RELATIVE TO GROSS DOMESTIC PRODUCT AND OF SOCIAL SPENDING PER CAPITA A. Social spending (percentages of GDP) 40 Simple average (21 countries) 2007-2008 2004-2005 2000-2001 1997-1998 1994-1995 1990-1991 35 30 25 Weighted average (21 countries) 2007-2008 2004-2005 2000-2001 1997-1998 1994-1995 1990-1991 14.2 12.8 12.4 11.3 11.0 9.5 18.0 15.9 15.5 14.7 14.4 12.2 20 18.0 15 12.2 10 GG 1990-1991 BCG 1994-1995 1997-1998 2000-2001 Ecuador Guatemala Dominican Rep. Jamaica Panama Honduras Colombia Chile Uruguay Cuba Paraguay Nicaragua Mexico Venezuela (Bol. Rep. of) Peru El Salvador PS Trinidad and Tobago NFPS Costa Rica Argentina Brazil 0 Bolivia (Plur. State of) 5 CG 2004-2005 2007-2008 B. Social spending per capita (dollars at constant 2000 prices) 2 400 Simple average 2007-2008 2004-2005 2000-2001 1997-1998 1994-1995 1990-1991 2 000 1 600 Weighted average 2007-2008 2004-2005 2000-2001 1997-1998 1994-1995 1990-1991 666 506 466 421 380 315 885 691 642 601 557 440 1 200 880 800 PS 1990-1991 1994-1995 BCG 1997-1998 2000-2001 CG 2004-2001 2007-2008 Source: conomic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. E Note: NFPS = non-financial public sector; PS = public sector; GG = general government; BCG = budgetary central government; CG = central government. Ecuador Guatemala Dominican Rep. Jamaica Colombia Panama Chile Cuba Uruguay Nicaragua Paraguay Venezuela (Bol. Rep. of) Mexico Peru El Salvador GG Trinidad and Tobago NFPS Costa Rica Bolivia (Plur. State of) Brazil Argentina 0 Honduras 440 400 30 The procyclical nature of social spending relative to economic growth 25 20 15 10 5 0 -5 2009 2007 2008 2005 2006 2003 2004 2001 2002 1999 2000 1997 1998 1995 1996 1993 1994 -15 1991 -10 Annual change in total public spending Annual change in GDP Annual change in public social spending Source: conomic Commission for Latin America and the Caribbean (ECLAC), social E expenditure database. a Weighted averages. The 2009 expenditure figures are estimates based on information from seven countries. Expenditure trends during the financial crisis all continued to increase their social spending. A number had already raised social spending in 2008, and five of the seven countries made a still greater effort in 2009 (Brazil, Colombia, Guatemala, Honduras and Panama). Although the others also increased their social spending, they did so more slowly than in 2008 (see figure 15). Figure 15 LATIN AMERICA (SEVEN COUNTRIES): CHANGES IN PUBLIC SPENDING, SOCIAL SPENDING, NON-SOCIAL SPENDING AND GROSS DOMESTIC PRODUCT DURING THE FINANCIAL CRISIS (Percentage changes) 50 40 30 20 10 0 -10 Brazil Colombia Cuba Change in public spending Change in non-social spending Guatemala Honduras 2008 2009 2007 2009 2006 2007 2008 2006 2008 2009 2007 2009 2006 2007 2008 2009 2006 2007 2008 2008 Chile 2009 2006 2007 2009 2006 -20 2007 Faced with the 2008 financial crisis, the region’s countries implemented measures of various kinds. Unlike those taken on other similar occasions, they set out not to shrink spending but to expand it. Measures of this kind encompassed the areas of monetary and financial policy, fiscal policy, exchange-rate and foreign trade policy, sectoral policies, employment and social policies and multilateral finance. Broadly speaking, the measures were aimed, first, at restoring confidence and making financial markets operational again and, second, at strengthening domestic demand for goods and services. The most commonly used fiscal measures in the countries have included cutting taxes, increasing tax benefits and subsidies and raising or bringing forward expenditure. In the social and production sectors, considerable extra resources have been put into house building, water and sanitation, support for small and medium-sized enterprises and the agricultural sector (easier credit and repayment terms), enhanced employment policies (unemployment insurance, recruitment subsidies, job creation programmes) and social programmes, especially conditional cash transfer programmes (which currently command resources equivalent to 0.4% of the region’s GDP and cover some 20% of the population of Latin America and the Caribbean). The data available for seven countries show that even as GDP declined in absolute terms in most of them, they 2008 Figure 14 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): ANNUAL CHANGE IN PUBLIC SOCIAL SPENDING, TOTAL PUBLIC SPENDING AND GROSS DOMESTIC PRODUCT, 1991-2009 a (Percentage changes) 1992 Although the region’s countries have steadily increased their public budgets, particularly where social spending is concerned, in most cases these have fluctuated for reasons generally determined by local economic developments. However, social spending is less sensitive to the economic cycle than the overall budget, as figure 14 shows. For all its procyclicality, then, social spending has been better protected against economic fluctuations than non-social public budget items. It is to be expected that some specific spending items will be countercyclical, like those that finance emergency programmes at times of crisis and rising poverty, as these tail off in periods of economic growth. Others are more stable, such as social security, while others again can be expected to expand along with the economy to a reasonable degree that avoids macroeconomic imbalances or any tendency towards deficit spending. 2006 Economic Commission for Latin America and the Caribbean (ECLAC) Panama Change in GDP Change in social spending Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. Social Panorama of Latin America • 2010 Social investment at early ages: growing progressive spending on education Investing in the capacities and capabilities of the new generations is vital to produce a more productive workingage population for the coming decades, something that will be essential to keep pace with the demographic transition and the steady rise in the proportion of older adults in Latin American and Caribbean societies. It is also important to have a more productive working-age population because of the impetus given to economic growth by the incorporation of know-how and innovation into the production system. Complemented by policies to promote social and employment rights, this is also a positive element for social protection systems. Education is unquestionably at the core of the investment needed in the capacities and capabilities of the new generations. Education budgets have increased substantially as a share of GDP over recent decades. While the region’s GDP almost doubled between 1990 and 2008 (growing by 3.4% a year and 84% over the whole period), the absolute expansion of public-sector education spending was 5% a year, or 140% over the whole period. The number of public-sector students in the region increased by almost 29 million in this time to a total of 91.2 million primary and secondary students in publicly run schools (with 18.5 million at privatelyfunded schools), while spending per student increased from US$ 312 to US$ 710 (see figure 16).5 The majority of the countries increased their spending by the most between 2000 and 2008. The exceptions are Chile, Mexico, Panama and Paraguay, which made the most increases in the 1990s. This is mainly because efforts to increase coverage were concentrated in the earlier period in most of the countries: on average, coverage increased by about 14 percentage points between 1990 and 2000, compared with a further 5 percentage points between 2000 and 2008. This meant that much of the extra public education spending went on incorporating new students. Since the progress of the 1990s (and earlier decades), extra spending has mainly gone into improving the conditions that directly or indirectly affect the education process: better infrastructure, equipment, teaching material and teacher pay, among other things. Public spending on education is a vital State tool for promoting greater equality of opportunity 5 31 The figures do not include secondary school students who are behind their age group (generally aged 18 or over). throughout the education cycle, and for closing gaps in attainment by level between households of different socio-economic origins. There is telling evidence that the more the child and youth population is incorporated into the different levels of education, and the more progression into the higher cycles is universalized, the greater the egalitarian redistributive effect of education spending will be. Figure 16 LATIN AMERICA (18 COUNTRIES): PUBLIC SPENDING PER PRIMARY AND SECONDARY SCHOOL STUDENT a (Dollars at constant 2000 prices) Simple average 710 Argentina Chile Mexico Uruguay Costa Rica Brazil Venezuela (Bol. Rep. of) Colombia Panama Dominican Republic Honduras Peru El Salvador Paraguay Guatemala Bolivia (Plur. State of) Ecuador Nicaragua 2 348 1 890 1 275 1 099 1 072 937 694 645 573 409 345 339 249 244 241 193 171 62 0 500 1 000 1990 1 500 2 000 2 500 2008 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/ Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Documentos de proyecto, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/ xml/0/40520/metas-educativas-2021.pdf, 2010. a Ranked in order of spending per student in 2008. Nothing has a greater egalitarian effect than policies which achieve universal coverage. Figure 17 is very suggestive here. It shows that increased coverage at the different levels of education is associated with a more redistributive impact for spending at those levels. What policy implications does this have? The great mistake would be to think, as the tendency was under the paradigm of the Washington Consensus and the wave of reforms in the 1980s and 1990s, that public spending on education needs to be reduced at those levels where coverage is lower (such as university education) so that this spending can be transferred to levels with greater coverage (such as primary or lower secondary). What strict analysis of the data shows is quite the opposite, i.e., that 32 Economic Commission for Latin America and the Caribbean (ECLAC) the great challenge from a rights and equality perspective is to promote progression right through the education cycles for those socio-economic sectors that do not at present go on to higher levels, thereby democratizing access to upper secondary and post-secondary education. Meanwhile, the withdrawal of the State from the higher levels of education (upper secondary and post-secondary) has another very negative affect from a rights standpoint, as it leaves these levels at the mercy of private-sector provision, which segments access and quality depending on families’ ability to pay for the service. This has a clear regressive effect in terms of the way opportunities are distributed by people’s socio-economic conditions of origin. To put it another way, it is precisely the existence of public-sector higher education that gives lower-income sectors a chance of real social mobility. Consequently, public-sector efforts need to be oriented towards ensuring that a larger and larger proportion of low-income students continue their post-secondary studies, and towards increasing the progressiveness of spending at this level. Figure 17 LATIN AMERICA (15 COUNTRIES): DISTRIBUTION OF PUBLIC EDUCATION SPENDING BY INCOME STRATUM AND COMPARISON WITH PER CAPITA INCOME a (Percentages) B. Preschool and primary education spending 100 Cumulative ratio of revenue to public spending Cumulative ratio of revenue to public spending A. Public education spending 90 80 70 60 50 40 30 20 10 0 0 10 20 30 40 50 60 70 80 90 100 100 90 80 70 60 50 40 30 20 10 0 0 10 20 Cumulative percentage of population Cumulative ratio of revenue to public spending Cumulative ratio of revenue to public spending 90 80 70 60 50 40 30 20 10 20 30 40 50 60 70 Cumulative percentage of population Per capita income Lower secondary education Upper secondary education Equidistribution 60 70 80 90 100 D. Tertiary education spending (vocational and university) 100 10 50 Per capita income Preschool education Primary education Equidistribution C. Secondary education spending (lower and upper) 0 40 Cumulative percentage of population Per capita income Public education spending Equidistribution 0 30 80 90 100 100 90 80 70 60 50 40 30 20 10 0 0 10 20 30 40 50 60 70 Cumulative percentage of population 80 90 100 Per capita income Post-secondary and tertiary education Equidistribution Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of the household surveys in the countries and data from the E United Nations Educational, Cultural and Scientific Organization (UNESCO) Institute of Statistics (UIS). a Simple averages. Social Panorama of Latin America • 2010 33 The generational economy, transfer systems and inequality in Latin America and the Caribbean The generational economy The previous chapters, especially the one on education, have underlined differences in educational achievement among children and young people from different socioeconomic levels and their substantial impact on the intergenerational reproduction of inequalities throughout life. This chapter completes the picture, with an analysis of differences between generations. It considers how public and private transfers target two stages in the life cycle: children and young people, and older persons. The most striking bias in Latin America in comparison with other regions of the world concerns the greater relative scale of public transfers to the older population. The life cycle includes two major periods of economic dependency when consumption exceeds labour output; one at the beginning, the other at the end (see figure 18). There are variations, but most of the consumption needs of children and older persons are met through large flows of resources from the working-age population. Some of these flows are direct, as in the case of parents providing for their children. Others are more indirect, such as transfers through governments, charitable organizations and other economic and social institutions. Some situations are more complex, like those involving savings from labour income. The total of all these flows constitutes the generational economy. Despite the major implications of intergenerational transfers for economic growth and for combating inequality and poverty, those transfers have not been exhaustively analysed. The national transfer accounts system provides the first comprehensive approach to overall measurement of aggregate financial flows between age groups and across time. The system includes flows relating to capital accumulation and to transfers, distinguishing those passing through public institutions from those in the private sphere. They estimate all aggregate flows in accordance with the System of National Accounts of the United Nations. Estimates are mostly based on analyses of household surveys relating to income, spending, assets, the workforce and transfers, in addition to detailed administrative records from various government bodies.6 Figure 18 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: AVERAGE LABOUR INCOME AND AVERAGE PER CAPITA CONSUMPTION COMPARED WITH PER CAPITA LABOUR INCOME IN THE 30-49 AGE GROUP, AROUND 2000 a (Percentages) 120 100 Percentage of per capita labour income in the 30-49 age group 80 60 40 20 0 0 10 20 30 40 Per capita labour income Age 50 60 70 80 90 Per capita consumption Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/East-West Center, October 2010. a Uses the simple average of 22 economies participating in the global national transfer accounts project: in Latin America: Brazil, Chile, Costa Rica, Mexico and Uruguay. In Asia: China, India, Indonesia, Japan, Philippines, Republic of Korea and Thailand. In Africa: Kenya and Nigeria. In Europe: Austria, Finland, Germany, Hungary, Slovenia, Spain and Sweden; and the United States. Per capita income includes private and public consumption. Per capita labour income includes fringe benefits and self-employed income. 6 For further details on the national transfer accounts system, see http://www.ntaccounts.org 34 Economic Commission for Latin America and the Caribbean (ECLAC) National transfer accounts: Latin America in the worldwide context Consumption profiles by age vary widely among the countries participating in the global national transfer accounts project. In the middle-income countries there is very little variation in consumption during adult life, whereas children’s consumption is a little lower than that of the average adult (see figure 19). In the high-income economies, children’s consumption is relatively high in comparison with the middle-income countries (between 15% and 33% during the first 15 years of life), and consumption levels rise as people get older (at age 85, for example, consumption in the high-income economies is around 25% higher than at age 45). This is due partly to lower investment in capacity-building in the middle-income countries, and partly to the greater coverage of public pensions systems and higher spending on health care for older persons in the high-income economies. Figure 19 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: PER CAPITA CONSUMPTION BY AGE GROUP IN MIDDLE- AND HIGH-INCOME ECONOMIES COMPARED WITH PER CAPITA LABOUR INCOME IN THE 30-49 AGE GROUP, AROUND 2000 a (Percentages) 160 Percentage of per capita labour income in the 30-49 age group 140 120 100 80 60 40 20 0 0 10 20 30 40 50 60 70 80 90 Age High-income Middle-income Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. a Per capita consumption in middle-income countries is calculated as a simple average of Brazil, Chile, China, Costa Rica, India, Indonesia, Mexico, Philippines, Thailand and Uruguay. Per capita consumption in high-income economies is calculated as a simple average of Austria, Finland, Germany, Hungary, Japan, Republic of Korea, Slovenia, Spain, Sweden, Taiwan Province of China and United States. In the countries participating in the global national transfer accounts project there is also considerable variation in typical ages of entry to and exit from the labour market. In most of the high-income countries, young people tend to stay longer in full-time education, and labour income is higher among older workers. As for the period during which labour income exceeds consumption, the countries of Latin America (aside from Uruguay) are those with the shortest periods of economic independence, varying from around 20 years in Brazil and Mexico to 28 years in Chile and Costa Rica. In the framework of the national transfer accounts system, three main mechanisms can be identified for reallocations between age groups and generations: public transfers, family (private) transfers, and asset-based reallocations. Public transfers generally come from the working-age population, since the taxes it pays often exceed the benefits it receives. Children and older persons are generally net beneficiaries of public transfers. Health care is the main source of these transfers to children under five; in the 5-15 age group, State education is the main component. As for older persons, as might be expected, social security and health care account for almost all public transfers. However, there is great diversity between countries in terms of taxation and public spending policies. For example, net transfers received by children and young people in relation to average labour income vary from 6% in China to 29% in Finland. In the case of older persons, this variation goes from -2% in Thailand —showing that older persons in that country pay more in taxes than they receive in benefits— to 87% in Brazil, where a widereaching pensions programme has been implemented, including non-contributory pensions. Corroborating the results for consumption, the countries of Latin America show relatively low levels of public investment on children and young people. In Brazil, Chile and Costa Rica, this low investment is combined with high levels of public transfers to older persons. As a percentage of labour income, States in Latin America spend about the same on older persons as Japan, the United States and the European Social Panorama of Latin America • 2010 governments, but they invest half as much on children and young people.7 Family transfers are the main source of support for consumption by children and young people in Asian countries and territories (between 67% and 76%, except for Japan), and in the Latin American countries (69% to 79%). In high-income countries, family transfers are lower in relative terms (43% to 57%), owing to more significant public-sector investment. In the case of older persons, labour income is a major source of consumption, especially in countries in Asia. In 35 European countries, however, older persons’ labour income makes up only a small fraction of consumption. The Latin American countries are between the two extremes, with labour income varying from 18% in Brazil to 26% in Mexico as percentages of older persons’ consumption. As in Europe, net public transfers are the main source of support for older persons in Latin America.8 In most of the countries participating in the global national transfer accounts project (including those in Latin America), net family transfers are downward, from older persons to younger family members. Public transfers by age and educational level in Brazil and Chile Compared with other emerging regions, Latin America has a relatively large public sector and a rapidly-ageing population, combined with one of the world’s highest levels of inequality in income distribution. Despite growing interest in public transfers as a means of combating poverty and inequality, transfers by age group and socio-economic level are not often studied concurrently. The analysis presented below moves forward in that regard, investigating the incidence of public spending by age group and socio-economic level (defined as the educational level of the head of household) in Brazil and Chile, by sectoral composition (education, health care and social security).9 In both countries, a greater proportion of public transfers targets older persons, and families account for most of the transfers to children and young people.. This pattern holds at all socio-economic levels but is significantly stronger at the highest level. The absolute progressivity of public spending is generally greatest in the case of children; it diminishes with rising age and then turns regressive, with greater benefits at the highest socio-economic levels. These differences are due to a large extent to the greater labour incomes of persons with higher educational levels, a determining factor in pension benefits. In Brazil, the point at which spending becomes regressive is age 45, whereas in Chile this occurs somewhat later, between 50 and 54 years.10 Despite public-sector involvement, total investment in education is rather unequal at the different socio-economic levels (see figure 20). In Brazil, investment in a child’s education at the highest socio-economic level is more than double the amount at the second level and more than three times the investment in education at the lowest level. Figures for Chile are very similar. This difference stems from the yawning gaps in education spending between high- and low-income families. Greater private spending by high-income households with highly-educated heads of households leads to markedly segmented education on the supply side determined by the payment capacity of the student´s household of origin. 7 9 8 When considering these results, it should be borne in mind that the sample of countries taking part in the global national transfer accounts project for Latin America excludes the region’s poorest countries, where the public sector plays a minor role in supporting the consumption both of children and young people and of older persons. Except in the case of Mexico, where income in the form of assets, particularly State property assets, represents the main source of support. The educational categories were: (a) no formal schooling; (b) 1 to 8 years of schooling; (c) 9 to 15 years of schooling; and (d) 16 or more years of schooling. 10 This is why it is important for pension systems to have a solidarity pillar as ECLAC has argued. Contributory systems are usually regressive to the extent that benefits are linked to contributions. 36 Economic Commission for Latin America and the Caribbean (ECLAC) Figure 20 TOTAL EDUCATIONAL INVESTMENT PER CHILD, BY EDUCATIONAL LEVEL OF THE HEAD OF HOUSEHOLD a B. Chile, 2007 (pesos at 2007 prices) A. Brazil, 2003 (reais at 2003 prices) 80 000 100 70 000 100 30 000 000 60 000 25 000 000 50 000 20 000 000 40 000 30 000 35 000 000 46 32 48 15 000 000 34 32 33 Under 1 year 1-8 years 10 000 000 20 000 5 000 000 10 000 Under 1 year 1-8 years 9-15 years 16 and over Families 0 9-15 years 16 and over Government Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of processing of data from the Brazilian National Household Survey (PNAD), 2003, and the Family Budgets Survey (POF), 2006/2007, in the case of Brazil, and from the National Socio-economic Survey (CASEN), 2007, and the Budgeting and Expenditure Survey (EPG) 2006/2007, in the case of Chile. a Total per capita spending on education includes public and private spending at the pre-primary, primary, secondary and tertiary education levels. Conclusion National transfer accounts furnish a global, consistent measurement of the role played by governments in providing economic support to young people and older adults. They also allow improved monitoring of the scope of government policies and provide a comprehensive view of the functions of other economic agents (financial markets, the family and civil society). Furthermore, national transfer accounts provide a basis for governments’ long-term fiscal projections, to anticipate the significant economic changes that will be brought about by the slow but inexorable advance of social forces such as population ageing, epidemiological transition and changes in educational levels.11 More subtle 11 The epidemiological transition is a change, largely caused by population ageing, where acute illnesses, more common among children, give way to chronic and degenerative diseases, more common among older persons, as main causes of morbidity and mortality. For further details, see ECLAC/CELADE (2010). changes in fiscal and public-spending policies can thus be detected. The results of this analysis have highlighted one of the most notable characteristics of the economies of Latin America: the low levels of consumption among children and young people associated with low public investment in these population groups. The results clearly indicate the need for much stronger public-sector involvement, to provide the necessary investment for the development of young people. This is not only in order to address the reproduction of inequalities throughout the life cycle —it is also the best way to prepare for the impending rapid ageing of the population. Social Panorama of Latin America • 2010 37 Public transfers early in the life cycle: a key challenge for fighting inequality over time Social deficits associated with life cycle stages and how to address them To make progress on the equality agenda the State must lead the way in several areas. As noted earlier, it falls to the State to decouple children’s and young people’s educational attainments and learning from their socioeconomic background and to foster greater convergence of these attainments throughout society to reduce labour market gaps and vulnerability. The State must also address asymmetries, both through active employment and wage policies and by means of clearly distributive public transfers throughout the life cycle. In this context, the welfare state model shows that universal policies achieve the most systemic impact in terms of progressive redistribution of opportunities, assets and access to well-being. This model can also include selective transfers to more vulnerable groups, where the guiding principle is not to target them but precisely to make conditions in society as a whole mor e egalitarian. This chapter therefore sets out options for public transfers to vulnerable sectors during childhood and youth and provides cost estimates for achieving universal coverage in education. These options are based on evidence put forth in preceding chapters. In Latin America, States and the transfers they make have little influence on the consumption structure of families with children and adolescents. On the other hand, in many Organization for Economic Cooperation and Development (OECD) countries, consumption by persons aged 0-19 is met almost equally by public and family transfers but the average State transfer component in Latin America does not exceed 20% for this age group. This means that the redistributive impact is very small compared with primary family income. It should therefore come as no surprise that inequality persists despite public transfers targeting families with children and young people. This constraint is compounded by educational systems (where a large part of the public transfers are focused on the youngest population segment) that are ineffective in reversing underlying structures of inequality. In short, the region faces enormous challenges in harnessing the redistributive role of the State in the fight against inequality over time. Alleviating these deficits, then, calls for redistributive measures in line with the life-cycle approach, focusing on the population of children and young people and involving transfers targeting families whose labour income is patently insufficient. These mechanisms should include different measures at each stage, and they fall into three broad categories. In one category are cash transfer schemes focusing on households with children to improve the odds that the family will have an appropriate environment for child socialization (nutrition, housing, clothing). In another, funding goes to instruments geared towards reversing the deficits in coverage and access to early childhood care and stimulation that trap children and adolescents in a pattern of exclusion, with the subsequent negative impact on young people as they approach emancipation. Last is another set of cash transfers for employment and job training services targeting young people in the process of becoming emancipated adults. These measures, encompassing the stage in life that is the subject of this edition of Social Panorama (0-29 years of age, culminating in emancipation and the transition to adulthood) should include the following components: • Early childhood: cash transfers to households with children (aged 0-4) and policies to ensure care (0-2) and preschool education (3-5). • Period between childhood and early stages of emancipation (childhood and early adolescence, 6-14): lengthening the time spent in school, investing in primary education and the lower cycle of secondary school to increase coverage and graduation rates. • Emancipation: cash transfers in the form of vouchers, that is, incentives to stay in or return to school or the labour market. For this instrument, the benchmark age is 15-29, but the analyses set out below centre on the group aged 15- 24 as the modal group in the vulnerable sectors. This chapter therefore proposes a set of transfers and shows the cost of achieving universal coverage from early 38 Economic Commission for Latin America and the Caribbean (ECLAC) childhood education through upper secondary school for the countries of Latin America. These transfers are explained in this chapter and listed below: 1. Transfer to all vulnerable families (with income at or below 1.8 poverty lines per household member) an amount equivalent to one poverty line per child aged 0-4 and 1.5 poverty lines in the case of single-parent families; the cost of this transfer at the national level is shown as a percentage of GDP. 2. For this group of families, transfer the equivalent of 0.5 poverty lines per child aged 5-14, or 0.75 poverty lines in the case of single-parent households; the cost of this transfer at the national level is shown as a percentage of GDP. Costs and impacts impact. For example, the poverty rate would fall from 61.8% to 34.6% in Nicaragua and from 45.7% to 29.9% in Guatemala. The decrease in more developed countries would also be significant. Poverty, inequality and income transfers: costsand impacts 20 6.35 2.38 15 3.00 0.45 0.92 Ages 0-4 6.47 5.59 5.77 5.86 Honduras 4.58 Paraguay Colombia 7.80 5.54 3.66 1.68 El Salvador Ecuador Venezuela (Bol. Rep. of) Dominican Rep. Peru Mexico Ages 5-14 7.28 Nicaragua 0.80 0.36 0.26 2.69 2.33 2.64 2.03 1.78 1.74 1.20 1.16 3.11 1.59 1.54 1.94 2.09 2.39 1.85 0.99 1.03 0.58 0.60 Panama Chile 0 0.66 0.54 0.77 0.71 Brazil 0.47 0.70 0.50 1.05 0.64 0.86 Guatemala 0.60 5 6.09 6.28 Bolivia (Plur. State of) 10 Uruguay The most direct and easiest-to-evaluate mechanisms are income transfers to children aged 0-14 and transfers or job and training subsidies to young people aged 15-24 who are neither studying nor working. In both cases, the cost and impact of these transfers is estimated and their scope is limited to the vulnerable population (belonging to households whose per capita income is below 1.8 poverty lines). As figure 21 shows, the cost of such a transfer system is fairly easily fundable for one group of countries, represents a major effort for another group and is beyond the range of possibility for a third set of countries. For Argentina, Chile, Costa Rica, Uruguay and, to a lesser extent, Brazil and Panama, the additional costs are manageable for a short period of time, representing some 2% of GDP. For the Bolivarian Republic of Venezuela, Colombia, Ecuador, Dominican Republic and Mexico, the effort is considerable (near to or in excess of 5 percentage points of GDP). For Guatemala, Honduras, Nicaragua, Paraguay and the Plurinational State of Bolivia, the fiscal requirement would be excessive, making it important to mobilize additional international cooperation resources. As for the effect on poverty, the three kinds of transfers proposed would, combined, have a substantial absolute Figure 21 LATIN AMERICA (16 COUNTRIES): COST OF ALL CASH TRANSFERS TARGETING THE VULNERABLE POPULATION, AROUND 2008 a (Percentages of GDP) Costa Rica In addition to knowing what these measures cost, we need to know their social yield, too, that is their impact on equality and well-being. Argentina 3. Transfer, to each young person aged 15-24 who is neither studying nor working, an allowance equivalent to the monthly public cost per pupil at the upper secondary school level; the cost of this transfer at the national level is shown as a percentage of GDP. 4. Invest in education an amount equal to what it would cost the educational system to bring in all of the children and young people who are currently not included in all levels; early childhood, preschool, primary, lower secondary and upper secondary, at the appropriate age. The monthly cost per pupil for each level is calculated and the aggregate total cost of allocating such an amount per month is simulated, taking into account all school-age children and young people who are not attending school. Ages 15-24 Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the relevant countries and projections of gross domestic product (GDP). a Here the vulnerable population is defined as the population whose income is at or below 1.8 poverty lines. Data for Nicaragua refer to 2005, for Argentina, Chile and Guatemala to 2006, and for Honduras and the Plurinational State of Bolivia, to 2007. The nature of the transfers is such that their impact is strongest among children and young people. In these cases, the relative decline in the poverty rate will be proportionally larger than shown in figure 22. And there Social Panorama of Latin America • 2010 39 will be a significant decrease in inequality–more striking in the less developed countries and more modest in the more advanced ones. Figure 22 LATIN AMERICA (18 COUNTRIES): IMPACT OF TRANSFERS ON POVERTY REDUCTION, AROUND 2008 a (Absolute poverty points) 68.7 70 61.8 60 53.8 54.7 50 42.6 42.7 34.7 27.6 21.0 4.4 7.6 13.9 20.4 22.9 26.1 1.5 9.4 1.0 Poverty, inequality, education cycle and life cycle: costs and impacts Taking aim at inequality and poverty among children and young people calls for initiatives on at least three critical fronts: extend coverage in early childhood by means of early childhood care and education systems (0-4 years of age), complete the process of achieving universal coverage in the basic education cycle age brackets (0-14) and work towards universal coverage among adolescents and young people in the upper cycle of secondary education (15-17). All of these targets, and the additional per-student cost in each country, are within the reach of all of the countries of the region. Indeed, as figure 23 shows, in 15 of the 18 countries reviewed the cost does not exceed one percentage point of GDP, considering the minimum required cost for completing coverage at constant investment rates because only the current expense per pupil is taken into account. Creating the infrastructure and improving the conditions that would enable such coverage to truly level the playing field would require substantially heavier outlays. For example, while the cost of achieving universal primary education is very low in terms of GDP (0.02%0.31%, depending on the country), extending coverage to a full day for children aged 6-11 would push the cost up substantially because in almost all of the countries of the region the vast majority of children in this age group did Peru Colombia Panama Ecuador Argentina Chile Dominican Rep. Brazil Bolivia (Plur. State 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 and projections of GDP. a Data for Nicaragua refer to 2005, for Argentina, Chile and Guatemala to 2006, and for Honduras and the Plurinational State of Bolivia, to 2007. 0.64 0.67 0.76 0.93 0.87 0.0 Costa Rica Honduras Paraguay Nicaragua Guatemala El Salvador Bolivia (Plur. State of) Ecuador Peru Dominican Rep. Poverty after transfers 0.53 0.53 0.54 0.56 0.58 0.59 0.5 0.44 0.52 0.29 0.40 Venezuela (Bol. Rep. of) Uruguay Current poverty rate Colombia Mexico Venezuela (Bol. Rep. of) Brazil Panama Argentina Costa Rica Chile 2.65 2.0 0 Uruguay 2.39 Honduras 5.0 14.4 13.5 16.8 2.35 Nicaragua 10 13.7 13.9 16.4 2.5 29.9 28.8 29.1 Guatemala 20 34.6 Paraguay 30 3.0 39.6 38.7 36.6 El Salvador 25.8 27.1 50.3 47.5 Figure 23 LATIN AMERICA (18 COUNTRIES): COST OF INCORPORATING CHILDREN AND YOUNG PEOPLE AGED 0-17 INTO THE EDUCATION SYSTEM, AROUND 2008 a (Percentages of GDP) Mexico 40 44.3 57.9 not have a full school day around 2008. It is easy to see that investing in the buildings and human resources required to extend the school day pose challenges for the countries that are far more complex than the data on coverage for the age brackets in this cycle would suggest. Universal early childhood Universal pre-primary Universal primary Universal lower secondary Universal upper secondary Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the relevant countries and projections of gross domestic product (GDP). a Data for El Salvador refer to 2004, for Nicaragua to 2005, for Argentina, Chile and Guatemala to 2006, and for Honduras and the Plurinational State of Bolivia, to 2007. For the 0-5 age group in countries without data for the entire bracket, the earliest available ages for the level were used: 4-5 in the Dominican Republic and 5 years of age in Ecuador, Guatemala, Panama, Paraguay and the Plurinational State of Bolivia. Even with these qualifications, an expansion programme like the one proposed would have a substantial impact on the circuits that reproduce inequality and exclusion among children and young people. The two extremes of the challenge (preschool and upper cycle of secondary school) provide an idea of the leap in coverage that this would bring, especially for the poor and vulnerable population segment. Chapter II of this edition of Social Panorama highlights the yawning gaps by income quintile among children and young people (especially when comparing the two extreme quintiles) in terms of preschool education and completion of the upper cycle of secondary school. For this reason, transfers geared towards narrowing gaps at these levels would have an enormous impact in reducing inequalities in education opportunities. For the most critical level in most countries (early childhood), even gradual incorporation would benefit a large group of countries in which the children that would be brought into the system account for a substantial portion of the population. In countries like El Salvador, Guatemala, Honduras and Nicaragua, between three fourths and nearly 9 out of 10 children in the vulnerable deciles (below 1.8 poverty lines) would come into the system. 40 Economic Commission for Latin America and the Caribbean (ECLAC) Funding over time Combining cash transfers and educational coverage increments at basic costs would make it possible, in almost all of the countries, to tackle the reproduction of inequality at its roots early in the life cycle, giving the State a larger role in the goods and services consumption structure of the youngest segment of the population. This would obviously involve considerable effort, and this goal would have to be made a top fiscal priority. The aggregate cost for both sets of measures can be seen in figure 24. Figure 24 LATIN AMERICA (16 COUNTRIES): COST OF TOTAL CASH TRANSFERS TO THE VULNERABLE POPULATION AND OF INCORPORATING CHILDREN AND YOUNG PEOPLE AGED 0-17 INTO THE EDUCATION SYSTEM, AROUND 2008 a (Percentages of GDP) 25 20 15 5 2.39 20 0 2.65 -5 2.35 0.87 20.62 0.93 Total cost of transfers (vulnerable population) -15 -20 -25 Honduras Nicaragua Paraguay 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Bolivia ( Plur. State of) Colombia 11.05 12.13 15.05 15.53 7.37 El Salvador Ecuador Venezuela (Bol. Rep. of) Dominican Rep. 5.34 5.57 4.02 4.14 5.07 5.09 Peru Panama Chile Brazil Costa Rica Uruguay Argentina 2.17 2.17 2.18 2.25 2.77 2.79 0.67 Mexico 0.58 0.40 0.56 0.44 0.52 0.53 0.64 0.54 0.29 0.76 0.53 -10 0.59 Guatemala 10 Deficit 15 0 Figure 25 LATIN AMERICA (16 COUNTRIES): TAX DEFICIT OR SURPLUS FOR FUNDING THE TRANSFER SYSTEM AND THE ENHANCEMENT OF CARE AND EDUCATION SERVICES IN GROWING GDP AND EXPANDING TAX BURDEN SCENARIOS a (Percentages of GDP) 10 25 5 growth rate is assumed to be somewhat greater than 2%; in countries whose GDP offers potential for expanding the tax burden, the impact of that expansion (in annual increments) is shown. As can be seen, most of the countries could reach the break-even point before the end of the period, with a sizeable surplus after covering the deficit. Surplus Total cost of incorporating ages 0-17 (entire population) Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the relevant countries and projections of GDP. a Data for Nicaragua refer to 2005, for Argentina, Chile and Guatemala to 2006, and for Honduras and the Plurinational State of Bolivia, to 2007. For the 0-5 age group in countries without data for the entire bracket, the earliest available ages for the level were used: 4-5 in the Dominican Republic and 5 years of age in Ecuador, Guatemala, Panama, Paraguay and the Plurinational State of Bolivia. Funding for these measures cannot be conjured out of nowhere. Depending on the countries, the resources needed to implement the proposed transfer scheme will depend on the following variables: (a) economic growth trends, because if tax pressure remains constant the total tax take will rise; (b) tax burden trends combined with economic growth (the countries with room to increase the tax burden might collect more resources by increasing the extraction rate in proportion to the effort of the economy); (c) any additional resources from restructuring public spending and making it more efficient; and (d) mobilization of additional international cooperation resources. Figure 25 shows the fiscal space that the countries have over a 10-year horizon to cover the additional costs arising from the set of measures proposed. The economic Argentina Colombia Bolivia (Plur. State of) Costa Rica Brazil Dominican Rep. Chile Ecuador El Salvador Guatemala Honduras Mexico Nicaragua Uruguay Panama Venezuela (Bol. Rep. of) Paraguay Peru Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the E basis of special tabulations of data from household surveys conducted in the relevant countries, projections of GDP and data from the Latin American and Caribbean Institute for Economic and Social Planning (ILPES) for effective and potential tax burden. a Data for Nicaragua refer to 2005, for Argentina, Chile and Guatemala to 2006, and for Honduras and the Plurinational State of Bolivia, to 2007. With a growing GDP combined with an expanding tax burden where possible, the countries of Latin America fall into three groups. The first group comprises those countries that in 2012 will be very near to taking in (or will be collecting far more than) the percentage points of GDP needed to afford the measures proposed. This group includes Argentina, Brazil, Chile, Costa Rica, Mexico, Panama and Uruguay. A second group of countries would be a position to do so around 2014. Such is the case with the Dominican Republic, Colombia and Ecuador. The remaining countries (Guatemala, Honduras, Nicaragua, Paraguay and the Plurinational State of Bolivia) would not —except for Paraguay in the final year— have enough revenues to cover these costs by the end of the period, even in the best-case scenario with combined impacts on fiscal space. Complementary resources, such as those from international cooperation, must therefore be considered. Social Panorama of Latin America • 2010 41 Chapter I Poverty, inequality and life cycle A. Poverty and inequality: crisis and recovery The economic crisis that shook the world and the region did not affect poverty and indigence as much as expected. Although output fell almost everywhere, there was virtually no rise in poverty rates, and indigence rates went up only slightly. There were a number of contributory factors, including steady real wages (thanks to low inflation) and policies geared towards preventing losses of income or large-scale redundancies, plus a slight improvement in the income distribution structure. This outcome helped keep the region on the road to meeting target 1A of Millennium Development Goals. It also laid the groundwork for the economic recovery expected in 2010 to push the poverty rate down further. The positive developments over the past few years encompassed such components of well-being as access to basic services and education. 42 Economic Commission for Latin America and the Caribbean (ECLAC) 1. Economic context Per capita GDP in Latin America and the Caribbean fell by 3% in 2009 in the midst of a generalized international crisis. This contraction impacted most of the countries of the region, especially the Bolivarian Republic of Venezuela, El Salvador, Honduras, Mexico and Paraguay. Only in the Dominican Republic and Uruguay did GDP rise by more than 2% (see table I.1). Table I.1 LATIN AMERICA (20 COUNTRIES): SELECTED SOCIO-ECONOMIC INDICATORS, 2000-2009 GDP per capita Country/ Year (Average annual variation) a Argentina 2000-2007 2.2 2008 5.7 2009 -0.2 Bolivia (Plurinational State of) 2000-2007 1.4 2008 4.3 2009 1.6 Brazil 2000-2007 2.2 2008 4.1 2009 -1.1 Chile 2000-2007 3.2 2008 2.6 2009 -2.5 Colombia 2000-2007 3.0 2008 0.9 2009 -1.1 Costa Rica 2000-2007 2.9 2008 1.5 2009 -2.3 Cuba 2000-2007 6.1 2008 4.1 2009 1.4 Dominican Republic 2000-2007 3.7 2008 3.8 2009 2.1 Ecuador 2000-2007 3.4 2008 6.1 2009 -0.7 El Salvador 2000-2007 2.3 2008 2.0 2009 -4.0 Guatemala 2000-2007 1.3 2008 0.8 2009 -1.9 Urban unemployment (Simple average for the period) b (percentages) Average real wages c Consumer price index d (Average annual variation) GDP per capita Country/ Year (Average annual variation) a Urban unemployment (Simple average for the period) b (percentages) Average real wages c Consumer price index d (Average annual variation) Haiti 14.2 7.9 8.7 3.1 8.8 11.7 9.9 7.2 7.7 8.0 6.7 7.9 -0.4 -7.4 … 4.6 11.8 0.3 9.7 7.9 8.1 -1.5 2.1 1.3 7.0 5.9 4.3 9.1 7.8 9.7 1.8 -0.2 4.8 3.4 7.1 -1.4 15.7 11.5 13.0 1.6 -2.0 1.1 6.3 7.7 2.0 6.1 4.8 7.6 0.6 -2.0 7.7 11.0 13.9 4.0 2.8 1.6 1.7 5.6 0.1 4.1 … … … 16.3 14.1 14.9 … … … 14.6 4.5 5.7 9.3 6.9 8.5 … … … 17.5 8.8 4.3 6.4 5.5 7.1 … … … 3.8 5.5 -0.2 5.0 … … -0.7 -2.6 0.1 7.3 9.4 -0.3 2000-2007 -1.2 2008 -0.8 2009 1.2 Honduras 2000-2007 3.1 2008 1.9 2009 -3.8 Mexico 2000-2007 1.8 2008 0.5 2009 -7.5 Nicaragua 2000-2007 2.0 2008 1.4 2009 -2.7 Panama 2000-2007 3.7 2008 8.9 2009 0.8 Paraguay 2000-2007 0.5 2008 3.9 2009 -5.5 Peru 2000-2007 3.6 2008 8.5 2009 -0.3 Uruguay 2000-2007 2.0 2008 8.2 2009 2.5 Venezuela (Bolivarian Republic of) 2000-2007 2.4 2008 3.0 2009 -4.9 Latin America 2000-2007 2008 2009 2.2 3.0 -3.0 … … … … … … 17.2 17.0 2.1 6.1 4.1 4.9 … … … 8.1 10.8 3.0 4.4 4.9 6.7 2.3 2.2 0.6 4.9 6.5 3.6 8.9 8.0 10.5 0.5 -3.8 6.5 8.8 12.7 1.8 13.6 6.5 7.9 -1.1 -0.6 -0.4 2.2 6.8 1.9 10.1 7.4 8.2 0.3 -0.7 4.3 9.0 7.5 1.9 9.1 8.4 8.4 0.6 2.2 0.3 2.2 6.6 0.2 13.6 7.9 7.7 -1.6 3.6 7.3 9.0 9.2 5.9 13.4 7.3 7.8 -1.4 -4.5 -6.6 19.6 31.9 26.9 9.8 7.3 8.2 0.5 -0.5 3.1 7.6 8.4 4.7 Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of official figures. E a Based on per capita GDP in dollars, at constant 2000 prices. b In the Bolivarian Republic of Venezuela, Chile, Cuba, the Dominican Republic and Nicaragua, the figures are for total national unemployment. In Guatemala, figures for the period 2000-2007 were only available for the three years from 2002 to 2004. The unemployment figures for Peru cover only the city of Lima. The data for Argentina, Brazil and Mexico have been adjusted to reflect changes in methodology in 2003, 2002 and 2005, respectively. c Generally speaking, coverage of this index is very partial. In most countries, it covers only formal workers in the industrial sector. Rates of change in Latin America as a whole were calculated using a global index calculated as a simple average of the indices for those countries of the region with data available. d Simple average of variations from December to December each year. Social Panorama of Latin America • 2010 43 Unlike prior crises, though, this time public policy was paramount in tempering the impact on labour and social conditions. The countries drew on solid macroeconomics built up during the economic and financial boom, applying countercyclical fiscal and monetary policies. So, although the employment rate did fall from 55.1% to 54.6% as unemployment rose from 7.3% to 8.2%, the impact on the labour market was less than initially forecast (ECLAC/ILO, 2010). Price stability helped protect the purchasing power of income and thus staved off a significant drop in domestic 2. demand. The simple average inflation rate for the region as a whole was 4.7% in 2009. Excluding the Bolivarian Republic of Venezuela brings the average down to 2.6%. Available data on average real wages for most of the countries show a slight uptick after the decrease posted in 2008. In this context, regional GDP growth is projected to recover quickly in 2010, to 5.2% (equivalent to a 3.7% rise in GDP per capita). Economic expansion is seen throughout the region, although the pace is higher in the countries of South America and the highest rate of growth is in Brazil (ECLAC, 2010e). Recent evolution of poverty The poverty rate in the region was 33.1% in 2009, with 13.3% of the population living in extreme poverty or indigence. These figures translate into 183 million poor and 74 million living in indigence (see figure I.1). Despite the marked drop in GDP in the region in 2009, the poverty rate worsened only slightly compared with 2008, equivalent to an increase of 0.1 percentage points. Extreme poverty posted a somewhat higher increase: 0.4 percentage points. The number of poor and indigent rose by 3 million. These figures point to relatively positive results over the past few years. Compared with 2002, when poverty and indigence rates were the highest since 1990, both indicators are down sharply —by 10.9 percentage points for the former and 6.1 percentage points for the latter. However, the two indicators have evolved differently over the past two years, with the indigence rate showing more appreciable deterioration. Unlike the poverty rate, indigence fell at a faster pace to 2007 than it did to 2009. Figure I.1 LATIN AMERICA: POVERTY AND INDIGENCE, 1980-2010 a (Percentages and millions of people) 300 60 48.3 Percentages 40 250 43.8 40.5 44.0 34.1 33.0 33.1 32.1 30 22.5 20 18.5 18.6 19.4 12.6 12.9 13.3 Millions of people 50 150 211 221 184 180 183 180 71 74 72 2008 2009 2010 136 93 100 12.9 10 200 200 89 97 68 62 50 0 0 1980 1990 1999 2002 2007 2008 2009 2010 Indigent 1980 1990 1999 2002 2007 Non-indigent poor 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. a Estimate for 18 countries of the region, plus Haiti. The figures above the bars are the percentage and total number of poor persons (indigent plus non-indigent poor). 44 Economic Commission for Latin America and the Caribbean (ECLAC) The differing dynamics of poverty and indigence are due in part to the evolution of food prices compared with the prices for other goods. Food prices rose nearly two and a half times more than non-food products between 2006 and 2009 (see figure I.2). The increase in food prices transfers in its entirety to the value of the indigence line, pushing the latter up more quickly than the poverty line.1 There is information available for assessing the evolution of poverty and indigence between 2008 and 2009 for nine countries. In six of them, poverty dropped appreciably between the two years. In the Dominican Republic and Uruguay (data for urban areas), the poverty rate fell by more than 3 percentage points; Brazil, Panama, Paraguay and Peru recorded declines between 0.9 percentage points and 2.2 percentage points. Slightly smaller negative poverty rate variations were posted in Colombia and Ecuador (see figure I.3).2 In 2009, the indigence rate came down considerably in Colombia, the Dominican Republic, Panama, Peru and Uruguay and declined slightly in Brazil and Paraguay. Costa Rica is the only country in which the poverty and indigence indicators deteriorated appreciably in 2009, rising by 2.5 percentage points and 1.4 percentage points, respectively (see figure I.3). Figure I.2 LATIN AMERICA (18 COUNTRIES): ACCUMULATED VARIATION OF FOOD CPI COMPARED WITH NON-FOOD CPI, 2006-2009 (Multiples) Latin America Argentina El Salvador Venezuela (Bol. Rep. of) Honduras Dominican Republic Guatemala Nicaragua Colombia Uruguay Paraguay Costa Rica Mexico Ecuador Brazil Peru Panama Bolivia (Plur. State of) Chile 0 1 2 3 4 5 6 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the respective countries. Figure I.3 LATIN AMERICA (18 COUNTRIES): ANNUAL VARIATION IN POVERTY AND INDIGENCE RATES, 2002-2008 AND 2008-2009 a (Percentage points) A. Poverty B. Indigence 3 2 2 1 1 0 0 -1 -2 -1 -3 -2 -4 -5 2008 -2009 2002 -2008 Uruguay b Venezuela (Bol. Rep. of) Peru Dominican Rep. Panama Paraguay Mexico Nicaragua Honduras Guatemala El Salvador Ecuador c Costa Rica Chile Colombia Brazil Uruguay b -4 Venezuela (Bol. Rep. of) Peru Dominican Rep. Panama Paraguay Mexico Nicaragua Honduras Guatemala Ecuador c 2002 -2008 El Salvador Costa Rica Chile Colombia Brazil Bolivia (Plur. State of) Argentina b -7 Argentina b Bolivia (Plur. State of) -3 -6 2008 -2009 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. a The variations are changes in percentage point rates divided by the number of years in the period. The year of the survey used differs from country to country. The period 2002 corresponds to the latest survey available between 2000 and 2002, and the period 2008 represents surveys available between 2006 and 2008. The year 2009 refers only to data for that year. b Urban areas. c The 2002-2008 variation relates to urban areas and the 2008-2009 variation to the national total. 1 2 Until 2007 the same price deflator was used to update the indigence and poverty lines, so the ratio between them held constant over time. But the widely diverging evolution of food and non-food prices led to the use of different deflators starting in 2007. The indigence line is updated using the food consumer price index (CPI); the non-food component of the poverty line is updated on the basis of the variation of the CPI for the relevant goods and services. For Colombia, this edition of the Social Panorama uses the new series of official poverty estimates produced by the country for the years 2002-2009. Accordingly, the figures may not match those published in previous editions. 2 For Colombia, this edition of the Social Panorama uses the new series of official poverty estimates produced by the country for the years 2002-2009. Accordingly, the figures may not match those published in previous editions. Social Panorama of Latin America • 2010 45 Box I.1 METHOD USED TO MEASURE POVERTY According to the approach used in this report to estimate poverty, a person is classified as poor when the per capita income of that person’s household is below the poverty line, that is, the minimum income needed to meet a person’s basic needs. Poverty lines expressed in national currency reflect a calculation of the cost of a basket of basic goods and services, using the costof-basic-needs method. Where relevant data were available, the cost of a basic food basket that covers a person’s nutritional needs was estimated for each country and geographical area, taking into account consumption habits, the actual availability of foodstuffs and their relative prices, as well as the price differences between metropolitan areas, other urban areas and rural areas. This is the indigence line. The poverty line is defined by adding to the indigence line an estimate of the resources needed by a household to satisfy its basic non-nutritional needs. This estimated amount is the result of multiplying the indigence line by a constant factor of 2 for urban areas and 1.75 for rural areas.a In most cases, data on the structure of household consumption of both foodstuffs and other goods and services came from national household-budget surveys.b Because those surveys were conducted before the poverty estimates were made, indigence lines and poverty lines have been updated using cumulative variations in the consumer price index (CPI). Until December 2006, the same variation was applied to both lines. Starting in 2007, however, the indigence line has been adjusted to reflect changes in the foodstuffs component of the CPI, whereas the part of the poverty line that corresponds to non-food spending is adjusted to reflect changes in that component of the CPI. From 2007 onwards, therefore, the differential between the indigence and poverty lines is no longer constant. Data on family income were taken from household surveys conducted in each country in the years that correspond to the poverty estimates contained in this publication. In line with its usual practice, ECLAC made corrections to account for a lack of response to some income-related questions (in the case of wage-earners, self-employed workers and retirees) and for probable biases that stem from underreporting. This was done by comparing the survey entries for income with figures from an estimate of the household income and spending account taken from each country’s system of national accounts, prepared for this purpose using official information. Income here means total current income; that is, income from wage labour (in both money and kind), self-employed work (including self-supply and the consumption value of home-made products), property income, retirement and other pensions and other transfers received by households. In most countries, household income also includes the imputed rental value of owner-occupied dwellings. Source: Economic Commission for Latin America and the Caribbean (ECLAC). a The 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 (IBGE), the Brazilian Institute of Applied Economic Research (IPEA) 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. b When data from the processing of a recent survey of this type were not available, other information on household consumption was used. The figures available to 2009 for Argentina, Chile and El Salvador show the evolution of poverty over a broader period. Between 2006 and 2009, poverty and indigence in Argentina (urban areas) dropped at the rate of 3.2 percentage points and 1.1 percentage points per year, respectively. In Chile, poverty declined slightly between 2006 and 2009, with the indigence rate remaining basically unchanged.3 Poverty and indigence rates in El Salvador did not change between 2004 and 2009. A broader look that encompasses changes between 2002 and the latest available estimate reveals a generalized trend towards lower poverty and indigence in the countries of the region. According to the poverty gap and the squared poverty gap indices, the net exit of persons from poverty and indigence during the period was accompanied by 3 The estimates published herein differ in many cases from official poverty figures issued by the countries because of differing methodological approaches. For Chile, the figures set out herein diverge for the first time from the country’s official estimates (MIDEPLAN, 2010). In keeping with the change in methodology introduced by ECLAC in 2007, the indigence line was updated in keeping with the food CPI. The part of the poverty line that corresponds to non-food spending was adjusted to reflect changes in the rest of the CPI instead of using the same deflator for both lines as in the past. rising average income among the poor and less distributive disparity in their income. These indices, whose formulation incorporates not only the percentage of poor but also the gap between average income for the poor and the poverty line (for the second index) and the way that income is distributed among the poor, declined more in percentage terms than did the poverty and indigence rates in most of the countries (see table I.A-1 in the appendix). These latest figures on poverty and indigence can also be used to evaluate the progress the countries are making towards meeting target 1A of the first Millennium Development Goal: to halve, between 1990 and 2015, the proportion of people living in extreme poverty. Despite the setback in 2008 and 2009, Latin America is well on the way to achieving target 1A. Progress stands at 82%, which is the accumulated decrease in indigence between 1990 and 2009 (9.2 percentage points) divided by the total expected decrease (11.3 percentage points). This is at the 72% mark of the time set for meeting the goal. Projections for GDP growth and inflation in the countries suggest that the poverty rate will resume its downward trend in 2010 and reach 32.1% —one percentage point lower than in 2009. The indigence rate is expected to fall by some 0.4 percentage points (see figure I.1). 46 3. Economic Commission for Latin America and the Caribbean (ECLAC) Factors behind the changing poverty rate As in previous editions of Social Panorama, two different methodological approaches are used to gauge the influence that some of the factors usually associated with poverty have had on the trend line. The first approach involves determining how much of the change in the poverty rate is due to income variation and how much to changes in income distribution. The second approach weighs the different sources of household income, focusing on labour market factors that affect labour income changes. The variation in poverty and indigence rates may be broken down into two components: growth in average individual income (the growth effect) and changes in how that income is distributed (the distribution effect). This breakdown reveals whether the change in income that pushed the poverty rate in a given direction is part of a general trend for all income groups or had a more specific effect on the poor. The results of this analysis, based on data from household surveys, are presented in such a way that the effect of both components entirely explains the poverty rate variation in a given period (see box I.2). Changes between the most recent estimate available last year and 2009 are due to different combinations of the growth effect and the distribution effect in each country.4 In one group of five countries, the principal factor behind declining poverty was average income growth. In three (Chile, Peru and Uruguay), the effect of this factor was boosted by an improvement in distribution —at least in the distribution area near the poverty line. On the other hand, the downward trend in poverty in Argentina and the Dominican Republic was, in part, slowed —not helped— by changes in distribution. In another group of five countries the distribution effect was the main determinant of falling poverty rates. In some cases (Ecuador and Panama) the distribution effect was heightened by rising average income, while in others (Brazil, Colombia and Paraguay) it offset declines in income. Costa Rica, the only one of the 12 countries reviewed in which poverty rose significantly, saw a clear deterioration of distribution that more than offset the increase in average income. The opposite happened in El Salvador, where the uptick in the poverty rate was triggered by a drop in average income combined with an improvement in distribution (see table I.2). A look at the period from 2002 to 2009 shows that poverty reduction was due to mutual complementarity between the growth effect and the distribution effect. Both effects contributed to the outcome in countries where the poverty rate came down by 7 percentage points or more, with the growth effect accounting for 41% to 80% and the distribution effect accounting for 20% to 59% (see table I.3). Box I.2 METHODOLOGY FOR ANALYSING GROWTH AND DISTRIBUTION EFFECTS According to the traditional scheme for measuring poverty based on insufficient income, a country’s poverty rate at a given point in time is determined entirely by three elements: the poverty line, average income and the income distribution structure. Accordingly, if the poverty line remains constant in real terms, any change in the poverty indicator can be analysed on the basis of variations in average income and income distribution. According to Datt and Ravallion (1992), a poverty indicator can be calculated using income distribution for the beginning period and average income for the ending period. The difference between this indicator and the poverty rate observed in the beginning period can be interpreted as a growth effect. It is also possible to calculate the poverty rate corresponding to average income in the beginning period, but with income distribution similar to that of the ending period. The difference between this indicator and the beginning poverty rate is the distribution effect. The two effects can also be calculated with the beginning and ending periods interchanged. In formal terms, if H(y t, dt) is the poverty indicator for period t, determined by average income (yt) and the shape of the distribution (dt), a breakdown into growth and distribution effects can be expressed as: H(y2, d2) – H(y1, d1) = [H(y2, d1) – H(y1, d1)] + [H(y1, d2) – H(y1, d1)] + R Growth effect Such a breakdown has two disadvantages. First, it is not exact: the residual has no analytical interpretation. The second shortcoming is that the size of each effect Distribution effect depends on the baseline year used in the comparison (beginning or ending year). Both disadvantages can be overcome by averaging the calculated effects using both baseline years (Kakwani, 1997). This is the procedure that was followed for the calculations presented in this chapter. Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Gaurav Datt and Martin Ravallion, “Growth and redistribution components of changes in poverty measures”, Journal of Development Economics, vol. 38, 1992; Nanak Kakwani, “On measuring growth and inequality components of changes in poverty with application to Thailand”, Discussion Paper, University of New South Wales, 1997. 4 The pre-2009 information available for Argentina and Chile dates from 2006 and for El Salvador from 2004. The changes examined therefore encompass a longer period than the crisis itself. Social Panorama of Latin America • 2010 47 Table I.2 LATIN AMERICA (12 COUNTRIES): CHANGES IN POVERTY RATES AND CONTRIBUTION OF GROWTH AND DISTRIBUTION EFFECTS, 2008-2009 a (Percentages) Year Poverty Contribution to total variation Effect Beginning Ending Beginning Ending Variation Growth Argentina b 2006 2009 21.0 11.3 -9.7 -9.7 Distribution 0.0 Growth 100 Distribution 0 Uruguay 2008 2009 13.7 10.4 -3.3 -2.1 -1.2 65 35 Dominican Republic 2008 2009 44.3 41.1 -3.2 -5.7 2.5 >100 <0 Chile 2006 2009 13.7 11.5 -2.2 -1.5 -0.7 70 30 Paraguay 2008 2009 58.2 56.0 -2.2 0.1 -2.3 <0 >100 Peru 2008 2009 36.2 34.8 -1.4 -2.1 0.7 65 35 Panama 2008 2009 27.7 26.4 -1.3 -0.5 -0.8 44 56 Brazil 2008 2009 25.8 24.9 -0.9 0.6 -1.5 <0 >100 Ecuador 2008 2009 42.7 42.2 -0.5 0.6 -1.1 <0 >100 Colombia 2008 2009 46.1 45.7 -0.4 0.8 -1.2 <0 >100 El Salvador 2004 2009 47.5 47.9 0.4 0.7 -0.3 >100 <0 Costa Rica 2008 2009 16.4 18.9 2.5 -1.3 3.8 <0 >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 respective countries. a Countries in order of total variation in poverty rate, expressed in percentage points. The period 2008 refers to the latest survey available between 2006 and 2008. b Urban area. Table I.3 LATIN AMERICA (18 COUNTRIES): CHANGES IN POVERTY RATES AND CONTRIBUTION OF GROWTH AND DISTRIBUTION EFFECTS, 2002-2009 a (Percentages) Year Poverty Beginning Argentina b Contribution to total variation Effect Ending Beginning Ending Variation Growth 2002 2009 45.4 11.3 -34.1 -27.3 Distribution -6.8 Growth 80 Distribution 20 Venezuela (Bolivarian Republic of) 2002 2008 48.6 27.6 -21.0 -11.7 -9.3 56 44 Peru 2001 2009 54.7 34.8 -19.9 -15.5 -4.4 78 22 Brazil 2001 2009 37.5 24.9 -12.6 -5.8 -6.8 46 54 Panama b 2002 2009 36.9 26.4 -10.5 -4.9 -5.6 47 53 Ecuador b 2002 2009 49.0 40.2 -8.8 -6.1 -2.7 70 30 Chile 2000 2009 20.2 11.5 -8.7 -3.8 -4.9 44 56 Colombia 2002 2009 54.2 45.7 -8.5 -6.4 -2.1 75 25 Bolivia (Plurinational State of) b 2002 2007 62.4 54.0 -8.4 -3.5 -4.9 41 59 Honduras 2002 2007 77.3 68.9 -8.4 -6.0 -2.4 71 29 Nicaragua 2001 2005 69.4 61.9 -7.5 -5.5 -2.0 73 27 Dominican Republic 2002 2009 47.1 41.1 -6.0 -11.4 5.4 >100 <0 Guatemala 2002 2006 60.2 54.8 -5.4 -7.1 1.7 >100 <0 Paraguay a 2001 2009 61.0 56.0 -5.0 -0.9 -4.1 18 82 Uruguay b 2002 2009 15.4 10.7 -4.7 -3.2 -1.5 69 31 Mexico 2002 2008 39.4 34.8 -4.6 -4.2 -0.4 90 10 Costa Rica 2002 2009 20.3 18.9 -1.4 -2.2 0.8 >100 <0 El Salvador 2001 2009 48.9 47.9 -1.0 2.5 -3.5 <0 >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 respective countries. a Countries in order of total variation in poverty rate, expressed in percentage points. The period 2009 refers to the latest survey available between 2006 and 2009. b Urban area. Economic Commission for Latin America and the Caribbean (ECLAC) 4. Figure I.4 LATIN AMERICA (12 COUNTRIES): ANNUAL VARIATION IN TOTAL INCOME PER PERSON AND BY SOURCE IN POOR HOUSEHOLDS, 2008-2009 a (Percentages) 28 15 20 10 12 5 4 0 -4 -5 -12 -10 Wages and salaries Other income Costa Rica Colombia Self-employment earnings Total income El Salvador Brazil Ecuador Peru Paraguay Chile Panama -28 Dominican Rep. -20 Uruguay -20 Argentina b -15 Change in poverty rate 20 Transfers Poverty rate Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the respective countries. a Countries in order of annual variation in poverty rate. The period 2008 refers to the latest survey available between 2006 and 2008. The percentage of population analysed is the same for both periods and refers to the poverty rate in 2008. b Urban area. Figure I.5 LATIN AMERICA (12 COUNTRIES): ANNUAL CHANGE OF LABOUR INCOME COMPONENTS PER PERSON IN POOR HOUSEHOLDS, 2008-2009 a (Percentages) 0.15 0.10 0.05 0.00 -0.05 -0.10 YL/E E/N Costa Rica Ecuador Chile Brazil Colombia El Salvador Paraguay Dominican Rep. Peru Panama -0.20 Uruguay -0.15 Argentina b The second approach for analysing poverty rate variation involves assessing the impact of variations in sources of income. Of particular interest are labour income (as the primary source of household resources) and public transfers. In 2009, changes in poor household income were triggered mainly by rising or falling labour income. In most of the countries reviewed, average labour income in poor households increased in real terms. Wage and independent work income tended to vary in the same direction, except in Colombia, the Dominican Republic and Ecuador. Transfers made a noticeable contribution to the increase in total income among the poor in six of the countries reviewed. Virtually all of these transfers are in the form of government subsidies or assistance. The exception is Argentina, where retirement pensions account for the largest portion of the increase in this source of income. Labour income per person can be expressed as the product of labour income per employed person and the ratio of the number of employed persons to the total population, making it possible to identify what each component contributes to the annual variation in labour income per person. In most of the countries reviewed, average labour income for poor households rose in real terms in 2009. In El Salvador, Peru and Uruguay this was the result of both an increase in labour income per employed person and a rise in the proportion of employed persons. In Argentina, the Dominican Republic and Panama the reason was a considerable increase in labour income per employed person. In Colombia and Paraguay, the drop in labour income per employed person was offset by a rising proportion of employed persons. Labour income decreased in Chile, Costa Rica and Ecuador. The factors assessed interacted in different ways in each of these countries. In Chile, the employment rate fell while income per employed person rose. The opposite happened in Ecuador; both factors declined in Costa Rica (see figure I.5). Change in income 48 Labour income 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. a Countries in order of annual variation in poverty rate. The period 2008 refers to the latest survey available between 2006 and 2008. The percentage of population analysed is the same for both periods and refers to the poverty rate in 2008. b Urban area. Recent evolution of inequality The distribution of income in the countries of Latin America is known as one of the most unequal in the world; this has not changed over the past four decades (UNDP, 2010). Broadly, the income share of the four poorest deciles averages less than 15% of total income, with the wealthiest decile accounting for about one third of the total. Average income received by the wealthiest 20% of the population is 19.3 times more than for the poorest quintile (see figure I.6). Social Panorama of Latin America • 2010 49 Figure I.6 LATIN AMERICA (18 COUNTRIES): INCOME DISTRIBUTION STRUCTURE, 2002, 2008 AND 2009 a (Percentages) A. Share of 40% poorest B. Share of 10% wealthiest 24 50 22 45 20 40 18 16 35 14 30 12 Brazil Guatemala Chile Colombia Honduras Nicaragua Bolivia (Plur. State of) Argentina b Mexico Dominican Rep. Panama Paraguay Ecuador b Peru Costa Rica Uruguay b El Salvador 20 Honduras Colombia Bolivia (Plur. State of) Brazil Dominican Rep. Nicaragua Guatemala Chile Panama Paraguay Peru Costa Rica Mexico El Salvador Ecuador b Argentina b Uruguay b Venezuela (Bol. Rep. of) 8 Venezuela (Bol. Rep. of) 25 10 C. Gap between wealthiest and poorest quintile 50 45 40 35 30 25 20 15 10 2002 Colombia Honduras Brazil Bolivia (Plur. State of) Dominican Rep. Guatemala Panama Paraguay 2008 Nicaragua El Salvador Chile Mexico Peru Argentina b Ecuador b Costa Rica Uruguay b Venezuela (Bol. Rep. of) 5 2009 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. a The year of the survey used differs from country to country. The period 2002 corresponds to the latest survey available between 2000 and 2002, and the period 2008 represents surveys available between 2006 and 2008. The year 2009 refers only to data for that year. b Urban area. Although distributive inequality is a significant problem in all of the countries of the region, it varies in magnitude. In the countries with less inequality (Bolivarian Republic of Venezuela and Uruguay), the four poorest deciles receive some 20% of total income. The wealthiest decile receives approximately 25%; average income for the wealthiest quintile does not exceed 10 times that for the poorest quintile. At the other extreme, in the countries with the greatest inequality the four poorest deciles receive less than 12% of income. The wealthiest quintile has a share of nearly 40%, and income for the wealthiest quintile can be more than 30 times that of the poorest quintile. Despite this heterogeneity, in most of the countries there has recently been an incipient trend towards less concentration of income: between 2002 and the most recent estimate available, the share of the poorest 40% increased in 12 countries (by at least 0.5 percentage points). The share of the wealthiest 10% fell in 14 countries, and the gap between the extreme distribution quintiles narrowed in 14 of the 18 countries studied (see figure I.6). The trend toward less inequality is corroborated by the variation of the Gini and Atkinson indices between 2002 and the most recent date for which information is available. These indices may show different trends because they assign different relative weights to each income distribution segment, so they should be viewed as complementary to each other (see box I.3). All three indices point to a decrease in distribution disparity in 13 countries. Results are mixed for Colombia, Costa Rica and Honduras because only some indicators show deteriorating distribution. The only countries with deteriorating distribution were the Dominican Republic and Guatemala (considering data to 2006, the most recent date for which information is available) (see figure I.7). 50 Economic Commission for Latin America and the Caribbean (ECLAC) Box I.3 INDICATORS FOR MEASURING DISTRIBUTIVE INEQUALITY A wide range of indicators can be used to measure the degree of concentration of a given income distribution. This chapter uses two of the best known inequality indicators, the Gini and Atkinson indices. The best-known of the indices used to analyse income distribution is the Gini. Its formulation is expressed graphically, as it corresponds to the area between the Lorenz curve and the equidistribution line. The greater the income concentration, the larger this area will be and the higher the value of the indicator. Despite its popularity, the Gini index does not satisfy the transfer sensitivity principle, a desirable property for inequality indicators whereby inequality should decrease in response to a progressive transfer of income (i.e., from a “wealthy” household to a “poor” one). The lower the position of the individuals concerned in the distribution, the greater the decrease in inequality should be. The Atkinson index does satisfy the transfer sensitivity principle, and the weight that it assigns to the lowest portion of the distribution can be regulated using a Gini index: Atkinson index: where n = population size, yi = per capita income of the ith individual and μ = mean income. parameter called “inequality aversion” (ε). The greater the value used, the higher the weight given to observations in the lower part of the distribution, most frequently between 0.5 and 2.0. Both indicators take values in the range of zero to one (where zero corresponds to absolute equality and one represents absolute inequality), such that the higher the value of the indicator, the greater the inequality. All inequality indicators are ordinal, so their values cannot be compared. Furthermore, as each of them measures partial aspects of inequality, they can generate different rankings for the same distribution. The ranking of a group of distributions can be considered definitive only if it does not vary between indices. The best procedure, therefore, is to see inequality indices as complementary to each other and analyse the findings together. Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of Frank Cowell, “Measuring Inequality”, LSE Handbooks in Economics, Prentice E Hall, 2000. Figure I.7 LATIN AMERICA (18 COUNTRIES): ANNUAL VARIATION IN SOME INEQUALITY INDICES, 2002-2009 a (Percentages) A. 2002 – most recent year 6 B. 2008-2009 15 4 10 2 5 0 0 -2 -5 -4 Atkinson (0.5) Dominican Rep. Chile Panama El Salvador Argentina b Ecuador b Peru Colombia Uruguay b Paraguay -15 Guatemala Dominican Rep. Honduras Gini Costa Rica Mexico Colombia Uruguay b Chile Ecuador b Panama Paraguay El Salvador Peru Brazil Bolivia (Plur. State of) Nicaragua Argentina b Venezuela (Bol. Rep. of) -8 Brazil -10 -6 Atkinson (1.5) Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries. a The year of the survey used differs from country to country. The period 2002 refers to the latest survey available between 2000 and 2002. The period 2008 corresponds to the latest survey available between 2006 and 2008. The year 2009 refers only to data for that year. b Urban area. Isolating the behaviour of inequality in 2009 from the rest of the period reveals contrasting trends in which improvements in distribution, albeit of lesser magnitude, predominate. Brazil, Colombia, Peru and Uruguay saw the largest declines in all three indices: at least 1.5% per year. While this is not a large value, it does represent a noticeable change. Argentina, Ecuador, El Salvador and Panama also recorded declines in all three inequality indicators. It is striking that Paraguay showed a significant drop in inequality according to the Gini coefficient and the Atkinson index (with an inequality aversion ratio of 0.5) but did not according to an index that assigns greater weight to the lower portion of the distribution. Social Panorama of Latin America • 2010 Inequality indicators in Chile remained virtually unchanged between 2006 and 2009. Hence, Costa Rica and the Dominican Republic are the only countries with a clear deterioration of distribution in 2009, recording Gini coefficient increases of more than 4% and even larger variations in the other indicators. While inequality in Latin America is still among the highest in the world, the favourable trend in recent years 5. 51 shows that distribution can be improved. Some studies indicate that the main factors behind this trend are the narrowing labour income gaps between highly skilled and less skilled recipients and the increase in income transfers to the poorest (López-Calva and Lustig, 2010). In both areas there is space for public policy to enhance redistribution efforts geared towards more equitable distribution, not only in income but also in opportunities. Multidimensional poverty Poverty encompasses deprivations across a broad spectrum of the dimensions of human well-being. Nonetheless, the usual way of quantifying these deprivations is to equate poverty to the lack of economic resources because income is the means whereby most material needs can be met and inadequate income is closely associated with deprivations in other areas of well-being. For all its virtues, income alone does not provide a complete picture of poverty in a country. There are various situations of deprivation that a lack of economic resources does not fully capture. This is especially clear when poverty is conceptualized in a way that looks beyond material needs to cover such areas as psychological wellbeing or self-acceptance, but it can also hold true when its definition is limited to these needs. This usually happens when the goods and services required to meet needs are not purchased in the market but are self-produced or provided by the state. For example, a successful literacy programme improves the well-being of the population but does not increase income (at least not in the short run). Consequently, a measure of poverty based on income inadequacy might be insensitive to certain changes in the well-being of the population. In recent years there has been growing interest in conceptualizing and measuring poverty multidimensionally. One of the conceptual frameworks receiving the most attention in this context is the “capabilities and functionings” approach proposed by Amartya Sen. According to this approach, an individual’s standard of living should be assessed on the basis of the freedom that person has (capabilities) to be or do something (functionings), not on the basis of the objects that person possesses or their “utility”. In this context, then, poverty is defined as the lack of certain basic capabilities. Poverty can also be seen as a violation of a person’s economic, social and cultural rights. In this context, “poverty may be defined as a human condition characterized by sustained or chronic deprivation of the resources, capabilities, choices, security and power necessary for the enjoyment of an adequate standard of living and other civil, cultural, economic, political and social rights” (United Nations, 2001). Taking a multidimensional approach to measuring poverty involves identifying the relevant dimensions, selecting the appropriate indicators and defining the thresholds for what is considered sufficient in each case. There are several ways do to this; they can be based on normative assumptions, empirical antecedents or public consensus, among others (Alkire, 2008). With a multidimensional measure, it is common to seek synthetic indices that sum up data on poverty in a single figure. There have been significant advances in this area in recent years, consolidating desirable properties for these indices and proposing families of indicators (Bourguignon and Chakravarty, 2003; Tsui, 2002; Alkire and Foster, 2009). Latin America has habitually issued figures equatable to the notion of multidimensional poverty, applying the unsatisfied basic needs method. This method rates basic deprivation among the population for such factors as housing, access to potable water and sanitation and education. While it is commonly used with data from population and housing censuses, it can also be applied to data from household surveys. Growing interest in developing multidimensional measures of poverty has led to new applications in the region and worldwide. One example is the official measure of multidimensional poverty for Mexico developed recently by the National Council for the Evaluation of Social Development Policy (CONEVAL, 2009). Worldwide, the United Nations Development Programme Human Development Report 2010 includes a multidimensional poverty index based on household surveys conducted in countries around the world. It replaced the Human 52 Economic Commission for Latin America and the Caribbean (ECLAC) Poverty Index presented in 1997 (Alkire and Santos, 2010). Thanks to the work done by the United Nations Children’s Fund (UNICEF), there has also been progress towards a multidimensional measure of child poverty in the world (Gordon and others, 2003). In line with the need to complement the monetary measure of poverty with a multidimensional approach, this section looks at the evolution of living conditions in the region using a method similar to the unsatisfied basic needs method, complemented by some more recent proposals for building synthetic indices. The basic needs considered are those that are usually measured by household surveys in the countries of the region. They concern housing quality and adequacy in aspects such as type of floor, access to potable water and sanitation, availability of electricity and crowding (Feres and Mancero, 2001). To capture shortfalls in education, the approach was similar to the one followed by Alkire and Santos (2010), linking attendance rates for schoolage children to educational deficiencies among the adult population.5 Box I.4 explains the selected satisfaction indicators and thresholds. Box I.4 UNSATISFIED BASIC NEEDS INDICATORS Unsatisfied basic needs of households were evaluated by referring to the traditional scheme for the region, with some modifications. The indicators chosen refer to housing characteristics, especially floor type, crowding (number of people per room), availability of potable water and sanitation and access to education for children (school attendance) and adults (number of years of schooling). The satisfaction thresholds for each indicator are similar to those used for previous applications of the method. Where relevant, differentiated thresholds were established for urban and rural areas. The following are considered unsatisfied needs: – Dwelling quality: dwellings with dirt floors (urban and rural areas); – Crowding: three or more people per room (urban and rural areas); – Water source: any source of water except a public system (urban areas); river, stream, rain etc. (rural areas); – Toilet facility: no sanitation, or toilet not connected to a sewer system or septic tank (urban areas); no sanitation, or untreated toilet system (rural areas); – Electricity: no electricity, either public or private (urban and rural areas); – Education: whether the household has children who are not attending an educational establishment, or no one has completed six years of schooling. Source: Economic Commission for Latin America and the Caribbean (ECLAC). The survey results show, first, how the deprivation rates evaluated vary widely among the countries of the region. For example, the lack of an appropriate floor in the dwelling is fairly widespread in Guatemala, Nicaragua and Peru, at 35% or more of the population, and, to a lesser extent, Bolivia (Plurinational State of), El Salvador and Honduras (20% to 30% of the population). By contrast, in six countries of the region less than 5% of the population lacks appropriate flooring (see figure I.8). The situation is similar for the other situations of deprivation evaluated. The percentage of persons without an appropriate source of drinking water ranges from 2% to 28%. Between 1% and 40% lack an appropriate sewage elimination system. Crowding (three or more persons per room) affects 1% to 20% of the population. The range is 3% to 40% for insufficient access to education. Figure I.8 also shows that all of the deprivations rated trended down between 2000 and 2009. In most cases, the decreases have been proportionally similar from one country to the next, so their ranking has not changed much since the early 1990s. One way to measure poverty multidimensionally is to count the situations of deprivation for each household and to define as poor those with a certain number of deprivations. The traditional aggregation approach under the unsatisfied basic needs method used in the region is to consider as poor those who have at least one situation of deprivation. But deprivation in any given dimension might not be representative of poverty. For this reason it is better to define the poverty threshold using deprivation in two dimensions, in line with other recent multidimensional measurements (Alkire and Santos, 2010; CONEVAL, 2009; Gordon and others, 2003). The aggregate indicator confirms the two findings discussed above: the magnitude of multidimensional poverty varies widely among the countries of the region, and the multidimensional poverty rate has been falling considerably. This wide range of multidimensional poverty indicators is, broadly speaking, similar to the outcomes from a monetary measure of poverty. The countries with the highest multidimensional poverty rates (Guatemala, Honduras, Nicaragua and the Plurinational State of Bolivia) are also those with the highest monetary poverty rates. At the other extreme, Chile, Costa Rica and Uruguay (urban area) are the countries with the lowest multidimensional poverty rates and the lowest monetary poverty rates (see table I.4). 5 This makes it possible to evaluate the education dimension for all households, not only those with school-age children as is usually done with the traditional unsatisfied basic needs method. Social Panorama of Latin America • 2010 53 Figure I.8 LATIN AMERICA (17 COUNTRIES): SELECTED BASIC NEEDS, 2000, 2008 AND 2009 a (Percentage of people) A. Dirt floor B. Access to drinking water 35 50 30 40 25 30 20 15 20 10 10 5 Chile Mexico Uruguay b Venezuela (Bol. Rep. of) Colombia Costa Rica Ecuador b Brazil Argentina b Nicaragua C. Crowding Guatemala Bolivia (Plur. State of) El Salvador Paraguay Honduras Chile Uruguay b Argentina b Ecuador b Costa Rica Dominican Rep. Mexico Venezuela (Bol. Rep. of) Colombia Paraguay Honduras El Salvador Bolivia (Plur. State of) Peru Guatemala Nicaragua Peru 0 0 D. Education 25 60 50 20 40 15 30 10 20 5 2000 2008 Chile Argentina b Uruguay b Ecuador b Venezuela (Bol. Rep. of) Costa Rica Mexico Paraguay Peru Brazil Dominican Rep. Bolivia (Plur. State of) Colombia El Salvador Nicaragua Honduras Guatemala 0 Brazil Chile Uruguay b Costa Rica Dominican Rep. Mexico Venezuela (Bol. Rep. of) Colombia Ecuador b Argentina b El Salvador Peru Paraguay Bolivia (Plur. State of) Honduras Nicaragua Guatemala 0 10 2009 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. a Countries listed in order of the rating for each basic need, for the latest year on which information is available. The year of the survey used differs from country to country. The period 2000 corresponds to the latest survey available in 2000, and the period 2008 represents the latest surveys available between 2006 and 2008. The year 2009 refers only to data for that year. b Urban area. Table I.4 LATIN AMERICA (17 COUNTRIES): MULTIDIMENSIONAL AND MONETARY POVERTY RATE, 2009 a (Percentage of persons) Multidimensional poverty > 40 > 60 45-59 30-39 Nicaragua Honduras Guatemala Bolivia (Plurinational State of) Peru 20-29 El Salvador Paraguay 5-20 0-5 Colombia 30-44 Dominican Republic Ecuador b Mexico 20-29 Brazil Venezuela (Bolivarian Republic of) Monetary poverty 10-20 Argentina b Chile Costa Rica Uruguay b 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. a Refers to the latest survey available between 2006 and 2009. b Urban area. Economic Commission for Latin America and the Caribbean (ECLAC) Figure I.9 LATIN AMERICA (17 COUNTRIES): MULTIDIMENSIONAL POVERTY RATE, 2000-2009 a (Percentages) 70 60 50 40 30 20 10 Chile Uruguay b Ecuador b Costa Rica Venezuela (Bol. Rep. of) Dominican Rep. Argentina b c Brazil Mexico Paraguay 2000 Colombia c El Salvador Peru Bolivia (Plur. State of) Honduras 0 Nicaragua Over the past decade, practically all of the countries of the region recorded a reduction in multidimensional poverty rates, with drops of more than 10 percentage points in six cases (see figure I.9). The only cases where multidimensional poverty did not decline was in some countries where rates were below 10% (which is to be expected because some of the indicators used are probably at the minimum threshold level). The evidence confirms the trend towards improving living conditions. However, this assessment of multidimensional poverty is limited to the material deprivations that household surveys conducted in the region can quantify. To make better use of the multidimensional approach, material deprivations should be assessed along with deprivation in other components of well-being. To do so requires improving the sources of information currently available. Guatemala 54 Most recent year Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the respective countries. a The year of the survey used differs from country to country. The period 2000 corresponds to the latest survey available in 2000, and the period 2009 represents the latest surveys available between 2006 and 2009. b Urban area. c The surveys available around 2000 do not allow a comparable estimate of multidimensional poverty. B. Fertility, early emancipation and poverty Early initiation of emancipation is a milestone in life for poor young persons. In most of the countries of the region, early fertility among poor mothers is falling at a slower pace than for all mothers. This means that a significant number of women are forming a family prematurely, with scant resources and a heavy child-rearing burden. Institutional disaffiliation (neither working nor going to school) is therefore more frequent among women than among men and for young people from lower-income strata than for their peers who are better off. This situation calls for comprehensive policies that, together, tackle issues involving reproductive outcomes, school dropout rates, emancipation paths and vulnerability to exclusion. 1. Poverty trends among children and adolescents and some of the demographic determinants In monetary terms, child poverty in Latin America declined significantly between 2000 and 2009; child and adolescent poverty fell in 13 of 15 countries of the region (see figure I.10). Nevertheless, poverty still affects children and adolescents proportionally more than the rest of the population. Between 2002 and 2009, the overrepresentation Social Panorama of Latin America • 2010 55 of children and adolescents living in poverty rose from 1.6 to 1.7 (see figure I.11), highlighting the need to better understand the factors and dynamics that are behind child poverty in order to design and implement policies for making substantial headway in bringing the child and adolescent poverty rate down. Figure I.10 LATIN AMERICA (15 COUNTRIES): CHILDREN AND ADOLESCENTS IN POOR HOUSEHOLDS, 1990-2009 a (Percentage variation of the poverty rate) 30 26 25 18 20 15 10 4 1 0 1 1 -3 -1 -3 -5 0 1 0 0 -1 -1 -1 -2 -2 -2 -2 -3 -5 -4 00 -6 0 0 -1 -3 -1 0 -2 -3 2 2 1 0 -4 -4 -5 -6 1999/2002 Venezuela (Bol. Rep. of) b Paraguay Uruguay c Honduras Ecuador c 1990/1999 El Salvador Colombia Costa Rica Chile Brazil Bolivia (Plur. State of) c Argentina b -15 c -10 Panama -10 2 Nicaragua 0 Mexico 5 2002/2009 Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the respective countries. a Annualized. Obtained by dividing the percentage change in the poverty rate during the period by the number of years in the period. b Metropolitan area. In Argentina, refers to Greater Buenos Aires. In Paraguay, refers to the Asunción metropolitan area. c Urban areas. Figure I.11 LATIN AMERICA (16 COUNTRIES): RATIO OF CHILD AND ADOLESCENT POVERTY TO THE POVERTY RATE IN THE REST OF THE POPULATION, 1999-2009 3.5 3.1 3 2.5 2 2.9 2.7 2.4 2.4 2.2 1.8 1.8 1.8 1.5 1.4 1.4 1.5 2.1 1.7 1.8 1.7 1.8 1.7 1.6 1.4 1.4 1.6 1.4 1.4 1.2 1.4 1.4 1.3 1.4 1.6 1.5 1.4 1.4 1 1.2 1.2 1.1 2.0 1.8 1.7 1.5 1.5 1.4 1.3 1.2 1.2 1.4 1.4 1.6 1.6 1.7 0.5 1999 2002 Latin America c Venezuela (Bol. Rep. of) Uruguay b Paraguay a Panama b Nicaragua Mexico Honduras Guatemala El Salvador Ecuador c Costa Rica Colombia Chile Brazil Bolivia (Plur. State of) b Argentina a 0 2009 Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the respective countries. a Metropolitan area. In Argentina, refers to Greater Buenos Aires. In Paraguay, refers to the Asunción metropolitan area. b Urban areas. c Simple averages. One of the keys to understanding the dynamics behind the reproduction of child poverty is to be found in behaviour during the early stages of the life cycle. Particular attention should be paid to reproductive behaviour leading to early fertility. It has been observed that children are highly likely to repeat the reproductive patterns of their parents, and in the poorest families these patterns involve early fertility and more children than the average for all households. It has been suggested that there is a vicious circle whereby poverty is linked to higher and earlier fertility and a heavy child-rearing burden for households that leads back to greater poverty (Carrasco, Martínez and Vial 1997; Paz and others, 2004; Rodríguez, 2006). A heavy child-rearing burden forces poor families to distribute scarce resources (material and time, among others) among a large number of children and makes it harder for mothers to participate in the labour market. All of this works against overcoming the poverty threshold (Rodríguez, 2006). Poor children develop at a disadvantage in terms of nutrition, health and access to the education system. This erodes their accumulation of human capital and funnels them into precarious jobs that are more poorly paid and generate less household income, thus contributing to the reproduction of poverty in the long run (Paz and others, 2004). In any event, as child poverty has come down in most of the countries of the region the overall fertility rate has also been declining in recent years. This is in keeping with the behaviour of factors linked to the demographic transition (ECLAC, 2004). In some countries the age at which the first child is born is increasing, especially among younger cohorts with higher school attendance rates (INE, 2006). Fertility rates also differ between socio-economic strata; new reproductive patterns such as an increase in adolescent fertility are appearing (Di Cesare, 2007). The drop in the child and adolescent poverty rate might be due in part to the declining fertility rate among poor mothers. However, this impact might have been offset somewhat by the slower decrease in the fertility rate for poor mothers than for all mothers. Table I.5 shows the percentage of change, between 1990 and 2009, in poverty rates for children aged 0-5 and for children and adolescents aged 0-15, as well as the fertility rate changes during the same period for four groups: (a) poor adolescent and young mothers; (b) all poor mothers; (c) all adolescent and young mothers; and (d)  all mothers. This classification is used to analyse the relationship, over time, between the child poverty rate and early fertility among poor mothers. It is also a criterion for comparing the fertility rate for all mothers, controlling for age. 56 Economic Commission for Latin America and the Caribbean (ECLAC) Table I.5 LATIN AMERICA (16 COUNTRIES): CHANGES IN CHILD AND ADOLESCENT MONETARY POVERTY RATE AND IN FERTILITY RATES, 1990 AND 2009 a (Percentages) Poor children aged 0-5 Argentina Fertility rate, poor mothers aged 15-24 b Fertility rate, all mothers aged 15-24 b Poor children aged 0-15 Fertility rate, all poor mothers b Fertility rate, all mothers b -54 -26 -33 -48 -7 -27 Bolivia (Plurinational State of) -14 -23 -30 -9 -17 -29 Brazil -25 -27 -53 -28 -19 -47 Chile -74 -63 -57 -74 -57 -51 -7 -19 -24 -6 -13 -19 Colombia Costa Rica -15 -46 -54 -15 -33 -43 Ecuador -21 -37 -51 -21 -25 -43 El Salvador -11 -39 -39 -7 -23 -26 Guatemala -7 -10 -16 -6 -4 -11 Honduras -8 -46 -49 -8 -29 -34 Mexico -9 -37 -49 -16 -34 -43 Nicaragua -10 -43 -48 -8 -25 -34 Panama -28 13 -19 -37 -7 -24 Paraguay 17 -23 -27 11 -22 -23 Uruguay -45 -33 -31 -45 -41 -39 Venezuela (Bolivarian Republic of) -11 -38 -53 -16 -29 -42 Latin America c -20 -31 -40 -21 -24 -33 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. a Changes in fertility rates for poor and non-poor mothers were calculated considering a constant overall poverty rate at the value for 1990. b The term “mothers” refers to all women identified as female heads of household or spouses of the head of household. c Simple averages. In terms of simple averages for the region, table I.5 shows: (a) poverty among children aged 0-5 and among children and adolescents aged 0-15 has come down at very similar rates (by 20% and 21% respectively); (b) the fertility rate for poor mothers has decreased less than for total mothers —both for early fertility (mothers aged 15-24) and for all poor mothers; and (c) the fertility rate decline among the youngest mothers (aged 15-24) is greater than for all mothers. The latter comparison should be interpreted with care because the age group 15-24 has a broader potential fertility horizon than the rest of the mothers simply because they are younger. As for the link between poverty rates among children aged 0-5 and fertility rates for mothers aged 15-24, in Chile and Uruguay (two of the four countries that brought child poverty down the most) the fertility rate among poor mothers fell more than for all mothers aged 15-24. On the other hand, Argentina (the second most successful country in reducing child poverty) saw the fertility rate for the youngest poor mothers decline less than for all mothers. In Panama, which ranked fourth in reducing child poverty, the fertility rate among poor mothers rose; this was the only case among 16 countries. In Paraguay, the only country where child poverty increased, the fertility rate among poor mothers declined less than for all mothers but the difference was slight (a decrease of 23% versus a decrease of 27%). From the data in table I.5 it can be deduced that, in four of the five countries where the poverty rate for children aged 0-5 fell the most (Argentina, Brazil, Chile and Uruguay), the simple average decline in the fertility rate for poor mothers aged 15-24 was 37%. For the countries that were least successful at decreasing the child poverty rate (Colombia, Honduras, Guatemala, Mexico and Paraguay), the simple average decrease was 27%. These calculations did not include Panama among the countries with the largest drops in the child poverty rate because the fertility rate among poor mothers aged 15-24 in Panama increased. Bringing the co-variation of child and adolescent poverty rates and fertility rates among all poor mothers into the picture does not change it substantially. In Chile and Uruguay, fertility dropped more among poor mothers than for mothers overall. Argentina and Panama saw the fertility rate for poor mothers decline far less than for all mothers. In Paraguay —the only country where child and adolescent poverty rose between 1990 and 2009— the decline in the fertility rate for poor mothers and for all mothers was nearly equal. Social Panorama of Latin America • 2010 57 So, despite positive trends in decreasing child poverty in the countries of the region (linked in some cases to declining early fertility rates among poor mothers), monetary poverty among children and young people is still high. Add to this the fact that early fertility rates among poor mothers aged 15-24 have fallen at a slower pace than for all mothers in the same age group and it emerges that there is still a significant number of mothers who are forming a family prematurely in a context of scant resources and a heavy child-rearing burden. In short, reproductive outcomes can have a long —and lasting— impact in terms of poverty for mothers and their children. This calls for policies targeting current and future mothers. Among such policy instruments are those that foster (a) postponing the age at which motherhood is initiated; (b)  improving access to information on reproduction control; (c)  retaining women in the education system; (d)  improving the quality of their education to ensure that learning outcomes meaningfully broaden labour opportunities; and (e)  making institutions available to provide care for young children, thus making it easier for mothers to attend (or return to) the education system and facilitating their stable participation in the labour market. In other words, poor young women should be offered an attractive, believable and accessible future that does not confine them to motherhood and the domestic world as their only alternatives for gaining a place in society. The countries should redouble their efforts to guarantee the fundamental rights of the child population, both to bring the poverty rate down and to prevent the reproduction of poverty throughout the life cycle. The States of the region have signed international instruments pledging to ensure the core rights of all children, but this has not happened. According to a rights-based approach to measuring child poverty, 17.9% of the children of Latin America (somewhat more than 32 million) were living in extreme poverty in 2007, that is, they suffered from one or more of the following serious deprivations: precarious housing; overall undernutrition and/or serious chronic undernutrition; lack of drinking water and sanitation in the household; lack of communications and information media; and lack of access to the education system. Forty-five per cent of the child population (nearly 81 million) suffered at least one moderate or serious deprivation (see box I.5). Box I.5 A MULTIDIMENSIONAL, RIGHTS-BASED APPROACH TO MEASURING CHILD POVERTY Over the past few years child poverty has come to be seen as a multidimensional issue. From this new vantage point, the lack of monetary income for meeting basic needs is not the only consideration. The lack of access to basic services as well as other factors (such as discrimination and exclusion) that keep children from developing to their full potential and hinder their social integration are also important. One path towards a multidimensional measure of child poverty is the rights-based approach, which requires a broader range of indicators than those habitually used to measure child poverty in Latin America. Along these lines, in 2008 and 2009 ECLAC, in conjunction with the UNICEF Regional Office for the Americas and the Caribbean, conducted the first comparative study of child poverty in Latin America and the Caribbean. This research painted a multidimensional picture Thresholds, dimensions and indicators of child poverty and established a regional baseline as a benchmark for follow-up rights-based studies on child poverty. Under the study’s multidimensional approach, the poor have unmet needs that are assessed using indicators of levels of deprivation during childhood as first proposed by the University of Bristol and the London School of Economics.a This approach is similar to the unsatisfied basic needs method that had already been used in Latin America. This criterion for identifying the poor was compared with the indirect method (more traditional in the region), which defines poverty on the basis of per capita household income. The basis for this was an analysis of available surveys of living conditions in households in the region, providing data for implementing both methodologies. The deprivation thresholds for the UNICEF global study refer only to the most serious violations of children’s rights. To enhance the diagnostic study, the assessment of Latin America and the Caribbean also used thresholds of moderate deprivation, which reflect unmet needs that undermine children’s well-being and development. This made it possible to measure the magnitude and depth of extreme child poverty (severe deprivations) and overall child poverty (the sum of severe and moderate deprivations) in the countries of the region. Under the child rights approach, each deprivation was considered to be an indicator of poverty, since it represents a violation of or failure to comply with at least one right. This methodology considers children poor when any one of their fundamental rights is not met, regardless of geographical location, ethnic origin or other social or cultural characteristics. The thresholds, dimensions and indicators used for the study are set out below. Article of the Convention on the Rights of the Child that is violated Moderate Severe/serious Nutrition Weight to age ratio Height to age ratio Moderately/severely underweight (general undernutrition) or moderately/ severely undersize for age (chronic undernutrition): less than -2 standard deviations from benchmark Severely underweight or severely undersize: less than -3 standard deviations from benchmark 24 (2) (c) Safe drinking water Access to safe drinking water by: - origin - supply - access time (if available) (a) Origin: well or pump (b) Water supplied from outside or away from the dwelling (for example, public cisterns, water trucks etc.) (a) Unsafe water source: natural sources (rivers, springs) (b) If indicator of access time to the water source is available, 15 minutes or more 24 (2) (e) 58 Economic Commission for Latin America and the Caribbean (ECLAC) Box I.5 (concluded) Thresholds, dimensions and indicators Article of the Convention on the Rights of the Child that is violated Moderate Severe/serious Sanitation Connection to sewage system (excreta disposal) No sewage connection (for example, cesspools) or access outside of house or beyond land parcel No sewage service (for example, channelled directly into a river) 24 (2) (c) Housing Number of persons per bedroom/room Floor material Wall material Roofing material Crowding: three or more persons per bedroom/room (excluding bathroom and kitchen); dirt floor, unsafe building materials (walls or roof of mud or similar materials) Overcrowding: five or more persons per bedroom/room, temporary housing (tents, etc.), walls or roofs built with waste materials 27 (3) Education School attendance and number of years of school completed Children and adolescents who have attended school but dropped out before completing secondary school Children and adolescents who have never attended school 28 (1) (a) (b) Information Access to electricity, possession of a radio, television or telephone No household access to at least two of: electricity, telephone (landline or mobile), radio or television No household access to any of: electricity, telephone (landline or mobile), radio and television 13/17 Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of E. Espíndola and N. Rico, “La pobreza infantil: un desafío prioritario”, Boletín E Desafíos, No. 10, Santiago, Chile, Economic Commission for Latin America and the Caribbean ECLAC/United Nations Children’s Fund (UNICEF), 2010. a In 2003, the United Nations Children’s Fund (UNICEF) and researchers from the University of Bristol and the London School of Economics conducted the first rights-based global measurement of child poverty. The study adopted seven dimensions of children’s rights as its principle: adequate nutrition, safe drinking water, decent sanitation, health, housing, education and access to information. An indicator was designed for each dimension (Gordon and others, 2003). 2. Emancipation paths, poverty and inequality The principal assets that people must mobilize if they are to have access to well-being as adults are accumulated earlier in the life cycle. Some of these assets, such as a certain degree of emotional maturity, development of cognitive abilities and social skills, are already put to use in the early years of life. But it is during adolescence and youth that people reach crucial junctures. On the basis of assets already accumulated they must choose between behaviours that lead to different paths to adulthood. Each one of these “emancipation paths” is paved with a series of decisions as to whether to continue school and when to enter the labour market, start a family, set up an autonomous household and have children.6 For society as a whole, the earlier in the life cycle that the different emancipation paths branch out, the more likely the social divides are to widen. Decisions as to how and how much to participate in any one of the spheres (education, work, family and parenthood) leave less room for choice as to how and how much to participate in the others. Hence, dropping out of school early restricts choices in the labour market, while the requirements for most jobs limit the possibilities for attending an educational establishment on a regular basis. And taking on domestic responsibilities at an early age is usually incompatible with staying in school. In short, 6 Because the scope of the choices an individual can make throughout the life cycle hinges directly on socio-economic status, the options open to adolescents and young people from poor households are usually very limited. decisions at this decisive stage of life hinge on complex patterns of causation and, once made, contribute to mapping a path of ever-diminishing choices. Educational attainments are so important in contemporary society that most public policy efforts targeting young people seek to keep them from dropping out of school and to prevent the early assumption of adult roles from leading them to exit the educational system or bar them from returning. Some examples are direct subsidies for attending educational institutions, flexible work hours for young people, day care centres, expanded school schedules, creation of opportunities for training outside the formal educational system and, indirectly, conditional cash transfers. It is harder to act on other factors with a major impact on school desertion, such as signals from the market concerning the value that society attaches to educational attainments and the inertia of traditional symbolic representations that define a place in society for women from lower socio-economic strata by assigning them roles as housekeepers and mothers. Most public policies in this sphere are grounded in the recognition that poor educational credentials and heavy family responsibilities produce a socially explosive mixture that is fertile ground for high vulnerability to poverty and social exclusion and for the intergenerational reproduction of just such situations. Add to this the negative impact of this mix of precariousness and responsibility and one of the results is the low level of life satisfaction among the 15-to-29-year-olds in Latin America who have children, Social Panorama of Latin America • 2010 59 lack a stable partner and must become providers at a very early age without appropriate support for shouldering such responsibilities. So, emancipation paths vary substantially for young people from different socio-economic strata. In stark contrast with the paths open to middle- and upper-class young people, early emancipation is common among those from low socio-economic strata. In the higher strata, socialization and the availability of material resources facilitate the adoption of patterns of deferred gratification that favour putting off entering the labour market, starting a family or becoming a parent. Even if such postponements might not always be an objective per se, they do reflect a certain ability to adjust to rising educational thresholds for adequate performance in society’s principal economic, social and cultural circuits.7 (a) Emancipation paths by gender and household income Early initiation of emancipation is a milestone in life for poor young persons. This is seen more clearly in figures I.12 and I.13, which provide a snapshot of the major differences in the emancipation paths followed by men and women in different social strata according to the demographic and socio-economic characteristics of the country in question. Figure I.12 ARGENTINA, CHILE AND URUGUAY: EMANCIPATION INDICATORS BY AGE AND INCOME GROUP, AROUND 2006 a (Percentages; simple averages) A. Men, quintile I B. Men, quintile V 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 14 29 15 16 17 18 19 20 C. Women, quintile I 100 21 22 23 24 25 26 27 28 29 24 25 26 27 28 29 Age Age D. Women, quintile V 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 14 15 16 17 18 19 20 Age 21 22 23 Age Attendance, quintile I No conjugal union, quintile I Inactivity, quintile I Single, quintile I Attendance, quintile V No conjugal union, quintile V Inactivity, quintile V Single, quintile V 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. a The data for Uruguay correspond to circa 2008. 7 Nevertheless, the possibility that certain forms of social exclusion can impact those who postpone taking on adult roles beyond the average age of their cohort cannot be ignored. Indeed, once past the upper threshold of the culturally accepted age for initiating emancipation, the social forces pushing for the performance of adult roles become broader and can even be mobilized by the parents themselves, prodding young people to leave the family household. In any event, because such postponement usually involves accumulating human capital, many of the young people who join adult life “late” have a much broader range of alternatives for social inclusion than those who do so early. 60 Economic Commission for Latin America and the Caribbean (ECLAC) Figure I.13 EL SALVADOR, GUATEMALA, HONDURAS AND NICARAGUA: EMANCIPATION INDICATORS BY AGE AND INCOME GROUP, AROUND 2006 a (Percentages; simple averages) B. Men, quintile V A. Men, quintile I 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 0 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 24 25 26 27 28 29 Age Age D. Women, quintile V C. Women, quintile I 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 14 15 16 17 18 19 20 21 22 23 Age Age Attendance, quintile I No conjugal union, quintile I Inactivity, quintile I Single, quintile I Attendance, quintile V No conjugal union, quintile V Inactivity, quintile V Single, quintile V 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. a The data for El Salvador correspond to 2004, for Guatemala to 2006, for Honduras to 2007 and for Nicaragua to 2005. Figures I.12 and I.13 highlight the differences between countries by focusing on two groups of societies at the extremes of Latin American heterogeneity in terms of stage of demographic transition and level of educational coverage. The two groups comprise: (a) Argentina, Chile and Uruguay, where the regional context is one of a relatively good education supply, with urbanization, fertility and age structure indicators that place them late in the first stage of demographic transition; and (b) El Salvador, Guatemala, Honduras and Nicaragua, with indices that differ strikingly in both dimensions (Filgueira, Filgueira and Fuentes, 2001). Figures I.12 and I.13 also show the different emancipation paths for adolescents and young people at opposite poles of the social stratification. To this end, behaviour indicators for persons from households in the highest 20% and the lowest 20% of the income distribution were taken. Figures I.12 and I.13 therefore do not show predominant youth behaviours in the region nor the characteristic patterns for each country. Rather, they underscore the breadth of the challenges that the region faces in keeping emancipation paths from diverging on the basis of gender, class and nationality and thus from contributing to the current trends towards social inequality within and between countries. A reading of these figures leads to a number of conclusions. First, there are substantial differences between the country groups in terms of school attendance rates among 15-year-olds, reflecting varying intensities of educational dropout at early stages. At that age, 100% of the adolescents in the highest strata in the first group are still in the educational system. The same is true for some 90% of the adolescents in the low strata. In the second group, on the other hand, the values are approximately 95% in the highest quintile and 75% in the lowest quintile. In both groups of countries, the emancipation paths are the most different for women in the lower-income Social Panorama of Latin America • 2010 strata, both compared with men and compared with their peers in the higher strata. One of the main features of the paths of the poorest adolescent and young women is that labour participation for poor women does not reach 50% for any of the ages in the 15-29 age bracket. Conversely, in the countries in the second group some 80% of the 29year-old women in the wealthiest strata participate in the labour market, as do 90% of their peers in the countries in the first group. In other words, the tendency for men and women to participate in the labour market converges in the higher strata while the opposite happens in the lower strata. This difference surely reflects a permanent division of labour within poor families, influenced by the traditional polarity between a private female world and a public male world. This polarity is even more pronounced in countries that have a high ratio of children per adult because they are in the earlier stages of the demographic transition. The fact that paths for men and women converge in the high-income strata is also indicative of an overlap between labour participation and school attendance. Young people in this stratum have opportunities for engaging in paid activities without giving up their studies; this holds more for men than for women and more for countries in the first group than for the second group. The paths clearly diverge for men and women in the lower strata. Men exchange their status as a student for status as a worker with no overlap between the two, while most women exchange their status as a student for one as a mother, housewife or assistant housewife without passing through the labour market. The age at which a family is formed (which as a gross approximation is equated here with ceasing to be single) also varies significantly between sexes, classes and national contexts. In the low strata in the second group of countries, half of the 20-year-old women are no longer single. In the first group, this change in civil status for women in the same stratum takes place at age 24. In the highest quintile, women form families at age 25 and age 27 in the second and first groups, respectively. So, while the higher strata in all of the countries clearly postpone the age for forming the first spousal couple (as is characteristic of the second demographic transition), this is still an incipient process among poor women in the countries of the region that are just entering the first demographic transition. Lastly, a comparison of the curves shows that in many cases forming a family does not coincide with setting up a household of one’s own. Only among young people in countries at an advanced stage of demographic transition is ceasing to be single part of the process of gaining autonomy from the family of origin. In all other cases, the autonomy curve traced by variations in the percentage of young people who are heads of household or spouses of heads of household 61 is always above the curve showing the declining percentage of single people. This indicates the existence of new core families without the resources to become independent from the household of origin of one of the spouses. (b) Young people who neither study nor work The data on the proportion of young people who are neither studying nor working raise a red flag for the risk of poverty and social exclusion in any society. Strictly speaking, the emancipation path scenario emerging from an assessment of the differences by country, class and sex clearly indicates that young people of the region can be classified into at least three general groups: (i) Those whose main activity is studying and who, by staying connected to educational institutions for most of this period, maximize the opportunities for accumulating the human capital required for full integration into adult life. This status can coexist (or not) with sporadic or stable participation in the world of work. (ii) Those whose main activity is work and who have left the educational system early. In certain conditions, labour experiences can mitigate the risk of lack of wellbeing in the future caused by leaving school early and can facilitate the insertion of dropouts in society. This is particularly the case with the kinds of productive insertion that provide ongoing training, job stability, labour union membership, benefits and social security. However, recognizing that the likelihood of access to such opportunities varies inversely with the levels of qualification attained highlights the importance of efforts to prevent early dropouts. (iii) Those who drop out of the educational system early and fail to achieve labour market insertion. As for the likelihood of full integration into adult life, there is no doubt that the longer the period of disaffiliation from the principal institutions that shape the passage to adulthood (education and work), the greater the danger of social exclusion. As discussed in the foregoing analysis of the figures on emancipation paths, men and women face different situations and risks merely because many poor young women have no attractive, believable and accessible options for joining society other than motherhood and confinement to the domestic world.8 8 The number of categories of institutional affiliation/disaffiliation can expand to differentiate between risky and precarious affiliation. In the case of education, for example, this would make it possible to identify the relative weight of young people with significant lags. And for the labour market, it would be possible to differentiate between formal and informal workers and between those who are looking for work and those who are not. Fluid changes in employment status are one of the most salient characteristics of youth. 62 Economic Commission for Latin America and the Caribbean (ECLAC) Table I.6 LATIN AMERICA (SEVEN COUNTRIES): POPULATION AGED 15-29 NEITHER STUDYING NOR WORKING BY AGE GROUP, INCOME QUINTILE AND COUNTRY GROUPING, AROUND 2006 (Percentages) First country grouping (Argentina, Chile and Uruguay) Male Female 15-19 years 20-24 years 25-29 years 15-29 years 15-19 years 20-24 years 25-29 years 15-29 years First quintile 23.5 34.7 22.5 26.2 30.8 59.5 64.2 47.6 Fifth quintile 6.3 5.6 3.7 5.0 5.8 8.5 10.0 8.3 Second country grouping (El Salvador, Guatemala, Honduras and Nicaragua) First quintile 10.0 13.4 12.5 11.6 56.1 77.3 73.6 67.2 Fifth quintile 6.5 8.2 7.0 7.3 15.0 24.7 25.3 21.7 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries. The data on the relative weight of the group of young people who neither study nor work are a danger sign for the risk of marginalization and social exclusion in any society. Table I.6 provides a simplified view of the relative weight of this population category among adolescents and young people from households at opposite extremes of the income distribution. As with the figures analysed above, only two groups of countries are considered, classified on the basis of where they are in the demographic transition and the extent of educational coverage of the population. Reading the data in the table leads to some broad conclusions. First, disaffiliation from the principal public institutions is more frequent among women than among men and for lower-income young people than for their peers at the other extreme of the distribution. Moreover, the percentage of institutional disaffiliation among poor men in the group of countries at a later stage in the demographic transition (first group) is twice to three times the percentage for young men in the lower strata in the second country group. These data might be the combined result of at least three trends. First, the relative development of countries is associated with less willingness on the part of young people to accept low-paying, unstable jobs with little or no protection. A second trend that could be contributing to the social disaffiliation of young men in the second country group is the rapid overall raising of the qualification thresholds for accessing good jobs. And a third trend, already reflected in figures I.12 and I.13, is that even with low participation rates for women in the first quintile, these rates are higher in the more developed countries than in the less developed countries of the region. A larger number of women in the market means they are competing with men for access to low-skill jobs; this could be undercutting job opportunities for men. Lastly, in the less developed countries of the region, young women in the higher strata who neither study nor work but surely perform traditional domestic tasks still outnumber their peers in more developed countries by more than three to one. C. Subjective well-being, living conditions and life cycle: Latin America and other regions of the world National life satisfaction averages in the countries of Latin America are far higher than what would be expected on the basis of per capita GDP, and the gaps in subjective well-being associated with monetary income are narrower than would be expected in view of the distributive inequality in the region. In Latin America, life dissatisfaction is more likely among persons aged 60 and older in the worst socio-economic situation, among 17-to-29-year-olds with children and among persons without a stable partner. Policies should thus take into consideration the difficulties associated with ageing without the necessary economic resources, as well as the problems arising from taking on the roles of provider and child caregiver early in conditions of greater vulnerability. Social Panorama of Latin America • 2010 Previous sections of this chapter have shown that Latin America is increasingly in need of moving towards a broader view of poverty and well-being that both incorporates and goes beyond the monetary dimension. The reasoning behind incorporating the subjective dimension in an assessment of well-being is a matter of general discussion. The answer lies in conceptual and normative reflection and in examining the empirical behaviour of the subjective indicators. This brings relevance to empirical studies analysing how expressions of subjective well-being are linked to objective living conditions in Latin America.9 In Latin America, unlike in developed countries, there have been few studies of the relationship between living condition indicators and subjective measurements of wellbeing.10 From the empirical antecedents available, Diener (2000) and Inglehart and others (2008) found that, compared with other regions, average life satisfaction in the countries of Latin America was higher than to be expected on the basis of degree of wealth. But these conclusions were drawn 1. 63 from a limited number of countries and observations over time.11 Nor have there been systematic studies on the region linking subjective well-being to indicators of an individual’s life-cycle position and associated tasks, or comparing this relationship with observations elsewhere in the world. This section therefore looks at the relationship between life satisfaction and income indicators (GDP per capita and household income, in this case), comparing Latin America and other regions cross-sectionally and over time. This analysis seeks to confirm, on the basis of the largest possible number of countries and observations, whether subjective well-being in Latin America is higher than would be expected on the basis of GDP per capita. It also examines the relationship between subjective wellbeing and indicators for the position and responsibilities of men and women in different stages of the life cycle (age, civil status and number of children), controlling for household monetary income and comparing the findings with other regions of the world. Empirical antecedents Researchers who first analysed subjective well-being focused on identifying external conditions (like income per capita) that could lead to more satisfactory lives. One of the most influential studies was conducted by Easterlin (1973, 1974), who observed that countries with the largest increments in GDP had stable levels of subjective well-being over time. These findings were corroborated by other research. For example, Frey and Stutzer (2002) noted that gains in subjective well-being level off once GDP per capita tops US$ 10,000, and Diener and Biswas-Diener (2002) found that the correlation between income and subjective well-being is far smaller in more developed countries. Diener and Suh (1999) observed a correlation of 0.62 between mean purchasing power12 and life satisfaction in the countries under review. But they did note outliers like Japan (high income and low subjective well-being) and poor countries whose population did not report extremely low satisfaction levels. The past few years have yielded evidence of a stronger relationship between income and subjective well-being at the country level. Boarini, Johansson and Mira d’Ercole (2007) note that the tendency for satisfaction to level off at high levels of GDP is less clear when considering Organization for Economic Cooperation and Development countries only, and that how these factors are linked depends on the countries evaluated and the measure of income used. Stevenson and Wolfers (2008) and Inglehart and others (2008) propose that there was an increase in subjective well-being in many countries associated with an increment in income. But Diener and others (2010) suggest that research outcomes vary and conclusions are based on uncertain statistics; Easterlin (2005) stresses that many countries saw increases in income without rising subjective well-being and that these disparate trends indicate that factors other than income influence life satisfaction. According to Stevenson and Wolfers (2008), the more 9 11 See the most recent editions of Social Panorama of Latin America (ECLAC, 2007, 2008a and 2009) and ECLAC (2010d). 10 This interest in the relationship between objective and subjective well-being is a long-standing one in the developed world. The first systematic studies of life satisfaction began in the 1950s (Keyes, Ryff and Shmotkin, 2002). Diener (2000) is based on data for Argentina, Brazil and Chile; Inglehart and others (2008) analyse evidence from 12 countries of Latin America and 2 countries in the Caribbean (4 of them with a single observation). 12 Refers to the ability to purchase a standard basket of goods that an average person in each country can afford on his or her annual income, expressed as a percentage of the mean purchasing power of individuals in the United States. Indicator constructed on the basis of information provided by the World Bank. 64 Economic Commission for Latin America and the Caribbean (ECLAC) time series and countries become available the stronger the evidence is that happiness increases along with GDP. The pattern is similar for the relationship between income and life satisfaction at the individual level: income has a positive but varying impact, and there are striking differences in how individuals turn income into well-being. In the slums of Calcutta, the ratio between income and life satisfaction was 0.45 (Diener, Oishi and Lucas, 2003). On the other hand, most studies in Europe show a positive but weak relationship between income and satisfaction (Dolan, Peasgood and White, 2008). In the United Kingdom of Great Britain and Northern Ireland, Shields and Price (2005) observed that 1% of the variance in subjective wellbeing was explained by income. Moreover, longitudinal studies show that changes in income are not followed by equivalent changes in subjective well-being and that different individuals do not transform income into well-being in the same way (Clark and others, 2005).13 2. Life satisfaction and income indicators Figure I.14 sets out the results of a study linking national average life satisfaction and GDP per capita in countries of Latin America and the Caribbean and in other regions for the period 1981-2008. For most of the countries and years, both for Latin America and the Caribbean and for the rest of the countries, life satisfaction data are from the World Values Survey (WVS). To have more cases, the series for Latin America was completed with data from the 2007 round of the Latinobarómetro survey for 10 countries of the region. The logarithm of GDP was used instead of GDP in United States dollars because changes in subjective wellbeing will be associated more with relative variations in living conditions (Kahneman and Deaton, 2010).14 The results set out in figure I.14 indicate that, worldwide, life satisfaction is correlated to GDP per capita. National life satisfaction averages rise significantly as 13 The research identified variables other than income that are associated with subjective well-being. Notable among these are employment status, education and physical health, as well as factors showing the subjects’ position in the life cycle. Among these are age, civil status and responsibilities in caring for other household members (Dolan, Peasgood and White, 2008). Concerning age, studies in developed countries have found a U curve where the highest levels of subjective well-being are among the youngest and oldest age groups and the lowest levels are in the intermediate age groups (Dolan, Peasgood and White, 2008; Shields and Price, 2005). As for civil status, being married is associated with the highest level of subjective well-being and being separated with the lowest level (Helliwell, 2003; Shields and Price, 2005). The time spent on activities related to the economy of care is associated with lower levels of happiness and more symptoms of depression (Dolan, Peasgood and White, 2008). This study was based on three rounds of the European Community Household Panel (1994 to 1996) on the basis of a sample of 109,425 cases (36,475 subjects for each round in 12 countries). 14 Logarithmic transformation can represent a regular quantitative perception of physical stimuli. It has an experimental basis known as Weber’s law. The rule is that the effective stimulus for perceiving and evaluating changes in the environment is proportional (not absolute) change. A US$ 100 wage hike would therefore not have the same significance for a company manager as for someone earning the minimum wage, but doubling the wages of both individuals should have a similar perceived impact for both subjects (Kahneman and Deaton, 2010). The problem is that individuals can evaluate the same stimulus on the basis of differential thresholds in different sociocultural contexts. GDP per capita increases (measured in logarithms).15 The national life satisfaction averages for the countries of Latin America seem to be far higher than their GDP per capita, not only because they exceed the scores in countries of Eastern Europe and Asia but also because they are comparable with national averages in the countries of Western Europe, North America and Oceania. One way to determine with greater certainty whether Latin Americans are more satisfied with life than their GDP per capita would suggest is to analyse the residuals of an ordinary least squares regression model with the subjective well-being indicator as the dependent variable and GDP per capita as the independent variable, where the residuals are equivalent to the distance between the value predicted by the equation and the observed value. The results of this analysis are set out in figure I.15, which shows that Latin America and the Caribbean have the highest average positive residuals (average of 0.92). This means that the countries of the region have satisfaction levels that are higher than would be expected on the basis of GDP per capita.16 The exact opposite is found in Eastern Europe (average of -0.96). The differences between Latin America and the Caribbean and the other regions, particularly Eastern Europe, are statistically significant. 15 16 P = 0.000*** (statistically significant difference at the 99.99% level). The average residuals for Latin America and the Caribbean without the Latinobarómetro data are slightly lower, suggesting that part of the deviation for Latin America could be due to the small number of observations. Social Panorama of Latin America • 2010 65 Figure I.14 LATIN AMERICA AND THE CARIBBEAN (20 COUNTRIES) AND OTHER REGIONS: LIFE SATISFACTION BY PER CAPITA GDP, 1981-2008 a Figure I.15 LATIN AMERICA AND THE CARIBBEAN (20 COUNTRIES) AND OTHER REGIONS: ORDINARY LEAST SQUARES REGRESSION RESIDUALS FOR LIFE SATISFACTION AND PER CAPITA GDP, 1981-2008 a (Standard deviation units) 10 1.5 7 1.0 6 0.5 5 4 2 2.0 2.5 2.0 3.5 4.0 4.5 5.0 Logarithm of per capita GDP b Western Europe, North America and Oceania Eastern Europe Asia Africa Latin America and the Caribbean Source: conomic Commission for Latin America and the Caribbean (ECLAC), E on the basis of special tabulations of data from the World Values Survey database, 1981-2008; the Latinobarómetro survey for 2007; World Bank, World Development Indicators [online] http://data.worldbank.org/indicator; information on per capita GDP of the relevant countries, 1981-2008. a Average values on a life satisfaction scale from 1 to 10 where 1 is very unsatisfied and 10 is very satisfied. Western Europe, Noth America and Oceania: Andorra, Australia, Canada, Cyprus, Finland, Germany, Italy, Netherlands, New Zealand, Norway, Spain, Sweden, Switzerland, United Kingdom and United States. Eastern Europe: Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Montenegro, Poland, Republic of Moldova, Romania, Russian Federation, Serbia, Slovakia, Slovenia, the former Yugoslav Republic of Macedonia and Ukraine. Asia: Armenia, Azerbaijan, Bangladesh, China, Georgia, Hong Kong Special Administrative Region of China, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kyrgyzstan, Malaysia, Pakistan, Philippines, Republic of Korea, Saudi Arabia, Singapore, Thailand, Turkey and Viet Nam. Africa: Algeria, Burkina Faso, Egypt, Ethiopia, Ghana, Mali, Morocco, Nigeria, Rwanda, South Africa, Uganda, United Republic of Tanzania, Zambia and Zimbabwe. Latin America and the Caribbean: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Trinidad and Tobago and Uruguay. The Latinobarómetro data were used to estimate life satisfaction in 2007 in the following countries: Bolivarian Republic of Venezuela, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Nicaragua, Panama, Paraguay and Plurinational State of Bolivia. The question used by Latinobarómetro is not 100% comparable with the WVS question because the Latinobarómetro survey used a scale from 1 to 10 and the WVS has been using a scale from 1 to 10 since 1981. Accordingly, the Latinobarómetro scores were corrected by increasing the national average by one point. Log (10) values: 2.5 = US$ 314 per capita; 3 = US$ 1,023 per capita; 3.5 = US$ 3,157 per capita; 4 = US$ 9,913 per capita; 4.5 = US$ 32,040 per capita. The analysis in figures I.14 and I.15 associates life satisfaction and GDP per capita in a cross-sectional fashion and cannot be used to examine the relationship between changes in GDP and variations in satisfaction levels or to compare trends across regions. This latter analysis is set out in figure I.16, which shows that changes in GDP per capita are significantly associated with changes in national satisfaction averages.17 In this case, the percentage of variance explained is smaller than in the cross-sectional analysis. However, a smaller number of observations was available for the change analysis. 17 0.92 0.12 0.0 Adjusted R-squared=0.20; standardized beta coefficient=0.457; p=0.000*** (significant at the 99.9% level). -0.05 -0.5 -0.96 -1.0 -1.5 Latin America and the Caribbean Western Europe, North America and Oceania Eastern Europe Asia Source: conomic Commission for Latin America and the Caribbean (ECLAC), E on the basis of special tabulations of data from the World Values Survey database, 1981-2008; the Latinobarómetro survey for 2007; World Bank, World Development Indicators [online] http://data.worldbank.org/indicator; information on per capita GDP of the relevant countries, 1981-2008. a Average difference between expected and observed values. Significance of differences between Latin America and the Caribbean and the other regions: p Eastern Europe = 0.000***; p Asia = 0.000***; p Western Europe, North America and Oceania = 0.001**. From post-hoc Scheffe comparisons. Figure I.16 LATIN AMERICA AND THE CARIBBEAN (nine COUNTRIES) AND OTHER REGIONS: CHANGES IN LIFE SATISFACTION AND GDP PER CAPITA, 1981-2008 a (Percentages) 40 Relative change in satisfaction Life satisfaction 8 20 0 -20 -40 -50 0 50 100 150 200 250 Relative change in GDP Western Europe, North America and Oceania Eastern Europe Asia Latin America and the Caribbean Source: conomic Commission for Latin America and the Caribbean (ECLAC), E on the basis of special tabulations of data from the World Values Survey database, 1981-2008; the Latinobarómetro survey for 2007; World Bank, World Development Indicators [online] http://data.worldbank.org/indicator; information on per capita GDP of the relevant countries, 1981-2008. a Latin America and the Caribbean: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Mexico, Peru, Puerto Rico and Uruguay. Western Europe, North America and Oceania: Australia, Canada, Finland, Germany, New Zealand, Norway, Spain, Sweden, Switzerland, United Kingdom and United States. Eastern Europe: Albania, Belarus, Bosnia and Herzegovina, Czech Republic, Hungary, Montenegro, Poland, Republic of Moldova, Romania, Russian Federation, Serbia, Slovakia, Slovenia, the former Yugoslav Republic of Macedonia and Ukraine. Asia: Bangladesh, China, India, Indonesia, Iran (Islamic Republic of), Japan, Jordan, Philippines, Republic of Korea, Turkey and Viet Nam. 66 Economic Commission for Latin America and the Caribbean (ECLAC) The greatest coincidence of the direction of change for GDP per capita and for life satisfaction is in Eastern Europe. The smallest coincidence is in Western Europe, North America and Oceania, where the greater number of observations show a rising GDP and a small decline in satisfaction. In Latin America and the Caribbean, several points on figure I.16 show a convergence between the direction of changes in GDP and in life satisfaction. But there are counter-intuitive situations, such as satisfaction rising when per capita GDP is falling, or increases in GDP while life satisfaction is declining. Measuring relative household monetary income also reveals these regional differences in behaviour of the subjective well-being indicator over time. This has the additional advantage of showing the evolution of differences in satisfaction among monetary income groups, taking into consideration recent historical events in the countries and regions (such as economic or political crises). Figure I.17 shows that over the past two decades life satisfaction levels in Latin America have been higher and more stable than in Asia and Eastern Europe and that the satisfaction gaps between lower and higher monetary income groups are less marked than in the other regions. The fact that income differences have such a slight influence on life satisfaction brings into question the impact of objective inequality on subjective well-being in the countries of Latin America.18 Figure I.17 LATIN AMERICA (FIVE COUNTRIES), EASTERN EUROPE AND ASIA: LIFE SATISFACTION IN HIGH- AND LOW-INCOME GROUPS, 1990-2008 a (1 = very unsatisfied; 10 = very satisfied) 9 8 7.8 7.4 8.4 7.4 7.7 6.8 7 6.1 7.9 7.2 8.5 8.3 7.6 8.5 7.9 9 8.4 8.6 8.2 8 7.1 6.9 6.4 6.7 6.1 6 6 7.5 7.2 7.7 7.8 8 6.9 7 6.4 5 4 5.6 5.1 5.3 4 6.2 5.4 5.2 7.9 7.4 6.6 6 5 7.9 7.6 6 5.1 4.9 4.5 3.5 3.5 3 3 3 7.3 3.9 3.2 3.4 2 2 1990 1990 1996 2000 2005 1990 1996 2000 2005 1997 2005 1996 2001 2008 1996 2006 Chile Mexico Colombia Peru Uruguay 1995 2006 1989 1997 Russian Federation Poland 2005 1996 2002 2006 Republic of Moldova 1996 2006 Ukraine 9 8 7 7.5 7.1 7.9 5.6 4.9 7.5 7.3 7 6 5 7.9 5.7 6.1 6 5.8 7.1 6.9 6.8 6 6 7 6.1 7.4 6.5 5.4 7.4 7.1 7.2 6.1 5.2 5.3 4.7 4 3 2 1990 1995 2001 2007 1990 1995 2001 2006 1990 1995 2000 2005 1990 2001 2005 China India Japan Low-income Republic of Korea High-income Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from the World Values Survey database,1981-2008. a The measure of income is based on self-reported income classified in 10 steps or groups, arranged from lowest to highest relative income. The classification, from the World Values Survey, defines income brackets as appropriate for the realities of each country. For reasons of sample size, this exercise used a recoding of the income groups originally defined in the World Values Survey. Steps 1 and 2 in each country refer to the low-income group, while steps 5-10 refer to the high-income groups of the population. 18 After all, Latin America and the Caribbean is among the regions of the world with the highest distributive inequality, and perceptions of distributive injustice are widespread in the region (ECLAC, 2010d). Social Panorama of Latin America • 2010 67 One possible interpretation is that in Latin America inequality is so firmly rooted in the population that it has lost relevance for subjective well-being, while in Eastern Europe the depth of change (not only in the economy but in life in general) since the fall of the Berlin wall might have triggered so many new stimuli that the population would have needed to draw on significant psychological and other resources to deal with the changes.19 In other words, the happiness system would be more a reflection of changing circumstances than of their desirability (see box I.6). Another possible interpretation is that drastic changes in the environment can significantly alter expectations. In Eastern Europe, then, expectations for greater well-being after the fall of the Berlin wall could have been generally low. But the collapse of the old order and the opening of a window on developed-country levels of consumption might have brightened expectations that subsequently went unfulfilled because of the crisis that hit Eastern Europe in the mid-1990s. A comparable case in Latin America would be Chile, where high life satisfaction among lowand high-income groups in 1990 could have been linked to the advent of democracy. But it would seem that the expectations of lower-income groups were not fully met, as figure I.17 shows.20 Box I.6 MEASURING SATISFACTION AND HAPPINESS The field of hedonic psychology seeks valid and reliable approaches to the concept of utility that indicate how individuals rate life experiences as pleasant. The most frequently used measures of subjective well-being are obtained from population surveys, where the interviewees answer general retrospective questions on wellbeing (life satisfaction or happiness). These reports tend to tie in with other measures of subjective well-being, which suggests a certain degree of validity (Diener and Tov, 2005). But such measures have been challenged, based mainly on issues of interpersonal comparability. 1. Adaptation Adaptation is the adjustment of the intensity of response to stimuli repeated over time. This objection is among those most frequently mentioned in the nonpsychological literature (see, for example, Sen, 1985). The problem is that if people adapt to their circumstances and adjust their expectations, individuals living in very different conditions will score equally high for subjective well-being. Brickman and Campbell (1971) proposed that human beings are trapped on a “hedonic treadmill”, meaning that they can do little to change their levels of satisfaction over time because adaptation is inevitable and no single circumstance could lead to lasting changes in satisfaction. Individuals would therefore revert to a neutral position after any significant emotional event (Diener and Tov, 2005). The hedonic treadmill theory is based on a model in which psychological systems 19 react automatically to deviations from their adaptation level. In these processes, a repeated stimulus loses relevance and this frees up resources for reacting to new stimuli. So, the “happiness system” would be more a reflection of changes in circumstances than of their desirability. Brickman, Coates and Janoff-Bulman (1978) provided early empirical support for the hedonic treadmill model when they concluded that lottery winners were no happier than losers and that paraplegics were not substantially unhappier than people who can walk. However, the following observations have been made over the past few years: (a) there is no neutral set-point (people are happy most of the time); (b) set-points vary between individuals and dimensions of well-being; (c) happiness changes over time; and (d) adaptation is not universal —there are types of pleasure and pain to which individuals do not adapt (Diener, Lucas and Scollon, 2006; Kahneman and Sugden, 2005). 2. The failures of affective forecasting An individual’s predictions of experienced utility are subject to systematic error because people do not consider how hedonic adaptation to new circumstances will influence future levels of well-being. Moreover, individuals tend to exaggerate the importance of their current focus of attention. Hence, although human beings are trapped on a hedonic treadmill they believe that they are improving their well-being. The systematic failure of affective forecasting lies in the fact that people incorrectly predict future happiness (Kahneman and Sugden, 2005). In sociological terms, this equates to a more general interpretation of psychological malaise informed by Durkeim’s anomie and not by Marx’s theory of alienation. For an explanation of the differences between these two approaches, see ECLAC (2008a). 20 3. Memory bias M e m o r i e s a r e i n f l u e n c e d by expectations and mood; in some cases individuals block out some experiences and exaggerate others. Such bias is especially present in reports based on general retrospective evaluations (example: how satisfied are you with your life as a whole) in which the subjects average the well-being they obtain from certain activities or domains. By contrast, when subjects report on their mood immediately (online), few memory biases are operating because the individual is reporting emotions and cognitions right then. Indicators based on general retrospective questions are modestly reliable for estimating an individual’s current well-being (Diener and Tov, 2005; Kahneman and Sugden, 2005). 4. Social comparison Self-ratings of well-being are based more on the relative status of individuals than on any absolute level of consumption or well-being. Wood (1996) holds that social comparison is a thought process based on the observation of similarities and differences with other individuals and that the focus of comparison is not determined on the sole basis of proximity or accessibility of other relevant factors. It was initially proposed that an individual should be happy if relevant others are worse off, and unhappy if relevant others are better off (Diener and Fujita, 1997). According to Brown and Dutton (1995), individuals compare themselves with others when they think that the comparison will make them This could be an affective forecasting issue because Chile systematically improved its objective living conditions indicators between 1990 and 2006. 68 Economic Commission for Latin America and the Caribbean (ECLAC) Box I.6 (concluded) feel good and avoid comparisons when they believe comparisons will make them feel bad. Lyubomirsky and Ross (1997) observe that happy individuals tend to compare themselves down and unhappy individuals tend to compare themselves both up and down. differences in subjective well-being might not be due to living conditions but rather to individual predisposition. In any event, while personality explains part of subjective well-being, living conditions are also an influence (Schmutte and Ryff, 1997; Dolan, Peasgood and White, 2008). 5. Personality factors 6. Cultural differences There is evidence that personality is a powerful predictor of subjective well-being (Diener and others, 1999). Costa and McCrae (1980) found links between extraversion and positive affect and between neuroticism and negative affect. This was confirmed by subsequent studies and explained by the joint operation of genetic, biological, psychological and social mechanisms (Diener and others, 1999). The problem is that because of their correlation with personality traits, measures of well-being could reflect individual differences beyond the reach of policies. Moreover, the observed Culture shapes the world vision and affects how individuals evaluate their circumstances and life experiences. These differences may be expressed in differing concepts of happiness or satisfaction, in the use of different kinds of information and even in different forms of self-conceptualization associated with specific cultural norms. For example, while internal emotional experience (the balance between positive and negative affect) predicts life satisfaction in individualistic cultures (Sweden or the United States of America), in more collectivistic societies like China or India life satisfaction is associated more with social norms (Suh, Diener and Updegraff, 2008). 7. Issues with operationalization and measurement Questions about life satisfaction are ordinal and have upper and lower limits. A life satisfaction score of 6 on a scale of 1 to 10 does not mean that the individual is twice as satisfied as another individual with a score of 3. For this reason it has been recommended that ordinal regressions be used instead of ordinary least squares procedures, even though recent research showed that this had little effect on findings (Clark and others, 2005). Other problems have to do with the order of questions (some items can stress some aspects of life over others) and the differential use of scales (some individuals may tend to use the extreme numbers while others may prefer the intermediate numbers) (Diener and Tov, 2005). Source: Economic Comission for Latin America and the Caribbean (ECLAC). In any event, the reasons why Latin America is a subjective well-being outlier should be researched more thoroughly. Some hypotheses concern the effect of cultural factors such as religion (Inglehart and others, 2008) and the high levels of social support and social closure that characterize Latin American societies (Diener and Tov, 2005). It has also been suggested that the consolidation of democracy in the countries of the region increased perceived freedom and led to a rise in subjective well-being in Latin America (Inglehart and others, 2008).21 There are methodological issues as well, such the effect of cultural differences on self-evaluations of wellbeing and how people respond to surveys. One possibility is that in Latin America life satisfaction, as one of the cognitive components of subjective well-being, is more strongly correlated to the emotional aspects of well-being (like happiness) than in other regions and is less correlated to income.22 However, the available data point in exactly the opposite direction (see table I.7). Table I.7 LATIN AMERICA AND THE CARIBBEAN (11 COUNTRIES) AND OTHER REGIONS: CORRELATION BETWEEN LIFE SATISFACTION AND HAPPINESS, 1981-2008 Latin America and the Caribbean a Correlation ratio Sample size Eastern Europe b Continental Europe c Anglo-Saxon countries d Nordic countries e 0.359 0.488 0.554 0.520 0.519 39 980 31 341 9 841 12 831 8 115 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from the World Values Survey 1981-2008. a Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Dominican Republic, El Salvador, Guatemala, Mexico, Peru and Uruguay. b Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Czech Republic, Hungary, Poland, Republic of Moldova, Romania, Russian Federation and Ukraine. c France, Germany, Netherlands and Switzerland. d Australia, New Zealand, United Kingdom and United States. e Finland, Norway and Sweden. 21 The consolidation of democracy is framed by a theory of cultural change tied to modernization. 22 For further details on the dimensions of subjective well-being and their relationship to measures of monetary income, see Diener, Kahneman and Heliwell (2010) and Kahneman and Deaton (2010). Social Panorama of Latin America • 2010 3. Satisfaction and life cycle This section looks at the relationship between subjective well-being and indicators for the position of men and women in the life cycle (age, civil status, number of children), comparing Latin America with other regions according to the welfare regimes they have in place. For the developed countries, the typology proposed by Esping-Andersen (1990) is used, distinguishing between liberal, conservative and social democratic regimes.23 Latin America and Eastern Europe were analysed as separate groups, with two elements in common: neither region is, strictly speaking, a “mature” welfare regime, and both are developing regions.24 The first phase of the analysis identified how life-cycle factors affect life satisfaction and compared the findings by region and welfare regime. A more exhaustive analysis followed, including the life-cycle factors most associated with life satisfaction in the first stage. This second analysis sought to identify interactions between life-cycle factors and living conditions because, for example, the effects of age on life satisfaction might not be the same at different levels of monetary income. To ensure sufficient sample sizes, all of the World Values Survey rounds available for the selected countries between 1981 and 2008 were used, although most of the cases are in the 1990-2008 segment.25 From the first phase of the analysis, perhaps the most interesting finding from a life-cycle viewpoint is the association between age and subjective well-being. The U-shaped pattern described in the literature (showing higher levels of satisfaction at younger ages and in older adults) is seen in the Nordic countries and does not strictly hold for continental Europe or the Anglo-Saxon countries, because the youngest are less likely to be satisfied than older persons are. The U pattern does not hold in Eastern Europe either, because young people there are significantly more likely to be satisfied than are older persons. No age effect is seen in Latin America (see table I.A-1 in the appendix). 23 69 These correspond to the Anglo-Saxon countries, the countries of continental Europe and the Nordic countries, respectively. The classification is based on criteria such as the degrees of commodification (dependence or not on market income to maintain an acceptable standard of living) and defamiliarization (emancipation of women from work related to the economy of care in the household) in the countries. 24 Regardless of any specific welfare configurations in the countries of Latin America and Eastern Europe. 25 Respectively, 93.1% in Latin America; 90.5% in the liberal AngloSaxon countries; 86% in the countries of continental Europe; 87.7% in the Nordic countries; 92.7% in Eastern Europe. Although the U-shaped pattern does not strictly apply for most of the regions, in almost all of the groups of countries analysed (except for Latin America) the likelihood of satisfaction declines in the intermediate age groups (30-44 and 45-59). This is regardless of the welfare regime in place and could be a reflection of the tensions and burdens that characterize this stage in life, when intermediate-age adults must be providers as well as care for dependants in the household. As for the association between gender and life satisfaction, the regression analysis shows no significant relationship in Latin America or Eastern Europe, while there is one in the more developed countries regardless of the specific welfare regime in place. In the Nordic countries and the Anglo-Saxon countries and in continental Europe, the likelihood of life satisfaction is significantly lower among men than among women (see table I.A-1 in the appendix). This could be an expression of malaise in societies that have undergone major changes in gender role models, with growing levels of autonomy for women. Being married, being in a shared living arrangement or having a partner significantly increase the likelihood of being satisfied with life compared with being single, separated, divorced or widowed, both in Latin America and the rest of the regions. Not having children reduces the likelihood of life satisfaction in the Nordic countries and in continental Europe, but —unexpectedly— this does not have the same effect in Latin America. What has been presented up to now is the outcome for the principal effects. From here on the focus will be on the relationship between subjective well-being and life-cycle indicators —this time to research interactions. First comes an examination of the relationship between age and subjective well-being, controlling for household monetary income. Then the focus will shift to the association between life satisfaction and such factors as civil status, number of children and age. For the latter, the universe is limited to the working-age population (age 17-59). Figure I.18 shows that the age effect differs among monetary income brackets in all of the country groups. Strictly speaking, in the more developed countries the U-shaped pattern is found only among individuals living in the lowest-income households, while in Latin America the life-satisfaction gap linked to income bracket is wider among individuals aged 60 or older. In Eastern Europe, life-satisfaction levels fall off consistently after age 30-44. 70 Economic Commission for Latin America and the Caribbean (ECLAC) Figure I.18 LATIN AMERICA (11 COUNTRIES) AND OTHER REGIONS: LIFE SATISFACTION BY AGE AND MONETARY INCOME, 1981-2008 a (1 = very unsatisfied; 10 = very satisfied) Latin America b 8.0 Nordic countries c 8.5 7.9 7.8 7.8 7.7 7.6 7.6 7.5 7.9 7.8 7.4 7.4 7.6 7.9 7.5 7.3 7.0 7.3 6.7 6.5 6.6 7.1 7.0 6.0 Aged 17-29 Aged 30-44 Aged 45-59 Aged 60 and older Aged 17-29 Aged 30-44 Aged 45-59 Aged 60 and older Anglo-Saxon countries e Eastern Europe d 6.5 8.5 6.2 8.2 8.0 5.8 5.5 5.7 5.6 5.5 5.0 7.2 5.1 4.9 7.0 4.8 7.8 7.7 7.7 7.5 5.0 4.5 7.9 7.5 7.3 7.1 6.0 8.1 8.1 7.8 7.5 7.3 7.3 8.1 7.6 7.4 7.2 8.0 7.8 7.8 7.7 7.0 7.1 6.9 6.7 4.0 4.2 4.1 6.5 4.0 3.5 6.5 6.0 Aged 17-29 Aged 30-44 Aged 45-59 Aged 17-29 Aged 60 and older Aged 30-44 Aged 45-59 Aged 60 and older Continental Europe f 8.0 7.8 7.8 7.6 7.6 7.6 7.8 7.7 7.4 7.2 7.4 7.5 7.4 7.3 7.1 7.0 6.8 6.9 6.6 6.6 6.4 6.2 6.0 Aged 17-29 Lowest income group Aged 30-44 Aged 45-59 Middle group Aged 60 and older Highest income group Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from the World Values Survey database,1981-2008. a Interaction income/age; Latin America p=0.027*; Eastern Europe, p=0.003**; Nordic countries, p=0.000***; continental Europe, p=0.000***; Anglo-Saxon countries, p=0.000***. b Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Dominican Republic, El Salvador, Guatemala, Mexico, Peru and Uruguay. c Finland, Norway and Sweden. d Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Czech Republic, Hungary, Poland, Republic of Moldova, Romania, Russian Federation and Ukraine. e Australia, New Zealand, United Kingdom and United States. f France, Germany, Netherlands and Switzerland. The data for Eastern Europe and Latin America bring into question the idea of hedonic adaptation of expectations among the population aged 60 and older. It is not the same thing to age without financial worries (either because of self-funded pensions or thanks to a more or less generous welfare state) than to do so in a precarious economic situation without social protections. Projections for the developing countries based on the trends observed in developed countries suggest a medium-term scenario for Latin America in which the relationship between life satisfaction, age and income could approach the pattern seen in the more affluent societies. Social Panorama of Latin America • 2010 71 As seen in figure I.19, in Latin America being married or in a shared living arrangement or having a partner is associated with higher levels of life satisfaction regardless of number of children or age. Such is not the case in the other regions, where the correlation between having (or planning to have) a family and life satisfaction always occurs in interaction with such other factors as number of children and age. At the same time, in Latin America there is an interaction effect between age and number of children: childless 17-to-29-year-olds report the highest levels of life satisfaction. The lowest life satisfaction levels are seen in the same age group with one or more children. A similar situation is observed in Eastern Europe and in the Anglo-Saxon countries. Figure I.19 LATIN AMERICA (11 COUNTRIES) AND OTHER REGIONS: LIFE SATISFACTION BY MARITAL STATUS AND NUMBER OF CHILDREN IN POPULATION AGED 17-59, 1981-2008 (1 = very unsatisfied and 10 is very satisfied) Latin America a Continental Europe b 8.2 8.0 8.0 8.0 7.8 7.8 7.5 7.6 7.5 7.5 7.1 7.2 6.9 7.0 7.2 7.2 7.1 7.0 6.8 7.1 6.7 6.6 6.4 6.8 0 children 1 or more Married, shared living arrangement, partner 0 children 0 children 1 or more Separated, widowed, single, never married 1 or more Married, shared living arrangement, partner Eastern Europe c 8.5 6.2 5.3 8.1 8.1 7.9 5.6 5.0 5.0 Separated, widowed, single, never married 7.5 7.5 7.3 5.0 7.2 7.1 7.1 4.6 4.5 8.0 7.7 7.7 5.2 1 or more 8.3 8.3 6.0 6.0 0 children Nordic countries d 6.5 5.5 7.7 7.4 7.5 7.5 7.4 7.7 7.7 7.6 7.8 7.0 6.9 6.7 6.5 4.0 0 children 1 or more Married, shared living arrangement, partner 0 children 1 or more 0 children Separated, widowed, single, never married 1 or more Married, shared living arrangement, partner 0 children 1 or more Separated, widowed, single, never married Anglo-Saxon countries e 8.0 7.8 7.6 7.9 7.7 7.7 7.8 7.4 7.4 7.2 6.9 7.0 6.9 6.7 6.8 6.6 6.4 0 children 1 or more Married, shared living arrangement, partner Aged 17-29 0 children 1 or more Separated, widowed, single, never married Aged 30-59 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from the World Values Survey database,1981-2008. a Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Dominican Republic, El Salvador, Guatemala, Mexico, Peru and Uruguay; interaction age*children (p=0.000***), principal effect of marriage (p=0.000***). b France, Germany, Netherlands and Switzerland; interaction marriage*children (p=0.000***), principal effect of age (p=0.006**). c Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Czech Republic, Hungary, Poland, Republic of Moldova, Romania, Russian Federation and Ukraine; interaction marriage*children (p=0.000***) and age*children (p=0.000***). d Finland, Norway and Sweden; interaction marriage*children (p=0.001**), principal effect of age (p=0.000*). e Australia, New Zealand, United Kingdom and United States; interaction age*marriage (p=0.004**), marriage*children (p=0.002**) and age*children (p=0.004**). 72 Life-cycle variables, then, influence subjective wellbeing in Latin America and other regions. How these factors are associated seems to have more to do with the degree of development at the county level than with the welfare regime in place. Strictly speaking, the greater responsibilities and tasks linked to intermediate ages in the life cycle do not always lead to lower life satisfaction; the likelihood of this happening increases when material living conditions are more precarious. The fact that in Latin America the life satisfaction gap linked to income bracket widens in the population aged 60 and older shows that individuals do not always adapt their expectations. As said earlier, better material living conditions make it easier to adapt. Economic Commission for Latin America and the Caribbean (ECLAC) Lastly, the family is still at the core of individual life projects in Latin America, as shown by the principal effect that being married, being in a shared living arrangement or having a partner has on subjective well-being. This effect is not seen in any of the other regions or countries included in this analysis. Also to be borne in mind is how well-being can be negatively impacted by the need to take on the role of provider and caregiver at a very early age without adequate support for shouldering these responsibilities. This is seen in the low levels of life satisfaction among 17-to-29-year-olds in Latin America with children and without a partner. Social Panorama of Latin America • 2010 73 Appendix Table I.A-1 LATIN AMERICA (18 COUNTRIES): POVERTY AND INDIGENCE INDICATORS, 1990-2009 a (Percentages) Poverty b Country Argentina c Year Households Incidence (H) Indigence Population Incidence (H) Gap (PG) Households Gap squared (FGT2) Incidence (H) Population Incidence (H) Gap (PG) Gap squared (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 2006 14.7 21.0 8.3 4.6 4.9 7.2 2.8 1.5 1.4 2009 Bolivia (Plurinational State of) 8.1 11.3 4.7 2.9 3.0 3.8 1.9 1989 e 48.9 52.6 24.5 15.0 21.9 23.0 9.7 6.1 1999 54.7 60.6 33.9 24.1 32.5 36.4 20.3 14.7 13.5 Brazil 2002 55.5 62.4 34.4 23.8 31.7 37.1 19.5 2007 47.2 54.0 27.8 18.2 27.2 31.2 14.5 9.7 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 2008 Chile 19.9 25.8 10.7 6.3 5.8 7.3 3.3 2.2 2009 19.3 24.9 10.5 6.2 5.7 7.0 3.2 2.2 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 2003 15.3 18.7 6.3 3.2 3.9 4.7 1.7 1.0 2006 11.3 13.7 4.4 2.2 2.7 3.2 1.1 0.7 2009 11.5 4.0 2.2 3.3 3.6 1.5 1.0 47.3 52.5 26.6 17.5 25.0 28.5 13.8 9.1 48.7 54.9 25.6 15.7 23.2 26.8 11.2 6.9 2002 f 48.2 54.2 26.3 16.5 17.6 19.9 8.8 5.6 2008 f 39.5 46.1 21.7 13.7 15.5 17.9 8.4 5.6 2009 f Costa Rica 9.8 1994 1999 Colombia 39.3 45.7 20.8 12.7 14.3 16.5 7.2 4.6 1990 23.6 26.3 10.7 6.5 10.0 10.1 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 2008 14.8 16.4 5.8 3.1 5.2 5.5 2.2 1.4 2009 Dominican Republic 16.8 18.9 6.9 3.9 6.4 6.9 3.0 2.0 2002 42.2 47.1 20.9 12.6 18.2 20.7 8.8 5.3 Ecuador c 2008 40.1 44.3 20.2 12.1 20.4 22.6 8.8 5.0 2009 37.8 41.1 18.5 11.0 19.8 21.0 8.0 4.5 1990 55.8 62.1 27.6 15.8 22.6 26.2 9.2 4.9 1999 58.0 63.5 30.1 18.2 27.2 31.3 11.5 6.3 2002 42.6 49.0 20.8 11.8 16.3 19.4 6.9 3.7 2008 36.5 42.7 16.6 9.0 14.8 18.0 6.1 3.2 2009 35.9 42.2 16.8 9.1 14.9 18.1 6.2 3.3 1995 47.6 54.2 24.0 14.3 18.2 21.7 9.1 5.6 1999 43.5 49.8 22.9 14.0 18.3 21.9 9.4 5.8 2001 El Salvador 42.9 48.9 22.7 14.0 18.3 22.1 9.5 5.7 2004 Guatemala 40.4 47.5 21.1 12.6 15.6 19.0 8.1 5.0 2009 41.8 47.9 19.4 10.5 14.1 17.3 5.7 2.7 11.2 1989 63.0 69.4 35.9 23.1 36.7 42.0 18.5 1998 53.5 61.1 27.3 15.4 26.1 31.6 10.7 5.1 2002 52.8 60.2 27.0 15.4 26.9 30.9 10.7 5.5 2006 46.7 54.8 25.5 15.2 22.7 29.1 11.3 5.8 74 Economic Commission for Latin America and the Caribbean (ECLAC) Table I.A-1 (concluded) Poverty b Country Honduras Households Year Incidence (H) Indigence Population Incidence (H) Gap (PG) Households Gap squared (FGT2) Incidence (H) Population Incidence (H) Gap (PG) Gap squared (FGT2) 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 Mexico 70.9 77.3 45.3 31.2 47.1 54.4 26.6 16.2 2007 63.1 68.9 39.5 27.6 39.9 45.6 23.9 15.7 1989 39.0 47.7 18.7 9.9 14.0 18.7 5.9 2.7 1998 38.0 46.9 18.4 9.4 13.2 18.5 5.3 2.2 2002 Nicaragua 31.8 39.4 13.9 6.7 9.1 12.6 3.5 1.4 2008 27.9 34.8 12.0 5.7 8.2 11.2 3.2 1.3 1993 68.1 73.6 41.9 29.3 43.2 48.4 24.3 16.2 1998 65.1 69.9 39.4 27.3 40.1 44.6 22.6 15.1 2001 69.4 37.1 24.5 36.5 42.5 19.2 12.0 54.4 61.9 29.1 17.3 26.8 31.9 12.3 6.5 c 27.4 32.7 13.7 8.1 10.1 11.5 5.2 3.4 1999 c 17.0 20.8 7.6 4.1 4.9 5.9 2.3 1.4 2002 Panama 63.0 2005 30.0 36.9 16.8 10.2 14.4 18.6 7.6 4.3 1991 2008 21.5 27.7 11.5 6.5 9.5 13.5 5.1 2.7 2009 20.6 26.4 10.0 5.2 8.2 11.1 3.8 1.9 1990 g 36.8 43.2 16.1 8.0 10.4 13.1 3.6 1.5 1999 Paraguay 51.7 60.6 30.2 19.0 26.0 33.8 14.5 8.5 2001 52.0 61.0 30.3 19.5 26.5 33.2 15.4 9.6 2008 50.2 58.2 26.9 15.9 25.1 30.8 12.1 6.5 2009 Peru 50.1 56.0 26.0 15.8 26.7 30.4 12.7 7.4 1997 40.5 47.6 20.8 12.0 20.4 25.1 10.1 5.7 1999 48.6 20.6 11.7 18.7 22.4 9.2 5.1 48.7 54.7 24.7 14.5 20.4 24.4 9.6 5.2 2008 h 31.0 36.2 13.6 7.0 10.5 12.6 4.0 1.8 2009 h Uruguay c 42.3 2001 h 30.3 34.8 12.9 6.5 9.9 11.5 3.5 1.6 1990 11.8 17.9 5.3 2.4 2.0 3.4 0.9 0.4 1999 5.6 9.4 2.7 1.2 0.9 1.8 0.4 0.2 2002 9.3 15.4 4.5 1.9 1.3 2.5 0.6 0.2 2008 Venezuela (Bolivarian Republic of) 8.5 13.7 4.2 1.9 1.8 3.4 0.9 0.3 2009 6.3 10.4 2.8 1.1 1.0 1.9 0.4 0.1 1990 34.2 39.8 15.7 8.5 11.8 14.4 5.0 2.4 1999 44.0 49.4 22.6 13.7 19.4 21.7 9.0 5.5 Latin America i 2002 43.3 48.6 22.1 13.4 19.7 22.2 9.2 5.7 2008 23.6 27.6 9.9 5.2 8.5 9.9 3.5 2.0 1990 41.0 48.3 … … 17.7 22.5 … … 1999 35.4 43.9 … … 14.1 18.7 … … 2002 36.1 44.0 … … 14.6 19.4 … … 2008 26.2 33.0 … … 10.0 12.9 … … 2009 26.3 33.1 … … 10.3 13.3 … … Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries. a H = headcount ratio; PG = poverty gap; FGT2 = Foster, Greer and Thorbecke index. b Includes households (individuals) living in indigence or extreme poverty. c Urban area. d Greater Buenos Aires. e Eight departmental capitals plus the city of El Alto. f Figures from the Mission to Reduce Poverty and Inequality (MERPD), the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE) of Colombia. These values are not comparable with those for previous years. g Asunción metropolitan area. h Figures from the National Institute of Statistics and Informatics (INEI) of Peru. These values are not comparable with those for previous years because of the change in sampling framework for the household survey. The figures for 2001 refer to the fourth quarter; the figures for 2005-2008 refer to entire years. i Estimate for 18 countries of the region plus Haiti. Social Panorama of Latin America • 2010 75 Table I.A-2 LATIN AMERICA (18 COUNTRIES): HOUSEHOLD INCOME DISTRIBUTION, 1990-2008 a Per capita income ratio c Percent of total income Average income b 20% before the wealthiest 10% Country Year Argentina d 1990 e 10.6 15.0 23.7 26.7 34.6 13.5 13.5 1999 11.3 15.8 22.1 25.3 36.8 16.2 16.6 2002 7.3 14.4 20.5 24.6 40.5 19.0 20.7 2006 10.8 16.9 22.9 25.2 35.0 14.4 15.5 2009 16.1 15.5 24.6 27.8 32.1 15.0 16.6 1989 f 7.7 12.1 21.9 27.9 38.1 17.1 21.4 1999 5.6 9.3 24.1 29.6 37.0 26.7 48.1 2002 6.1 9.5 21.4 28.3 40.8 30.3 44.2 2007 6.1 11.2 25.2 28.2 35.4 22.2 31.5 Bolivia (Plurinational State of) Brazil Poorest 40% Next 30% Wealthiest 10% D10 / D(1 to 4) Q5 / Q1 35.0 32.0 35.6 11.0 10.3 17.4 25.6 46.7 32.2 36.9 12.1 12.7 19.2 24.7 43.4 23.8 26.2 11.8 13.2 20.3 25.5 41.0 21.1 23.9 1990 9.5 13.2 20.8 25.3 40.7 18.2 18.4 13.7 13.0 20.4 26.6 40.0 19.1 19.7 13.6 13.8 20.8 25.6 39.8 18.8 18.4 2006 14.4 14.6 21.6 26.7 37.1 15.9 15.7 2009 14.5 14.4 21.2 26.0 38.4 16.3 15.9 1994 7.7 9.9 21.3 27.0 41.8 26.8 35.2 1999 6.7 12.4 21.6 26.0 40.0 22.3 25.6 2002 6.9 10.9 21.2 27.2 40.7 27.1 32.9 2008 7.3 11.3 22.2 26.9 39.6 25.4 32.8 2009 7.1 11.8 22.5 26.3 39.4 23.1 28.0 1990 9.5 16.7 27.4 30.2 25.7 10.1 13.1 1999 11.4 15.3 25.7 29.7 29.3 12.6 15.3 2002 11.7 14.4 25.6 29.7 30.3 13.7 16.9 2008 11.1 15.4 25.2 28.4 31.0 12.5 13.5 2009 11.5 14.3 24.3 28.5 32.9 14.8 16.4 2002 6.9 12.7 22.7 26.9 37.7 17.8 20.7 2008 7.3 11.5 23.3 30.4 34.8 21.2 25.3 2009 8.4 10.7 21.5 27.5 40.3 24.3 28.0 1990 5.5 17.1 25.4 26.9 30.6 11.4 12.3 1999 5.6 14.1 22.7 26.5 36.7 17.2 18.4 2002 6.7 15.5 24.3 26.1 34.1 15.7 16.8 2008 7.1 15.5 24.4 27.0 33.1 14.1 15.5 2009 7.0 15.8 24.6 26.9 32.7 14.5 15.3 1995 6.2 15.5 24.8 27.0 32.7 14.1 16.9 1999 6.6 13.8 25.0 29.1 32.1 15.2 19.6 2001 6.7 13.5 24.7 28.7 33.1 16.2 20.3 2004 6.2 15.9 26.0 28.8 29.3 13.3 16.3 2009 Guatemala 31.2 47.2 2003 El Salvador 43.9 25.4 1998 Ecuador d 28.0 17.4 2009 Dominican Republic 18.5 10.0 2008 Costa Rica 9.6 11.3 2001 Colombia 9.4 1999 Chile 1990 5.8 16.6 25.2 26.8 31.4 12.0 13.0 1989 6.0 11.8 20.9 26.9 40.4 23.6 27.4 1998 7.1 14.3 21.6 25.0 39.1 20.4 19.8 2002 6.8 14.1 22.4 27.3 36.2 18.6 19.3 2006 7.6 12.8 21.8 25.7 39.7 22.0 23.9 76 Economic Commission for Latin America and the Caribbean (ECLAC) Table I.A-2 (concluded) Per capita income ratio c Percent of total income Average income b 20% before the wealthiest 10% Country Year Honduras 1990 4.3 10.2 19.7 27.1 43.0 27.4 30.7 1999 3.9 11.8 22.9 29.0 36.3 22.3 26.5 2002 4.3 11.4 21.7 27.6 39.3 23.6 26.3 2007 4.7 10.1 23.5 29.5 36.9 23.6 32.5 1989 8.6 15.8 22.5 25.1 36.6 17.2 16.9 1998 7.7 15.0 22.7 25.6 36.7 18.4 18.5 2002 8.2 15.7 23.8 27.2 33.3 15.1 15.5 2008 8.6 16.0 24.0 25.6 34.4 16.1 16.0 1993 5.2 10.4 22.8 28.4 38.4 26.1 37.7 1998 5.6 10.4 22.1 27.0 40.5 25.3 35.1 2001 5.8 12.0 21.7 25.6 40.7 23.6 27.5 2005 6.5 14.3 24.0 26.2 35.5 17.2 18.6 1991 d 10.8 14.1 23.9 29.3 32.7 16.8 20.1 1999 d 12.6 15.6 25.2 27.8 31.4 14.0 15.9 2002 9.8 12.2 23.6 28.0 36.2 20.1 25.7 2008 10.3 14.5 25.7 27.8 32.0 15.2 18.8 2009 10.4 14.7 25.5 28.3 31.5 15.3 18.2 1990 g 7.7 18.7 25.7 26.8 28.8 10.2 10.6 1999 6.2 13.2 23.0 27.8 36.0 19.3 22.6 2001 6.2 12.9 23.5 26.3 37.3 20.9 25.6 2008 5.7 14.7 24.7 26.4 34.2 16.7 18.4 2009 5.6 13.7 25.3 28.3 32.7 14.7 18.3 1997 7.5 13.3 24.6 28.7 33.4 17.9 20.9 1999 7.5 13.3 23.1 27.1 36.5 19.5 21.7 2001 6.4 13.4 24.6 28.5 33.5 17.4 19.3 2008 7.8 15.7 26.5 28.4 29.4 12.8 14.4 2009 8.0 15.9 26.5 28.4 29.2 12.4 13.7 1990 9.9 18.9 23.3 22.5 35.3 11.0 10.5 1999 11.9 21.6 25.5 25.8 27.1 8.8 9.5 2002 9.4 21.7 25.4 25.6 27.3 9.5 10.2 2008 9.2 21.1 25.5 26.4 27.0 9.0 9.6 2009 9.8 21.8 25.8 26.1 26.3 8.7 9.1 1990 8.9 16.7 25.7 28.9 28.7 12.1 13.4 1999 7.2 14.5 25.0 29.0 31.5 15.0 18.0 2002 7.1 14.3 25.0 29.5 31.2 14.5 18.1 2008 8.6 19.2 27.9 28.1 24.8 8.4 9.7 México Nicaragua Panama Paraguay Peru Uruguay d Venezuela (Bolivarian Republic of) Poorest 40% Next 30% Wealthiest 10% D10 / D(1 to 4) Q5 / Q1 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. a Households in the country as a whole, in order of per capita income. b Average monthly household income, in multiples of the per capita poverty line. c D(1 to 4) refers to the 40% lowest-income households; D10 refers to the 10% highest-income households. The same notation is used for quintiles (Q), which refer to 20% segments of all households. d Total urban areas. e Greater Buenos Aires. f Eight major cities plus El Alto. g Asunción metropolitan area. Social Panorama of Latin America • 2010 77 Table I.A-3 LATIN AMERICA (18 COUNTRIES): INCOME CONCENTRATION INDICATORS, 1990-2009 a Country Argentina c Year Percentage of people with per capita income lower than 50% of the median Concentration indices Atkinson Gini b Theil (ε = 0.5) (ε = 1.0) (ε = 1.5) 1990 d 0.205 0.501 0.555 0.216 0.360 0.473 1999 0.222 0.539 0.667 0.250 0.410 0.530 2002 0.578 0.724 0.282 0.464 0.593 0.217 0.519 0.626 0.234 0.393 0.522 2009 Bolivia (Plurinational State of) 0.243 2006 0.214 0.510 0.549 0.219 0.377 0.509 1989 e 0.206 0.537 0.574 0.243 0.430 0.600 1999 0.295 0.586 0.658 0.293 0.537 0.738 2002 Brazil 0.286 0.614 0.776 0.322 0.556 0.738 2007 0.272 0.565 0.611 0.269 0.493 0.709 1990 0.266 0.627 0.816 0.324 0.528 0.664 1999 0.259 0.640 0.914 0.341 0.537 0.663 2001 0.639 0.914 0.340 0.536 0.665 0.243 0.594 0.808 0.298 0.477 0.604 2009 Chile 0.261 2008 0.239 0.576 0.716 0.277 0.455 0.586 1990 0.204 0.554 0.644 0.255 0.422 0.546 1998 0.210 0.560 0.654 0.261 0.430 0.553 2003 0.195 0.552 0.674 0.257 0.418 0.535 2006 0.185 0.522 0.568 0.228 0.381 0.497 2009 Colombia 0.174 0.524 0.585 0.231 0.384 0.501 1994 0.260 0.601 0.794 0.308 0.517 0.684 1999 0.218 0.572 0.734 0.275 0.450 0.603 2002 0.248 0.594 0.753 0.293 0.487 0.640 2008 Costa Rica 0.249 0.589 0.737 0.289 0.486 0.787 2009 0.243 0.578 0.706 0.279 0.469 0.702 1990 0.194 0.438 0.328 0.152 0.286 0.412 1999 0.207 0.473 0.395 0.179 0.328 0.457 2002 0.212 0.488 0.440 0.193 0.349 0.491 2008 0.185 0.473 0.427 0.183 0.323 0.439 2009 Dominican Republic 0.203 0.501 0.474 0.204 0.358 0.485 2002 0.221 0.537 0.569 0.236 0.404 0.536 Ecuador c 2008 0.250 0.550 0.593 0.249 0.429 0.569 2009 0.243 0.574 0.677 0.273 0.455 0.589 1990 0.174 0.461 0.403 0.173 0.306 0.422 1999 0.188 0.526 0.567 0.228 0.381 0.498 2002 0.513 0.563 0.222 0.371 0.487 0.206 0.504 0.507 0.210 0.363 0.486 2009 El Salvador 0.196 2008 0.197 0.500 0.502 0.207 0.356 0.475 1995 0.220 0.507 0.502 0.213 0.377 0.525 1999 0.242 0.518 0.496 0.224 0.416 0.601 2001 0.244 0.525 0.528 0.232 0.423 0.602 2004 0.213 0.493 0.449 0.203 0.379 0.552 2009 Guatemala 0.203 0.478 0.440 0.189 0.333 0.449 1989 0.227 0.582 0.736 0.282 0.460 0.590 1998 0.200 0.560 0.760 0.273 0.428 0.534 2002 0.179 0.542 0.583 0.239 0.401 0.515 2006 0.247 0.585 0.773 0.291 0.467 0.590 78 Economic Commission for Latin America and the Caribbean (ECLAC) Table I.A-3 (concluded) Country Honduras Year Percentage of people with per capita income lower than 50% of the median Concentration indices Atkinson Gini b Theil (ε = 0.5) (ε = 1.0) (ε = 1.5) 1990 0.261 0.615 0.817 0.317 0.515 0.649 1999 0.257 0.564 0.636 0.263 0.451 0.603 2002 Mexico 0.265 0.588 0.719 0.288 0.476 0.608 2007 0.305 0.580 0.650 0.282 0.496 0.661 1989 0.197 0.536 0.680 0.248 0.400 0.509 1998 0.229 0.539 0.634 0.245 0.403 0.515 2002 Nicaragua 0.212 0.514 0.521 0.218 0.372 0.485 2008 0.199 0.515 0.599 0.227 0.375 0.485 1993 0.274 0.582 0.671 0.270 0.458 0.619 1998 0.268 0.583 0.731 0.285 0.481 0.654 2001 0.579 0.783 0.288 0.470 0.620 0.226 0.532 0.614 0.241 0.402 0.526 1991 c 0.220 0.530 0.543 0.228 0.398 0.534 1999 c 0.217 0.499 0.459 0.202 0.361 0.490 2002 Panama 0.238 2005 0.266 0.567 0.616 0.266 0.466 0.618 2008 0.254 0.524 0.522 0.229 0.410 0.557 2009 0.248 0.523 0.522 0.226 0.398 0.533 1990 f 0.164 0.447 0.365 0.161 0.287 0.386 1999 Paraguay 0.257 0.565 0.668 0.268 0.455 0.599 2001 0.264 0.570 0.702 0.277 0.471 0.631 2008 0.227 0.527 0.597 0.235 0.397 0.525 2009 Peru 0.245 0.512 0.527 0.220 0.388 0.529 1997 0.256 0.533 0.567 0.238 0.415 0.554 1999 0.236 0.545 0.599 0.249 0.424 0.560 2001 0.239 0.525 0.556 0.231 0.397 0.527 2008 Uruguay c 0.223 0.476 0.428 0.187 0.335 0.457 2009 0.218 0.469 0.414 0.181 0.325 0.442 1990 0.174 0.492 0.699 0.227 0.349 0.441 1999 0.190 0.440 0.354 0.158 0.286 0.393 2002 0.196 0.455 0.385 0.169 0.301 0.412 2008 0.187 0.445 0.372 0.163 0.291 0.397 2009 Venezuela (Bolivarian Republic of) 0.174 0.433 0.354 0.154 0.275 0.374 1990 0.201 0.471 0.416 0.183 0.327 0.446 1999 0.216 0.498 0.464 0.202 0.363 0.507 2002 0.224 0.500 0.456 0.201 0.361 0.507 2008 0.178 0.412 0.295 0.136 0.255 0.363 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. a Calculated on the basis of the distribution of per capita income for individuals in the country as a whole. b Includes people with income equal to zero. c Total urban areas. d Greater Buenos Aires. e Eight major cities plus El Alto. f Asunción metropolitan area. 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.000*** 0.027* 0.277 0.000*** Significance level 6 549 4.3% 0.000 0.313 0.000 -0.239 -0.163 -0.108 0.000 -0.306 -0.328 0.000 -0.049 -0.085 0.000 -0.081 Estimate 0.000*** 0.000*** 0.000*** 0.042* 0.000*** 0.000*** 0.107 0.040* 0.002** Significance level Continental Europe c 5 376 4.8% 0.000 0.281 0.000 -0.298 -0.185 0.044 0.000 -0.195 -0.399 0.000 -0.064 -0.137 0.000 -0.145 Estimate 0.000*** 0.000*** 0.000*** 0.437 0.000*** 0.000*** 0.053* 0.007** 0.000*** Significance level Nordic countries d Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from the World Values Survey database,1981-2008. E Note: * = significance level of 95%; ** = significance level of 99%; *** = significance level of 99.9%. a Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Dominican Republic, El Salvador, Guatemala, Mexico, Peru and Uruguay. b Australia, New Zealand, United Kingdom and United States. c France, Germany, Netherlands and Switzerland. d Finland, Norway and Sweden. e Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Czech Republic, Hungary, Poland, Republic of Moldova, Romania, Russian Federation and Ukraine. 7 897 5.6% 1.5% 21 588 Cox and Snell R-squared Sample 0.000 Single, separated, divorced, widowed 0.375 0.000*** Married, living together, has partner -0.433 0.000 0.701 Aged 60 and older -0.169 -0.009 Aged 45-59 -0.474 -0.408 -0.042 Aged 30-44 0.061 -0.016 Aged 17-29 0.535 0.000 High-income group -0.240 -0.338 -0.130 Middle-income group 0.000*** -0.264 Low-income group 0.000*** 0.000 3 or more children -0.059 -0.039 0.305 0.137 0.050 -0.016 1 or 2 children -0.108 Estimate No children 0.771 Significance level Liberal Anglo-Saxon countries b 0.000 0.004 Estimate Latin America a Female Male Factores 21 688 7.7% 0.000 0.144 0.000 -0.053 -0.008 0.164 0.000 -0.302 -0.680 0.000 -0.030 0.011 0.000 -0.001 0.000** 0.007** 0.670 0.000*** 0.000*** 0.000*** 0.082 0.717 0.936 Significance level Eastern Europe e Estimate Table I.A-4 LATIN AMERICA (12 COUNTRIES) AND OTHER REGIONS: LIFE SATISFACTION, LIFE-CYCLE FACTORS AND MONETARY INCOME, 1981-2008 (Probit ordinal regressions) Social Panorama of Latin America • 2010 79 Social Panorama of Latin America • 2010 81 Chapter II Education and the intergenerational reproduction of inequality and exclusion: realities and challenges in Latin America A. The education agenda in the region Education is at the core of all the developmental stages of the life cycle discussed in this edition of Social Panorama. The data indicate that it is one of the best tools at the disposal of States and public policy for reversing the intergenerational reproduction of inequality and dissociating an individual’s social background from the well-being he or she attains. But the region has not harnessed the education system as a driver of equal opportunity. In the IberoAmerican Year of Education, the regional agenda is, to a large extent, a double one because the unresolved issues of the twentieth century (coverage, access, timely progression and completion of education cycles) are compounded by the great challenge of the twenty-first century: how to narrow the digital divide and improve the quality of education to address the new formative requirements of the knowledge society. In the Ibero-American Year of Education, education must take centre stage in each of the phases of lifelong personal development examined in this edition of Social Panorama. The dynamics of the information society have revived the centrality of education in dealing with the challenges of international competitiveness, democratic sustainability and social equity. This idea is grounded in an abundance of evidence linking the number of students completing the middle level of education and the quality of the skills acquired to greater competitiveness at the country level and to the heightened citizen awareness of rights and responsibilities that is essential for enhancing democracy. The data also bear out the idea that government action on the education front can contribute substantially to dissociating an individual’s social background from the well-being he or she attains. 82 But the region has not harnessed the education system as a driver of equal opportunity, in part because household environment and disposable income are major determinants of educational attainments and returns. Most of the time, this inequality is also reflected in highly segmented and stratified quality and efficiency on the supply side of education. Education moved up on the social policy agenda in Latin America when the education agenda was globalized by the 1990 World Conference on Education for All in Jomtien, Thailand. After the Jomtien World Declaration on Education for All, global education agenda milestones with repercussions for the region were the World Education Forum held in Dakar in 2000 and the United Nations Millennium Declaration signed that same year. The Forum led to the Dakar Framework for Action on Education for All, which reaffirmed the commitments made under the Jomtien World Declaration on Education for All (UNESCO, 2000). One of the highlights of the Forum was the pledge to achieve basic education for all. This began to lay the conceptual groundwork for the Education for All movement led by the United Nations Educational, Scientific and Cultural Organization (UNESCO) and gave rise to the idea of inclusive education as a way to address the exclusion of some citizens from (and within) the formal education system. The Millennium Declaration in turn led to the Millennium Development Goals project that set goals, targets and deadlines for action on several social fronts. Millennium Development Goal 2 seeks achievement of universal primary education; target 2A calls for ensuring that, by 2015, children everywhere, boys and girls alike, will be able to complete a full course of primary schooling. These international instruments have put such issues front and centre on regional and national agendas, for contextualized discussion. For example, the Education for All in the Americas: Regional Framework of Action was drafted at the 2000 conference in Santo Domingo. The framework highlights progress made on the priority area of access to primary education, the relative decrease in illiteracy rates, the increase in the number of years of compulsory education and the increase in early childhood care and education (UNESCO, 2000). It also recognizes that challenges remain for the region, including the formulation of inclusive policies to ensure access and create conditions that promote timely progression and completion and quality learning, especially in the basic cycle but also at the secondary level. In addition, the framework calls for a pledge to advance towards non-discrimination on the basis of gender, culture, language or socio-economic Economic Commission for Latin America and the Caribbean (ECLAC) status, viewing education as a universal right. Accordingly, there is a need for meaningful curricula, intercultural and bilingual education and initiatives for involving the families of excluded children and young people (UNESCO, 2000) in view of the enormous weight of the family environment in determining the relationship between family members and education. Virtually universal access to basic education has been achieved in Latin America and the Caribbean, so education policy efforts have shifted to early childhood education. The social and economic returns from investing in early childhood education are vital (UNESCO, 2010a). The focus on early childhood education in recent years led to the World Conference on Early Childhood Care and Education held in Moscow in 2010, providing a comprehensive approach to the developmental needs of children in this stage of life. Among these, education is critical. The region took up this challenge when the members of the Organization of American States (OAS) signed the Hemispheric Commitment to Early Childhood Education and pledged to turn recognition of early childhood care and education into specific actions within the institutional framework of each country. The regional agenda is, to a large extent, a double one (ECLAC/OEI/SEGIB, 2010). There are the unresolved challenges of the twentieth century: coverage, access and timely progression and completion of education cycles. Then comes the great challenge of the twenty-first century: the quality of education provided by schools. This second dimension includes improving teaching through training and integrating new educational resources such as information and communications technologies and putting traditional educational resources to better use. Concern as to the quality of education in the region was reaffirmed at the Santo Domingo conference by including this dimension in the 12 commitments of the regional framework of action (UNESCO, 2000) and the global monitoring report on the Education for All project in the region (UNESCO, 2007). A noteworthy region-wide project is “Goals 2021: The Education We Want for the Bicentennial Generation”, which divides the region’s dual agenda into targets referring to unresolved issues in education and targets concerning future challenges in this arena. One of the first targets addresses the extra-school factors that affect general well-being and the school performance of children and young people in each education cycle. The goal is to achieve education equality by eliminating the discrimination that works against insertion and participation in the school system. For the post-secondary cycle there are targets related to the nexus of education, knowledge and employment linking the challenges of the twentieth century to those of the twenty-first. In this new century, the focus is on Social Panorama of Latin America • 2010 quality of education, stressing that the skills acquired by students must be practical and relevant to social integration. In this process, the emphasis is not only on academic subjects but also on reading, education in democratic values, art education, sports and the use of new technologies in education. To complete this picture, the resources provided for education and the number of full-time primary schools must be increased. And the quality of education cannot be improved without enhancing the teaching profession. Initial training, accreditation and continuing education are therefore among the project targets. International cooperation under the Organization of Ibero-American American States for Education, Science and Culture (OEI) and the Ibero-American General Secretariat (SEGIB) is an important part of the project 83 and involves the countries of the Iberian peninsula on the basis of shared but differentiated responsibility. A promising avenue for financial partnership is SouthSouth cooperation, an initiative for financial aid between countries of the region. This requires gathering up-to-date information on the status of education in the region, the cost of achieving education targets and potential sources of funding. The Economic Commission for Latin America and the Caribbean (ECLAC) has been actively involved in this task. The general targets have already been approved by the countries, and it is hoped that a pledge to move forward in meeting the specific goals that will guide action for developing education in the region will emerge from the Twentieth Ibero-American Summit of Heads of State and Government, to be held in Mar del Plata, Argentina, in December 2010. B. Gaps in attainment and in learning In recent decades, advances in coverage, access and progression through education cycles have caused stratification in learning and attainment within educational systems. Access to preschool learning is uneven across the region; some countries have nearly universal enrolment while in others it is in the area of 30%. Access to primary education is virtually universal, with room for improvement in timely progression and completion and in inclusion of the most neglected social groups. Access and timely progression in secondary education are substantially lower and differ more among countries. The gaps in secondary school completion rates exacerbate socio-economic inequalities by geographic area and ethnic background. Access to the final cycle of post-secondary education is generally reserved for a relatively small portion of the region’s young people. Among the factors of inequality, household socio-economic conditions and level of formal education of the head of household are among the root causes for disparate results in learning and progression through the education system, as is widely varying access to quality education. As for the dynamics of skill acquisition, the promise of digital convergence (or rather, the threat of a widening digital divide) has been looming on the horizon for some time now. 84 Economic Commission for Latin America and the Caribbean (ECLAC) In successive editions of Social Panorama and in contributions to the Millennium Development Goals, ECLAC, aware of the pace of educational devaluation in the region, has focused on monitoring changing levels of educational attainment that effectively reduce vulnerability to poverty and social exclusion. One of the greatest difficulties that the education system faces is the snowballing levels of knowledge needed to meet individual and collective goals. Studies show that what each period of history regards as minimum qualifications depends to a large extent on the skills and knowledge required in that period for individuals to participate in the dynamics of progress and well-being. Educational devaluation is happening in Latin America, where modernization has, among other things, been effacing the social prestige attached to certain qualifications and specialties. This prestige is shifting to other skills sets that are more in line with ever-changing requirements for competitiveness and full participation in society. Over the course of the twentieth century, skill thresholds shifted from the dividing line between literacy and illiteracy to the divide between 1. those who completed primary school and those who did not, and subsequently to completion of the basic cycle of secondary education. The threshold is now at completion of secondary education, although in some countries of the region there are already signs that even those who complete this cycle are vulnerable to poverty and social exclusion. The permanent pressure on skill thresholds for attaining decent living conditions is thus nothing new. What is new is the pace, which is creating complex problems for keeping the workings of the education system in sync with outcomes. While there have been advances in education in recent decades, expanding access has also led to greater segmentation in attainment and in quality on the supply side. This means that the intergenerational reproduction of inequality does not occur because some have access to formal education and others do not, but rather that everyone has access but the outcome is differentiated in terms of what students learn and how far they progress in the system. The clearest manifestations of this segmentation in the education systems of Latin America are examined in the following pages. Access to early childhood and preschool education Preschool education has recently become a top public policy issue in the region.1 The situation varies widely, with access rates (starting with preschool enrolment of children between 3 and 6 years of age) that are nearly universal in Cuba and Mexico but in the area of 30% in the Dominican Republic, Guatemala and Honduras (see figure II.1.A). Enrolment in early childhood education (from birth to age 3) is, as a rule, lower, owing to less coverage on the supply side and to cultural factors. Across the region, differences between socioeconomic strata in terms of enrolment in the last year before entering primary education are smaller, with rates ranging from 80% for the lowest income quintile to 92% for the wealthiest quintile. The differences in enrolment between boys and girls are not substantial (ECLAC/OEI/ SEGIB, 2010). But the regional average masks marked inequalities in smaller countries in the region with lower coverage —there are gaps of 30 percentage points or more in El Salvador, Honduras, Nicaragua and Paraguay (see figure II.1.B).2 While it seems that there are no significant socio-economic inequalities in attendance towards the end of the preschool cycle, evidence from household surveys does suggest that inequalities are more striking at younger ages. Moreover, there are marked differences in access between urban and rural areas and for indigenous groups (ECLAC, 2008a). 1 In 2007 the ministers of education of the member States of the Organization of American States agreed to develop legal frameworks and financing mechanisms to ensure the sustainable implementation of early childhood policies and improve coverage and quality of education. The agreement calls for comprehensive policies and a targeted approach focusing on attending to the poor, vulnerable and excluded segments of society in keeping with their particular needs, characteristics and contexts. At a meeting held in 2009 in the framework of the Organization of Ibero-American States for 2 Education, Science and Culture (OEI), the ministers of education approved a comprehensive early childhood project that is at the heart of the project “Goals 2021: The Education We Want for the Bicentennial Generation” (ECLAC/OEI/SEGIB, 2010). Some countries of the region have extended the beginning of compulsory education into the preschool cycle. Such is the case in countries with more generalized attendance, such as Uruguay (4 years) and Mexico (3), but also in El Salvador (4) and Paraguay (5). Social Panorama of Latin America • 2010 85 Figure II.1 LATIN AMERICA (19 COUNTRIES): NET ENROLMENT RATIO FOR PRE-PRIMARY LEVEL (3 TO 6 YEARS); ESTIMATED ENROLMENT RATIO FOR EARLY CHILDHOOD EDUCATION (0 TO 3 YEARS); AND DIFFERENCES IN ATTENDANCE RATES BETWEEN THE FIRST AND FIFTH QUINTILES FOR CHILDREN ONE YEAR YOUNGER THAN THE OFFICIAL AGE FOR STARTING PRIMARY SCHOOL, AROUND 2008 a (Percentages) B. Preschool attendance rates for children who are one year younger than the official age for starting primary school, first and fifth quintiles A. Net enrolment ratios 96 98 100 100 90 90 80 70 60 47 50 40 30 27 32 36 54 54 55 50 50 53 61 63 66 69 73 72 73 80 70 58 60 50 40 40 30 Preschool education Early childhood education Quintile I Latin America Simple average Mexico (2008) Uruguay (2008) Argentina (2006) Venezuela (Bol. Rep. of) (2008) Brazil (2008) Chile (2006) Ecuador (2008) Panama (2008) Colombia (2008) El Salvador (2004) Dominican Rep. (2008) Peru (2008) Costa Rica (2008) Paraguay (2008) Honduras (2007) Nicaragua (2005) Bolivia (Plur. State of) (2007) Guatemala (2006) Latin America Simple average Cuba Brazil Mexico Uruguay Peru Argentina Panama Colombia Nicaragua Venezuela (Bol. Rep. of) Chile Costa Rica Ecuador Paraguay El Salvador Bolivia (Plur. State of) 0 Honduras 10 0 Dominican Rep. 20 10 Guatemala 20 Quintile V Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute for Statistics (UIS), estimates and household surveys E conducted in the respective countries (attendance rates). a Early childhood enrolment ratio estimate based on exponential models on the basis of household surveys in countries with information available (see ECLAC/OEI, 2010). The age groups vary, depending on the official cycles in the countries. Access to primary education and unequal completion rates 100 90 73 74 80 81 82 86 90 90 91 92 93 93 93 93 94 94 95 95 95 96 96 96 96 97 97 97 97 98 98 99 99 99 99 99 100 100 100 Figure II.2 LATIN AMERICA AND THE CARIBBEAN (36 COUNTRIES AND TERRITORIES): NET PRIMARY EDUCATION ENROLMENT RATIO, 2007-2008 a (Percentages) 93 95 70 60 50 40 30 20 10 0 Dominica Antigua and Barbuda Turks and Caicos Islands Dominican Rep. Jamaica Suriname Saint Kitts and Nevis Bahamas Venezuela (Bol. Rep. of) Ecuador Paraguay Nicaragua Brazil Saint Lucia Colombia Chile Bolivia (Plur. State of) Anguilla Cayman Islands El Salvador Grenada Montserrat Guatemala Trinidad and Tobago British Virgin Islands Honduras Saint Vincent and the Grenadines Uruguay Guyana Panama Argentina Aruba Mexico Cuba Belize Peru Historically, primary education has been regarded as crucial for a child’s future, since it is possible to have a positive and effective influence on children during this stage of development. It is no coincidence that all international agreements on education call for universal access to primary education (ECLAC, 2010b). It is hoped that this will translate into more students remaining in and completing the entire cycle of primary education and become a successful springboard to secondary education. Completion of the latter is becoming more and more a necessity. Access to primary education is generally assessed by looking at the enrolment ratio. The net ratio shows the proportion of pupils of primary school enrolment age who are actually enrolled. Access to primary education is, with few exceptions, widespread across Latin America and the Caribbean and is nearly universal in some countries (see figure II.2). Differences in access between girls and boys and between socio-economic strata are not significant at this level. Nonetheless, access to the education system does not necessarily ensure appropriate progression or, more important, completion of primary education. At this level there are problems of school lag and retention (dropping out). Educational lag is costly for the education systems of the region. It is estimated that the region spends more Simple average Weighted average 2. Source: UNESCO Institute for Statistics (UIS), online database, www.uis.unesco.org. a Adjusted net enrolment ratio. The calculation of enrolment ratios can be somewhat erratic since it relies on population estimates and projections that do not always reflect migratory movements. For this reason, some of the figures should be read with caution, particularly for smaller countries and territories. Data for Argentina and the Turks and Caicos Islands correspond to 2005; and data for Anguilla and Paraguay correspond to 2006. 86 Economic Commission for Latin America and the Caribbean (ECLAC) than US$ 9 billion on children who are in primary school but should be in secondary school according to their age (ECLAC/OEI, 2010). Even bearing in mind that several countries have automatic promotion systems for the first few grades, by 9-11 years of age there is already a significant percentage of children who are two or more years behind the grade they should be in (see figure II.3.A.). According to UNESCO, in the period 2007-2008 the overall percentage of repeaters for all primary education grades was 3.8% and the drop-out rates for grades one through six were 3.7%, 1.7%, 2.0%, 1.5% and 2.8% respectively (UNESCO, 2010b). In 2006-2007, nearly 3 million children were not in school. Gender differences according to socio-economic level and geographic area, among other factors, also become apparent upon examination of school completion rates: girls do slightly better than boys. And while only 2 out of 100 children in the higher-income strata (fifth quintile) do not finish primary school, in the poorer strata some 12 out of 100 do not (see figure II.3.B). Primary education completion rates are 96% in urban areas but only 85% in rural areas. The problem is worse among indigenous and Afro-descendent children: just 80% complete this cycle (ECLAC, 2008a). Judging by primary education access rates from the early 1990s (about 90%) and the relatively poor progress in this regard, there are obviously some obstacles in the path to universal access. This is because when access to primary education is widespread, the investment needed to promote enrolment among disadvantaged groups (the extremely poor, inhabitants of rural areas, indigenous and Afro-descendent groups) is substantial and should focus not only on increasing the supply of education but also on ensuring the conditions for effective access to these services. This often involves action in multiple sectors. Figure II.3 LATIN AMERICA (17 COUNTRIES): EDUCATIONAL LAG AMONG CHILDREN AGE 9-11 AND PRIMARY EDUCATION COMPLETION AMONG YOUNG PEOPLE AGE 15-19 OF THE TOTAL POPULATION, BY SEX AND INCOME QUINTILE, AROUND 2007-2008 a (Percentages) A. Educational lag B. Completion rate Guatemala 100 26 Nicaragua 25 Paraguay 21 Dominican Rep. 94 86 90 22 Colombia 92 90 91 93 94 96 96 97 98 98 80 20 Honduras 70 17 Bolivia (Plur. State of) 14 60 13 El Salvador 12 Ecuador Brazil Panama 50 11 10 40 10 Peru Uruguay 30 10 9 Chile 20 6 Argentina 10 5 Costa Rica 3 Mexico 0 10 20 30 0 Total Quintile I Males Quintile II Quintile III Quintile IV Quintile V Females Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Information System on Educational Trends in Latin America (SITEAL), Statistical E Summary I, National Totals, October 2008, and special tabulations of data from household surveys conducted in the respective countries. a Educational lag is calculated on the basis of children who are two or more years behind the grade they should be in for their age. 3. Unequal access to, progression in and completion of secondary education The ratios for access to and timely progression through the secondary cycle are significantly lower than for primary education and vary more widely from country to country. The net attendance rate for the secondary level is 88%, versus 97% for the primary level (see tables II.A-1 and II.A-2). Educational lags accumulate at this stage, and socio-economic inequalities according to geographic location or ethnic background grow more marked. Household educational climate emerges as a determining factor in educational lags for children age 12-14: a child living in a household with a low educational climate is 10 times more likely to fall behind in school than one in a household with a positive climate. There are also notable differences by area of residence. This is naturally linked to household and student well-being. Hence, in terms of completion (timely or otherwise) of the lower cycle of secondary schooling, there is a marked difference between young people who are from poor households (52%) and those who are not (82%) (ECLAC/OEI/SEGIB, 2010). Social Panorama of Latin America • 2010 87 Poor or not, females complete this level of education more frequently than males, owing in part to the higher likelihood of males entering the labour market early. In contrast, there is evidence showing that among young people from indigenous groups the ratio is reversed, with a smaller proportion of females completing secondary education (ECLAC, 2008a). Such differences in educational access, progression and completion are gradually amplified throughout the educational cycle. The chain of inequality is thus reproduced through the education system itself. Young people approaching the upper secondary cycle already have opportunities to enter the labour market. This acts as a disincentive to staying in school, especially if students face adverse economic or academic conditions or problems with integration or identity formation. In addition, this level of education is still not compulsory in many countries of the region, so States cannot force young people to stay in school. Access and timely progression at this stage vary widely across the region, ranging from a net enrolment ratio of more than 80% (Bahamas, Chile, Cuba, Grenada and Montserrat) to very low ratios, where two thirds or more of the young people are behind in school or simply drop out (El Salvador, Guatemala and Nicaragua). The regional average barely exceeds 50% (see figure II.4). Figure II.4 LATIN AMERICA AND THE CARIBBEAN (36 COUNTRIES AND TERRITORIES): NET ENROLMENT RATIO IN THE FIRST AND SECOND CYCLES OF SECONDARY EDUCATION, 2007-2008 a (Percentages) 100 96 95 90 100 100 91 85 86 83 90 82 80 94 81 95 90 86 85 84 78 93 92 91 75 70 80 75 76 71 71 81 70 79 70 70 71 74 70 70 67 65 65 60 62 61 83 79 77 82 78 77 71 75 71 58 78 68 66 61 56 55 52 51 50 55 50 56 48 48 48 47 42 41 40 54 38 41 52 42 33 32 30 20 15 10 Simple average Weighted average Nicaragua El Salvador Colombia Guatemala Paraguay Suriname Costa Rica Brazil Belize Mexico Panama Honduras Ecuador Lower secondary Dominica Dominican Rep. Uruguay Venezuela (Bol. Rep. of) Argentina Saint Lucia Bolivia (Plur. State of) Netherlands Antilles British Virgin Islands Peru Turks and Caicos Islands Aruba Saint Kitts and Nevis Jamaica Anguilla Trinidad and Tobago Saint Vincent and the Grenadines Chile Cayman Islands Cuba Bahamas Grenada Montserrat 0 Upper secondary Source: conomic Commission for Latin America and the Caribbean (ECLAC), estimates on the basis of data from the UNESCO Institute for Statistics (UIS). E a Data for the Netherlands Antilles correspond to 2003; data for Anguilla, the Turks and Caicos Islands, Paraguay and Suriname correspond to 2005; and data for Argentina, Guatemala and Panama correspond to 2006. In addition to heterogeneity among countries, there are ever more pronounced differences within countries: between rural and urban areas, poor and non-poor students, different socio-economic groups and indigenous and non-indigenous groups, as well as other discriminating factors. Four out of five students from the highest-income households (fifth quintile) complete their secondary education, whereas only one out of five at the lowest socio-economic level do. The difference in attainment between males and females begins to widen in the intermediate socio-economic levels (see figure II.5). In rural areas where indigenous communities occupy more or less defined territorial spaces and have a culture and identity that is often clearly different from the prevailing “westernized” urban culture, early dropout rates for girls are much higher than for boys and their upper secondary education completion rates are lower. Girls tend to focus on activities related to agricultural production in their communities or families. This pattern is not seen among indigenous young people living in urban areas. Figure II.5 LATIN AMERICA (18 COUNTRIES): POPULATION AGE 20-24 WITH COMPLETE SECONDARY EDUCATION BY PER CAPITA INCOME AND SEX, AROUND 2008 a (Percentages) 100 90 81 80 72 70 60 50 86 59 55 49 44 40 62 49 35 30 23 26 22 20 26 31 20 10 0 Total Quintile I Quintile II Quintile III Quintile IV Quintile V Income quintile Males Indigenous Nonindigenous Rural areas Females Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the respective countries. a The data for indigenous and non-indigenous young people refer to eight countries and correspond to 2007. 88 4. Economic Commission for Latin America and the Caribbean (ECLAC) Discrimination and lag in primary and secondary education among indigenous and Afro-descendent groups Historically, ethnic minorities and indigenous groups have been affected by unequal conditions in the region. The barriers to equitable access to the education system are related to higher incidence of poverty, distance from school, quality of educational establishments to which there is access, curriculum relevance and discrimination. All of these factors diminish educational opportunities. On top of a low standard of living and the social discrimination that makes them targets of rejection and refusal, many of these groups live in rural areas far from the main centres of education. Local supply is scarce, infrastructure is poorly maintained and the quality of teachers and teaching materials is wanting (ECLAC, 2008a). Another barrier that keeps these groups from entering and staying in the school system is the lack of appropriate, relevant and meaningful curricula. This is another instance of poor linkage between culture and environment, on one hand, and school subject content, on the other (ECLAC/OEI, 2010). Table II.1 LATIN AMERICA (Nine COUNTRIES): NET PRIMARY AND SECONDARY SCHOOL ATTENDANCE RATIOS, PRIMARY CYCLE COMPLETION FOR YOUNG PEOPLE AGE 15-19 AND SECONDARY CYCLE COMPLETION FOR YOUNG PEOPLE AGE 20-24 BY AREA OF RESIDENCE AND ETHNIC background, AROUND 2008 (Percentages) Net attendance, primary education Country Net attendance, secondary education Primary education completed National total National total Rural areas National total Indigenous or Not indigenous or Afro-descendent Afro-descendent Indigenous or Not indigenous or Afro-descendent Afro-descendent Indigenous or Not indigenous or Afro-descendent Afro-descendent Indigenous or Not indigenous or Afro-descendent Afro-descendent Bolivia (Plurinational State of) (2007) … … 90 95 86 90 90 94 Brazil (2008) 98 99 93 95 83 89 91 93 Chile (2006) 98 99 98 99 97 98 94 95 Ecuador (2008) 97 98 89 95 89 93 76 86 El Salvador (2004) 92 92 74 78 63 65 83 79 Guatemala (2006) 86 91 49 71 40 58 61 75 Nicaragua (2005) 85 81 58 71 46 54 86 84 Panama (2008) 98 99 73 97 73 93 74 89 Paraguay (2008) 96 98 83 94 82 87 71 92 Total 93 97 82 93 70 84 85 92 Lower cycle of secondary education completed Upper cycle of secondary education completed National total Rural areas National total Rural areas Indigenous or Not indigenous or Afro-descendent Afro-descendent Indigenous or Not indigenous or Afro-descendent Afro-descendent Indigenous or Not indigenous or Afro-descendent Afro-descendent Indigenous or Not indigenous or Afro-descendent Afro-descendent Country Bolivia (Plurinational State of) (2007) 76 88 62 68 55 71 38 44 Brazil (2008) 74 78 49 53 47 56 24 27 Chile (2006) 94 96 84 89 65 81 50 63 Ecuador (2008) 47 73 38 48 31 59 23 33 El Salvador (2004) 60 57 41 35 37 36 17 17 Guatemala (2006) 19 44 12 20 13 33 7 12 Nicaragua (2005) 34 44 11 21 21 32 5 13 Panama (2008) 36 79 36 58 12 60 12 40 Paraguay (2008) 45 80 40 54 25 62 21 36 Total 62 77 38 49 40 56 20 28 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. Social Panorama of Latin America • 2010 5. 89 Access to and completion of post-secondary education: the bottleneck Generally speaking, access to post-secondary education is reserved for a relatively small proportion of young people in the region (see figure II.6.A). Very few students complete technical/vocational studies or a university education, because they have not acquired the competencies needed to succeed at higher levels. At the root of this problem is the uneven quality of primary and secondary education, plus other factors such as the need to earn money in order to attain a minimum level of well-being. Only 8.3% of young people age 25-29 have completed at least five years of post-secondary education (typical length of time for a university degree programme). There is marked stratification by per capita income quintile: for every 27 young persons from high-income strata (fifth quintile) who complete five years of post-secondary studies only one lower-income one does (see figure II.6.B). Figure II.6 LATIN AMERICA (17 COUNTRIES): POST-SECONDARY EDUCATION ATTENDANCE AMONG YOUNG PEOPLE AGE 20-29 AND COMPLETION OF AT LEAST FIVE YEARS OF UNIVERSITY EDUCATION AMONG ThOSE AGE 25-29 BY PER CAPITA INCOME AND SEX, AROUND 2008 (Percentages) B. Completion of five years of post-secondary education A. Post-secondary education attendance Latin America Brazil (2008) Peru (2008) Venezuela (Bol. Rep. of) (2008) El Salvador (2004) Chile (2006) Paraguay (2008) Nicaragua (2005) Guatemala (2006) Panama (2008) Mexico (2008) Ecuador (2008) Dominican Rep. (2008) Honduras (2007) Bolivia (Plur. State of) (2007) Argentina (2006) Costa Rica (2008) Colombia (2008) 50 33 23 27 29 30 30 0 45 40 35 36 36 36 37 38 20 12.4 15 46 47 49 10 53 55 58 40 23.9 25 42 20 30.4 30 60 7.4 2.1 5 0 80 100 8.2 9.1 0.7 Total 1.0 Quintile I 3.4 5.5 1.6 Quintile II Quintile III Quintile IV Quintile V Income quintile Post-secondary education attendance Males Females 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. The promising side of the coin is the large contingent of first-generation college students for whom the future holds unprecedented potential for socio-occupational mobility compared with their parents. In several countries of the region, more than one half of the university students are “first-timers” in their direct family. But here, too, the percentage of young persons from lower-income or lesseducated families who do attend college is still very low. As a rule, when development strategies leave postsecondary education entirely up to the workings of supply and demand, access to the highest levels is confined to a small elite of students. And the limited level of development in some economies of the region has led the better qualified to emigrate to more developed countries in search of better job opportunities and greater specialization. The lack of a critical mass of young people in technical and vocational fields who are familiar with cutting-edge tools for innovation is hindering modernization and efforts to increase competitiveness in most countries of the region (ECLAC/OIJ, 2008). 90 6. Economic Commission for Latin America and the Caribbean (ECLAC) Intergenerational transmission of education inequalities (a) In families It is hard to grasp the complex challenges faced by education in decreasing inequalities without noting that social patterns are not reproduced by any single institution but rather by the institutional structure as a whole, where the education system combines, above all, with family and neighbourhood life to form a child’s most immediate community environments. Also, much of the success of institutionalized education depends on how well the efforts and influences of these three spheres of socialization are meshed. When families and neighbourhoods fail to provide adequate support, it is harder for the education system to fulfil its key role in integrating new generations or to capitalize on its particular ability to dissociate educational achievement from student background. Against this backdrop, household socio-economic conditions and education level of the head of household continue to be the root cause of differences in learning outcomes. Some of the most influential conditions are discussed below. First come physical capital (such as dwelling infrastructure, income and household equipment), human capital (educational climate) and cultural capital (habits and values in common with the educational ideology). Substandard housing, overcrowding, a large number of children, scarce human capital, fragile ties to the labour market and income instability are some of the factors that undermine a family’s ability to meet basic needs and can raise sometimes insurmountable barriers to achieving the conditions required for regular school attendance and adequate learning. In addition, how motivated families are to invest resources in their children’s education is directly related to the credibility they attach to the education system as a vehicle for social mobility —that is, the perception that the quality of the educational opportunities that the family’s available resources put within the children’s reach will really open alternatives for them to access society’s main social and economic circuits. Likewise, the “subjective educational climate” in the household depends to a large extent on the quality of education supply, on how the school involves and motivates the community of parents and on how families generally view meritocracy and the broadening of opportunities in society. The intergenerational reproduction of inequality in education obstructs mobility. Children of low-income, poorly educated parents tend to learn and achieve less than their peers from families with more educational capital. This will in turn confine the former to lower-paid jobs throughout their life, and so on. Figure II.7 shows the high correlation between household educational climate (years of education or educational attainment of the parents) and the children’s educational attainments, especially when comparing parents with different levels of education. While only 3.4% of the children whose parents did not complete primary school go on to finish post-secondary studies, the rate climbs to 71.6% when the parents have completed tertiary education. Figure II.7 LATIN AMERICA (SELECTED COUNTRIES): YOUNG PEOPLE AGE 25-29 WHO COMPLETED VARYING LEVELS OF EDUCATION BY HOUSEHOLD EDUCATIONAL CLIMATE, AROUND 2006 a (Percentages) 97.1 100 90 98.3 98.8 98.4 85.5 92.7 80 91.1 90.8 71.6 70 60 50 51.9 40 30 20 10 0 32.7 18.7 5.9 5.4 Up to incomplete secondary Complete secondary 3.1 Incomplete primary Complete primary Complete secondary Incomplete technical and tertiary Complete tertiary Complete tertiary Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of special tabulations of data from household surveys conducted in the respective countries. a Average years of education their parents completed, except for young people who are already emancipated and are themselves heads of households. In this case, refers to their own level of educational attainment. Conversely, when parents did not complete primary school, one out of three of their children finish secondary school and 85.5% complete primary school. This indicates a high (and thus rigid) correlation between parent and child educational stratification, but also a clear tendency for children to surpass their parents in education. So there is systemic mobility owing to the joint expansion of attainment thresholds, but there is also rigid stratification to the detriment of the lowest socio-economic levels, rural areas and indigenous and Afro-descendent groups. Social Panorama of Latin America • 2010 (b) At school The social and cultural disadvantages that burden lower-resource students as they enter the educational system are compounded by access to lower-quality education services than are available to students with more resources. This reinforces the inequality of their learning paths. Over the past few decades, expanding access to the educational system for traditionally excluded sectors has come with greater segmentation of supply and a sharp increase in out-of-pocket expenses and the number of private schools. The quality of education tends to be segmented on the basis of the students’ socio-economic background. Private schools are increasingly a magnet for the upper-middle and upper classes seeking to preserve their upwards differentiation in the intergenerational transmission of human capital and to avoid the quality concerns surrounding mass public education. The social make-up of student bodies is, then, increasingly uniform; this determines the profile of the peer group with which the child will be in contact every day. The key factors that determine how homogeneous the social make-up of an educational establishment will be can be spatial, economic or a combination of the two. Spatial factors refer to the fact that schools usually recruit students in the immediate geographical area and thus tend to reproduce, inside the school, the social make-up of the environs. Economic factors refer to household purchasing power, which is mirrored in different opportunities to access private or for-pay schools. Urban segregation and segmentation among schools are thus mutually reinforcing. Educational segmentation leads to differentiations that exacerbate divides in school life. First, it weakens the 7. 91 oversight that better-qualified, more “authoritative” parents could exercise over education in public establishments. Second, school segmentation by household purchasing power generates significant differences in how well equipped the schools are and how well trained the teaching staff is. Both affect learning outcomes. Third, living in an environment with a high density of other children from higher-strata households helps students accrue social and cultural capital that will subsequently facilitate their entry into the labour market and the networks of adult life. Fourth, segmentation undermines the integrative capacity of schools, part of which is based on their ability to gather under one roof students from different social backgrounds. This inhibits interaction between children and young people from diverse socioeconomic and cultural realities. Fifth, for schools in highly vulnerable or poor areas, the magnitude and seriousness of problems outside the school make it harder to manage life and pedagogical processes inside the school. The most dramatic extreme is intra-school violence at many establishments in marginal urban areas of Latin American cities. It is a major factor behind learning disorders, the dropout rate and the unravelling fabric of coexistence. Conversely, studies on learning impacts show that if children from poor households can attend schools with a heterogeneous social make-up, their expectations for their own educational attainment change for the better. They have more cognitive and practical resources for problem-solving and broader social capital/exchange networks, as well as regular opportunities to build shared codes for the timely learning of civic responsibilities and mutual respect for the rights of other groups. Learning outcome gaps within and between countries Monitoring and measuring the region’s progress in this sphere is not without its difficulties. Research and decision-making in the field of public education policy have generally focused on measuring the quality of students’ academic outcomes, using standardized national or international tests. These measurements are generally confined to assessing basic learning subjects such as language development, math skills and, in some cases, scientific knowledge. Although such measurements limit the analysis of the range of skills that children should acquire during their school years, recent international evaluations have shown a disturbing basic skills-learning deficit among students in the region. The most recent data available on academic outcomes in countries of the region are from the OECD Programme for International Student Assessment (PISA), dating from 2006, and from the Second Regional Comparative and Explanatory Study (SERCE) conducted in 2006 by the UNESCO Latin American Laboratory for Assessment of the Quality of Education. The former surveys a sample of 15-year-old students to assess the basic skills they have acquired in science, mathematics and reading 92 Economic Commission for Latin America and the Caribbean (ECLAC) comprehension. In 2006, six countries of the region took part in the survey: Argentina, Brazil, Chile, Colombia, Mexico and Uruguay. SERCE, in which 16 countries of the Latin American region took part, measured basic skills in the same curricular areas, but for third- and sixth-grade pupils. Although they assessed students in different age brackets, both measurements are consistent in revealing a high percentage of the student population with very poor performance in basic educational competencies. Moreover, the difference in PISA performance between the countries of Latin America and the average for developed OECD countries is very significant (around 75 points). Between 40% and 60% of students in Latin America who took part in PISA fall below the levels of performance regarded as essential for participating as citizens in academic, social and labour life. Because their relative SERCE ranking is similar, it can be concluded that improving the performance level of all students is a region-wide challenge (OEI, 2008). SERCE shows that except for Cuba (which has very high achievement levels), at least 40% of the third-graders of most of the countries of Latin America have the lowest possible math achievement score. This means that a significant percentage of the student population will have serious difficulties in progressing in a timely fashion and successfully completing their education, with a domino effect on future job opportunities and social integration (ECLAC/OEI/SEGIB, 2010). The situation varies among the countries of the region and is significantly associated with each country’s level of development and wealth. There are therefore clear differences between countries by per capita income. In general, the wealthier countries provide their students with better education in basic competencies. Figures II.8 and II.9 show the association between GDP and academic performance in the language area in primary school (on the basis of SERCE 2006) and in the science area in secondary school (on the basis of PISA 2006). The trend they show is that the higher the per capita GDP, the better average academic outcomes are. But some countries in each figure with similar per capita GDP rank higher or lower, leading to the conclusion that while this variable is important, it is not the only determining factor. Other national context factors must also be taken into consideration. Figure II.8 LATIN AMERICA (15 COUNTRIES): AVERAGE SECOND REGIONAL COMPARATIVE AND EXPLANATORY STUDY (SERCE) READING TEST SCORES FOR SIXTH-GRADERS BY 2006 PER CAPITA GDP, 2006 a Figure II.9 LATIN AMERICA (SIX COUNTRIES) AND OTHER PARTICIPANTS IN THE PROGRAMME FOR INTERNATIONAL STUDENT ASSESSMENT (PISA) (20 COUNTRIES): AVERAGE PISA SCIENCE TEST SCORES FOR 15-YEAR-OLD STUDENTS BY 2006 PER CAPITA GDP, 2006 600 600 Costa Rica Chile 550 Reading scores 500 El Salvador Nicaragua Guatemala Mexico Panama Ecuador Paraguay 400 Russian Federation 450 Uruguay Colombia 4 000 6 000 8 000 10 000 2006 per capita GDP in current dollars Portugal Greece Italy Sweden Germany United Kingdom France United States Israel Brazil Argentina 350 2 000 Chile Turkey Spain Netherlands Mexico 400 350 New Zealand Poland 500 Dominican Rep. 0 Japan Canada Rep. of Korea Brazil Peru 450 Uruguay Science scores Argentina Colombia Finland Hong Kong (SAR of China) 550 0 10 000 20 000 30 000 40 000 2006 per capita GDP in current dollars Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of figures from the Second Regional Comparative and Explanatory Study (SERCE), 2006; and World Bank, World Development Indicators. a Cuba is not included because it does not have a World Bank per capita GDP indicator. Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the E basis of figures from the Programme for International Student Assessment (PISA), 2006; and World Bank, World Development Indicators. Inequality and social exclusion, which are such problematic extra-school factors in the region, are being reproduced by the educational system and are reflected in outcomes and associated opportunities. PISA, SERCE and educational research in general show a clear link between students’ socio-economic and cultural environment and academic performance. In most countries of the region, family socio-economic and cultural environment is at the root of the most significant differences in learning. Figure II.10 shows the distribution by socio-economic and Social Panorama of Latin America • 2010 93 cultural status of academic performance for 15-year-old students in science.3 Most students in the first and second socio-economic and cultural quartiles in countries of Latin America perform below level 2, meaning that they have not developed the basic competencies for performance in this area. Level 2 is the level at which students possess adequate scientific knowledge to provide possible explanations in familiar contexts or draw conclusions based on simple investigations. At level 3, students can identify clearly described scientific issues in a range of contexts, select facts and knowledge to explain phenomena and apply simple models or inquiry strategies. At level 4, students can work effectively with situations and issues that may involve explicit phenomena requiring them to make inferences about the role of science; they can integrate explanations from different disciplines of science, reflect on their actions and communicate decisions using scientific evidence. The students presenting the best performance in science are classified in levels 5 and 6. Unlike the case among students of the third and fourth quartiles in OECD countries, few students in Latin America reach these two levels. Students at level 5 can identify the scientific components of many complex life situations and apply scientific concepts; they can use well-developed inquiry abilities, link knowledge appropriately and bring critical insights to situations. The top-performing students (those at level 6) can consistently identify, explain and apply scientific knowledge in a variety of complex life situations; they clearly demonstrate advanced scientific thinking and use it to develop arguments in support of recommendations. Only 1.3% of all students in the OECD countries attain this level of competency. Although OECD countries also show some variations in educational attainment among students in different quartiles, in all those countries —unlike in Latin America— the vast majority of students attain the expected basic level of competency (level 2 and higher). Figure II.10 LATIN AMERICA (six COUNTRIES) AND OECD (30 COUNTRIES): DISTRIBUTION OF LEVELS OF PERFORMANCE ON THE PISA SCIENCE ASSESSMENT FOR 15-YEAR-OLD STUDENTS BY INDEX OF FAMILY ECONOMIC, SOCIAL AND CULTURAL STATUS, 2006 a (Percentages) 120 100 80 60 40 20 0 20 40 60 Below level 1 Brazil Colombia Level 1 Level 2 Uruguay Level 3 Chile Level 4 Latin America Level 5 Top quartile ESCS Upper-middle quartile ESCS Bottom quartile ESCS Lower-middle quartile ESCS Top quartile ESCS Upper-middle quartile ESCS Bottom quartile ESCS Lower-middle quartile ESCS Top quartile ESCS Upper-middle quartile ESCS Bottom quartile ESCS Lower-middle quartile ESCS Top quartile ESCS Upper-middle quartile ESCS Bottom quartile ESCS Mexico Lower-middle quartile ESCS Top quartile ESCS Upper-middle quartile ESCS Bottom quartile ESCS Lower-middle quartile ESCS Top quartile ESCS Upper-middle quartile ESCS Bottom quartile ESCS Lower-middle quartile ESCS Top quartile ESCS Upper-middle quartile ESCS Bottom quartile ESCS Argentina Lower-middle quartile ESCS Top quartile ESCS Upper-middle quartile ESCS Bottom quartile ESCS Lower-middle quartile ESCS 80 100 OECD Level 6 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of microdata from the PISA 2006 survey. a The distribution of performance levels in Latin America and in the Organization for Economic Cooperation and Development (OECD) refers to the simple average of the weighted mean national achievement levels of the countries participating in PISA 2006. 3 PISA prepares this index using three factors assumed to be related to socio-economic status (OECD, 2008): household purchasing power and the occupational status and educational level of the parents of students participating in PISA tests. Purchasing power is measured by the presence of certain items in the household (e.g., DVD player, dishwasher, desk, personal computer, number of television sets). Occupational status is determined by asking students what each of their parents does for a living; the occupation having the higher status is classified and then converted into a score based on the International Standard Classification of Occupations (ISCO). Educational level of the parents is classified according to the International Standard Classification of Education (ISCED) ranking, using the higher of the rankings between the two parents. 94 Economic Commission for Latin America and the Caribbean (ECLAC) As for gender, girls, on average, perform better in language assessments and boys perform better in mathematics and science evaluations. These differences could suggest that socially imposed differentiated gender roles permeate pedagogical and socialization practices in schools (UNESCO/LLECE, 2008). However, gender gaps in academic outcomes differ among countries (see figure II.11). Costa Rica, Peru and Colombia have the largest gender gaps in favour of boys in math performance in the sixth grade of primary school. In Brazil, boys perform significantly better in mathematics and girls in reading. Along with Brazil, girls in Uruguay, Panama and Cuba show higher levels of reading competency than do boys. Lastly, segmentation between rural and urban areas is dramatic. In almost all of the countries of the region, pupils in urban schools perform significantly better than those in rural schools. The average difference in reading competency scores in the countries participating in SERCE is 44.7 points in favour of urban students. The difference for the math assessment is 36.3 points. Because indigenous groups are more concentrated in rural areas, it could be assumed that many of these groups are caught up in this performance gap. This is corroborated by the cognitive achievement study conducted by the UNESCO Latin American Laboratory for Assessment of the Quality of Education (UNESCO/ LLECE) on the basis of the SERCE 2006 study. All of the countries that included indigenous groups in the assessment showed a negative association between this characteristic 8. and learning outcome. This association is most relevant in learning to read. Controlling for other factors associated with learning (socio-economic context and the characteristics of the school), indigenous sixth-graders will tend to score an average of 17 points lower in reading in Colombia, 24 points less in Costa Rica, 21 points less in Ecuador, 18 in Guatemala and 15 in Peru. Figure II.11 LATIN AMERICA (16 COUNTRIES): AVERAGE MATH AND READING PERFORMANCE BY SEX (GIRLS-BOYS), SECOND REGIONAL COMPARATIVE AND EXPLANATORY STUDY (SERCE) SCORE, SIXTH GRADE, 2006 a Costa Rica Peru Colombia Nicaragua Brazil El Salvador Guatemala Chile Latin America Argentina Paraguay Uruguay Ecuador Dominican Rep. Panama Mexico Cuba -25 -20 -15 -10 -5 0 5 10 15 20 25 Test scores Significant difference in mathematics Significant difference in reading Source: conomic Commission for Latin America and the Caribbean (ECLAC), on E the basis of figures from the Second Regional Comparative and Explanatory Study (SERCE), 2006. a The lighter-coloured bars show differences that are not statistically significant. Acquisition of digital competencies: new kinds of exclusion Another new development is that educational credentials alone are declining in importance among the qualifications for full participation in the economy, society and political life. The penetration of information and communications technologies (ICT) in all corners of society is making attainment of digital competency thresholds a prerequisite for social inclusion, and the pace of change is even more vertiginous than in education. Both trends (in education and in technology) are indeed very closely related. First, the telematics revolution has confirmed the supremacy of human capital in defining an individual’s assets and in making countries more competitive, thus bringing educational systems back to the forefront in promoting production and well-being. Second, educational systems cannot sidestep the challenges of the digital revolution in teaching. Third, they cannot ignore how the new technologies are changing the qualifications required by the labour markets. Last, while there is still no conclusive evidence, it is widely suspected that the confluence of formal education attainments and digital competencies multiplies and enhances knowledge.4 Using ICT in schools is not merely a question of ensuring digital literacy among the population, but also of introducing ICT throughout the teaching and learning process in order to facilitate the acquisition of modern 4 Recognition of this potential positive synergy is reflected, inter alia, in how hard it now is to find publications on the status of education at a national or international level that do not refer extensively to the incorporation of digital equipment into teaching practices, and to the levels of digital competency that pupils bring to the classroom. But unlike for educational attainment, there are still no standardized measurements of levels of digital competency that could track changes in the demand for these skills on the market. It could be that the speed of change, combined with the difficulty of measuring these factors, has so far made it impossible to devise a standard measurement for levels of digital competency that would guide national institutes of statistics in gathering the requisite data. Social Panorama of Latin America • 2010 5 Unweighted average on the basis of special processing of household surveys reconciled by the Observatory for the Information Society in Latin America and the Caribbean (OSILAC): Brazil (2008), Chile (2006), Colombia (2008), Costa Rica (2008), Bolivarian Republic of Venezuela (2008), El Salvador (2007). Guatemala (2006), Honduras (2008), Mexico (2008), Paraguay (2008), Peru (2008), Plurinational State of Bolivia (2007) and Uruguay (2008). See Kaztman (2010). Figure II.12 LATIN AMERICA (11 COUNTRIES): DIFFERENCE IN THE PROPORTION OF HOUSEHOLDS WITH AN INTERNET CONNECTION IN THE HIGHEST AND LOWEST INCOME QUINTILES BY PRESENCE OR ABSENCE OF HOUSEHOLD MEMBERS AGE 13-19, AROUND 2008 a (Percentages) 90 80 70 60 50 40 30 20 Uruguay (2009) Brazil (2008) Chile (2006) Costa Rica (2008) Mexico (2007) Peru (2009) Panama (2007) Ecuador (2009) Paraguay (2008) 0 El Salvador (2008) 10 Honduras (2007) competencies and improve overall student achievement (United Nations, 2010). The skills involved in mastering ICT are an increasingly important part of the set of core assets that people need in order to take advantage of new opportunities in the economy, the State and the community, and for full participation in today’s society (Kaztman, 2010). However, just as ICT create an opportunity for equity and social integration, the current distribution of resources and competencies in the societies of Latin America is such that the very dynamics of ICT penetration can lead to vicious circles, widening existing gaps or superimposing new ones and contributing to societal polarization. The digital divide in Latin America is, in part, rooted in unequal access stemming from enormous differences in the availability of equipment. But it also has to do with how pupils use and can benefit from such equipment. At this other level, inequality is evidenced in different levels of ability to use ICT productively and take advantage of their potential for developing the competencies and skills that are increasingly necessary for integration in the globalized world (Sunkel and Trucco, 2010). The burgeoning, market-driven penetration of ICT in the region is creating substantial gaps in access to equipment by social class. While approximately 55% of the households in the highest income quintile (average for 13 countries of Latin America) have a computer connected to the Internet, only 26% of the households in the first income quintile do.5 In general, studies show that despite this segmented access to technology, children and young people are entering the world of technology in greater numbers. In households with 13-to-19-year-olds, connectivity is rising at a faster rate than in households where all members are over 20. Identifying different connectivity access rates by generation leads to an examination of how much this weakens or reinforces class-based gaps (Kaztman, 2010). A look at the figures shows that in the countries of the region where technology is more market-driven (such as Brazil, Chile and Uruguay) the class gaps for younger-generation users are not narrowing. They are widening (see figure II.12). In Uruguay, for example, the connectivity gap between households with younger members in the highest and lowest quintiles is more than 80 percentage points. In households without young people the gap is less than 40 percentage points. 95 Households with 13-to-19-year-olds Households with members over 20 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special processing of household surveys reconciled by the Observatory for the Information Society in Latin America and the Caribbean (OSILAC); and R. Kaztman, “Impacto social de la incorporación de las TIC en el sistema educativo”, Políticas sociales series, No. 166 (LC/L.3254-P), Santiago, Chile, ECLAC, 2010. a Countries shown in order of the percentage of households with Internet connection in each country. The fact that access is available elsewhere than at home brightens this pessimistic picture of unequal opportunities to acquire digital competencies. Figure II.13 shows the differences between the highest and lowest quintiles in terms of percentage of Internet users, regardless of the place where they access equipment and the Internet. The relative intensity of the digital gaps changes for both groups. In 4 of the 11 countries studied (Chile, Costa Rica, Mexico and Uruguay), the digital gap between the poorest and wealthiest quintiles of the population of 13-to-19-year-olds is narrower than for the population age 20 or older. In the other seven countries, the digital gap between socio-economic levels is wider for the younger group. The school system has been called to lead the way in policies for achieving mass access to, training in and use of the new digital technologies, precisely because of its ability to counteract underlying inequalities. But the school system has not been the only door to technology for the lower-income segments of the population. Neighbourhood cybercafés have also played a significant role, especially in countries with greater purchasing power. Despite efforts to offset the underlying social inequalities stemming from the market-driven penetration of such equipment, the school system has not had much influence. The only clear signs of an impact are in Chile (see figure II.14). 96 Economic Commission for Latin America and the Caribbean (ECLAC) Figure II.13 LATIN AMERICA (11 COUNTRIES): DIFFERENCE IN THE PROPORTION OF INTERNET USERS IN THE HIGHEST AND LOWEST INCOME QUINTILES BY AGE GROUP, AROUND 2008 a (Percentages) 80 70 60 50 40 30 20 Uruguay (2009) Brazil (2008) Chile (2006) Costa Rica (2008) Mexico (2007) Peru (2009) Panama (2007) Ecuador (2009) Paraguay (2008) Honduras (2007) 0 El Salvador (2008) 10 Users age 13-19 Source: Economic Commission for Latin America and Users 20 and older the Caribbean (ECLAC), on the basis of special processing of household surveys reconciled by the Observatory for the Information Society in Latin America and the Caribbean (OSILAC); and R. Kaztman, “Impacto social de la incorporación de las TIC en el sistema educativo”, Políticas sociales series, No. 166 (LC/L.3254-P), Santiago, Chile, ECLAC, 2010. a Countries shown in order of the percentage of households with an Internet connection in each country. Figure II.14 LATIN AMERICA (11 COUNTRIES): DIFFERENCE IN THE PROPORTION OF 13-TO-19-YEAR-OLD INTERNET USERS IN THE HIGHEST AND LOWEST INCOME QUINTILES BY PLACE OF CONNECTION, AROUND 2008 a (Percentages) 100 integration than do young people who can access the Internet at home. This leads us to another dimension of the digital divide, one that is not related to access but rather to modes and intensity of use. A recent study (Sunkel, Trucco and Möller, 2010) profiled young ICT users in three countries on which PISA 2006 information was available (Chile, Colombia and Uruguay) on the basis of what they reported using computers and the Internet for, and how intensely. The typology shows that there are four types of user, differentiated on the basis of how intensely they use the technology and the degree of specialization they have acquired. One group is “distant” users, that is, young people who use the computer infrequently for a variety of tasks. Another group is the “Web surfers” who use the computer mainly to browse the Internet and to collaborate with groups, download software or music and communicate (e-mail and other media). A third group is the “specialized” users. These young people more frequently use software to write documents or create spreadsheets, graphic presentations, programs or educational software. The last group comprises “multifunctional” users, who frequently engage in both technical and recreational activities. It is this type of user that is making the most complete use of the potential opportunities provided by digital technologies (Sunkel and Trucco, 2010). Figure II.15 CHILE, COLOMBIA AND URUGUAY: PROPORTION OF 15-YEAROLDS BY TYPE OF ICT USE AND COUNTRY OF ORIGIN, 2006 a Technical use 80 Specialized 60 32.1 12.5 40 Multifunctional 24.5 22.3 28.2 20.6 20 Internet use Honduras (2007) El Salvador (2008) Paraguay (2008) Ecuador (2009) Peru (2009) Panama (2007) Mexico (2007) Costa Rica (2008) Chile (2006) Brazil (2008) -20 Uruguay (2009) 0 Home School Commercial establishment Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special processing of household surveys reconciled by the Observatory for the Information Society in Latin America and the Caribbean (OSILAC); and R. Kaztman, “Impacto social de la incorporación de las TIC en el sistema educativo”, Políticas sociales series, No. 166 (LC/L.3254-P), Santiago, Chile, ECLAC, 2010. a Countries in order of percentage of households with an Internet connection. The problem with access opportunities at commercial establishments (and even in educational establishments in some cases) is the low intensity at which individuals can make use of the technology. Because of the cost, or because of access conditions at educational establishments, those who use these locations normally do so for shorter periods of time and so have fewer possibilities for developing digital competencies for social and productive 23.9 27.3 28.9 25.4 Distant Chile 36.3 18 Web surfers Colombia Uruguay Source: G. Sunkel, D. Trucco and S. Moller, “Aprender y enseñar con tecnologías de la información y las comunicaciones (TIC) en América Latina. Potenciales beneficios”, Políticas sociales series, No. 169 (LC/L.3291-P), Santiago, Chile, ECLAC, 2010. a The construction of the ICT use indicators meets methodological and statistical requirements set out in chapter 16 of the PISA 2006 Technical Report (OECD, 2009). The analysis indicates that there are structuring variables, such as socio-economic and cultural differences and student gender, that define user types. Males are more likely to be multifunctional users; females are more likely to be distant users. Young people from more privileged social groups have more options for developing multifunctional digital competencies. Social Panorama of Latin America • 2010 97 C. The transition from education to employment and the intergenerational reproduction of unequal productive opportunities and access to well-being In a context of unequal access to educational opportunities, the link between education and employment reproduces social inequalities and can worsen them. Stratified education coupled with self-regulating labour markets segmented by level of productivity cement the gaps passed on from generation to generation throughout the life cycle. Education is segmented by socioeconomic conditions and educational levels in the household of origin, and the return on that education also reproduces the gaps in access to decent jobs and well-being. The rates of return on education rise along with years of schooling, but the biggest leaps are upon completing secondary school, upon beginning tertiary education and, above all, upon completing tertiary education. Education levels being equal, the rates of return (measured by labour income) are lower for females than for males, and they are lower for informal workers than for formal workers; that is tangible evidence of the patterns of exclusion existing in the workplace. This edition of Social Panorama focuses on the lifecycle period from birth to 29 years of age, encompassing childhood, adolescence and young adulthood. It is during this part of the life cycle that people transition from the intensive acquisition of knowledge and development of skills to productive integration into society; from dependence to economic autonomy; from living in the household of origin to forming one’s own household. This transition determines, to a large extent, the success (or rather, the skills and potential) that the new generations will have in being full members of society throughout their adult lives, free to pursue their life plans, participate as citizens and contribute to development. This formative period determines whether social inequalities will be perpetuated or whether they will lessen from one generation to the next. The disparity in skills development relates not just to educational attainment but also to self-regulating labour markets in their role as “factories of segmentation” by level of productivity, access to well-being and full enjoyment of social entitlements. Structural inequality (as replicated from the productive structure, markets and institutions) thus compounds intergenerational inequalities, with gaps becoming further entrenched throughout the life cycle and propagated from one generation to the next. Accordingly, the approach adopted must be a comprehensive one, addressing structures and institutions as well as the life cycle. Education is a key consideration here, as it prepares individuals to be full participants in all spheres of society throughout their adult life. One of those spheres, among various others, is the workplace. ECLAC has conclusively documented that, in the current situation of most countries of the region, individuals who do not complete secondary education are exposed to a high level of social vulnerability since their labour-derived earnings will tend to be low as a reflection of low educational attainment; and they will be at high risk of falling into poverty and becoming excluded or marginalized if they have to work in self-regulating labour markets without any minimum assurances or labour rights. Against this backdrop there is a wide-ranging debate and considerable concern about the link between education and employment. The bridge between the two generally leads from dependence to autonomy, from acquisition of knowledge and skills to their use in adult life, and from conditions in the household of origin to those in the individual’s own household. It is known that the level of education attained has a strong bearing on the kind and quality of employment that can be accessed, but young people seeking to enter the 98 Economic Commission for Latin America and the Caribbean (ECLAC) world of work face particular obstacles. How gaps entrenched in the educational system are reproduced when people enter the world of work is discussed below. As ECLAC and UNESCO noted as long ago as 1992, education and employment are linked as basic pillars of changing production patterns with equity (ECLAC/ UNESCO, 1992). To put it another way, it is impossible to fight social inequality without achieving equity in educational attainment and then turning it into jobs with smaller gaps in income and in access to social protection. Unfortunately, when there is unequal access to educational opportunities and productive structures are exclusionary, that link between education and employment reproduces social differences and inequities and can even amplify them. As seen above, this holds true for the countries of the region. In Latin America, employment is still the mainstay of social inclusion. It provides differing degrees of access to well-being via the autonomous (or heteronomous, in the case of wage workers) generation of income. Labour income is still the principal source of household resources, Minimum thresholds for well-being, credentials and educational devaluation Figure II.16 LATIN AMERICA (18 COUNTRIES): YEARS OF SCHOOLING REQUIRED TO BE LESS LIKELY TO LIVE IN POVERTY OR TO EARN ABOVE-AVERAGE LABOUR INCOME AMONG THE EMPLOYED POPULATION AGE 20-29, AROUND 2008 a (Years of schooling) 25 20 10 10 15 15 15 15 16 16 15 13 11 12 12 12 12 12 11 11 11 11 12 12 Paraguay 5 8 9 16 13 Brazil 10 12 17 17 Costa Rica 12 13 16 14 14 Argentina b Bolivia (Plur. State of) Colombia 15 15 13 13 12 Years of schooling needed to have above-average labour income Modal value Dominican Rep. Peru Chile Panama Ecuador Mexico Venezuela (Bol. Rep. of) Guatemala Uruguay El Salavdor Honduras 0 Nicaragua A few decades ago, a relatively low percentage of the population managed to access educational systems and reach significant milestones (completion of secondary education, tertiary education). This high concentration of (scarce) educational capital worked in favour of a high return on education because having completed primary education was enough to access good jobs with wages and benefits, mainly in the primary and secondary sectors. Mass access to and completion of primary education in the 1980s and 1990s, plus the generalization of secondary education (chiefly the lower cycle), have led to creeping devaluation. These levels of educational attainment are no longer enough to reach social positions with incomes that offer an easy escape from poverty, let alone above-average labour income. ECLAC has repeatedly noted that completion of secondary education is the minimum educational threshold in the region for ensuring a future free of poverty (ECLAC, 2000; ECLAC/OIJ, 2008 and 2004). Attaining this level of education is crucial for acquiring the basic skills needed for development and lifelong learning in a globalized, democratic world. It is also a determining factor in the attainment of a baseline well-being that will shatter the mechanisms that reproduce inequality. Otherwise, these mechanisms will impact that individual’s children (see figure II.16). Years of schooling needed 1. accounting for some 80% of total household income (ECLAC, 2008a). Employment is still the basic connection with social protection systems —specifically, access to social security and health systems. This is despite the strengthening, in some countries of the region, of non-contributory inclusion and protection mechanisms. Noteworthy among these mechanisms is the solidarity component of financing (and hence accessing) basic social security and preventive health-care benefits, as well as policies and programmes geared towards fighting poverty through social policies targeting lower-income sectors that are not integrated in the labour market (ECLAC, 2009; ECLAC, 2010a). Work also enhances the feeling of belonging. For many, being outside the world of work is the most dramatic way to “not belong”, to be excluded both socially and symbolically. This feeling is particularly marked among young people because employment is the main road to integration in society. It facilitates interpersonal development, self-esteem and mutual recognition in groups with shared characteristics (ECLAC/OIJ, 2008). Years of schooling needed to have less-thanaverage likelihood of falling into poverty 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. a Employed persons working 20 or more hours per week. b Urban areas. Social Panorama of Latin America • 2010 99 Although trends in labour market incorporation and the quality of employment depend on many different factors and on just how the labour market is segmented in each country (inter alia, gender differences, the weight of the informal sector and the degree of development of social protection systems), the relevance of educational attainment in the structure of labour supply and demand is clear. So, and especially for females, higher rates of participation in the labour force are found precisely among those who have completed secondary education and have some kind of post-secondary education. Because a certain percentage of young people is still in school, participation is slightly higher for those who left school early and for those who have already acquired some kind of credential (see figure II.17 (A and B) and the breakdown by country in table II.A-7). The trend is much clearer among the adult female population: the higher the level of education, the greater the proportion of participation in the labour force. For men, figure II.17.B shows a higher proportion of labour market participation, with a significant group starting to work quickly after leaving school early (with or without completing primary school). As the primary source of family income, men are often forced by economic necessity to leave school early (see sections above), precisely to enter the labour market. But this higher participation rate does not mean access to good-quality employment, as discussed in the following section. Figure II.17 LATIN AMERICA (SELECTED COUNTRIES): PARTICIPATION AND UNEMPLOYMENT RATES, AGES 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages) B. Male participation rates A. Female participation rates 100 100 70 80 70 64.3 68.3 60 45.4 80.3 72.8 50 48.2 47.1 39.6 80.2 78.2 76.4 60 52.4 50 87.0 83.3 80.6 80 40 89.9 90 90 40 30 30 20 20 10 10 0 0 Incomplete Complete Incomplete Incomplete Complete Incomplete Complete primary primary lower upper secondary tertiary university secondary secondary Age 15-29 Age 30-64 Incomplete Complete Incomplete Incomplete Complete Incomplete Complete primary primary lower upper secondary tertiary university secondary secondary Total 15 and older Age 15-29 C. Female unemployment rates Age 30-64 Total 15 and older D. Male unemployment rates 25 25 20 20 15.1 15 10.5 10 5 0 15 9.6 4.4 10 8.8 8.3 7.9 5.9 Incomplete Complete Incomplete Incomplete Complete Incomplete Complete primary primary lower upper secondary tertiary university secondary secondary Age 15-29 Age 30-64 15 and older 6.1 6.5 5 4.9 Total 0 3.7 5.7 5.5 4.5 4.2 Incomplete Complete Incomplete Incomplete Complete Incomplete Complete primary primary lower upper secondary tertiary university secondary secondary Age 15-29 Age 30-64 Total 15 and older 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. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). 100 Economic Commission for Latin America and the Caribbean (ECLAC) Those who have the most common level of education —incomplete or complete secondary education— have the hardest time finding work (see figure II.17 (C and D)). Sixty-four per cent of young people have an incomplete secondary education (upper or lower cycle) or have completed secondary education but have no further schooling. For the adult population, the figure is 44%, with 36% of the adult population having completed primary education or less. There is obviously a tipping point for labour market participation that could be related (especially for the younger generations) to changing expectations as to the kind of employment they can aspire to: jobs that require higher degrees of specialization but do not seem to be in ample supply. 2. Unemployment impacts young people the most, with an average unemployment rate of 11.8% versus 4.1% for adults. It is even larger for young females. Although the distribution of unemployment rates shows similar trends for males and females, they are higher for young females at all levels of educational attainment. Evidence from several periods shows that completion of the primary cycle and, later, secondary education has become relatively devalued on the labour market. This is seen in terms of both quantity —demand relative to the supply of labour at these levels of education— and price, with wages declining relatively over time (see tables II.A.7-14). This can be seen especially among the young population (ECLAC/OIJ, 2004 and 2008). Education and quality of employment The quality of labour market participation is highly subject to the level of education attained. This becomes more apparent with conclusion of higher cycles of education. This link between education and quality of employment is seen in levels of participation in the formal economy (or in medium- and high-productivity sectors), in access to social protection systems and in income, as discussed below. First, the higher the level of education attainment, the higher the proportion of wage-earners. Contrary to some hypotheses that identify independent work as prevalent in more dynamic, modern and globalized labour markets with a labour force that values autonomy and hence chooses such occupations, evidence seems to show that in Latin America independent work is associated more with the informal labour market, low productivity, low levels of qualification and lower income (for further information, refer to ECLAC, 2009). Wage labour employment is higher among the young labour force (75% of those employed) than among adults (just above 60% of the employed age 30-64). This latter trend would, in part, be due to the higher likelihood of independent work —the level of education attainment being the same— later in the life cycle. But it is also true that in all of the countries self-employment is the only option open to a significant portion of the lessqualified adult population for generating labour income (see table II.A-11). Second, an increase in educational attainments is inversely related to employment in the informal or lowproductivity sector (see figure II.18.A), which is to a certain degree also related to the potential for employment as a wage-earner. Therefore, if 47% of the employed population age 15 and older works in the informal sector, the percentage rises to 74% for those who did not complete primary education and falls to 64% for those who did, 32% for those who completed secondary education and just 14% for those who completed education at a university level. The adult labour force is more likely than young people to be inserted in low-productivity sectors (48.4% of employed adults versus 39.7% of employed young people). This, too, is closely linked to access to social protection systems associated with employment: the higher the education level of the workforce, the greater the proportion of those who belong and pay into social security. While some 43% of the total workforce participates in social security, only 21% of workers who completed a few grades of primary education are protected by such systems, compared with 69% of those who have some kind of post-secondary education. There is also marked dissimilarity in social security system coverage (in terms of the percentage of the workforce enrolled), ranging from less than one fifth (Paraguay) to more than two thirds (Costa Rica). And the lower the general enrolment in social security, the greater the differences in enrolment based on level of education (see table II.A-13). Lastly (and expectedly), there is a strong link between the level of educational attainment and labour income. While the average income for the employed labour force in the region is a little more than US$ 660 (at 2000 purchasing power parity prices), those who completed primary education or less earn just US$ 350, on average. Those who attained post-secondary education average more than US$ 1,400 per month (see figure II.18.B). Social Panorama of Latin America • 2010 101 Figure II.18 LATIN AMERICA (SELECTED COUNTRIES): INFORMALITY AND MONTHLY LABOUR INCOME FOR THE EMPLOYED POPULATION AGE 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages) A. Informality rates by level of education B. Average monthly labour income (in 2000 PPP dollars) (percentages) 100 2 500 90 80 70 2 000 73.5 1 964 64.4 60 51.8 50 1 500 46.1 47.0 1 086 1 000 40 31.7 30 21.2 20 500 13.6 307 424 500 548 686 666 10 0 0 Incomplete Complete Incomplete Incomplete Complete Incomplete Complete primary primary lower upper secondary tertiary university secondary secondary Age 15-29 Age 30-64 Total Incomplete Complete Incomplete Incomplete Complete Incomplete Complete primary primary lower upper secondary tertiary university secondary secondary 15 and older Age 15-29 Age 30-64 Total 15 and older 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. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). 3. Internal rates of return on education A classic way to show the relationship between educational attainments and income is to calculate the internal rates of (private) return on education, showing the percentage increase in labour income according to additional years of education, educational cycles completed or other ways of specifying an individual’s accrued educational capital. Doing so provides a snapshot of the “yield” on education in terms of greater labour income (usually, wages), taking into account several factors involved in this relationship.6 Noteworthy among the factors to bear in mind when assessing the private return on education are those related to labour market segmentation. Taken into consideration here were three major factors that distinguish between dual labour markets and those that operate in a parallel (albeit not separate) fashion and have a significant impact on educational returns. These factors are employment in low-productivity sectors, sex and area of residence (see box II.1 and the results of the regression analyses in table II.A-15). 6 It is not being said here that the purpose of education, either exclusively or primarily, is to achieve the rates of return that years of schooling produce in competitive labour markets. It is worthwhile showing, however, to what extent democratization of educational opportunities is crucial to ensuring people’s right to exercise their positive liberty, i.e. to pursue life projects on the basis of, inter alia, timely development of their skills. That development of skills is necessary but not sufficient in and of itself, inasmuch as labour markets should be subject to regulatory policies and guidance to ensure full enjoyment of labour rights and social protection. In this regard, the State should play a core role in preventing educational differentiation from condemning to exclusion those not achieving the educational attainments indicated. Hence, productivity increases should not be understood solely in terms of return on learning but also in terms of the possibility of a society —through the State and the tax system— redistributing resources and extending social protection to the most disadvantaged sectors. 102 Economic Commission for Latin America and the Caribbean (ECLAC) Box II.1 PROCEDURE FOR ESTIMATING INDIVIDUAL RETURNS ON EDUCATION The origins of the empirical analysis showing the influence of schooling on income formation date from the late 1950s and the 1960s. The work of Jacob Mincer (1958 and 1962) and Gary Becker (1964) generated evidence on the income differential by sex and educational background. The classic study positing a positive relationship between schooling and income was conducted by Mincer in 1974; in it, he links the natural log of income with the number of years of study and experience, through the following equation: (1) where parameter β0 is the natural log of the income of an individual without any schooling, while β1 is the percentage increase in income for each additional year of education completed, i.e., the rate of return. Various studies on this subject have been conducted during the last few decades; in the case of Latin America the available results show the positive effect of schooling in determining labour income (Psacharopoulus and Chu, 1992; ECLAC, 2002). There is also abundant literature on the problems deriving from selection bias in estimating these models, as well as on the problems arising in interpreting the results when instrumental variables designed to correct them are incorporated (Kling, 2000). The results presented in the 20012002 edition of Social Panorama were The variable Sch represents the number of years of schooling of each individual; b is the total number of years corresponding to the basic cycle; s is the number corresponding to the secondary cycle; db is a binary variable that has a value of 1 when an individual has a number of years of schooling equal to or greater than b; ds is equal to 1 when an individual has s or more years of schooling, while the potential experience is obtained by subtracting from the reported age the age of entry into the formal educational system and the accumulated years of schooling. Equation (2) corresponds to an additive effects model, so that the rate of return for a given level of education is calculated by adding together the values of the parameters estimated in previous cycles. Thus, β1 corresponds to the baseline parameter and is equivalent to the rate of return for primary schooling, while (β1+ β2) corresponds to the secondary cycle of education and (β1+ β2+ β3) corresponds to individuals who have completed higher studies. Variables dgender, darea and dsector are binaries with a value of 1 if the individual is male or lives in an urban area or works in the formal sector. The results of the regressive analyses presented herein are for equation (2), but separate results were generated for generated by adjusting a function for estimating the increase in income, that is, the return on a larger number of years of schooling. The average rate of return was calculated on the basis of equation (2), which was applied in order to estimate the differences generated between each of the education cycles (basic, secondary and higher): (2) males and females, for urban and rural areas and for formal and informal sector workers. The estimation method used was minimum weighted squares, and the expansion factor associated with each observation was included in the calculation algorithm. The sampling refers to persons age 20 and older who reported being wage-earners who usually work more than 19 hours per week and who earned some income from work during the survey period. Monthly income (per hour worked, assuming a standard 48-hour work week) was expressed in local currency at average prices for 2002. Source: Economic Commission for Latin America and the Caribbean (ECLAC), Social Panorama of Latin America 2001-2002 (LC/G.2183-P), Santiago, Chile, 2001. United Nations publication, Sales No. E.02.II.G.65. Generally speaking, primary education has a return (or income increment) of 4.7% per year of education (simple average of 18 countries), which rises to 7.0% per additional year in the secondary cycle and 14.9% per each year of post-secondary education. Although this trend is general across countries, the return on each education cycle differs widely from one country to another in terms of effective increment. As table II.2 shows, the return ranges from 1% to 8.7% per additional year of primary education (Costa Rica and Honduras), from 2.9% to 12.4% per additional year of secondary education (Plurinational State of Bolivia and Guatemala) and from 8.4% to 25.5% per additional year of postsecondary education (Argentina and Brazil). Perhaps the most striking examples are the Plurinational State of Bolivia and Peru, where the return on secondary education is lower than for primary education and could become a disincentive for completing the 12 years of education that, as seen above, is the minimum threshold for attaining well-being.7 The differences in income between labour market segments should also be weighed. It is not that rates of return differ significantly across labour segments, but rather that income levels and, therefore, income trajectories do. The results shown below reflect the application of separate models for the formal sector, the informal sector, males, females and urban and rural areas, without controlling for other segmentations involved.8 7 8 This is not the case in the Plurinational State of Bolivia if the rates of return are calculated for the informal sector only, nor in Peru if only women are considered. These models based on labour market segments give rise to the curves in figure II.19, but the results are not shown here for space reasons. The segmentation variables are considered jointly in the general model summarized in tables II.2 and II.A-15. Social Panorama of Latin America • 2010 103 Table II.2 LATIN AMERICA (18 COUNTRIES): INTERNAL RATES OF RETURN ON EDUCATION AND RELEVANCE OF OTHER FACTORS IN WAGE INCREMENT a (Percentages of increment of base wage) Internal rate of return Country Year Argentina (urban areas) 2006 Primary education Weight of other factors Secondary education Post-secondary education 7.6 8.3 3.0 Living in urban area … Being male Inserted in formal sector 15.8 47.8 Bolivia (Plurinational State of) 2007 5.1 2.9 * 16.5 59.2 18.3 30.5 Brazil 2008 6.7 9.2 25.5 18.7 24.5 26.9 Chile 2006 3.0 7.5 19.4 7.4 20.7 24.3 Colombia 2008 5.1 5.6 * 14.0 7.7 11.8 40.8 Costa Rica 2008 1.0 5.6 16.0 7.1 * 23.0 29.5 Dominican Republic 2008 4.4 4.5 * 18.2 9.1 21.7 30.3 Ecuador 2008 4.3 6.0 10.8 12.7 17.6 28.4 El Salvador 2004 3.7 7.1 17.3 13.9 10.8 23.1 Guatemala 2006 7.5 12.4 14.8 8.0 15.7 9.7 Honduras 2007 8.7 10.9 14.4 44.4 Mexico 2008 4.5 9.0 14.8 21.4 0.2 * 17.6 67.1 33.2 Nicaragua 2005 5.2 7.9 14.0 10.2 15.6 21.5 Panama 2008 5.3 6.1 * 12.3 11.1 18.7 55.4 Paraguay 2008 5.5 7.7 * 16.6 10.9 30.5 Peru 2008 6.3 3.7 11.0 25.2 32.7 43.1 Uruguay 2008 2.9 8.7 14.9 -3.1 21.5 35.8 Venezuela (Bolivarian Republic of) 2008 Simple average 4.1 * 2.9 3.6 9.8 … 14.5 36.0 4.7 7.6 14.9 17.6 18.3 34.1 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries. a An asterisk is used to denote instances in which the regression is not statistically significant at 5%. First, there is an obvious segmentation by worker gender (see figure II.19.A). Although the rates of return are higher for females, mainly in secondary education but also at the tertiary level, their levels of income are consistently lower than for men: labour income rises an average of slightly more than 17% just for being male. Second, the differences between urban and rural labour markets lead to different rates of return on education. They are higher in rural areas, especially for post-secondary education. These significant differences in returns mean that although the baselines (wage levels without education or with just a few years) favour urban areas, the increment is larger in rural areas, especially at higher levels of education attainment. The shortage of qualified workers in rural areas is one of the reasons for their income being, on average, higher than in cities (see figure II.19.B). In any event, and considering that in rural areas the less educated account for a higher proportion of the working population, the employed earn, on average, 13.9% more income just for participating in urban labour markets.9 Last, the greatest differences in the rates of return appear when the labour markets are segmented along formal and informal lines. Figure II.19.C shows that labour income trajectories by years of schooling are clearly unequal: while at lower levels of education the wage differences do not exceed 10% to 12%, at higher levels the wage in the formal sector can be 80% higher than in the informal sector with the same level of qualification. On average, employment in the formal economy yields an income that is 34% higher than in the informal economy. 9 There are striking differences between countries. In the Plurinational State of Bolivia and in Honduras, the income increment is 40% more in urban areas. The differences are minimal in Costa Rica and Uruguay, and in the latter even seem to favour rural labour markets. 104 Economic Commission for Latin America and the Caribbean (ECLAC) Figure II.19 LATIN AMERICA (SELECTED COUNTRIES): INCOME TRAJECTORY BY YEARS OF SCHOOLING, WAGE-EARNERS AGE 20 AND OLDER WORKING 20 OR MORE HOURS PER WEEK, BY SEX, GEOGRAPHIC AREA AND LABOUR MARKET FORMALITY a (Wages with zero years of schooling in the comparison category with the highest income=100) A. Wage trajectories for men and women 1 300 Tertiary education Postgraduate 1 100 1 000 900 800 700 600 500 400 300 200 100 0 Secondary education Primary education 1 200 Wage index (Zero years of education in urban areas=100) Wage index (Zero years of education among males=100) Secondary education Primary education 1 200 B. Wage trajectories in urban and rural areas 1 300 Tertiary education Postgraduate 1 100 1 000 900 800 700 600 500 400 300 200 100 0 1 2 3 4 5 6 7 8 9 0 10 11 12 13 14 15 16 17 18 19 20 21 0 1 2 3 4 5 6 Number of years of schooling Males 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Number of years of schooling Females Urban areas Rural areas C. Wage trajectories in the formal and informal sector 1 300 Primary education Wage index (Zero years of education in formal sector=100) 1 200 Secondary education Tertiary education Postgraduate 1 100 1 000 900 800 700 600 500 400 300 200 100 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Number of years of schooling Formal sector Informal sector 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. a Simple average trajectory for each segment of the labour market, by country. The trajectory within each segment was calculated using a separate model that does not control for the other segmentations. Despite the persistent labour segmentation owing to ascriptive factors such as gender, geography and levels of productivity, educational expansion has also increased the proportion of intermediately qualified workers who are paid sufficiently (although unemployment is also higher among them). Concentrations of labour income are therefore lower. Examination of the labour Gini coefficient by age group reveals some positive data. What table II.3 shows is that among all employed age groups, the lowest Gini coefficient (both for labour income in general and for wage income in particular) is among young people. This could indeed be because education attainment for this age group as a whole is higher. Educational expansion increases the proportion of the economically active population with average levels of qualification and pay, increasing the total income and wages distributed in the labour market. Social Panorama of Latin America • 2010 105 Table II.3 LATIN AMERICA (18 COUNTRIES): CONCENTRATION OF LABOUR AND WAGE INCOME AMONG WORKERS IN DIFFERENT AGE GROUPS (Gini coefficient) Workers age 15-29 Country Workers age 30-39 Workers age 40-49 Workers age 50-64 Year All workers Wage-earners All workers Wage-earners All workers Wage-earners All workers Wage-earners Argentina (urban areas) 2006 0.39 0.35 0.41 0.37 0.48 0.40 0.49 0.41 Bolivia (Plurinational State of) 2007 0.61 0.39 0.55 0.41 0.58 0.41 0.67 0.48 Brazil 2008 0.47 0.38 0.51 0.45 0.56 0.50 0.63 0.54 Chile 2006 0.45 0.41 0.52 0.47 0.54 0.48 0.57 0.49 Colombia 2008 0.45 0.37 0.49 0.44 0.53 0.48 0.58 0.51 Costa Rica 2008 0.34 0.31 0.43 0.37 0.50 0.42 0.48 0.43 Dominican Republic 2008 0.53 0.38 0.50 0.41 0.53 0.48 0.54 0.50 Ecuador 2008 0.47 0.33 0.49 0.37 0.54 0.41 0.56 0.45 El Salvador 2004 0.48 0.37 0.50 0.43 0.54 0.45 0.60 0.50 Guatemala 2006 0.57 0.37 0.57 0.43 0.64 0.48 0.65 0.51 Honduras 2007 0.57 0.45 0.56 0.46 0.60 0.51 0.64 0.56 Mexico 2008 0.52 0.43 0.54 0.44 0.58 0.47 0.66 0.51 Nicaragua 2005 0.55 0.38 0.52 0.45 0.56 0.48 0.57 0.45 Panama 2008 0.44 0.33 0.44 0.35 0.49 0.41 0.55 0.45 Paraguay 2008 0.51 0.34 0.49 0.34 0.55 0.40 0.63 0.50 Peru 2008 0.59 0.40 0.56 0.44 0.57 0.48 0.61 0.50 Uruguay 2008 0.41 0.36 0.45 0.40 0.49 0.43 0.52 0.45 Venezuela (Bolivarian Republic of) 2008 0.32 0.28 0.33 0.30 0.35 0.31 0.38 0.32 0.48 0.37 0.49 0.41 0.53 0.44 0.57 0.48 Simple average Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys conducted in the respective countries. D. Key factors for fighting inequality from within the educational system: progress and challenges Education policy must dovetail with other social promotion and protection measures if inequality in the intergenerational transmission of educational opportunities is to be successfully reversed. There are key intervention factors in the field of education. One of them is extending early childhood education coverage. Another is lengthening the school day at the primary level. This is particularly important for students who do not have an appropriate educational climate or place for studying at home. Incorporating digital technologies into education is seen as a critical opportunity in the battle for equity. Conditional cash transfer programmes for families can bolster timely education progression and help prevent dropouts, extending achievements to the most disadvantaged sectors of society. The supply of training for work is also essential, and the formal education system should coordinate with informal training programmes and the productive world. One of the main challenges in higher education is how to reconcile education quality with expanding access to traditionally excluded sectors. 106 Economic Commission for Latin America and the Caribbean (ECLAC) Addressing inequality in the region is not an easy task. Nor can education be expected to solve problems involving multiple factors. That is why education policy must be linked with other social promotion and protection measures in an integrated approach that will help reverse inequality in the intergenerational transmission of educational opportunities. It is important for education policy to provide for investing in schools. What is needed is educational infrastructure and resources, improved teacher training 1. and a better teaching environment, enhanced school management and better curriculum content at all levels of education (ECLAC, 2010b). Public education for young people should extend beyond the end of the compulsory education cycle to ease the transition into the labour market and help reduce inequalities in the return on education throughout life. Set out below are key factors in education that can make a significant contribution to reducing inequality in the age bracket that is the focus of this edition of Social Panorama. Early entry: early childhood and preschool education ECLAC has proposed that broadening early childhood education coverage should be a pro-equality policy priority in the region (ECLAC, 2010a). Preschool education recently became a top public policy issue in the region because of its key role in providing basic care for children, especially for families in a vulnerable socio-economic environment. Publicly funded institutional care for children under 6 has well-documented benefits (UNESCO, 2010). Such care facilitates the integration of females into the labour market, fosters their autonomy and increases household resources. For the young cohort, it provides an opportunity for young mothers, giving them more free time to continue studying and avoid breaking their own education cycle. In-school meals and health care, as well as early stimulation, offset deficiencies at home. Such care also has a positive effect on future cognitive, psychomotor and attention-span development and activity levels and has a substantial impact on the child’s prospects in subsequent education cycles. It is during the early years of life that personality, intelligence and social behaviour develop most quickly. Quality of care and educational strategy must also be taken into consideration (ECLAC/OEI, 2010). Expanding the supply of education at the preschool (3-5 years of age) and early childhood (birth to 3 years) levels, along with appropriate policies that target and facilitate access for the most vulnerable sectors, will help build a strong educational base for the fight against problems such as repeating grades and dropping out. There is clear evidence of the positive effect that preschool education has on academic outcomes for pupils in primary education and subsequent levels (UNESCO, 2010a). This effect is more apparent in the outcomes of learning to read, which is one of the skills that most influences household educational capital. Enhancing these skills in the first years of life is crucial. Aided by early stimulation from early childhood education, it makes a difference in future cognitive development. This association is not seen in all of the countries participating in SERCE, and it varies in intensity in those where it does have an impact (see figure II.20). Figure II.20 LATIN AMERICA (15 COUNTRIES): IMPACT OF YEARS OF PRESCHOOL ATTENDANCE ON READING PERFORMANCE IN THIRD AND SIXTH GRADE a (Multilevel model coefficients) Uruguay Nicaragua Guatemala El Salvador Cuba Costa Rica Colombia Chile Brazil Argentina Latin America 0 1 2 3 4 5 6 7 8 Reading score variation Sixth grade Third grade Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Latin American Laboratory for Assessment of the Quality of Education, Factores asociados al logro cognitivo de los estudiantes de América Latina y el Caribe, Santiago, Chile, UNESCO Regional Office for Education in Latin America and the Caribbean, 2010. a The coefficients for Guatemala and Nicaragua are not statistically significant. The coefficients for the regional model were worked out with equivalent weights for each country. Education is compulsory in all countries of the region, at least in primary education (six years). But in recent years many countries have lowered the entry age to include compulsory preschool education. Mexico is the country that has added the most years (three, from age 3 to age 6) of compulsory preschool education. Next come Chile, El Social Panorama of Latin America • 2010 Salvador, Guatemala, Panama and Uruguay, with two years of compulsory preschool (age 4 to age 6). Beyond compulsory education in the early years, the countries of the region are promoting policies and programmes geared towards protecting and fostering early childhood development. These programmes generally provide supplemental care for children in the most vulnerable social sectors; some of the components they have in common are discussed below. First is the role of public day-care centres and kindergartens in providing meals and preventing childhood undernutrition. Studies of early childhood and preschool education policies in 13 countries of Latin America (Argentina, Chile, Colombia, Costa Rica, Cuba, Ecuador, El Salvador, Guatemala, Mexico, Panama, Paraguay, Peru and the Plurinational State of Bolivia) show that all have preschool meal policies. For many families, these supplemental nutrition programmes take pressure off family budgets and do a great deal to further the healthy development of the recipient children. 2. 107 The region has also advanced in early childhood education quality and methods, involving families in the education process. Several countries are implementing programmes to train and/or support parents in better caring for their children. Gaps in coverage are most significant for the youngest, from birth to age 3 —when family involvement in care is essential. There is a need for education on the demand side of out-of-home care and programmes that support in-home care because turning to such public services is not part of the culture in most of the countries. There are many kinds of support available to meet a variety of needs. Several countries of the region also stress multicultural education. To address the historical marginalization of indigenous groups, several countries of Latin America have added policies geared towards increasing preschool education coverage for them. One of the benefits documented by international studies of preschool education is its ability to decrease inequality among children from different ethnic groups as they enter primary school. Extended school day Advances in current pedagogical models and the education needs of the modern world are making longer school days increasingly important. There is much left to do on this front in Latin America. In most of the countries of the region, the primary school day is 4-5 hours long, with 5-6 hours of class in the lower cycle of secondary education (Johansen, 2005). Lengthening the school day would not only mean more absolute time in school but would also help reorganize the entire system in line with changing curricula and modern teaching models. An extended school day would be expected to change the ratio between time spent on working and time for rest, increasing pedagogical work for pupils at school and decreasing the time spent on homework. This is especially important for students who lack an educational climate at home and whose environment does not provide appropriate stimulus or support for learning. Previous sections of this chapter have already shown that the household educational climate is one of the major determining factors behind unequal educational attainment. Extended days should also take some pressure off school management tasks and reduce the time that teachers and managers spend on individual and group planning. For teachers, expanding to a full workday can help improve job and wage stability and reduce their usually excessive workload. It would involve changing their contract status and eliminating moonlighting at other educational establishments. And increasing teacher well-being could improve their pedagogical capacity. A full school day also has positive externalities for families, such as easing concerns about out-of-school care, including meals. Children who are in school longer can be less exposed to the external risks involved in spending several hours a day on the street. This can help improve family life by increasing safety and peace of mind as to what the children are doing. A longer day also facilitates the incorporation of mothers into the labour market. As seen in several ECLAC publications, this is a significant source of income for lower-resource households. In most of the countries of the region, most of the supply of extended days and better quality is in private schools. Coverage depends on families’ ability to pay, with the resulting segmentation (ECLAC, 2010a). Most efforts to extend the school day in public education have been at the secondary level. The countries that have made the greatest efforts to extend the day at the primary level are Cuba, Chile and Colombia (see figure II.21). 108 Economic Commission for Latin America and the Caribbean (ECLAC) Figure II.21 LATIN AMERICA (15 COUNTRIES): SIXTH-GRADERS ATTENDING EDUCATIONAL ESTABLISHMENTS WITH PARTIAL OR EXTENDED DAYS (SEVEN OR MORE CHRONOLOGICAL HOURS) BY TYPE OF SCHOOL ADMINISTRATION, 2006 a (Percentages) 100 80 60 Public education 40 20 0 20 40 Private education 60 80 Seven or more hours Panama Latin America Nicaragua Guatemala Paraguay El Salvador Peru Mexico Dominican Rep. Ecuador Uruguay Argentina Costa Rica Chile Colombia Cuba 100 Fewer than seven hours Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of microdata from the Second Regional Comparative and Explanatory Study (SERCE) of 2006. a Latin America represents the simple average for countries participating in SERCE. Brazil is not included in the analysis because of lack of consistency in measuring the school day. The most recent study on Chile (Pires and Urzúa, 2010) showed that extended days at the secondary level decreased teenage pregnancy by 4%, raised the likelihood of not dropping out of school by 32% and reduced the likelihood of being arrested. Cognitive measurement scores doubled. The study shows that the positive impact is greater for the most vulnerable children because it offsets the lack of household educational resources and 3. equipment and reduces the likelihood of risky behaviour. The extended school day also increases the likelihood of going on to post-secondary studies, thus improving future job opportunities. SERCE (2006) learning assessments show that in countries that have establishments with an extended primary school day there is a positive association between length of the school day and math outcomes at those establishments. But in all of the countries analysed (except Chile), the academic outcomes for the most vulnerable pupils fell short of those of pupils with a shorter school day. So, at educational establishments serving the socially most disadvantaged population, just extending the school day might not have an impact on academic performance.10 It is probably not enough to do more of the same, but rather to make more substantial changes in how the system is organized in addition to adding more hours. Changing the school day usually requires expanding school space, improving the equipment available at schools and considering the infrastructure and costs associated with more meals for pupils. Extending the day also requires that resources be allocated in keeping with each establishment’s needs, such as providing enough drinking water, sanitation facilities and educational resources like libraries and computer labs to ensure an enhanced educational environment. The condition of the educational establishment can have a negative or positive effect on students. Another significant cost in effectively implementing an extended day is teacher pay. Lengthening the teacher workday entails costs associated with changing the type of contract and the work hours; these costs need to be considered when planning the change. Incorporating digital technology into education: cutting-edge competencies The ongoing technological revolution is redefining the role of education in the effort to achieve equal opportunities. However, as happened with educational attainment differentials, there is a risk that relative market-based advantages for families will continue to be the prime determinant of digital divides. This being the case, incorporating new technologies into education might just reinforce existing inequalities. Incorporating digital programmes through education has revealed a collective imaginary with high expectations for educational opportunities for the new generation, as seen in Uruguay’s Basic Computer Connectivity for Online Learning Plan (CEIBAL). An ECLAC study of the social impacts of incorporating ICT into the educational system (Kaztman, 2010) reviews some of the ways these technologies could be harnessed for individual growth. First, participating in peer-to-peer networks with a high degree of digital socialization stimulates and facilitates exploration and use of the virtual world. This increases the opportunities for each participant to accrue knowledge and skills in handling digital tools. Second, gradual expansion of the frontiers of the virtual world also broadens 10 These results should be interpreted with caution because few socio-economically and culturally disadvantaged children attend educational establishments with an extended school day. Social Panorama of Latin America • 2010 exchanges with other stakeholders in society and multiplies affiliations and belongings, i.e., communities of interests and potential actions. This makes it possible to expand technical competencies and spaces for citizen participation, and to build a collective identity. Young people’s interest in participating in virtual communities and networks seems to be related to a search for recognition and for belonging to spaces that transcend the domestic and institutional borders in which they usually move (Winocur, 2006). This requires more than universal access. Children and young people must shift from being distant users to being multifunctional ones. Greater intensity and productivity in use requires more time in front of the monitors and good programmes for developing the requisite skills set. Here, the difference between those who access these technologies at home and those who do not currently determines the depth of the digital divide and reinforces underlying socio-economic and capital gaps. For the same reasons, school should play a basic role in counteracting these inequalities by preparing to offer more and better access to technology to those who have none at home, deepening penetration in order to increase usage time per pupil and offering pedagogical guidance that motivates students to use the technology independently for research and homework. Evidence from research associated with PISA 2006 seems to indicate that the degree of confidence with which young people use the Internet, and the proportion of computers connected to the Internet at the educational establishment, are positively associated with learning in the science area. Moreover, the type of pedagogical approach taken is not neutral and is related to how the students use the technology. 4. 109 As ECLAC research on the social impact of incorporating ICT through educational systems (Kaztman, 2010) shows, most educational systems in the region are faced with a scenario that forces them to work doubly hard to achieve equity, to the extent that the problems they inherited and could not resolve compound those posed by incorporating ICT into learning processes. The magnitude of the challenges is such that it would not be reasonable to expect the educational system to make this contribution without sustained support from other primary institutions of society. Defining the criteria for choosing the models for incorporating ICT into teaching practices should be subordinated to State goals for education in each country. One of the priorities for the States of Latin America (and for those in charge of their educational systems) is to make universal access to computer skills a key tool in the effort to dissociate social background from learning attainments. This is seen as an essential step in reducing poverty and inequality and in enhancing social integration. Some of the approaches to this challenge in the region have been more successful than others. For example, over a 20year period Chile has consistently implemented policies for achieving mass access to ICT through educational establishments. This approach is having an impact on distributive equity in access (as noted in the preceding section). Uruguay, with a much more recent policy, opted for proactive school-to-home outreach under its student-targeted policy to achieve universal access. Such strategies seek to involve and mobilize households and the community to complement the work being done by the educational system. Support for families in order to reinforce educational progression in vulnerable sectors: conditional cash transfer programmes Public policy cannot obviate the role that family environment plays in the intergenerational reproduction of inequalities. As discussed above, completion of secondary education is a key challenge for achieving equity and social inclusion through the schools. It is therefore important to test instruments and strategies that help keep students in the system during this cycle, that is, that foster sustained, timely school progression. When thinking about policies for narrowing gaps in school progression rates, the first approaches that come to mind are usually reforms of the educational system. However, as noted here, factors that influence learning and attainment are also found outside the system and are closely tied to the students’ family environment. Conditional cash transfer programmes are one of the pillars that the countries have built over the past two decades in order to encourage lower-income families to buy into keeping children in the educational system. Such programmes have the virtue of improving, however marginally, the monetary resources available to poor households, preventing dropouts for opportunity cost reasons (staying in school is part of the transfer programme contract). There is much 110 room for deepening here. First, by gradually increasing the transfers and extending them to keep young people in secondary school. Second, by linking these programmes to broad social protection networks that operate in concert to ensure basic thresholds of stability, income and wellbeing in vulnerable households. Third, by using them to reinforce deep family commitment to school attainment and learning for children and young people. Fourth, by coordinating improvements on the educational demand side under these programmes with improvements on the educational service supply side so as to create areas of synergy and prevent early discouragement. Fifth, by using these programmes to bring parents in closer contact with the school system and thus build an education community involving all stakeholders. Most conditional transfer programmes in the region have at least one condition linked to education. This is usually in the form of a cash transfer to families that hinges on the school-age children enrolling, attending or staying in the educational system (see table II.A-4). While these programmes promote demand for educational services among poor and vulnerable families, they usually do not create incentives on the supply side.11 Hence these programmes are implemented in areas with an adequate educational infrastructure, making it difficult for them to gain traction in remote rural areas. Programmes that stress the enhancement of educational attainment and skills set explicit, firm sanctions for failure to comply with education conditions. Transfers are calculated in order to offset the opportunity costs of using social services. Programmes based on this logic are Oportunidades in Mexico and Let’s Advance Together in Costa Rica. The latter targets families that for economic reasons are having difficulties in keeping their children in school. For the programmes geared towards ensuring a basic level of consumption for poor families, eligibility does not hinge on compliance, so verification mechanisms are weak and the associated sanctions are moderate or non-existent. Such is the case with the Human Development Grant (BDH) in Ecuador.12 Last, there are programmes that seek to combine ensured access for poor 11 The Family Allowance Programme (PRAF) II in Honduras and the Social Protection Network (RPS) and Crisis Care System (SAC) in Nicaragua, all terminated in 2006, were an exception in that they included innovative benefits in the form of transfers to educational establishments (Moore, 2008 and 2009; Cecchini and others, 2009). 12 The Human Development Grant programme had no specific conditions for transfers. However, for a brief period, television spots highlighted how important it was for BHD beneficiary families to send their children to school. An assessment of the programme showed an increase in school enrolment and a decrease in child labour (see table II.A-5). This could be associated with how the beneficiaries perceived this condition, although they were not monitored administratively (Schady and Araujo, 2006). Economic Commission for Latin America and the Caribbean (ECLAC) and vulnerable families to a broad set of benefits, as is the case with Chile Solidario and the Together Network in Colombia. In these programmes, education is but one of several components, and the conditions are part of a broad intervention agreement between programme field representatives and families. Such diversity also entails different educational targets. Some programmes only seek to enhance attendance. Others also hope to impact performance and grade promotion, foster greater education incorporation among target gender and age groups, and even reduce child labour. For this reason, the way in which education transfers are calculated varies in accordance with programme goals. In the Family Allowance Programme (PRAF) in Honduras and the Oportunidades Programme in Mexico, the transfer covers the direct costs of sending children to school (registration, supplies and transportation) and the opportunity cost for poor and vulnerable families who send their children to school instead of putting them to work. Oportunidades, Colombia’s Families in Action and the Programme of Advancement through Health and Education (PATH) in Jamaica step up transfers during secondary education, reflecting the greater opportunity cost of sending children to school. Oportunidades and PATH pay different amounts according to student gender in order to address gender inequality in the secondary education participation rate, albeit in opposing directions: Oportunidades makes larger transfers to girls, PATH to boys. The impact of conditional transfer programmes on education has been assessed from several viewpoints in most of the countries that have or have had such programmes (see table II.A-5).13Although the impacts were not consistent in all countries and the outcomes vary depending on the focus of each programme, the assessments generally reveal improvements in the intermediate goals for educational attainment and skills building (Bastagli, 2008). In other words, they show that conditional transfer programmes improve access to school and also improve indirect indicators such as school enrolment and attendance. Indicators for access and coverage tend to rise more in countries where the baselines were lower, in transitional grades with high drop-out rates (such as the move from primary to secondary school) and in the poorest households and locations. But the assessments provide no information on areas such as child learning, the improvement of which has not been among the explicit goals of conditional transfer programmes (Reimers, DeShano da Silva and Trevino, 2007; Villatoro, 2007). 13 Most of these assessments were based on random sampling designs that were quasi-experimental or, less frequently, experimental (Barrera-Osorio and others, 2008; Levy and Ohls, 2007) or nonexperimental (Perova and Vakis, 2009), with control groups in each case to compare impacts on treatment groups. Social Panorama of Latin America • 2010 Evaluations of the Education, Health and Nutrition Programme (PROGRESA) rolled out in Mexico in 1997 and recast as Oportunidades in 2001 show more improvement in secondary education than at the primary level and better outcomes for girls than for boys and for rural areas than in urban ones (De Brauw and Hoddinott, 2008). They also reveal a positive impact in terms of higher enrolment and grade promotion rates for indigenous children (World Bank, 2009; Escobar and de la Rocha, 2002, 2008). Families in Action in Colombia also had more significant impacts in increasing school attendance among secondary school students than at the primary school level, because school attendance was already high in the latter before the programme was launched (Attanasio and others, 2008). According to Colombia’s National Planning Department (DNP, 2008), secondary school attendance rose about five percentage points in urban areas and seven percentage points in rural areas. The Solidarity programme in the Dominican Republic increased by 14 percentage points the likelihood of adolescents age 14-16 attending school (Government of the Dominican Republic, 2008). The enrolment rate in Paraguay rose 2.5% among children in families enrolled in the Tekoporã programme, and the school attendance rate increased between five and eight percentage points. The best outcomes were for adolescents age 11-15, for whom this indicator rose between 9 and 15 percentage points. The assessment of the Tekoporã programme also shows that it decreased the likelihood of dropping out of school and checked the 5. 111 increase of child labour in Paraguay, presumably because of the increase in school attendance —especially among older boys, i.e., those who leave school earliest in order to work (Veras Soares, Perez and Issamu, 2008). Gertler, Patrinos and Rubio-Codina (2007) evaluated the role of other educational policies in Mexico in schools where a large percentage of the pupils are enrolled in the Oportunidades programme. These authors report that schemes seeking to empower associations of parents and legal guardians (the School Management Support Programme, or AGE, part of the broader Compensación Educacional programme) successfully decrease grade repetition and school drop-out rates. These impacts seem to indicate that greater feedback and coordination between conditional transfer programmes and other types of educational and social interventions can bring improvements in educational processes and outcomes. The neighbourhood peer effects of these programmes should also be highlighted. For PROGRESA, Bobonis and Finan (2008) show that children who are not eligible for transfers are still influenced by peers who are enrolled in the programme, with more of the former remaining in the educational system at the secondary level. The results show that in locations where the programme was implemented, school enrolment among children not participating in the programme rose five percentage points anyway, compared with data for control locations. This impact is especially beneficial for children in the poorest segments. Better training for work The path leading young people to the world of work is, as we have seen, highly segmented by educational attainment levels. On average for Latin America, only half of the population age 20-24 completes the upper cycle of secondary school. Only 33% of young people age 20-29 are enrolled in some sort of post-secondary education programme, and less than 10% have completed five years of education at this level. There is also a large group of young people who neither study nor work and are at high risk for institutional disaffiliation and social disintegration. This situation calls for timely, effective alternatives for training for work. The formation of competencies in the 15-20 age group is essential for successful entry into the labour market with meaningful opportunities for the future. Public efforts are therefore required to target this area of education and link this supply of education services to the production sector. According to UNESCO and the International Labour Organization (ILO), the supply of technical and vocational education is “a comprehensive term referring to those aspects of the educational process involving, in addition to general education, the study of technologies and related sciences, and the acquisition of practical skills, attitudes, understanding and knowledge relating to occupations in various sectors of economic and social life”. Such education can be provided by the educational establishment or by another entity supervised by the public authority. It includes formal and informal education programmes (UNESCO/ UNEVOC, 2006) and is an important “means of preparing for occupational fields and for effective participation in the world of work” as well as “a method of facilitating poverty alleviation” (UNESCO, 2005). This broad field of education for work encompasses an array of hard-to-classify learning activities. Coverage 112 Economic Commission for Latin America and the Caribbean (ECLAC) and supply at this level of education vary widely. In developed countries, especially in Europe, their coverage and impact are far higher. In Europe, approximately half of the students enrolled in the upper cycle of secondary school are in technical and vocational education programmes (UNESCO/UNEVOC, 2006). In countries like Austria, Germany and Switzerland there is a historically consolidated vocational track in the upper level of secondary school. English-speaking countries tend to postpone technical and vocational programmes until the post-secondary cycle. In Latin America and the Caribbean, the situation in the upper level of secondary education also varies widely. Coverage at this level of education is very low in Brazil despite strong technical and vocational programmes in the post-secondary cycle. In Argentina and Guatemala, a high percentage (more than 80%) of those enrolled in the upper cycle of secondary education are in such programmes (see figure II.22). Figure II.22 LATIN AMERICA AND THE CARIBBEAN (28 COUNTRIES): STUDENTS ENROLLED IN TECHNICAL/VOCATIONAL PROGRAMMES COMPARED WITH TOTAL ENROLMENT IN THE UPPER CYCLE OF SECONDARY EDUCATION, AROUND 2002 (Percentages) 100 90 80 70 60 50 40 30 20 10 Asia Oceania Europe Jamaica Barbados Brazil Guyana Trinidad and Tobago Dominican Rep. Mexico Venezuela (Bol. Rep. of) Anguilla Nicaragua Belize Uruguay Grenada Paraguay Turks and Caicos Islands Costa Rica Aruba Colombia Netherlands Antilles Chile British Virgin Islands Ecuador Panama Suriname El Salvador Cuba Argentina Guatemala 0 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of UNESCO International Centre for Technical and Vocational Education and Training, Participation in Formal Technical and Vocational Education and Training Programmes Worldwide. An initial statistical study. Montreal, 2006. Changing industrialization and development processes in Latin America in the closing decades of the twentieth century brought into question the region’s traditional institutional approach to education for work as a specialized branch of secondary education for specific occupations and as vocational training provided by large institutions with ties to government, labour unions and business. Globalization and new requirements for more flexible competencies that can be shaped over time are shifting such training away from State-run institutions and leading to the use of public funds to outsource it to the private sector, seeking to meet the training needs of the production sector (Gallart, 2002). Programmes, reforms and initiatives have taken different paths in the region over the past few decades. Generally speaking, specialized training has been postponed to as late as possible in the secondary education cycle. Technical educational establishments at the secondary level have strongly resisted having to provide a general education; rather, they have sought to redesign the kind of vocational education they provide (Gallart, 2002). As for post-secondary education, Jacinto (2010) describes two prevailing models for the supply of vocational training in the region in the late 1990s. All of the models involve coordinating the public and private sectors. In the first model, such education is provided at traditional vocational training establishments developed in the 1950s and run by the State or by three-way partnerships (the State, labour unions and business). The other model involves ad hoc, decentralized programmes that report to the ministry of labour or to vocational training institutions and delegate training to other institutions (private or run by civil society organizations). In this model there are two kinds of supply: one based on the open market, with specific training courses for formal employment; and one with subsidies for organizations benefiting disadvantaged sectors, seeking their social inclusion through employment (informal or self-employment). According to the review conducted by Jacinto (2010), new administrations in the first decade of the twenty-first century and criticism of the social costs of privatization policies led to a certain retooling of this kind of education. Efforts to reach vulnerable populations affected by varying forms of exclusion were beefed up. There have also been measures to improve the quality of education provided by these programmes and to devolve resources and capacities to the local stakeholders who manage them. Most of the countries have taken the approach to learning based on development of competencies. Despite recent action to link existing institutions, the sector is still not well coordinated. Substantially different approaches separate the formal education system and the vocational training system and set both apart from the production sector. Policies and programmes often lack continuity. They overlap and are sometimes irrelevant for the labour integration of young people. The developed countries understand how important such education is to having the highly qualified labour force that on-the-job training cannot be expected to deliver. Changes in the production and manufacturing sector have done away with the long-term labour relationships that made investing in specialized training for employees Social Panorama of Latin America • 2010 worthwhile for most businesses. According to OECD (2010), development of such programmes should focus on long-term career paths and deliver competencies that 6. 113 enable young people to enter the labour market directly while allowing them to continue their education in the future. Support for continuing higher education Education at the university level must meet the demands of the world of work and further the consolidation of the knowledge society, thereby helping enhance the university as a centre for producing and transferring knowledge (Malagón, 2004). The higher education system in Latin America and the Caribbean has expanded and grown substantially over the past few decades. However, as noted in preceding sections of this chapter, coverage is still limited and it is concentrated in the medium- and high-income levels. Ensuring greater equality of opportunities at the university level calls for policies that offset the lack of monetary resources and of time among young people graduating from secondary school who need to work to survive or to help their families. Some such policies could include cross subsidies for higher education to ensure that it is free for those who cannot pay, and to make it bankable; scholarships and soft loans for students from lower-income households; and flexible class schedules with morning and evening modules. Despite all efforts there is still no broad scholarship mechanism for disadvantaged students, just a mix of loans and scholarships that are mostly available to medium- and medium-low income groups. For young people in lower income brackets to have access to such funding and truly be able to attain education at this level requires enhancement of the entire educational chain. Once young people are inside the system, mechanisms must be developed to enable them —who are often the first generation to access this level of education— to stay in the system and complete the cycle. The internal rates of efficiency for higher education systems in the region are quite low overall compared with the developed countries. This means that many more young people are entering the system but few complete their education (especially those from lower-income households, who are usually the first generation to go on to higher education). 98 81 97 75 98 87 98 81 Honduras (2007) Mexico (2008) Nicaragua (2005) 86 90 99 93 99 98 97 Peru (2008) Uruguay (2008) Venezuela (Bolivarian Republic of) (2008) Latin America b 98 98 … 99 99 99 95 98 99 84 99 91 92 94 98 97 99 97 99 99 98 99 Urban 97 99 100 87 99 95 98 98 99 100 99 98 100 99 99 100 95 … 98 90 95 98 78 98 85 87 90 97 96 98 94 98 98 97 … Rural 97 98 99 92 96 99 80 98 86 90 92 98 97 99 96 99 98 98 99 97 98 99 93 98 99 82 99 87 88 92 98 97 99 97 99 99 98 99 Male Female Sex 112 108 113 106 119 109 113 105 112 105 107 104 118 120 115 114 121 112 109 Total 116 109 117 109 121 112 114 106 105 100 105 105 122 122 121 116 129 113 112 105 104 106 102 114 104 102 102 115 109 102 101 109 114 107 110 105 109 105 Quintile I Quintile V Income level 111 … 113 103 117 107 109 104 113 106 107 102 117 118 113 114 117 110 109 Urban 114 … 108 109 121 112 116 106 111 105 108 106 121 123 122 115 135 115 … Rural Geographical area Sex 114 109 115 107 121 110 114 106 113 107 109 105 123 123 119 115 125 112 110 110 107 111 105 117 108 112 105 111 103 105 103 113 118 112 114 116 112 109 Male Female Gross attendance rate, primary education 93 94 97 94 89 95 71 96 79 63 76 95 88 94 94 99 95 93 98 Total 88 90 93 87 80 87 48 91 62 38 60 91 83 91 89 98 90 87 96 98 97 99 98 96 99 95 99 94 89 95 98 94 100 99 99 99 95 99 Quintile I Quintile V 96 … 97 97 94 98 85 98 90 77 86 96 91 96 96 99 96 96 98 Urban 85 … 97 89 83 88 53 92 70 49 64 92 83 91 86 98 89 87 … Rural Geographical area Sex 92 92 96 94 88 94 66 95 77 67 74 94 84 94 92 98 93 94 97 94 95 98 94 90 95 76 96 81 58 78 95 92 94 95 99 96 92 98 Male Female Completion of primary education Income level 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. a Net attendance rate refers to children in the official age group for primary education; gross attendance rate refers to pupils in primary education regardless of age. b National averages include urban areas of Argentina. 96 97 95 99 97 Panama (2008) Paraguay (2008) 84 92 96 89 Ecuador (2008) 98 94 El Salvador (2004) 98 Dominican Republic (2008) 94 Guatemala (2006) 99 97 Costa Rica (2008) 99 96 Chile (2006) Colombia (2008) Brazil (2008) 97 98 98 99 Bolivia (Plurinational State of) (2007) 99 Quintile I Quintile V Income level 99 Total Geographical area Net attendance rate, primary education Table II.A-1 LATIN AMERICA (18 COUNTRIES): NET AND GROSS PRIMARY SCHOOL ATTENDANCE AND COMPLETION RATES AMONG YOUNG PEOPLE AGE 15-19 BY SELECTED PER CAPITA INCOME QUINTILES, AREA OF RESIDENCE AND SEX, AROUND 2008 a (Percentages) Argentina (2006) Appendix 114 Economic Commission for Latin America and the Caribbean (ECLAC) 92 93 95 92 88 96 85 81 71 66 80 84 88 84 88 84 94 88 Bolivia (Plurinational State of) (2007) Brazil (2008) Chile (2006) Colombia (2008) Costa Rica (2008) Dominican Republic (2008) Ecuador (2008) El Salvador (2004) Guatemala (2006) Honduras (2007) Mexico (2008) Nicaragua (2005) Panama (2008) Paraguay (2008) Peru (2008) Uruguay (2008) Venezuela (Bolivarian Republic of) (2008) America b 85 93 76 83 71 80 71 74 43 50 73 79 96 82 90 92 91 88 95 97 98 96 91 98 95 93 88 89 91 96 96 93 95 98 98 91 97 91 … 85 92 92 93 89 84 82 82 87 91 96 92 93 95 93 95 89 80 … 68 82 73 79 73 73 51 55 71 74 94 82 87 92 90 88 … Urban Rural Quintile I Quintile V 84 Geographical area Income level 88 93 81 88 85 86 83 79 64 71 83 84 95 86 91 95 92 93 88 85 94 79 82 69 83 72 75 46 50 68 79 95 81 91 91 90 83 85 Male Female Sex 107 119 101 105 99 101 125 89 96 91 95 111 127 136 114 110 114 109 110 Total 102 118 85 103 82 90 104 80 59 62 85 106 124 121 114 105 110 104 102 114 121 125 111 110 110 137 105 128 109 105 123 119 141 113 113 117 106 114 Quintile I Quintile V Income level 110 … 102 107 109 107 132 95 119 104 102 118 129 146 115 110 114 111 110 96 … 77 102 85 90 111 79 74 72 83 100 122 124 111 106 112 104 … Urban Rural Geographical area 107 119 98 107 102 99 130 89 92 91 97 112 126 136 114 110 114 110 110 106 119 104 103 97 103 122 89 100 90 93 110 127 136 115 109 114 108 110 Male Female Sex Gross attendance rate, secondary education 52 61 38 74 48 56 32 45 30 26 37 56 52 45 30 80 55 64 69 Total 25 42 11 44 18 23 8 18 4 3 9 32 32 15 8 61 24 35 45 83 83 78 93 74 84 61 80 62 67 70 82 69 80 71 95 90 85 92 Quintile I Quintile V 59 … 39 83 61 67 43 53 45 40 49 66 58 53 37 82 60 74 69 27 … 23 50 26 33 13 29 13 9 17 31 39 30 5 61 27 41 … Urban Rural Geographical area Sex 49 55 32 75 47 52 26 45 27 27 37 53 45 42 28 79 50 67 64 55 68 45 72 50 61 37 46 32 24 36 58 59 48 32 81 60 63 73 Male Female Completion of secondary education Income level 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. a Net attendance rate refers to children in the official age group for secondary education; gross attendance rate refers to students in secondary education regardless of age. b National averages include urban areas of Argentina. Latin 89 Argentina (2006) Total Net attendance rate, secondary education Table II.A-2 LATIN AMERICA (18 COUNTRIES): NET AND GROSS SECONDARY SCHOOL ATTENDANCE AND COMPLETION RATES AMONG POPULATION AGE 20-24 BY SELECTED PER CAPITA INCOME QUINTILES, AREA OF RESIDENCE AND SEX, AROUND 2008 a (Percentages) Social Panorama of Latin America • 2010 115 116 Economic Commission for Latin America and the Caribbean (ECLAC) Table II.A-3 LATIN AMERICA (12 COUNTRIES): 13-TO-19-YEAR-OLD INTERNET USERS BY UPPER AND LOWER HOUSEHOLD PER CAPITA INCOME QUINTILES AND PLACE OF CONNECTION, AROUND 2008 a (Percentages) Country/year Place Quintile I Quintile V Quintile V-Quintile I Total Uruguay, 2009 Home 08.0 91.5 83.5 33.0 School 20.6 40.6 20.0 23.3 Commercial establishment 27.4 12.8 -14.6 28.3 Home 04.4 72.2 67.8 26.6 School 08.9 32.2 23.3 16.8 Commercial establishment 27.5 26.2 -01.3 34.1 Home 03.7 60.9 57.2 21.5 School 42.2 41.3 -00.9 41.5 Commercial establishment 25.8 21.9 -03.9 30.4 Home 01.7 48.1 46.4 13.9 School 07.1 27.3 20.2 14.4 Commercial establishment 28.3 30.9 02.6 37.8 Home 01.1 45.3 44.2 10.6 School 03.4 10.7 07.3 06.3 Commercial establishment 28.0 25.8 -02.2 30.9 Home 00.6 47.4 46.8 09.3 School 07.0 26.4 19.3 15.0 Commercial establishment 06.1 26.4 20.3 19.6 Home 00.6 39.5 38.9 09.2 School 01.9 09.4 7.5 05.2 Commercial establishment 18.9 46.5 27.6 43.7 Home 01.3 34.0 32.7 09.9 School 12.6 37.9 25.3 24.1 ... ... Home 00.8 33.7 32.9 07.3 School 01.3 17.8 16.5 06.1 Commercial establishment 07.2 24.9 17.7 13.0 Home 0.00 22.0 22.0 04.0 School 00.6 06.3 05.7 02.4 Commercial establishment 05.4 26.6 21.2 14.3 Home 00.1 10.3 10.2 01.9 School 00.3 11.0 10.7 02.9 Commercial establishment 02.5 40.2 37.7 15.2 Home 00.0 04.3 04.3 00.7 School 02.5 16.4 13.9 06.8 Commercial establishment 04.8 40.0 35.2 15.3 Brazil, 2008 Chile, 2006 Costa Rica, 2008 Mexico, 2007 Panama, 2007 Peru, 2009 Ecuador, 2009 Commercial establishment Paraguay, 2008 El Salvador, 2008 Honduras, 2007 Nicaragua, 2006 ... ... Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special processing of household surveys reconciled by the Observatory for the Information Society in Latin America and the Caribbean (OSILAC); and R. Kaztman, “Impacto social de la incorporación de las TIC en el sistema educativo”, Políticas sociales series, No. 166 (LC/L.3254-P), Santiago, Chile, ECLAC, 2010. Social Panorama of Latin America • 2010 117 Table II.A-4 LATIN AMERICA (17 COUNTRIES): EDUCATION-RELATED COMPONENTS OF CONDITIONAL TRANSFER PROGRAMMES Country (Programme/Transfer) Targets Condition Sanctions Argentina (Universal allowance per child for social protection) 5-to-18-year-olds Proof of regular attendance Withholding of 20% of the transfer until proof of meeting the condition is provided Bolivia (Plurinational State of) (Juancito Pinto Grant) Children under 18 up to eighth grade School attendance record of at least 80% Benefit suspended if records delivered by the school principal are not correct Brazil (Bolsa Família/Basic, variable benefit) 6-to-15-year-olds School attendance record of at least 85% Upon third absence, benefit suspended for 60 days. Upon fifth absence, family unenrolled (Bolsa Família/Variable benefit linked to adolescents) 16-to-17-year-olds School attendance record of at least 75% Upon second absence, benefit suspended for 60 days. Definitive suspension upon third absence Chile (Chile Solidario) 5-to-15-year-olds Attendance at educational establishment As provided in the family contract Colombia (Families in Action) 7-to-17-year-olds in second to eleventh grade School attendance record of at least 80% Suspension of the benefit if more than eight unexplained absences per two-month period Costa Rica (Let’s Advance Together) 12-to-25-year-olds in secondary school (seventh to twelfth grade) Enrolment in the school year; punctual, consistent school attendance Suspension of the benefit if the student drops out Dominican Republic (Programa Solidaridad/Incentivo a la asistencia escolar) 6-to-16-year-olds enrolled in basic public education grades one to eight 85% school attendance Definitive suspension if noncompliance with co-responsibility in three consecutive periods (six months) Ecuador (Human Development Grant) 5-to-17-year-olds School attendance record of 75% El Salvador (Comunidades Solidarias Rurales) 6-to-15-year-olds Enrolment and regular school attendance from nursery school (if space is available) to sixth grade Suspension of the benefit if more than four unexplained absences per month Guatemala (My Family Progresses) 6-to-15-year-olds 80% school attendance Benefit cancelled if co-responsibilities not fulfilled on three occasions Honduras (PRAF/School grant for first to sixth grade) 6-to-14 year-olds up to sixth grade in public schools No more than nine unexplained absences per trimester, and 85% actual class attendance 13- and 14-year-olds who have not completed sixth grade and have not fulfilled the conditions are not entitled to the bimonthly grant (PRAF/urban and rural youth grant) 13-to-24-year-olds Daily attendance and minimum academic performance of 70% ... Jamaica (PATH/Education grant) 6-to-17-year-olds Monthly attendance of at least 85% Transfers suspended for noncompliance, until responsibility met (PATH/Grant) Adolescents enrolled in higher education ... ... Mexico (Oportunidades/ Education support) Children and young people attending school at the basic, secondary and upper secondary levels School attendance of at least 85% Definitive suspension in the case of beneficiary duplication and if secondary-school students receive benefits for more than four years. For four or more unexplained absences per month, suspension applies for the current month (Oportunidades/Jóvenes con oportunidades) Students between third year of junior high school and fourth year of high school Upper secondary education completed by age 22, and being a beneficiary of Oportunidades Transfer suspended if re-enrolment in high school detected Panama (Opportunity Network) 4-to-17-year-olds Enrolment, and absences not to exceed 10% of actual class days; attendance at bimonthly meetings with managers ... Paraguay (Tekoporã) 6-to-18-year-olds Enrolled; with 85% attendance record. Participation of adults in literacy programmes Peru (Together) 6-to-14-year-olds 85% school attendance Noncompliance with co-responsibility triggers suspension for three months Uruguay (Family Allowances) 4-to-14-year-olds in primary school and 15-to-18-yearolds in high school Enrolment and attendance Benefit suspended if records forged or compliance with conditions not proven Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the database of social programmes. 118 Economic Commission for Latin America and the Caribbean (ECLAC) Table II.A-5 LATIN AMERICA (12 COUNTRIES): ASSESSMENT OF THE EDUCATIONAL IMPACT OF CONDITIONAL TRANSFER PROGRAMMES Country (Programme) Type of assessment Indicator Age group and/or level of education Brazil (Bolsa Família) Longitudinal, quasiexperimental b Likelihood of school absence in the most recent month Likelihood of dropping out of school 7-to-14-year-olds in families living in poverty Baseline Impact a Author (year) … - 3.6 c MDS (2007) - 1.6 c Chile (Chile Solidario) Review of secondary information Effectiveness in eliminating child labour e Families with children under 15 5 992 families 96.6%(5 787 families) Alonso (2007) Colombia (Families in Action) Quasi-experimental f Enrolment 8-to-13-year-olds … +1 to +3 Attanasio and others (2006) 14-to-17-year-olds … +5 to +7 Domestic child labour 8-to-13-year-olds in rural areas - 10 g -13 g Attendance Primary education (8-to-11-year-olds) … +2 (rural areas); no impact on urban areas Secondary education (12-to-17-year-olds) … +5 (urban areas) and +7 (rural areas) Decrease in labour participation 10-to-17-year-old girls in rural areas … -35.6% 10-to-17-year-old girls in urban areas … -29.2% 10-to-17-year-old boys in rural areas … -19% Experimental, on the basis of a panel survey h DNP (2008) Dominican Republic (Solidarity) Experimental i Likelihood of attending school 14-to-16-year-olds … +14 Solidarity (2008) Ecuador (Bono Solidario) Experimental j Enrolment Sixth-graders … +17.8 Schady and Araujo (2006) Child labour Children enrolled in the programme … -17 Honduras (PRAF II) Experimental, on the basis of panel surveys k Enrolment 5-to-12-year-olds … +17 IFPRI (2003) Jamaica (PATH) Experimental, on the basis of a survey l Number of days of school attendance in a typical 20-day period 6-to-17-year-olds 17.5 +0.5 Levy and Ohls (2007) Mexico (Progresa/ Oportunidades) m Random experimental, Enrolment with data from panel survey Primary education 90%-94% +0.96 to +1.25 (girls); +0.74 to +1.07 (boys) Schultz (2000) Secondary education 67% (girls) 73% (boys) +7.2 to +9.3 (girls) +3.5 to +5.8 (boys) Children under 10 -1% n +1.2% 10-to-13-year-olds -0.3% n +2.4% 14-to-17-year-olds +5.1% n +7.5% n +3.3% Random experimental Enrolment 6-to-17-year-olds +1.6% Attanasio and others (2005) Random experimental School attendance Between sixth grade and the first level of secondary education 58% +11.1 (both sexes); +14.8 (girls); +6.5 (boys) Schultz (2004) Random experimental Enrolment Transition from primary to secondary education 63.2% 75.7% De Janvry and Sadoulet (2006) Social Panorama of Latin America • 2010 119 Table II.A-5 (conclusion) Country (Programme) Type of assessment Indicator Age group and/or level of education Baseline Impact a +23 Primary education … +7 7-to-13-year-olds … -5 Enrolment 4-to-14-year-olds in nonindigenous rural areas 87.4% 91.3% 67.1% 82.9% 78.5% 92.6% Total children enrolled in the programme 93% 95.5% … +6 to +11 11-to-15-year-olds … +9 to +15 6-to-14-year-olds 81% 85% 7-year-olds Non-experimental q … Children enrolled Peru (Together) Children enrolled in the programme 6-to-11-year-olds in indigenous rural areas Quasi-experimental p +18 4-to-14-year-olds in indigenous rural areas Paraguay (Tekoporã) … Child labour Analysis of the Standard of Living Survey (SLV) o Children enrolled in the programme Promotion to sixth grade Panama (Opportunity Network) Enrolment Attendance Nicaragua Random (Social Protection experimental n Network) 83% Author (year) 93% Attendance Enrolment Maluccio and others(2005) Bustos (2009) in Rodríguez (2010) Veras Soares and others (2008) Perova and Vakis (2009) Source: Economic Commission for Latin America and the Caribbean, (ECLAC). a Refers to changes in the control group or in total beneficiaries as an effect of the programme. How this impact is expressed varies according to the indicator used in each study: increase (+) or decrease (-), percentage points or percentages (%). b Study conducted in 2005. c Results from the treatment group (beneficiary families) compared with the control group. d Data from families exiting the Bridge programme in 2007. e Percentage of families whose children were working at initiation of the programme and who resolved the situation. f Data gathered in 2001 and 2003. g Decrease in the domestic child labour rate among children enrolled in the programme in the same time period. h Data from household surveys conducted in 2002, 2003 and 2006. i Data gathered between 2003 and 2005. j Data for 2000-2001. k Data gathered between 2003 and 2005. l Data gathered between 1997 and 1998. m Changes in the control group in the same time period. n Study conducted between 2001 and 2003. ñ Data from the 2008 SLV. Lacking a baseline for the programme, considers historical administrative records for households and the results of the household survey conducted in 2007. o Results drawn from the 2007 household survey. p Data for the control group drawn from a survey conducted between 2006 and 2007. q Control group defined as eligible children who were unable to participate in the programme. Results drawn from data gathered in 2002 and 2007. 120 Economic Commission for Latin America and the Caribbean (ECLAC) Table II.A-6 LATIN AMERICA (18 COUNTRIES): DISTRIBUTION OF THE POPULATION AGE 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages) Education level attained Country Year Population group b Argentina (urban areas) 2006 Bolivia (Plurinational State of) 2007 Brazil 2008 Chile 2006 Colombia 2008 Costa Rica 2008 Dominican Republic 2008 Ecuador 2008 El Salvador 2004 Guatemala 2006 Honduras 2007 Mexico 2008 Nicaragua 2005 Panama 2008 Paraguay 2008 Peru 2008 Uruguay 2008 Venezuela (Bolivarian Republic of) 2008 Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Latin America Incomplete primary 2.9 8.7 8.8 12.0 42.2 32.5 7.9 23.4 21.3 2.7 14.0 14.3 8.6 25.6 22.7 8.7 17.2 17.6 14.5 35.8 31.4 6.8 20.9 19.8 26.1 47.8 42.1 41.5 62.2 54.7 24.6 50.0 41.3 7.2 25.4 22.6 31.6 53.3 45.6 6.2 13.2 14.1 12.5 32.1 27.1 7.6 33.8 28.8 3.6 10.1 13.0 7.1 15.5 14.7 9.2 24.8 22.5 Complete primary 1.3 0.6 0.8 3.3 4.2 3.8 4.3 13.0 10.5 1.4 7.4 6.7 9.2 18.1 15.1 21.3 31.1 26.7 4.1 5.6 4.7 14.3 28.6 23.0 9.0 12.3 10.6 18.5 13.6 15.3 29.7 25.1 25.7 11.3 19.5 16.1 14.9 14.0 14.0 11.9 21.0 18.3 14.1 25.3 19.8 7.7 4.7 5.5 14.7 23.6 23.3 10.2 22.1 18.1 8.0 14.7 12.4 Incomplete lower secondary 34.4 33.4 35.3 11.1 8.0 8.9 29.8 23.5 24.4 11.9 14.7 13.0 33.3 17.4 22.4 27.6 14.7 18.8 16.0 17.1 16.1 23.8 11.1 15.0 30.1 14.2 19.9 19.5 6.3 11.8 20.8 6.7 12.6 36.3 23.4 26.7 25.0 13.1 17.8 25.5 18.0 19.9 25.4 12.5 17.2 19.0 10.5 13.0 32.3 21.8 22.7 23.1 17.8 19.0 28.9 20.7 22.7 Incomplete upper secondary 6.7 8.0 7.0 29.3 8.6 17.0 16.4 4.3 8.3 29.2 15.9 19.6 25.4 19.5 20.3 8.9 2.3 4.6 28.4 12.3 17.8 16.3 4.4 8.5 8.8 2.6 5.0 2.9 0.6 1.6 5.2 0.8 2.8 13.8 5.0 8.0 5.5 2.0 3.5 16.3 5.4 8.9 16.2 4.3 9.0 9.0 1.9 4.4 22.8 14.3 15.2 8.9 2.6 4.9 15.5 6.2 9.2 Complete secondary 30.6 21.8 24.0 22.1 14.6 16.9 29.1 21.4 22.6 32.0 27.0 26.6 0.1 0.1 0.1 13.6 12.1 12.0 18.9 11.8 13.6 20.2 16.1 16.5 16.1 12.0 12.8 5.7 3.9 4.5 4.5 2.3 3.2 15.4 11.2 12.0 12.8 7.1 9.3 21.5 20.2 19.4 19.6 13.1 15.0 31.3 22.3 24.0 9.3 8.9 8.1 22.9 20.3 20.3 21.5 16.4 17.2 Incomplete tertiary 17.0 8.3 10.6 17.3 11.4 13.3 10.7 10.7 10.0 18.7 13.2 13.8 16.4 7.0 9.9 17.1 13.9 14.3 17.0 14.4 14.3 14.7 9.6 10.6 8.4 5.5 6.3 10.6 9.0 9.2 13.6 10.6 11.4 12.5 8.1 9.1 6.9 4.6 5.3 13.5 9.5 10.2 12.3 12.7 11.9 18.8 13.2 14.2 15.4 15.7 13.8 20.8 10.6 14.0 13.5 9.9 10.5 Complete university 7.1 19.2 13.5 4.9 11.0 7.7 1.8 3.7 2.9 4.2 7.7 6.0 7.0 12.3 9.5 2.8 8.7 6.0 1.2 3.0 2.2 4.0 9.4 6.7 1.6 5.6 3.4 1.2 4.4 2.8 1.6 4.5 2.9 3.5 7.4 5.5 3.3 5.9 4.3 5.0 12.7 9.1 0.0 0.1 0.0 6.7 13.6 10.1 1.9 5.5 3.9 6.9 11.1 9.0 3.5 7.3 5.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). b Total population in each age group. The category “15 and older” includes the population age 65 and older. Social Panorama of Latin America • 2010 121 Table II.A-7 LATIN AMERICA (18 COUNTRIES): PARTICIPATION RATES FOR THE POPULATION AGE 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages) Education level attained Country Argentina (urban areas) Year Population group b 2006 Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Bolivia (Plurinational State of) 2007 Brazil 2008 Chile 2006 Colombia 2008 Costa Rica 2008 Dominican Republic 2008 Ecuador 2008 El Salvador 2004 Guatemala 2006 Honduras 2007 Mexico 2008 Nicaragua 2005 Panama 2008 Paraguay 2008 Peru 2008 Uruguay 2008 Venezuela (Bolivarian Republic of) 2008 Latin America Incomplete primary 44.8 65.4 43.9 75.3 84.7 79.1 60.9 68.0 55.3 40.3 55.4 38.5 59.2 66.7 55.3 58.1 59.6 45.9 64.3 66.5 55.9 61.4 69.3 59.6 56.5 61.9 54.0 60.2 68.6 63.0 58.6 64.6 58.7 59.4 62.5 53.3 61.0 66.1 60.1 57.6 63.5 51.8 67.8 72.0 63.8 72.4 83.2 73.6 50.4 67.6 40.3 66.3 68.7 57.9 61.0 67.7 56.7 Complete primary 45.5 76.7 55.4 81.0 91.2 84.4 68.6 71.0 61.9 46.2 58.2 44.1 67.9 71.7 64.2 65.0 67.4 62.6 54.7 73.0 64.3 75.3 74.6 70.4 56.9 74.1 63.6 67.6 75.9 70.0 61.3 71.2 65.0 63.8 66.3 61.9 61.1 73.5 65.4 67.1 68.9 61.4 72.0 77.7 73.5 76.6 85.9 79.8 67.3 76.1 57.4 70.9 74.0 67.1 66.8 70.6 63.6 Incomplete lower secondary 46.0 71.9 53.2 62.3 80.8 69.1 59.9 76.0 66.7 30.2 67.9 53.1 38.0 75.1 52.7 43.4 73.4 55.0 52.5 74.5 62.3 51.0 78.4 60.8 46.2 76.8 56.3 54.9 86.6 62.6 38.8 74.4 47.3 56.2 73.8 63.6 51.7 79.0 60.5 48.7 74.1 59.1 52.5 79.2 61.8 58.9 85.0 69.1 57.7 82.4 66.7 48.3 78.3 62.7 54.0 75.4 62.8 Incomplete upper secondary 52.6 74.6 62.9 48.3 81.6 56.7 59.0 77.3 63.4 24.6 70.4 45.0 74.7 79.1 75.4 38.8 71.3 47.0 43.7 77.5 55.4 34.3 79.1 46.0 36.0 79.0 46.5 37.5 85.7 45.7 29.2 71.7 35.0 39.7 75.7 51.2 43.8 81.7 53.6 38.0 74.4 49.1 52.3 85.1 59.6 48.8 88.4 57.4 58.3 83.9 67.6 31.6 78.3 44.7 51.8 77.2 60.1 Complete secondary Incomplete tertiary Complete university Total 62.7 77.2 65.6 63.6 80.3 69.6 82.8 81.1 80.0 67.9 75.5 69.9 51.3 74.5 58.3 65.0 72.0 66.9 70.2 79.5 73.7 69.8 78.9 72.7 72.9 80.1 75.0 61.4 78.4 67.0 38.8 75.0 50.6 64.0 76.1 69.1 63.0 80.2 68.7 72.2 78.6 72.6 77.7 80.9 77.9 70.1 83.1 75.0 67.9 84.9 73.2 59.1 80.6 69.6 74.0 79.7 75.1 55.4 82.7 65.5 48.3 83.5 62.3 82.0 85.5 81.7 51.5 83.3 67.8 57.2 84.8 67.0 67.9 79.0 72.2 70.5 88.1 78.8 55.9 85.6 69.2 51.3 85.2 64.6 79.9 83.8 80.1 60.5 78.4 67.0 53.4 83.5 67.0 56.4 82.6 66.6 63.6 84.7 72.8 78.0 92.5 83.9 68.5 84.4 75.3 72.1 88.8 77.4 53.4 83.5 65.2 64.8 84.7 73.6 87.5 89.2 83.8 83.5 89.0 85.9 88.2 90.5 86.7 85.5 91.5 86.6 79.5 90.5 85.2 92.2 90.5 87.3 92.1 90.4 86.5 82.5 91.8 88.0 86.1 89.1 86.4 82.3 91.5 86.6 80.0 90.9 86.2 85.4 88.1 85.4 85.7 90.3 88.3 88.6 88.3 84.2 100.0 77.7 82.7 81.1 89.4 84.8 84.4 94.6 85.8 72.1 87.2 80.3 83.2 89.5 85.1 56.1 77.0 61.5 59.3 84.1 71.3 69.7 76.2 68.6 47.4 71.7 57.3 58.0 75.7 64.1 57.4 71.2 60.9 58.7 75.0 63.6 58.2 77.5 66.2 54.3 71.0 59.6 62.3 73.6 66.2 53.5 69.9 59.7 56.9 71.6 62.2 58.5 72.3 63.0 58.8 75.3 63.9 65.2 78.7 69.5 67.2 84.6 74.4 62.7 81.5 64.0 55.6 77.9 65.2 62.1 75.5 65.7 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). b Total population in each age group. The category “15 and older” includes the population age 65 and older. 122 Economic Commission for Latin America and the Caribbean (ECLAC) Table II.A-8 LATIN AMERICA (18 COUNTRIES): EMPLOYMENT RATES FOR THE POPULATION AGE 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages) Education level attained Year Population group b Incomplete primary Complete primary Incomplete lower secondary Incomplete upper secondary Complete secondary Incomplete tertiary Complete university Total Argentina (urban areas) 2006 Bolivia (Plurinational State of) 2007 Brazil 2008 Chile 2006 Colombia 2008 Costa Rica 2008 Dominican Republic 2008 Ecuador 2008 El Salvador 2004 Guatemala 2006 Honduras 2007 México 2008 Nicaragua 2005 Panama 2008 Paraguay 2008 Peru 2008 Uruguay 2008 Venezuela (Bolivarian Republic of) 2008 Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older 37.9 60.4 40.0 73.4 83.1 77.7 55.2 65.5 53.0 33.3 52.1 36.0 50.9 62.3 51.3 52.2 56.8 43.3 53.1 60.8 50.5 58.3 67.5 58.1 51.4 58.8 50.5 59.3 68.0 62.4 56.4 63.6 57.5 55.7 60.8 51.5 59.2 65.0 58.8 54.9 62.7 50.9 62.6 70.0 61.5 71.4 82.5 73.0 42.4 63.7 37.8 59.8 65.7 54.7 56.4 65.3 54.5 33.4 71.6 46.7 77.1 89.8 82.2 62.9 68.7 59.4 40.9 55.8 42.1 59.2 66.6 58.8 57.5 65.4 59.1 45.4 64.9 56.3 70.6 72.6 68.0 50.9 71.0 59.6 66.3 75.4 69.0 58.9 69.9 63.2 59.7 64.6 59.6 58.1 72.1 63.2 63.2 67.2 59.4 69.3 75.0 70.9 74.6 85.3 78.4 56.3 72.3 53.3 63.4 70.5 62.9 61.8 68.1 60.7 37.4 66.6 47.6 59.7 80.2 67.6 52.0 72.3 61.4 25.9 64.1 49.4 30.9 68.7 46.2 38.9 71.0 51.5 40.6 66.4 53.2 45.9 75.9 56.8 41.8 72.5 52.0 52.1 85.1 60.2 36.9 72.7 45.5 50.9 71.8 60.0 48.0 76.2 57.2 42.6 71.3 55.0 46.6 75.3 56.7 53.7 83.5 65.7 46.6 77.6 59.9 42.9 74.8 58.4 47.4 71.8 58.0 45.1 69.8 57.6 44.8 79.5 53.6 48.3 73.2 54.8 20.3 66.2 40.9 58.5 72.0 64.3 34.6 68.8 43.2 33.2 67.9 45.4 30.2 76.9 42.5 33.2 74.6 43.4 35.3 85.7 43.8 28.1 69.5 33.8 36.4 74.2 48.6 38.8 78.7 49.2 33.2 72.1 45.2 45.8 81.5 53.9 43.7 85.5 52.8 49.3 80.1 62.0 27.8 75.0 41.1 43.3 72.6 53.2 50.7 71.8 57.7 53.4 78.4 63.2 72.3 77.0 73.1 58.6 71.7 64.1 39.7 62.4 47.2 60.5 70.7 64.3 49.0 69.7 57.8 57.7 75.1 65.2 65.2 76.8 69.4 57.3 76.7 63.9 36.2 73.5 48.4 58.9 74.0 65.6 57.1 77.1 63.8 61.5 76.3 67.1 69.2 78.7 72.3 65.1 80.4 71.3 57.8 81.9 68.2 52.0 77.2 64.7 64.8 76.0 69.0 46.3 77.7 58.3 40.2 79.4 56.1 73.9 82.9 77.1 44.8 79.4 62.7 45.1 76.8 56.5 63.6 77.1 69.3 57.2 80.0 68.4 48.4 81.6 63.5 47.2 81.4 60.7 76.1 81.6 77.1 55.6 77.1 63.8 50.2 82.0 64.7 50.4 78.1 61.2 56.2 80.7 67.3 69.9 90.7 79.5 61.3 81.7 70.5 63.8 85.9 73.1 46.9 78.8 59.5 57.5 81.5 68.6 80.6 87.2 80.9 63.7 84.9 77.5 81.3 88.2 83.5 78.2 89.2 83.3 65.7 84.8 77.5 90.5 90.0 86.6 82.5 86.4 81.6 71.6 88.7 83.3 72.1 85.9 81.2 78.6 90.5 85.2 75.0 89.5 83.8 75.5 85.8 81.4 71.9 87.5 81.6 79.9 86.3 81.0 100.0 77.7 82.7 73.1 85.9 80.2 75.9 92.8 83.1 62.6 83.9 75.3 73.6 86.6 80.7 46.5 72.4 55.7 53.0 81.9 67.5 60.9 73.0 63.7 40.8 68.1 53.1 47.0 69.9 56.9 52.2 69.2 57.9 45.4 67.4 54.5 51.5 74.9 62.3 49.1 67.6 55.5 60.4 72.7 64.9 50.9 68.7 58.0 52.3 69.8 59.4 54.7 70.5 60.4 52.0 73.2 60.3 59.0 76.2 65.6 62.1 82.7 71.4 52.7 77.8 59.2 49.1 74.4 60.7 54.8 72.4 61.3 Country 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 respective countries. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). b Total population in each age group. The category “15 and older” includes the population age 65 and older. Social Panorama of Latin America • 2010 123 Table II.A-9 LATIN AMERICA (18 COUNTRIES): UNEMPLOYMENT RATES FOR THE ACTIVE POPULATION AGE 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages) Education level attained Country Year Population group b Incomplete primary Complete primary Incomplete lower secondary Incomplete upper secondary Complete secondary Incomplete tertiary Complete university Total Argentina (urban areas) 2006 Bolivia (Plurinational State of) 2007 Brazil 2008 Chile 2006 Colombia 2008 Costa Rica 2008 Dominican Republic 2008 Ecuador 2008 El Salvador 2004 Guatemala 2006 Honduras 2007 Mexico 2008 Nicaragua 2005 Panama 2008 Paraguay 2008 Peru 2008 Uruguay 2008 Venezuela (Bolivarian Republic of) 2008 Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older 15.3 7.6 8.9 2.5 1.9 1.7 9.3 3.7 4.2 17.4 6.0 6.4 14.0 6.5 7.4 10.2 4.7 5.8 17.4 8.7 9.7 5.0 2.6 2.7 9.0 5.1 6.5 1.6 0.8 1.0 3.7 1.5 1.9 6.2 2.7 3.3 2.9 1.7 2.0 4.7 1.3 1.6 7.6 2.8 3.6 1.4 0.8 0.9 16.0 5.7 6.3 9.8 4.5 5.5 7.5 3.5 3.9 26.5 6.7 15.7 4.8 1.5 2.6 8.2 3.3 3.9 11.5 4.2 4.5 12.8 7.1 8.4 11.5 3.0 5.6 17.1 11.1 12.5 6.2 2.7 3.5 10.6 4.2 6.3 2.0 0.6 1.4 4.0 1.7 2.9 6.4 2.6 3.6 5.0 2.0 3.3 5.8 2.5 3.3 3.7 3.4 3.5 2.6 0.7 1.7 16.4 5.0 7.1 10.6 4.8 6.2 7.5 3.5 4.4 18.6 7.4 10.5 4.1 0.7 2.3 13.3 4.8 8.0 14.4 5.5 6.9 18.6 8.5 12.4 10.3 3.2 6.3 22.7 10.9 14.6 10.1 3.2 6.7 9.5 5.7 7.6 4.9 1.8 3.8 5.0 2.3 4.0 9.3 2.7 5.7 7.0 3.6 5.5 12.5 3.7 6.9 11.4 5.0 8.3 8.7 1.8 5.0 19.2 5.8 10.2 11.2 4.6 7.0 12.2 4.7 7.7 14.2 6.3 8.4 7.4 2.7 5.5 18.1 5.4 13.6 17.5 6.0 8.9 21.8 9.0 14.8 10.9 3.5 8.0 23.9 12.5 18.1 12.1 2.8 7.7 7.6 5.6 6.8 5.9 0.0 4.0 3.7 3.1 3.5 8.2 2.0 5.1 11.4 3.6 8.3 12.6 3.2 7.9 12.5 4.3 9.6 10.5 3.3 7.9 15.4 4.6 8.3 12.0 4.3 8.1 16.4 5.9 11.4 19.1 6.9 12.1 16.0 2.4 9.2 12.7 5.0 8.6 13.6 5.1 8.3 22.6 16.3 19.0 6.9 1.9 4.0 30.2 12.4 21.6 17.4 4.9 10.3 10.6 4.0 7.4 6.7 2.2 4.5 6.6 2.0 4.3 8.0 2.7 5.1 9.4 3.9 7.1 14.8 2.9 7.5 10.9 2.7 7.1 7.1 3.2 4.9 14.9 3.5 6.8 12.0 4.2 7.1 12.4 4.6 8.1 16.5 6.1 11.0 16.7 4.9 9.9 9.9 3.1 5.6 13.0 4.7 7.5 21.2 9.4 15.6 6.3 2.4 4.0 18.9 9.2 13.2 13.4 4.7 8.3 8.0 4.5 6.0 4.8 2.6 3.7 8.1 1.8 4.8 6.0 1.7 3.5 10.6 5.5 8.1 11.6 4.8 7.6 10.4 2.0 5.3 10.5 3.1 6.4 11.5 3.2 5.6 12.2 5.6 8.8 11.2 3.8 6.8 7.9 2.3 3.4 23.7 4.7 9.8 7.8 2.6 3.7 8.5 2.5 3.8 17.3 6.3 9.0 1.8 0.6 0.8 10.4 4.4 5.6 13.2 3.4 5.4 16.3 3.6 6.0 4.5 1.1 1.7 6.2 1.6 2.7 11.6 2.6 4.7 16.0 3.2 7.6 9.9 2.2 3.8 0.0 0.0 0.0 9.9 3.8 5.4 10.1 1.9 3.1 13.2 3.7 6.3 11.5 3.3 5.2 17.0 6.0 9.5 10.6 2.6 5.3 12.7 4.2 7.1 13.8 5.0 7.3 18.9 7.7 11.3 8.9 2.8 4.9 22.6 10.1 14.3 11.6 3.4 6.0 9.6 4.8 6.8 3.1 1.1 1.9 4.8 1.7 2.9 8.1 2.5 4.5 6.5 2.5 4.2 11.4 2.9 5.6 9.6 3.2 5.6 7.6 2.2 4.0 15.8 4.5 7.5 11.6 4.5 6.9 11.8 4.1 6.7 Latin America Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys conducted in the respective countries. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). b Active population in each age group. The category “15 and older” includes the population age 65 and older. 124 Economic Commission for Latin America and the Caribbean (ECLAC) Table II.A-10 LATIN AMERICA (18 COUNTRIES): DISTRIBUTION OF EMPLOYED POPULATION AGE 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages) Education level attained Country Year Population group b Argentina (urban areas) 2006 Bolivia (Plurinational State of) 2007 Brazil 2008 Chile 2006 Colombia 2008 Costa Rica 2008 Dominican Republic 2008 Ecuador 2008 El Salvador 2004 Guatemala 2006 Honduras 2007 Mexico 2008 Nicaragua 2005 Panama 2008 Paraguay 2008 Peru 2008 Uruguay 2008 Venezuela (Bolivarian Republic of) 2008 Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Latin America Incomplete primary 2.4 7.2 6.3 16.6 42.8 37.4 7.1 21.0 17.7 2.2 10.7 9.7 9.3 22.9 20.5 8.7 14.1 13.1 16.9 32.2 29.1 7.7 18.9 18.5 27.3 41.6 38.4 40.7 58.2 52.5 27.3 46.3 41.0 7.7 22.1 19.6 34.2 49.2 44.5 6.6 11.3 11.9 13.2 29.5 25.4 8.8 33.7 29.5 2.9 8.3 8.3 8.6 13.7 13.2 9.5 22.4 20.0 Complete primary 0.9 0.6 0.7 4.9 4.6 4.6 4.5 12.2 9.8 1.4 6.1 5.3 11.6 17.3 15.6 23.5 29.3 27.3 4.0 5.3 4.9 19.6 27.8 25.1 9.3 13.0 11.4 20.4 14.1 16.2 34.3 25.5 28.0 12.9 18.0 16.2 15.9 14.3 14.7 14.5 19.3 18.1 16.6 24.9 21.4 9.3 4.9 6.0 15.7 21.9 21.0 13.2 20.9 18.7 9.0 13.9 12.3 Incomplete lower secondary 27.6 30.7 30.2 12.5 7.8 8.9 25.5 23.3 23.5 7.5 13.8 12.1 21.9 17.1 18.2 20.6 15.1 16.7 14.3 16.9 15.7 21.2 11.2 13.7 25.7 15.3 18.6 16.8 7.3 11.0 15.0 7.1 9.9 35.4 24.0 27.0 21.9 14.1 16.9 20.9 17.6 18.1 20.0 12.4 14.8 16.4 10.6 12.0 28.5 21.7 22.9 20.2 17.9 18.3 25.0 20.5 21.4 Incomplete upper secondary 6.5 7.7 7.3 24.8 8.4 13.5 13.0 4.4 7.1 14.5 15.5 15.1 31.6 20.1 22.9 5.9 2.3 3.5 20.8 12.4 14.8 9.6 4.5 5.8 6.0 2.8 3.9 1.7 0.7 1.1 2.9 0.9 1.6 9.6 5.4 6.6 3.9 2.3 2.9 10.4 5.3 6.7 12.6 4.6 7.4 6.3 2.0 3.2 21.3 14.7 15.9 5.0 2.6 3.3 12.3 6.2 8.0 Complete secondary Incomplete tertiary Complete university Total 33.3 21.7 24.9 22.3 14.0 15.8 34.6 22.5 25.9 45.9 28.5 32.1 0.1 0.1 0.1 15.8 12.4 13.3 20.3 12.2 14.5 22.6 16.1 17.2 21.4 13.7 16.0 5.4 4.1 4.5 3.2 2.5 2.7 17.4 11.8 13.2 13.4 7.7 9.9 25.4 21.0 21.6 23.0 13.5 16.5 32.8 21.7 24.0 10.2 9.4 9.3 24.3 21.1 21.6 25.4 17.2 19.3 16.9 8.9 11.1 13.1 11.0 11.0 12.9 12.1 12.1 20.5 15.3 16.2 15.7 7.7 9.8 20.8 15.5 17.1 21.5 17.0 17.9 13.8 10.4 10.8 8.0 6.6 6.8 13.4 10.1 11.0 14.9 11.9 12.6 12.0 9.5 10.0 6.4 5.1 5.4 14.6 10.5 11.3 14.6 15.1 14.4 18.6 13.0 14.0 18.7 17.3 17.1 19.9 11.3 13.7 14.1 11.2 11.8 12.3 23.2 19.6 5.9 11.4 8.8 2.4 4.5 3.8 8.0 10.1 9.4 9.8 14.9 12.9 4.8 11.3 9.0 2.1 3.9 3.2 5.5 11.2 9.0 2.3 7.1 5.0 1.6 5.5 3.7 2.4 5.9 4.2 5.1 9.2 7.5 4.3 7.4 5.8 7.7 15.0 12.2 0.0 0.1 0.1 7.9 14.1 11.3 2.8 6.5 5.5 8.8 12.5 11.1 4.7 8.7 7.2 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). b Employed population in each age group. The category “15 and older” includes the population age 65 and older. Social Panorama of Latin America • 2010 125 Table II.A-11 LATIN AMERICA (18 COUNTRIES): SALARIED PROPORTION OF EMPLOYED POPULATION AGE 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages) Education level attained Country Year Population group b Incomplete primary Complete primary Incomplete lower secondary Incomplete upper secondary Complete secondary Incomplete tertiary Complete university Total Argentina (urban areas 2006 Bolivia (Plurinational State of) 2007 Brazil 2008 Chile 2006 Colombia 2008 Costa Rica 2008 Dominican Republic 2008 Ecuador 2008 El Salvador 2004 Guatemala 2006 Honduras 2007 Mexico 2008 Nicaragua 2005 Panama 2008 Paraguay 2008 Peru 2008 Uruguay 2008 Venezuela (Bolivarian Republic of) 2008 Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older 80.0 71.3 68.8 29.8 19.7 18.6 62.6 48.5 46.4 78.7 66.2 63.4 48.3 36.1 35.3 80.7 64.0 64.8 29.6 36.2 33.3 68.1 42.5 40.4 64.4 42.9 47.3 54.5 36.3 40.6 57.1 30.0 35.3 74.1 54.7 53.0 49.8 33.5 37.1 48.1 38.3 35.6 51.1 30.1 31.3 36.5 19.2 18.4 65.8 59.4 54.9 55.2 39.9 40.3 58.3 43.8 42.5 71.7 68.4 69.4 26.3 23.9 23.8 60.3 55.0 53.6 82.6 64.4 62.1 50.0 39.0 40.4 83.7 61.4 67.1 54.1 40.9 44.0 65.0 46.2 49.0 69.0 52.2 56.4 59.2 53.7 56.0 62.3 37.8 49.5 78.0 63.0 65.9 53.8 46.4 48.7 51.9 53.7 51.6 43.4 39.0 39.4 38.0 27.4 32.4 78.3 65.0 64.9 58.6 45.2 47.0 63.2 53.1 54.0 86.8 72.8 75.5 39.3 35.3 37.0 72.0 62.2 65.1 79.2 70.5 70.9 53.5 40.7 44.9 83.0 64.4 71.8 50.2 46.5 47.4 64.2 49.3 55.8 69.8 57.6 63.4 60.2 55.7 58.5 60.8 45.1 54.5 83.3 72.8 77.2 64.3 51.8 58.4 69.4 61.8 63.7 61.7 49.9 55.4 43.8 33.5 37.7 82.8 68.5 71.7 63.5 50.1 54.4 72.3 62.0 65.4 82.1 71.2 72.8 44.4 43.8 43.4 78.6 64.6 72.8 84.5 71.2 73.5 64.3 49.8 55.6 86.3 61.0 75.7 56.7 50.6 53.0 58.2 51.4 54.6 69.9 51.3 61.9 67.3 51.6 62.0 65.0 50.9 60.8 83.3 76.9 79.7 59.3 50.1 55.0 71.5 63.1 66.8 60.7 58.2 59.2 45.7 39.6 43.2 84.7 69.4 73.5 64.1 49.9 56.6 73.0 61.7 67.0 87.6 73.0 77.9 55.5 45.8 50.0 86.0 71.1 77.4 90.2 75.8 80.5 55.4 52.2 53.4 90.5 69.2 77.6 67.1 57.1 61.6 75.1 58.0 64.4 83.9 68.2 75.7 72.4 66.2 68.5 62.9 54.6 58.4 86.9 75.3 80.1 76.4 66.0 71.3 84.4 73.1 76.6 77.9 59.1 68.2 63.3 45.6 52.9 86.5 70.1 73.5 71.9 58.3 62.8 82.8 68.5 74.3 86.4 72.3 78.2 69.1 76.0 72.7 87.7 76.1 79.8 87.1 77.9 80.3 73.1 61.3 66.8 91.4 75.1 81.5 82.3 73.5 77.0 78.7 66.9 71.3 82.3 80.3 81.1 81.1 70.1 75.7 82.4 66.3 73.4 88.2 81.2 83.7 67.6 70.7 68.6 87.4 77.9 81.3 79.4 74.5 75.5 69.1 58.3 62.7 88.7 77.4 79.6 77.8 69.5 73.2 83.4 74.1 77.4 88.1 74.9 76.6 85.7 66.1 70.2 81.3 69.4 70.9 88.3 80.3 81.3 70.9 65.6 66.1 89.2 80.2 80.7 79.5 73.3 73.0 84.5 69.7 71.6 81.8 78.4 78.6 85.6 75.1 74.3 85.7 73.6 75.7 88.9 80.0 81.6 86.6 74.7 78.0 93.5 86.6 87.5 100.0 100.0 100.0 79.6 72.9 73.3 73.2 58.3 59.4 84.2 78.9 79.7 82.9 73.6 74.9 86.5 73.0 75.9 48.6 38.3 39.3 78.7 62.6 66.4 87.4 73.4 75.7 60.8 46.5 49.6 86.4 67.4 72.9 59.2 50.3 52.1 69.7 52.8 55.7 72.5 55.0 60.3 61.7 47.0 51.6 64.3 40.7 48.7 83.4 69.0 72.1 60.3 45.7 50.4 74.0 65.4 66.1 63.5 46.7 51.2 56.6 39.9 43.0 83.2 68.1 70.0 68.9 55.2 58.4 75.0 60.1 63.4 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 respective countries. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). b Employed population in each age group. The category “15 and older” includes the population age 65 and older. 126 Economic Commission for Latin America and the Caribbean (ECLAC) Table II.A-12 LATIN AMERICA (18 COUNTRIES): PROPORTION OF EMPLOYED POPULATION AGE 15-29, 30-64 AND 15 AND OVER, WORKING IN THE INFORMAL SECTOR BY LEVEL OF EDUCATION a (Percentages) Education level attained Country Year Population group b Incomplete primary Complete primary Incomplete lower secondary Incomplete upper secondary Complete secondary Incomplete tertiary Complete university Total Argentina (urban areas) 2006 Bolivia (Plurinational State of) 2007 Brazil 2008 Chile 2006 Colombia 2008 Costa Rica 2008 Dominican Republic 2008 Ecuador 2008 El Salvador 2004 Guatemala 2006 Honduras 2007 Mexico 2008 Nicaragua 2005 Panama 2008 Paraguay 2008 Peru 2008 Uruguay 2008 Venezuela (Bolivarian Republic of) 2008 Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older 56.9 61.2 63.1 89.7 89.6 91.0 45.1 61.4 62.2 37.4 52.0 53.4 85.3 87.4 88.1 50.6 62.1 62.0 80.3 77.8 78.8 68.8 82.0 82.6 76.1 81.5 80.7 61.9 75.1 71.5 76.8 74.4 76.0 64.5 74.9 75.9 77.2 83.0 82.0 79.0 81.6 84.1 85.1 88.7 88.9 85.6 89.3 90.4 62.8 66.8 69.7 68.6 73.9 74.5 63.9 72.5 73.5 70.4 65.7 67.8 88.3 87.6 88.3 48.1 55.7 55.9 39.5 52.3 53.2 82.3 80.6 81.5 44.7 56.9 54.0 66.5 70.2 69.4 70.5 77.7 76.6 67.4 65.6 66.8 53.5 52.3 53.1 61.1 56.9 59.1 59.7 66.0 64.8 67.6 69.8 69.2 73.5 67.6 70.3 84.2 79.8 81.5 83.3 84.1 83.9 55.4 57.9 59.0 62.5 63.9 64.5 62.1 64.1 64.4 52.3 54.2 54.4 84.8 82.3 83.6 36.7 46.6 43.4 36.9 47.8 46.2 75.8 74.7 75.4 42.6 49.9 47.2 67.6 65.0 65.8 72.1 71.6 72.1 60.1 58.6 59.7 43.9 42.1 43.3 58.7 47.8 54.5 51.3 52.5 52.1 59.4 62.2 60.8 55.7 53.1 54.7 74.5 63.8 69.6 81.0 78.8 80.1 46.2 48.7 48.5 57.6 57.4 57.7 49.3 52.9 51.8 46.3 50.4 50.0 81.4 74.0 78.9 28.2 39.8 32.9 29.7 42.2 39.6 55.7 59.4 58.1 39.3 49.0 43.4 58.6 59.2 58.9 72.3 66.5 69.7 53.3 54.8 53.9 36.9 30.1 34.6 49.0 37.8 45.8 46.9 37.2 42.1 61.5 53.1 57.9 49.3 51.0 50.4 68.4 56.3 64.3 79.3 74.9 77.9 36.0 38.1 37.9 53.5 55.3 54.6 43.3 48.3 46.1 39.2 37.3 38.6 66.7 63.2 64.9 16.6 25.7 21.8 19.5 30.7 27.0 62.0 59.0 59.4 25.0 37.9 32.7 43.1 47.3 45.6 52.2 55.2 54.2 30.6 38.6 34.7 28.3 24.4 27.3 40.0 30.1 35.1 35.5 37.9 36.9 44.3 46.0 45.3 29.9 35.6 33.8 47.1 45.8 46.9 62.8 66.6 65.2 27.7 29.8 29.6 40.7 44.6 43.5 27.7 34.2 31.7 26.3 27.4 27.2 38.9 26.3 31.7 8.3 13.4 11.8 12.8 18.5 17.0 34.6 39.4 37.3 10.6 19.8 16.1 22.7 16.4 18.8 31.1 33.7 32.9 22.3 20.2 21.1 15.6 22.4 18.9 17.9 21.8 20.3 22.8 23.2 23.3 41.1 32.5 37.3 19.6 24.1 22.6 24.4 18.2 21.2 44.0 47.5 46.0 14.0 16.5 16.2 28.9 29.2 29.2 20.2 21.5 21.2 13.0 13.6 13.7 7.6 16.4 14.4 8.0 10.6 10.2 4.2 5.3 5.2 15.5 17.0 16.9 4.2 7.5 7.4 0.6 13.2 12.5 15.8 19.6 19.2 9.1 15.2 14.3 9.6 6.1 6.5 6.1 12.1 10.8 10.1 15.3 14.1 14.9 17.6 17.3 5.3 9.1 8.7 40.4 0.0 11.0 21.3 20.6 21.3 5.0 8.2 8.3 12.9 10.4 11.2 11.7 13.9 13.6 38.6 39.0 39.8 70.4 68.6 71.2 25.4 40.1 36.5 20.4 34.0 31.5 58.7 64.3 63.7 32.3 42.7 40.1 51.8 56.2 55.7 58.3 62.6 63.0 54.2 60.5 59.4 47.9 58.0 54.9 56.3 56.8 57.8 44.7 51.2 50.4 61.8 67.3 66.1 43.5 45.7 47.0 63.1 65.4 65.9 64.0 67.6 68.3 36.9 40.7 41.3 45.2 49.2 48.9 39.7 48.4 47.0 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 respective countries. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). b Employed population in each age group. The category “15 and older” includes the population age 65 and older. Social Panorama of Latin America • 2010 127 Table II.A-13 LATIN AMERICA (18 COUNTRIES): SOCIAL SECURITY SYSTEM ENROLMENT RATES FOR EMPLOYED POPULATION AGE 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Percentages) Education level attained Country Year Population group b Incomplete primary Complete primary Incomplete lower secondary Incomplete upper secondary Complete secondary Incomplete tertiary Complete university Total Argentina (urban areas) 2006 Bolivia (Plurinational State of) 2007 Brazil 2008 Chile 2006 Colombia 2008 Costa Rica 2008 Dominican Republic 2008 Ecuador 2008 El Salvador 2004 Guatemala 2006 Honduras 2007 Mexico 2008 Nicaragua 2005 Panama 2008 Paraguay 2008 Peru 2008 Uruguay 2008 Venezuela (Bolivarian Republic of) 2008 Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older 9.6 25.3 21.7 10.3 11.7 15.3 21.2 27.8 24.5 46.5 49.4 46.2 5.4 9.9 8.7 46.3 57.7 53.1 9.6 18.1 16.0 9.1 17.9 16.8 7.1 7.7 7.1 8.4 8.0 7.7 5.3 5.7 5.2 7.0 9.9 8.3 2.6 5.6 4.2 11.8 17.1 13.1 0.8 4.5 3.5 1.8 7.5 8.8 29.2 46.4 39.5 28.6 40.4 36.7 12.6 18.7 16.5 9.9 19.9 15.8 16.8 11.8 15.3 24.7 43.1 38.6 41.4 52.3 49.1 9.1 19.3 16.8 56.4 67.3 63.4 22.9 25.4 24.6 14.5 22.9 21.5 15.3 24.8 21.5 15.8 23.8 19.2 15.1 16.5 15.6 14.4 18.8 17.1 10.1 17.5 13.7 18.8 34.0 28.6 1.4 6.8 5.2 2.5 6.6 5.1 43.4 61.3 55.5 37.8 58.2 52.2 18.2 32.5 28.3 24.3 35.6 31.7 9.9 15.7 13.3 34.3 51.2 44.6 48.7 56.3 54.3 12.4 25.7 20.8 62.2 66.8 64.7 18.1 29.4 25.7 15.6 27.2 21.9 22.9 32.3 27.5 21.9 31.6 25.2 20.9 25.7 22.7 25.3 34.1 30.1 17.2 22.8 19.6 29.7 45.0 38.7 3.5 15.5 9.2 3.8 19.3 13.1 53.4 66.7 61.8 42.4 63.9 54.9 27.9 43.0 36.8 31.7 42.1 38.4 12.7 22.4 17.2 42.2 57.0 47.8 52.1 60.7 57.8 35.3 41.4 38.8 63.1 69.7 65.8 25.1 31.3 28.2 18.8 27.0 23.1 26.6 36.3 30.8 25.0 29.4 26.5 26.6 32.8 28.3 29.8 52.0 41.1 22.9 29.3 25.4 35.0 47.2 40.7 7.5 30.5 15.7 3.5 22.9 10.6 65.4 73.9 70.4 43.4 67.6 53.8 35.4 48.9 41.9 46.7 54.0 50.3 15.7 22.8 20.1 68.6 71.1 69.7 72.9 70.5 71.0 20.3 37.3 30.0 78.5 74.1 75.5 42.8 43.7 43.1 30.0 43.4 38.3 55.0 55.5 55.2 46.6 44.5 45.0 30.5 36.8 33.6 42.3 48.7 45.8 35.7 38.1 36.3 60.4 63.9 62.0 17.5 35.2 25.7 15.4 34.4 26.3 74.2 81.0 78.5 60.8 77.3 70.4 56.8 62.6 59.8 49.8 59.0 54.4 38.0 63.8 53.5 73.3 81.7 78.3 69.1 78.2 75.0 54.0 61.0 57.6 83.9 84.6 83.8 64.9 69.5 67.7 43.5 61.0 54.4 63.1 77.0 70.9 49.7 53.4 51.4 53.7 51.4 52.1 47.9 61.2 55.7 40.1 50.6 45.0 72.7 74.7 73.4 38.7 58.6 50.5 28.9 54.2 43.8 82.1 87.9 85.8 69.9 84.4 77.3 59.9 72.3 67.2 67.3 68.5 67.2 46.0 64.0 60.2 76.5 83.0 80.7 73.8 86.0 82.6 72.7 75.6 74.8 92.9 89.0 88.5 75.6 69.5 69.2 61.5 70.8 69.6 67.2 77.0 74.9 53.4 57.1 54.5 66.1 68.4 67.5 57.2 63.7 61.6 59.6 59.3 59.1 87.1 86.8 86.1 59.6 100.0 89.0 42.8 76.2 69.0 88.5 94.9 93.6 82.7 91.0 88.7 66.9 75.0 72.7 41.4 49.0 45.6 18.1 26.2 24.3 51.9 55.2 52.6 66.3 66.4 65.1 31.1 34.3 32.4 68.1 71.9 69.7 34.6 35.9 34.7 24.8 35.3 31.5 29.2 30.5 28.9 20.8 20.9 19.9 21.1 20.0 19.5 30.2 34.0 31.5 17.1 19.0 17.4 46.0 53.2 48.7 11.7 20.0 16.0 15.0 30.6 25.1 62.1 71.8 67.4 55.9 71.4 65.3 40.3 46.1 42.9 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 respective countries. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). b Employed population in each age group. The category “15 and older” includes the population age 65 and older. 128 Economic Commission for Latin America and the Caribbean (ECLAC) Table II.A-14 LATIN AMERICA (18 COUNTRIES): LABOUR INCOME OF EMPLOYED POPULATION AGE 15-29, 30-64 AND 15 AND OVER, BY LEVEL OF EDUCATION a (Dollars at constant 2000 prices, expressed in purchasing power parity) Education level attained Country Year Population group b Incomplete primary Complete primary Incomplete lower secondary Incomplete upper secondary Argentina (urban areas) 2006 Bolivia (Plurinational State of) 2007 Brazil 2008 Chile 2006 Colombia 2008 Costa Rica 2008 Dominican Republic 2008 Ecuador 2008 El Salvador 2004 Guatemala 2006 Honduras 2007 Mexico 2008 Nicaragua 2005 Panama 2008 Paraguay 2008 Peru 2008 Uruguay 2008 Venezuela (Bolivarian Republic of) 2008 Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older Age 15-29 Age 30-64 15 and older 567 825 801 151 191 168 202 282 260 380 554 540 315 376 361 525 546 531 579 667 640 169 200 189 217 305 271 202 359 319 145 197 175 254 360 337 216 430 354 205 271 254 235 377 329 123 203 180 271 413 386 485 555 529 242 332 307 685 831 772 136 252 214 221 409 380 369 602 593 346 472 441 544 651 615 568 865 779 185 290 265 286 414 373 251 560 400 208 339 274 291 518 458 255 587 439 231 406 364 247 472 407 145 238 192 341 507 471 541 671 638 286 470 424 718 1 091 995 143 297 233 281 512 432 433 627 598 338 512 449 557 713 646 593 957 851 172 344 262 299 458 377 268 919 496 259 452 334 354 640 516 338 621 468 368 577 503 279 683 477 176 361 277 376 605 535 566 718 664 335 598 500 863 1 411 1 284 170 431 267 301 583 412 448 748 688 473 672 591 554 793 654 663 948 830 168 394 279 311 533 405 268 888 478 278 462 333 356 907 640 377 866 580 356 589 474 339 646 449 153 376 237 424 779 666 532 688 613 362 730 548 Latin America Complete secondary 949 1 596 1 357 285 415 353 458 801 650 563 931 803 357 812 606 725 948 859 601 1 041 838 281 491 409 414 632 522 484 910 698 364 700 536 465 901 713 422 702 627 504 732 661 499 844 662 272 465 377 494 981 854 619 819 748 480 837 686 Incomplete tertiary 1 022 1 873 1 526 345 568 480 750 1 502 1 240 784 1 542 1 301 606 1 027 823 976 1 458 1 254 675 1 589 1 231 354 624 517 568 864 733 525 1 075 797 512 795 659 643 1 505 1 169 528 919 728 597 964 822 642 1 203 1 012 416 645 544 615 1 207 1 047 689 964 838 676 1 343 1 086 Complete university Total 1 349 2 485 2 291 738 1 115 1 031 1 539 2 886 2 609 1 771 3 116 2 860 1 212 2 073 1 880 1 483 2 470 2 314 1 925 2 806 2 649 584 957 926 782 1 235 1 152 1 013 2 248 2 225 1 221 1 730 1 614 1 036 2 272 2 022 1 028 2 266 1 865 871 1 575 1 453 463 711 644 576 1 011 906 970 2 215 2 070 980 1 328 1 243 1 165 2 165 1 964 929 1 597 1 406 244 401 329 427 747 631 671 1 114 998 507 779 684 709 1 016 905 651 1 048 907 247 425 362 334 497 423 296 630 493 275 427 353 427 832 684 338 670 527 443 733 633 379 639 530 274 454 375 451 838 731 628 810 746 449 789 666 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. a The length of education cycles was defined in accordance with the 1997 International Standard Classification of Education (ISCED). b Employed population in each age group. The category “15 and older” includes the population age 65 and older. Social Panorama of Latin America • 2010 129 Table II.A-15 LATIN AMERICA (18 COUNTRIES): RESULTS OF THE GENERAL REGRESSION MODEL (WITH CONTROL VARIABLES) FOR ASSESSING THE IMPACT OF ADDITIONAL YEARS OF SCHOOLING PER EDUCATIONAL CYCLE ON WAGES OF WAGE-EARNERS AGE 20 AND OLDER WHO WORK 20 OR MORE HOURS PER WEEK, AROUND 2008 Country Argentina (urban areas) Bolivia (Plurinational State of) Brazil Year Parameters a β0 β1 β2 β3 β4 0.0076 (2.31) 0.0258 (26.82) -0.0003 (-15.21) 2006 5.079 0.0304 (5.94) 0.0453 (7.55) 2007 3.110 0.0512 -0.0219 * 0.1355 0.0422 (3.56) (-1.13) (10.91) (12.92) β7 0.4781 (55.78) 0.1579 (21.99) -0.0006 0.3050 (-9.28) (10.12) β8 0.285 0.1829 0.5922 0.452 (6.91) (15.34) 0.0670 0.0249 0.1628 0.0364 -0.0004 0.2687 0.2450 0.1872 (9.49) (92.67) (73.84) (-41.54) (42.38) (62.87) (29.86) 0.0453 0.1188 0.0210 -0.0002 0.2429 0.2066 0.0741 (14.6) (53.4) (36.69) (-21.29) (41.98) (43.91) (15.34) 0.375 4.859 Dominican Republic 2008 3.765 Ecuador 2008 3.543 0.0508 0.0047 * 0.0849 0.0297 -0.0004 0.4080 0.1180 0.0771 (1.75) (54.71) (65.37) (-38.94) (101.22) (35.55) (11.08) 0.0100 0.0457 0.1043 0.0183 -0.0003 0.2954 0.2300 0.0071 * (2.79) 2008 3.746 0.0296 0.484 (23.99) Costa Rica 2008 4.440 Adjusted R2 a … … (12.09) Colombia 2006 3.651 β6 (31.16) Chile 2008 β5 (9.29) (21.98) (15.11) (-11.43) (27.33) (24.82) (0.79) 0.0443 (7.23) 0.0003 * (0.03) 0.1373 (15.59) 0.0292 (14.2) -0.0004 (-10.88) 0.3031 (14.8) 0.2171 (13.51) 0.0909 (5.21) 0.436 0.397 El Salvador 0.0483 0.0260 -0.0003 0.2841 0.1755 0.1273 (3.63) (12.11) (22.81) (-14.92) (28.62) (18.02) 0.0368 0.0346 0.1019 0.0255 -0.0004 0.2313 0.1079 0.1387 (6.33) (16.42) (17.27) (-13.99) (18.95) (9.56) (11.73) 0.0490 0.0239 0.0320 -0.0004 0.0972 0.1568 0.0804 (8.09) (3.05) (19.5) (-15) (6.51) (11.52) 0.0866 0.0224 0.0354 0.0314 -0.0004 0.6710 -0.0022 * 0.4443 (3.85) (5.31) (19.63) (-14.36) (45.53) (-0.18) Panama 0.0455 0.0580 0.0395 -0.0005 0.3324 0.1762 0.2136 (8.91) (13.02) (34.66) (-24.36) (34.07) (19.56) 0.0518 0.0277 0.0609 0.0289 -0.0004 0.2150 0.1560 0.1019 (3.26) (6.28) (12.3) (-9.04) (12.18) (8.97) (5.53) Uruguay 2008 2008 4.567 0.0088 * 0.0613 0.0220 -0.0003 0.5541 0.1867 0.1107 (1.42) (15.43) (17.83) (-10.36) (45.5) (18.34) 0.0555 0.0215 * 0.0891 0.0378 -0.0005 0.3053 0.1088 0.0413 * (1.75) (7.54) (13.61) (-9.98) (12.55) (4.9) 0.0626 -0.0257 0.0729 0.0262 -0.0003 0.4312 0.3266 0.2518 (-2.54) (11.68) (16.5) (-10.12) (28.57) (24.71) 5.415 0.343 0.374 (10.59) 0.506 (15.44) 0.403 (1.69) 0.0292 0.0578 0.0615 0.0371 -0.0004 0.3575 0.2155 -0.0306 (5.81) Venezuela (Bolivarian Republic of) 2008 3.322 0.0526 (8.88) Peru 3.633 0.570 (21.06) (5.92) 2008 4.200 0.0449 (10.22) Paraguay 2008 3.421 0.419 (32.48) (11.1) 2005 4.127 0.390 (6.38) (11.99) Nicaragua 2008 2.945 0.0751 (23.03) Mexico 2007 3.669 0.452 (12.51) (22.67) Honduras 2006 4.138 0.0167 (10.59) Guatemala 2004 0.0430 (12.08) 0.488 (10.32) (18.31) (42.36) (-27.13) (45.74) (32.77) (-2.48) 0.0294 (12.47) 0.0067 (2.13) 0.0615 (26.69) 0.0193 (28.76) -0.0003 (-19.3) 0.3599 (54.18) 0.1454 (28.91) … … 0.367 0.357 0.333 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. a β : Constant term (wage value —natural log— with other variables equal to 0); β : Regression coefficient for the number of years of schooling. Gives the rate of private return for 0 1 each additional year of primary schooling; β2: Regression coefficient for the number of additional years of schooling after completing the primary cycle. The expression β1 + β2 gives the rate of private return for each additional year of secondary schooling; β3: Regression coefficient for the number of additional years of schooling after completing the secondary cycle. The expression β1 + β2 + β3 gives the rate of private return for each additional year in the higher education cycle; β4: Regression coefficient for the individual’s potential experience; β5: Regression coefficient for potential experience squared; β6: Regression coefficient for the dummy variable for informal or formal market integration (informal integration =0); β7: Regression coefficient for the dummy variable for sex (female=0); β8: Regression coefficient for the dummy variable for geographic area (rural areas=0). T-statistic values for the significance test for each regression are shown in parentheses. An asterisk (*) shows when the regression is not statistically significant at 5%. Adjusted r2: Squared correlation coefficient, adjusted for sample size and number of independent variables. Social Panorama of Latin America • 2010 131 Chapter III Public social spending in Latin America: general trends and investment in developing the skills of the new generations A. Introduction In the past two decades, the countries of the region have made a substantial effort to increase the resources available for social policy implementation. Practically all public social spending items have increased not just in absolute terms but in relative terms, too, except for a few cases and periods. Much of this effort has been concomitant with economic growth, which has helped to expand resources. Overall budget growth, particularly social spending budgets, has outpaced GDP growth (especially in the 1990s). But minor GDP contractions have also led to larger-than-necessary budget cuts. While procyclical budget execution is generally driven by fiscal responsibility and international recommendations, budget cuts in some spending areas, such as education, health and social security, can come at substantial economic and social cost. To counter this trend, most of the region’s countries took what have so far been temporary measures to increase public spending in order to deal with the fallout from the global financial crisis. Many of these spending measures were taken to diminish the effects of the crisis on the real economy and contain the increase in unemployment and ultimately poverty. The following pages will review both long-term trends and the latest shifts in public social spending growth in countries for which adequate information is available, from the time the potential impact of the international economic crisis was first identified. This chapter will also examine trends in social spending geared towards the development and protection of the new generations, in accordance with the approach chosen for the 2010 edition of Social Panorama of Latin America. Specifically, it will review the countries’ efforts to invest more in education and the factors that have been most important in the expansion of resources to develop the skills of the region’s children and young people. Lastly, it will analyse the distributive impact of social spending, showing that the beneficiaries of stepped-up investment to extend educational coverage are, precisely, children and young people in the lowest income strata. This furthers social integration and mobility and lays a broader foundation for future economic development. 132 Economic Commission for Latin America and the Caribbean (ECLAC) B. Public social spending in Latin America and effects of its procyclicality on economic growth Public social spending has risen substantially in the region over recent decades, both absolutely (from US$ 445 per person in 1990-1991 to US$ 880 in 2007-2008) and in terms of the macroeconomic priority given to it (up from 12.3% of GDP to 18.4% of GDP). Investment in social areas has also increased as a share of public social spending. Nonetheless, both public spending generally and social spending in particular remain very procyclical, especially in education and health. However, the great majority of countries developed active social and fiscal policies to confront the international financial crisis, not merely maintaining but actually increasing spending to implement a variety of pro-employment and subsidy and transfer programmes. This reflects a recognition that periods of economic contraction are precisely when social policy efforts need to be stepped up and resources increased. As different editions of Social Panorama of Latin America have noted, the region has made a fairly systematic effort to increase public spending, and social spending in particular. This began after a period of crisis, structural adjustment and subsequent fiscal measures that resulted in sharp cutbacks in all expenditure items, market deregulation and privatization of social services, among other actions recommended by the international financial organizations and embodied in the Washington Consensus. While most of the region’s countries implemented these reforms, at different speeds, between the mid-1980s and late 1990s, social spending recovered gradually in the latter decade, largely thanks to economic growth that was relatively sustained if also highly volatile. In line with the recommendations for greater fiscal discipline, public expenditure trends in the region closely tracked the ups and downs of its economies. Put another way, volatile growth was reflected in the highly procyclical behaviour of fiscal expenditure, with recurrent cutbacks in public spending precisely at times of economic retrenchment and rising unemployment and poverty. In the mid-1990s, new social policy tools began to be tested with a view to addressing the persistent problems of poverty, equity and inequality. The economic crises of the late 1990s (the Asian crisis, natural disasters in Central America, falling international prices for staple grains, the slowdown in the world economy in 2000 and, shortly afterwards, the crisis affecting Argentina and Uruguay) prompted a reformulation of social policy generally and anti-poverty policies in particular. New approaches emerged, emphasizing protection against falling incomes, income poverty and social exclusion that expose individuals to vulnerability and risk (Serrano, 2005). This shift was cast primarily in terms of new networks and social protection system reforms. Among other things, they spurred a drive for coordinated social programmes combining traditional social security, social services and assistance programmes. Although these were originally seen as provisional responses to particular crises, there has been an increasing determination to strengthen these networks in pursuit of greater income stability and minimum levels of wellbeing, given the evidence that the problem of economic volatility has not been eradicated once and for all (Acosta and Ramírez, 2004). The guiding principle behind this new social policy trend was so-called social risk management. One of the risks considered when programmes of this type are designed is the absence or loss of employment, particularly for certain population groups (young people, women, ethnic minorities, the low-skilled) and the drop in household income when the head of household loses his or her job. Also considered are the risks associated with certain stages of the life cycle (such as old age or Social Panorama of Latin America • 2010 motherhood), the negative effects on human skills that arise from dropping out of school, inadequate nutrition and lack of health care, and the impact of natural disasters (floods, earthquakes, droughts). The programmes that have arisen under this new social policy approach can largely be divided into three major groups: job creation programmes (public works, subsidies for new jobs and subsidized credit lines), training programmes (young people and the unemployed) and conditional transfer or co-responsibility programmes. The growth of social spending since the 1990s, the rise of these more integrated new forms of social policy and the expanded coverage of public-sector social transfers in the present decade have borne down on poverty and, in some cases, on inequality. This was particularly true of the years running up to the 2008 global financial crisis. The actual and threatened impact of the crisis in terms of social costs gave even greater impetus to the debate in the region about the role of the State as regulator, arbiter, main redistributor of resources and guarantor of more universal systems of social protection against vulnerability and poverty. The countercyclical measures adopted by most national States in Latin America and the Caribbean when faced with the impact of the crisis on employment, economic activity and social vulnerability reflect this change of course. The countercyclical logic of social spending has played a decisive part in forestalling the social costs of the crisis, unlike what happened during the debt crisis of the 1980s. Although the social role of the State in response to the crisis has varied from country to country, depending on the volume of resources it can mobilize, its institutional strength and the degree of coordination between anti-crisis measures and between these and more permanent sectoral programmes, there can be no doubt that the idea of a more active role for the State and the idea that social spending is less subject to the vagaries of economic growth have gained purchase in the region. This chapter will analyse long-term trends in public social spending and use the information available to examine the reaction of the Latin American States to the recent financial crisis, including anti-poverty programmes. The long-term trend of public social spending Figure III.1 LATIN AMERICA (21 COUNTRIES): TOTAL PUBLIC SPENDING AND PUBLIC SOCIAL SPENDING (WEIGHTED AVERAGES), 1990-2008 (Percentages of regional GDP and total public spending) 28.5 28.0 25.9 64.7 25 58.9 20 70 65 60 18.4 15 10 55 15.3 12.3 50 45 5 Percentage of total public spending 30 43.8 40 2007 2008 2005 2006 2003 2004 2001 2002 1999 2000 1997 1998 1995 1996 1993 1994 1991 1992 0 1990 As the countries of the region came to recognise the importance of public social spending as an instrument for channelling resources to the poorest in society and the role of social development as a driver of economic development, they began to ratchet up this spending. Public spending, and social spending in particular, has burgeoned across the region over the past two decades: while public spending has held steady at around 26% of GDP, social spending rose from 12.3% of GDP in 1990-1991 to 18.4% in 2007-2008. Social spending as a percentage of total public spending has thus risen considerably, from just under 45% to 65% (see figure III.1). The countries are enormously diverse, not only in the extent to which they have increased social spending but also in their past and current levels of public spending. There are obvious differences in the macroeconomic priority they give to social spending, which ranges from less than 8% of GDP in Ecuador, Guatemala and Peru (central government) to more than a fifth of GDP in Argentina, Brazil, Cuba and Uruguay (see box III.1 for institutional coverage of public social spending), even though virtually all the countries have striven to increase such coverage since the 1990s. Percentage of GDP 1. 133 Total public spending as percentage of GDP Public social spending as percentage of GDP Ratio of social spending to all spending Source: conomic Commission for Latin America and the Caribbean (ECLAC), social E expenditure database. 134 Economic Commission for Latin America and the Caribbean (ECLAC) Box III.1 UPDATING SOCIAL EXPENDITURE FIGURES To update social expenditure figures for the present edition of Social Panorama of Latin America, up-to-date public social spending data running up to 2009 were obtained in accordance with the total and sectoral series published in previous editions. Information up to 2009 was obtained for 6 of the 21 countries considered, and these figures have been published because it is important to have recent data, even if they are provisional, estimated or incomplete. The figures were updated during the third quarter of 2009; the cut-off point was mid-September. In most cases it was possible to collect data on central government budget execution, and in a number of countries figures were obtained for actual spending by agencies with budgetary autonomy, local governments and non-financial public enterprises. Although differences in institutional coverage make comparisons between countries difficult, the most extensive data available for each country are being published except when they involve significant constraints for constructing a series for 1990-2009. This is because ECLAC’s primary interest is to establish the amount of public social spending in each country as accurately as possible, in order to convey the effort being made by States in this area. The following is a classification of the countries by institutional coverage of the social expenditure series used: • Total public sector (NFPS + FPS): Costa Rica • N o n - f i n a n c i a l p u b l i c s e c t o r (GG + NFPE): Argentina, Brazil and Plurinational State of Bolivia • General government (CG + LG): Peru and El Salvador • Central government (BCG + AA): Chile, Colombia, Cuba, Dominican Republic, Ecuador, Guatemala, Honduras, Jamaica, Panama, Trinidad and Tobago and Uruguay • Budgetary central government: Bolivarian Republic of Venezuela, Mexico, Nicaragua, and Paraguay where: AA: agencies with budgetary autonomy; BCG: budgetary central government; CG: central government; LG: local government; NFPE: non-financial public enterprises; PFE: public financial enterprises. Considering that a number of countries only very recently adopted the classification system of the International Monetary Fund (IMF) Government Finance Statistics Manual 2001, which is harmonized with the 1993 System of National Accounts (SNA), the 1990-2009 series is not always compatible at the subfunctions or subgroups level, or both. Most of the countries publish the functional classification in aggregated form and use classifications of their own. Data continuity problems brought about by the switch include a lack of information for the full series or for certain years or functions (or both) in particular cases. This is the case with social protection in the Plurinational State of Bolivia between 1990 and 1994, social protection in El Salvador between 1990 and 1992 and in Trinidad and Tobago between 1990 and 1999, and figures relating to social security in Nicaragua. In other countries such as Jamaica and Trinidad and Tobago, it was not possible to construct the full series from 1997 to 1999 as data on intermediate periods were lacking. The 2009 and 2010 figures for Colombia are provisional: a methodological change and a switch in the basis for calculating GDP mean that the series is not comparable between 19901999 and 2000-2009, and the guidelines of the Government Finance Statistics Manual 2001 are being incorporated into the classification of functions. In Peru, whereas the 1990-1999 series covers budgetary central government, the series for 2000 onward is for general government. Lastly, the Bolivarian Republic of Venezuela has series for agreed public social spending (budget act and amendments as of 31 December each year) and for disbursed public spending, the latter beginning in 1999. The institutional coverage of the country’s figures is budgetary central government. Because it is a federal country, the published figures may underestimate total social spending by more than those of other countries reporting this coverage. The same is true of Mexico, although what is known about highly decentralized spending execution in that country indicates that the figures should be read more carefully than in other cases because social spending execution may be substantially underestimated. ECLAC (2006) gives examples of centralized and decentralized execution of social spending. Like previous editions, Social Panorama of Latin America 2010 uses biennial averages to present social spending data. The indicators published are for total public social spending and its component functions and sectors (education, health, social security and assistance, and housing, sanitation and other functions not included in the above categories) as a percentage of GDP, in dollars per capita, and as a percentage of total public spending. In the case of this last indicator, official information from the countries is used, but these figures may differ from those based on other systems (such as economic or administrative classification of spending) because some include interest payments on the public debt and others do not, and because different methodologies are used to classify disbursements. The figures used to calculate 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 to obtain per capita social spending, 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. The figures for constant 2000 dollar GDP are official ECLAC statistics; the population figures come from projections by the Latin American and Caribbean Demographic Centre (CELADE)-Population Division of ECLAC. Source: Economic Commission for Latin America and the Caribbean (ECLAC), Social Panorama of Latin America 2006 (LC/G.2326-P), Santiago, Chile, 2007. United Nations publication, Sales No. E.06.II.G.133; for GDP: ECLAC, on the basis of official figures; for population: Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC; and United Nations, System of National Accounts 1993 (ST/ESA/STAT/SER.F/2/Rev.4), New York, 1993. United Nations publication, Sales No. E.94.XVII.4. Social Panorama of Latin America • 2010 135 Only in Ecuador did social spending become less of a macroeconomic priority between 1990-1991 and 2007-2008. In Brazil, Colombia, Cuba, El Salvador, Paraguay and the Plurinational State of Bolivia such spending increased by more than 6 percentage points in this period. Other than in Cuba, Ecuador, Honduras and Nicaragua, the largest increases in social spending as percentages of GDP were during the 1990s (see figure III.2.A and table III.A-1). However, the differences between countries lie not only in the share of GDP devoted to social spending but also in the wealth level of each country. Different development levels and tax burdens and thence the size of general public budgets and, specifically, social budgets are behind the large disparities in the amount of resources per capita that States can spend on social areas such as education, health and social security and assistance. The lowest spending per capita is in Ecuador, Guatemala, Honduras and Nicaragua; the first two give social spending a low priority as a share of GDP. The countries spending the largest amounts per capita are Argentina (more than US$ 2,000 per capita), Brazil, Cuba, Trinidad and Tobago and Uruguay, all of which have social spending of over US$ 1,000 a year per inhabitant. On average, the highest-spending countries devote 13 times more per capita funding to this area than those that spend the least. The Dominican Republic, El Salvador, Paraguay, Peru and Trinidad and Tobago are the countries which increased funding the most in absolute terms between 1990-1991 and 2007-2008 (at least tripling their per capita expenditure in the period), although only Trinidad and Tobago currently has a high level of expenditure (see figure III.2.B and table III.A-2). Figure III.2 LATIN AMERICA (21 COUNTRIES): EVOLUTION OF SOCIAL SPENDING RELATIVE TO GROSS DOMESTIC PRODUCT AND SOCIAL SPENDING PER CAPITA B. Social spending per capita A. Social spending (as a percentage of GDP) 40 Simple average (21 countries) 2007-2008 2004-2005 2000-2001 1997-1998 1994-1995 1990-1991 35 30 25 Weighted average (21 countries) 2007-2008 2004-2005 2000-2001 1997-1998 1994-1995 1990-1991 14.2 12.8 12.4 11.3 11.0 9.5 (dollars at constant 2000 prices) 2 400 18.0 15.9 15.5 14.7 14.4 12.2 Simple average 2007-2008 2004-2005 2000-2001 1997-1998 1994-1995 1990-1991 2 000 1 600 Weighted average 2007-2008 2004-2005 2000-2001 1997-1998 1994-1995 1990-1991 666 506 466 421 380 315 885 691 642 601 557 440 1 200 20 18.0 880 800 15 12.2 10 440 400 NFPS BCG 1990-1991 2000-2001 GC 1994-1995 2004-2005 1997-1998 2007-2008 NFPS GG 1990-1991 2000-2001 1994-1995 2004-2001 Ecuador Honduras Guatemala Jamaica Dominican Rep. Colombia Chile Panama Cuba BCG Trinidad and Tobago Uruguay Paraguay Nicaragua Venezuela (Bol. Rep. of) Peru Mexico Costa Rica PS El Salvador Brazil Bolivia (Plur. State of) Ecuador Guatemala Dominican Rep. Panama Jamaica Honduras Trinidad and Tobago Chile GCP Colombia Cuba Uruguay Paraguay Mexico Nicaragua Peru Venezuela (Bol. Rep. of) Costa Rica PS El Salvador Bolivia (Plur. State of) Brazil Argentina 0 0 Argentina 5 CG 1997-1998 2007-2008 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. Note: NFPS = non-financial public sector; PS = public sector; GG = general government; BCG = budgetary central government; CG = central government. 2. The procyclicality of social spending relative to economic growth: an ongoing debate Although the region’s countries have steadily increased th1eir public budgets, particularly where social spending is concerned, in most cases these have fluctuated for reasons generally determined by local economic developments. This section takes a look at the procyclical nature of spending. Economic Commission for Latin America and the Caribbean (ECLAC) Once again, there are outliers in the region. While GDP and social spending are highly correlated in countries such as Argentina, Brazil, the Dominican Republic, Mexico, Panama and Uruguay, in others such as Costa Rica, Guatemala, Honduras, Jamaica, Paraguay, the Plurinational State of Bolivia and Trinidad and Tobago social spending is fairly independent of growth. However, this does not just mean that the social services budget is protected during economic downturns, but also that any budget growth can far outpace (or be outpaced by) upswings in the economy. The differences between the countries that are most and least procyclical in their social spending can be seen in figure III.4. Figure III.4 LATIN AMERICA (SELECTED COUNTRIES): CHANGES IN SOCIAL SPENDING RELATIVE TO ECONOMIC GROWTH (Percentages) A. Countries with highly procyclical spending: Argentina, Dominican Republic, Mexico and Uruguay a 25 20 15 10 5 0 2007 2008 2005 2006 2003 2004 2001 2002 1999 2000 1997 1998 1995 1996 1993 -10 Figure III.3 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): ANNUAL CHANGE IN PUBLIC SOCIAL SPENDING, TOTAL PUBLIC SPENDING AND GROSS DOMESTIC PRODUCT, 1991-2009 a (Percentage change) 1994 -5 1991 The debate centres on the following considerations. Although budgeting tied to the economic cycle generally reflects responsible fiscal management, it can sometimes impair economic and social development processes that depend on a stable flow of resources. This is because many of the processes involved in the production of public services entail a large proportion of recurrent expenditure deriving from legal or contractual commitments, such as wages and retirement and other pensions. Budgetary fluctuations can sometimes affect pay levels and continuity for the personnel required to maintain public services. In other cases the non-discretionary nature of some public spending results in drastic cuts to investment (for example, in building, maintaining, renovating and equipping public facilities such as schools and hospitals). Accordingly, while responsible fiscal management is vital to long-term economic development, the over-adjustments often made to public spending and social spending when growth slows can adversely affect the very processes that prudent fiscal management is meant to safeguard. As a rule, when cuts to public social spending occur in the region, they are sharper than the slowdown in growth: between 1991 and 2008, there were 45 episodes in which countries cut public social spending in absolute terms. On 93% of these occasions (42) the cut was larger than the decline in GDP (including periods in which GDP continued to rise). Notwithstanding this, social spending is less sensitive to the economic cycle than the overall budget, as figure III.3 shows. For all its procyclicality, then, social spending has been better protected against economic fluctuations than non-social public budget items. 1992 136 B. Countries where spending is not procyclical: Costa Rica, Paraguay, Plurinational State of Bolivia and Trinidad and Tobago a 25 35 20 30 15 25 10 20 5 15 10 0 5 -5 0 -10 Annual change in GDP Annual change in public social spending Annual change in total public spending Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a Weighted averages. The 2009 expenditure figures are estimates based on information from seven countries. Annual change in public social spending 2008 2007 2005 2006 2003 2004 2001 2002 1999 2000 1997 1998 1995 1996 1993 1994 1991 1992 2009 2007 2008 2005 2006 2004 2003 2001 2002 2000 1999 1997 1998 1996 1994 1995 1993 1991 -5 1992 -15 Annual change in GDP Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a Simple average of growth rates in the countries. Social Panorama of Latin America • 2010 137 Lastly, evaluation criteria based on how closely or otherwise the budget tracks economic growth cycles provide only a general guide: the fact of public spending not being highly procyclical does not mean that the social area is neglected. In most cases, spending has effectively expanded. Inertial social spending may be insensitive to economic downturns, but it will not be sensitive to economic expansion either, and wholly countercyclical social spending is not desirable because it would fall just when the economy was growing. Of 3. The evolution of social spending by sector As social spending has risen, all sectors or major spending items have risen with it, but this growth has been uneven. Social security and assistance have recorded the strongest increase: almost three percentage points of GDP, or just over half of the total rise in public social spending. This is due in some degree to the new emphasis on anti-poverty policies and conditional cash transfer programmes in particular, as will be seen further on. At the same time, population ageing and associated commitments for funding retirement and other pensions, together with improvements to social security systems in a number of the region’s countries (including the strengthening of their non-contributory components), have caused this sector to grow faster than the rest (see figure III.5). Figure III.5 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): EVOLUTION OF PUBLIC SOCIAL SPENDING BY SECTOR, 1990-1991 TO 2007-2008 (Percentages of GDP) 22 5.9 a 20 18.0 18 15.8 16 14 12 2.9 12.2 1.7 10 0.8 6 4 3.2 a a 8 4.3 4.9 2.9 a 7.7 6.9 3.7 3.3 0.5 1.2 Total social spending Education spending Health spending a 4.8 2 0 course, it is to be expected that some specific spending items will indeed be countercyclical, like those which finance emergency programmes at times of crisis and rising poverty and tail off in periods of economic growth. Others may prove more stable because they involve regular payment commitments, as is the case with social security. Still others can be expected to expand along with the economy to a reasonable degree that does not trigger macroeconomic imbalances or a tendency towards deficit spending. Social security and assistance spending 1990-1991 1994-1995 2004-2005 Housing and other spending 1997-1998 2000-2001 1.7 1.4 2007-2008 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a Percentage point increases in spending between 1990-1991 and 2007-2008. Education spending is the item that has seen the next-largest increase, in accordance with the international commitments entered into by the region’s countries, rising by just over 50% as a proportion of GDP. This substantial rise in resources has not been free of volatility, however, as the following section will discuss. Together with social security and assistance, education spending accounts for almost 80% of the rise in total social spending between 1990-1991 and 2007-2008. Lastly, of the sectors that can be examined separately across all the countries analysed, spending on public health systems saw the lowest growth over almost two decades, lagging behind even housing expenditure and related items (such as water and sanitation). This is partly due to the tendency in a number of countries for health service expansion to be carried out by the private sector, in line with the reforms that followed the structural adjustment of the 1980s. Another reason, though, is that this is a highly procyclical item with a significant investment spending component that is cut back severely at times of economic contraction or slow growth (ECLAC, 2008a). Uneven growth across spending items led to something of a shift in the weight of different sectors within total social spending. Social security increased its share to almost 43% of the region’s social expenditure. The share of education also rose slightly, to 27%, all to the detriment of spending on housing (9.7%) and, above all, health, whose share of total social spending dropped from 24.1% in 1990-1991 (just under US$ 110 per capita) to 20.5% in 2007-2008 (just over US$ 180 per capita). 138 Expenditure trends during the financial crisis countries. These data show that while GDP contracted in absolute terms in most of these countries, they all continued to increase their social spending. A number had already done so in 2008, and five of the seven countries (Brazil, Colombia, Guatemala, Honduras and Panama) made a still greater effort in 2009. Although the others also stepped up social spending, they did so more slowly than in 2008. All the countries other than Cuba also increased total public spending, albeit almost always to a lesser degree than its social component. As figure III.6 shows, however, Cuba, Guatemala and Honduras had to make absolute cuts in public spending on non-social functions to be able to increase their social spending. Of the countries analysed, only Brazil and Panama increased non-social spending by more than social spending (Panama by almost twice as much). Figure III.6 LATIN AMERICA (SEVEN COUNTRIES): CHANGES IN PUBLIC SPENDING, SOCIAL SPENDING, NON-SOCIAL SPENDING AND GROSS DOMESTIC PRODUCT DURING THE FINANCIAL CRISIS (Percentage change) 50 40 30 20 10 0 -10 Brazil Chile Colombia Change in public spending Change in non-social spending Cuba 2009 2007 2008 2009 Honduras 2006 2007 2008 2009 Guatemala 2006 2007 2008 2009 2006 2007 2008 2006 2007 2008 2009 2009 2006 2007 2008 2009 2006 2007 -20 2008 The region’s countries adopted a broad range of measures in the face of the financial crisis. Unlike action taken on similar occasions (such as the crises of the 1980s and 1990s), these measures set out not to shrink spending but to expand it, at least temporarily (see figure III.3). Measures of this kind (including those announced and those actually implemented) encompassed monetary and financial policy, fiscal policy, exchange-rate and foreign trade policy, sectoral policies, employment and social policies and multilateral financing (ECLAC, 2010c). Broadly speaking, they were aimed, first, at restoring confidence and making financial markets operational again and, second, at strengthening demand. The range of measures was quite wide, not just because the impact of the crisis varied from one country to another, requiring different instruments to counter it, but also because of differences in each country’s capacity to implement initiatives, as determined by the availability of resources. In the early stages, central banks mobilized to inject liquidity into financial systems in order to restore normal functioning to local credit markets or provide financing resources where these were in shortest supply. But the nature of the crisis, particularly the nose-dive in confidence, called for additional measures. Although it was necessary to shore up liquidity and hold interest rates as low as possible, the former would not guarantee an increased supply of credit and the latter would not ensure higher demand for goods. This made fiscal policy important as well. In the area of fiscal policy, measures to increase spending had greater potential than those based on reducing taxes. While tax cuts do increase the disposable income of the private sector, in a crisis a large proportion could go to savings. Conversely, spending measures directly increase demand. If higher spending takes the form of direct transfers, however, it will have the greatest impact when targeted on sectors more inclined to consume. Transfers of this type are harder to implement in the short run and more demanding institutionally than untargeted transfers, however. Programmes to boost infrastructure investment were also implemented, although not all such projects were equally effective in bolstering employment and demand for locally produced inputs. At the time the present edition of Social Panorama of Latin America went to press, information on 2009 public spending and social spending levels was available for seven 2006 4. Economic Commission for Latin America and the Caribbean (ECLAC) Panama Change in GDP Change in social spending Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. The most commonly used fiscal measures in the countries have included cutting taxes, increasing tax benefits and subsidies and raising or bringing forward expenditure. In the social and production sectors, considerable extra resources have been put into housing, water and sanitation, support for small and medium-sized enterprises and the agricultural sector (easier credit and repayment terms), enhanced employment policies (unemployment insurance, recruitment subsidies, job creation programmes) and social programmes, especially conditional cash transfer programmes. Social Panorama of Latin America • 2010 5. Conditional cash transfer programmes: protecting the poor throughout the life cycle Conditional cash transfer programmes (CCTPs) are now the leading mechanism for combating the intergenerational reproduction of poverty in the region’s countries. The beneficiary population for these programmes consists of poor and vulnerable families with children. These families receive monetary transfers on condition they meet certain requirements intended to develop skills and improve educational attainments (see chapter II for more information on CCTPs and education). These programmes provide protection in the early stages of the life cycle: transfers with health- and nutrition-related conditions attached are aimed at the neonatal stage and early childhood, while those with educational conditions target children and adolescents.1 However, some countries’ programmes also include transfers for older persons (Dominican Republic, Ecuador, Honduras, Jamaica, Mexico, Paraguay and Peru), persons with disabilities (Argentina, Ecuador, Jamaica and Paraguay) and poor working-age adults (Jamaica), usually without conditions (Cecchini and Madariaga, 2010). (a) The growth of CCTPs In the decade and a half that has passed since the first CCTPs were implemented in Brazil, with its Bolsa Escola, and Mexico, with its education, health and nutrition programme (PROGRESA), these social assistance programmes have grown at a steady pace in the Latin American and Caribbean countries in terms of both population coverage and spending. Around 2000, CCTPs or their direct precursors —major poverty reduction programmes based on direct income transfers such as Ecuador’s solidarity grant and the Family Allowance Programme (PRAF) in Honduras— were already operating in six countries, covering about 6% of the region’s population and spending the equivalent of 0.19% of GDP.2 These programmes expanded very rapidly in the following five years, so that by 2005 they had spread to 17 countries in the region and covered 14% of the region’s population, spending the equivalent of 0.24% of GDP. 1 2 139 In Latin America and the Caribbean, the maximum age for receiving transfers with educational conditions attached is generally about 18. The exceptions are the Programa Ciudadanía Porteña of the city of Buenos Aires and Avancemos in Costa Rica, which cover young people up to the age of 25 (Cecchini and Madariaga, 2010). Brazil, Costa Rica, Ecuador, Honduras, Mexico and Nicaragua. Spending on CCTPs increased to 0.34% of GDP in 2008 and 0.40% of GDP in 2009; this latter increase was due to the combined effects of rising budgets for these programmes and falling GDP as a result of the global economic crisis (see figure III.7). In 2010, six of the 10  countries for which information is available increased their CCTP budgets in nominal terms, while four cut them. Figure III.7 LATIN AMERICA AND THE CARIBBEAN (19 COUNTRIES): COVERAGE OF CONDITIONAL CASH TRANSFER PROGRAMMES AND PUBLIC EXPENDITURE ON THEM a A. Coverage, 2000-2010 (percentage of total population) 19.2 20 19.3 2009 2010 17.6 15 13.5 10 5.7 5 0 2000 2005 2008 B. Expenditure, 2000-2009 (percentage of GDP) 0.5 0.40 0.4 0.34 0.3 0.24 0.2 0.19 0.1 0 2000 2005 2008 2009 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official figures. a Weighted averages. Thanks to this expansion, as of 2010 one in five inhabitants of Latin America and the Caribbean (113 million people) are receiving State cash transfers through CCTPs. About 52 million of these are children aged 0 to 14. Figure III.8 LATIN AMERICA AND THE CARIBBEAN (19 COUNTRIES): COVERAGE OF CONDITIONAL CASH TRANSFER PROGRAMMES, AROUND 2000, 2005 AND 2010 (Percentages of total population) 44.3 45 40 35 3 Not considering programme inclusion and exclusion errors. 24.6 22.6 20 21.2 15 8.3 8.7 8.2 6.8 11.3 10.9 11.6 8.6 7.6 3.3 5 2.4 Peru Dominican Rep. Mexico 2005 Nicaragua Jamaica Honduras Guatemala Ecuador El Salvador Costa Rica Chile Colombia Brazil 2000 Panama 0 0 Paraguay 10 (b) Dissimilar experiences 2010 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official figures. Figure III.9 LATIN AMERICA AND THE CARIBBEAN (19 COUNTRIES): PUBLIC SPENDING ON CONDITIONAL CASH TRANSFER PROGRAMMES, AROUND 2005, 2008 AND 2009 (Percentages of GDP) 1.2 1.17 1 0.8 0.6 0.40 0.24 0.14 0.19 2008 Uruguay Peru Dominican Rep. Paraguay Panama Nicaragua Mexico Jamaica Honduras 0.00 ... Guatemala El Salvador Ecuador Costa Rica Colombia Chile 0.02 2005 0.45 0.36 0.32 0.11 Brazil 0 0.51 0.51 0.39 0.20 Argentina 0.2 0.39 0.33 Trinidad and Tobago 0.47 0.4 Bolivia (Plur. State of) Although rising spending and population coverage are common to the region’s CCTPs, the coverage levels actually achieved by each programme vary substantially. As of about 2010, Ecuador, with its Human Development Voucher, is the country where the largest percentage of the population (44%) is covered by a CCTP. The programmes with the largest number of beneficiaries in absolute terms are Bolsa Família family grants in Brazil (52 million people, or about half of all CCTP beneficiaries in the region), Oportunidades in Mexico (27 million) and Families in Action in Colombia (12 million) (see figure III.8 and table III.1). In six countries (Argentina, Brazil, Chile, Ecuador, Mexico and Uruguay), the number of beneficiaries is as great as or greater than the number of indigent people,3 although it could be argued that there is still scope to expand programmes of this type and cover a larger number of families that are unable to meet their basic needs, since in 2009 some 190 million people were living in poverty. Bolsa Família and Oportunidades are also the programmes with the largest budgets in the region (US$ 6.2 billion and US$ 3.5 billion, respectively), although as percentages of GDP (0.47% and 0.51%, respectively) they are surpassed by Ecuador’s Human Development Voucher (1.17%) (see figure III.9 and table III.1). 25.2 17.5 Uruguay 26.4 25 Trinidad and Tobago 30 Argentina Eighteen countries now have CCTPs, following the launch of the Conditional Cash Transfer Programme (CCTP) in Trinidad and Tobago in 2006 and Mi Familia Progresa in Guatemala in 2008, and the halting of such programmes by Nicaragua in 2006. In addition, new programmes have been launched or existing ones modified in recent years. In 2009, Argentina launched its Universal Child Allowance for Social Protection, which took over the beneficiaries of the Families for Social Inclusion programme, and the Plurinational State of Bolivia created the Juana Azurduy de Padilla mother-and-child voucher. In 2010, Honduras added a transfer of 10,000 lempiras a year to the benefits of the Family Allowance Programme (the Bono 10000, worth about US$ 500) with a view to improving education, health and nutrition in indigent households with children and adolescents (see table III.1). Economic Commission for Latin America and the Caribbean (ECLAC) Bolivia (Plur. State of) 140 2009 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official figures. Social Panorama of Latin America • 2010 141 Table III.1 LATIN AMERICA (18 COUNTRIES): INDICATORS OF COVERAGE AND PUBLIC SPENDING ON CONDITIONAL CASH TRANSFER PROGRAMMES (CCTPs), 2007-2010 CCTP coverage (percentage of total (thousands of (thousands households) of people) population) Coverage Country   Programme Argentina Universal Social Protection Benefit for Each Child Bolivia (Plurinational State of) Juancito Pinto Grant Brazil Bolsa Família 756 d (2010) … 8.3 Costa Rica 46.4 > 100.0 0.20 Government of Argentina 17.5 3 400 1 729 32.4 50.7 0.33 26.4 84.6  > 100.0  0.47 e Government of the Plurinational State of Bolivia, World Bank Government of Brazil, World Bank 6.8 51.7 > 100.0 0.11 Government of Chile 25.2 56.5 > 100.0 0.39 e Government of Colombia, IDB, World Bank 3.3 17.4 52.2 0.39 Government of Costa Rica, World Bank 21.2 46.3 89.0 0.51 e Government of the Dominican Republic 44.3 > 100.0  > 100.0  1.17 Government of Ecuador, IDB, World Bank (2009) Chile Solidario 12 583 51 590 d (2010) 333 f (2008) Colombia CCTP CCTP spending, coverage a 2009 b c (percentage Financing sources of indigent (percentage of population) GDP) (2010) (2010) Chile CCTP coverage a (percentage of poor population) Families in Action Avancemos 2 589 g (2010) … 1 147 f (2008) 11 651 d g (2010) 151 (2009) Dominican Republic Solidaridad Ecuador Human Development Voucher El Salvador Solidarity in Rural Communities Guatemala Mi Familia Progresa 758 2 098 (2010) (2010) 1 179 h 6 100 d h (2010) (2010) 106 (2009) 508 d (2009) 8.2 17.1 38.7 0.02 World Bank, IDB, other bilateral and multilateral sources 3 254 d 22.6 39.7 70.5 0.32 Government of Guatemala Government of Honduras, IDB, other bilateral and multilateral sources Government of Jamaica, World Bank 592 (2010) Honduras Family Allowance Programme (PRAF) Jamaica Programme of Advancement Through Health and Education (PATH) Oportunidades (2010) 132 i (2010) 661 d i (2010) 8.7 12.3 17.2 0.24 j 307 11.3 > 100.0 k >100.0 k 0.40 … (2009) Panama l Paraguay Red de Oportunidades Tekoporã 5 561 27 247 d 24.6 62.8 > 100.0 (2010) 77 (2010) 377 d i 10.9 39.5 81.0 0.22 em World Bank, IDB (2009) Mexico (2009) 8.6 13.9 25.2 0.36 n IDB 7.6 21.2 60.6 0.14 Government of Peru 2.4 14.6 >100.0 k 0.19 Government of Trinidad and Tobago 11.6 84.6 >100.0 0.45 Government of Uruguay 19.3 p 47.5 q > 100.0 q 99 n (2010) Peru Juntos 410 554 n Government of Mexico, IDB, World Bank (2010) 2 253 d (2009) (2009) 33 Trinidad and Tobago Targeted Conditional Cash Transfer Programme (TCCTP) … Uruguay Family Allowances 91 d k (2009) 390 (2009) Latin America and the Caribbean 0.51 (2009) 25 263 o 113 449 o 0.40 p Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official figures; and ECLAC, Economic Survey of Latin America and the Caribbean, 2008-2009 (LC/G.2410-P), Santiago, Chile, 2009. United Nations publication, Sales No. E.09.II.62. a Programme inclusion and exclusion errors are not taken into account. b Unless otherwise indicated, data correspond to the budget for each programme. c GDP figures are projections. d Coverage estimated on the basis of the number of beneficiary families and average size of urban households in the poorest Quintilee in the most recent year for which information is available from the CEPALSTAT social indicators and statistics database (BADEINSO) of ECLAC. e Budget as executed. f Puente programme beneficiaries. g Includes indigenous and displaced beneficiary families. h Includes beneficiaries who are older persons or persons with disabilities. i Planned coverage. j Includes Family Allowance Programme (PRAF)/IDB phase III pilot stage. k Figure calculated on the basis of national poverty estimates which are incompatible with ECLAC estimates on the countries of Latin America. l Includes Family Vouchers for Food Purchases programme. m 2008 data. n Includes Ñopytyvo and ProCountry II programmes. o Total relates to all countries for which information is available. p Weighted average. q Simple average. 142 Economic Commission for Latin America and the Caribbean (ECLAC) C. Social investment at early ages: spending per student The social sectors which saw the greatest increases in public-sector resources were social security and assistance, followed by education. Some social assistance spending goes into the effort to combat the intergenerational reproduction of poverty, and to that extent is directed at the new generations. Undoubtedly, however, it is education spending that is chiefly directed at children and the young, and copious resources are dedicated to this. Spending per student has increased significantly, although this is largely due to the substantial economic growth of the past two decades. The States have also made a significant effort to increase the weight of this spending within their budgets. But population ageing and the decline in the school-age population ratio can be a factor in lowering per-student spending, and the expansion of education coverage itself has constrained further increases in this area. Still, this expansion has also helped to make education spending more progressive, since more of it goes to lower-income students, at least at the preschool, primary and lower secondary levels. Much of the social spending growth discussed earlier herein has been maintained at times of economic upheaval precisely because spending items associated with social protection have been increased, especially social security and assistance. The strengthening of social protection systems, combining contributory and non-contributory mechanisms, has unquestionably been a major advance for social policy and its impact on the well-being of the poorest. A great deal certainly remains to be done both in expanding coverage and in improving benefits. Conditional cash transfer programmes enshrine a determination to combat the intergenerational reproduction of poverty (see chapter II); most of these programmes take a life cycle approach in which income transfers to cover basic needs in the poorest families are combined with investment in developing the skills of the new generations in these families so that they have greater opportunities in their adult lives. It is important to highlight these in the present edition of Social Panorama, whose focus is precisely on the life cycle and the reproduction (or reversal) of intergenerational inequalities. These programmes, and the solidarity components of social security and health systems, complement broad social policy goals and are thus but a part of overall public spending in this area. By way of example, while public social spending in the region is around 18% of GDP, spending on anti-poverty programmes is only 0.4% of GDP. The very design of social protection systems in the region, specifically the weight of their contributory component and thus their dependence on the operation of labour markets, means that the future role of the younger generations in funding and sustaining these systems in the long run is critical. As ECLAC has stressed on numerous occasions, the region currently has the potential to benefit from a demographic dividend (a growing ratio of working-age people to dependents), but this is clearly time-limited and the opportunity needs to be seized now (ECLAC/OIJ, 2008; ECLAC, 2009). Taking advantage of this demographic dividend means first and foremost investing in the new generations. Their lesser relative weight in the total population has opened a window of opportunity, but these new generations will have to be highly productive in their adult lives, when society will have to sustain a larger demographic burden as the elderly population swells. Investing in skills development for the young thus becomes doubly important —to keep pace with the demographic transition and to halt the intergenerational reproduction of poverty, inequality and low productivity. It is also important to have a more productive economically Social Panorama of Latin America • 2010 143 active population as a driver of economic growth bringing knowledge and innovation into the productive system. Combined with policies fostering social and labour rights, this will also boost social protection systems. The prime areas for investment in the new generations are health (especially mother and child health) and education. Budgets for both sectors have increased substantially over the past two decades, although they have been very much subject to economic fluctuations. It is public spending in these areas that has suffered most from the economic instability (whether internally or externally generated) of many of the region’s countries. There can be no doubt, in any case, that the countries have made enormous efforts to increase their social 1. Public-sector education spending Education spending is highly procyclical, growing strongly in periods of vigorous economic growth but also contracting sharply during economic slowdowns or downturns, sometimes by even more than would be expected on the basis of GDP performance (see figure III.10). Figure III.10 LATIN AMERICA (19 COUNTRIES): RATES OF ANNUAL VARIATION IN GROSS DOMESTIC PRODUCT AND PUBLIC-SECTOR EDUCATION SPENDING, 1991-2009 a (Percentages) 30 25 20 15 10 5 0 2009 2007 2008 2005 2006 2003 2004 2001 2002 1999 Gross domestic product 2000 1997 1998 1995 1996 1993 1994 1991 1992 -5 -10 investment in education and health, partly with the support of international initiatives and commitments, particularly where education is concerned (see the first section of chapter II). Not enough information is available to conduct a specific region-wide analysis of health spending on infants, children and adolescents, so the following pages will examine trends in public-sector education spending (particularly at the primary and secondary levels) and the factors that have most influenced the growth of this spending. They will also review the distributive impact of public education spending at the preschool, primary, secondary and tertiary levels and assess how progressive this is, especially in the case of educational levels where universal access has been achieved. Public education spending Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official figures and information from the Commission’s social expenditure database. a The 2009 education spending figures are estimates based on official information for six countries. Despite this procyclicality, the countries’ efforts have resulted in their education budgets increasing relative to GDP. To a large degree, economic growth has facilitated the extension of education services in this decade. Thus, education spending in the countries for which adequate information is available increased on average from 3.1% of GDP in 1990 to 3.6% in 2000 and 4.2% in 2008.4 The region’s GDP almost doubled between 1990 and 2008 (growing by 3.4% a year and 84% over the whole period), and public-sector education spending in the region expanded 5% a year in absolute terms, or 140% over the whole period. In per capita terms, the average increase was from US$ 86 per person in 1990 to US$ 119 in 2000 and US$ 171 in 2008. The above figures mask vastly dissimilar levels of per capita spending and rates of increase. Countries such as the Dominican Republic, Ecuador, El Salvador, Guatemala, Nicaragua, Paraguay, Peru and the Plurinational State of Bolivia spent less than US$ 100 per inhabitant on education in 2008, while Argentina, Costa Rica, Mexico and Uruguay spent over US$ 250. Ecuador, Nicaragua and Panama are the countries that increased their per capita spending by the least (in Ecuador it actually fell slightly), while Guatemala, Paraguay, Peru and the Plurinational State of Bolivia at least trebled it (see table III.2). 4 These figures might not match those presented in the first section of the chapter because the information used in the present section comes from the administrative classification of spending (by origin) rather than the functional classification (by destination). 144 Economic Commission for Latin America and the Caribbean (ECLAC) Table III.2 LATIN AMERICA (18 COUNTRIES): INDICATORS OF PUBLIC-SECTOR EDUCATION SPENDING, 1990 AND 2008 a (Percentages and dollars) Education spending as percentage of GDP Education spending per inhabitant Primary or secondary school-age population Spending on primary and secondary schooling per school-age person b 1990 2008 1990 2008 1990 2008 1990 Argentina 3.4 4.9 190 489 23.7 20.6 616 1 773 2008 Bolivia (Plurinational State of) 2.7 6.7 23 76 29.2 27.8 70 166 Brazil 4.6 5.3 154 232 24.6 19.3 349 911 Chile 2.7 3.6 83 224 22.3 19.8 258 837 Colombia 2.8 5.1 59 147 25.3 21.4 139 531 Costa Rica 4.5 5.2 140 268 23.8 20.2 331 974 Dominican Republic 2.0 2.5 37 91 28.7 25.1 80 279 Ecuador 2.6 2.1 34 36 c 29.3 24.7 72 120 El Salvador 2.0 3.6 33 82 31.4 25.2 70 196 Guatemala 1.4 3.2 20 61 28.8 27.8 43 160 101 c 30.7 29.0 84 288 378 27.8 21.6 398 1185 Honduras 3.7 7.0 39 Mexico 4.0 5.8 197 Nicaragua 4.4 3.2 30 30.8 26.3 37 49 Panama 5.4 4.1 159 229 26.9 22.8 356 463 Paraguay 1.1 4.1 15 62 29.0 26.8 35 173 Peru 1.5 2.7 25 81 26.5 22.2 48 269 Uruguay 3.1 3.1 169 272 c 20.8 18.9 551 998 Venezuela (Bolivarian Republic of) 3.1 3.8 150 227 25.7 21.7 144 515 Simple average 3.1 4.2 86.5 171.4 27.0 23.4 205 549 29 c Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Project documents, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/xml/0/40520/metas-educativas-2021.pdf, 2010. a The figures follow the administrative classification of public spending and might not match those based on the functional classification. b Primary and secondary school-age population as per the 1997 International Standard Classification of Education (ISCED). c Estimates based on data from the UNESCO Institute of Statistics (UIS). Despite the efforts made in the region, public-sector resources remain inadequate. Although the average commitment of public resources by the developed countries has been taken as the benchmark and it has been suggested that the region’s countries need to set out to achieve the same percentage expenditure (public education spending in 27 countries of the European Union averaged 5.04% of GDP in 2006),5 a number of countries in Latin America and the 5 See [online] http://epp.eurostat.ec.europa.eu/tgm/table.do?tab=ta ble&init=1&language=en&pcode=tsdsc510&plugin=1. Caribbean actually spend a higher proportion, as figure III.11 shows, but the absolute amounts still fall short of needs. Notwithstanding the above, many countries still have some room to expand public-sector education spending. In a context of relatively sustained future growth, this could involve substantial resources that could be used to achieve universal primary and secondary education and to enhance other areas such as school retention and learning quality. Social Panorama of Latin America • 2010 145 Figure III.11 LATIN AMERICA AND THE CARIBBEAN (36 COUNTRIES): PUBLIC-SECTOR EDUCATION SPENDING, 2006-2008 a (Percentages of GDP) 14 13.8 12 10 8 6 4 9.9 7 7 6.7 6.7 6.3 6.1 European Union (27 countries) 5.04% 5.8 5.5 5.3 5.2 5.2 5.1 5.1 4.8 4.8 4.94.2 4.1 4.1 4 3.9 3.8 3.6 3.6 3.6 3.3 3.2 3.2 3.1 3.1 2.7 2.6 2 2.5 2.1 Guatemala British Virgin Islands Uruguay Peru Cayman Islands Dominican Rep. Ecuador Cuba Saint Kitts and Nevis Honduras Saint Vincent and the Grenadines Barbados Bolivia (Plur. State of) Saint Lucia Guyana Mexico Jamaica Brazil Grenada Costa Rica Belize Colombia Aruba Dominica Argentina Trinidad and Tobago Paraguay Panama Anguila Antigua and Barbuda Venezuela (Bol. Rep. of) El Salvador Bahamas Chile Montserrat Nicaragua 0 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Documentos de proyecto, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/xml/0/40520/metas-educativas-2021.pdf, 2010. a The figures follow the administrative classification of public spending and might not match those based on the functional classification. Primary and secondary education spending 6 The full secondary cycle is not compulsory in all the region’s countries; the basic education cycle, encompassing primary school and the lower cycle of secondary school, is compulsory, however, and typically represents nine years of schooling (see table III.3). Figure III.12 LATIN AMERICA: POPULATION BY MAJOR AGE GROUP, 1950-2050 (Percentages) 100 90 80 70 60 50 40 37.1 34.1 34.1 27.8 30 17.6 21.1 20 Population aged 5 to 19 2050 2045 2040 2035 2030 2025 2020 2015 2010 2005 2000 1995 1990 1985 1980 1975 1970 1965 0 1960 10 1955 A better way of analysing the evolution of spending is to focus on the target population. Education is a lifelong process; the public resources used to provide it should therefore benefit all members of society to a greater or lesser degree. However, the formal education system (preschool, primary, secondary and tertiary) is generally aimed at more specific populations: children and young people. Neither preschool nor tertiary education is compulsory in most of the countries, and there are no age limits for tertiary education, so our focus at this stage is on spending on primary and secondary education.6 The effect of population ageing is germane to any analysis of education spending on the target population of young people that is the focus of this edition of Social Panorama. In Latin America, this effect is mainly in the form of the demographic dividend. As can be seen in figure III.12, the decline between 1990 and 2010 in the demographic weight of the age groups typically in school (5 to 19), combined with a steady increase in the working-age group, has been an important development. The growth of the older adult population is a trend that will accelerate in the coming years. 1950 2. Population aged 15 to 59 Population aged 60 and over Source: Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC, population estimates and projections. Table III.3 provides a more precise account of the primary and secondary school age population, following the educational cycle duration criteria of the United Nations Educational, Scientific and Cultural Organization (UNESCO) 1997 International Standard Classification 146 Economic Commission for Latin America and the Caribbean (ECLAC) of Education (ISCED).7 On average, this population declined from 27% of the total in 1990 to 23.4% in 2008. The countries are naturally at different stages of the demographic transition, and this affects the rate of decrease. In Brazil, Ecuador, El Salvador, Mexico and Nicaragua the decline in the primary and secondary school-age population ratio has been in excess of 4.5 percentage points (which does not mean an absolute decline in the number of people). In Guatemala, Honduras, the Plurinational State of Bolivia and Uruguay the relative decline has been very small. While the first three of these countries are at a moderate stage of the demographic transition, the last is at the very advanced stage (Chackiel, 2004). Because the school-age population represents only about a quarter of the total and has been declining, average public spending on primary and secondary education has increased significantly in relation to the potential target population, from US$ 215 per school-age person in 1990 to US$ 352 in 2000 and US$ 549 in 2008. Thus, the demographic transition has helped boost education spending, since for every US$ 1 per potential student budgeted in 1990, US$ 2.7 were budgeted in 2008. These demographic conditions have enabled the region to accelerate the skills development in the younger generations. However, to determine effective spending per student (i.e., in relation to the proportion of the primary or secondary school age population benefiting from public investment in these levels of education), two other key factors must come into the picture: the actual percentage of students enrolled and the percentage attending publicly-funded establishments. Regarding the percentage of students enrolled, much of the progress with education in the region has consisted precisely in increasing the coverage of and access to education systems. On average, the level of access among the region’s primary and secondary school-age population is almost 90%, with substantial growth seen mainly between 1990 and 2000 (from 71% to 85%). Much educational investment has been designed to increase educational coverage at the secondary level (primary education was already virtually universal by the beginning of the 1990s). Spending growth has made it possible to integrate a larger proportion of children and young people, particularly those from low-income families. In half the 18 countries analysed, over 90% of children and young people of compulsory school attendance age actually do attend. Only in the Dominican Republic, Guatemala, Honduras, Nicaragua and Paraguay are actual access levels below 85%. In 1990, access levels were below this in virtually all the countries, while in 13 countries over 20% of the school-age population was outside the education system (see table III.4). Nonetheless, this very increase in coverage also kept spending per student from rising more. Regarding the percentage of students attending publiclyfunded establishments, some of the large expansion of education system access is due in part to gradually increasing private investment in education services, including services provided through church- and community-associated foundations and organizations. This has shifted a large proportion of students to privately-funded establishments, freeing up capacity in the public sector (and helping to raise public spending per student), but it also set into motion the processes of school segregation and gradual differentiation in the quality of education services. Almost 84% of students were attending publicly financed institutions in 1990, a percentage that had dropped to just under 81% by 2008. Although this is a fairly widespread trend in the region’s countries, there are large differences in the extent to which education services have been privatized. In Brazil, Colombia, El Salvador, the Plurinational State of Bolivia and Uruguay, the percentage of students in public education systems increased, although the number of students attending private institutions (either for-profit or non-profit) also rose in all but Uruguay, by 2.5 million. In Chile, Ecuador, Honduras and Peru, meanwhile, the percentage of private students rose substantially (by seven percentage points or more), although the absolute number of public-sector students did not fall in any of these countries. Only in Chile do more than 50% of students attend private-sector educational establishments (including publicly-subsidized private establishments); the percentage in the other countries is 30% or less. The number of primary and secondary school students attending public establishments in the region increased by almost 29 million between 1990 and 2008 to a total of 91.2 million (with 18.5 million attending private schools).8 7 8 Children and young people aged approximately 6 to 17. This varies from country to country according to the official starting age of the primary cycle and the duration of this and the secondary level. The students analysed here are those of primary or secondary education age who are actually in those levels of education. The figures do not include secondary school students who are behind their year (generally aged 18 or over). Social Panorama of Latin America • 2010 147 Table III.3 Latin America and the Caribbean (41 countries AND TERRITORIES): COMPULSORY EDUCATION AND OFFICIAL DURATION OF THE PRIMARY AND SECONDARY CYCLES, 2007-2008 a (By age groups and number of years) Compulsory education Country or territory Age group b Duration in years Total Excluding preschool Primary education Official age group Duration in years Secondary education Official age group Duration in years Compulsory years and total duration of primary and secondary education Anguila 5-17 13 13 5-11 7 12-16 5 12/12 Antigua and Barbuda 5-16 12 12 5-11 7 12-16 5 12/12 Netherlands Antilles 6-15 10 10 6-11 6 12-17 6 10/12 Argentina 5-15 11 10 6-11 6 12-17 6 10/12 Aruba 6-16 11 11 6-11 6 12-16 5 11/11 Bahamas 5-16 12 12 5-10 6 11-16 6 12/12 Barbados 5-16 12 12 5-10 6 11-15 5 11/11 Belize 5-14 10 10 5-10 6 11-16 6 10/12 12/13 Bermuda 5-16 12 12 5-10 6 11-17 7 Bolivia (Plurinational State of) 6-13 8 8 6-11 6 12-17 6 8/12 Brazil 7-14 8 8 7-10 4 11-17 7 8/11 Chile 6-17 12 12 6-11 6 12-17 6 12/12 Colombia 5-15 11 10 6-10 5 11-16 6 10/11 Costa Rica 6-15 10 10 6-11 6 12-16 5 10/11 Cuba 6-14 9 9 6-11 6 12-17 6 9/12 Dominica 5-16 12 12 5-11 7 12-16 5 12/12 Dominican Republic 5-14 10 9 6-11 6 12-17 6 9/12 Ecuador 5-14 10 9 6-11 6 12-17 6 9/12 El Salvador 7-15 9 9 7-12 6 13-18 6 9/12 Grenada 5-16 12 12 5-11 7 12-16 5 12/12 Guatemala 6-15 10 9 7-12 6 13-17 5 9/11 Guyana 6-15 10 10 6-11 6 12-16 5 10/11 Haiti 6-11 6 6 6-11 6 12-18 7 6/13 Honduras 6-13 8 8 6-11 6 12-16 5 8/11 Cayman Islands 5-16 12 12 5-10 6 11-16 6 12/12 Turks and Caicos Islands 4-16 13 11 6-11 6 12-16 5 11/11 12/12 British Virgin Islands 5-16 12 12 5-11 7 12-16 5 Jamaica 6-12 7 7 6-11 6 12-16 5 7/11 Mexico 6-15 10 10 6-11 6 12-17 6 10/12 12/12 Montserrat 5-16 12 12 5-11 7 12-16 5 Nicaragua 6-11 6 6 6-11 6 12-16 5 6/11 Panama 6-14 9 9 6-11 6 12-17 6 9/12 Paraguay 6-14 9 9 6-11 6 12-17 6 9/12 Peru 6-18 13 13 6-11 6 12-16 5 11/11 Saint Kitts and Nevis 5-16 12 12 5-11 7 12-16 5 12/12 Saint Vincent and the Grenadines 5-15 11 11 5-11 7 12-16 5 11/12 Saint Lucia 5-15 11 11 5-11 7 12-16 5 11/12 Suriname 7-12 6 7 6-11 6 12-18 7 7/13 Trinidad and Tobago 6-12 7 8 5-11 7 12-16 5 8/12 Uruguay 6-15 10 10 6-11 6 12-17 6 10/12 Venezuela (Bolivarian Republic of) 5-14 10 9 6-11 6 12-16 5 9/11 Source: United Nations Educational, Scientific and Cultural Organization (UNESCO), Education for All Global Monitoring Report 2010: Reaching the Marginalized, Paris, 2010. a Cycle durations as per the 1997 International Standard Classification of Education (ISCED). b Ages at which school attendance or the right to an education can be enforced until completion of the educational cycle. The last column shows how many grades of the primary and secondary education cycles are compulsory within the age range shown in the first column. 148 Economic Commission for Latin America and the Caribbean (ECLAC) Table III.4 LATIN AMERICA (18 COUNTRIES): INDICATORS OF EDUCATION COVERAGE AND PUBLIC EDUCATION SPENDING, 1990 AND 2008 (Percentages and dollars at constant 2000 prices) Total percentage studying 1990 2008 Public-sector students as percentage of school-age population Percentage in public-sector establishments 1990 2008 1990 Public spending per student (primary and secondary) a 2008 1990 2008 Argentina 84.6 b 97.2 78.9 b 74.9 66.7 b 72.8 893 2 348 Bolivia (Plurinational State of) 64.1 89.9 89.1 b 89.9 57.1 b 80.8 119 193 Brazil 50.7 98.7 85.1 b 87.6 43.1 b 86.5 750 937 Chile 78.1 94.9 60.0 45.3 46.9 43.0 517 1890 Colombia 76.4 93.3 78.0 78.4 59.6 73.1 196 645 Costa Rica 74.0 94.2 b 94.0 91.2 69.6 85.9 450 1 072 Dominican Republic 61.8 81.9 78.8 b 78.8 48.7 b 64.5 151 409 Ecuador 82.7 b 90.5 85.6 b 70.5 70.8 b 63.8 92 171 El Salvador 48.9 86.1 78.3 87.1 38.3 75.0 176 249 Guatemala 53.3 b 82.6 77.0 b 75.9 41.0 b 62.7 99 241 Honduras 69.1 79.8 b 93.6 86.6 64.7 69.1 117 345 1 275 Mexico 83.0 95.3 92.5 89.3 76.8 85.1 478 Nicaragua 70.0 b 84.2 86.1 82.7 60.3 69.6 58 62 Panama 79.0 89.1 90.4 87.5 71.4 78.0 462 573 Paraguay 69.9 82.4 83.8 81.5 58.6 67.2 57 244 Peru 86.5 93.5 86.5 78.9 74.8 73.8 57 339 1 099 Uruguay 81.2 b 90.7 83.7 86.4 68.0 78.4 695 Venezuela (Bolivarian Republic of) 63.4 88.0 84.1 80.0 53.3 70.4 247 694 Simple average 70.9 89.6 83.6 80.7 59.4 72.2 311.9 710.3 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Project documents, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/xml/0/40520/metas-educativas-2021.pdf, 2010. a In 2000 dollars. b Estimates based on data from the United Nations Educational, Scientific and Cultural Organization (UNESCO) Institute of Statistics (UIS). 3. The rise in per-student spending and associated factors The factors noted above (economic growth, fiscal measures, population growth and ageing and the rise in education coverage, among others) caused public spending per primary and secondary school student to rise unevenly. On the one hand, Argentina, Chile, Costa Rica and Mexico increased their public spending per student by US$ 600 or more over the whole period, and all the countries of Latin America, including Uruguay, topped US$  1,000 per student. In Ecuador, El Salvador, Guatemala, Panama and the Plurinational State of Bolivia, on the other hand, the increase over practically two decades was less than US$  150 per student. According to the information available, Nicaragua saw no significant increase in spending per student between 1990 and 2008. Within the group of countries where there has been little increase in funding, Panama spends over US$ 500 per student and El Salvador and Guatemala about US$ 250 (see figure III.13). On average, spending on students attending public establishments more than doubled in the region, rising by 4.7% a year. Figure III.13 LATIN AMERICA (18 COUNTRIES): PUBLIC SPENDING PER PRIMARY AND SECONDARY SCHOOL STUDENT, 1990 AND 2008 a (Dollars at constant 2000 prices) Simple average 710 Argentina Chile Mexico Uruguay Costa Rica Brazil Venezuela (Bol. Rep. of) Colombia Panama Dominican Rep. Honduras Peru El Salvador Paraguay Guatemala Bolivia (Plur. State of) Ecuador Nicaragua 2 348 1 890 1 275 1 099 1 072 937 694 645 573 409 345 339 249 244 241 193 171 62 0 500 1 000 1990 1 500 2 000 2 500 2008 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/ Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Project documents, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/ xml/0/40520/metas-educativas-2021.pdf, 2010. a Ranked in order of spending per student in 2008. Social Panorama of Latin America • 2010 149 An examination of the timing of the rise in public spending per student (1990-2000 and 2000-2008) shows that the majority of the countries increased their spending the most between 2000 and 2008, even though this was the shorter time period. The exceptions are Chile, Mexico, Panama and Paraguay, which recorded greater progress in the 1990s (see figure III.14). This is mainly because most of the countries increased coverage more in the earlier period. On average, coverage increased by about 14 percentage points between 1990 and 2000, compared with a further 5 percentage points between 2000 and 2008 (see table III.4). This meant that much of the extra public education spending went to incorporating new students, which limited the growth of average spending per student. Since the progress of the 1990s (and earlier decades), extra spending has largely gone into improving the conditions that directly or indirectly affect the education process: better infrastructure, equipment, teaching material and teacher pay, among other things. Figure III.14 LATIN AMERICA (18 COUNTRIES): TIMING OF THE RISE IN PUBLIC SPENDING PER STUDENT, 1990-2000 AND 2000-2008 a (Dollars at constant 2000 prices) 1 600 number of students (additional expenditure of public resources because of school repetition).9 • Demographic and educational factors: population growth, population ageing (school-age population ratio), greater access to education and the extent to which education services have been privatized. • The interaction between the two groups of factors. In the first place, while economic growth and budgets have been the main drivers of the rise in public spending per student, demographic factors and the expansion of public education systems have tended to restrain this spending, as noted earlier, largely because increasing numbers of people have gained access to education services. Thus, the average increase in the region has been the result of an absolute expansion of public education spending (largely thanks to economic growth, as will be seen later) that would have taken the level up to just under US$ 850 per student (compared with the actual level of US$ 710 at present) and a population and public education coverage effect that has reduced spending per student by just under US$ 170. Nonetheless, the greater weight of economic and budgetary factors, and the favourable interaction between the two groups of factors, allowed spending to increase by some US$ 400 per student between 1990 and 2008 (see figure III.15). 1 400 1 200 Figure III.15 LATIN AMERICA (18 COUNTRIES): GROUPS OF FACTORS ASSOCIATED WITH CHANGES IN PUBLIC SPENDING PER STUDENT (Dollars at constant 2000 prices) 1 000 800 600 400 200 Simple Average Nicaragua El Salvador Bolivia (Plur. State of) Panama Dominican Rep. Guatemala Brazil Paraguay Honduras Peru 2000-2008 Ecuador Colombia Venezuela (Bol. Rep. of) Uruguay Costa Rica Chile Mexico Argentina -400 -600 169 Simple average 0 -200 1990-2000 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/ Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Project documents, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/ xml/0/40520/metas-educativas-2021.pdf, 2010. a Ranked by total change between 1990 and 2008. The rise in public education spending per student can also be examined in terms of the positive or negative impact of different factors. The factors considered in the present analysis are: • Economic and budgetary factors: economic growth, the macroeconomic priority given to public spending, the fiscal priority given to public spending on primary and secondary education, and the ratio between daily spending per student and the total Argentina Chile Mexico Costa Rica Colombia Venezuela (Bol. Rep. of) Uruguay Peru Dominican Rep. Honduras Brazil Paraguay Guatemala Panama Ecuador Bolivia (Plur. State of) El Salvador Nicaragua -1 000 -500 35 0 533 500 1 000 1 500 2 000 Economic and budgetary factors Interaction of factors Demographic and educational factors Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/ Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Project documents, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/ xml/0/40520/metas-educativas-2021.pdf, 2010. 9 The differences in these spending levels only relate to secondary school students who are not in the age group that is supposed to be attending that level. This effect was recorded only for spending differences and not for the number of people covered, to avoid double counting of the effect produced by repeaters. for them to keep up, this tends to push per-student spending up at the expense of expansion in countries that have made greater efforts with education. Between 1990 and 2008 some countries succeeded in reducing the proportion of students lagging behind, even in a context of expanding education coverage. This led to an average increase of about US$ 11 a year per student. Argentina, Brazil, El Salvador, Honduras, Mexico, Nicaragua and the Plurinational State of Bolivia increased the proportion of additional spending for over-age students at the secondary level, the result being a loss of about US$ 10 per student. Brazil is the country where the rise in the number of secondary school students who lag behind their age group has had the greatest impact, entailing additional spending of some US$ 1 billion a year. Figure III.16 LATIN AMERICA (18 COUNTRIES): ECONOMIC AND BUDGETARY FACTORS ASSOCIATED WITH CHANGES IN SPENDING PER STUDENT a (Dollars at constant 2000 prices) 1 400 1 200 1 000 800 600 400 200 0 -200 Economic growth Fiscal priority of education spending a Latin America Paraguay Nicaragua Bolivia (Plur. State of) Ecuador Peru Guatemala Honduras El Salvador Dominica Venezuela (Bol. Rep. of) Colombia Brazil Mexico Panama Uruguay Chile -400 -600 Costa Rica In all the countries analysed, economic and budgetary factors made the greatest contribution to the change in spending per student. This is particularly striking in Argentina, Chile, Mexico and, to a lesser extent, Costa Rica, Paraguay and Uruguay. In Brazil, El Salvador, Guatemala, Nicaragua, Panama and the Plurinational State of Bolivia, these factors barely sufficed to counteract the negative contribution of population and coverage factors. With the exception of Nicaragua, where progress was slightly less, all countries increased educational coverage by 20 percentage points or more (see table III.4). Again, it is interesting to note that Chile, Ecuador and Peru were the countries where the number of public-sector students increased the least (by 3.6%, 2.1% and 7.1%, respectively). All three made great progress with educational coverage, but this went with a large expansion of the private-sector presence in the education sector. This was largely responsible for the limited effect of demographic factors on the increase in spending per student in these countries. There can be no doubt that budget-related economic factors did the most to drive up spending per student and that the demographic dynamic and the rise in education coverage in general constrained this expansion. Economic growth has been one of the economic and budgetary factors contributing most to the rise in spending per student. This has been particularly true of Argentina, Chile, Costa Rica, the Dominican Republic, Honduras, Panama, Peru, the Plurinational State of Bolivia and Uruguay, as figure III.16 shows. In some countries, much of the increase in spending per student has been due to rising public budgets, bringing an inertial increase in education budgets (Argentina, Ecuador, El Salvador, Guatemala, Panama, Paraguay, the Plurinational State of Bolivia and Uruguay). But in others the specific effort made to increase education budgets was also important (the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Honduras, Mexico, Paraguay and Peru). Broadly speaking, the second most important factor (after economic growth) in the rise in spending per student was the greater fiscal priority given to education spending. Lastly, a relatively small proportion of resources need to be spent on retaining secondary school students and helping those who fall behind to complete the cycle, whether by repeating grades or by leaving the system and returning to it later. In general, increasing educational coverage incorporates students from lower-income groups. Because it is harder Economic Commission for Latin America and the Caribbean (ECLAC) Argentina 150 Additional spending on repeaters Macroeconomic priority of public spending Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/ Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Project documents, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/ xml/0/40520/metas-educativas-2021.pdf, 2010. a Ranked by the contribution of economic growth to the rise in spending per student. Taken together, demographic factors affecting education coverage and the roles of public and private agents in providing education have restrained the rise in spending per student, even though not all the factors considered have pushed in the same direction or had the same weight. First, natural population growth, which is still strong in most of the region’s countries, has played Social Panorama of Latin America • 2010 151 Figure III.17 LATIN AMERICA (18 COUNTRIES): INCREASE IN SPENDING PER STUDENT AS DETERMINED BY DEMOGRAPHIC AND EDUCATIONAL FACTORS a (Dollars at constant 2000 prices) the largest part in limiting the increase in resources per student. To put it another way, the considerable rise in education spending over the past two decades has been mainly extensive in character (rise in the number of students) and has been a major complicating factor for public investment in education (increased resources per student). This is also reflected in the negative impact of rising public education coverage, as can be seen in figure III.17. Population growth has been the most important factor in all the countries except the Bolivarian Republic of Venezuela, Brazil, the Dominican Republic, El Salvador, Guatemala, the Plurinational State of Bolivia and Uruguay. In Brazil, El Salvador and Uruguay, the rise in public education coverage has been the most important factor. Lastly, two factors that have operated in favour of higher spending per student are population ageing (which has caused the school-age proportion of the population to shrink, particularly in Argentina, Brazil, Chile and Mexico) and the rise of private-sector involvement in the provision of education services (especially in Argentina and Chile). Table III.5 provides an overview of the different weight of all these factors. 400 200 0 -200 -400 Population growth Population ageing Latin America Nicaragua Peru Ecuador Uruguay Paraguay El Salvador Bolivia (Plur. State of) Dominica Guatemala Colombia Honduras Brazil Panama Venezuela (Bol. Rep. of) Chile Mexico Argentina -800 Costa Rica -600 Educational coverage Privatization of education services Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/ Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Project documents, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/ xml/0/40520/metas-educativas-2021.pdf, 2010. a Ranked by the contribution of population growth in holding down spending per student. Table III.5 LATIN AMERICA (18 COUNTRIES): CONTRIBUTION OF ECONOMIC AND DEMOGRAPHIC FACTORS TO THE RISE IN SPENDING PER STUDENT, 1990-2008 (Dollars at constant 2000 prices) Contribution of demographic and educational coverage factors Contribution of economic and budgetary factors Economic growth Argentina Macroeconomic priority of public spending Fiscal priority Additional of education spending spending on in public repeaters b spending a Population growth Population ageing Increase Privatein sector education involvement coverage Interaction of factors Increase in spending per student 1 153 436 101 -5 -339 218 -235 82 45 Bolivia (Plurinational State of) 104 75 9 -5 -69 8 -56 -2 9 74 Brazil 457 -117 509 -33 -230 203 -628 -25 52 188 Chile 988 -501 754 39 -313 142 -248 316 197 1 373 Colombia 228 63 264 23 -135 67 -89 -2 30 449 Costa Rica 643 17 280 1 -330 121 -194 23 63 622 Dominican Republic 258 -5 114 9 -93 37 -85 0 23 79 73 70 -71 0 -42 22 -12 25 13 72 El Salvador 146 347 -227 -2 -78 46 -133 -23 -5 258 Guatemala 112 135 26 0 -82 7 -84 2 27 142 Honduras 150 43 141 -22 -105 13 -35 18 25 227 Mexico 428 25 428 -6 -232 212 -126 32 37 797 -9 -5 -20 10 -11 2 -2 4 21 -183 85 -63 17 13 112 Ecuador Nicaragua Panama Paraguay 38 566 127 -470 1 454 63 82 102 0 -66 12 -27 5 17 282 Peru 135 46 115 11 -57 33 -16 18 -2 187 Uruguay 485 335 -342 6 -67 87 -101 -29 29 404 Venezuela (Bolivarian Republic of) 241 57 330 17 -180 77 -170 24 53 447 Simple average of the countries 348 68 114 3 -145 78 -128 27 35 398 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Project documents, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/xml/0/40520/metas-educativas-2021.pdf, 2010. a Primary and secondary education spending. b Cost for secondary students who are not in the right age group for their level. 152 Economic Commission for Latin America and the Caribbean (ECLAC) 4. Resources needed to achieve universal primary and secondary education As was seen in previous pages, Latin America has experienced a remarkable expansion in public-sector education spending over the past decades. Much of this increase has gone to extending education coverage. However, some of the extra funding has also gone to improving the operating conditions of education systems, something that is expressed in the growth of spending per student. Both processes have been buoyed by substantial economic growth in this period, by measures to increase the public budget and the education budget, by the relative decline in the school-age population and, in some countries, by the greater involvement of the private sector in providing education services. For all the progress made with education coverage, a large percentage of the region’s population has yet to be incorporated and kept in the formal education system: a total of almost seven million children and adolescents, chiefly from the lowest-income sectors of each country. Given the major advances made, the extra investment required is not very onerous from a budgetary standpoint. However, the situation is somewhat more complicated in the region’s poorest countries, which are also the ones with the largest proportions of children and young people outside the education system. Assuming that the entire school-age population currently outside the education system is to be covered from public funds, effective universalization of educational access would entail redistributing public resources within the education system or expanding its budget. Redistributing resources to cover the whole school-age population would mean cutting per-student spending by some US$ 66 a year on average. The largest proportional reductions in funding per student would be in the Dominican Republic, Guatemala, Honduras and Paraguay, ranging between US$ 51 and US$ 88 a year per student (see figure III.18.A). Lastly, if the method chosen to universalize primary and secondary education is an increase in budgetary funding, the average budget increase would represent only 0.4% of 2008 GDP. This increase is affordable for most of the countries and would bring average publicsector education spending up to about 4.6% of GDP for the 18 countries analysed. In view of international normative standards and the scope for budget increases, most of the countries ought to be in a position to carry out this expansion. The exceptions are Honduras and the Plurinational State of Bolivia, where education spending is already well in excess of 6.5% of GDP (see figure III.18.B). In any event, with gradual budget increases over the coming years and, in some cases, with a little international assistance, it is possible for the region to achieve universal access to and completion of primary and secondary education. Noteworthy among other initiatives to increase national budgets in combination with international financial and technical assistance is “Educational Goals for 2021: the education we want for the bicentennial generation”, a project recently approved by the governments of the Ibero-American countries that sets financial targets and lays down goals for different areas of the education system. Figure III.18 LATIN AMERICA (18 COUNTRIES): ESTIMATES OF THE COST OF UNIVERSALIZING PRIMARY AND SECONDARY EDUCATION A. Universalization with lower annual spending per student (dollars at constant 2000 prices) Latin America B. Universalization with no change in current spending per student (percentages of 2008 GDP) 78 51 53 88 22 38 52 72 72 23 123 27 72 86 14 0 500 0.76 0.61 0.51 0.48 0.38 0.32 0.31 0.30 0.28 0.25 0.24 0.24 0.22 0.20 0.16 0.14 0.05 208 102 12 4.6 0.38 66 Honduras Paraguay Guatemala Dominican Rep. Bolivia (Plur. State of) El Salvador Colombia Chile Venezuela (Bol. Rep. of) Nicaragua Panama Costa Rica Ecuador Uruguay Mexico Peru Argentina Brazil 1 000 1 500 2 000 2 500 0 1.40 3.0 4.0 3.5 2.3 3.9 4.1 4.4 7.2 5.4 5.4 3.3 6.0 2.9 2 8.4 4.9 3.8 5.0 5.4 4 6 8 Spending per student with universal public coverage Additional spending Current spending per student 10 Total education spending with universalization Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the UNESCO Institute of Statistics (UIS) and ECLAC/Organization of Ibero-American States for Education, Science and Culture (OIS), “Metas Educativas 2021: estudio de costos”, Project documents, No. 327 (LC/W.327), Santiago, Chile [online] http://www.eclac.org/publicaciones/xml/0/40520/metas-educativas-2021.pdf, 2010. Social Panorama of Latin America • 2010 153 Box III.2 ESTIMATING EXPENDITURE PER STUDENT Expenditure per student is public-sector education spending divided by the number of students attending public establishments. Both spending and the number of students can be expressed, in turn, as a series of ratios whose impact on changes in spending and student numbers, and thus on spending per student, can then be identified. The following formula expresses this identity, budgetary priorities and the ratios between educational coverage and population: PSEt GPSEt TPS t ⋅ ⋅ ⋅ GDPt PSEt GPSEt TPS t GDPt = ExpenditurexStudent = PubStut StuSt StuPt PubStut ⋅ ⋅ ⋅ Popt StuPt Popt StuS t where: Economic indicators is total public spending as a percentage of GDP in year t, an indicator of the macroeconomic priority given to public spending overall; represents (gross) public spending on primary and secondary education as a proportion of all public spending in Economic factors Demographic factors year t, an indicator of the fiscal priority given to public-sector education spending (primary and secondary); is public spending on primary and secondary education (not including grade repetition) as a proportion of (gross) public spending on primary and secondary education in year t, a proxy for internal efficiency (or lack of it) in the education system (school repetition); Coverage and population indicators is the school-age population as a share of the whole population in year t, an indicator of educational dependency (demographic dividend); represents students as a share of the school-age population in year t, an indicator of educational access or coverage, and represents public-sector students as a share of all students in year t, an indicator of the commercialization or otherwise of education services. Viewed over time, fluctuations in a country’s spending per student depend on changes in spending and in the number of students, and can be analysed by way of these. To estimate the influence of the economic factor (spending) and the demographic factor (students) on changes in expenditure per student, the methodology used to explain changes in poverty (Datt and effect. Similarly, an estimate of spending Ravallion, 1992) was used. This consists in per student is calculated by considering TPS estimating expenditure per studentPSEt ⋅ GPSEtpublic tspending in the initial period and the by taking ⋅ ⋅ GDPt PSE GPSEt TPS GDPt public spending in the finalt period and the t number of students in the final period; in = ExpenditurexStudent = t number of students inPubStut period; the the initial PubStut StuSthis case, the difference is interpreted as StuPt difference between this estimateStuS theStuP ⋅ Pop ⋅ Popt and ⋅ the (demographic) student effect. t t t initial spending per student observed is This procedure can be expressed interpreted as the (economic) expenditure using the following formula: where ExS is expenditure per student in the starting period (t) or final period (t+1), PSE is public spending on primary and secondary education in the initial and final periods (t, t+1) and PubStu is the number of primary and secondary school students in public establishments in the initial and final periods (t, t+1). This procedure has the drawback of generating a residual (R) which does not have an analytical interpretation for each factor, as it is the interaction between them. Changes in public spending and the number of students can be cast in the form of an expression that shows different budgetary priorities and education coverage indicators. The effects are calculated in the present chapter using the full formula for spending per student, i.e., by conducting separate and joint analyses of the effects of budgetary priorities and coverage indicators on spending per student. To deal with the residual, Kakwani (1997) developed a procedure that allows Economic factors Demographic factors this to be removed from the two-factor analysis. It consists in averaging out the effects calculated with two base years, the initial base year and the final base year. This procedure does not completely do away with the residual when the analysis includes three or more effects, although it does reduce it significantly by comparison with analyses of factors of change involving just one base year. The calculations in the present chapter were carried out using this procedure. Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Gaurav Datt and Martin Ravallion, “Growth and redistribution components of changes in poverty measures”, Journal of Development Economics, vol. 38, No. 2, 1992; Nanak Kakwani, “On measuring growth and inequality components of changes in poverty with application to Thailand”, Discussion Paper, University of New South Wales, 1997; and ECLAC, Social Panorama of Latin America 2009 (LC/G.2423-P), Santiago, Chile, 2009. United Nations publication, Sales No. E.09.II.G.135. 154 Economic Commission for Latin America and the Caribbean (ECLAC) 5. The distributive impact of public-sector education spending This section will analyse the distribution of public-sector education spending used to finance public-sector schools not run by the private sector, although in some cases there might be some private financing from households. The procedure involves imputing expenditure per student at each level, expressed in monthly values, to those reporting they attend public-sector schools in household surveys. This is then expressed in per capita terms by household and compared with the per capita income distribution of the different income groups. The distribution of spending is analysed in accordance with the ranking by disposable per capita income before this transfer in kind. In the first place, taking a simple average for 15 countries in the region, public-sector education spending is slightly progressive in absolute terms and far more progressive than per capita income distribution, as can be seen in figure III.19.A. Furthermore, primary education spending is the most progressive in the region. This is largely because virtually universal coverage has been achieved at this level in the great majority of the countries, even though the private sector only serves an average of just over 17% of students. Next in progressiveness comes preschool education spending.10 This level is not compulsory in most of the countries, however, which means that coverage is fairly low, especially in low-income sectors, while high-income families generally use private services at this level. Figure III.19 LATIN AMERICA (15 COUNTRIES): DISTRIBUTION OF PUBLIC EDUCATION SPENDING BY INCOME STRATA AND COMPARISON WITH PER CAPITA INCOME a (Cumulative percentages) A. Public education spending B. Preschool and primary education spending 100 90 90 Ratio between cumulative income percentage and public spending Ratio between cumulative income percentage and public spending 100 80 70 60 50 40 30 20 10 0 0 10 20 30 40 50 60 70 Cumulative percentage of population 80 90 80 70 60 50 40 30 20 10 0 100 0 10 Public education spending Per capita income Equidistribution 30 40 50 60 C. Secondary education spending (lower and upper) 80 90 100 Preschool education Equidistribution D. Tertiary education spending (vocational and university) 90 Ratio between cumulative income percentage and public spending 100 90 70 Cumulative percentage of population Per capita income Primary education 100 Ratio between cumulative percentage of income and public spending 20 80 70 60 50 40 30 20 10 0 0 10 20 30 40 50 60 70 Cumulative percentage of population 80 90 80 70 60 50 40 30 20 10 0 100 Lower secondary education Per capita income Upper secondary education Equidistribution 0 10 20 30 40 50 60 70 Cumulative percentage of population Per capita income 80 90 100 Post-secondary and tertiary education Equidistribution 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 and information from the UNESCO Institute for Statistics (UIS). a Simple averages. 10 Given the information available in household surveys, in most of the countries it was only possible to analyse the distribution of preschool spending for children aged 4 and 5. Social Panorama of Latin America • 2010 155 Spending on secondary education is less progressive. At the lower secondary level, it remains progressive in absolute terms (see figure III.19.C) because attendance remains compulsory in all the countries and access levels are high. However, by the last years of secondary education, which is not compulsory in all the countries (see table III.3), access for the lowest-income strata falls off sharply and by more than in the other socio-economic groups (see figure III.20). This makes the distribution of public spending at this level less progressive. Moreover, the private-sector share of secondary education services is higher: an average of 25% of students, most of them from high-income strata, go to private schools. Figure III.20 LATIN AMERICA (15 COUNTRIES): ACCESS TO PUBLIC EDUCATION a (Percentages of household members) 70 62 60 52 50 42 40 40 30 30 26 0 22 20 20 10 25 15 14 9 13 12 9 6 4 Total Preschool Quintile I (poorest) Primary Quintile II Lower secondary 17 16 16 9 8 15 15 11 6 Quintile III Quintile IV Upper secondary 14 9 9 3 Quintile V (richest) Tertiary 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 and information from the UNESCO Institute for Statistics (UIS). a Simple average of the countries, taking the percentage of people in households where some member is attending a public education establishment, and not the percentage of households, to obtain statistics comparable with those for per capita income distribution. Lastly, for spending on post-secondary education (especially university education) to be progressive, coverage must obviously be expanded towards young people in lower socio-economic strata. In any case, it is less regressive than per capita income, albeit not in all countries. This spending is even more regressive than income distribution in El Salvador, Guatemala and Honduras, and is almost as regressive in Nicaragua and Paraguay (see table III.6). Access to post-secondary education is very low in all these countries and is largely confined to the high-income strata. The fact that spending on post-secondary education, and university education in particular, is highly regressive is often used as an argument for reducing public spending at this level and redirecting it to lower levels, where it can be targeted better on the lower-income strata. Given that what operate in education systems are really self-targeting mechanisms, however, it is precisely the existence of publicly funded higher education that gives lower-income sectors a chance of genuine social mobility. Consequently, public-sector efforts should be oriented towards enabling a larger and larger proportion of low-income students to continue their postsecondary studies and making spending at this level more progressive. Witness the fact that spending is considerably less regressive in countries where higher education has greater coverage. The evidence speaks for itself. The more children and young people are incorporated at all education levels and universal progression to upper cycles is attained, the larger the egalitarian redistributive impact of spending on education. There are, then, no policies with a greater egalitarian impact than those that achieve universal coverage. The data reflected herein show that greater coverage at all education levels is associated with the most redistributive impact of spending on those levels. Table III.6 LATIN AMERICA (15 COUNTRIES): GINI CONCENTRATION RATIO FOR PER CAPITA PERSONAL INCOME DISTRIBUTION AND EDUCATION SPENDING BY LEVEL Spending by education level Country Year Per capita income Preschool education spending Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Dominican Republic El Salvador Guatemala Honduras Mexico Nicaragua Paraguay Peru Uruguay Simple average of the countries 2008 2007 2008 2006 2008 2008 2008 2008 2006 2007 2008 2005 2008 2008 2008 0.519 0.572 0.595 0.525 0.574 0.475 0.550 0.493 0.587 0.583 0.519 0.538 0.531 0.476 0.446 0.532 -0.298 -0.174 -0.360 -0.201 -0.289 -0.245 0.022 -0.142 -0.246 -0.124 -0.232 … -0.116 -0.249 -0.460 -0.222 Primary education Lower secondary Upper secondary Post-secondary education spending spending spending spending -0.432 -0.222 -0.397 -0.210 -0.327 -0.296 0.151 -0.240 -0.211 -0.183 -0.263 -0.223 -0.295 -0.327 -0.462 -0.263 -0.304 -0.176 -0.290 -0.191 -0.234 -0.199 0.121 -0.091 0.109 0.067 -0.163 0.035 -0.106 -0.214 -0.346 -0.132 -0.102 -0.026 -0.106 -0.129 -0.128 -0.047 0.273 0.092 0.272 0.233 0.018 0.177 0.008 -0.114 -0.044 0.025 0.120 0.308 0.472 0.303 0.335 0.453 0.442 0.506 0.692 0.592 0.333 0.529 0.510 0.251 0.434 0.419 Total education spending -0.228 -0.045 -0.265 -0.150 -0.169 -0.115 0.269 -0.127 0.074 0.080 -0.109 0.021 -0.115 -0.205 -0.215 -0.086 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 and information from the UNESCO Institute for Statistics (UIS). 156 Economic Commission for Latin America and the Caribbean (ECLAC) Appendix Table III.A-1 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PUBLIC SOCIAL SPENDING AS A PERCENTAGE OF GROSS DOMESTIC PRODUCT (Percentages) Country Argentina Bolivia (Plurinational State of) b Period 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a 19.1 20.1 21.1 20.0 21.0 21.8 19.4 19.6 22.1 24.2 … … 12.9 14.6 16.2 16.3 17.4 17.0 16.2 … Brazil 16.6 16.1 19.5 19.4 21.6 21.2 22.1 22.4 24.1 26.2 Chile 15.3 12.0 12.4 12.2 12.8 14.3 15.1 14.8 13.2 12.2 Colombia c 5.9 7.0 10.2 13.6 12.2 11.1 11.1 11.9 12.4 13.5 Costa Rica 15.6 15.2 15.8 16.8 16.4 18.0 18.7 17.6 17.2 19.3 Cuba 27.6 32.8 28.5 23.1 22.4 23.7 26.5 31.0 34.5 40.8 Dominican Republic 3.8 5.4 5.7 5.4 5.6 6.8 6.5 6.8 8.0 … Ecuador d 7.4 8.0 6.1 5.6 4.9 4.9 5.5 6.2 6.4 … … 2.9 5.4 6.3 8.2 10.0 10.8 11.1 11.3 … Guatemala 3.7 4.6 4.6 4.8 6.7 6.8 7.3 7.3 7.5 7.6 11.4 El Salvador e Honduras 6.3 6.3 5.5 5.5 6.2 8.4 9.5 9.9 10.0 Jamaica f 8.4 8.0 8.2 9.0 … 9.5 8.3 8.6 … … Mexico 6.5 8.1 8.8 8.5 9.2 9.7 10.2 10.2 11.2 12.5 12.3 Nicaragua 6.6 6.5 7.2 6.5 7.6 8.1 9.3 10.8 11.4 Panama 7.5 9.3 8.3 8.8 9.7 9.5 8.3 8.0 9.2 9.8 Paraguay 3.2 6.6 7.8 8.7 9.1 8.0 8.9 7.7 11.3 8.9 Peru g 3.9 5.1 6.5 6.9 8.5 8.8 9.5 9.2 8.2 7.8 Trinidad and Tobago h 6.9 7.3 6.6 6.4 … 9.1 9.7 9.9 8.7 12.1 16.8 18.9 20.2 21.3 20.0 21.6 21.8 19.6 21.2 21.7 Venezuela (Bolivarian Republic of) Uruguay 8.8 9.2 7.8 8.6 8.8 11.6 11.7 11.7 13.4 … Latin America and the Caribbean i 9.5 10.6 11.0 11.1 11.7 12.4 12.7 12.8 13.6 14.4 Latin America and the Caribbean j 12.2 12.8 14.4 14.3 15.3 15.5 15.7 15.9 17.2 18.4 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. Figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data, while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. j Weighted average of the countries. Includes estimates for countries without available information. Social Panorama of Latin America • 2010 157 Table III.A-2 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PER CAPITA PUBLIC SOCIAL SPENDING (Dollars at constant 2000 prices) Country Argentina Bolivia (Plurinational State of) b Period 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a 1 166 1 409 1 551 1 547 1 683 1 635 1 299 1 527 1 997 2 387 … … 122 143 164 165 177 179 178 … Brazil 554 537 697 713 784 785 827 883 1 009 1 165 Chile 381 458 501 595 686 747 758 734 732 945 Colombia c 129 160 249 338 295 264 270 309 355 401 Costa Rica 486 516 566 606 651 727 773 775 856 1006 Cuba 864 779 632 563 568 661 772 1028 1395 1793 Dominican Republic 69 109 121 127 146 188 188 201 276 … Ecuador d 99 107 82 76 65 66 78 98 106 … El Salvador e … 53 104 128 175 222 248 266 290 … Guatemala 49 62 64 70 100 105 113 114 124 127 Honduras 67 71 61 63 70 97 114 127 139 162 Jamaica f 294 284 298 324 … 331 294 309 … … Mexico 358 457 492 482 559 621 644 673 784 889 45 42 47 45 57 63 73 90 100 110 Panama 229 317 287 315 377 371 328 345 457 559 Paraguay 45 95 115 128 129 107 116 105 162 135 Nicaragua Peru g 64 85 125 140 172 179 201 211 214 229 Trinidad and Tobago h 303 312 294 304 … 588 728 874 909 1 318 Uruguay 841 1 034 1 180 1 317 1 289 1 314 1 173 1 232 1 524 1 740 Venezuela (Bolivarian Republic of) 433 480 388 430 426 549 474 547 708 … Latin America and the Caribbean i 315 357 380 403 435 466 459 506 601 697 Latin America and the Caribbean j 440 481 557 573 623 642 637 691 813 917 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. Figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. j Weighted average of the countries. Includes estimates for countries without available information. 158 Economic Commission for Latin America and the Caribbean (ECLAC) Table III.A-3 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PUBLIC SOCIAL SPENDING AS A PERCENTAGE OF TOTAL PUBLIC SPENDING a (Percentages) Country Argentina Bolivia (Plurinational State of) c Period 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 b 62.2 63.4 65.7 65.5 64.3 62.8 66.2 64.2 63.9 62.8 … … 36.6 44.1 50.0 42.8 49.4 48.1 49.1 … Brazil 48.9 47.2 58.6 51.0 55.8 62.1 70.4 73.2 73.4 73.6 67.0 Chile 61.2 63.0 64.5 65.5 66.4 68.4 68.1 67.3 66.3 Colombia d 28.8 32.2 36.5 … … … … 74.8 71.5 69.5 Costa Rica 38.9 41.2 38.2 42.0 40.7 40.5 37.8 36.1 36.0 35.6 Cuba 35.6 34.7 39.4 45.7 44.8 47.0 51.4 53.0 52.4 53.4 Dominican Republic 43.1 44.3 50.6 45.6 43.3 49.9 47.9 46.2 48.6 … Ecuador e 42.8 48.5 33.7 27.6 21.7 20.9 25.2 28.5 27.9 … … 22.2 23.2 28.1 32.5 38.6 39.5 45.8 45.7 … Guatemala 29.9 33.3 41.3 42.7 45.1 47.3 50.4 53.8 51.8 54.1 50.0 El Salvador f Honduras 40.7 36.6 40.6 40.5 39.5 45.4 49.9 52.8 53.6 Jamaica g 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 58.6 59.3 68.7 Nicaragua 34.0 38.5 39.9 37.0 37.1 38.4 42.0 47.9 50.2 53.8 Panama 38.1 50.6 48.6 39.6 46.4 42.5 39.1 39.3 42.1 41.6 Paraguay 39.9 42.9 43.3 47.1 44.5 38.3 48.5 41.6 57.1 55.0 Peru h 33.0 35.0 39.4 39.6 0.0 52.2 52.3 52.3 53.1 51.2 Trinidad and Tobago i 40.6 40.6 42.8 40.7 … 43.5 44.6 37.9 29.4 34.4 Uruguay 62.3 67.7 70.8 70.8 67.3 68.1 61.4 61.8 67.5 75.4 Venezuela (Bolivarian Republic of) 32.8 40.1 35.3 35.4 36.6 37.8 38.6 41.0 44.0 … Latin America and the Caribbean j 40.0 42.9 44.8 44.6 45.5 47.3 48.9 49.4 50.4 51.0 Latin America and the Caribbean k 44.1 46.5 51.8 50.7 54.6 57.3 60.2 61.8 62.3 63.9 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a Official public spending totals are taken from the functional classifications of public spending in the countries, but it is possible that they may differ from other officially reported figures based on classifications of other types. b The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. c The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. d Preliminary figures. Figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). Discontinued series. The 1994-1995 figure is from 1994 and the 2004-2005 figure from 2005. e The 2006-2007 figure is from 2006. f The 1992-1993 figure is from 1993. g The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. h The figures from 1990 to 1999 are budgetary central government data, while those from 2000 onward are general government data. i The 1996-1997 figure is from 1996. j Simple average of the countries. Includes estimates for countries without available information. k Weighted average of the countries. Includes estimates for countries without available information. Social Panorama of Latin America • 2010 159 Table III.A-4 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PUBLIC SOCIAL SPENDING ON EDUCATION AS A PERCENTAGE OF GROSS DOMESTIC PRODUCT (Percentages) Country Argentina Bolivia (Plurinational State of) b Period 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a 3.6 4.0 4.2 4.2 4.7 5.1 4.2 4.5 5.3 6.0 … … 5.5 5.9 6.0 5.8 6.6 6.6 6.3 … Brazil 3.4 2.8 5.1 4.3 5.5 5.0 4.7 4.6 5.0 5.7 4.3 Chile 2.3 2.4 2.6 3.0 3.6 3.9 4.0 3.6 3.3 Colombia c 2.4 2.9 3.0 4.2 4.1 3.3 3.8 3.2 3.0 3.1 Costa Rica 3.9 4.2 4.2 4.6 4.4 5.1 5.7 5.5 5.2 5.9 10.8 11.9 9.0 7.3 7.7 9.1 11.1 13.3 14.6 18.4 Dominican Republic Cuba 0.9 1.3 1.6 1.8 2.2 2.5 2.6 1.8 2.3 … Ecuador d 2.8 3.0 2.6 2.5 2.5 2.1 2.6 2.6 2.6 … … 1.8 2.0 2.5 3.0 3.4 3.5 3.2 3.1 … Guatemala 1.8 2.0 1.9 1.9 2.5 2.9 2.9 2.9 3.0 3.2 7.5 El Salvador e Honduras 3.6 3.6 3.1 3.3 3.8 5.2 6.0 6.6 6.7 Jamaica f 4.1 4.0 4.1 4.9 … 5.8 4.5 4.7 … … Mexico 2.6 3.5 3.9 3.7 3.8 3.9 4.0 3.8 4.0 4.1 Nicaragua 2.6 2.2 2.8 2.9 3.4 3.7 4.4 4.7 5.1 5.5 Panama 3.6 3.7 3.5 4.0 4.1 4.2 4.1 3.8 4.0 3.9 Paraguay 1.3 2.9 3.6 4.2 4.4 4.3 4.0 3.9 4.5 4.1 Peru g 1.6 2.0 2.7 2.5 2.9 2.8 3.0 3.0 2.6 2.6 Trinidad and Tobago h 3.2 3.3 3.0 3.0 … 3.9 4.4 4.4 3.8 5.0 Uruguay 2.5 2.5 2.5 3.0 3.0 3.0 3.3 3.3 3.9 4.3 Venezuela (Bolivarian Republic of) 3.5 4.0 3.8 3.2 4.0 5.1 5.1 5.0 5.5 … Latin America and the Caribbean i 3.2 3.5 3.6 3.7 4.0 4.3 4.5 4.5 4.7 5.1 Latin America and the Caribbean j 3.2 3.4 4.2 3.9 4.5 4.5 4.4 4.3 4.6 5.0 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. The figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data, while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. j Weighted average of the countries. Includes estimates for countries without available information. 160 Economic Commission for Latin America and the Caribbean (ECLAC) Table III.A-5 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PUBLIC SOCIAL SPENDING ON HEALTH AS A PERCENTAGE OF GROSS DOMESTIC PRODUCT (Percentages) Country Argentina Bolivia (Plurinational State of) b Period 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a 4.3 4.6 4.9 4.6 4.9 5.0 4.4 4.5 4.9 5.3 … … 3.3 3.3 3.3 3.0 3.1 3.2 3.2 … Brazil 3.3 2.4 4.1 3.8 3.8 4.1 4.0 4.3 4.6 5.0 3.7 Chile 1.8 2.1 2.3 2.4 2.7 2.9 3.0 2.8 2.9 Colombia c 0.9 1.1 2.6 2.9 3.3 2.2 1.8 2.0 1.9 1.9 Costa Rica 4.9 4.5 4.7 4.7 4.8 5.2 5.7 5.0 5.0 5.8 Cuba 5.0 6.6 5.6 4.9 5.4 5.6 5.7 6.5 8.5 10.5 Dominican Republic 0.8 1.0 1.0 1.1 1.2 1.6 1.4 1.2 1.4 … Ecuador d 1.4 1.6 0.8 0.9 0.7 0.8 1.1 1.2 1.3 … … 1.1 2.6 2.8 3.2 3.3 3.4 3.4 3.6 … Guatemala 1.0 1.1 1.0 0.8 1.2 1.2 1.1 1.1 1.2 1.3 3.1 El Salvador e Honduras 2.4 2.4 2.2 2.0 2.0 2.8 3.2 3.0 2.8 Jamaica f 2.2 2.4 2.2 2.3 … 2.2 2.2 2.4 … … Mexico 3.0 3.4 2.3 2.2 2.3 2.3 2.3 2.5 2.8 2.8 Nicaragua 2.8 2.5 2.8 2.5 2.7 2.9 3.3 3.3 3.6 3.7 Panama 1.6 1.9 1.8 1.9 2.0 2.3 2.0 2.3 2.1 2.2 Paraguay 0.3 1.1 1.2 1.3 1.4 1.2 1.4 1.2 2.1 1.5 Peru g 0.9 0.9 1.3 1.4 1.2 1.4 1.5 1.4 1.2 1.2 Trinidad and Tobago h 2.6 2.8 2.2 2.0 … 2.1 2.3 2.6 2.3 3.4 Uruguay 2.9 3.0 3.4 2.5 3.2 3.5 3.4 3.3 3.8 4.5 Venezuela (Bolivarian Republic of) 1.6 1.7 1.1 1.1 1.4 1.5 1.6 1.6 1.8 … Latin America and the Caribbean i 2.2 2.4 2.5 2.4 2.6 2.7 2.7 2.8 3.0 3.2 Latin America and the Caribbean j 2.9 2.9 3.2 3.0 3.2 3.2 3.1 3.3 3.6 3.7 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. Figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. j Weighted average of the countries. Includes estimates for countries without available information. Social Panorama of Latin America • 2010 161 Table III.A-6 LATIN AMERICA AND THE CARIBBEAN (20 COUNTRIES): PUBLIC SOCIAL SPENDING ON SOCIAL SECURITY AND ASSISTANCE AS A PERCENTAGE OF GROSS DOMESTIC PRODUCT (Percentages) Period Country 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a Argentina 9.6 Bolivia (Plurinational State of) b 9.9 10.3 9.8 9.9 10.3 9.7 9.2 10.1 11.1 … … 1.5 2.8 3.9 5.6 5.8 5.1 4.7 … Brazil 8.5 9.7 10.0 10.6 11.7 11.2 12.0 12.1 12.8 13.6 6.9 Chile 7.7 7.6 7.1 7.1 7.6 7.9 7.5 6.5 5.8 Colombia c 2.3 2.6 4.0 5.4 3.8 4.8 4.9 6.0 7.0 7.9 Costa Rica 4.9 4.7 5.2 5.8 5.7 6.1 5.5 5.3 5.2 5.5 Cuba 7.0 9.9 8.6 7.0 7.0 6.5 7.1 8.2 8.7 9.2 Dominican Republic 0.3 0.3 0.3 0.5 0.6 1.1 0.9 2.1 2.2 … Ecuador d 3.2 3.4 2.2 2.0 1.5 1.7 1.7 2.2 2.3 … … 0.0 0.8 0.9 1.1 1.1 2.2 2.5 2.3 … Guatemala 0.8 0.9 0.8 0.8 1.0 1.2 1.3 1.2 1.1 1.2 0.8 El Salvador e Honduras 0.3 0.3 0.2 0.3 0.3 0.2 0.2 0.2 0.4 Jamaica f 0.6 0.4 0.4 0.3 … 0.4 0.4 0.4 … … Mexico 0.1 0.1 1.3 1.5 1.9 2.3 2.4 2.2 2.4 3.7 Panama 1.2 2.2 1.5 1.0 1.9 1.6 1.2 1.1 1.5 1.6 Paraguay 1.2 2.3 2.4 2.7 3.1 2.1 3.3 2.5 4.3 2.9 1.3 2.2 2.5 2.8 3.6 4.0 4.5 4.4 3.8 3.3 Peru g Trinidad and Tobago h 0.1 0.1 0.1 0.1 … 1.4 1.8 1.5 1.2 1.8 11.2 13.1 13.9 15.3 12.6 13.7 13.6 11.7 12.0 11.0 2.0 2.1 2.3 3.0 2.5 3.7 4.1 4.1 4.6 … Latin America and the Caribbean i 3.2 3.7 3.8 4.0 4.0 4.3 4.5 4.4 4.6 4.7 Latin America and the Caribbean j 4.8 5.4 6.0 6.4 6.6 6.7 6.9 6.9 7.3 8.0 Uruguay Venezuela (Bolivarian Republic of) Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. Figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data, while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. Nicaragua is not included. j Weighted average of the countries. Includes estimates for countries without available information. Nicaragua is not included. 162 Economic Commission for Latin America and the Caribbean (ECLAC) Table III.A-7 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PUBLIC SOCIAL SPENDING ON HOUSING AND OTHER ITEMS AS A PERCENTAGE OF GROSS DOMESTIC PRODUCT (Percentages) Country Argentina Period 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a 1.7 1.6 1.6 1.4 1.5 1.4 1.1 1.5 1.9 1.9 … … 2.6 2.6 2.9 1.8 1.9 2.1 2.0 … Brazil 1.4 1.3 0.4 0.8 0.6 1.1 1.5 1.4 1.7 2.0 Chile 0.2 0.2 0.2 0.3 0.4 0.3 0.3 0.3 0.3 0.4 Colombia c 0.5 0.5 0.7 1.0 1.0 0.9 0.6 0.7 0.5 0.5 Bolivia (Plurinational State of) b Costa Rica 1.9 1.8 1.7 1.8 1.5 1.6 1.8 1.8 1.8 2.1 Cuba 4.8 4.4 5.3 4.0 2.3 2.6 2.6 3.0 2.8 2.8 Dominican Republic 1.8 2.8 2.9 2.1 1.7 1.6 1.7 1.8 2.1 … Ecuador d 0.0 0.1 0.4 0.2 0.1 0.4 0.2 0.2 0.2 … Salvador e … 0.0 0.0 0.2 0.8 2.1 1.7 2.0 2.3 … Guatemala 0.1 0.6 0.8 1.3 1.9 1.6 1.9 2.1 2.2 1.9 Honduras 0.0 0.0 0.0 0.0 0.1 0.2 0.1 0.1 … … El Jamaica f 1.5 1.2 1.6 1.4 … 1.1 1.2 1.1 … … Mexico 0.9 1.2 1.3 1.2 1.1 1.3 1.5 1.8 2.1 1.9 Nicaragua 1.2 1.8 1.5 1.2 1.5 1.5 1.6 2.7 2.8 3.1 Panama 1.1 1.4 1.4 1.9 1.7 1.3 1.0 0.8 1.5 1.6 Paraguay 0.5 0.3 0.6 0.4 0.2 0.5 0.2 0.2 0.4 0.4 Peru g 0.1 0.1 0.1 0.2 0.8 0.6 0.5 0.4 0.6 0.8 Trinidad and Tobago h 1.0 1.1 1.3 1.3 … 1.5 1.3 1.4 1.3 1.8 Uruguay 0.3 0.4 0.5 0.5 1.2 1.4 1.5 1.4 1.6 1.9 Venezuela (Bolivarian Republic of) 1.7 1.4 0.6 1.3 0.9 1.3 0.9 1.0 1.6 … Latin America and the Caribbean i 1.1 1.2 1.2 1.2 1.2 1.2 1.2 1.3 1.5 1.6 Latin America and the Caribbean j 1.2 1.2 1.0 1.1 1.0 1.2 1.3 1.4 1.7 1.7 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. Figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data, while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. j Weighted average of the countries. Includes estimates for countries without available information. Social Panorama of Latin America • 2010 163 Table III.A-8 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PER CAPITA PUBLIC SOCIAL SPENDING ON EDUCATION (Dollars at constant 2000 prices) Period Country 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a Argentina 218 Bolivia (Plurinational State of) b 278 311 328 374 382 281 349 480 588 … … 52 58 61 59 67 69 69 … Brazil 114 93 181 157 200 183 175 180 208 252 268 Chile 73 90 105 139 175 195 206 198 195 Colombia c 51 66 72 106 100 78 94 83 85 93 Costa Rica 123 142 151 164 176 206 234 241 261 305 Cuba 338 283 200 178 196 253 324 442 589 808 Dominican Republic 17 26 33 41 57 70 74 52 79 … Ecuador d 37 40 36 35 33 28 37 41 44 … El Salvador e … 31 39 51 64 76 81 77 79 … Guatemala 24 27 27 27 38 44 45 45 49 54 Honduras 39 41 34 37 43 61 72 84 94 107 Jamaica f 144 142 147 175 … 201 159 170 … … Mexico 143 196 219 207 233 250 255 250 276 291 17 14 19 20 26 30 35 39 45 49 Panama 109 128 122 145 160 164 162 165 199 222 Paraguay 18 41 53 62 63 57 53 53 64 63 Peru g 27 33 51 50 58 57 64 68 68 75 Nicaragua Trinidad and Tobago h 139 142 134 142 … 264 330 386 399 550 Uruguay 123 135 143 187 195 185 175 205 281 349 Venezuela (Bolivarian Republic of) 174 210 188 161 194 243 207 233 290 … Latin America and the Caribbean i 95 105 111 118 134 147 149 163 191 227 Latin America and the Caribbean j 115 126 163 156 183 184 177 186 218 247 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. The figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data, while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. j Weighted average of the countries. Includes estimates for countries without available information. 164 Economic Commission for Latin America and the Caribbean (ECLAC) Table III.A-9 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PER CAPITA PUBLIC SOCIAL SPENDING ON HEALTH (Dollars at constant 2000 prices) Period Country 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a Argentina 261 Bolivia (Plurinational State of) b 320 362 356 392 378 294 349 439 520 … … 31 33 34 30 32 34 35 … Brazil 110 80 145 138 138 150 148 171 193 223 227 Chile 59 80 95 112 129 144 153 157 172 Colombia c 19 24 63 72 79 52 43 51 54 58 Costa Rica 153 154 168 171 189 210 235 220 248 303 Cuba 157 157 125 119 135 156 166 215 345 459 Dominican Republic 14 20 21 25 31 44 39 36 50 … Ecuador d 19 21 11 12 10 11 15 19 21 … El Salvador e … 20 50 57 70 75 77 82 93 … Guatemala 13 15 14 13 18 18 18 17 20 22 Honduras 26 27 24 22 22 32 39 39 39 44 Jamaica f 77 85 79 84 … 78 77 87 87 … 162 189 129 122 142 146 147 166 193 198 Nicaragua Mexico 19 17 18 18 20 23 26 28 31 33 Panama 49 66 63 66 79 90 79 98 106 … Paraguay 4 16 18 20 20 16 18 17 31 23 15 15 24 29 0 28 32 31 32 34 Peru g Trinidad and Tobago h 115 119 99 94 … 136 170 234 242 372 146 164 201 155 207 211 185 205 271 358 Venezuela (Bolivarian Republic of) 77 87 55 57 68 69 65 76 94 … Latin America and the Caribbean i 73 81 85 84 95 100 98 111 133 159 Latin America and the Caribbean j 106 108 123 120 129 133 126 144 168 187 Uruguay Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. The figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data, while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. j Weighted average of the countries. Includes estimates for countries without available information. Social Panorama of Latin America • 2010 165 Table III.A-10 LATIN AMERICA AND THE CARIBBEAN (20 COUNTRIES): PER CAPITA PUBLIC SOCIAL SPENDING ON SOCIAL SECURITY AND ASSISTANCE (Dollars at constant 2000 prices) Period Country 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a Argentina 586 Bolivia (Plurinational State of) b 697 758 755 795 773 650 716 910 1 095 … … 15 28 40 57 59 54 52 … Brazil 283 322 357 389 423 413 448 477 538 603 Chile 424 244 279 291 331 366 392 386 364 345 Colombia c 49 58 97 135 92 114 119 157 201 235 Costa Rica 152 160 187 208 226 248 227 234 260 288 Cuba 217 234 191 171 178 181 206 273 349 402 5 7 7 12 16 31 27 62 75 ... 43 46 29 27 21 24 24 35 38 … Dominican Republic Ecuador d El Salvador e … 1 15 18 24 25 50 60 60 … Guatemala 11 13 12 12 15 18 21 19 18 20 11 Honduras 3 4 3 3 4 2 3 3 6 Jamaica f 21 15 15 12 … 13 14 14 … … 7 6 71 86 116 146 149 142 166 264 Mexico Panama 37 76 54 35 72 64 48 47 78 … Paraguay 17 33 36 40 44 27 43 33 62 44 23 36 48 57 0 82 95 102 99 95 Peru g Trinidad and Tobago h 3 4 4 5 … 90 133 129 132 195 Uruguay 558 717 807 948 812 833 732 734 861 883 Venezuela (Bolivarian Republic of) 100 108 113 149 122 175 165 192 241 … Latin America and the Caribbean i 118 142 156 171 173 185 180 192 225 252 Latin America and the Caribbean j 197 233 278 301 320 321 311 334 396 470 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. Figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data, while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. Nicaragua is not included. j Weighted average of the countries. Includes estimates for countries without available information. Nicaragua is not included. 166 Economic Commission for Latin America and the Caribbean (ECLAC) Table III.A-11 LATIN AMERICA AND THE CARIBBEAN (21 COUNTRIES): PER CAPITA PUBLIC SOCIAL SPENDING ON HOUSING AND OTHER ITEMS (Dollars at constant 2000 prices) Country Argentina Period 1990-1991 1992-1993 1994-1995 1996-1997 1998-1999 2000-2001 2002-2003 2004-2005 2006-2007 2008-2009 a 102 116 121 108 121 103 74 114 168 184 Bolivia (Plurinational State of) b … … 25 26 30 19 20 22 22 … Brazil 47 42 15 29 23 39 57 56 70 87 27 7 9 10 13 17 17 14 16 19 Colombia c Chile 10 12 16 25 25 22 14 18 15 16 Costa Rica 58 61 61 64 60 64 77 81 88 109 154 105 118 96 59 72 77 99 112 123 34 57 61 49 44 44 49 52 72 … 0 1 6 3 2 6 3 4 3 … … 1 1 5 18 47 40 47 58 … 2 8 12 20 30 25 30 34 37 33 … Cuba Dominican Republic Ecuador d El Salvador e Guatemala Honduras 0 0 0 0 2 2 1 1 … Jamaica f 53 43 59 52 … 40 44 38 38 … Mexico 47 67 74 67 69 81 93 116 149 136 8 11 10 8 12 12 13 23 25 27 Panama Nicaragua 35 49 49 68 67 52 40 36 76 … Paraguay 6 5 9 6 4 7 3 3 6 6 Peru g 0 0 0 0 0 13 11 10 15 24 Trinidad and Tobago h 46 47 58 64 … 98 95 126 137 199 Uruguay 15 19 29 29 76 85 81 88 112 150 Venezuela (Bolivarian Republic of) 83 76 32 63 43 63 38 46 82 … Latin America and the Caribbean i 34 36 37 38 40 43 41 49 64 74 Latin America and the Caribbean j 44 47 38 43 41 48 53 62 80 87 Source: Economic Commission for Latin America and the Caribbean (ECLAC), social expenditure database. a The figures for Brazil, Chile, Colombia, Cuba, Guatemala, Honduras and Panama are from 2009. b The 1994-1995 figures are from 1995 and the 2006-2007 figures from 2006. c Preliminary figures. Figures from 2000 onward are from the Ministry of Finance and are not comparable with earlier ones. The data in the earlier series are from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE). d The 2006-2007 figure is from 2006. e The 1992-1993 figure is from 1993. f The 1996-1997 figure is from 1996 and the 2004-2005 figure from 2004. g The figures from 1990 to 1998 are budgetary central government data while those from 1999 onward are general government data. The 1998-1999 figure is from 1999. h The 1996-1997 figure is from 1996. i Simple average of the countries. Includes estimates for countries without available information. j Weighted average of the countries. Includes estimates for countries without available information. Social Panorama of Latin America • 2010 167 Table III.A-12 LATIN AMERICA (15 COUNTRIES): DISTRIBUTION OF PUBLIC SPENDING ON EDUCATION, BY EDUCATION LEVEL AND PER CAPITA INCOME Quintile, AROUND 2008 (Percentages) Country Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Dominican Republic El Salvador Guatemala Honduras Mexico Nicaragua Paraguay Peru Uruguay Simple average Country Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Dominican Republic El Salvador Guatemala Honduras Mexico Nicaragua Paraguay Peru Uruguay Simple average Country Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Dominican Republic El Salvador Guatemala Honduras Mexico Nicaragua Paraguay Peru Uruguay Simple average Year 2008 Preschool education Personal per capita income quintile Quintile I Quintile Quintile Quintile Quintile V (poorest) II III IV (richest) 34.8 26.9 19.1 14.3 4.9 Total 100.0 2007 2008 2006 2008 2008 25.9 38.9 29.7 32.5 32.0 27.8 27.6 25.0 28.1 26.8 20.0 18.9 18.9 20.7 18.7 17.5 10.5 16.9 13.5 13.9 8.8 4.1 9.5 5.2 8.6 100.0 100.0 100.0 100.0 100.0 2008 2008 2006 2007 2008 2005 2008 2008 2008 13.4 24.3 31.3 26.1 31.7 … 20.8 31.4 47.3 30.0 23.8 24.6 24.4 22.3 23.9 … 20.6 24.8 26.7 25.3 22.6 22.2 20.6 20.2 20.3 … 29.8 22.3 16.4 20.8 21.9 18.9 16.4 18.5 16.6 … 21.4 14.6 7.7 15.9 18.3 10.0 7.3 12.8 7.5 … 7.4 6.8 1.9 8.1 100.0 100.0 100.0 100.0 100.0 … 100.0 100.0 100.0 100.0 Year 2008 Primary education Personal per capita income quintile Quintile I Quintile Quintile Quintile Quintile V (poorest) II III IV (richest) 45.4 28.2 14.2 8.2 3.9 2007 2008 2006 2008 2008 16.2 19.5 24.5 22.4 20.0 23.2 25.3 24.4 24.9 19.8 23.6 26.0 20.5 23.3 24.8 24.0 19.3 18.2 19.8 21.8 13.0 9.8 12.4 9.6 13.6 100.0 100.0 100.0 100.0 100.0 2008 2008 2006 2007 2008 2005 2008 2008 2008 9.5 10.9 4.2 6.1 14.9 8.7 16.2 21.2 15.4 15.6 14.1 19.9 12.0 13.9 22.1 18.0 22.8 26.0 24.7 20.9 17.4 22.9 27.9 23.4 23.6 21.2 21.0 22.4 26.3 23.0 22.6 27.7 25.4 30.4 23.0 27.1 23.3 19.6 22.9 22.9 36.3 18.7 30.5 26.3 16.3 25.0 16.8 10.8 10.7 17.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Year 100.0 28.7 42.7 31.1 36.4 34.4 26.6 27.0 23.8 27.6 27.1 21.5 16.9 19.0 19.1 19.8 15.2 9.6 15.7 12.0 12.6 8.1 3.7 10.3 4.8 6.1 100.0 100.0 100.0 100.0 100.0 2008 2008 2006 2007 2008 2005 2008 2008 2008 14.3 29.5 28.0 26.8 32.9 30.8 32.6 37.6 48.0 33.3 18.0 27.6 25.8 25.3 26.0 24.7 29.2 25.7 26.6 26.0 16.6 21.5 22.4 21.9 19.8 20.3 19.3 19.8 15.2 19.2 20.2 14.3 16.6 17.2 13.7 15.7 13.9 11.5 7.6 13.6 30.9 7.1 7.2 8.7 7.5 8.5 5.0 5.4 2.5 8.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Year 2008 Total 2007 2008 2006 2008 2008 Lower secondary education Personal per capita income quintile Quintile I Quintile Quintile Quintile Quintile V (poorest) II III IV (richest) Year Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Dominican Republic El Salvador Guatemala Honduras Mexico Nicaragua Paraguay Peru Uruguay Simple average Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Dominican Republic El Salvador Guatemala Honduras Mexico Nicaragua Paraguay Peru Uruguay Simple average Total 2008 36.2 26.8 17.6 13.3 6.1 100.0 2007 2008 2006 2008 2008 24.9 32.3 30.0 29.1 26.3 26.4 28.4 23.6 26.9 26.4 23.7 21.8 18.3 21.8 23.3 16.4 12.4 18.0 15.6 17.3 8.6 5.1 10.2 6.6 6.7 100.0 100.0 100.0 100.0 100.0 2008 2008 2006 2007 2008 2005 2008 2008 2008 16.4 21.4 8.8 13.2 26.4 13.4 20.8 26.2 35.6 24.1 14.5 22.8 19.4 19.0 24.8 20.9 24.1 28.2 30.2 24.2 20.6 23.0 24.8 24.3 21.6 25.1 25.1 23.0 19.9 22.3 23.4 21.9 27.5 25.1 16.4 22.8 20.3 16.4 11.1 18.5 25.1 10.9 19.5 18.5 10.8 17.8 9.7 6.2 3.2 11.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2008 Vocational and university education Personal per capita income quintile Quintile I Quintile Quintile Quintile Quintile V (poorest) II III IV (richest) 14.7 16.1 19.9 23.3 25.9 Total 100.0 2007 2008 2006 2008 2008 3.5 3.2 8.8 4.9 3.8 14.2 8.4 10.8 10.4 6.7 19.0 13.2 16.9 18.5 15.6 30.2 22.7 26.7 29.9 25.0 33.0 52.4 36.7 36.3 48.9 100.0 100.0 100.0 100.0 100.0 2008 2008 2006 2007 2008 2005 2008 2008 2008 3.9 2.3 0.6 1.6 5.1 1.1 3.1 7.2 1.9 4.4 8.2 6.6 2.3 3.2 11.3 5.5 5.8 13.9 8.1 8.8 12.8 11.2 5.9 10.5 18.4 12.5 11.1 20.3 16.3 14.8 26.9 25.9 13.8 21.2 28.6 27.1 25.1 29.5 29.9 25.7 48.3 54.0 77.4 63.5 36.7 53.7 54.9 29.0 43.8 46.3 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Year Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Dominican Republic El Salvador Guatemala Honduras Mexico Nicaragua Paraguay Peru Uruguay Simple average Upper secondary education Personal per capita income quintile Total Quintile I Quintile Quintile Quintile Quintile V (poorest) II III IV (richest) 23.9 22.9 21.2 18.8 13.3 100.0 Total public spending on education Personal per capita income quintile Quintile I Quintile Quintile Quintile Quintile V (poorest) II III IV (richest) Total 2008 32.9 24.4 17.6 14.6 10.5 100.0 2007 2008 2006 2008 2008 19.6 33.1 27.4 27.1 25.5 22.8 26.3 23.3 24.5 22.6 21.4 20.0 19.3 20.6 20.5 20.7 12.8 17.6 17.1 17.0 15.6 7.8 12.5 10.7 14.4 100.0 100.0 100.0 100.0 100.0 2008 2008 2006 2007 2008 2005 2008 2008 2008 9.5 24.0 17.9 17.0 24.3 17.6 23.7 28.2 31.4 23.9 13.9 24.4 18.5 17.9 23.0 20.3 24.3 25.8 24.2 22.4 16.1 21.4 18.7 19.5 20.9 20.8 20.6 21.6 19.0 19.9 23.5 18.3 17.5 20.4 18.3 22.1 18.5 16.1 15.1 18.0 36.9 11.8 27.4 25.2 13.5 19.2 12.9 8.3 10.3 15.8 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries and information from the UNESCO Institute for Statistics (UIS). Social Panorama of Latin America • 2010 169 Chapter IV The generational economy, transfer systems and inequality in Latin America and the Caribbean A. The generational economy As part of a look at the intergenerational reproduction of inequality throughout the life cycle, this chapter takes the observed differences between generations and examines how public and private transfers target two periods of life: youth and old age. In this framework, analyses based on National Transfer Accounts for a set of countries in the region are provided as a basis for comparing the generational nature of such transfers in countries of Latin America and in developed countries. A generational and life-cycle approach like the one described in this edition of the Social Panorama of Latin America, is essential for any analysis of how to achieve greater equality in Latin America and the Caribbean. This is particularly important because the region is experiencing considerable demographic changes that have significant impacts on the age structure of the population, particularly with the rising proportion of adults and older persons. This is shifting the relative sizes of the potentially active segment (adults) and the potentially dependent one (children, young people and older persons) and is thus changing the mix of investments in human capital (education) and consumption of health care, social security, and personal care for dependent persons. In the region, with its high levels of inequality (ECLAC, 2010a), public and private mechanisms for funding and meeting the needs and consumption of dependent persons have profound consequences in terms of generations, gender and geography. All this contributes to the intergenerational transmission of poverty and can be worsened by trends such as population ageing. For example, if population ageing requires increasing public transfers to older population segments, rising pension and health care costs for these segments can eat into transfers 170 to younger groups that are not yet independent in terms of income generation and need public or private investment to develop skills. This chapter takes a critical look at a key dimension of this hard-to–solve equation discussed in earlier chapters of this edition of the Social Panorama on childhood and youth as stages of the life cycle: financing consumption via public and private transfers to differing age groups. The life cycle includes two major periods of economic dependency —one at the beginning, the other at the end— during which consumption exceeds labour income. This economic life cycle is present in all modern economies. Children and older persons have consumption needs ranging from the most basic, such as food, clothing and housing, to more complex ones, such as education in the case of children and health care in the case of older adults. There are variations, but the consumption needs of these two groups are mainly met through large flows of economic resources from the working-age population. Some of these flows are direct, as in the case of parents providing for their children. Others are more indirect, such as transfers through governments, charitable organizations and other economic and social institutions. Other mechanisms are still more complex, like savings from labour income that are subsequently converted, through direct investments or financial institutions, into the financial flows needed to meet the needs of older persons. The generational economy is the total of all these flows. In all societies, intergenerational flows —public or private— tend to be large-scale transfers and usually have a major impact on social equality or inequality and on economic growth. The degree of development of a particular generation of young people depends mostly on the resources it receives from older generations, particularly in terms of education and health care. Older persons depend for their well-being on factors that include the savings they may have built up, family support, and social programmes funded by current generations of taxpayers. Economic growth is closely related to the accumulation of capital for two purposes: to help support older persons and to transfer wealth to future generations. Relative consumption varies widely throughout the life cycle, so intergenerational transfers are not ageneutral. Changes in the age structure therefore tend to have a major impact on intergenerational resource flows. For example, during the demographic transition there is a period when the workforce grows more rapidly than the population groups that depend on it, not only because of falling fertility rates but also owing to women’s growing labour-force participation.1 All other things being equal, 1 The demographic transition is the shift from a mainly rural and agricultural society, with high fertility and mortality rates to predominately urban and industrial society with low fertility and mortality rates. Economic Commission for Latin America and the Caribbean (ECLAC) this situation produces a demographic dividend, freeing resources that can then be used for bettering family well-being or for investing in human and physical capital in order to promote long-term economic growth and development (Bloom and Williamson, 1998; Bloom, Canning and Sevilla, 2003).2 With the passage of time, and following a sustained period of low fertility rates, working-age population growth begins to slow while the older segments start to grow more quickly, partly owing to falling mortality rates among older adults. Population ageing considerably increases the burden borne by families and governments in providing health care and pensions to older adults. Most of the Latin American countries are now in the favourable stage of the demographic dividend, but many of them will very soon face the challenges of population ageing, as the developed countries have been doing for some time (Saad, Miller and Martínez, 2009; Saad and others, 2009; ECLAC/CELADE, 2008; ECLAC, 2008c; Rosero and Robles, 2008; Mejía, Vélez and García, 2010). Intergenerational flows do not necessarily change direction smoothly (as an ever-increasing share goes to older persons), and these shifts are not necessarily conducive to economic progress or generational equity. The speed and intensity of change can shake hallowed practices, entrenched political systems and obsolete and inflexible economic systems. The problems are tending to worsen in Latin America, where a number of countries are likely to experience headlong population ageing with relatively low levels of development, low income levels and relatively undeveloped political and financial institutions that, in industrialized societies, have been instrumental in dealing with population ageing. Furthermore, since income distribution is still extremely unequal in most of the Latin American countries, population ageing is very likely to take place against a background of persistently high levels of inequality. Having a full picture of the generational economy makes it easier to design and assess the public policies that are needed to face the challenges of population ageing —all the more so with the benefit of the experience of countries which have been dealing with those challenges over a longer period. Intergenerational transfers clearly 2 The demographic dividend is referred to both in this chapter and in the one on social spending. It is a stage in the demographic transition when the productive population increases in proportion to the dependent population as the ratio of children falls, the share of working-age persons climbs and the ratio of older persons is only just beginning to increase. Such is the situation in most Latin American countries, although there are some differences in the timing of the beginning and end of the demographic dividend period. The period ends when the relative weight of the older population increases to a point that the ratio of the working-age population to the dependent population is no longer favourable. Social Panorama of Latin America • 2010 171 help to improve the socio-economic well-being of specific population subgroups. In many cases, the transfers are substitutes for the accumulation of wealth during the life cycle. In others, they may influence childbearing decisions, with considerable impacts on fertility rates. Financial equity between generations hinges on historical development and future changes in private and public transfer systems. As for public transfers, their structure generally reflects the emphasis placed by each society on human capital in relation to consumption. Despite the major implications of intergenerational transfers for economic growth and for combating inequality and poverty, the ensemble of reallocations between age groups have not been analysed comprehensively. As a rule, the components of the generational economy have been studied separately. The National Transfer Accounts system provides the first comprehensive approach to overall measurement of aggregate financial flows between age groups and across time (see box IV.1). The accounts include flows relating to capital accumulation and to transfers, distinguishing those passing through public institutions from those taking place privately. They estimate all aggregate flows in accordance with the System of National Accounts (SNA) of the United Nations. Estimates are mostly based on analyses of household surveys relating to income, spending, assets, workforce and transfers, in addition to detailed administrative records available from various government bodies. Box IV.1 The national transfer accounts system The national transfer accounts system was created as part of an international project led by professors Ronald Lee, of the University of California at Berkeley, and Andrew Mason, of the East-West Center. The project began in 2004 with three participating countries (Brazil, Chile and the United States) as well as Taiwan Province of China. There are now over 30 participating countries across all the continents. They vary in terms of demographic configuration, levels of development, support systems for older adults, ways of investing in educating children and young people, and savings patterns. Comparisons between their accounts underline these differences and define the economic implications of population ageing under different institutional structures. Through the Latin American and Caribbean Demographic Centre (CELADE) Population Division, ECLAC has since 2007 been coordinating a regional project on national transfer accounts for Latin America and the Caribbean as part of the global project. This project receives financial support from the International Development Research Centre (IDRC) of Canadaa and the University of California at Berkeley. The first phase of the project has recently been completed, with the participation of five countries (Brazil, Chile, Costa Rica, Mexico and Uruguay). The second phase has begun with three additional participants: Argentina, Colombia and Jamaica. b This study uses data on national transfer accounts available for 22 countries, which are listed below with the abbreviations used in the figures and the year to which the estimates relate. Country Abbreviation Year Germany DEU 2003 Austria AUT 2000 Brazil BRA 1996, 2003 Chile CHL 1997, 2007 China CHN 2002 Costa Rica CRI 2004 Slovenia SVN 2004 Spain ESP 2000 United States USA 2003 Philippines PHL 1999 Finland FIN 2004 Hungary HUN 2005 India IND 2004 Indonesia IDN 2005 Japan JPN 2004 Kenya KEN 1994 Mexico MEX 2004 Nigeria NGA 2004 Republic of Korea KOR 2000 Sweden SWE 2003 Thailand THA 2004 Uruguay URY 2006 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from the national transfer accounts project [online] http://www.ntaccounts.org. a “Intergenerational Transfers, Population Aging and Social Protection in Latin America”, project, No. 104231 [online] http://www.idrc.ca. b Project on intergenerational transfers, population aging and social protection in Latin America (see http://www.cepal.cl/celade/proyecto_transferencias). While the national transfer accounts are not without limitations (see box IV.2), the system is grounded in wide-ranging research in the field of intergenerational transfers. Following the pioneering work of Samuelson (1958) and Willis (1988), Lee and his colleagues established a theoretical framework on transfers which has been applied in a number of contexts (Bommier and Lee, 2003; Lee, 1994a and 1994b). “Generational accounting” was developed as well, and has been used in several countries to project public-sector accounts into the future (Auerbach, Gokhale and Kotlikoff, 1991; Auerbach, Kotlikoff and Leibfritz, 1999). And considerable progress has been made in modelling private and family transfers (Altonji, Hayashi and Kotlikoff, 2000; Frankenberg, Lillard and Willis, 2002; Lillard and Willis, 1997; McGarry and Schoeni, 1997). Family transfers play a particularly vital role because, in the case of children, they are almost universally the main source of income. Family transfers to older persons generally have a profound effect on intergenerational 172 Economic Commission for Latin America and the Caribbean (ECLAC) equity (Mason and Miller, 2000). Advances in modelling household resource allocation have been vitally important for estimating intergenerational transfers within the household and their interaction with alternative transfer systems and for studying how population ageing affects this system (Bourguignon, 1999; Bourguignon and Chiappori, 1992; Deaton, 1997; Lazear and Michael, 1988, Mason and others, 2009). With a robust, well-defined conceptual framework, a broad set of analyses, and the growing availability of household surveys, it has been possible to estimate a complete set of National Transfer Accounts for a significant group of countries (see box IV.1). This chapter uses that information to analyse the role of public and private intergenerational transfers in a number of Latin American contexts, focusing on their impact on inequality and the potential effects of current demographic changes on these transfers in the near future. Thus, the information provided here is essential for moving forward in the areas covered by the two previous chapters concerning social spending on education (that is, on the current young generation) and the ability of public policies to sustain, over the long run, investment designed to reduce gaps and improve in educational system achievements. The remainder of this chapter is organized into four sections. Following this introduction, section B provides an international comparison of national transfer accounts, underlining the particularities of the Latin American countries in terms of the economic life cycle, consumption and labour income by age group, and public and private transfers. Section C analyses how public transfers help to satisfy the consumption needs of children and older persons from different socio-economic subgroups in Brazil and Chile, in order to assess the impact of those transfers on the reduction of inequality in each of the countries. Lastly, section D summarizes the main conclusions arising out of the previous sections and offers some general recommendations on the use of National Transfer Accounts as a tool for guiding public policies. It also sets out specific public-policy recommendations based on the results of this study. Box IV.2 Methodological problems of national transfer accounts Although the national transfer accounts system provides a fairly comprehensive conceptual and methodological framework for assessing how economic resources are allocated among different age groups and generations, its empirical estimates are subject to implicit assumptions which may affect the findings. Differences between countries in terms of data availability and quality may impair the comparability of the analyses. As a result, a number of methodological challenges need to be explained. The first challenge is that the national transfer accounts system uses a fixed age matrix of economic profiles. Estimates of relationships between economic and demographic variables therefore do not take into account changes in economic behaviour caused by exogenous demographic variations, such as fertility or mortality rates (Shultz, 2009). A clear example of this methodological limitation is the non-inclusion of any changes in family transfers to children (such as education and health care) which may result from smaller family size or longer life expectancy. While national transfer accounts should have a more flexible age matrix that includes endogenous effects, the evidence shows that pure composition effects captured in the framework of the system are too significant to be disregarded. The second problem is that the accounts use average flows between age groups to estimate how resources are allocated during the life cycle. Nonetheless, in societies with high levels of inequality, as in the case of Latin America, average flows may be masking substantial differences within socio-economic groups. Recently, some of the countries participating in the national transfer accounts project —including Brazil, Chile, South Africa and Uruguay— began to produce estimates which do take account of socio-economic levels (see section C of this chapter). A further methodological problem is how to incorporate the effects of social mobility into estimates of inter- and intragenerational transfers. A third issue is that the accounts do not consider time transfers. As a result, their accounting system fails to include unpaid activities that often replace other types of financial flows. Since women generally bring less into the household in monetary terms but spend much of their time caring for children and older persons, estimates of transfers by gender are probably biased. A research group in the project is working on this issue. The main methodological problem facing them is how to, on the basis of surveys, identify and assign a cost to unpaid activities so that they are comparable internationally (data on time transfers are not available for all countries). Lastly, the lack of sufficient information prevents most of the countries taking part in the global National Transfer Accounts project from having longer time series for the accounts as would be necessary in order to construct the cohorts’ real experience. Current estimates use synthetic cohorts, which might entail biased age profiles if the events examined were to vary between cohorts. Source: Economic Commission for Latin America and the Caribbean, on the basis of information from studies of national transfer accounts. Social Panorama of Latin America • 2010 173 B. National transfer accounts: Latin America in the international context Consumption profiles based on age vary significantly among the countries participating in the global National Transfer Accounts project. In middle-income countries consumption varies very little during adulthood and consumption by children is slightly lower than for the average adult. In high-income countries, consumption by children is relatively higher compared with medium-income countries and consumption levels rise with age. This is because middleincome countries invest less in education and because, in higher-income countries, public pension systems provide greater coverage and spending on health care for older people is higher. Corroborating the findings on consumption, the countries of Latin America present relatively low levels of public investment in children and young people. The economic life cycle In modern societies, the economic life cycle comprises three stages: a surplus stage (when labour income exceeds consumption) between two dependency or deficit stages (when consumption exceeds labour income). The deficit stages involve massive resource flows from the working-age population towards dependent age groups. These flows between age groups and generations —via the family, the State, and financial markets— define the generational economy. Falling family sizes and rising longevity are altering the age structure of the Latin American population. This is having a profound impact on intergenerational flows and, consequently, on economic growth and inequality in the region, including the economic well-being of children and older persons. While the general economic life-cycle pattern shown in figure IV.1 is observed in all the countries participating in the global project on National Transfer Accounts, there are some significant differences which merit further examination. The general characteristics of the two main components of the economic lifecycle (consumption and labour income) should be considered first. Figure IV.1 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: AVERAGE LABOUR INCOME AND AVERAGE PER CAPITA CONSUMPTION RELATIVE TO PER CAPITA LABOUR INCOME IN THE 30-49 AGE GROUP, AROUND 2000 a (Percentages) 120 Percentage of per capita labour income in the 30-49 age group 1. 100 80 60 40 20 0 0 10 20 30 40 50 60 70 80 90 Age Per capita labour income Per capita consumption Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/East-West Center, October 2010. a Simple average of 22 countries participating in the global national transfer accounts project: in Latin America, Brazil, Chile, Costa Rica, Mexico and Uruguay; in Asia, China, India, Indonesia, Japan, Philippines, Republic of Korea and Thailand; in Africa, Kenya and Nigeria; in Europe, Austria, Finland, Germany, Hungary, Slovenia, Spain and Sweden; and the United States. Per capita consumption includes private and public consumption. Per capita labour income includes fringe benefits and selfemployed income. Economic Commission for Latin America and the Caribbean (ECLAC) (a) Consumption profile by age group The per capita consumption profile includes both private and public consumption (the latter being publicsector transfers in kind). There is a wide variety of consumption profiles among the countries participating in the global National Transfer Accounts project, in terms of both the shape and the relative height of the curves (Tung, 2011). In the case of private consumption, in most countries the curves have a classical shape with a single peak, where consumption rises with age, reaches a maximum level and then decreases. But in some countries the curves have multiple peaks at different ages. In the case of public consumption, while public programmes usually target the young and the old, their relative scale tends to vary with the size of the economy and the types of institutional arrangements available. Figure IV.2 shows per capita consumption by age group relative to per capita consumption between ages 30 and 49 for the countries participating in the global National Transfer Accounts project, distributed between two groups: high-income and middle-income, according to the World Bank classification.3 For the middleincome countries, relative consumption begins at 0.43 at birth, reaches 1 at around age 20 and remains more or less at that level throughout life. Very little variation in consumption is observed during adult life, whereas children’s consumption is, as expected, somewhat lower than that of the average adult. For the high-income countries, the consumption pattern differs from that of middle-income countries in at least two major respects. First, children’s consumption is relatively higher because during the first 15 years of life relative consumption in the high-income economies is between 15% and 33% higher than in the middle-income group. This is mostly due to the countries’ investment in human capital. According to Becker’s hypothesis on the quantity-quality trade-off in fertility (Becker, Murphy and Tamura, 1990), lower fertility levels entail lower dependency ratios in households and, as a result, higher private investment per child.4 Lee and Mason (2009) found a negative correlation between fertility levels and human-capital investment per 3 4 The middle-income countries are those whose per capita GDP was between US$ 996 and US$ 12,195 in 2009. The high-income countries had per capita GDP exceeding US$ 12,195. Of the economies participating in the global project on National Transfer Accounts, the high-income ones are the European countries, Japan, the Republic of Korea and the United States. The other participating economies are middle-income ones. The dependency ratio is the ratio of persons of economically dependent age (children and older persons) to working-age persons. child in the countries participating in the global project on national transfer accounts. This may help to explain the differences shown in figure IV.2. The higher investment in education observed in the higher-income economies is largely due to the leading role played by the State in this area. Data from the project, for example, show that public consumption as a proportion of children’s total consumption in Europe is 62% above the level in Latin America. Figure IV.2 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: PER CAPITA CONSUMPTION BY AGE IN MIDDLE- AND HIGH-INCOME ECONOMIES, RELATIVE TO PER CAPITA LABOUR INCOME IN THE 30-49 AGE GROUP, AROUND 2000 a (Percentages) 160 Percentage of per capita labour income in the 30-49 age group 174 140 120 100 80 60 40 20 0 0 10 20 30 High income 40 Age 50 60 70 80 90 Middle income Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. a Per capita consumption in middle-income economies is calculated as a simple average of Brazil, Chile, China, Costa Rica, India, Indonesia, Mexico, Philippines, Thailand and Uruguay. Per capita consumption in high-income economies is calculated as a simple average of Austria, Finland, Germany, Hungary, Japan, Republic of Korea, Slovenia, Spain, Sweden and United States. Figure IV.2 also shows higher consumption levels at more advanced ages in high-income countries. At age 85, for example, consumption in that group of countries is approximately 25% higher than at age 45. This pattern differs widely from that seen in the middle-income countries, where consumption is fairly stable throughout adulthood, for two reasons. First, public-sector pensions are practically universal in the high-income countries, where they make up a significant part of the resources used for older persons’ consumption. Second, public and private spending on health care at more advanced ages tends to be much greater in the richer countries compared with the middle-income ones. Data from the National Transfer Accounts project show that average per capita spending on health care at age 80 in the high-income countries (approximately 20% of per capita GDP per worker) is almost triple the relative spending observed Social Panorama of Latin America • 2010 Figure IV.3 ECONOMIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: PER CAPITA CONSUMPTION BY OLDER PERSONS AND THE YOUNG, RELATIVE TO PER CAPITA CONSUMPTION IN THE 20-64 AGE GROUP, AROUND 2000 a (Percentages) 150 140 Per capita consumption among persons aged 65 and over in the middle-income countries (around 7% of per capita GDP per worker). There are a number of possible reasons for this difference in health care. First, there have been changes in medical procedures for chronic illnesses such as cancer, heart disease and diabetes, with increasingly aggressive and costly forms of treatment. Second, much long-term care for older persons in the middleincome countries is given within the household by family members (and is therefore not taken into account financially), whereas in the high-income countries such care is provided in institutions or by health workers in the home (and is therefore taken into account). The expectation of rising health-care costs among older persons amplifies the impact of demographic ageing on health-care spending. In a recent study, CELADEPopulation Division of ECLAC forecasts that as the ratio of older persons in the population rises and the intensity of health-care consumption among those older adults grows, there can be profound changes in the supply of services by the region’s health-care systems and a significant rise in health-care spending. The rise may amount to three percentage points of GDP by 2040 in Argentina, Brazil, Chile, Colombia, Costa Rica, Mexico and Panama (ECLAC/CELADE, 2010). Some projections show that in a number of the region’s countries, the fiscal burden for funding health care will probably be greater than for pensions (Miller, Mason and Holz, 2009). While much of the public debate in Latin America has focused on pensions, these studies draw attention to the urgent need to include public health-care funding in the discussions. Figure IV.2 highlights the differences between the two groups of countries in terms of consumption by children and older persons. The figures are still more striking when these two population groups’ per capita consumption is compared directly. In figure IV.3, which shows the distribution of the participating countries for which data are available on per capita consumption among the 0-19 and 65-and-over age groups (in relation to per capita consumption in the 20-64 age group), Brazil, Chile, Costa Rica and Mexico stand out for their low levels of consumption among children and young people (values to the left of the median), reflecting the low general levels of investment in human capital in Latin America. This situation reflects the concentration of poverty among children in those societies, which could also partly explain the relatively low levels of consumption observed among children in Germany and the United States, which are close to Brazil’s level in figure IV.3. 175 SWE USA 130 JPN BRA 120 DEU NGA 110 IND CRI PHL CHL KEN 100 SVN HUN FIN AUT URY ESP CHN THA MEX 90 KOR IDN 80 50 60 70 80 90 100 110 Per capita consumption among persons aged 0-19 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. a Per capita consumption includes private and public consumption. The dotted line shows the median for the variable on each axis. The key to country and territory abbreviations is in box IV.1. On the other hand, following the pattern seen in figure IV.2, relative consumption by older persons in most Latin American countries is proportionate to adults’ consumption (value close to 1 in figure IV.3). In Brazil, however, relative consumption among older persons is almost double the level among children and young people. Only three of the participating countries surpass Brazil in terms of consumption by older persons: Japan, Sweden and the United States. In these three countries, higher consumption is due mostly to generous public-sector spending on health care for older persons. On the bottom right-hand side of figure IV.3, China and the Republic of Korea stand out for their high levels of consumption among children and young people, reflecting their commitment to education. At the same time, the relatively low per capita consumption among persons aged 65 and over reflects the lack of more general pensions systems and public health-care programmes, and, consequently, how much consumption by older persons depends on family transfers. Co-residence of older persons and adult children in the family home tends to be quite high in these societies. Another factor may be the widespread practice whereby health care is provided to older persons within the home by family members. As mentioned above, this is not taken into account in the national transfer accounts system. 176 Economic Commission for Latin America and the Caribbean (ECLAC) (b) The age profile of labour income As has already been stated, the economic life cycle is defined by age patterns in consumption and labour income. In the framework of the National Transfer Accounts system, labour income is the sum of wages and fringe benefits plus part of self-employed income. Figure IV.4 shows the profile of average labour income by age for the countries participating in the global National Transfer Accounts project, in relation to per capita labour income in the 30-49 age group. As might be expected, the curve is bell-shaped: it rises gradually with age, reaches a peak around age 35-55 and then falls with advancing age. There are, however, considerable variations between countries, as has been widely illustrated in the economic literature. The factors responsible for these include changes in individual productivity according to age, preferences regarding consumption and leisure, and institutional factors such as the existence of State pension programmes and each society’s commitment to education. Other factors, such as age and gender discrimination in the labour market, may also be producing differentiated effects on rates of activity and wages among the countries participating in the global National Transfer Accounts project. Figure IV.4 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: AVERAGE PER CAPITA LABOUR INCOME BY AGE, RELATIVE TO PER CAPITA LABOUR INCOME IN THE 30-49 AGE GROUP, AROUND 2000 a (Percentages) 120 Percentage of per capita labour income in the 30-49 age group 100 80 60 40 20 0 0 10 20 30 50 40 60 70 80 90 Age Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. a Per capita labour income includes fringe benefits and self-employed income. Uses the simple average of 22 countries participating in the global National Transfers Accounts project: in Latin America, Brazil, Chile, Costa Rica, Mexico and Uruguay; in Asia, China, India, Indonesia, Japan, Philippines, Republic of Korea and Thailand; in Africa, Kenya and Nigeria; in Europe, Austria, Finland, Germany, Hungary, Slovenia, Spain and Sweden; and the United States. No clear regional pattern appears from the analysis of labour income age profiles for the participating countries, but there is considerable regional variation in the typical ages for entering and exiting the labour market. In order to illustrate these differences, an estimate was first made of modal ages at which the variance of labour income is the greatest between the countries considered, that is, 21 and 57 years. Second, for each country, labour income at those two modal ages was calculated against labour income in the 30-49 age group. The results are shown in figure IV.5. Inasmuch as per capita labour income is calculated by dividing total labour income for a given age group by the total population in that age group, this indicator reflects not only labour income per worker but also workforce activity rates by age. Dividing figure IV.5 into four quadrants according to the median per capita labour income at ages 21 and 57 in the countries participating in the global National Transfer Accounts project reveals that most high-income countries are in the upper left-hand quadrant, meaning that they have low incomes at age 21 and high incomes at 57. This reflects, on the one hand, longer education periods for young people and, on the other hand, the fact that adults stay longer in the labour market, probably owing to the gradual rise of the minimum retirement age. Four countries (Brazil, Kenya, Slovenia and Spain) stand out because of relatively low incomes both at age 21 and at age 57. Brazil is particularly noteworthy because gradual improvements in the State education system have prompted children and young people to stay in the educational system longer, and a generous State pension system has been developed. The remaining Latin American countries present no distinctive patterns, with most of them grouped around the average levels of labour income (see figure IV.5). A related question is the duration of economic independence through the life cycle, in other words, how long labour income exceeds consumption. To analyse this issue, figure IV.6 shows the ages at which economic independence begins and ends in a number of countries participating in the global National Transfer Accounts project.5 The results show that the median duration of economic independence for the sample of the countries is only 32 years. Aside from Uruguay, the countries of Latin America have the shortest periods of economic independence, ranging from around 20 years in Brazil and Mexico to 28 years in Chile and Costa Rica. A number of microeconomic factors are involved, such 5 The results are ordered by country from top to bottom according to the length of the period of economic independence. Social Panorama of Latin America • 2010 177 as high levels of income inequality and the relatively low rates of labour-market participation by women in the countries of Latin America compared with other countries participating in the National Transfer Accounts project. However, this situation reflects mainly the high aggregate levels of consumption in relation to labour income, resulting from low levels of savings (as in the case of Brazil) and from dependence on natural resources to finance current consumption (as in the case of petroleum in Mexico and copper in Chile) (Tung, 2011). Figure IV.5 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: PER CAPITA LABOUR INCOME AT AGE 21 AND AGE 57, RELATIVE TO PER CAPITA LABOUR INCOME IN THE 30-49 AGE GROUP, AROUND 2000 a (Percentages) Figure IV.6 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: DURATION OF ECONOMIC INDEPENDENCE, AROUND 2000 a (Years) Mexico (16) Brazil (21) Costa Rica (28) Chile (28) India (29) Nigeria (30) Slovenia (31) Germany (31) Mean(31.7) Thailand (32) Rep. of Korea (32) Indonesia (32) Philippines (33) Spain (33) United States (34) Japan (34) Hungary (34) Finland (34) Kenya (35) Austria (36) China (38) Uruguay (38) Sweden (38) 120 NGA Per capita labour income at age 57 110 JPN 100 SWE USA 90 URY PHL MEX CRI CHL THAIDN IND FIN HUN 80 DEU ESP 70 60 CHN BRA 50 SVN KEN 40 30 AUT KOR 0 10 20 30 40 50 60 70 Per capita labour income at age 21 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. a The dotted line shows the median for the variable on each axis. 2. 48 33 32 52 54 53 27 26 57 29 32 61 55 25 27 26,3 26 24 27 27 26 26 26 25 26 24 57 56,9 57 55 58 59 58 59 59 58 59 58 21 22 56 59 24 25 20 25 61 62 30 35 40 45 50 55 60 65 Age Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. a Economic independence is defined as the period during which labour income exceeds consumption. The countries are ordered from low to high (values in parentheses beside country name abbreviations). The figure shows the ages of onset and end of independence. Financing consumption throughout the life cycle: intergenerational transfers A sizeable part of the life cycle is generally spent in economic dependency, so sources of support other than labour income are needed to help to meet consumption needs during the life cycle. In the framework of the National Transfer Accounts system, there are three main reallocation mechanisms between age groups and generations: public transfers, family transfers and asset-based reallocations. Figure IV.7 shows net public transfers, that is, the difference between benefits received and taxes paid, as a percentage of per capita labour income in the 30-49 age group, for 19 of the countries participating in the global National Transfer Accounts project. During the working-age period, when individuals reach the highest surplus in their life cycle and therefore have the greatest capacity to pay taxes and contribute to the public sector, net public transfers are negative. Taxes are generally low in the case of older persons, lower still for children and young people, and considerably higher in the case of working-age adults because of how economic activities are taxed. Taxes that depend heavily on labour income lead to higher flows of public transfers from working-age adults; higher property taxes tend to increase flows of public transfers from older adults. Taxes on consumption, on the other hand, tend to be distributed more equitably among the age groups. Since the combination of income sources varies between countries, there are also differences in the flows of public transfers among age groups. The 178 Economic Commission for Latin America and the Caribbean (ECLAC) general pattern, however, is that public transfers mostly come from the working-age population. Figure IV.7 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: AVERAGE PER CAPITA NET PUBLIC TRANSFERS, BY AGE, RELATIVE TO PER CAPITA LABOUR INCOME IN THE 30-49 AGE GROUP, AROUND 2000 a (Percentages) net transfers received by children and young people as a percentage of the per capita labour income of adults aged 30-49 range from 6% in China to 29% in Finland. In the case of older persons, the range is from -2% in Thailand (showing that older persons in that country pay more in taxes than they receive in benefits) to 87% in Brazil, where a wide-reaching pension programme, including non-contributory pensions, is in place. 40 Figure IV.8 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: PER CAPITA NET PUBLIC TRANSFERS TO YOUNG PEOPLE (AGED 0 TO 19) AND OLDER PERSONS (65 AND OVER), RELATIVE TO PER CAPITA LABOUR INCOME IN THE 30-49 AGE GROUP, AROUND 2000 a (Percentages) Percentages of per capita labour income in the 30-49 age group 30 20 10 0 -10 30 -20 0 22 59 90 Age Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. a Per capita net public transfers are calculated as the difference between benefits received from the State and taxes paid. They are expressed as a percentage of per capita labour income in the 30-49 age group in the respective countries. Simple average of 22 countries participating in the global national transfer accounts project: in Latin America, Brazil, Chile, Costa Rica, Mexico and Uruguay; in Asia, China, India, Indonesia, Japan, Philippines, Republic of Korea and Thailand; in Africa, Kenya and Nigeria; in Europe, Austria, Finland, Germany, Hungary, Slovenia, Spain and Sweden; and the United States. Children and older persons tend to be net beneficiaries of public transfers. Health care is generally the main source of public transfers towards those aged under five. In the 5-to-15 age group, public education becomes the main component. As for older persons, as might be expected, social security and health care make up almost all public transfers. Benefits are generally the lowest for the working-age population, higher for children and young people, and significantly higher in the case of older persons. The high levels of per capita net benefits among children and older persons are the combined result of higher levels of transfers and low levels of taxation. After analysing the typical pattern of net transfers on the basis of the simple average of the participating countries, the impact of each government’s taxation and public spending policies on per capita benefits received by children and young people from birth to age 19 was compared with benefits received by older persons (65 and over). As can be seen in figure IV.8, the countries vary widely in this regard. Per capita Per young person (aged 0 to 19) -30 FIN HUN JPN 25 SWE SVN USA 20 DEU AUT ESP 15 10 KOR THA MEX IDN PHL CHL BRA URY CHN 5 0 -10 CRI 0 10 20 30 40 50 60 70 80 90 100 Per older person (aged over 65) Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. a Per capita net public transfers are calculated as the difference between benefits received from the State and taxes paid. They are expressed as a percentage of per capita labour income in the 30-49 age group in the respective countries. The dotted line shows the median for the variable on each axis. Corroborating the findings for consumption, the countries of Latin America show relatively low levels of public investment in children and young people. In Brazil, Chile and Costa Rica, these low levels of investment in children and young people are combined with high levels of public transfers to older persons. Brazil is an extreme example of a system of public transfers skewed towards older persons, owing to the high volume of pensions going to that age group (around 12% of GDP). In Brazil, average net public transfers to children and young people are one ninth of the average level going to older persons. As can be seen in figure IV.8, the ratio of net public transfers to older adults and to children and young people is much more balanced in the high-income countries than in the countries of Latin America. Governments Social Panorama of Latin America • 2010 in Europe, Japan and the United States spend on older persons (as a percentage of labour income) approximately the same as the Latin American countries do, but they invest twice as much on children and young people. In considering these results it is important to take into account that the sample of Latin American countries participating in the global National Transfer Accounts project does not include the region’s poorest countries, where the public sector plays a smaller part in supporting consumption by children and young people and by older persons. As a general pattern, figure IV.8 shows a strong positive correlation between public transfers to young people and transfers to older persons. The simple correlation between the two transfers is 0.55, rising to 0.73 if the atypical result from Brazil is discounted. This cross-cutting evidence is consistent with the approach which considers government action to be the result of intergenerational cooperation. It generally coincides with the ideas of Becker and Murphy (1988), who held that generations cooperate through the public sector to deal with low levels of income security in old age and to ensure the necessary investment in education during youth. The countries of Latin America, however, are clear exceptions to this pattern. In most Asian countries net public transfers are relatively low both for young people and for older adults. In most European countries and in Japan, both types of transfers are relatively high. But in most Latin American countries the transfers are significantly lower for the young than for older persons. Turra and Queiroz (2005) suggest that these imbalances in the Latin American countries may be more closely related to high levels of income inequality than to the political influence of older persons. Figure IV.9, which expands the analysis presented in figure IV.8 by including all sources of support available during the economic life cycle, shows clearly that family transfers are the main source of support for consumption by children and young people in the Asian economies, except for Japan (between 68% and 79%). The same occurs in the Latin American countries (68% to 77%), although in this case overdependence on family transfers may be more harmful to the wellbeing of children and young people than in Asia because 179 income inequality among Latin American families is greater. In Europe, Japan and the United States, family transfers are relatively lower (39% to 63%), owing to more significant public-sector investment, as has already been mentioned. In many economies, older persons continue to work up to quite advanced ages and their labour income is an important source of support for their consumption needs. Examples include Indonesia (44%) and the Philippines (39%). In European countries such as Austria and Germany, on the other hand, the labour income of older persons represents a very small fraction of consumption (2% to 3%). The Latin American countries are between these two extremes. As a percentage of consumption, the labour income of older persons in these countries ranges from a low of 18% in Brazil to a high of 26% in Mexico. Net public transfers are the main source of support for older persons in both Europe (59% to 94%) and Latin America, except Mexico (49% to 89%). In Mexico, income from assets, particularly State-owned assets, is the main source of support for older persons (71%). The use of assets for consumption by older persons varies considerably among the participating countries, from 2% in Hungary to 81% in Indonesia. Family transfers are a large part of consumption in some economies, particularly in Asia; one example of this is Thailand (30%). In most of the participating countries, however, net family transfers are downward, from older persons to younger family members. This pattern is particularly strong in Brazil (-31%), Mexico (-19%) and Uruguay (-11%). Noteworthy in figure IV.10 is the negative value of net private transfers in countries where public transfers play a major part in consumption by older persons, such as Austria, Brazil, Costa Rica, Spain, Sweden, United States and Uruguay. At first sight, these findings might suggest a substitution effect between public-sector transfers and family support for older persons in highincome countries and in Latin America. Nonetheless, the negative correlation between net public-sector and private-sector transfers to older persons is quite weak among the countries participating in the global national transfer accounts project (r=- 0.22, excluding the atypical values for Brazil). 180 Economic Commission for Latin America and the Caribbean (ECLAC) Figure IV.9 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: SOURCES OF SUPPORT FOR YOUNG PEOPLE (AGED 0 TO 19) RELATIVE TO PER CAPITA CONSUMPTION, AROUND 2000 (Percentages) Figure IV.10 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: SOURCES OF SUPPORT FOR OLDER PERSONS (65 AND OVER), RELATIVE TO PER CAPITA CONSUMPTION, AROUND 2000 (Percentages) Hungary 80 Indonesia China Finland Thailand 70 Phillipines 50 40 Brazil 20 United States 10 40 20 Indonesia -20 Uruguay Slovenia Mexico Germany Costa Rica Austria Chile Spain Public Family Mexico Germany -40 Chile Rep. of Korea United States Spain Uruguay Rep. of Korea Japan Costa Rica Employment Assets Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. 3. Slovenia 0 0 10 - Thailand Brazil 60 Sweden 30 Phillipines Austria 80 Japan 60 Hungary 100 Public Family Employment Assets Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010. The fiscal impact of population ageing The age patterns in intergenerational transfers, particularly public transfers, can be used to assess the impacts of demographic change in terms of fiscal risks in the different regions of the world. Population ageing is likely to reduce the support ratio, that is, the ratio of net contributors to net beneficiaries, in countries where public transfers to older persons predominate. On the other hand, in countries where public transfers to children are more significant, demographic change may bring about fiscal relief. Table IV.1 shows the direction of net public transfers between age groups in a number of countries participating in the global national transfer accounts project, based on the aggregate and per capita values of transfers to older persons relative to children and young people. The results in table IV.1 generally reflect those obtained from previous analyses. As mentioned above, in the Latin American countries participating in the global National Transfer Accounts project, public investment on children and young people is relatively low, while public transfers to older adults are relatively high. It is therefore unsurprising that the ratio of net public transfers to older persons in relation to young people is above one in all the Latin American countries, particularly in Brazil (9.53), Chile (3.99) and Costa Rica (3.90), where these values are the highest of all the participating countries. Since population ageing in the Latin American countries is still not very advanced, this pattern of public transfers skewed towards older persons is mitigated by an age structure that is still relatively young. Consequently, the aggregate average of net public transfers to older persons as a ratio of transfers to young people in the Latin American countries (0.77) is significantly lower than in Europe and Japan (1.84). As the demographic transition progresses in the Latin American countries, however (and if there are no major changes in the pattern of age transfers), it can be expected that these countries will come to spend relatively more on older persons, in aggregate terms, than the developed countries. Social Panorama of Latin America • 2010 181 Table IV.1 countries participating in the global national transfer accounts project: AGE-GROUP DIRECTION OF NET PUBLIC TRANSFERS, AROUND 2000 Ratio of total net public transfers received by older persons to those received by young people Ratio of the population of older persons to that of young people Ratio of per capita net public transfers received by older persons to those received by young people Germany 2.56 0.88 2.91 Sweden 2.38 0.72 3.33 Austria 2.32 0.67 3.48 Japan 1.67 1.02 1.65 Hungary 1.65 0.73 2.26 Spain 1.62 0.79 2.05 Slovenia 1.58 0.73 2.16 Uruguay 1.39 0.42 3.29 Finland 1.34 0.67 1.99 Brazil 1.21 0.13 9.53 Chile 0.79 0.20 3.93 China 0.73 0.23 3.11 United States 0.63 0.44 1.42 Costa Rica 0.55 0.15 3.67 Republic of Korea 0.26 0.25 1.07 Mexico 0.23 0.12 1.90 Indonesia 0.01 0.15 0.08 Philippines -0.01 0.07 -0.09 Thailand -0.03 0.21 -0.16 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010; Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC, population estimates and projections, 2008 and United Nations, World Population Prospects: The 2008 Revision, New York, 2008. Changes in the age structure of the population throughout the demographic transition have a fiscal impact because older persons and children and young people are net recipients of public benefits, whereas working-age adults are net contributors (see figure IV.7). At the early stages of population ageing, during the demographic dividend period, the working-age population grows more quickly than the younger population. These changes decrease the tax burden for governments. In the case of federal systems such Brazil and the United States, this is felt more strongly at the state and local government level, which are traditionally the main sources of funding for publicly-funded education. This weakening of tax burdens does not necessarily imply a real reduction in taxes. In many countries, in fact, the funding of State education has remained unchanged or even increased, leading to wider coverage and higher investment per student. As the countries continue to move through the demographic transition, the demographic dividend period comes to an end and the older adult population begins to grow more quickly than the working-age population. From that point onward, governments face decades of continuously increasing fiscal pressure caused by population ageing. The age profiles of public transfers can be used as a first approximation for assessing fiscal pressures by calculating the fiscal support ratio, which is the ratio of aggregate taxation to benefits. In the absence of assetbased government reallocations, such as loans and debt repayments, that ratio should be equal to 1, with total aggregate tax receipts equal to total aggregate benefits paid. As the population ages, the fiscal support ratio drops as the number of contributors falls in relation to the number of beneficiaries of public transfers. Changes in the fiscal support ratio indicate, in relative terms, the amount by which taxes should rise or benefits fall in order to return to the initial fiscal position. Table IV.2 shows changes in the fiscal support ratio over a period of 100 years (1950-2050) for a selected group of countries participating in the global National Transfer Accounts project. The estimates are based on the age profiles of public transfer flows observed in each country around 2005, applied to population estimates and projections by age from 1950 to 2050. The reference year is 2010, and countries are ranked in the table according to the size of the fiscal adjustment needed by 2050 as a result of population ageing. 182 Economic Commission for Latin America and the Caribbean (ECLAC) Table IV.2 COUNTRIES PARTICIPATING IN THE GLOBAL NATIONAL TRANSFER ACCOUNTS PROJECT: FISCAL SUPPORT RATIO, 1950-2050 Most favourable demographic period Fiscal support ratio Country 1950 2010 2020 2030 2050 Year Fiscal support ratio Brazil 1.00 1 0.94 0.86 0.69 2000 1.02 Chile 0.94 1 0.93 0.83 0.72 2004 1.01 Slovenia 1.01 1 0.91 0.81 0.72 2002 1.04 Spain 0.94 1 0.96 0.87 0.73 2010 1.00 Austria 1.08 1 0.93 0.83 0.74 1950 1.08 Japan 0.91 1 0.92 0.87 0.74 1976 1.15 Germany 1.11 1 0.94 0.84 0.75 1950 1.11 Costa Rica 0.89 1 0.97 0.91 0.76 2012 1.00 Hungary 1.06 1 0.97 0.93 0.77 1950 1.06 China 0.93 1 0.94 0.87 0.80 2007 1.00 Republic of Korea 0.76 1 0.97 0.89 0.80 2008 1.00 Finland 1.08 1 0.92 0.87 0.83 1991 1.11 Mexico 0.85 1 1.02 0.99 0.86 2019 1.02 Sweden 1.15 1 0.96 0.90 0.86 1950 1.15 United States 0.99 1 0.96 0.92 0.89 2006 1.00 Uruguay 1.08 1 1.00 0.98 0.90 1959 1.09 Thailand 0.66 1 1.04 1.04 1.04 2039 1.04 Indonesia 0.79 1 1.06 1.10 1.08 2033 1.10 Philippines 0.87 1 1.06 1.11 1.16 2050 1.16 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ronald Lee and Andrew Mason, “National Transfer Accounts Version 1.0”, Berkeley, Center for the Economics and Demography of Aging, University of California/ East-West Center, October 2010; Latin American and Caribbean Demographic Centre (CELADE) Population Division of ECLAC, population estimates and projections, 2008 and United Nations, World Population Prospects: The 2008 Revision, New York, 2008. Of the countries taking part in the global National Transfer Accounts project, Brazil is expected to feel the strongest fiscal impact associated with population ageing. In combination with the current tax and benefits policies, population ageing in Brazil will bring the fiscal support ratio down by 31% by 2050. This means a cut of 31% in benefit transfers by 2050 or a 45% increase in taxation, or a combination of both. Brazil is not alone in facing this situation of growing fiscal pressure. In Europe, the reduction in the fiscal support ratio by 2050 will vary between 14% in Sweden and 28% in Slovenia. In the other Latin American countries, the fall will range from 10% in Uruguay to 28% in Chile. In the United States, the fiscal support ratio is expected to be down 11% by 2050 (a little less than in Sweden and somewhat more than in Uruguay). In Asia, the three countries where the fiscal impacts are expected to be the most severe are Japan (with a 26% decline in the fiscal support ratio) and China and the Republic of Korea (with declines of about 20%). These figures demonstrate that population ageing is a worldwide phenomenon that is not restricted to the developed countries. Consequently, it should not come as a surprise that some of the most serious fiscal impacts of population ageing will be felt outside Europe. A major issue in several of those countries is that not only will the fiscal support ratio tend to decline rapidly in future, but also that this decline will represent a sharp departure from earlier decades, when the fiscal support ratio remained stable or even rose. This is true, for example, for Brazil, Chile, China, the Republic of Korea, Slovenia, Spain and the United States, which reached the stage of lowest fiscal pressure during the 2000s with rising fiscal pressure thereafter in response to demographic changes (see table IV.2). There is another group of countries where the fiscal support ratio will increase because under their current tax and expenditure policies, older persons are net contributors or their fiscal costs are only moderate. This is true for Indonesia, the Philippines and Thailand. The scale and direction of demographic effects on fiscal risks will depend on how public policies change in the future. Rather than relying on the fiscal support ratio, data from national transfer accounts can easily be combined with more realistic assumptions as to future changes in public benefits policies, in order to provide governments with medium- and long-term fiscal projections. Some Social Panorama of Latin America • 2010 projections prepared for Latin American countries (for example, Miller, Mason and Holz (2009), for 10 countries; Miller and Castanheira (2010), for Brazil) show that the fiscal impact of population ageing in the region will be similar to that for Europe. All these fiscal projections are based on assumptions regarding future public-policy changes. As fiscal pressures increase in countries where net public transfers by age are skewed upward, society can be expected to respond by seeking to reform pension and health-care programmes 183 and to increase investment in education, in order to foster economic growth and promote equality. In countries where public transfers to children currently predominate, as in the case of Indonesia and some Latin American countries which are not yet part of the global National Transfer Accounts project, population ageing together with changes in family structures may, in the future, necessitate public welfare programmes for older persons, reversing the age orientation of net public transfers and increasing the fiscal pressure on governments. C. Public transfers by age and educational level in Brazil and Chile A look at Brazil and Chile shows that public transfers towards older persons are proportionately higher and that family transfers are the principal component of transfers to children and young people. This bias is found at all socio-economic levels but is significantly more pronounced in the highest-level group. Overall, public spending on children exhibits greater absolute progressivity that diminishes with age and then turns regressive, with greater benefits for groups at higher socio-economic levels. Despite public-sector involvement, total investment in education is quite unequal among different socio-economic groups. This is due especially to enormous gaps in spending on education between high- and low-income families. 1. Public transfers and inequality In recent years, the role of government in allocating resources among population subgroups has been the focus of numerous empirical and theoretical analyses. In cases of market failure, government interventions are needed to ensure income equality and redistribution, to provide insurance against certain types of risk and to generate public goods. To a great extent, the multiple functions and goals of government are complementary. For example, policies to combat poverty can lead to improved distribution of income. Government actions, however, are subject to faulty information, and this may lead to unexpected adverse effects. Policymakers might also favour private interests that might not be consistent with public interest principles. To understand the role of government it is necessary to understand the incidence of public transfers in different population groups. As was seen at length in section B, the incidence of public transfers by age group is no longer unknown territory, thanks to recent research mainly associated with the National Transfer Accounts project. And researchers are increasingly interested in issues relating to income-linked public 184 transfers (for example, Barro and others, 2006; Breceda, Rigolini and Saavedra, 2009; Lindert, Skouflas and Shapiro, 2006). National Transfer Accounts provide answers regarding the fiscal effects of ageing and intergenerational equity but yield little information on differences between socio-economic groups and the effects of ageing on their well-being. As a result, CELADE-Population Division of ECLAC is working to expand the analytical framework of these accounts in order to measure resource flows, not only between age groups but also between socio-economic groups. This section presents the preliminary results of this exercise for Brazil and Chile. Latin America is an interesting context for identifying associations between intergenerational transfers, population ageing and social inequality that have not yet been fully explored. Compared with other emerging regions, Latin America has a relatively large public sector and a rapidly ageing population, combined with one of the world’s highest levels of inequality in income distribution. There has been much research on the causes of income inequality and poverty in Latin America. For example, in a thorough study on Brazil, Barro and others (2006) examine the reasons for the rapid reduction of inequality in recent years. The authors report that nearly half of the considerable change in the Gini coefficient between 2001 and 2004 (from 0.593 to 0.569) was due to improvements in social security programmes for the poorest (in particular, the launch of conditional cash transfer programmes) and to narrowing gaps in educational levels among workers. This suggests that, in the long term, greater investment in education to promote equal opportunities among workers as well as increasing the progressivity of public taxes and spending could have a positive effect on income distribution on an even more significant scale. In another study for Brazil, Wajnman and Turra (2010) use microsimulation modelling to analyse inequality over a much longer period (1983 to 2008). They believe that changes in the proportion of adults per household as a result of transitions in fertility and mortality, as well as changes in living arrangements, have contributed a good deal (around 22%) to improving income distribution over the period under consideration. Over those 25 years, demographic effects were not as important as the impacts of social policies geared towards income transfer, such as social security and, particularly, cash transfers targeting the poorest, such as the Bolsa Família programme. There are currently many studies in Brazil and other Latin American countries highlighting the importance of public transfers (particularly social security benefits) for poverty reduction in certain age groups. Many of these Economic Commission for Latin America and the Caribbean (ECLAC) studies use simple hypothetical analyses to compare poverty rates with and without public benefits. Turra, Marri and Wajnman (2008), using household data for 2005, show that the incidence of poverty among people aged 60 and over in Brazil would increase by some 4% to 64% in the case of men, and by 16% to 83% in the case of women, if pension income were not taken into account. Cotlear and Tornarolli (2009) compare poverty rates with and without pensions for two major age groups (60 and over, and under 15) for a number of Latin American countries. They report that Argentina, Brazil, Chile and Uruguay are the countries where pensions have the greatest impact on poverty among older persons. Public transfers have only a minor impact on poverty levels in Colombia, Mexico and Paraguay. The impacts tend to be greater in rural areas, where non-contributory pensions account for a major part of household income. In a more recent document, Turra and Rocha (2010) use an age-period-cohort model to distinguish effects associated with historical changes (cohort effects) and contemporaneous changes (period effects) on poverty rates among children and older persons in Brazil. The findings suggest that poverty reduction in these two dependent age groups happens in two different ways. Among older people, period effects predominate and are probably associated with the expansion of social benefits (public pensions), which is consistent with the National Transfer Accounts estimates presented above. As for children, the long-term effects related to gradual changes in the cohorts’ life trajectories (such as changes in parents’ educational levels and in the support relationship within the household) played a preponderant role during most of the observation period. This explains why poverty reduction has been slower among children. In the 2000s, period effects accelerated poverty reduction, coinciding with increases in the real minimum wage, and the development and expansion of the Bolsa Família programme. Ros (2009), in a broad study comparing 12 Latin American countries, uses cross-sectional data to estimate the relative contribution of changes in the demographic dependency ratio, income inequality, levels of public social spending and economic growth to the recent drops in poverty rates. The results show that, on average, reductions in the demographic dependency ratio have a much greater positive impact on poverty levels than other factors do. The declines in poverty (and consequently in income inequality) in smaller households (with low proportions of dependent children) are probably larger in the early stages of the demographic transition. In countries where the fertility rate has already fallen to low levels, there is little scope for additional direct impacts from Social Panorama of Latin America • 2010 the demographic transition. Unfortunately, Ros (2009) does not distinguish the effects of social spending and the other independent variables by age or cohort. The results of the analysis are therefore not comparable with those of other studies in that regard (for example, Turra and Rocha, 2010). Despite researchers’ growing interest in issues relating to public transfers by age and income level, few studies look at the role of intergenerational transfers relating to age and socio-economic level at the same time, although research in this area has been growing. Turra and Queiroz (2005), for example, analysed intergenerational transfer systems in Brazil by socioeconomic level, finding different patterns for public and private transfers in different subgroups defined by the educational level of the head of household. The analysis showed that consumption by children of higher socio-economic levels depends mainly on private transfers, whereas consumption by children at lower socio-economic levels depends more on public transfers, particularly in education. In contrast, it was public transfers, mainly social security and healthcare benefits, that contributed the most to funding consumption by older persons regardless of socioeconomic level. 2. Turra, Holz and Cotlear (2009) observed the incidence of public spending by five-year age groups and by income quintile on social sectors in Brazil and Chile. They found interesting patterns in absolute progressivity (social spending by socio-economic group) in both countries. Their findings show that public spending is neutral in the case of education, slightly progressive in the case of health care (more favourable to the low-income quintiles) and strongly regressive in the case of public pensions (favouring higher-income quintiles). This last shows that in Brazil and Chile there is a strong correlation between spending targeting older persons and spending targeting wealthy people, which is consistent with the idea that, although all older persons receive something from the public sector, there is still much inequality in the distribution of resources to that age group. The remainder of this section will discuss the incidence of public spending by age group and socioeconomic level in Brazil and Chile, assessing the results by sectoral composition (social security, education and health care). The analysis complements the existing literature by looking jointly at social spending and taxation and presenting a comparative analysis of two Latin American countries. Public transfers by age and educational level Section B grouped the population by age and examined the resource flows between age groups, using data from the National Transfer Accounts project. This section will extend the National Transfer Accounts methodology in order to estimate resource flows between socioeconomic groups, dividing the population by age and by the educational level of the head of household, in order to analyse transfers from the public sector among these groups.6 Household survey microdata are combined with administrative records to estimate per capita age profiles for public transfers at each socio-economic level (for an explanation of the methodology, see box IV.3). Unfortunately, such estimates in the National Transfer Accounts project are not yet more widely available, which is why the findings in this section are restricted to the cases of Brazil and Chile. 6 185 The educational categories were: (a) no formal schooling; (b) 1 to 8 years of schooling; (c) 9 to 15 years of schooling; and (d) 16 or more years of schooling. Figure IV.11 shows the distribution of the population of Brazil and Chile by age and level of education of the head of household. The major transformation that has occurred in these societies is evident. Around 30% of older persons in Brazil live in households where the head of household has no formal education. Among Brazilian children, however, this proportion is only 15%. In Chile, 60% of older persons live in households where the head of household has fewer than eight years of formal education, but only 35% of Chilean children live in such households. As population ageing progresses in these societies, the distribution of workers (and, eventually, of older persons) by level of education will shift markedly towards higher educational levels, with profound economic and social consequences. 186 Economic Commission for Latin America and the Caribbean (ECLAC) in households whose head has 16 years or more of schooling. This difference is greater still in Chile, with the first group consuming only a tenth of the amount consumed by individuals in households whose head has 16 or more years of formal education. These major differences persist throughout the life cycle, underscoring the impact of education on the opportunities available to people throughout their lives. Figure IV.11 POPULATION BY AGE GROUP AND years of schooling OF THE HEAD OF HOUSEHOLD (Percentages) A. Brazil, 2003 100 90 80 70 60 Figure IV.12 ANNUAL PER CAPITA CONSUMPTION BY AGE GROUP AND years of schooling OF THE HEAD OF HOUSEHOLD RELATIVE TO THE GROUP WITH THE HIGHEST LEVEL OF EDUCATION a (Percentages) A. Brazil, 2003 50 40 30 20 10 85+ 80-84 70-74 75-79 65-69 55-59 60-64 45-49 50-54 35-39 40-44 25-29 30-34 15-19 20-24 5-9 10-14 100 0-4 80 Age 70 B. Chile, 2006 100 90 60 50 90 40 80 30 70 20 60 40-44 45-49 50-54 55-59 60-64 65+ 40-44 45-49 50-54 55-59 60-64 65+ 35-39 30-34 25-29 15-19 20-24 30 10-14 0 40 5-9 10 50 0-4 0 Age 20 B. Chile, 2006 100 10 85+ 80-84 75-79 70-74 65-69 55-59 60-64 45-49 50-54 35-39 40-44 25-29 30-34 15-19 20-24 10-14 5-9 0-4 90 Less than 1 year 1 to 8 years 9 to 15 years 80 70 Age 16 years or more 60 50 Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the E basis of data from the Brazilian National Household Survey (PNAD), 2003, in the case of Brazil, and from the National Socio-economic Survey (CASEN) 2006, in the case of Chile. 40 30 20 35-39 30-34 25-29 15-19 20-24 10-14 5-9 0 0-4 10 While inequality in these societies has been well documented using measurements such as poverty rates and income levels, data from National Transfer Accounts can show inequality in per capita consumption throughout the life cycle. Figure IV.12 shows annual per capita consumption by age and by the level of education of the head of household in Brazil and Chile, in relation to consumption by the group with the highest educational level (those with 16 or more years of schooling). In both countries, those living in households headed by a person with nine to 15 years’ schooling consume, on average, less than half (40% to 50%) of what is consumed by members of households where the head of household has at least 16 years’ schooling. The differences are sharper still at lower educational levels. In Brazil, those living in households whose head has no formal education consume a fifth of what is consumed by those living Age Less than 1 year 1 to 8 years 9 to 15 years 16 years or more Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the Family Budgets Survey (POF), 2006/2007, in the case of Brazil, and the Budgeting and Expenditure Survey (EPG), 2006/2007, in the case of Chile. a Per capita private consumption includes consumption in the areas of health care, education, durables and others. Understanding the role of public transfers in this unequal pattern of consumption during the life cycle requires examination of the benefits received and the taxes paid by age and educational level. The analysis begins by looking at the absolute incidence of public spending by age and educational level. The results for Brazil and Chile are shown in figure IV.13. As discussed in section B, public transfers for older persons are substantial in both countries, and especially in Brazil. Social Panorama of Latin America • 2010 187 In the four educational groups considered, older persons receive the highest benefits. For example, at the lowest educational level, the per capita benefits in the 80-84 age group in Brazil are five times higher than in the 10-14 age group. This bias towards public spending targeting older persons is significantly greater for the group with the highest education level, where per capita benefits in the 80-84 age group are 45 times higher than in the 10-14 age group. The results for Chile show that in the group with the lowest level of education, the ratio is three times more benefits for older persons than for young people. As in Brazil, the difference tends to increase along with socio-economic level and is 15 times larger for the group with the highest level of education. Figure IV.13 PER CAPITA PUBLIC SOCIAL BENEFITS BY AGE GROUP AND Years of schooling OF THE HEAD OF HOUSEHOLD a A. Brazil, 2003 Figure IV.14 PER CAPITA PUBLIC SOCIAL BENEFITS BY AGE GROUP AND Years of schooling OF THE HEAD OF HOUSEHOLD, RELATIVE TO PER CAPITA BENEFITS RECEIVED BY THE GROUP WITH THE HIGHEST LEVEL OF EDUCATION a (thousands of reais) 40 for children. In Brazil, per capita public spending on children in the lowest-educated group is 3.5 to 4.5 times higher than for children in the highest-educated group. In Chile the gap is narrower but still considerable, ranging from 1.5 to 2.4 times. With rising educational levels, absolute progressivity diminishes and public spending eventually becomes regressive, with higher benefits for the groups with the most years of schooling. In Brazil, the turning point where spending becomes regressive is at age 45. In the 80-84 age group, benefits in comparison with the group with the highest educational level stand at 0.26 for the lowest-educated group and around 0.6 for the second-highest group. The turning point occurs somewhat later in Chile, in the 50-54 age group, and public spending on older persons is generally less regressive than in Brazil. The ratios in Chile are between 0.42 and 0.71 in the 80-84 age group. 35 30 25 A. Brazil, 2003 20 10.0 15 10 60-64 70-74 80-84 60-64 70-74 80-84 50-54 40-44 30-34 20-24 1.0 10-14 Age 0-4 80-84 70-74 60-64 50-54 40-44 30-34 20-24 10-14 0 0-4 5 B. Chile, 2006 (millions of pesos) 7 6 0.1 5 Age 4 B. Chile, 2006 3 10.0 2 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the Brazilian National Household Survey (PNAD), 2003, in the case of Brazil, and the Household Quality of Life Survey, 2006, in the case of Chile. a Per capita public social benefits include public spending on education, health care and pensions. The same data show how spending on each age group is distributed according to educational levels. Figure IV.14 shows per capita public spending by age and educational group in relation to the highest-educated group. In both countries, absolute progressivity is greater 0.1 50-54 40-44 1.0 16 years or more 30-34 9 to 15 years 20-24 1 to 8 years 10-14 Age Less than 1 year 0-4 80-84 70-74 60-64 50-54 40-44 30-34 20-24 10-14 0 0-4 1 Age Less than 1 year 1 to 8 years 9 to 15 years Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the Brazilian National Household Survey (PNAD), 2003, in the case of Brazil, and the National Socio-economic Survey (CASEN) 2006, in the case of Chile. Note: Per capita public social benefits include public spending on education, health care and pensions. Figure IV.15 PER CAPITA PUBLIC EDUCATION BENEFITS BY AGE GROUP AND years of schooling OF THE HEAD OF HOUSEHOLD, RELATIVE TO PER CAPITA BENEFITS RECEIVED BY THE GROUP WITH THE HIGHEST LEVEL OF EDUCATION a A. Brazil, 2003 30-34 35-39 35-39 25-29 20-24 30-34 0.1 15-19 10-14 1.0 5-9 10.0 0-4 Age B. Chile, 2006 25-29 20-24 15-19 1.0 10-14 10.0 5-9 For the life cycle as a whole, the educational levels attained during childhood and youth clearly help determine the share of public spending received later in life. It is not only a matter of regressive distribution of university education in the corresponding age group; this regressivity is more strongly reflected later in the life cycle, especially because the attainment of higher educational levels by young people will lead to greater access to social security during their working lives and thus to higher returns from social security when they are older. Chapter III showed the high incidence of social security in public social spending, which means greater resources not only for older persons but also for those who received more education when younger. Chapter II showed the strong correlation between household socio-economic level and children’s educational achievement level. Thus, there is a vicious circle of inequality throughout the life cycle, since the poorer children and young people will receive less education, will obtain less well-paid and more informal employment, and will receive a lower proportion of social security benefits later in life. What explains these differences? In order to form a fuller picture, public transfers received by each educational and age group were broken down into three areas: education, health care and social security. Figure IV.15 shows per capita public education benefits by age and educational group in relation to the highest-educated group. In the 5-14 age group in Brazil, individuals at the lowest educational level receive 2.5 to 4 times more public education transfers than those in the highest educational level; this pattern has already been described (see Turra and Queiroz, 2005). There is a turning point in the 15-19 age group, where the incidence of per capita public spending in the richest group becomes higher. The pattern in Chile is very similar. The reason for this pattern is that children from the lowest socio-economic level generally depend on publicly-funded education at the primary and secondary levels, whereas children from the higher socio-economic levels usually attend private primary and secondary schools. Levels of investment in education for these children are considerably higher at early stages of the life cycle. It is therefore unsurprising that these children are much more likely to attend publicly-funded universities, which select their students on the basis of competitive examinations. Governments invest heavily in public universities. In Brazil, for example, public spending per student at the university level is 14 times higher than at the primary education level. Economic Commission for Latin America and the Caribbean (ECLAC) 0-4 188 0.1 Age Less than 1 year 1 to 8 years 9 to 15 years 16 years or more Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the Brazilian National Household Survey (PNAD), 2003, in the case of Brazil, and the National Socio-economic Survey (CASEN) 2006, in the case of Chile. a Per capita public education benefits include public spending on preschool, primary, secondary and tertiary education. Despite strong public-sector participation in education, there are wide differences in education investment (public and private) between the different educational groups. Figure IV.16 shows total per capita spending on education in Brazil and Chile for the four educational groups. In both countries, the amount invested in the education of a child in the highest socio-economic group is, on average, more than twice that invested in a child from the secondhighest socio-economic group —and more than triple that invested in a child from the lower socio-economic groups. These major differences in education investment are probably an important factor in lifelong inequality for these children, perpetuating the high levels of inequality observed in these societies. Social Panorama of Latin America • 2010 189 Figure IV.16 TOTAL PER CAPITA EDUCATION SPENDING, BY AGE GROUP AND years of schooling OF THE HEAD OF HOUSEHOLD a A. Brazil, 2003 (reais at 2003 prices) 80 000 100 70 000 60 000 50 000 40 000 30 000 46 32 32 Less than 1 year 1 to 8 years Figure IV.17 PER CAPITA PUBLIC HEALTH-CARE BENEFITS BY AGE GROUP AND years of schooling OF THE HEAD OF HOUSEHOLD, RELATIVE TO PER CAPITA BENEFITS RECEIVED BY THE GROUP WITH THE HIGHEST LEVEL OF EDUCATION a 20 000 10 000 0 when working with these estimates because they do not break down costs according to the type of health care. People in the groups with the most education tend to demand more expensive treatments in the public healthcare sector than those in the lowest education group, so the system may be less progressive than the observations seem to indicate. The public health-care system in Chile appears less progressive than that of Brazil. In fact, in the highest age groups (85 and over), those from the group with the highest level of education receive more in public health-care benefits than any other group. 9 to 15 years 16 years or more A. Brazil, 2003 10.0 B. Chile, 2006 (pesos at 2007 prices) 35 000 000 100 70-74 75-79 80-84 85+ 75-79 80-84 85+ 65-69 65-69 70-74 55-59 60-64 55-59 60-64 45-49 50-54 35-39 40-44 25-29 20 000 000 30-34 15-19 20-24 5-9 10-14 1.0 25 000 000 0-4 30 000 000 48 15 000 000 34 33 10 000 000 0.1 Age 5 000 000 0 16 years or more B. Chile, 2006 10.0 As for the progressivity of public spending on health care, the conclusions are different (see figure IV.17). While in public education there is a clear tipping point towards a more regressive system during adulthood, spending on the public health-care system is progressive at almost all ages. In Brazil, children and older persons in the group with the lowest educational level mostly depend on the public health-care system and the per capita benefits are always higher for the groups with the lowest educational level. Some caution is needed 0.1 45-49 50-54 35-39 40-44 25-29 30-34 1.0 15-19 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the Brazilian National Household Survey (PNAD), 2003 and Family Budgets Survey (POF), 2006/2007, in the case of Brazil, and the National Socio-economic Survey (CASEN) 2006, in the case of Chile. a Total per capita education spending includes public and private spending on preschool, primary, secondary and tertiary education. 20-24 Public 10-14 Private 9 to 15 years 5-9 1 to 8 years 0-4 Less than 1 year Age Less than 1 year 1 to 8 years 9 to 15 years 16 years or more Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the Brazilian National Household Survey (PNAD), 2003, in the case of Brazil, and the National Socio-economic Survey (CASEN) 2006, in the case of Chile. a Per capita health-care benefits include public spending on hospital and non-hospital health services. 190 Economic Commission for Latin America and the Caribbean (ECLAC) Lastly, figure IV.18 contrasts per capita public spending on social security among the various education groups. The generosity of the pay-go pension scheme in Brazil, particularly for to the highest education groups, is the reason why public transfers are higher not only among the older people but also among the richest. These differences may be due to higher labour income during people’s working lives (a determining factor for benefits) among those with higher educational levels, in addition to the high proportion of public-sector professionals who belong to this group (and who therefore enjoy an income replacement rate close to 100%). Social security benefits for older persons are also regressive in Chile, although less markedly so than in Brazil. With time, public pensions are expected to decrease significantly for the highest education group, as workers in this group retire under the new pension system of State-mandated private retirement accounts. Pension benefits are more progressive among younger people (aged under 50), particularly in Chile. This is probably due to a higher level of non-contributory benefits received by groups having lower educational levels. Figure IV.18 PER CAPITA PUBLIC PENSION BENEFITS BY AGE GROUP AND years of schooling OF THE HEAD OF HOUSEHOLD, RELATIVE TO PER CAPITA BENEFITS RECEIVED BY THE GROUP WITH THE HIGHEST LEVEL OF EDUCATION a A. Brazil, 2003 B. Chile, 2006 0,1 0,1 Age Less than 1 year 1 to 8 years 9 to 15 years 85+ 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 85+ 80-84 75-79 70-74 65-69 60-64 55-59 50-54 45-49 1,0 40-44 1,0 35-39 10,0 30-34 10,0 Age 16 years or more Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the Brazilian National Household Survey (PNAD), 2003, in the case of Brazil, and the National Socio-economic Survey (CASEN) 2006, in the case of Chile. a Per capita public spending on pensions includes contributory and non-contributory pensions from all public-sector institutions (including the armed forces). 3. Net public transfers and taxation The following analysis focuses on tax incidence: in particular, the capacity of each age group and socio-economic group to contribute to total government tax receipts. Although the relative capacity to pay taxes is generally measured in relation to income, this analysis will estimate taxes in relation to private consumption, which offers a better measurement of capacity at ages when income is close to zero, such as during childhood. Figure IV.19 shows that there are no great differences in rates of taxation (as a percentage of private consumption) by socio-economic level up to age 19. This is because most taxes paid at that age are taxes on consumption. Among older persons the rate of taxation drops sharply in all educational groups in both countries, contrasting with increases in social spending on those age groups. The strong net fiscal impact of older persons is therefore the product of rising public benefits and falling rates of taxation. In Brazil and Chile, adults pay the majority of taxes. Among adults, groups with high educational levels pay significantly higher taxes than those with low educational levels; this is mostly due to taxes on labour income and on capital. In the 60-64 age group, the category with the highest educational level in Brazil pays, in relative terms, three times more than the group with the lowest level. There are also marked differences in Chile, although they appear to be smaller for intermediate educational groups owing to the low relative weight of income taxes as a proportion of the total taxes that they pay. Social Panorama of Latin America • 2010 191 Figure IV.19 RATE OF TAXATION: per capita taxes relative to per capita consumption a (Percentages) A. Brazil, 2003 180 160 140 120 100 80 levels continues in the two countries, the distribution of the working-age population will tend towards higher educational levels, and the same will occur in relation to the population of older persons as new, better-educated cohorts grow older. The fiscal impact of this change is clearly apparent in the data. If the current structure of taxes and benefits remains, the educational change in the working-age population will tend to boost tax receipts; the educational change in the highest age groups will tend to increase the payout of social benefits. 60 Figure IV.20 PER CAPITA NET PUBLIC TRANSFERS BY AGE GROUP AND Years of schooling OF THE HEAD OF HOUSEHOLD a 40 20 0 0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 A. Brazil, 2003 80-84 Age (reais at 2003 prices) 35 000 B. Chile, 2006 30 000 120 25 000 100 20 000 15 000 80 10 000 60 5 000 40 -5 000 0 -10 000 20 -15 000 0-4 10-14 0 0-4 10-14 20-24 30-34 40-44 50-54 60-64 70-74 20-24 1 to 8 years 9 to 15 years 16 years or more Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the Brazilian National Household Survey (PNAD), 2003 and Family Budgets Survey (POF), 2006/2007, in the case of Brazil, and the National Socio-economic Survey (CASEN) 2006 and Budgeting and Expenditure Survey (EPG), 2006/2007, in the case of Chile. a Total taxation includes taxes on income, capital and consumption. The rate of taxation is the result of dividing total per capita taxes by pewr capita consumption for each age group. 40-44 50-54 60-64 70-74 80-84 60-64 70-74 80-84 B. Chile, 2006 Age Less than 1 year 30-34 Age 80-84 (pesos at 2006 prices) 6 000 000 4 000 000 2 000 000 0 -2 000 000 To show the fiscal impact on the various socioeconomic groups, figure IV.20 compares net transfers (public benefits received minus taxes paid), by age group and level of education of the head of household. In both countries, the group with the lowest level of education is a net recipient of public transfers at all ages; that is, it receives more in benefits than it pays in taxes. Social spending in both countries is funded by of working-age adults in the highest educational groups, through their net tax payments. As the transition towards higher educational -4 000 000 -6 000 000 0-4 10-14 20-24 30-34 40-44 50-54 Age Less than 1 year 1 to 8 years 9 to 15 years 16 years or more Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the Brazilian National Household Survey (PNAD), 2003 and Family Budgets Survey (POF), 2006/2007, in the case of Brazil, and the National Socio-economic Survey (CASEN) 2006 and Budgeting and Expenditure Survey (EPG) 2006/2007, in the case of Chile. a Per capita net public transfers are calculated as the difference between benefits received from the State and taxes paid. 192 Economic Commission for Latin America and the Caribbean (ECLAC) D. Conclusions The international review of the generational economy presented in the foregoing sections has identified a number of particular characteristics of the economies of Latin America. One of the most notable concerns the low levels of consumption among children and young people associated with low levels of public investment in these population groups. The analysis showed that in the highest-income economies the State plays a fundamental part in providing support to children and young people and that public transfers make up almost half of consumption by these age groups. Support is provided mostly in the form of publicly-funded education. Naturally, this may not be the only possible route to the high investment levels needed in modern economies. In many Asian countries, education is mainly funded by families, with relatively low levels of State participation. This route to development, however, appears to be open only to economies with low levels of income inequality, where a sizeable middle class has the means to pay for quality education for its children. In the case of Latin America, the high levels of inequality that still persist in these societies call for strong State involvement to provide the necessary investment for the development of young people. That investment, as mentioned earlier in this document, should take account not only of aspects related to formal education, but also the full spectrum of the development of children and young people, including investment in families in order to provide a favourable environment for development. Investment in education can help reduce inequality and can also help prepare for rapid population ageing, which is imminent. In a recent study, Lee and Mason (2009) found that investments in education can compensate for the negative economic effects of population ageing. It seems clear that the current inaction of the governments of the region will have considerable long-term consequences when they are faced with growing fiscal and economic pressure resulting from population ageing in a context of considerable social inequality. National transfer accounts are a particularly useful instrument for contributing to public policy discussions and increasing governments’ capacity to take action, providing a comprehensive and consistent measurement of the considerable and increasingly vital role of governments in the provision of financial support to young people and older persons. They also enable governments to monitor the impact of their policies and evaluate the effects of all taxation and public expenditure programmes. National transfer accounts also provide governments with a comprehensive view of the functions of other economic agents (the financial market, the family, civil society) in providing support to young people and older persons. The fact that the National Transfer Accounts project involves a diverse group of countries provides space for an international exchange of experience, for example, in terms of public policies and their impact on the well-being of young people and older persons. National transfer accounts are also a flexible tool that can encompass other key social dimensions in addition to age. This is true, for example, of the methodology which is being developed for measuring the generational economy by socio-economic levels. Section C of this chapter showed the usefulness of this approach in the case of Brazil and Chile. The levels of inequality present in those two economies are well known, but National Transfer Accounts show that reality in a new light, underlining the major differences in terms of consumption and investment in the education of young people, as well as the long-term consequences of low investment in education. Social Panorama of Latin America • 2010 193 Box IV.3 Methodological notes on estimating national transfer accounts by age group and socio-economic level Socio-economic levels for individuals are measured by the level of education of the head of household. This measurement is strongly correlated with the household’s overall socio-economic level, and is preferred to other indicators (such as income or wealth) because it provides better comparability between age groups. Levels of education are classified into four categories: no formal education, 1 to 8 years’ education, 9 to 15 years’ education and 16 or more years of education. Since a relatively high number of observations are needed to avoid stochastic errors in the estimates, economic flows are calculated by five-year age groups. In the case of Brazil, household surveys are used: the Brazilian National Household Survey (PNAD) for 2003 and the Family Budgets Survey (POF) for 2002-2003. PNAD has been applied every year in Brazil (except in census years) since the late 1970s; it contains a broad and comparable set of demographic and economic variables. In 2003, 384,834 people in 133,255 households were interviewed for PNAD. The sample is representative of the population at the national level, except for the population of rural areas in the country’s northern states. POF is a household budget survey conducted in 1987-1988, 1995-1996, 2002-2003 and then in 2008-2009. The 2002-2003 POF comprises data from a representative sample of the total population comprising 48,470 households interviewed over a period of 12 months. In the case of Chile, data from two household surveys are combined: the National Socio-economic Survey (CASEN) 2007 and the Budgeting and Expenditure Survey (EPG) 2006/2007. CASEN is a nationwide representative survey which has been conducted every two years since 1985. It includes a complete set of socio-economic variables and is used for producing estimates of poverty and inequality in Chile. The sample for 2007 comprised 268,673 persons in 73.720 households. EPG is a household budget survey conducted in the principal regional capitals in Chile; it has been conducted every 10 years since 1987. In addition to the household survey data, administrative information is used for both countries, yielding aggregate values for total taxation and public spending on health care, education and social security. Public health-care spending is allocated on the basis of usage rates by age group and socio-economic level from PNAD (Brazil) and CASEN (Chile). PNAD reflects individual persons who report having made use of hospital and non-hospital medical services provided by the public sector during the reference period. It is assumed that the users generate the same per capita cost within each type of health care. Administrative information from the Ministry of Health is therefore used to determine total public spending in these two broad categories. In Chile, rates of use are estimated by type of care (for example, hospitalization or surgery) and by financial modality (without payment or with co-payment). Then the average cost is assigned to each type of care, using administrative data. Public spending on education in Brazil and Chile is estimated on the basis of enrolment rates by age group and socioeconomic level for children and adults who report, in PNAD and CASEN, that they are enrolled in publicly-funded schools. To allocate spending in accordance with administrative data, the calculation takes into account variations in the cost per student by level of education and the distribution of students between the levels. Pension profiles by age group and socio-economic level are estimated on the basis of data from PNAD and CASEN, in relation to amounts received in the form of benefits during the reference period. Unfortunately, in neither country is it possible to distinguish between types of benefits (for example, survivor’s and old age benefits), or between social security systems (such as general pension systems and systems for public employees). To control for discrepancies between the weighted amount of benefits and the actual cost of these programmes, the data are adjusted to reproduce the official aggregate values. Estimating taxation profiles by age group and socio-economic level involves several steps. First, taxes are classified in accordance with the category to which they refer. Then, for Brazil, it is assumed that (i) taxes on wages and income are applied to taxable labour income, and they are estimated by applying the 2003 rate to the information on labour income (PNAD); (ii) taxes on gains are on capital income, estimated using data on owners of assets (POF); (iii) taxes on production and consumption are on private consumption, estimated using individual and household-level data on private consumption (POF); (iv) property taxes are on taxable property estimated on the basis of information on vehicle and dwelling ownership (POF); and (v) other taxes are on taxable labour income. Social security contributions are estimated directly from PNAD. The method for Chile is basically the same, although some changes were made to capture specific characteristics of the Chilean taxation system and the availability of data. It is therefore assumed that (i) capital taxes refer to a combination of information from entrepreneurs and owners of assets (CASEN); (ii) other taxes on production are on labour and capital income estimated on the basis of survey data (CASEN); (iii) local taxes are estimated on the basis of information from entrepreneurs and the owners of assets, such as real estate (CASEN); (iv) taxes on consumption are estimated using individual and household-level information on private consumption (EPG); and (v) taxes on wages, pensions and social contributions apply to formal workers and recipients of public social security. On the basis of the classifications described above, and using aggregate values from administrative data, taxation profiles by age group and socio-economic group were adjusted to the official aggregate for each type of tax. Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of information from national transfer accounts studies. 194 Lastly, national transfer accounts provide a basis for governments’ long-term fiscal projections. Generally speaking, these projections anticipate the significant economic changes which will be brought about by the slow but inexorable advance of various social forces, such as population ageing, the epidemiological transition or changes in educational levels.7 Long-term projections are important for governments for at least two key reasons. First, policy options with greater rates of return (such as investment in public education) tend to take a relatively long time between implementing 7 The epidemiological transition is a change, largely caused by population ageing, where acute illnesses, more common among children, give way to chronic and degenerative diseases, more common among older persons, as main causes of morbidity and mortality. For further details, see ECLAC/CELADE (2010). Economic Commission for Latin America and the Caribbean (ECLAC) the policy and obtaining the results. Approaches essentially based on short-term policies are more at risk from mistaken or less effective decision-making, which generally fails to take account of the full scope of longer-term investments such as those designed to increase skills development. Second, a long-term approach fosters marginal changes and corrections in policy that are politically more feasible to implement. These avoid imposing an unfair burden on any particular generation and enable smooth fiscal and public-spending policy transitions. Social Panorama of Latin America • 2010 195 Chapter V Public transfers early in the life cycle: a major challenge in the effort to combat inequality across time A. Social deficits associated with life-cycle stages Poverty in Latin America is highly concentrated in the early stages of life. The large share of family spending that goes on child and youth development and the low share of public transfers to these generations combine with stratified educational attainments and learning to foster the intergenerational reproduction of inequality and social vulnerability. Three types of measures are proposed to address this: cash transfers to households with children aged 0 to 14 to improve the environment for child socialization (nutrition, housing, clothing); funding to cover the ongoing costs of extending the education and care system to uncovered 0- to 17-year-olds; and a range of cash transfers combined with employment and training services targeting vulnerable young people who are on their way to becoming emancipated adults (15 to 24 years of age). If progress is to be made with the equality agenda, it is essential for the State to lead the way in several areas. As noted earlier in this document, it basically falls to the State to decouple children’s and young people’s educational attainments and learning from their socio-economic background and to foster greater convergence of these attainments throughout society. The State must also seek to close labour market gaps and reduce vulnerability to various risks through active employment and wage policies and by means of clearly redistributive public transfers throughout the life cycle. 196 Economic Commission for Latin America and the Caribbean (ECLAC) The welfare State model shows that universal, non-market-based policies achieve the greatest systemic impact in terms of progressive redistribution of opportunities and assets and of access to well-being. This can also include selective transfers to more vulnerable groups, where the guiding principle is not targeting but precisely the development of more egalitarian conditions in society as a whole.1 This chapter presents options for public transfers to vulnerable sectors during childhood and youth and provides cost estimates for the universalization of education coverage, based on evidence given in preceding chapters. In Latin America, States and the transfers they make have little influence on the consumption structures of families with children and adolescents. As seen in chapter IV, which discusses generational balances and transfers, the consumption needs of 0- to 19-year-olds in countries such as Finland, Hungary, Japan and Norway are met almost equally by family transfers and State transfers. In countries like Germany and Spain, 35% to 40% of this age group’s consumption needs are met by the State. By contrast, in Latin America (for those countries on which data are available) the average is no more than 20%. Indeed, in all the Latin American countries reviewed, more than 70% of consumption by people in this age group (including types of consumption that are vital to the development of capabilities, such as nutrition, health care and education) is provided for by their families or their own labour. These transfers are therefore patterned on the unequal structure of primary family income or on the earnings of children and young people who work. It should thus come as no surprise that inequality persists despite public transfers targeting families with children and young people. This constraint is compounded by education systems, which absorb a large share of the public transfers targeting the youngest population segment, but are ineffective in reversing underlying structures of inequality. In short, the region faces enormous challenges in the effort to harness the redistributive role of the State and its capacity to combat inequality over time. Table V.1 LATIN AMERICA: MEASURES PROPOSED TO COMBAT INEQUALITY EARLY IN THE LIFE CYCLE Life-cycle stage Problem to be addressed or prevented Type of transfer Early childhood (ages 0 to 4 or 5) Inequities strongly determined early in life, inability of households to provide certain basic resources such as nutrition, early cognitive development and psychosocial development. Cash transfers to vulnerable households equivalent to 1 poverty line per child aged 0 to 4 and 1.5 poverty lines in the case of singleparent households. Investment in the care and education systems equivalent to the current monthly operating cost at the level concerned, times the number of children at the official age for that cycle who are not attending. Cash transfers to vulnerable households equivalent to 0.5 poverty lines per child aged 5 to 14 and 0.75 poverty lines for single-parent households. Intermediate stage (ages 4 or 5 to 14) Persistence and entrenchment of inequality, regressive distribution of learning and attainment. Investment in the education system equivalent to the current monthly operating cost at the level concerned, times the number of children at the official age for that cycle who are not attending school, to cover the cost of incorporating non-attending children. Although no estimate is provided, these costs should vary (increase) by educational attainment equalization goal (repetition, timely completion, learning, digital literacy). Should be accompanied by heavy investment in primary and lower secondary education (starting with the former) to extend full school day coverage. Start of emancipation (ages 15 to 29) Incomplete, low-quality emancipation process, crystallization of the tendency towards exclusion and intergenerational transmission. Source: Economic Commission for Latin America and the Caribbean (ECLAC). 1 ECLAC (2009), Filgueira (2007 and 2009), Filgueira, Papadópulos and Tobar (2005) and Kaztman (1999) discuss the role of the State in providing certain basic goods outside the market and offer descriptions of welfare regimes in Latin America. Cash transfers to individuals in vulnerable households equivalent to the current monthly cost of upper secondary education. These transfers should operate as an incentive subsidy for institutional reaffiliation in education or vocational training (estimated for the population aged 15 to 24). Social Panorama of Latin America • 2010 Given this situation, the countries should at least reflect on the advisability of implementing measures to address the predicament of the younger generations and their inadequate share of State transfers geared towards maintaining basic standards of well-being regardless of market status or family affiliation. Right from birth, a significant proportion of children in vulnerable households are set upon a life path that is very likely to reproduce their social status of origin and transmit it to ensuing generations. This idea is supported by the existence of three segmentation dynamics operating throughout childhood and youth that have been examined in preceding chapters and will now be summarized. (i) Firstly, while progress has been made, the multidimensional methodology for measuring poverty shows that as of around 2007, 17.9% of children in Latin America were living in extreme poverty and 45% in total poverty (with less severe deprivations). In six countries of the region, between about a third and half of all children lived in extreme poverty (at least one severe deprivation). Only in four countries was the figure below 10%. Poverty means that children’s socialization has to take place in households with multiple deficiencies, at the very ages when they depend most on family resources. Because the market is the only mechanism available for obtaining needed resources, but is inaccessible to families, these resources must be secured either by redistributing income via transfers to these households that enable them to access market services, or by the State providing benefits and services directly. (ii) Secondly, chapter II of this publication shows that education systems in the region’s countries have not established themselves as powerful mechanisms for the equalization of opportunities. The very advances made with coverage, access and progression through cycles of education over the past few decades have gone together with greater stratification of learning and attainment by the socio-economic, ethnic and territorial (rural versus urban, and urban segregation) status of pupils’ households of origin. Chapter II showed that in addition to tremendous gaps in attainment between countries, there are striking inequalities between groups of children and young people within each country in terms of access to early childhood education (which is vital for early stimulation and preparation for subsequent cycles), the rate of progression through primary and secondary education, completion of the secondary cycle, access to post-secondary education and the quality of education available. 197 The following considerations concerning age subgroups are germane to the approach taken to education in the present chapter. To date, access to early childhood care and stimulation has generally been via private spending and the market. This limits the options of the vulnerable population at a key stage of development in terms of nutrition, psychomotor skills, protection and cognitive development. Virtually universal coverage at the primary school level is good news for the region, but the system is not addressing inequalities accumulated during the preschool stage or the socio-economic and educational conditions of children’s households of origin. This means that a high percentage of children from this age group in vulnerable sectors suffer from educational underperformance and low learning attainment and have no access to the language of ICT, making their progress through the system little more than a formality in some cases (Kaztman, 2010). So, while broadening coverage is a prerequisite for dealing with these issues, it must be accompanied by measures such as lengthening the school day and achieving greater quality convergence between private and publicly funded education. Segregation and segmentation increase throughout secondary education. Completing secondary education is a vital gateway to greater employment opportunities that enable individuals to break free of poverty and exclusion and achieve upward social mobility. Moreover, this cycle is important because it is where the first steps towards emancipation are taken. Staying in the education system during this stage thus helps to keep young people from making a premature and unsatisfactory transition to autonomy. (iii) Thirdly, chapter I showed that the paths to emancipation and adulthood vary significantly between young people from different socio-economic strata. Premature and ill-prepared emancipation is common in low socioeconomic strata, whereas the socialization patterns of higher strata and the availability of material resources there favour the postponement of labour market entry, family formation and parenthood. Furthermore, the proportion of young people who are neither in school nor working is far higher in the lower socio-economic strata, with the resulting risks of social exclusion. For this group, the challenge is to create mechanisms that can reverse situations of disaffiliation through training or work. Taken together, these points highlight the need to address a sequence of asset accumulation shortfalls that originate early in life (early childhood and the preschool cycle), structuring different attainment trajectories and 198 Economic Commission for Latin America and the Caribbean (ECLAC) routes out of primary and secondary education and crystallizing and intensifying with emancipation and adulthood (end of the education cycle, emancipation from the household of origin, first job, family formation and reproduction). These incipient exclusion circuits thus need to be “switched off” in order to pre-empt irreversible processes of disaffiliation and marginalization that so starkly perpetuate the intergenerational reproduction of inequalities. To be consistent with the generational, life-cycle character of these issues, measures to address them must also be tailored to the different stages in life. That is what this chapter proposes.2 This set of measures would comprise the following: (i) Cash transfers equivalent to one poverty line for children aged 0 to 4, half a poverty line for children aged 5 to 14 and the equivalent of one month’s current upper secondary expenditure for young people aged 15 to 24 who are neither in school nor working.3 (ii) A budgetary top-up at each educational level equivalent to current spending at that level for each child or young person of the official age for that cycle who is not attending school.4 The following sections of this chapter assess the cost and impact of these measures.5 B. Poverty, inequality and cash transfers: costs and impacts Activating and completing the proposed transfers involves varying levels of financial effort for the countries. In one group of countries, the costs are affordable at around 2% of GDP. For another they represent approximately 5% of GDP, while the third group would have to cope with a far higher fiscal burden necessitating a more gradual approach and additional sources of funding. This transfer regime would bring the poverty rate down by nearly 10 percentage points in Argentina, Brazil, Chile, Costa Rica and Uruguay, by nearly 30% in Nicaragua and by 25% in Guatemala. This means that in some countries poverty would fall to some two thirds of its current rate. Poverty would be nearly halved in countries with the highest poverty rates at present. 1. Costing the measures The simplest way to express gaps in well-being within countries is to start with the monetary gaps for poverty and indigence and the aggregate amounts that would be required to remedy them, as proportions of current GDP, if they could be allocated perfectly to households below the poverty and indigence lines. This calculation cannot be used to break down the factors affecting the well-being gap (demography, distribution, employment and social spending), but it does provide an approximate absolute value for the 2 Risks associated with issues of sanitation and access to preventive and curative health care at different stages of the life cycle are not discussed in this chapter and are not among the subjects addressed in this issue of the Social Panorama. population deemed to be poor and extremely poor. It also shows the magnitude of the additional expenditure that, if perfectly allocated to the relevant households, would be needed to eliminate these gaps. 3 4 5 Although the baseline age group for the emancipation stage is 15 to 29, it was thought best to base the estimates on a modal group of the most disadvantaged socio-economic strata in the 15 to 24 age range. In this case, the amount allocated should be adjusted to reflect the level completed by the non-attending child or young person. For example, the cost calculated for a non-attending young person aged 15 to 17 will be equivalent to the monthly operating cost at the upper secondary level. Nonetheless, this young person might not have completed the lower secondary cycle. See ECLAC (2010a) for a direct precursor of this exercise. Social Panorama of Latin America • 2010 199 Table V.2 LATIN AMERICA (18 COUNTRIES): POVERTY AND INDIGENCE GAPS Indigence Country Chile Uruguay Argentina Costa Rica Mexico Brazil Peru Panama Venezuela (Bolivarian Republic of) Ecuador Colombia El Salvador Dominican Republic Paraguay Guatemala Bolivia (Plurinational State of) Nicaragua Honduras Year of measurement Gap per person (in local currency) Total annualized amount (millions of current dollars) 2006 2008 2006 2008 2008 2008 2008 2008 2008 2008 2005 2004 2008 2008 2006 2007 2005 2007 8 054.2 413.7 52.5 10 855.2 228.5 41.9 35.5 17.1 106.6 14.1 39 620.5 12.7 782.8 98 172.1 147.1 88.9 158.9 377.6 Year of measurement Gap per person (in local currency) Total annualized amount (millions of current dollars) Indigence gap (percentage of GDP) 2006 2008 2006 2008 2008 2008 2008 2008 2008 2008 2008 2005 2004 2007 2008 2006 2005 2007 14 386.9 903.8 108.4 17 406.6 33.4 545.1 91.8 187.2 82.2 29.8 1 695.3 83 667.6 27.5 186.6 216 177.7 334.7 376.5 787.6 723.0 238.8 2 138.9 298.6 373.0 21 020.0 29 944.3 8 007.7 3 332.0 2 114.4 2 455.2 8 755.2 1 059.1 1 517.7 1 963.2 3 752.6 850.1 2 604.3 0.5 0.7 1.0 1.0 1.6 1.9 2.1 2.6 2.6 3.9 5.4 6.1 6.7 11.6 11.6 12.4 17.4 21.0 94.7 27.3 358.3 62.6 2 848.4 3 850.2 500.5 93.2 1 636.6 423.1 1 788.4 195.4 578.4 472.9 874.8 417.0 185.1 826.6 Indigence gap (percentage of GDP) 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.4 0.5 0.8 1.2 1.2 1.3 2.8 2.9 3.2 3.8 6.7 Poverty Country Chile Uruguay Argentina Costa Rica Panama Mexico Brazil Venezuela (Bolivarian Republic of) Peru Ecuador Dominican Republic Colombia El Salvador Bolivia (Plurinational State of) Paraguay Guatemala Nicaragua Honduras Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys from the countries concerned and GDP series. All cash transfer systems should take account of two factors that prevent them from being fully targetable. First, poverty is a discrete cut-off point on the household income scale at a given moment in time. The rationale for a guaranteed partial income system is to create a basic floor that does not depend on the labour market but provides a permanent cushion against economic and life cycles (even though it does not ensure an exit from poverty) and substantially mitigates economic privation. Second, the amounts allocated to each household are not calculated for each specific case. In other words, households’ individual or per capita income shortfall relative to the poverty line can be measured by a household survey, but this cannot be the basis for allocating the exact amount that would bring each household above the poverty line. What can be allocated is a standard amount that would bring some households above the poverty line and not others. In other words, a basic guaranteed partial income system for households with children and adolescents seeks not to remove poverty surgically but to decrease its likelihood systemically, prevent it from becoming permanent in individual households and lessen its structural severity. The mechanisms that are most direct and easiest to evaluate in terms of impacts and costs are income transfers for children aged 0 to 14 and transfers or subsidies for jobs and training for young people aged 15 to 24 who are neither in education nor working. In both cases, the cost and impact of these transfers is estimated on the basis that they are limited to the vulnerable population (those in households whose per capita income is below 1.8 poverty lines). As figure V.1 shows, the cost of such a system is easily affordable for one group of countries, represents a major effort for a second and requires a longer-term effort or more diversified funding sources for a third. 200 Economic Commission for Latin America and the Caribbean (ECLAC) Figure V.1 LATIN AMERICA (18 COUNTRIES): COST OF ALL CASH TRANSFERS TARGETING THE VULNERABLE POPULATION, BY AGE GROUP, AROUND 2008 a (Percentages of GDP) 20 6.35 2.38 15 3.00 0.45 0.92 10 0.60 5 0.64 0.86 0.80 0.36 0.26 5.54 6.09 6.28 7.28 7.80 3.66 1.68 2.69 6.47 0.58 0.60 2.33 2.64 2.03 5.59 5.77 5.86 1.78 1.74 4.58 0.66 1.20 1.16 1.59 1.54 1.94 2.09 2.39 1.85 3.11 0.54 0.99 1.03 Ages 0 to 4 Ages 5 to 14 Honduras Nicaragua Guatemala Paraguay Bolivia (Plur. State of) El Salvador Colombia Ecuador Venezuela (Bol. Rep. of) Dominican. Rep. Peru Mexico Panama Chile Argentina 0.71 Costa Rica Uruguay 0 0.77 Brazil 0.47 0.70 0.50 1.05 Ages 15 to 24 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys from the countries concerned and GDP series. a Data relate to 2004 for El Salvador, 2005 for Nicaragua, 2006 for Argentina, Chile and Guatemala and 2007 for Honduras and the Plurinational State of Bolivia. For Argentina, Chile, Costa Rica, Uruguay and, to a lesser extent, Brazil and Panama, the additional costs are manageable and affordable over a short period of time, representing some 2% of GDP. For the Bolivarian Republic of Venezuela, Colombia, Dominican Republic, Ecuador and Mexico, the effort is considerable (some 5 percentage points of GDP or more). For Guatemala, 2. Honduras, Nicaragua, Paraguay and the Plurinational State of Bolivia, lastly, it would clearly entail an unaffordable fiscal commitment. In such cases, a very selective, gradualist strategy would be needed for progress to be made with these schemes, and the option of mobilizing additional international cooperation resources should be considered. These differences should come as no surprise, as the three country groups are situated very differently in terms of GDP and current levels of social spending and public revenue. For the countries with a higher degree of economic and social development, the transfers proposed here constitute a strategy for creating universal basic minimum incomes that fit in with an existing income transfer structure. For the intermediate countries it is a more ambitious undertaking that involves setting up a system of transfers to vulnerable population segments which was formerly non-existent or rudimentary. For the least developed countries, lastly, the proposal entails the creation of a welfare system from scratch or upon very partial foundations. The proposed transfers are costly. Coverage is not universal, although it is not limited to the poor as it encompasses a considerable proportion of the population and households (between 30% of the population in countries with fewer vulnerable people and nearly 80% in the poorest countries). These percentages are even greater when the child and adolescent population alone is considered, exceeding 50% of children aged 0 to 14 in all cases. Impacts Implementing and completing this transfer system would have very significant impacts in terms of poverty reduction, bringing the poverty rate down by nearly 10 percentage points in Argentina, Brazil, Chile, Costa Rica and Uruguay, by close to 30% in Nicaragua and by 25% in Guatemala. This means that the poverty rate would come down to some two thirds of its current level in countries like Chile and Uruguay and fall by more than half in the poorest countries. The measures proposed would also reduce the poverty gap for people who would not actually exit poverty despite receiving the benefit. For those who did not exit poverty, the gap would narrow by between 20% and almost 45%. Where inequality is concerned, lastly, the Gini coefficient would come down by between 7% (in Brazil) and 24% (in Honduras). These impacts would bring about substantial changes in the region’s societies: childhood and adolescence would no longer be the most vulnerable period or the one in which inequalities were reproduced and entrenched. These effects do not take account of improvements in poverty and inequality that would anyway be expected over time thanks to economic growth itself and the measures analysed here, or of their consequences for the life cycle and the intergenerational reproduction of well-being. Social Panorama of Latin America • 2010 201 Figure V.2 LATIN AMERICA (18 COUNTRIES): IMPACT OF TRANSFERS ON POVERTY, AROUND 2008 a (Percentages of people) 68.7 70 61.8 57.9 60 53.8 54.7 50 42.6 30 20 10 13.7 13.9 5.0 16.4 7.6 21.0 25.8 14.4 13.5 13.9 16.8 20.4 39.6 38.7 36.6 27.1 27.6 22.9 26.1 50.3 47.5 28.8 34.6 29.9 29.1 El Salvador 34.7 44.3 Dominican Rep. 40 42.7 9.4 4.4 Current poverty Honduras Paraguay Nicaragua Guatemala Bolivia (Plur. State of) Ecuador Peru Colombia Mexico Venezuela (Bol. Rep. of) Brazil Panama Argentina Costa Rica Chile Uruguay 0 Poverty after transfers Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys from the countries concerned and GDP projections. a Data relate to 2005 for Nicaragua, 2006 for Argentina, Chile and Guatemala and 2007 for Honduras and the Plurinational State of Bolivia. C. Poverty, inequality, the education cycle and the life cycle Taking aim at inequality and poverty requires initiatives on at least three critical fronts: extending coverage in early childhood by means of early childhood care and education systems (between ages 0 and 4); completing the universalization of coverage at basic and lower secondary education ages (0 to 14); and working towards universal coverage among adolescents and young people of upper secondary age (15 to 17). All these targets, and the additional cost per student in each country and cycle, are within the reach of all of the region’s countries. In 15 of the 18 countries reviewed, the cost does not exceed one percentage point of GDP. It can be seen that this would signify an enormous increase in coverage at both ends of the education cycle (preschool and upper secondary), especially for the poor and vulnerable. 202 Costing the measures here, then, is the minimum cost of completing coverage at constant investment rates, because only current expenditure per pupil is considered. Creating the infrastructure and improved conditions that would turn system coverage into a real force for equality will require substantially heavier outlays. The cost of training human resources for educational services is not considered either. A look at the results of the estimates shows that the additional costs estimated from spending per current pupil are affordable for all the countries in the region. Indeed, as figure V.3 shows, in 15 of the 18 countries reviewed they do not exceed one percentage point of GDP. Figure V.3 LATIN AMERICA (18 COUNTRIES): COST OF INCORPORATING CHILDREN AND YOUNG PEOPLE AGED 0 TO 17 INTO THE EDUCATION SYSTEM, AROUND 2008 a (Percentages of GDP) 3.0 2.39 2.5 2.65 2.35 2.0 1.5 0.93 1.0 0.67 0.58 0.59 0.64 0.40 0.44 0.52 0.53 0.53 0.54 0.56 0.5 0.29 0.76 0.87 Universal early childhood Honduras Universal preschool Universal lower secondary Nicaragua Guatemala Paraguay El Salvador Peru Mexico Colombia Bolivia (Plur. State of) Panama Argentina Brazil Ecuador Chile Dominican Rep. Uruguay 0.0 Costa Rica As already discussed here and in earlier issues of this publication (ECLAC, 2008a and ECLAC, 2009), addressing inequality and poverty via the education system involves, at the least, extending coverage in early childhood with early childhood care and stimulation systems (0 to 4 years of age), completing the universalization of basic and lower secondary education coverage (5 to 14) and working towards universal coverage for adolescents and young people in the upper cycle of secondary education (15 to 17). How much would achieving these goals cost the countries of the region? Unlike the cash transfers discussed earlier, whose threshold for evaluation and determination of benefit levels is an officially decreed amount (the poverty line), the amounts involved here derive from a concrete situation, namely average expenditure per pupil by education systems in each country. This per capita cost estimation basis yields cost units that vary widely from country to country. For example, the chapter on social spending reports that public expenditure per primary and secondary pupil in the region’s countries ranges from a low of US$ 62 to a high of more than US$ 2,000. In countries where the cost is low, of course, the additional cost pressure from incorporating children and young people not currently enrolled will likewise be lower. In this case, the cost will not reflect the real effort required. Instead, it will underestimate that effort because the system in question does not currently invest enough per pupil. Where the per capita cost of the education system is sufficiently high, raising the level of expenditure, while necessary, should not be as pressing a requirement because there is likely to be some scope for making the current spending structure more efficient. In short, a low estimate of the cost of incorporating the unenrolled can actually mask inadequate investment per student. Conversely, an estimate that might seem high could be manageable within the margin provided by the current spending level. Again, basing estimates on per capita cost means that the current coverage of each education system must be considered. Hence, countries facing major coverage challenges will have to spend heavily to incorporate children and young people who are not currently enrolled. The estimates do not take account of the additional investments that expanding coverage would require. The cost per reincorporated child or young person is calculated by dividing total expenditure by the number of students enrolled. This amount includes investments planned for the period under review but not those that might be called for by a specific education quality improvement policy (such as the cost of lengthening the school day). The figure presented Venezuela (Bol. Rep. of) 1. Economic Commission for Latin America and the Caribbean (ECLAC) Universal primary Universal upper secondary Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys from the countries concerned and GDP series. a Data relate to 2004 for El Salvador, 2005 for Nicaragua, 2006 for Argentina, Chile and Guatemala and 2007 for Honduras and the Plurinational State of Bolivia. These estimated costs cover the minimum required to ensure the system can operate with the new students. Figure V.4 shows, as an example, that the cost of universalizing primary education is almost marginal when compared with the percentage of students in each country who do not follow the extended school day, based on enrolment in publicly funded urban schools. It follows that the cost in infrastructure and human resources of extending the school day is far higher than that of universalizing coverage for the age group in this cycle. Extending the school day is one of the pending items on our countries’ agenda. This at least is what studies in this area seem to suggest, although findings vary (ANEP, 2005; Raczynski, 2001; García-Huidobro and Concha, 2009). Social Panorama of Latin America • 2010 203 Figure V.4 LATIN AMERICA (15 COUNTRIES): COST OF UNIVERSALIZING SCHOOL ENROLMENT FOR CHILDREN AGED 6 TO 11 AND PERCENTAGE OF CHILDREN IN PUBLICLY FUNDED URBAN SCHOOLS WHO ARE NOT yet IN ALL-DAY EDUCATION, AROUND 2008 a (Percentages of GDP and percentages of all students) 100 91 80 75 70 92 93 94 97 97 98 100 100 100 100 0.35 0.31 0.30 81 0.24 0.25 60 0.20 50 0.15 40 37 30 20 10 0.08 0.07 25 0.03 0.03 0.10 0.09 0.10 Cost of incorporation Students not yet in all-day education 90 0.06 0.02 0.01 0.03 0.02 0.05 0.02 0.01 0.00 Cost of incorporation Nicaragua Guatemala El Salvador Panama Paraguay Mexico Peru Dominican Rep. Uruguay Ecuador Argentina Costa Rica Colombia Brazil Chile 0 Students not yet in all-day education Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys from the countries concerned, special tabulations of microdata from the Second Regional Comparative and Explanatory Study (SERCE) and GDP series. a The data used to calculate costs are from 2004 in El Salvador, 2005 in Nicaragua and 2006 in Argentina, Chile and Guatemala. 2. Impacts The impacts of the estimated spending required to incorporate children and young people into the education system differ in their logic from those of direct cash transfers. The challenge of incorporation is not equivalent to the cost. In other words, it would be difficult to relate incorporation directly to increased spending as its cause. It is a goal with political and social ramifications that transcend the financial aspect. Because the basic costs of incorporation are being discussed here, what can be examined are the gains they would deliver by bringing in children and young people who are not currently attending any educational establishment. Incorporation does not guarantee that everyone will progress satisfactorily or complete their schooling when they should, since what is considered is the official age of those who are not attending school irrespective of the level they have reached in the event of incorporation or re-enrolment. If a 15-year-old is not in school, in other words, what is estimated is the impact of incorporating that pupil, even if it is not at the appropriate level. The child might not be incorporated into the upper secondary cycle, despite being of the official age for this, if he or she has not completed the lower secondary cycle. This consideration aside, the first thing is to incorporate the child, and this means having resources available to expand coverage. The internal dynamics of the system that go to the heart of inequality can be addressed later. Looking at either end of the education cycle (preschool and upper secondary) shows how enormously this would expand coverage, especially for the poor and vulnerable. Table V.3 shows the percentages of children and young people not attending school at these critical levels, by income decile, highlighting the coverage “gained” for all population deciles and the coverage resulting from a more gradual incorporation strategy limited to vulnerable households. For the early childhood level, which is the most critical in the majority of countries, even gradual incorporation would benefit a very substantial portion of the corresponding age group in a large number of countries. In countries like El Salvador, Guatemala, Honduras and Nicaragua, between three fourths and nearly 9 out of 10 children in the vulnerable deciles would be incorporated. 204 Economic Commission for Latin America and the Caribbean (ECLAC) Table V.3 LATIN AMERICA (16 COUNTRIES): NUMBER OF CHILDREN AND YOUNG PEOPLE NOT ATTENDING UPPER SECONDARY SCHOOL (AGES 15 TO 17) AND PRESCHOOL (AGES 3 TO 5), BY INCOME DECILE AND VULNERABILITY STATUS, AROUND 2008 a (Percentages of each age group) Income decile Country Education level I Argentina Preschool Upper secondary Bolivia (Plurinational State of) II III IV V VI VII VIII IX X 55.0 43.6 45.6 38.4 41.4 30.1 28.9 25.4 24.3 25.2 25.5 23.1 20.9 18.5 13.4 11.8 7.8 10.7 4.6 55.6 Brazil Preschool 63.7 38.1 36.1 23.6 48.9 48.1 33.8 33.0 29.7 36.9 Upper secondary 32.7 16.2 15.5 17.3 13.5 11.8 11.5 9.0 7.1 14.7 Preschool 39.1 40.7 38.1 33.5 34.7 31.1 28.4 23.5 19.3 12.2 20.3 17.9 17.6 14.0 12.7 8.2 5.9 Upper secondary Chile 22.3 19.4 20.5 Preschool 43.4 44.7 44.3 38.3 36.1 37.3 35.0 35.4 32.9 23.1 12.6 7.8 7.9 8.0 4.3 2.5 2.9 51.6 53.8 50.3 44.8 43.6 36.1 24.3 Upper secondary 14.0 11.9 9.7 Colombia Preschool 56.1 55.5 56.4 Upper secondary 22.2 21.1 20.5 19.6 19.4 20.1 18.1 15.3 13.8 8.9 Costa Rica Preschool 71.7 67.1 69.3 72.2 76.2 67.1 70.2 67.0 48.0 30.9 Upper secondary 34.9 23.6 14.3 22.3 16.8 17.9 21.6 16.8 16.4 11.9 16.8 11.6 20.3 4.8 5.6 3.6 0.1 2.9 Ecuador Preschool 29.2 23.9 Upper secondary 29.7 33.7 30.1 31.7 30.5 25.2 24.8 19.4 15.3 8.8 El Salvador Preschool 73.9 65.0 71.9 64.1 63.6 63.6 55.8 51.7 46.4 36.4 Upper secondary 57.9 54.1 49.4 57.4 46.7 42.7 34.7 34.3 30.4 18.7 90.9 91.1 92.5 87.2 86.1 89.5 92.7 84.8 Guatemala 93.6 89.5 Upper secondary Honduras Preschool 71.0 71.8 67.8 57.4 64.7 54.6 52.1 41.0 29.5 17.7 84.3 83.0 83.1 83.2 79.2 75.2 67.5 51.3 47.4 38.4 38.7 35.0 24.8 17.1 84.3 85.5 82.1 Upper secondary Mexico Preschool 63.6 67.8 58.5 Nicaragua Preschool 35.5 38.5 29.8 37.5 33.8 30.4 28.0 26.4 23.7 19.3 Upper secondary 47.8 46.3 42.0 42.0 37.6 42.7 28.7 30.0 17.4 12.3 Preschool 77.7 69.2 77.2 68.1 70.2 66.4 56.3 64.0 59.8 48.0 48.1 45.2 43.5 51.2 27.2 32.8 29.0 23.5 9.7 Upper secondary Panama 48.5 Paraguay Preschool 29.3 32.8 33.7 31.7 22.7 21.3 19.9 12.5 7.1 2.4 Upper secondary 44.9 35.4 28.9 25.9 19.8 20.1 19.3 13.1 8.0 5.2 Preschool 68.6 50.8 58.2 46.0 53.8 29.1 30.8 22.1 20.4 10.1 27.4 27.2 32.1 28.2 13.6 23.8 11.9 16.0 Upper secondary Uruguay 53.5 40.8 Preschool 33.3 30.8 30.4 30.3 27.1 27.0 22.8 17.3 12.7 6.6 34.9 32.3 27.1 25.6 17.2 15.8 11.6 3.6 Upper secondary 44.1 41.6 Venezuela Preschool (Bolivarian Republic of) Upper secondary 41.5 42.1 39.9 35.4 35.6 32.7 28.5 26.7 25.1 23.4 17.7 19.5 18.9 18.0 14.4 16.4 16.2 14.0 12.2 19.5 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys from the countries concerned. a Data relate to 2004 for El Salvador, 2005 for Nicaragua, 2006 for Argentina, Chile and Guatemala and 2007 for Honduras and the Plurinational State of Bolivia. For preschool age (3 to 5) in countries for which data on the entire age group was not available, the earliest age for the level was used, this being 5 in Ecuador, Guatemala, Panama, Paraguay and the Plurinational State of Bolivia. The income data used to define deciles in the vulnerable population are from around 2007. The shaded areas indicate vulnerability (per capita income of 1.8 poverty lines or less). Social Panorama of Latin America • 2010 205 D. Funding from an intertemporal perspective Provision of the resources needed to implement the transfer scheme and support services would differ in timing from country to country, depending on GDP performance, the tax burden, public spending goals and access to complementary resources such as international cooperation. Assuming GDP growth and an expanding tax burden in cases where this is possible, the countries of Latin America break down into three broad groups. The first comprises countries whose revenues, measured in points of GDP, should be very close to (or exceed) the level required to fund the proposed measures by the end of 2012. A second group should be in a position to afford them by about 2014. The other countries would not have enough revenue to meet the costs involved by the end of the period and would therefore need complementary sources of funding. This exercise should be treated with care because it does not consider alternative costs in other strategic social areas such as health care, social security or housing. What are discussed here are orders of magnitude for social investment in the younger generations and the fiscal leeway needed to address these challenges. The primary aim is to help define priorities and timing, not to map out a strict predetermined spending path. The region’s countries have already allocated all their fiscal receipts to the various spending items, so implementing an additional transfer and coverage scheme is difficult (Jiménez, 2009). Generally speaking, their ability to address these shortcomings depends on the performance of the variables mentioned (growth, tax revenues, reallocation of spending and mobilization of external resources). Figure V.6 shows the fiscal space available to the countries over the next 10 years to cover the additional cost of the proposed measures. The economic growth rate is therefore assumed to be somewhat greater than 2% and, in countries whose GDP offers potential room for expanding the tax burden, the impact of that expansion (in annual increments) is shown. This projection does not take into account resources that might come from retargeting spending or from external cooperation. As can be seen, most of the countries could reach the break-even point before the end of the period, with a sizeable surplus after covering the deficit. In the most optimistic scenarios (GDP growth combined with an expanding tax burden where this is possible), the countries of Latin America fall into three groups. The first comprises those whose revenues, measured in points of GDP, should be very close to (or exceed) the level required to fund the proposed measures by the end of 2012. This group includes Argentina, Brazil, Chile, Costa Rica, Panama and Uruguay (Mexico lies between this group and the next on the basis of GDP growth alone, but would fall squarely into the first group if its tax burden were to increase). A second group, including the Bolivarian Republic of Venezuela, Colombia, Dominican Republic, Ecuador and Peru, should be in a position to afford them by about 2014 or 2015. El Salvador is not expected to raise the requisite funding until about 2018. Even if the different variables combine to broader fiscal capacity in the most optimistic scenario, the other countries (Guatemala, Honduras, Nicaragua, Paraguay and the Plurinational State of Bolivia) are not expected to have enough revenue by the end of the period to cover the costs (except Paraguay, and then only in the very last year). These countries therefore need to mobilize external resources. 206 Economic Commission for Latin America and the Caribbean (ECLAC) Figure V.5 LATIN AMERICA (18 COUNTRIES): TOTAL COST OF CASH TRANSFERS TO VULNERABLE POPULATIONS AND INCORPORATION OF CHILDREN AND YOUNG PEOPLE AGED 0 TO 17 INTO EDUCATION SYSTEMS, AROUND 2008 a (Percentages of GDP) 25 2.39 20 2.65 2.35 15 0.87 0.64 0.54 0.29 0.76 0.53 11.05 12.13 15.05 15.53 Honduras Nicaragua Guatemala Paraguay Bolivia (Plur. State of) 7.37 El Salvador Colombia Ecuador Venezuela (Bol. Rep. of) Mexico 5.34 5.57 4.02 4.14 5.07 5.09 Dominican Rep. Panama Chile 2.25 2.77 2.79 Brazil Costa Rica 2.17 2.17 2.18 0.67 Peru 0.58 0.40 0.56 0.44 0.52 0.53 Uruguay 0 0.93 Argentina 5 0.59 20.62 10 Total cost of incorporating children and young people aged 0 to 17 (whole population) Total cost of transfers (vulnerable population) Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys from the countries concerned and GDP series. a Data relate to 2004 for El Salvador, 2005 for Nicaragua, 2006 for Argentina, Chile and Guatemala and 2007 for Honduras and the Plurinational State of Bolivia. Figure V.6 LATIN AMERICA (18 COUNTRIES): FISCAL DEFICIT OR SURPLUS AVAILABLE TO FUND THE TRANSFER SYSTEM AND ENHANCED CARE AND EDUCATION SERVICES IN SCENARIOS OF GROWING GDP AND A GROWING TAX BURDEN (Percentages of 2008 GDP) Lastly, it is worth taking at least an exploratory look at the other potential source of funding for these measures: the reorientation of social expenditure itself. Once again, the countries that would be best positioned to take advantage of this potential fiscal space are those where the least additional effort is needed. In other words, the less the additional effort needed over and above current expenditure, the greater the likelihood that fiscal margin can be found within the social spending budget itself. One final requirement is to consider the relative cost of monetary measures and services measures and to determine differentiated baselines for each group of countries based on their capacity to afford these costs, as just discussed. In less developed countries, it is most realistic to start by universalizing education system coverage, which costs far less in these countries, while having more modest basic transfer amounts. The more developed countries can address themselves to all the proposed measures at once. Table V.4 summarizes the balance between coverage and transfers for the country groups, the costs they can afford and the potential impact on poverty reduction and expansion of educational coverage. Figure V.7 LATIN AMERICA: ADDITIONAL COSTS OF THE TRANSFERS AND EDUCATIONAL SERVICES MODEL, 2007-2008 a (Percentages of current social expenditure) 250 25 20 200 15 Surplus 10 5 0 150 100 -5 Deficit -10 -15 -20 50 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household surveys from the countries concerned, GDP projections and data from the Latin American and Caribbean Institute for Economic and Social Planning (ILPES) for actual tax burdens. Additional cost Nicaragua Guatemala Paraguay Honduras Peru Colombia El Salvador (2006-2007) Bolivia (Plur. State of) (2006-2007) Ecuador (2006-2007) Ecuador El Salvador Guatemala Dominican Rep. Uruguay Venezuela (Bol. Rep. of) Mexico 2018 2019 2020 2021 Dominican Rep. Chile Colombia Costa Rica Panama Paraguay Peru 2017 Chile 2015 2016 Venezuela (Bol. Rep. of) Argentina Bolivia (Plur. State of) Brazil Honduras Mexico Nicaragua 2014 Panama 2013 Brazil 2012 Costa Rica 2011 Uruguay 2009 2010 Argentina 0 -25 Social expenditure Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of cost estimates, GDP series and social expenditure. a Both figures (social expenditure and additional cost) are expressed as percentages of GDP. Social Panorama of Latin America • 2010 207 Table V.4 LATIN AMERICA: MEASURES, COSTS AND IMPACTS OF EQUALITY STRATEGIES, BY FISCAL CAPACITY Countries in first group a Countries in second group b Countries in third group c Measures proposed All proposed coverage and income transfer measures: cash transfers to households with children aged 0 to 14, coverage of education and care services (ages 0 to 17) and cash transfers coordinated with employment and training services (ages 15 to 24) Cash transfers to households with children aged 0 to 4 and 15 to 24 All coverage measures All coverage measures Cash transfers to households with children aged 0 to 4; half the benefit or half the coverage Estimated cost Between 2.5% and 3.5% of GDP Between 2.9% and 4.2% of GDP Between 2.5% and 5.6% of GDP Estimated aggregate effects on poverty Drop in poverty rate of between 13.5 and 8.7 percentage points. Drop of between 70% and 50% from original poverty level Drop in poverty rate of between 6.6 and 11.9 percentage points. Drop of between 30% and 16.6% from original poverty level Drop in poverty rate of between 2.8 and 4.0 percentage points. Drop of between 4% and 8% from original poverty level Percentage of preschool-age children who would be brought into the system Between 24% and 64% Between 30% and 47% Between 59% and 90% Percentage of upper secondary school-age children who would be brought into the system Between 8% and 25% Between 17% and 35% Between 36% and 53% Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of continuous household surveys and GDP data. a Argentina, Brazil, Chile, Costa Rica, Panama and Uruguay. b Bolivarian Republic of Venezuela, Colombia, Dominican Republic, Ecuador, Mexico and Peru. c El Salvador, Guatemala, Honduras, Nicaragua, Paraguay and Plurinational State of Bolivia. 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Social Panorama of Latin America • 2010 Statistical appendix 218 Economic Commission for Latin America and the Caribbean (ECLAC) Social Panorama of Latin America • 2010 219 Table A-1 Latin America and the Caribbean: TRENDS IN SELECTED ECONOMIC INDICATORS, 1990-2009 Annual Unemployment variation in (percentage) consumer price index b Annual average variations in the period Country Year Per capita GDP (in 2000 dollars) Argentina 1990 5 832.7 5 690.1 7.4 1999 7 852.3 7 598.8 14.3 -1.8 1990-1999 2002 6 433.7 6 147.0 19.7 41.0 2002 2008 9 884.9 9 926.2 7.9 7.2 2008 5.7 2009 9 869.6 9 823.1 8.7 7.7 2009 -0.2 1990 17 373.3 … … … 1999 17 694.8 … 7.8 … 1990-1999 0.2 2002 17 790.8 … 9.1 … 2002 0.9 2008 18 349.3 … 8.7 … 2008 2009 17 357.2 … 14.2 … 1990 8 673.5 … 14.7 3.4 1999 9 928.2 … 10.4 2002 9 790.9 … 10.3 2008 11 468.2 … 2009 11 012.2 … 1990 2 775.3 1999 3 024.1 2002 Per capita income (in 2000 dollars) a Period Per capita GDP Per capita income a Mean real remuneration Real urban minimum wage 1 343.9 Belize Bolivia (Plurinational State of) 0.0 15.0 -19.4 -19.5 7.0 8.8 15.3 -1.0 11.7 15.3 … … … … … … -2.8 … … … 2009 -5.4 … … … 2.9 1990-1999 1.5 … … … 0.9 2002 0.7 … … … 8.1 7.3 2008 0.5 … … … 10.0 4.4 2009 -4.0 … … … … … … … 12.8 … 1990-1999 1.0 … … … 3 476.7 … 10.0 … 2002 2.7 … … … 3 949.7 … 8.2 … 2008 1.7 … … … 2009 Barbados 3.3 -13.3 2008 Bahamas 3.4 -11.8 3 872.1 … 13.1 … 2009 -2.0 … … … 10.2 18.0 7.2 3.1 1990-1999 1.6 1.5 2.1 2002 1 010.5 1 058.0 8.7 2.5 2002 0.4 3.6 3.3 4.7 1 173.3 1 502.5 6.7 11.8 2008 4.3 6.1 -7.4 -1.5 1 191.9 1 453.4 7.9 0.3 2009 1.6 -3.3 … 8.2 1990 3 356.1 3 280.6 4.3 2 101.3 3 600.2 3 491.3 7.6 8.9 1990-1999 0.8 0.7 0.2 3.1 2002 3 743.8 3 635.4 11.7 12.5 2002 1.2 1.4 -2.1 4.2 2008 4 465.9 4 463.0 7.9 5.9 2008 4.1 4.5 2.1 3.9 2009 4 416.0 4 399.1 8.1 4.3 2009 -1.1 -1.4 1.3 7.4 1990 3 081.3 2 951.8 7.8 27.3 1999 4 747.1 4 576.1 10.1 2.3 1990-1999 4.9 5.0 4.0 5.5 2002 5 055.1 4 834.7 9.8 2.8 2002 1.0 1.7 2.0 2.9 2008 6 262.0 6 903.9 7.8 7.1 2008 2.6 0.2 -0.2 -0.1 2009 6 106.1 6 712.8 9.7 -1.4 2009 -2.5 -2.8 4.8 5.4 1990 2 167.6 2 077.2 10.5 32.4 1999 2 337.2 2 297.7 19.4 9.2 1990-1999 0.8 1.1 2.6 -0.1 2002 2 396.9 2 364.6 18.1 7.0 2002 0.8 0.8 3.0 0.7 2008 2 983.3 3 097.9 11.5 7.7 2008 0.9 2.3 -2.0 -1.6 2009 Costa Rica 7.3 1 026.6 1999 Colombia 901.0 1 005.6 2009 Chile 869.8 1999 2008 Brazil 1990 2 951.4 2 971.3 13.0 2.0 2009 -1.1 -4.1 1.1 3.1 1990 3 123.1 3 034.9 5.4 27.3 1999 4 078.2 3 734.3 6.2 10.1 1990-1999 3.0 2.3 2.2 1.1 2002 4 049.3 3 961.9 6.8 9.7 2002 0.8 2.1 4.1 -0.6 2008 5 206.4 4 857.5 4.8 13.9 2008 1.5 2.0 -2.0 -1.3 2009 5 084.3 4 687.8 7.6 4.0 2009 -2.3 -3.5 7.7 4.0 220 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-1 (continued) Annual Unemployment variation in (percentage) consumer price index b Country Year Per capita GDP (in 2000 dollars) Cuba b 1990 3 340.9 … 5.4 2 613.0 2 695.0 6.3 2002 2 873.8 2 889.2 3.3 2008 4 362.9 … 2009 4 426.2 … Dominican Republic 1990 1999 2002 2008 2009 1 828.4 2 657.1 2 885.0 3 688.1 3 764.0 Ecuador 1990 1999 2002 2008 2009 Annual average variations in the period … 1999 El Salvador Guatemala Haiti Honduras Jamaica Mexico Nicaragua Per capita income (in 2000 dollars) a Per capita income a Mean real remuneration Real urban minimum wage Period Per capita GDP … 1990-1999 -2.7 …. -9.4 … … 2002 1.2 1.3 9.3 5.3 1.6 … 2008 4.1 … 0.1 -1.6 1.7 … 2009 1.4 … 4.1 1.2 1 794.8 2 801.7 3 031.6 3 663.0 3 802.8 ... 13.8 16.1 14.1 14.9 79.9 5.1 10.5 4.5 5.7 1990-1999 2002 2008 2009 4.2 4.2 3.8 2.1 5.1 4.9 3.5 3.8 … … … … 2.6 -0.5 -6.5 7.0 1 311.3 1 288.1 1 397.9 1 782.2 1 770.0 1 155.6 1 223.5 1 371.7 2 039.0 1 905.4 6.1 14.4 9.2 6.9 8.5 49.5 60.7 9.4 8.8 4.3 1990-1999 2002 2008 2009 -0.2 2.2 6.1 -0.7 0.6 3.5 10.4 -6.6 3.7 10.9 … … 2.1 0.9 8.5 3.6 1990 1999 2002 2008 2009 1 572.1 2 176.3 2 280.4 2 672.9 2 566.1 1 614.2 2 391.9 2 587.2 3 044.2 2 936.8 10.0 6.9 6.2 5.5 7.1 19.3 -1.0 2.8 5.5 -0.2 1990-1999 2002 2008 2009 3.7 1.9 2.0 -4.0 4.5 -0.7 0.4 -3.5 … … … … 0.1 -1.8 0.2 9.5 1990 1999 2002 2008 2009 1 289.6 1 513.5 1 549.7 1 687.3 1 655.8 1 265.6 1 571.7 1 701.2 1 838.7 1 824.2 … … … … … 59.6 4.9 6.3 9.4 -0.3 1990-1999 2002 2008 2009 1.8 1.3 0.8 -1.9 2.4 4.7 -1.3 -0.8 5.4 -0.9 -2.6 0.1 -7.4 0.3 -10.2 5.1 1990 1999 2002 2008 2009 515.7 430.9 408.1 389.1 393.8 556.8 517.1 490.4 482.6 504.4 … … … … … 26.1 9.7 14.8 17.0 2.1 1990-1999 2002 2008 2009 -2.0 -1.8 -0.8 1.2 -0.8 -2.1 -6.0 4.5 … … … … -7.3 -8.9 -12.9 28.0 1990 1999 2002 2008 2009 1 061.4 1 113.5 1 179.2 1 450.6 1 394.9 1 022.5 1 246.6 1 216.4 1 512.1 1 522.1 7.8 5.3 6.1 4.1 4.9 36.4 10.9 8.1 10.8 3.0 1990-1999 2002 2008 2009 0.5 1.7 1.9 -3.8 2.2 0.8 -1.6 0.7 … … … … -1.1 2.1 0.2 70.4 1990 1999 2002 2008 2009 3 516.5 3 489.4 3 508.6 3 703.2 3 588.9 … … … … … 15.3 15.7 14.2 10.6 11.4 29.8 6.8 7.3 16.9 10.2 1990-1999 2002 2008 2009 -0.1 0.2 -1.4 -3.1 … … … … … … … … … … … … 1990 1999 2002 2008 2009 5 393.6 6 121.8 6 320.4 7 094.6 6 563.1 5 235.6 6 043.8 6 265.3 7 269.3 6 657.3 2.7 3.7 3.9 4.9 6.7 29.9 12.3 5.7 6.5 3.6 1990-1999 2002 2008 2009 1.4 -0.5 0.5 -7.5 1.6 0.1 0.6 -8.4 0.7 1.9 2.2 0.6 -4.1 0.7 -2.1 -1.5 1990 1999 2002 2008 2009 682.1 753.7 778.4 894.2 869.8 577.4 799.8 812.8 899.1 908.9 7.6 10.7 11.6 8.0 10.5 13 490.2 7.2 4.0 12.7 1.8 1990-1999 2002 2008 2009 1.1 -0.6 1.4 -2.7 3.7 0.7 -2.1 1.1 3.1 3.5 -3.8 6.5 0.8 3.7 7.6 16.8 Social Panorama of Latin America • 2010 221 Table A-1 (concluded) Annual Unemployment variation in (percentage) consumer price index b Annual average variations in the period Country Year Per capita GDP (in 2000 dollars) Panama 1990 1999 2002 2008 2009 2 941.5 3 910.6 3 902.0 5 687.8 5 732.4 3 017.0 3 814.7 3 939.5 5 019.2 5 203.9 20.0 13.6 16.5 6.5 7.9 0.8 1.5 1.9 6.8 1.9 1990-1999 2002 2008 2009 3.2 0.4 8.9 0.8 1990 1999 2002 2008 2009 1 400.1 1 401.2 1 299.3 1 521.4 1 437.5 1 396.7 1 453.4 1 293.2 1 614.3 1 495.4 6.6 9.4 14.7 7.4 8.2 44.0 5.4 14.6 7.5 1.9 1990-1999 2002 2008 2009 1990 1999 2002 2008 2009 1 649.1 2 023.8 2 098.0 2 923.9 2 915.7 1 594.5 2 019.4 2 075.9 2 987.9 2 962.0 8.3 9.2 9.4 8.4 8.4 7 646.8 3.7 1.5 6.6 0.2 1990 1999 2002 2008 2009 1 848.8 1 648.6 1 748.8 2 142.0 2 167.3 … … … … … 15.8 14.0 10.0 … … Trinidad and Tobago 1990 1999 2002 2008 2009 4 337.9 5 913.2 7 025.6 10 963.9 10 820.2 … … … … … Uruguay 1990 1999 2002 2008 2009 4 925.4 6 326.0 5 325.4 8 035.7 8 238.3 1990 1999 2002 2008 2009 Per capita income (in 2000 dollars) a Venezuela (Bolivarian Republic of) Latin America c 0.7 -3.0 -0.6 -0.4 1.7 -1.2 2.7 -2.4 0.0 -2.0 3.9 -5.5 0.4 -4.8 8.6 -7.4 1.3 -5.0 -0.7 4.3 -1.3 -0.7 -2.5 0.7 1990-1999 2002 2008 2009 2.3 3.6 8.5 -0.3 2.7 3.4 6.2 -0.9 0.6 4.6 2.2 0.3 2.3 -0.2 2.5 -2.9 … … … … 1990-1999 2002 2008 2009 -1.3 1.2 3.3 1.2 … … … … … … … … … … … … 20.1 13.2 10.4 4.6 5.3 9.5 3.4 4.3 14.5 1.3 1990-1999 2002 2008 2009 3.5 7.5 1.9 -1.3 … … … … … … … … … … … … 4 975.1 6 270.1 5 371.8 7 727.7 7 974.1 8.5 11.3 17.0 7.9 7.7 128.9 4.2 25.9 9.2 5.9 1990-1999 2002 2008 2009 2.8 -11.0 8.2 2.5 2.6 -10.4 8.6 3.2 1.4 -10.7 3.6 … -5.3 -10.1 10.8 … 4 737.6 4 631.5 4 276.5 5 773.5 5 493.2 4 431.4 4 112.9 3 999.0 7 298.5 6 149.5 10.4 15.0 15.8 7.3 7.8 36.5 20.0 31.2 31.9 26.9 1990-1999 2002 2008 2009 -0.3 -10.5 3.0 -4.9 -0.8 -10.3 9.0 -15.7 -3.9 -11.0 -4.5 … -0.8 -5.4 -6.4 … 1990 3 535.8 3 428.8 … 1 376.8 1999 4 004.0 3 899.2 11.0 9.7 1990-1999 1.4 1.4 2.0 2.5 3 992.1 3 900.5 11.1 12.2 2002 -1.7 -1.6 -1.3 0.6 4 923.8 5 067.7 7.3 8.4 2008 3.0 3.7 -0.5 0.1 2009 Suriname 2.6 2.8 6.1 3.7 2008 Peru Real urban minimum wage 2002 Paraguay Mean real remuneration 4 777.5 4 841.9 8.2 4.7 2009 -3.0 -4.5 3.1 9.0 Period Per capita GDP Per capita income a Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries. a Real per capita gross national income. b Simple average of December-to-December variations for each year. c The aggregate figure for Latin America was calculated by weighting the figures for all the countries for which information was available for each indicator. 222 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-2 Latin America and the Caribbean: TOTAL POPULATION BY COUNTRY OR TERRITORY, 1980-2020 (Thousands at mid-year) Country 1980 1985 1990 1995 2000 2005 2010 2015 2020 28 094 30 305 32 581 34 835 36 896 38 747 40 738 42 676 44 486 5 355 5 964 6 669 7 482 8 317 9 182 10 031 10 854 11 638 Brazil 121 618 136 124 149 527 161 620 174 167 186 110 195 498 202 954 209 090 Chile 11 174 12 102 13 179 14 395 15 412 16 294 17 133 17 914 18 606 Colombia 26 881 29 984 33 186 36 436 39 763 43 046 46 299 49 385 52 278 Costa Rica 2 347 2 697 3 076 3 475 3 929 4 327 4 639 4 962 5 255 Cuba 9 823 10 064 10 564 10 885 11 075 11 189 11 203 11 213 11 193 Dominican Republic 5 808 6 487 7 179 7 888 8 560 9 237 9 899 10 515 11 077 Ecuador 7 961 9 099 10 272 11 397 12 305 13 060 13 773 14 550 15 349 El Salvador 4 660 4 996 5 326 5 724 5 942 6 057 6 192 6 381 6 616 Guatemala 7 014 7 935 8 908 10 004 11 229 12 709 14 376 16 195 18 076 Haiti 5 691 6 388 7 109 7 837 8 578 9 295 10 089 10 918 11 752 Honduras 3 634 4 236 4 901 5 589 6 234 6 898 7 621 8 392 9 141 69 321 76 808 83 906 91 621 98 957 105 001 110 675 115 735 120 099 Nicaragua 3 250 3 709 4 137 4 658 5 100 5 455 5 822 6 189 6 529 Panama 1 949 2 176 2 411 2 670 2 950 3 231 3 508 3 773 4 027 Paraguay 3 198 3 702 4 248 4 799 5 349 5 904 6 460 7 007 7 533 17 324 19 519 21 765 23 927 25 997 27 833 29 495 31 197 32 881 Latin America Argentina Bolivia (Plurinational State of) Mexico Peru Uruguay 2 914 Latin America 3 009 3 106 3 218 3 318 3 324 3 372 3 430 3 493 15 091 17 317 19 731 22 078 24 402 26 724 29 043 31 291 33 412 353 109 Venezuela (Bolivarian Republic of) 392 620 431 779 470 537 508 479 543 622 575 867 605 531 632 530 18 The Caribbean Anguilla 7 7 8 10 11 14 15 17 Antigua and Barbuda 72 68 62 68 77 84 89 93 97 Aruba 61 64 63 80 91 101 107 109 111 Bahamas 210 234 256 281 305 325 346 366 384 Barbados 249 254 260 258 252 253 257 260 262 Belize 144 165 190 220 252 282 313 344 375 Cayman Islands 17 21 26 33 40 53 57 59 61 Dominica 73 72 69 69 68 67 67 67 67 Grenada 89 100 96 100 101 103 104 107 108 Guyana 776 771 749 759 756 764 761 754 745 Jamaica 2 133 2 296 2 364 2 466 2 568 2 668 2 730 2 786 2 834 Montserrat 12 11 11 10 5 6 6 6 6 174 182 191 191 181 186 201 207 210 3 197 3 378 3 528 3 701 3 819 3 913 3 998 4 074 4 135 43 42 41 43 46 49 52 56 59 Saint Lucia 118 127 138 147 157 165 174 182 190 Saint Vincent and the Grenadines 100 104 107 108 108 109 109 110 110 Suriname 366 376 407 436 467 500 524 547 568 1 082 1 176 1 219 1 265 1 295 1 318 1 344 1 368 1 384 8 9 12 15 19 31 33 35 36 98 105 103 107 109 110 109 108 106 29 860 32 063 34 384 36 640 38 650 40 566 42 312 43 958 45 470 362 655 402 103 442 310 482 265 521 228 556 512 588 649 618 486 645 543 Netherlands Antilles Puerto Rico Saint Kitts and Nevis Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands The Caribbean a Latin America and the Caribbean b Source: conomic Commission for Latin America and the Caribbean (ECLAC), Database on Social Statistics and Indicators (BADEINSO) [online]. Information from the Latin E American and Caribbean Demographic Centre - Population Division of ECLAC, 2008 revision. Population Database and United Nations, Department of Economic and Social Affairs, Population Division, World Population Prospects, 2008 revision; Population database, published on CD-ROM. a Includes 24 economies: Anguilla, Antigua and Barbuda, Aruba, Bahamas, Barbados, British Virgin Islands, Cayman Islands, Cuba, Dominica, Dominican Republic, Grenada, Guadeloupe, Haiti, Jamaica, Martinique, Montserrat, Netherlands Antilles, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Trinidad and Tobago, Turks and Caicos Islands and United States Virgin Islands. b Includes 46 economies: Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivarian Republic of Venezuela, Brazil, British Virgin Islands, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Netherlands Antilles, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Turks and Caicos Islands, United States Virgin Islands and Uruguay. Social Panorama of Latin America • 2010 223 Table A-3 Latin America and the Caribbean: GLOBAL FERTILITY RATES BY COUNTRY AND FIVE-YEAR PERIOD, 1980-2020 (Children per woman) Country 1980-1985 1985-1990 1990-1995 1995-2000 2000-2005 2005-2010 2010-2015 2015-2020 Latin America Argentina 3.15 3.05 2.90 2.63 2.35 2.25 2.16 2.08 Bolivia (Plurinational State of) 5.30 5.00 4.80 4.32 3.96 3.50 3.09 2.75 Brazil 3.80 3.10 2.60 2.45 2.25 1.90 1.70 1.60 Chile 2.67 2.65 2.55 2.21 2.00 1.94 1.89 1.85 Colombia 3.68 3.24 3.00 2.75 2.55 2.45 2.30 2.19 Costa Rica 3.53 3.37 2.95 2.58 2.28 1.96 1.97 1.85 Cuba 1.85 1.85 1.65 1.61 1.63 1.50 1.54 1.57 Dominican Republic 4.15 3.65 3.31 2.98 2.83 2.67 2.48 2.32 Ecuador 4.70 4.00 3.40 3.10 2.82 2.58 2.38 2.22 El Salvador 4.80 4.20 3.73 3.30 2.60 2.35 2.22 2.13 Guatemala 6.10 5.70 5.45 5.00 4.60 4.15 3.71 3.29 Haiti 6.21 5.70 5.15 4.62 4.00 3.54 3.19 2.91 Honduras 6.00 5.37 4.92 4.30 3.72 3.31 2.95 2.66 Mexico 4.25 3.63 3.19 2.67 2.40 2.21 2.04 1.89 Nicaragua 5.85 5.00 4.50 3.60 3.00 2.76 2.55 2.37 Panama 3.52 3.20 2.87 2.79 2.70 2.56 2.41 2.29 Paraguay 5.20 4.77 4.31 3.88 3.48 3.08 2.76 2.51 Peru 4.65 4.10 3.57 3.10 2.80 2.60 2.38 2.22 Uruguay 2.57 2.53 2.49 2.30 2.20 2.12 2.03 1.96 Venezuela (Bolivarian Republic of) 3.96 3.65 3.25 2.94 2.72 2.55 2.39 2.26 Latin America 3.95 3.44 3.04 2.74 2.50 2.27 2.09 1.98 The Caribbean Aruba 2.36 2.30 2.17 2.00 1.82 1.74 1.75 1.80 Bahamas 3.16 2.62 2.60 2.40 2.11 2.02 1.95 1.88 Barbados 1.92 1.75 1.60 1.50 1.50 1.53 1.58 1.63 Belize 5.40 4.70 4.35 3.85 3.35 2.94 2.65 2.41 Grenada 4.23 4.14 3.46 2.81 2.43 2.30 2.20 2.10 Guyana 3.26 2.70 2.55 2.50 2.43 2.33 2.22 2.13 Jamaica 3.55 3.10 2.84 2.67 2.53 2.40 2.28 2.17 Netherlands Antilles 2.36 2.30 2.28 2.12 2.09 1.98 1.91 1.86 Puerto Rico 2.46 2.26 2.18 2.02 1.84 1.83 1.85 1.85 Saint Lucia 4.20 3.65 3.15 2.60 2.10 2.05 1.90 1.85 Saint Vincent and the Grenadines 3.64 3.10 2.85 2.55 2.24 2.13 2.05 1.97 Suriname 3.70 3.00 2.60 2.80 2.60 2.42 2.29 2.19 Trinidad and Tobago 3.22 2.80 2.10 1.73 1.61 1.64 1.69 1.74 United States Virgin Islands 3.70 3.09 3.09 2.50 2.23 2.15 2.06 1.98 3.40 3.12 2.83 2.63 2.51 2.37 2.30 2.22 3.93 3.42 3.02 2.73 2.50 2.26 2.09 1.98 The Caribbean a Latin America and the Caribbean b Source: conomic Commission for Latin America and the Caribbean (ECLAC), Database on Social Statistics and Indicators (BADEINSO) [online]. Information from the Latin E American and Caribbean Demographic Centre - Population Division of ECLAC, 2008 revision. Population Database and United Nations, Department of Economic and Social Affairs, Population Division, World Population Prospects, 2008 revision; Population database, published on CD-ROM. a Includes 24 economies: Anguilla, Antigua and Barbuda, Aruba, Bahamas, Barbados, British Virgin Islands, Cayman Islands, Cuba, Dominica, Dominican Republic, Grenada, Guadeloupe, Haiti, Jamaica, Martinique, Montserrat, Netherlands Antilles, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Trinidad and Tobago, Turks and Caicos Islands and United States Virgin Islands. b Includes 46 economies: Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivarian Republic of Venezuela, Brazil, British Virgin Islands, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Netherlands Antilles, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Turks and Caicos Islands, United States Virgin Islands and Uruguay. 224 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-4 Latin America: POVERTY AND INDIGENCE LEVELS, 1990-2009 (Percentages) Population below the poverty line a Country Year National total Urban areas Total Metropolitan area Other urban Population below the indigence line Rural areas National total Urban areas Total Metropolitan area Other urban Rural areas Argentina 1990 1999 2002 2006 2009 … … … … … … 23.7 45.4 21.0 11.3 21.2 19.7 41.5 19.3 9.6 … 28.5 49.6 22.8 13.3 … … … … … … … … … … … 6.7 20.9 7.2 3.8 5.2 4.8 18.6 6.7 3.1 … 8.8 23.3 7.9 4.5 … … … … … Bolivia (Plurinational State of) 1989 1999 2002 2007 … 60.6 62.4 54.0 52.6 48.7 52.0 42.4 … 45.0 48.0 40.6 … 63.9 58.2 44.9 … 80.7 79.2 75.8 … 36.4 37.1 31.2 23.0 19.8 21.3 16.2 … 17.5 18.8 15.4 … 29.0 25.0 17.4 … 64.7 62.9 59.0 Brazil 1990 1999 2002 2008 2009 48.0 37.5 37.8 25.8 24.9 41.2 32.9 34.4 22.8 22.1 … … … … 16.7 9.3 10.0 5.5 5.5 … … … … 23.4 12.9 12.6 7.3 7.0 … … … … 70.6 55.3 55.7 41.2 39.3 … … … … 46.1 27.1 26.4 16.5 15.2 Chile 1990 1998 2003 2006 2009 38.6 21.7 18.7 13.7 11.5 38.5 20.7 18.5 13.9 11.7 32.1 14.6 12.4 10.4 8.3 43.5 25.0 22.7 16.0 13.8 38.8 27.5 20.0 12.3 10.4 13.0 5.6 4.7 3.2 3.6 12.5 5.1 4.4 3.2 3.5 9.3 3.3 2.8 2.3 2.7 14.9 6.4 5.6 3.7 3.9 15.6 8.6 6.2 3.5 4.4 Colombia 1991 1999 2002 b 2008 b 2009 b 56.1 54.9 54.2 46.1 45.7 52.7 50.6 48.7 40.0 39.7 … 43.1 36.0 22.6 22.1 … 53.1 52.3 44.8 44.7 60.7 61.8 69.6 65.3 64.5 26.1 26.8 19.9 17.9 16.5 20.0 21.9 15.4 13.1 12.4 … 19.6 8.6 3.9 4.1 … 22.7 17.3 15.7 14.7 34.3 34.6 32.8 32.7 29.2 Costa Rica 1990 1999 2002 2008 2009 26.3 20.3 20.3 16.4 18.9 24.9 18.1 17.5 15.6 18.5 22.8 17.5 16.8 13.9 16.7 27.7 18.7 18.0 22.3 25.4 27.3 22.3 24.3 17.5 19.5 9.9 7.8 8.2 5.5 6.9 6.4 5.4 5.5 4.3 5.4 4.9 4.3 5.5 3.7 4.9 8.4 6.5 5.6 6.4 7.3 12.5 9.8 12.0 7.3 9.1 2002 2008 2009 47.1 44.3 41.1 42.4 42.0 39.3 … … … … … … 55.9 49.1 44.7 20.7 22.6 21.0 16.5 19.5 19.4 … … … … … … 28.6 29.0 24.3 Ecuador 1990 1999 2002 2008 2009 … … … 42.7 42.2 62.1 63.5 49.0 39.0 40.2 … … … … … … … … … … … … … 50.2 46.3 … … … 18.0 18.1 26.2 31.3 19.4 14.2 15.5 … … … … … … … … … … … … … 25.6 23.3 El Salvador 1995 1999 2001 2004 2009 54.2 49.8 48.9 47.5 47.9 45.8 38.7 39.4 41.2 42.3 34.7 29.8 32.1 33.2 32.6 55.1 48.7 47.7 48.6 49.5 64.4 65.1 62.4 56.8 57.6 21.7 21.9 22.1 19.0 17.3 14.9 13.0 14.3 13.8 12.8 8.8 7.7 9.9 8.4 7.3 20.1 19.0 19.2 18.8 16.8 29.9 34.3 33.3 26.6 25.2 Guatemala 1989 1998 2002 2006 69.4 61.1 60.2 54.8 53.6 49.1 45.3 42.0 … … … … … … … … 77.7 69.0 68.0 66.5 42.0 31.6 30.9 29.1 26.4 16.0 18.1 14.8 … … … … … … … … 50.2 41.8 37.6 42.2 Honduras 1990 1999 2002 2007 80.8 79.7 77.3 68.9 70.4 71.7 66.7 56.9 59.9 64.4 56.9 47.8 79.5 78.8 74.4 64.0 88.1 86.3 86.1 78.8 60.9 56.8 54.4 45.6 43.6 42.9 36.5 26.2 31.0 33.7 25.1 18.0 54.5 51.9 45.3 32.5 72.9 68.0 69.5 61.7 Mexico 1989 1998 2002 2008 47.7 46.9 39.4 34.8 42.1 38.9 32.2 29.2 … … … … … … … … 56.7 58.5 51.2 44.6 18.7 18.5 12.6 11.2 13.1 9.7 6.9 6.4 … … … 6.4 … … … 19.8 27.9 31.1 21.9 19.8 Dominican Republic Social Panorama of Latin America • 2010 225 Table A-4 (concluded) Population below the poverty line a Country Year National total Urban areas Total Metropolitan area Other urban Population below the indigence line Rural areas National total Urban areas Total Metropolitan area Other urban Rural areas Nicaragua 1993 1998 2001 2005 73.6 69.9 69.3 61.9 66.3 64.0 63.8 54.4 58.3 57.0 50.8 48.7 73.0 68.9 72.1 58.1 82.7 77.0 77.0 71.5 48.4 44.6 42.4 31.9 36.8 33.9 33.4 20.8 29.5 25.8 24.5 16.4 43.0 39.5 39.1 23.7 62.8 57.5 55.1 46.1 Panama 1991 1999 2002 2008 2009 … … 36.9 27.7 26.4 32.7 20.8 26.2 17.0 16.3 … … … … … … … … … … … … 54.6 46.3 43.9 … … 18.6 13.5 11.1 11.5 5.9 9.0 4.7 4.6 … … … … … … … … … … … … 34.6 28.8 22.3 Paraguay 1990 1999 2001 2008 2009 … 60.6 61.0 58.2 56.0 … 49.0 50.1 52.5 48.2 43.2 39.5 42.7 48.8 43.9 … 61.3 59.1 58.2 54.9 … 73.9 73.6 66.1 67.1 … 33.9 33.2 30.8 30.4 … 17.4 18.4 22.1 19.0 13.1 9.2 10.4 18.9 15.8 … 28.0 28.1 27.2 23.9 … 52.8 50.3 43.1 46.6 Peru 1997 1999 2001 c 2008 c 2009 c 47.6 48.6 54.8 36.2 34.8 33.7 36.1 42.0 23.5 21.1 … … … … … … … … … … 72.7 72.5 78.4 59.8 60.3 25.1 22.4 24.4 12.6 11.5 9.9 9.3 9.9 3.4 2.8 … … … … … … … … … … 52.7 47.3 51.3 29.7 27.8 Uruguay 1990 1999 2002 2008 2009 … … … 13.7 10.4 17.9 9.4 15.4 14.0 10.7 11.3 9.8 15.1 15.2 12.8 24.3 9.0 15.8 13.1 9.1 … … … 9.4 5.9 … … … 3.4 1.9 3.4 1.8 2.5 3.5 2.0 1.8 1.9 2.7 4.6 3.1 5.0 1.6 2.2 2.7 1.1 … … … 2.4 1.3 Venezuela (Bolivarian Republic of) d 1990 1999 2002 2008 39.8 49.4 48.6 27.6 38.6 … … … 29.2 … … … 41.2 … … … 46.0 … … … 14.4 21.7 22.2 9.9 13.1 … … … 8.0 … … … 14.5 … … … 21.3 … … … Latin America e 1980 1990 1999 2002 2007 2008 2009 40.5 48.3 43.9 44.0 34.1 33.0 33.1 29.5 41.4 37.2 38.4 28.9 27.6 27.8 … … … … … … … … … … … … … … 59.8 65.4 63.7 61.8 52.1 52.3 52.8 18.6 22.5 18.7 19.4 12.6 12.9 13.3 10.6 15.3 12.1 13.5 8.1 8.3 8.8 … … … … … … … … … … … … … … 32.7 40.4 38.2 37.8 28.2 29.5 30.0 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of household survey data from the respective countries. a Includes persons below the indigence line or living in extreme poverty. b Figures from the National Planning Department (DNP) and the National Administrative Department of Statistics (DANE) of Colombia. The values shown for 2002 on are not strictly comparable with those for earlier years owing to methodological changes made by DNP and DANE. c Figures from the Institute of Statistics and Informatics (INEI) of Peru. d From 1997, the sample design for the survey does not permit urban-rural breakdown. Figures therefore correspond to the national total. e Estimate for 18 countries of the region plus Haiti. 226 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-5 Latin America: POVERTY AND INDIGENCE LINES (PL and IL) (Per capita monthly values) Countries Year Urban Income reference period Currency a IL Rural PL IL Urban PL Variation b IL Currency in use Argentina 1990 c 1999 2002 2006 2009 September September October 2nd semester Year A $ $ $ $ Bolivia (Plurinational State of) 1989 1999 2002 2007 October Oct.-Nov. Oct.-Nov. Year Bs Bs Bs Bs 68 167 167 232 Brazil 1990 1999 2002 2008 2009 September September September September September Cr$ R$ R$ R$ R$ Chile 1990 1998 2003 2006 2009 November November November November November Colombia 1991 1999 2002 2008 2009 Costa Rica 255 928 511 856 72 143 99 198 138 276 165 342 Rural PL IL PL Dollars … … … … … … … … 5 791.0 1.0 3.6 3.1 3.7 44.2 71.6 27.5 45.1 44.6 88.4 143.3 55.0 90.2 92.1 … … … … … … … … 137 333 334 449 … 130 133 180 … 228 234 307 2.9 5.9 7.4 7.9 23.8 28.0 22.6 29.6 47.5 56.1 45.2 57.2 … 21.9 18.1 22.9 … 38.3 31.6 39.1 3 109 51 63 96 100 6 572 126 155 225 238 2 634 43 54 84 88 4 967 91 114 177 188 75.5 1.9 3.35 1.80 1.82 41.2 26.7 18.9 53.2 54.8 87.0 66.2 46.3 125.3 130.7 34.9 22.7 16.3 46.7 48.2 65.8 48.1 34.0 98.6 103.4 Ch$ Ch$ Ch$ Ch$ Ch$ 9 297 18 944 21 856 23 549 31 422 18 594 37 889 43 712 47 099 56 383 7 164 14 598 16 842 18 146 24 213 12 538 25 546 29 473 31 756 38 638 327.4 463.3 625.5 527.4 507.8 28.4 40.9 34.9 44.7 61.9 56.8 81.8 69.9 89.3 111.0 21.9 31.5 26.9 34.4 47.7 38.3 55.1 47.1 60.2 76.1 August August Year Year Year Col$ Col$ Col$ Col$ Col$ 18 093 69 838 79 941 124 310 128 600 36 186 139 716 204 086 292 973 305 781 14 915 57 629 58 820 92 449 95 319 26 102 100 851 134 958 195 775 204 448 645.6 1 873.7 2 504.2 1 967.7 2 166.8 28.0 37.3 31.9 63.2 59.4 56.1 74.6 81.5 148.9 141.1 23.1 30.8 23.5 47.0 44.0 40.4 53.8 53.9 99.5 94.4 1990 1999 2002 2008 2009 June June June June June ¢ ¢ ¢ ¢ ¢ 2 639 10 708 14 045 31 325 34 514 5 278 21 415 28 089 58 245 63 099 2 081 8 463 11 132 24 423 26 910 3 642 14 811 19 481 40 165 43 626 89.7 285.3 358.1 519.7 576.7 29.4 37.5 39.2 60.3 59.9 58.9 75.1 78.5 112.1 109.4 23.2 29.7 31.1 47.0 46.7 40.6 51.9 54.4 77.3 75.7 Dominican Republic 2002 2008 2009 September September September RD$ RD$ RD$ 793 2 091 2 080 1 569 4 010 3 933 714 1 882 1 872 1 285 3 263 3 206 18.8 35.0 36.2 42.2 59.7 57.5 83.5 114.5 108.6 38.0 53.8 51.7 68.4 93.2 88.6 Ecuador 1990 1999 2002 2008 2009 November October November November November S/. S/. US$ US$ US$ 18 465 36 930 301 716 603 432 35 69 49 91 50 94 … … … 34 36 … 854.8 … 15 656.8 … 1.0 57 1.0 59 1.0 21.6 19.3 34.6 48.7 50.4 43.2 38.5 69.1 90.6 94.2 … … … 34.3 35.6 … … … 56.5 58.7 El Salvador 1995 1999 2001 2009 Jan.-Dec. Jan.-Dec. Jan.-Dec. Year ¢ ¢ ¢ ¢ 254 293 305 417 508 586 610 829 158 189 197 270 315 378 394 536 8.8 8.8 8.8 8.8 29.0 33.5 34.9 47.7 58.1 66.9 69.7 94.8 18.0 21.6 22.5 30.8 35.9 43.2 45.0 61.2 Guatemala 1989 1998 2002 2006 April Dec.97-Dec.98 Oct.-Nov. Mar.-Sep. Q Q Q Q 64 260 334 467 127 520 669 935 50 197 255 362 88 344 446 633 2.7 6.4 7.7 7.6 23.6 40.7 43.6 61.5 47.1 81.5 87.2 123.0 18.7 30.8 33.3 47.6 32.7 54.0 58.2 83.3 Social Panorama of Latin America • 2010 227 Table A-5 (concluded) Countries Year Urban Income reference period Currency a IL Rural PL IL Urban PL Variation b IL Currency in use Honduras 1990 1999 2002 2007 August August August August L L L L 115 561 689 945 229 1 122 1 378 1 872 Mexico 1989 1998 2002 2008 3rd quarter 3rd quarter 3rd quarter Aug.-Nov. 08 $ MN$ MN$ MN$ Nicaragua 1993 1998 2001 2005 21 Feb.-12 Jun. 15 Apr.-31 Aug. 30 Apr.-31 Jul. Jul.-Oct. C$ C$ C$ C$ 167 275 369 491 334 550 739 981 129 212 284 378 Panama 1991 1999 2002 2008 2009 August July July July July B B B B B 35.0 40.7 40.7 54.8 57.4 70.1 81.4 81.4 103.1 105.8 Paraguay 1990 d 1999 2001 2008 2009 Jun., Jul., Aug. Jul.-Dec. Sep.00-Aug. 01 Oct.-Dec. Oct.-Dec. G G G G G 43 242 138 915 155 461 295 998 312 371 Peru 1997 1999 2001 4th quarter 4th quarter 4th quarter N$ N$ N$ Uruguay 1990 1999 2002 2008 2009 2nd semester Year Year Year Year NUr$ $ $ $ $ Venezuela (Bolivarian Republic of) 1990 1999 e 2002 e 2008 e 2nd semester 2nd semester 2nd semester 2nd semester Bs Bs Bs Bs PL IL PL Dollars 141 691 849 1 155 4.3 14.3 16.6 18.9 26.5 39.3 41.6 50.0 52.9 78.6 83.3 99.1 18.6 27.7 29.3 35.2 32.6 48.4 51.3 61.1 68 810 120 418 385 674 530 928 719 1 227 2 510.0 9.5 9.9 11.6 34.4 56.8 75.0 87.1 68.8 113.6 150.1 169.3 27.4 40.7 53.6 62.2 48.0 71.3 93.8 106.3 225 370 498 661 4.6 10.4 13.4 16.9 36.6 26.4 27.6 29.1 73.3 52.7 55.2 58.2 28.2 20.3 21.3 22.4 49.4 35.5 37.2 39.2 … … 31.5 42.4 44.5 … … 55.0 70.5 72.6 1.0 1.0 1.0 1.0 1.0 35.0 40.7 40.7 54.8 57.4 70.1 81.4 81.4 103.1 105.8 … … 31.5 42.4 44.5 … … 55.0 70.5 72.6 86 484 277 831 310 922 562 817 580 796 … 106 608 119 404 226 691 239 191 … 186 565 208 956 379 950 393 347 1 207.8 3 311.4 3 718.3 4 712.7 4 786.9 35.8 42.0 41.8 62.8 65.3 71.6 83.9 83.6 119.4 121.3 … 32.2 32.1 48.1 50.0 … 56.3 56.2 80.6 82.2 103 109 117 192 213 230 83 89 102 128 141 159 2.7 3.5 3.5 42.2 31.2 34.0 84.3 61.2 66.8 31.6 25.5 29.5 55.3 40.5 46.0 41 972 640 793 1 588 1 652 83 944 1 280 1 586 2 957 3 095 … … … 1 223 1 298 … … … 2 013 2 148 1 358.0 11.3 21.3 21.0 22.6 30.9 56.5 37.3 75.8 73.2 61.8 112.9 74.6 141.1 137.1 … … … 58.4 57.5 … … … 96.1 95.2 1 924 3 848 48 737 95 876 80 276 154 813 301 540 525 958 1 503 … … … 2 630 … … … 49.4 626.3 1 161.0 2 147.0 39.0 77.8 69.2 140.5 77.9 153.1 133.4 245.0 30.4 … … … 53.2 … … … 86 400 172 800 537 1 074 742 1 484 1 006 1 955 Source: Economic Commission for Latin America and the Caribbean (ECLAC). a National currencies: Argentina: (A) Austral; ($) Peso Bolivia (Plurinational State of): (Bs) Boliviano Brazil: (Cr$) Cruzeiro; (R$) Real Chile: (Ch$) Peso Colombia: (Col$) Peso Costa Rica: (¢ ) Colón Dominican Republic: (RD$) Peso Ecuador: (S/.) Sucre, 1990-2001. Since 2002, United States dollar (US$). El Salvador: (¢ ) Colón Guatemala: (Q) Quetzal Honduras: (L) Lempira Mexico: ($) Peso; (MN$) New Peso Nicaragua: (C$) Córdoba Panama: (B/.) Balboa Paraguay: (G/.) Guaraní Peru: (N$) Peso Uruguay: (Nur$) New Peso; ($) Peso Venezuela (Bolivarian Republic of): (Bs) Bolívar b International Monetary Fund (IMF) “rf” series. c Greater Buenos Aires. d Asunción. e National total. 81 395 485 665 Rural 228 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-6 Latin America: MALE AND FEMALE ECONOMIC PARTICIPATION RATES, BY AGE GROUP, 1990-2009 Age group Country Males Year Females Total 15 to 24 years 25 to 34 years 35 to 49 years 50 and over Total 15 to 24 years 25 to 34 years 35 to 49 years 50 and over Argentina a 1990 b 1999 2002 2006 2009 76 74 72 75 74 62 53 48 54 51 97 94 93 94 93 97 97 96 96 96 55 59 60 64 61 38 44 46 50 49 41 36 35 38 34 52 62 64 67 68 52 61 67 69 70 19 27 27 34 33 Bolivia (Plurinational State of) 1997 1999 2002 2007 82 81 83 82 60 59 64 61 94 94 94 94 99 98 98 99 83 82 85 82 60 62 62 62 46 48 46 44 66 67 72 69 73 75 75 77 56 61 58 62 Brazil 1990 1999 2002 2008 2009 84 82 81 80 80 81 75 73 72 71 96 95 94 95 95 95 94 94 94 94 63 64 63 63 62 44 54 56 58 58 47 52 53 54 54 54 67 69 73 74 52 66 68 71 72 22 33 33 36 36 Chile 1990 1998 2003 2006 2009 74 75 73 73 71 51 46 42 43 43 94 93 92 92 91 95 96 96 95 94 58 64 64 65 62 33 39 42 43 42 27 30 30 30 30 44 54 58 61 64 42 50 56 59 59 18 23 27 29 28 Colombia 1991 1999 2002 2008 2009 85 81 82 79 81 71 64 67 58 61 97 97 97 95 96 98 97 97 96 97 76 71 70 68 71 44 50 54 51 54 40 44 49 39 43 57 66 68 67 70 52 63 67 66 70 25 26 31 32 36 Costa Rica 1990 1999 2002 2008 2009 83 82 79 78 77 74 68 63 60 58 96 96 97 96 96 96 96 96 97 96 64 64 63 66 64 33 39 41 45 45 35 37 35 38 36 41 48 54 62 62 39 49 53 57 58 12 18 22 25 27 2002 2008 65 68 40 43 82 89 86 94 47 48 35 41 19 31 46 59 54 62 18 20 Dominican Republic 2002 2008 2009 75 75 73 54 56 50 91 90 90 94 93 93 68 66 66 39 40 39 29 29 26 54 52 53 54 57 56 22 24 24 Ecuador 1990 a 1999 a 2002 a 2008 2009 80 82 81 82 80 56 64 60 62 60 95 97 96 96 95 98 98 98 98 98 78 76 74 78 77 43 54 53 52 51 33 45 40 40 39 54 65 65 63 63 56 67 67 65 65 31 36 41 42 43 El Salvador 1995 1999 2001 2009 82 78 79 79 70 65 67 63 95 93 93 95 96 94 95 96 75 70 70 71 42 44 44 46 32 34 33 32 55 58 59 61 57 59 61 63 29 31 32 34 Guatemala 1989 1998 2002 2006 90 88 91 88 82 79 85 80 98 97 96 97 98 98 98 98 84 84 86 84 28 46 49 47 28 41 45 41 32 49 54 54 32 55 59 57 22 38 39 39 Honduras 1990 1999 2002 2007 87 87 85 83 78 78 75 70 96 98 96 95 97 97 97 97 81 81 80 80 32 44 38 40 26 36 30 28 39 52 46 51 42 57 49 52 25 34 29 33 Mexico 1989 1998 2002 2008 79 82 81 81 64 68 65 65 94 94 94 96 94 94 95 97 73 73 75 71 30 41 43 45 26 37 34 36 38 48 51 55 35 48 54 58 21 31 32 32 Cuba c Social Panorama of Latin America • 2010 229 Table A-6 (concluded) Age group Country Males Year Females Total 15 to 24 years 25 to 34 years 35 to 49 years 50 and over Total 15 to 24 years 25 to 34 years 35 to 49 years 50 and over Nicaragua 1993 1998 2001 2005 77 85 86 84 62 77 79 74 89 95 97 95 91 94 96 95 70 77 77 79 36 43 46 44 24 31 36 32 47 56 55 53 51 56 61 59 26 31 36 34 Panama 1991 a 1999 a 2002 2008 2009 72 77 80 82 81 52 61 63 67 65 95 97 97 98 97 96 96 97 98 97 48 58 67 69 69 48 50 45 47 48 39 42 34 34 34 66 67 61 62 63 65 68 61 65 65 20 26 24 31 34 Paraguay 1990 d 1999 2001 2008 2009 84 85 85 85 85 69 73 76 73 77 97 96 96 97 96 99 96 97 97 96 75 80 77 78 76 50 48 53 54 56 51 39 46 46 50 63 59 64 64 67 58 60 64 67 67 27 38 42 45 45 Peru 1997 1999 2001 2008 2009 85 78 79 84 84 70 61 61 68 68 97 91 92 94 94 98 94 95 97 97 83 76 75 80 81 64 58 58 65 66 54 48 45 55 54 73 67 69 74 75 76 69 72 78 80 53 49 48 57 58 Uruguay 1990 a 1999 a 2002 a 2008 2009 75 73 72 75 75 68 67 63 61 61 98 96 96 95 96 97 97 96 96 97 54 50 51 59 60 44 50 50 54 55 47 50 47 45 45 69 74 76 78 79 64 74 76 78 78 21 26 28 36 36 Venezuela (Bolivarian Republic of) 1990 1999 2002 2008 79 83 84 79 59 66 67 56 93 97 97 95 96 97 97 97 74 74 74 72 35 47 55 50 23 35 42 31 48 60 69 65 49 63 71 69 20 30 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 respective countries. a Urban total. b Greater Buenos Aires. c National Statistical Office (ONE) of Cuba, on the basis of tabulations of the National Occupation Survey. d Asunción metropolitan area. 230 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-7 Latin America: BREAKDOWN OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY, 1990-2009 (Population aged 15 and over, in percentages) Own-account and unpaid family workers Wage or salary earners Country Year Employers Total Private sector Public sector Total a Professional Non-professional, Domestic and technical non-technical employment Total b Non-professional, non-technical Argentina c 1990 d 1999 2002 2006 2009 5.4 4.4 4.0 4.1 4.4 69.0 72.6 73.1 75.8 75.9 … 15.5 21.7 16.2 15.9 69.0 57.1 51.3 59.5 60.0 6.9 9.1 10.3 9.4 10.3 56.4 42.2 35.1 42.8 42.8 5.7 5.8 6.0 7.4 6.9 25.6 23.0 22.9 20.1 19.6 23.0 18.6 18.4 16.2 15.3 Bolivia (Plurinational State of) 1989 e 1999 2002 2007 2.2 2.8 4.3 5.2 54.0 29.8 30.4 36.2 17.9 6.6 6.7 8.3 36.1 23.2 23.7 27.9 4.3 4.1 2.6 2.5 26.0 17.2 18.8 22.1 5.8 1.9 2.3 3.3 43.8 67.3 65.3 58.5 41.0 66.1 63.9 57.9 Brazil 1990 1999 2002 2008 2009 4.7 4.1 4.2 4.5 4.3 65.5 58.8 61.9 65.8 66.4 … 11.1 11.0 11.3 11.6 65.5 47.7 50.9 54.5 54.8 11.8 8.8 3.9 6.1 6.4 48.0 31.5 39.3 41.2 40.5 5.6 7.4 7.7 7.2 7.8 29.9 37.1 33.8 29.7 29.3 28.8 35.5 32.4 27.1 26.7 Chile 1990 1998 2003 2006 2009 2.6 4.0 3.9 3.1 3.1 73.0 74.6 74.6 75.7 76.3 … … 9.3 9.8 11.6 73.0 74.6 65.3 65.9 64.7 11.4 15.3 11.0 10.3 12.6 55.3 53.8 48.0 50.0 47.2 6.3 5.5 6.2 5.6 4.8 24.5 21.4 21.4 21.3 20.6 22.9 17.1 16.3 17.0 17.7 Colombia 1991 1999 2002 2008 2009 5.1 4.0 4.9 4.8 5.0 58.6 53.6 49.8 44.5 42.8 6.6 6.8 6.4 5.2 4.6 52.0 46.7 43.4 39.2 38.3 3.9 4.3 3.2 3.6 3.2 43.9 38.1 35.2 32.0 31.4 4.2 4.4 5.0 3.6 3.7 36.3 42.4 45.3 45.8 47.7 34.9 40.6 43.1 42.9 44.9 Costa Rica 1990 1999 2002 2008 2009 5.3 8.1 7.9 7.5 7.2 70.0 71.0 68.3 72.9 72.7 17.0 13.0 14.0 14.1 15.6 53.0 58.0 54.3 58.8 57.1 3.6 5.8 9.2 11.8 11.1 45.1 46.7 40.7 42.3 41.1 4.3 5.4 4.3 4.7 4.9 24.7 20.9 23.8 19.6 20.1 23.4 19.7 21.6 17.2 17.7 Dominican Republic 2002 2008 2009 3.2 4.0 4.8 53.1 51.9 50.8 12.0 11.2 12.2 41.1 40.7 38.6 5.9 6.8 6.0 30.9 28.0 27.0 4.3 5.9 5.6 43.8 44.1 44.3 42.2 42.1 41.9 Ecuador 1990 c 1999 c 2002 c 2008 2009 5.0 8.8 6.9 5.2 4.1 58.9 59.1 58.4 54.9 53.4 17.5 10.7 11.5 8.0 8.1 41.4 48.4 46.9 46.8 45.3 4.5 7.0 6.4 5.6 5.3 32.4 36.0 36.0 37.8 36.7 4.5 5.4 4.5 3.4 3.4 36.1 32.1 34.7 40.0 42.5 34.5 31.5 32.9 38.6 41.1 El Salvador 1995 1999 2001 2009 6.1 4.4 4.6 4.1 56.8 59.8 56.4 55.4 8.7 9.1 8.5 7.6 48.1 50.7 48.0 47.8 4.6 6.1 5.1 5.1 39.5 39.7 38.2 38.2 3.9 4.9 4.7 4.6 37.0 35.8 39.0 40.5 36.4 35.1 38.1 39.2 Guatemala 1989 1998 2002 2006 1.5 3.2 6.5 3.5 48.6 49.8 43.5 48.5 7.3 4.5 3.6 5.0 41.3 45.4 39.9 43.5 2.8 3.7 3.6 4.5 34.6 39.3 33.8 35.8 3.8 2.4 2.5 3.2 49.9 47.0 50.0 48.1 48.7 45.9 49.2 47.0 Honduras 1990 1999 2002 2007 1.0 4.6 2.8 2.3 48.2 46.1 46.5 47.5 8.5 6.6 5.6 6.5 39.7 39.6 40.9 41.0 2.4 3.8 4.0 6.6 33.3 32.2 34.3 31.6 4.0 3.6 2.6 2.8 50.8 49.3 50.7 50.2 50.0 48.9 49.5 41.2 Social Panorama of Latin America • 2010 231 Table A-7 (concluded) Own-account and unpaid family workers Wage or salary earners Country Year Employers Total Private sector Public sector Total a Professional Non-professional, Domestic and technical non-technical employment Total b Non-professional, non-technical Mexico 1989 1998 2002 2008 3.0 4.7 3.9 5.0 67.0 62.0 65.7 72.1 … 10.9 11.2 11.3 67.0 51.1 54.5 60.8 6.2 4.3 4.5 6.5 58.1 43.3 45.5 49.8 2.7 3.5 4.5 4.5 30.0 33.4 30.3 23.0 28.9 32.0 29.1 21.8 Nicaragua 1993 1998 2001 2005 0.5 3.6 5.0 4.5 50.9 52.5 49.8 48.5 14.2 … 9.0 7.8 36.7 52.5 40.8 40.7 4.2 9.3 2.7 3.6 26.9 37.5 34.1 33.5 5.5 5.7 4.0 3.6 48.6 43.9 45.2 47.0 41.6 43.0 44.2 46.3 Panama 1991 c 1999 c 2002 2008 2009 3.0 3.2 2.9 3.1 3.1 78.6 76.7 62.0 65.2 63.9 30.1 21.1 16.1 14.6 14.6 48.5 55.6 45.9 50.7 49.2 9.0 12.1 4.6 5.4 5.6 32.1 37.4 35.7 39.9 38.7 7.4 6.1 5.6 5.4 4.9 18.4 20.1 35.1 31.6 33.1 17.2 18.9 34.0 30.5 31.8 Paraguay 1990 f 1999 2001 2008 2009 8.9 5.2 5.8 5.0 5.5 68.4 46.4 44.9 50.4 48.1 11.9 8.0 7.1 8.8 8.4 56.5 38.4 37.8 41.6 39.7 4.3 3.2 3.4 4.1 3.4 41.7 28.4 26.8 30.1 29.6 10.5 6.8 7.6 7.5 6.7 22.7 48.4 49.3 44.6 46.3 21.2 47.2 47.8 43.0 44.5 Peru 1997 1999 2001 2008 2009 5.7 5.9 5.1 5.6 5.5 40.9 40.0 40.2 42.2 42.3 9.4 8.6 8.9 9.1 9.4 31.5 31.4 31.2 33.1 32.9 2.4 2.1 4.2 5.2 5.3 27.3 26.7 24.7 25.3 25.2 1.8 2.6 2.3 2.6 2.4 53.3 54.1 54.7 52.2 52.2 52.7 53.2 53.0 50.8 50.5 Uruguay 1990 c 1999 c 2002 c 2008 2009 5.8 4.0 3.7 4.8 4.8 74.2 72.4 70.5 71.1 71.4 21.8 16.2 17.3 14.3 13.9 52.4 56.1 53.2 56.8 57.5 9.7 6.5 5.9 5.9 6.2 35.8 42.1 37.4 42.1 42.4 6.9 7.5 9.9 8.7 8.9 20.1 23.6 25.8 24.1 23.7 19.3 20.6 21.8 20.3 20.0 Venezuela (Bolivarian Republic of) 1990 1999 2002 2008 7.5 5.1 5.4 4.0 66.6 57.9 54.7 58.1 19.3 14.9 13.8 17.9 47.2 43.0 40.8 40.2 5.0 4.9 3.9 5.2 36.4 36.1 34.3 33.2 5.8 2.0 2.6 1.7 25.9 36.9 39.9 37.9 25.0 35.3 38.2 35.8 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries. a The figures for Brazil (1990), Chile (1990, 1998), Mexico (1989) and Nicaragua (1998) include public sector wage-earners. b Includes professional and technical workers. c Urban total. d Greater Buenos Aires. e Eight departmental capitals plus El Alto. f Asunción metropolitan area. 232 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-8 Latin America: URBAN POPULATION EMPLOYED IN LOW-PRODUCTIVITY SECTORS OF THE LABOUR MARKET, 1990-2009 (Percentages of the total urban employed population) Microenterprises a Unskilled self-employed workers b Wage or salary earners Country Year Argentina d 1990 1999 2002 2006 2009 Bolivia (Plurinational State of) 1989 1999 2002 2004 2007 Brazil f Total Employers Total Professional and technical Nonprofessional, non-technical Domestic employment Total c Manufacturing Commerce and and services construction 44.1 40.7 42.1 39.7 39.0 3.8 3.2 2.9 2.7 3.0 11.7 15.0 16.1 14.3 14.5 0.4 1.0 1.1 1.0 1.4 11.4 13.9 15.0 13.3 13.2 5.7 5.3 5.6 7.5 6.6 23.0 17.3 17.5 15.2 14.8 6.9 5.0 6.8 5.0 5.0 16.1 12.2 10.7 10.1 9.3 62.1 62.9 65.3 70.0 62.7 2.2 2.6 3.4 4.2 5.4 13.7 12.7 13.9 18.2 15.2 1.6 1.0 0.7 1.4 0.5 12.1 11.7 13.2 16.8 14.7 5.4 2.7 3.7 4.6 5.3 40.8 44.9 44.3 43.0 36.8 9.7 12.1 12.5 10.9 8.5 29.8 30.2 28.3 28.2 25.2 1990 1999 2002 2008 2009 48.0 46.7 46.0 40.2 41.1 … 2.3 2.3 2.4 2.4 20.9 10.1 10.6 10.1 10.3 4.4 1.7 0.6 0.8 0.9 16.5 8.3 10.0 9.3 9.4 5.8 8.5 8.6 7.8 8.4 21.3 25.8 24.6 20.0 19.9 3.5 5.1 6.7 5.9 6.1 15.8 16.1 13.7 10.7 10.7 Chile 1990 1998 2003 2006 2009 38.9 34.2 32.9 30.6 30.0 0.8 2.6 2.4 1.7 1.1 10.3 10.7 9.0 7.2 7.1 0.9 1.0 0.8 0.7 0.8 9.4 9.7 8.2 6.5 6.3 7.0 5.8 6.5 5.8 5.0 20.9 15.1 14.9 15.9 16.8 5.7 4.1 4.8 4.8 4.1 14.0 10.1 9.3 10.1 11.9 Colombia 1991 1999 2002 2008 2009 … … … 59.3 60.5 … … … 3.9 4.1 … … … 11.5 11.2 … … … 0.3 0.3 … … … 11.1 10.9 5.3 5.2 5.5 4.0 4.2 27.1 35.5 39.1 39.8 40.9 6.4 7.5 8.1 8.4 8.2 19.9 26.6 28.0 29.4 30.2 Costa Rica 1990 1999 2002 2008 2009 36.6 41.2 40.2 36.9 36.1 4.4 6.0 6.3 5.7 5.5 10.4 13.1 12.2 11.6 11.2 0.8 1.4 1.4 1.6 1.7 9.6 11.7 10.8 10.0 9.5 4.3 5.1 4.0 4.4 4.5 17.5 17.1 17.7 15.2 14.9 6.4 4.4 4.7 3.4 3.6 10.1 11.8 12.2 11.2 10.6 Dominican Republic 2002 2008 2009 54.1 49.9 50.0 3.2 3.4 3.5 14.0 5.7 5.9 1.7 0.6 0.4 12.3 5.1 5.6 4.3 5.6 5.8 32.6 35.2 34.8 7.4 8.2 7.6 21.9 22.9 23.0 Ecuador 1990 1999 2002 2008 2009 53.7 58.3 55.8 56.9 56.5 3.7 7.2 4.9 4.9 3.6 11.7 14.9 14.1 16.0 15.9 0.6 1.6 0.9 1.1 1.0 11.1 13.2 13.3 14.9 14.9 4.3 5.4 4.4 4.2 4.1 34.0 30.9 32.3 31.8 32.8 7.8 5.6 6.9 5.2 5.6 23.9 23.3 23.2 24.6 24.6 El Salvador 1995 1999 2001 2009 50.6 51.7 53.7 56.4 5.0 4.2 4.5 4.0 10.5 14.5 14.3 14.7 0.2 0.8 0.8 0.8 10.3 13.7 13.5 13.9 4.3 4.2 4.2 4.6 30.9 28.8 30.7 33.1 8.1 6.5 6.4 6.1 20.2 19.8 22.3 23.7 Guatemala 1989 1998 2002 2006 53.3 63.4 55.2 56.1 2.1 3.7 5.6 4.5 14.5 22.3 13.7 15.2 0.8 2.4 0.8 1.2 13.7 19.9 12.9 14.1 6.6 3.8 3.8 3.9 30.0 33.6 32.2 32.5 7.2 8.1 8.2 7.5 14.8 20.5 18.8 19.4 Honduras 1990 1999 2002 2007 52.5 54.1 55.7 42.9 1.1 5.3 3.7 3.0 13.6 12.0 14.0 10.3 0.7 1.0 1.2 1.1 12.9 11.0 12.9 9.2 6.5 4.6 4.0 3.8 31.3 32.2 34.0 25.8 8.7 7.1 9.5 9.1 18.5 21.4 19.7 12.7 e Social Panorama of Latin America • 2010 233 Table A-8 (concluded) Microenterprises a Unskilled self-employed workers b Wage or salary earners Country Year Total Employers Total Professional and technical Nonprofessional, non-technical Domestic employment Total c Manufacturing Commerce and and services construction Mexico g 1989 1998 2002 2008 … 43.6 46.8 43.3 … 3.6 3.3 3.5 … 15.8 18.3 20.2 … 1.0 1.3 1.8 … 14.8 16.9 18.4 2.7 4.1 4.7 4.6 18.6 20.0 20.6 15.0 2.9 3.1 4.1 2.7 12.5 16.2 15.9 12.0 Nicaragua 1993 1998 2001 2005 48.9 59.4 58.3 57.6 0.6 3.1 3.8 4.7 13.5 16.3 16.7 14.7 1.7 1.8 0.7 0.6 11.8 14.5 16.0 14.0 6.3 6.5 4.5 4.1 28.5 33.5 33.3 34.1 7.7 4.4 5.5 7.8 17.0 25.2 24.1 22.5 Panama 1991 1999 2002 2008 2009 32.3 33.9 38.2 35.6 35.4 1.8 2.2 2.3 2.7 2.5 5.9 7.0 8.8 7.9 7.7 0.8 0.8 0.7 0.7 0.6 5.1 6.2 8.1 7.2 7.1 7.4 6.0 6.7 6.3 5.5 17.2 18.8 20.4 18.7 19.6 3.9 4.3 4.4 3.8 4.3 11.5 13.7 15.0 14.1 14.4 Paraguay 1990 1999 2001 2008 2009 54.7 58.5 60.9 55.7 58.5 6.9 5.1 6.6 5.3 5.1 16.4 15.8 14.6 14.2 17.4 1.1 1.0 1.4 1.2 1.5 15.3 14.9 13.1 13.0 16.0 10.0 9.0 10.2 9.1 8.4 21.4 28.6 29.5 27.1 27.6 5.3 5.3 5.3 4.9 5.5 15.5 20.7 21.2 19.4 18.6 Peru 1997 1999 2001 2008 2009 60.8 63.8 62.2 59.0 57.6 5.0 4.7 4.2 4.7 4.9 13.1 14.7 14.6 12.9 12.2 0.5 0.5 1.0 1.0 1.0 12.7 14.2 13.6 11.9 11.2 2.3 3.5 3.2 3.3 3.1 40.3 40.9 40.2 38.1 37.4 5.6 5.4 5.2 5.1 5.0 30.4 31.5 29.3 28.3 28.0 Uruguay 1990 1999 2002 2008 2009 40.8 41.4 45.7 42.7 42.6 3.9 2.4 2.4 2.9 3.0 10.6 10.9 11.6 11.9 11.6 1.1 0.6 0.6 0.6 0.6 9.4 10.4 11.0 11.3 11.1 6.9 7.5 9.9 9.0 9.1 19.4 20.6 21.8 19.0 18.8 5.6 7.0 8.1 6.1 6.0 13.5 12.6 12.5 11.3 11.2 Venezuela (Bolivarian Republic of) i 1990 1999 2002 2008 39.1 53.8 56.5 49.8 4.9 3.9 4.2 3.1 6.6 12.5 11.5 9.3 0.2 0.5 0.4 0.5 6.4 12.1 11.1 8.8 6.3 2.0 2.6 1.7 21.4 35.3 38.2 35.8 4.1 6.7 6.5 7.0 15.3 23.7 26.4 24.1 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 respective countries. a Refers to establishments employing up to five persons. In the case of the Bolivarian Republic of Venezuela, the Dominican Republic, El Salvador, Panama (up to 2002), the Plurinational State of Bolivia (1999 and 2002) and Uruguay (1990) establishments with up to four employees were counted. b Refers to own-account and unpaid family workers without professional or technical skills. c Includes persons employed in agriculture, forestry, hunting and fishing. d Greater Buenos Aires. e Eight departmental capitals plus El Alto. f Up to 1990, the category of “microenterprises” referred to wage-earners with no employment contract. Since 1993, however, this category refers to wage-earners in establishments employing up to five persons. g The 1994 survey does not contain information on the size of the establishments employing wage-earners. h Asunción metropolitan area. i From 1997 on, the sample design for the survey does not permit urban-rural breakdown. Figures therefore correspond to the national total. 234 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-9 Latin America: OPEN UNEMPLOYMENT RATES BY SEX AND AGE IN URBAN AREAS, AROUND 1990, 1999, 2002, 2008 AND 2009 a Age groups 45 and over 4.9 13.0 15.7 … 9.3 4.3 16.1 22.1 … 7.5 3.0 13.2 10.3 … 6.6 Total 9.4 4.5 4.4 … … 17.4 9.5 7.1 … … 8.5 4.7 5.6 … … 5.1 2.5 3.1 … … 6.6 1.9 1.9 … … Males 9.5 3.8 3.2 … … 18.2 7.9 5.3 … … 7.5 3.3 3.4 … … 5.5 1.5 2.1 … … 8.5 2.6 2.2 … … Females 9.1 5.3 5.8 … … 16.5 11.6 9.5 … … 9.9 6.4 8.4 … … 4.6 3.6 4.2 … … 3.8 0.9 1.5 … … Total 3.8 9.6 9.3 7.1 8.3 6.9 18.3 17.9 15.5 17.8 3.8 9.2 9.0 7.3 8.6 2.1 6.1 6.0 4.4 5.3 1.2 4.3 4.2 2.8 3.5 Males 3.9 7.8 7.5 5.2 6.1 6.9 15.1 14.6 11.9 13.9 4.0 6.9 6.4 4.6 5.8 2.4 4.7 4.6 2.8 3.6 1.5 4.1 4.1 2.3 2.8 Females 3.5 12.1 11.9 9.6 11.0 6.8 23.0 22.4 20.5 23.1 3.4 12.3 12.3 10.5 12.0 1.5 7.8 7.8 6.2 7.2 0.5 4.5 4.5 3.5 4.5 Total 8.3 9.9 10.4 … 10.2 16.5 21.3 22.0 … 24.9 7.9 9.6 10.7 … 11.3 5.1 7.1 7.8 … 7.2 5.2 6.1 7.2 … 5.6 Males 7.7 9.0 … 8.9 15.0 19.5 21.0 … 22.4 7.2 8.7 9.4 … 10.4 4.8 6.3 7.1 … 5.9 5.4 6.3 7.3 … 4.8 Females 9.6 11.3 11.7 … 12.2 19.0 24.0 23.6 … 28.3 9.4 11.1 12.6 … 12.7 5.7 8.6 9.1 … 9.0 4.5 5.6 6.9 … 7.0 Total 7.2 16.3 15.6 11.3 12.1 14.9 30.6 28.2 22.8 23.4 6.9 16.0 15.5 11.9 12.2 3.3 11.4 10.9 7.7 8.7 2.4 7.9 8.9 6.2 7.1 Males 4.8 12.5 12.6 4.2 11.6 11.5 2.2 5.4 5.8 2.2 7.6 8.7 5.9 6.7 5.2 15.5 14.1 10.8 12.2 2.8 8.6 9.4 6.9 7.8 Bolivia (Plurinational State of) Brazil Chile Colombia Females Costa Rica 9.6 8.9 9.4 10.2 23.9 23.0 18.1 18.3 8.9 8.7 11.4 22.0 19.8 14.8 15.8 22.4 39.8 35.2 29.6 30.8 11.0 22.0 20.7 16.0 16.8 8.3 8.5 2009 … 25.1 2008 … 10.4 15.6 26.3 36.3 2002 6.4 16.5 19.5 1999 5.6 Females 2008 … 2002 6.0 4.2 12.7 16.7 1999 … 4.4 2008 3.8 12.9 14.1 … 2002 5.7 8.0 14.8 1999 … 3.9 1990 4.1 11.6 18.1 7.5 2009 8.3 … 2008 … 5.0 11.3 15.3 2002 4.9 12.0 15.4 … 19.5 1999 … 21.8 8.1 11.5 22.8 31.7 1990 9.1 13.0 24.3 33.8 … 2009 … 5.7 13.4 18.5 2008 5.9 14.7 19.0 Males 2002 Total 1999 Argentina (Greater Buenos Aires) 1990 Sex 1990 35 to 44 years Country 2009 25 to 34 years 1990 15 to 24 years 2009 Total 6.4 4.9 7.8 8.3 12.7 14.1 11.0 17.9 3.7 5.3 5.2 4.8 7.4 2.4 3.1 3.7 2.8 5.0 2.4 2.3 2.9 2.2 3.3 4.8 5.6 4.1 6.6 7.6 10.9 12.4 9.6 15.5 3.0 4.1 4.5 3.5 5.8 2.0 2.4 2.9 2.3 3.7 2.5 2.1 2.8 2.1 3.1 5.8 8.0 7.9 6.3 9.9 10.0 16.0 17.3 13.4 22.1 5.3 7.5 6.4 6.6 9.8 3.0 4.5 5.0 3.7 6.9 2.1 2.7 3.2 2.4 3.7 Total 5.4 6.3 2.3 1.6 … … … 6.4 3.8 … … … 3.4 2.2 … … … 1.7 1.5 … … … 0.8 0.7 … Males 3.6 4.3 1.9 1.5 … … … 6.1 3.5 … … … 2.8 1.9 … … … 1.3 1.4 … … … 0.6 0.7 … Females 8.5 9.6 2.9 1.8 … … … 6.8 4.1 … … … 4.2 2.6 … … … 2.3 1.6 … … … 1.1 0.6 … Total … … 6.4 4.7 5.7 … … 12.5 9.4 13.3 … … 8.3 5.6 5.9 … … 3.7 3.6 3.2 … … 2.3 1.3 2.6 Males … … 4.5 3.3 4.1 … … 6.2 8.4 … … 5.4 4.6 4.7 … … 2.3 1.6 2.0 … … 2.0 1.4 2.4 Females Ecuador 5.9 4.0 Females Dominican Republic 4.5 Males Cuba b Total … … 10.1 7.3 8.6 … … 19.5 15.4 23.1 … … 12.7 7.3 7.9 … … 6.1 6.7 5.1 … … 2.9 1.1 2.9 9.0 6.1 14.2 9.1 6 6.5 13.5 25.9 17.4 13.8 14.1 6.4 13.6 9.2 5.9 8.3 2.7 9 5.9 3.4 3.7 1.3 8.3 5.2 2.8 2.7 Males 4.2 10.5 5.8 4.3 5.2 11.2 20.0 12.0 11.0 11.7 3.2 4.7 3.8 6 1.7 5.5 3.1 1.4 2.3 1.3 8.6 4.3 2.3 2.5 Females El Salvador Total 9.2 19.5 13.9 8.3 8.4 17.2 33.9 25.5 18.2 18.1 11.3 21.3 15.3 4.5 13.6 9.8 6 5.4 1.4 7.7 6.7 3.7 3 8 8.6 11.6 7.0 … 7.4 … 12.5 11.2 … 13.8 … 6.1 6.3 … 6.7 4.7 5.2 … 5.0 … 3.5 5.2 … 4.9 8.3 8.2 … 9.1 … 14.0 12.2 … 14.4 … 6.9 7.3 … 8.1 6.3 5.9 … 6.4 … 5.0 6.5 … 7.3 … 4.6 5.3 … 4.9 … 9.9 9.4 … 12.5 … 5.1 4.9 … 5.0 2.7 4.3 … 3.3 … 0.9 3.3 … 1.2 Total 2.1 1.9 3.4 … … 3.8 3.3 5.3 … … 2.1 2.3 2.6 … … 0.9 1.4 2.0 … … 0.8 0.5 2.5 … … Males 1.7 2.2 2.9 … … 3.0 3.7 3.9 … … 1.7 2.4 2.4 … … 0.7 1.8 1.1 … … 0.8 0.7 3.2 … … Females 3.3 1.4 4.2 … … 6.0 2.5 7.7 … … 3.1 2.1 3.0 … … 1.5 0.8 3.1 … … 1.0 0.2 1.1 … … Total 4.2 3.4 3.9 … … 7.0 5.7 6.0 … … 4.4 3.2 4.2 … … 2.7 2.3 2.8 … … 2.0 1.6 2.1 … … Males 3.8 3.4 3.6 … … 5.7 5.2 4.9 … … 3.5 3.0 3.5 … … 2.9 2.5 2.8 … … 2.5 2.1 2.3 … … Females Mexico 6.8 … Females Honduras … Males Guatemala Total 5.3 3.4 4.7 … … 10.7 6.6 8.4 … … 6.2 3.4 5.4 … … 2.1 2.1 2.8 … … 0.6 0.7 1.4 … … Total 2.6 2.5 2.9 4.5 … 6.5 5.6 6.7 9.8 … 1.9 2.1 3.0 4.2 … 0.7 1.2 1.2 2.3 … 0.5 0.8 1.3 2.5 … Males 2.6 2.7 3.4 5.3 … 6.2 5.8 7.6 11.1 … 1.9 2.3 3.4 4.7 … 0.9 1.4 1.3 2.7 … 0.6 1.0 1.7 3.5 … Females 2.7 2.1 2.1 3.1 … 7.4 5.2 4.9 … 1.8 1.7 2.3 3.5 … 0.2 0.7 1.0 1.7 … 0.0 0.2 0.7 0.5 … 7.7 Social Panorama of Latin America • 2010 235 Table A-9 (concluded) Age groups 45 and over … … 5.9 … … Females … 13.1 12.7 … … … 24.1 22.5 … … … 10.2 9.9 … … … 9.5 9.8 … … … 7.8 7.1 … … Total 20.0 13.6 13.5 5.6 6.6 38.8 28.3 27.5 13.6 15.2 21.7 13.5 14.3 6.2 7.2 10.4 8.4 8.8 3.2 4.6 8.1 5.9 5.5 1.8 2.7 Males 17.9 11.4 10.6 4.4 5.1 37.0 24.3 22.9 10.9 11.9 17.8 4.2 5.0 6.5 5.9 2.2 3.2 9.1 6.8 5.2 1.7 2.5 Females 22.8 16.7 18.5 7.5 8.9 41.0 33.6 36.6 19.3 21.6 26.5 19.0 20.4 9.1 10.3 12.7 10.5 13.3 4.6 6.5 6.4 4.5 6.2 2.1 3.0 Panama Paraguay c 9.7 10.2 8.4 2009 6.3 8.1 2008 8.0 … 1990 … … 2009 … … 2008 … 8.4 2002 9.0 … 11.5 1999 … 10.7 … 1990 … … 2009 … 8.2 2008 8.9 7.4 1990 8.5 … 2009 … … 2008 … … 2002 … … 13.9 15.0 1999 … 16.9 17.4 … 1990 … … 2009 … … 10.5 10.0 2008 … 11.4 11.0 Males 2002 Total 1999 Nicaragua 1990 Sex 2002 35 to 44 years Country 1999 25 to 34 years 2002 15 to 24 years 1999 Total 6.6 7.6 5.6 6.5 15.5 11.9 13.8 11.8 13.4 4.8 5.3 7.3 4.5 5.4 2.3 4.4 4.4 2.6 3.2 1.4 4.4 3.9 3.2 3.4 6.2 6.1 6.7 4.4 5.6 14.7 10.8 11.7 8.7 10.7 5.0 4.0 6.1 2.5 3.6 3.2 4.5 3.0 2.1 3.6 2.0 4.5 4.5 3.6 3.6 Females 6.5 7.5 8.9 7.5 7.9 16.5 13.9 17.3 16.8 17.9 4.7 7.3 9.0 7.4 7.9 1.1 4.3 6.3 3.4 2.5 0.0 4.1 2.9 2.5 3.1 Total … 5.3 5.0 4.2 3.9 … 11.3 8.9 9.5 8.6 … 4.3 4.9 4.2 4.1 … 2.9 3.4 2.2 2.2 … 2.8 3.4 2.0 2.1 Males … 5.0 4.7 3.7 3.8 … 10.4 8.5 8.6 8.6 … 3.8 4.0 3.2 3.6 … 2.5 2.7 1.6 1.4 … 3.2 3.7 1.9 2.2 Females … 5.6 5.4 4.9 4.1 … 12.6 9.4 10.7 8.6 … 4.9 6.0 5.5 4.8 … 3.4 4.2 2.8 3.1 … 2.2 2.9 2.1 1.9 Total 8.9 11.2 16.9 7.5 7.3 24.4 25.8 37.9 20.9 20.2 8.2 10.0 16.4 7.3 7.5 4.3 7.2 12.1 4.6 4.4 3.5 6.1 9.6 3.7 3.5 Males Uruguay 6.3 Males Peru Total 7.3 5.3 5.2 22.2 21.4 32.0 16.7 16.1 6.0 4.1 4.5 2.5 3.7 7.8 2.4 2.1 3.0 4.9 7.7 2.6 2.5 6.4 11.2 16.8 7.2 6.9 4.4 7.7 12.1 5.1 4.8 Females Venezuela Total (Bolivarian Republic of) d Males Females 8.6 13.4 11.1 14.5 21.1 10.1 7.2 12.7 9.8 27.5 32.0 46.1 26.7 25.8 11.0 13.5 20.8 11.0 10.7 10.2 14.5 16.2 6.9 … 19.3 25.7 28.2 13.6 … 11.3 14.7 16.3 7.4 … 5.9 10.2 11.1 4.6 … 4.5 7.8 9.9 3.9 … 11.2 13.6 14.4 6.5 … 19.9 22.2 24.4 12.3 … 12.3 12.8 13.5 6.5 … 6.9 10.1 9.9 4.3 … 5.5 9.4 10.4 4.3 … 8.4 16.1 18.8 7.4 … 18.0 32.6 34.5 15.9 … 8.7 … 4.0 10.4 12.9 5.0 … 1.7 4.7 3.2 … 9.6 17.7 20.4 9.0 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household surveys conducted in the respective countries. a For the exact years of the surveys in each country, see table A-5. b Based on special tabulations of data from the National Occupation Survey supplied by the National Statistical Office of Cuba. The figures for 1990-1999 relate to total unemployment (urban and rural); those for 2003-2008 relate to urban unemployment. c Total for urban areas, except that the figure for 1990 relates to the Asunción metropolitan area. d The sample design in the surveys conducted since 1997 does not distinguish between urban and rural areas. The figures therefore refer to the nationwide total. 236 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-10 Latin America: AVERAGE INCOME OF THE EMPLOYED ECONOMICALLY ACTIVE POPULATION BY OCCUPATIONAL CATEGORY, URBAN AREAS, 1990-2009 (Multiples of the relevant per capita poverty line) Own-account and unpaid family workers Wage or salary earners Private sector Country Year Total Employers Non-professional, non-technical Total Argentina c Public sector Total a Professional and technical Establishments employing more than 5 persons Establishments employing up to 5 persons Domestic employment Total b Nonprofessional, non-technical 4.7 5.3 9.4 9.3 4.5 5.2 3.6 3.6 2.5 2.4 8.4 8.5 7.6 7.0 4.7 20.9 3.5 3.3 3.5 6.7 3.1 2.1 1.7 5.9 4.3 6.0 21.0 4.8 5.7 4.6 7.4 4.9 3.4 1.7 7.8 6.6 9.5 28.6 7.8 11.1 7.2 11.9 7.2 5.0 2.7 12.2 10.2 1989 d 4.5 16.3 3.7 4.1 3.5 7.7 3.6 2.8 1.5 4.8 4.5 1999 3.8 8.2 4.2 4.7 4.0 7.4 3.9 2.5 2.0 2.8 2.7 2002 3.6 7.3 4.1 5.2 3.8 7.7 4.1 2.5 2.1 2.6 2.4 3.8 7.7 4.1 5.4 3.7 8.8 3.9 2.5 1.9 2.4 2.4 1990 e 4.9 16.1 4.2 … 4.2 8.2 3.8 2.7 1.0 4.3 3.9 1999 4.7 14.8 4.1 6.6 3.5 6.9 3.2 f 2.1 1.4 4.2 3.7 2002 4.5 14.3 4.0 6.6 3.4 11.1 3.3 f 2.2 1.4 3.8 3.3 2008 5.0 15.0 4.6 7.7 3.9 8.0 3.9 2.6 1.7 4.2 3.4 2009 5.1 15.0 4.7 7.9 4.0 7.9 4.1 2.7 1.8 4.1 3.3 1990 4.7 24.8 3.8 … 3.8 7.4 3.5 2.4 1.4 5.4 5.0 1998 7.4 34.0 5.6 … 5.6 11.7 4.3 3.0 2.2 8.7 6.5 2003 7.4 36.7 5.7 7.6 5.3 12.4 4.0 2.9 2.4 7.8 5.9 2006 6.8 28.0 5.6 7.8 5.3 11.8 4.2 3.1 2.4 8.3 6.3 2009 7.7 34.4 6.4 9.0 5.9 11.9 4.6 3.4 2.7 8.9 6.6 1991 2.9 7.4 2.8 3.9 2.5 5.3 2.4 … 1.2 2.7 2.4 1999 3.4 9.5 3.7 6.3 3.2 6.8 2.8 … 2.1 2.3 2.0 2002 3.9 11.8 3.7 6.5 3.2 7.2 2.9 … 1.8 3.2 2.7 2008 4.4 12.0 4.4 8.1 3.8 7.9 4.1 2.2 1.9 3.6 3.1 2009 4.2 10.9 4.2 8.1 3.8 7.9 4.1 2.1 1.8 3.3 2.8 1990 5.3 6.8 5.4 7.3 4.5 9.0 4.4 3.2 1.5 4.2 3.9 1999 6.1 10.5 6.0 8.8 5.1 9.7 4.8 3.7 1.8 4.8 4.4 2002 6.6 10.2 6.9 9.5 6.0 9.7 5.9 3.7 2.0 4.0 3.4 2008 6.0 12.2 5.9 8.9 5.0 8.0 4.6 3.3 1.7 4.0 3.1 2009 Costa Rica … 6.9 2007 Colombia 4.7 5.6 2009 Chile 20.6 23.8 2006 Brazil 6.5 7.0 2002 Bolivia (Plurinational State of) 1990 1999 6.3 10.7 6.3 9.4 5.3 8.8 5.0 3.1 1.7 4.1 3.2 4.0 4.7 3.7 7.0 3.7 2.6 1.3 3.6 3.0 3.8 2.8 4.4 2.8 1.6 1.1 6.3 5.6 5.4 21.1 3.2 4.2 2.8 4.8 2.8 1.9 1.2 6.9 6.1 1990 3.1 4.8 3.3 4.1 2.9 6.1 2.9 2.3 0.8 2.3 2.3 3.1 7.6 2.8 3.8 2.6 4.5 2.9 1.7 0.9 2.2 2.2 3.7 8.7 3.4 4.7 3.1 5.0 3.4 2.2 1.5 3.0 2.8 2008 4.1 11.6 3.8 6.4 3.3 5.3 3.4 2.3 1.9 3.1 2.9 2009 4.0 11.4 3.9 6.6 3.3 5.7 3.4 2.3 2.2 2.9 2.7 1995 3.7 9.2 3.6 5.3 3.1 6.9 2.9 2.1 1.0 2.7 2.5 1999 4.4 9.6 4.5 6.9 4.0 8.3 3.7 2.4 2.1 3.0 2.8 2001 4.4 10.5 4.4 6.7 3.9 8.2 3.8 2.4 2.0 3.2 3.0 2009 Guatemala 15.6 17.9 2002 El Salvador 4.3 4.9 1999 Ecuador 2002 2008 2009 Dominican Republic 3.4 3.6 8.3 3.8 6.5 3.3 6.1 3.3 2.1 2.0 2.4 2.2 1989 3.8 17.7 3.1 4.8 2.6 5.2 2.7 1.8 1.4 4.0 3.7 1998 3.8 16.0 3.3 4.5 3.1 5.3 3.5 2.1 1.3 2.9 2.7 2002 4.0 11.0 3.5 5.6 3.2 5.5 3.3 1.7 1.7 3.1 2.8 2006 3.9 17.0 2.8 4.7 2.5 4.3 2.7 1.5 1.3 3.7 3.4 Social Panorama of Latin America • 2010 237 Table A-10 (concluded) Own-account and unpaid family workers Wage or salary earners Private sector Country Year Total Employers Non-professional, non-technical Total Honduras Public sector Total a Professional and technical Establishments employing more than 5 persons Establishments employing up to 5 persons Domestic employment Total b Nonprofessional, non-technical 2.6 6.5 2.8 1.6 0.8 2.0 1.8 2.9 1.9 3.1 2.1 1.2 0.5 1.6 1.5 2.5 5.1 2.7 4.3 2.4 5.3 2.3 1.4 0.8 1.6 1.5 2.8 5.8 3.2 5.2 2.7 5.0 2.4 1.5 1.3 1.8 1.4 1989 1998 4.5 4.2 21.7 18.0 3.4 3.5 … 5.1 3.4 3.1 6.8 6.7 3.1 3.1 … 1.9 1.4 1.2 5.8 3.7 5.4 3.3 4.3 15.8 3.6 5.3 3.2 6.9 3.3 2.1 1.4 4.5 4.1 2008 4.0 17.0 3.3 5.2 2.9 5.8 3.0 1.9 1.3 3.9 3.4 1993 3.8 8.6 3.3 3.4 3.3 6.2 3.1 2.4 2.1 4.5 3.8 1998 3.5 11.3 3.2 … 3.2 6.3 2.7 2.0 1.7 2.9 2.7 2001 3.6 14.4 3.1 4.5 2.7 5.4 3.0 1.9 1.5 2.7 2.6 2005 3.1 9.9 3.0 4.3 2.7 4.6 2.9 1.7 1.6 2.2 2.1 1991 5.7 14.9 5.8 7.8 4.6 9.8 4.2 2.7 1.3 3.4 3.0 1999 6.3 11.9 6.7 9.0 5.8 11.3 4.9 2.8 2.1 3.8 3.4 2002 6.3 17.8 6.3 8.9 5.3 9.1 5.8 3.1 1.6 4.6 4.3 2008 6.0 19.2 5.4 7.5 4.8 7.3 5.0 3.1 1.9 5.7 5.3 2009 6.3 19.3 5.8 7.8 5.1 8.2 5.3 3.4 2.0 5.9 5.1 1990 g 3.5 10.3 2.5 3.4 2.3 4.1 2.8 1.9 0.8 3.9 3.7 1999 3.5 8.9 3.3 4.8 2.9 6.7 3.1 2.1 1.6 2.5 2.3 2001 3.3 8.6 3.2 5.2 2.7 4.5 3.3 2.0 1.5 2.2 1.8 2008 2.8 6.4 2.7 3.9 2.5 4.1 2.7 1.9 1.3 2.0 1.8 2009 Peru 4.9 2.1 2002 Paraguay 3.1 5.1 2007 Panama 16.4 2.1 2002 Nicaragua 3.0 1999 Mexico 1990 2.8 6.1 2.7 3.9 2.5 4.4 2.7 2.1 1.4 2.0 1.8 1997 3.5 7.9 3.9 4.1 3.9 7.3 4.2 2.4 2.1 2.3 2.2 1999 3.5 7.3 4.0 4.6 4.0 9.5 4.5 2.0 2.9 2.1 2.0 2001 3.2 6.9 3.5 4.0 3.5 6.4 3.6 2.0 1.8 2.2 2.1 2003 3.0 7.8 3.2 3.9 3.2 5.7 3.2 1.8 1.8 2.0 1.9 2008 Uruguay 3.6 7.8 4.0 4.7 3.9 6.2 4.1 2.1 1.8 2.3 2.2 2009 3.9 7.6 4.4 5.0 4.3 6.6 4.6 2.2 2.0 2.4 2.2 1990 4.5 17.9 3.7 4.0 3.5 5.0 3.8 2.5 1.5 3.4 3.4 1999 5.5 14.1 5.3 6.7 4.9 11.2 4.9 3.2 2.1 4.4 3.9 2002 10.6 4.4 5.8 3.9 7.9 4.3 2.6 2.0 3.3 2.5 4.3 11.8 4.2 5.8 3.7 7.0 4.1 2.2 1.8 3.1 2.3 2009 Venezuela (Bolivarian Republic of) h 4.3 2008 4.6 11.5 4.5 6.4 4.0 7.4 4.5 2.4 1.9 3.2 2.5 1990 4.5 11.9 3.7 4.0 3.6 6.6 3.6 2.5 2.1 4.5 4.3 1999 3.5 9.2 3.1 3.7 3.0 6.4 2.9 2.0 1.4 3.4 3.2 2002 3.4 9.9 3.0 4.5 2.4 4.8 2.5 1.7 1.2 3.2 3.1 2008 3.9 7.5 4.0 5.2 3.5 5.1 3.6 2.6 1.8 3.4 3.2 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household survey conducted in the respective countries. for Argentina (1990-1997), Brazil (1990), Chile (1990, 1994 and 1998), Mexico (1989, 2004-2006) and Nicaragua (1998) include public-sector wage-earners. In addition, in the case of non-professional, non-technical workers, the figures for the following countries include establishments with up to four employees: Bolivarian Republic of Venezuela, Chile (1996), the Dominican Republic, El Salvador, Panama (up to 2002), the Plurinational State of Bolivia (1999 and 2002) and Uruguay (1990). Where no information is available on the size of establishments, no figures are given for the total number of employed in low-productivity sectors. b Includes professional, technical and own-account workers. c Greater Buenos Aires. d Eight departmental capitals plus El Alto. e No information is available on the size of establishments for 1990. Therefore the figure given for Brazil in the column for establishments employing more than five persons refers to wage-earners who have an employment contract (“carteira”), while the column for establishments employing up to five persons refers to workers who do not have such contracts. f Includes non-technical and non-professional private sector workers employed in establishments of undeclared size. g Asunción metropolitan area. h From 1997 on, the sample design for the survey does not permit urban-rural breakdown. Figures therefore correspond to the national total. a Figures 238 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-11 Latin America: RATIO OF AVERAGE FEMALE INCOME TO AVERAGE MALE INCOME, BY YEARS OF SCHOOLING, URBAN AREAS, 1990-2009 (Percentages) Disparity in labour income by years of schooling a Country Argentina c Year Total 0 to 3 years 4 to 6 years 7 to 9 years 10 to 12 years 13 years or more Wage disparity by years of schooling b Total 0 to 3 years 4 to 6 years 7 to 9 years 10 to 12 years 13 years or more 1990 65 66 … 66 63 51 84 80 … 83 68 1999 65 64 82 58 63 51 86 71 -.- 63 79 63 67 2002 59 62 81 55 61 46 76 -.- -.- 56 70 61 2006 Brazil 63 49 48 57 63 80 56 69 59 73 70 72 55 55 57 64 67 90 71 73 68 75 78 1989 d 59 62 68 76 78 46 69 44 59 63 93 49 1999 63 64 65 66 71 66 77 -.- 67 36 80 65 2002 61 62 67 75 66 60 77 39 83 95 74 60 2007 Bolivia (Plurinational State of) 65 2009 63 62 53 59 74 65 83 56 67 73 71 71 52 1990 56 46 46 50 49 49 76 65 60 61 54 1999 65 59 51 55 56 56 85 76 67 67 62 57 2002 67 59 53 56 57 57 86 78 69 68 65 58 2008 Chile 68 62 55 58 59 59 85 80 71 70 67 62 2009 68 60 57 59 61 58 85 79 73 72 69 61 1990 62 60 60 71 63 49 79 82 62 83 77 55 1998 66 70 63 65 70 54 83 79 65 74 80 63 2003 68 68 64 69 53 81 69 71 67 79 63 70 71 73 65 67 62 86 76 75 75 76 71 2009 Colombia 64 2006 65 70 66 67 68 55 82 81 75 72 74 67 68 1991 69 57 60 70 72 64 85 84 79 82 80 1999 75 66 71 75 73 70 90 82 85 85 82 74 2002 72 66 70 67 69 63 98 90 93 88 83 73 2008 Costa Rica 73 68 61 65 65 67 94 94 84 79 80 74 2009 75 61 59 63 66 71 95 86 83 80 77 76 1990 72 53 62 65 73 66 83 73 79 75 79 66 1999 70 49 62 57 65 68 88 87 84 74 75 71 2002 63 56 60 72 72 85 74 71 74 79 69 70 68 57 63 62 65 88 70 74 78 72 75 2009 Dominican Republic 75 2008 76 48 55 60 66 71 95 72 68 76 80 78 78 72 56 56 62 69 66 89 79 64 73 82 61 48 58 45 53 58 83 72 68 72 82 67 2009 Ecuador 2002 2008 62 73 51 51 47 57 84 82 71 68 67 70 56 1990 66 49 57 68 79 57 78 67 64 87 78 1999 67 63 62 62 71 60 98 75 73 78 93 72 2002 67 73 69 66 70 57 87 96 90 78 80 64 2008 El Salvador 69 67 63 66 70 62 95 84 76 84 81 74 2009 71 65 65 75 70 64 93 77 78 87 81 72 1995 62 62 55 63 68 63 89 76 67 74 84 72 1999 76 81 76 78 81 70 96 78 86 86 91 74 2001 73 80 69 69 82 69 99 83 79 82 91 79 2009 81 87 84 77 76 79 105 88 90 89 85 84 Social Panorama of Latin America • 2010 239 Table A-11 (concluded) Disparity in labour income by years of schooling a Country Guatemala Year Total 0 to 3 years 4 to 6 years 7 to 9 years 10 to 12 years 13 years or more Wage disparity by years of schooling b Total 0 to 3 years 4 to 6 years 7 to 9 years 10 to 12 years 13 years or more 1989 68 59 78 71 80 57 97 66 83 89 88 68 1998 55 62 53 58 56 53 72 54 60 67 69 62 2002 Honduras 56 56 63 68 58 56 79 82 71 81 71 67 2006 58 80 53 72 63 44 82 87 67 77 77 57 1990 59 47 50 58 69 54 98 71 73 74 83 63 1999 65 60 62 59 66 66 88 83 83 65 77 74 2002 Mexico 76 66 69 67 77 65 95 87 84 81 83 64 2007 81 65 66 71 80 76 103 91 83 85 87 77 1989 55 62 52 70 62 46 76 83 73 83 79 62 1998 58 67 66 68 65 47 76 72 83 80 82 55 2002 Nicaragua 62 57 60 59 61 61 80 69 76 71 76 69 2008 62 65 64 65 66 53 83 76 71 71 80 71 1993 77 95 73 71 91 58 83 85 81 74 78 65 1998 65 67 80 67 52 54 88 70 81 71 59 68 2001 Panama 69 84 76 60 80 52 90 87 88 69 78 62 2005 71 73 68 68 71 60 96 89 91 79 81 66 1991 78 47 55 69 82 69 89 60 72 82 86 73 1999 78 61 56 63 75 71 89 -.- 75 75 81 71 2002 76 57 51 53 78 64 93 97 72 74 85 70 2008 74 62 52 58 69 65 97 -.- 77 78 89 75 2009 78 74 52 58 77 69 96 85 73 85 88 73 1990 e 55 69 55 60 65 42 83 -.- 72 80 77 58 1999 Paraguay 72 62 77 62 73 63 96 91 90 69 92 70 2001 63 63 73 64 63 102 75 83 99 97 65 71 54 65 66 57 75 92 70 95 87 68 75 2009 Peru 68 2008 75 56 61 69 68 79 97 80 88 76 84 81 70 64 60 72 52 77 59 62 57 81 63 65 60 102 67 61 81 58 58 66 71 73 67 80 82 67 70 62 80 51 78 75 77 67 2008 61 67 61 60 60 63 71 53 63 63 68 63 2009 63 65 63 63 60 64 77 53 59 60 69 69 1990 44 50 41 40 42 37 73 67 67 71 61 57 1999 68 63 60 62 62 55 78 63 66 72 69 58 2002 73 82 67 63 66 59 82 69 70 71 73 61 2008 68 54 56 56 60 58 80 51 61 63 68 63 2009 Venezuela (Bolivarian Republic of) 59 64 2001 Uruguay 1997 1999 69 61 55 55 59 61 81 58 60 61 68 64 1990 66 63 58 68 61 62 87 89 81 84 78 71 1994 70 63 61 70 63 66 87 92 79 95 70 74 Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of data from household survey conducted in the respective 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. b Refers to the income differential in total income among wage-earners. This differential is calculated as the quotient of average female income and average male income multiplied by 100. c Greater Buenos Aires. d Eight departmental capitals plus El Alto. e Asunción metropolitan area. … No data. -.- Insufficient observations. 240 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-12 Latin America and the Caribbean (SELECTED COUNTRIES): INDICATORS OF PUBLIC SOCIAL SPENDING, 1990-1991 AND 2007-2008 a Public social spending b Country Per capita (in dollars at 2000 prices) Coverage c 19901991 Argentina e 19971998 Percentage of total public spending d Percentage of GDP 20002001 20072008 19901991 19971998 20002001 20072008 19901991 19971998 20002001 20072008 861 821 1 133 11.3 10.6 11.0 11.8 60.3 66.5 61.3 59.8 1 500 1 512 2 108 17.9 18.5 20.2 21.9 62.7 65.9 63.2 63.6 1 166 1 620 1 635 2 276 19.1 20.0 21.8 23.6 62.2 65.1 62.8 63.3 CG 47 104 122 … 5.2 10.3 12.0 … 34.4 33.5 35.4 … NFPS … 156 165 178 … 15.5 16.3 16.2 … 46.9 42.8 49.1 309 434 453 598 9.2 11.8 12.2 13.7 52.3 64.4 60.6 80.5 554 Brazil g 687 1 090 NFPS Bolivia (Plurinational State of) f CG GG 753 785 1 083 16.6 20.5 21.2 24.7 48.9 50.5 62.1 73.5 FG consolidated Chile CG 381 635 747 818 12.0 13.2 15.1 13.2 61.2 65.7 68.4 66.3 Colombia h CG 129 320 264 376 5.9 12.8 11.1 12.6 28.8 … 68.6 70.9 Costa Rica SP 486 636 727 951 15.6 16.9 18.0 18.4 38.9 41.9 40.5 36.2 Cuba CG 864 532 661 1 656 27.6 21.6 23.7 37.4 35.6 42.9 47.0 54.6 Dominican Republic i CG 69 134 188 288 3.8 5.4 6.8 8.1 43.1 43.2 49.9 46.9 Ecuador j CG 99 71 66 106 7.4 5.1 4.9 6.4 42.8 25.0 20.9 27.9 El Salvador k GG … 153 222 290 … 7.3 10.0 11.1 … 30.7 38.6 46.8 Guatemala CG 49 86 105 120 3.7 5.8 6.8 7.1 29.9 44.8 47.3 51.0 Honduras CG 67 63 97 150 6.3 5.4 8.4 10.4 40.7 38.3 45.4 51.3 Jamaica l CG 294 … 331 309 8.4 … 9.5 8.6 26.8 … 17.1 16.3 Mexico BCG 358 521 621 856 6.5 8.8 9.7 12.1 41.3 54.9 61.3 64.1 Nicaragua BCG 45 44 63 107 6.6 6.2 8.1 12.0 34.0 35.0 38.4 52.7 CG 229 365 371 506 7.5 9.7 9.5 9.3 38.1 42.4 42.5 41.5 NFPS 496 645 680 … 16.2 17.2 17.4 … 40.0 41.6 44.3 … Paraguay BCG 45 126 107 165 3.2 8.6 8.0 11.1 39.9 46.4 38.3 59.5 Peru BCG 64 151 158 … 3.9 7.3 7.7 … 33.0 40.8 45.0 … GG … … 179 224 … … 8.8 8.0 … … 52.2 52.5 CG 303 … 588 1 135 6.9 … 9.1 10.5 40.6 … 43.5 33.4 CG-consolidated 841 1 316 1 314 1 686 16.8 20.5 21.6 21.8 62.3 68.7 68.1 73.4 GG … … 1 272 … … … 20.9 … … … 62.8 … NFPS … … 1 364 … … … 22.4 … … … 64.4 … BCG-approved 433 457 549 708 8.8 9.0 11.6 13.4 32.8 36.6 37.8 44.0 BCG-executed … … 483 614 … … 10.2 10.8 … … 43.5 41.8 Panama Trinidad and Tobago m Uruguay n Venezuela (Bolivarian Republic of) o 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 education, health and nutrition, social security, employment and social welfare, housing, water and sewerage systems. b The figures are simple averages for the relevant bienniums. c CG: central government; GG: general government; NFPS: non-financial public sector; FG: federal government; PS: public sector/total public sector; BCG: budgetary central government. d For most countries, the figure shown for total public spending is the official statistic provided by the country; no consideration is given to whether debt servicing is included or excluded. e Includes the spending of the national government, provincial governments and the central government of Buenos Aires, as well as municipal governments. f In the Plurinational State of Bolivia, in the case of the NFPS, the figure listed for 2006-2007 is the 2006 figure from the new 2002-2006 series published by the country. As such, it is not comparable to those of previous years. g The data up to 1999 are an estimate of consolidated social spending, which includes federal, state and municipal spending. h The figures for the 2006-2007 biennium correspond to the new series published since 2002 and are not comparable to those of previous years. i The figures listed for 2007-2008 are the 2007 figures. j The figures of the series remain unchanged. Social security spending is under review. The figure listed for 2006-2007 is the 2006 figure. k The figures listed for 2007-2008 are those for 2007. l Old series with no data for 1997 and 1998. The data shown for 2007-2008 are those for 2004. New series under review. m In Trinidad and Tobago, the Classification of the Functions of Government (COFOG) series begins in 2000 and is not comparable with earlier series; the figures for 2007-2008 are preliminary. n In Uruguay, the figures from 2000-2001 correspond to the series published by the Ministry of Social Development (MIDES) and are not comparable with those of previous years. o Corresponds to the budget law, which it includes the amendments introduced yearly on 31 December. The figures shown for approved central government budget for 2007-2008 are those for 2006. Social Panorama of Latin America • 2010 241 Table A-13 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) Goal 1 Eradicate extreme poverty and hunger Target 1.A Halve, between 1990 and 2015, the proportion of people whose income is less than one dollar a day Country or territory Indicator 1.1 Proportion of population below $1 (PPP) per day b Indicator 1.3 Share of poorest quintile in national consumption Indicator 1.2 Poverty gap ratio Level 1990 Level 2008 Level 1990 Level 2008 Level 1990 Level 2008 Latin America and the Caribbean c Latin America c Argentina d Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador d El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay d Venezuela (Bolivarian Republic of) 22.5 22.5 8.2 39.5 23.4 13.0 26.1 10.1 … … 26.2 27.7 41.8 12.9 12.9 5.8 32.4 7.3 3.7 22.9 5.5 … 22.6 14.2 18.2 29.3 8.6 8.6 1.6 9.7 9.7 4.4 13.8 4.8 … 8.8 9.2 9.1 18.5 4.4 4.4 2.6 4.5 3.3 1.1 8.3 2.2 … 8.8 4.7 8.1 11.3 3.2 3.2 4.2 3.2 2.1 3.5 2.0 4.3 … 3.2 4.8 3.4 2.7 3.5 3.5 3.7 4.3 2.6 4.1 2.9 4.4 … 2.9 4.4 3.4 2.8 60.9 18.7 51.4 16.2 35.0 25.0 3.4 14.4 47.1 11.2 33.8 13.5 30.8 12.6 3.5 9.9 31.5 5.9 24.3 5.2 3.6 10.1 0.9 5.0 23.9 3.2 12.3 1.6 5.7 4.0 0.9 3.5 2.3 3.9 2.1 3.2 5.2 3.0 4.8 4.3 1.9 4.0 3.5 4.6 5.0 4.0 4.9 5.2 The Caribbean c Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize e British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana e Jamaica e Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia e Saint Vincent and the Grenadines Suriname e Trinidad and Tobago e Turks and Caicos Islands United States Virgin Islands … … … … … … 13.4 … … … … … … 5.8 2 … … … … … 20.9 … 15.5 4.2 … … … … … … … … … … … … … … … 7.7 2 … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, U Economic Commission for Latin America and the Caribbean, August 2010. a The indicators are presented in numerical order; those for which there is no information have not been included. b Does not include the Dominican Republic. Figures for 1990 are not comparable with those for 2000 on. c Weighted averages. d The figures refer to urban areas. e Corresponds to the proportion of the population with income below one purchasing power parity (PPP) dollar per day. Data available on the official United Nations site for Millennium Development Goals Indicators [online] http://mdgs.un.org/unsd/mdg/Default.aspx. 242 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-14 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) Goal 1 Eradicate extreme poverty and hunger Target 1B Achieve full and productive employment and decent work for all, including women and young people Country or territory Indicator 1.4 Growth rate of GDP per person employed Indicator 1.5 Employment-topopulation ratio Indicator 1.6 Proportion of employed people living below $ 1 (PPP) per day Level 1992-1997 Level 2003-2008 Level 1990 Level 2008 Level 1990 Level 2008 Latin America and the Caribbean b Latin America b Argentina c Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador c El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay c Venezuela (Bolivarian Republic of) 0.3 0.3 3.5 0.1 -0.5 5.8 0.9 1.8 … 1.4 -1.4 3.5 3.9 -6.1 -0.4 -0.6 0.8 0.6 -1.2 2.4 3.0 -1.2 2.2 2.2 6.0 1.1 1.8 2.7 1.7 3.0 … 4.1 2.3 1.0 -1.1 -1.7 4.0 1.5 -0.2 4.2 0.3 4.0 6.9 2.5 54.3 54.5 52.5 53.5 61.1 47.7 58.6 54.7 53.0 52.9 57.1 55.8 56.5 56.0 56.1 52.1 49.6 48.1 61.4 67.9 52.6 51.6 59.5 59.6 57.0 58.7 63.7 53.1 56.9 57.9 56.0 54.5 61.1 55.5 64.9 55.9 58.0 59.4 60.4 60.3 63.8 71.3 58.8 60.8 17.8 3.2 4.2 3.2 2.1 3.5 2.0 4.3 … 3.2 4.8 3.4 2.7 3.5 3.5 3.7 4.3 2.6 4.1 2.9 4.4 … 2.9 4.4 3.4 2.8 2.3 3.9 2.1 3.2 5.2 3.0 4.8 4.3 The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize d British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana d Jamaica d Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia d Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands 0.9 … … … -0.6 -0.9 -1.2 … … … … … … 5.1 1.7 … … … … … … … -0.3 -2.4 … … 2.0 … … … 0.0 1.9 0.9 … … … … … … 1.6 0.1 … … … … … … … 4.3 5.7 … … 47.3 … … … 63.0 56.9 47.6 … … … … … 44.5 51.7 61.5 46.2 … 49.0 38.1 … … … 44.6 45.0 … … 51.2 … … … 66.6 66.9 56.8 … … … … … 43.1 58.9 58.2 42.5 … 53.5 42.4 … … … 44.7 61.5 … … … … … … … … … … … … … … … … … … … … … … … … … … … … Indicator 1.7 Proportion of ownaccount and contributing family workers in total employment b Level Level 1990 2008 1.9 4.0 3.5 4.6 5.0 4.0 4.9 5.2 32.0 32.0 25.6 43.7 28.9 24.5 44.6 24.3 … 41.7 35.6 36.2 48.0 … 49.6 29.4 46.5 33.8 22.9 52.4 20.1 25.7 31.1 31.2 19.3 36.0 29.1 21.3 45.6 19.5 … 43.8 36.2 35.3 44.5 … 48.9 22.6 44.9 30.7 26.4 51.4 24.9 37.5 … … … … … … … … … … … … … … … … … … … … … … … … … … 32.2 … 14.6 3.9 … 11.7 … … … 29.1 … … … … 42.3 … 12.6 8.1 … 12.1 23.5 20.2 15.6 21.7 … … 27.1 … … … … 23.5 … … … … … … … 35.4 … … 11.2 … … … … … 15.6 … … Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, U Economic Commission for Latin America and the Caribbean, August 2010. a The indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. c The figures refer to urban areas. d Simple averages. Social Panorama of Latin America • 2010 243 Table A-15 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) Goal 1 Eradicate extreme poverty and hunger Target 1.C Halve, between 1990 and 2015, the proportion of people who suffer from hunger Country or territory Target 1.8 Prevalence of underweight children under five years of age Level 1989-1999 Level 1996-2008 Target 1.9 Proportion of population below minimum level of dietary energy consumption Level 1990-1992 Level 2004-2006 Latin America and the Caribbean b Latin America b Argentina c Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador c El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay c Venezuela (Bolivarian Republic of) 8.6 8.6 1.9 11.2 7.0 0.9 10.1 2.8 … 10.3 14.6 11.2 26.6 26.8 18.0 7.5 11.0 6.1 3.7 10.8 4.4 7.7 6.3 6.3 3.8 5.9 4.6 0.6 6.9 4.0 … 4.3 8.6 8.6 22.7 22.2 11.4 5.0 6.9 6.8 4.2 7.6 6.0 4.6 10.7 10.7 <=5 24 10 7 15 <=5 5 27 24 9 14 63 19 <=5 52 18 16 28 5 10 7.3 7.3 <=5 23 6 <=5 10 <=5 <=5 21 13 10 16 58 12 <=5 21 17 12 13 <=5 12 The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands 7.6 … … … … … 6.2 … … … … … … 18.3 4.6 … … … … … … … … … … … 5.9 … 1.6 … … … 6.1 … … … … … … 12.4 4.0 … … … … … … … … 5.9 … … 11.9 … … … 9 … 7 … … 4 … 9 … 21 11 … … 14 … 13 8 22 13 11 … … 7.2 … 27 … 6 … … … … … … 23 … 6 5 … … 5 … 15 8 6 7 10 … … Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, U Economic Commission for Latin America and the Caribbean, August 2010. a The indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. c The figures refer to urban areas. 244 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-16 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) Goal 2 Achieve universal primary education Target 2.A Ensure that, by 2015, children everywhere, boys and girls alike, will be able to complete a full course of primary schooling Country or territory Indicator 2.1 Net enrolment ratio in primary education Indicator 2.2 Proportion of pupils starting grade 1 who reach last grade of primary Indicator 2.3 Literacy rate of 15-24 yearolds, women and men Level 1991 Level 2007 Level 1992 Level 2004-2008 Level 1991 Level 2007 Latin America and the Caribbean b Latin America b Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela (Bolivarian Republic of) 88.2 88.2 … … 85.4 89.4 69.5 87.6 97.6 54.6 99.2 … … 22.0 87.6 98.6 69.0 … 92.8 … 92.4 88.9 95.0 95.0 99.1 95.0 93.5 94.5 93.5 … 99.5 82.4 92.6 95.6 96.8 … 97.2 99.4 93.4 98.9 93.1 99.7 97.8 92.1 83.9 83.9 97.1 67.1 82.2 95.5 85.6 84.6 … 76.3 89.8 69.0 52.2 … 61.7 86.7 60.2 89.3 78.3 85.4 96.2 88.3 93.1 93.1 97.8 96.4 94.7 98.7 93.6 94.1 … 88.3 96.2 76.1 62.6 … 79.2 95.7 70.8 94.6 95.0 93.9 96.7 93.5 92.0 90.9 98.3 93.9 91.8 98.4 90.5 97.4 96.2 87.5 96.2 84.9 76.0 54.8 79.7 95.4 68.2 95.1 95.6 95.4 98.6 95.4 97.1 95.9 99.1 99.4 97.8 99.1 98.0 98.0 100.0 96.0 95.4 93.6 85.5 81.7 93.9 98.2 87.0 96.3 98.8 97.4 98.8 98.4 The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands 94.1 … … … 90.3 84.3 94.4 … … … … … … 95.4 97.1 … … … … … 96.4 … 82.1 91.1 … … 90.8 95.3 74.0 99.2 90.8 … 99.7 97.1 95.6 73.3 … 96.0 … 98.5 85.5 … 96.2 … … 90.4 93.5 97.5 90.1 96.9 80.7 … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … … 94.0 … … … … 99.8 76.4 … … … … … … … 91.2 … … 97.0 96.1 … … … … 99.3 … … 97.2 … … 99.3 … 99.8 84.2 … 98.9 … … … 99.8 … 94.3 99.7 … 98.2 97.7 … … … 95.2 99.5 … … Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, U Economic Commission for Latin America and the Caribbean, August 2010. a The indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. Social Panorama of Latin America • 2010 245 Table A-17 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) Goal 3 Promote gender equality and empower women Target 3.A Eliminate gender disparity in primary and secondary education, preferably by 2005, and in all levels of education no later than 2015 Country or territory Indicator 3.1 Ratio of girls to boys in primary education Indicator 3.1 Ratio of girls to boys, secondary education Indicator 3.1 Ratio of girls to boys, tertiary education Indicator 3.2 Share of women in wage employment in the non-agricultural sector Indicator 3.3 Proportion of seats held by women in national parliament Level 1991 Level 2007 Level 1991 Level 2007 Level 1991 Level 2007 Level 1990-2002 Level 1991-2007 Level 1990-1992 Level 2007 Latin America and the Caribbean b Latin America b Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela (Bolivarian Republic of) 0.98 0.98 … 0.92 … 0.98 1.02 0.99 0.97 1.00 0.99 1.01 0.87 0.95 1.04 0.97 1.06 … 0.97 0.97 0.99 1.03 1.00 1.00 … 1.01 1.00 0.99 1.00 … 1.00 1.01 1.01 1.02 0.96 … 1.02 1.00 1.01 0.99 … 1.00 1.00 1.00 1.05 1.05 … … … 1.07 1.19 1.06 1.15 … … 1.22 … 0.94 1.23 0.99 1.20 … 1.05 0.94 … 1.38 1.05 1.05 … 0.99 1.10 1.03 1.11 … 1.02 1.22 1.02 1.03 … … … 1.03 1.15 … … 1.01 1.11 1.14 1.08 1.08 … … 1.11 … 1.07 … 1.40 … … … … … 0.79 0.74 0.96 … … … … 1.27 1.27 … 0.84 1.29 1.01 1.09 … 1.85 … 1.22 1.09 1.00 … … 0.98 … 1.59 … … 1.75 36.2 36.3 37.1 35.2 35.1 34.7 41.8 37.2 41.7 31.0 34.1 45.6 36.8 44.2 33.3 36.5 … 45.4 41.0 37.2 42.3 35.2 41.8 41.7 45.0 38.6 41.6 37.4 48.5 41.1 43.7 38.8 36.6 48.6 43.0 … 33.4 39.4 38.6 43.1 40.2 42.9 45.5 41.4 11.9 12.0 6.3 9.2 5.3 7.5 4.5 10.5 33.9 7.5 4.5 11.7 7.0 3.6 10.2 12.0 14.8 7.5 5.6 5.6 6.1 10.0 22.2 22.8 40.0 16.9 9.0 15.0 8.4 36.8 43.2 19.7 27.6 19.0 12.0 4.1 23.4 23.2 18.5 16.7 12.5 29.2 12.1 18.6 The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands 0.99 … … … 1.03 1.00 0.98 … … … … 0.85 … 0.99 0.99 … … … … 1.02 0.94 0.98 1.03 1.00 … … 0.99 … 0.98 0.99 1.03 … 1.01 1.01 1.05 1.06 … 1.00 … … 0.98 … 1.08 … … 1.02 0.95 0.97 0.98 0.99 … … 1.07 … … … … … 1.15 … … 1.06 … … 1.04 1.06 … 1.09 1.12 1.26 1.02 … 1.00 … … 1.05 … 1.01 1.35 … … … … 1.24 … … … … … … … … 0.74 … … … … … 1.35 … … 0.78 … … 2.34 … … 1.41 … … … … … … … … … 2.12 … … … … … … 2.34 … … … … … 44.4 42.8 … 43.9 49.6 46.8 33.9 49.9 50.0 39.7 36.1 40.4 46.6 38.5 46.2 45.4 43.4 42.7 46.5 … 51.8 … 39.5 35.6 43.1 … 43.6 48.8 50.6 45.9 48.8 48.7 37.6 49.1 49.3 43.8 38.2 42.6 45.7 34.7 45.8 48.1 … 49.9 41.5 … 47.5 … 38.1 43.9 40.7 … 9.3 … 0.0 … 4.1 3.7 0.0 … … 10.0 … 20.0 … 36.9 5.0 … … … … 6.7 0.0 9.5 7.8 16.7 … … 15.1 … 10.5 … 12.2 10.0 0.0 … … 18.8 … 13.3 … 30.0 13.3 … … … … 6.7 11.1 18.2 25.5 26.8 … … … 1.16 … 1.06 1.06 … … 1.19 … 1.11 1.45 1.24 1.16 1.04 … … … 0.91 1.15 … … 1.07 … … Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, U Economic Commission for Latin America and the Caribbean, August 2010. a The indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. 246 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-18 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) Goal 4 Reduce child mortality Target 4.A Reduce by two-thirds, between 1990 and 2015, the under-five mortality rate Country or territory Indicator 4.1 Under-five mortality rate (per 1 000 live births) Level 1991 Latin America and the Caribbean b Latin America b Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Ecuador El Salvador Dominican Republic Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela (Bolivarian Republic of) The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands Level 2009 Indicator 4.2 Infant mortality rate (per 1 000 live births) Level 1990 Indicator 4.3 Proportion of 1 year-old children immunized against measles Level 2009 Level 1990 Level 2007 55.5 55.9 30.1 114.6 60.1 19.1 42.5 18.4 18.9 65.5 64.8 64.2 85.5 137.3 70.8 44.2 75.9 35.9 57.8 85.1 24.3 31.6 26.2 26.3 14.9 57.1 27.6 8.5 25.3 11.2 7.7 24.4 24.6 31.3 36.5 68.2 40.2 18.9 23.8 22.9 37.0 30.7 15.8 21.1 42.7 43.0 25.8 82.6 47.5 16.3 31.5 16.0 15.6 49.9 47.1 55.3 61.0 92.7 48.0 36.3 56.5 28.3 44.8 57.8 21.4 25.0 20.4 20.4 12.9 42.6 22.5 7.0 18.7 9.7 4.8 20.0 20.0 28.0 27.6 46.6 27.2 15.6 20.0 17.5 31.0 18.5 12.7 16.4 76.3 76.4 93.0 53.0 78.0 97.0 82.0 90.0 94.0 60.0 98.0 96.0 68.0 31.0 90.0 75.0 82.0 73.0 69.0 64.0 97.0 61.0 93.0 93.4 99.0 81.0 99.0 91.0 95.0 90.0 99.0 99.0 98.0 96.0 93.0 58.0 89.0 96.0 99.0 89.0 80.0 99.0 96.0 55.0 32.9 ... ... 21.2 24.7 17.8 38.5 ... ... ... 26.3 40.5 20.4 90.2 33.9 12.4 ... ... 14.9 ... 24.4 39.3 49.4 35.2 ... 18.3 21.5 ... ... 17.4 11.2 10.1 19.8 ... ... ... 14.4 14.1 8.7 52.4 27.1 7.7 ... 13.4 8.7 ... 15.1 26.8 30.4 32.1 ... 9.7 25.7 ... ... 18.3 16.6 15.1 30.6 ... ... ... 22.5 33.0 15.6 64.9 27.8 9.8 ... 16.1 12.7 ... 18.5 32.3 36.5 28.7 ... 15.8 17.1 ... ... 14.9 8.0 9.5 15.9 ... ... ... 13.0 12.8 6.7 40.3 22.5 6.5 ... 12.4 6.9 ... 12.0 22.3 21.7 25.1 ... 8.8 74.7 ... 89.0 ... 86.0 87.0 86.0 ... ... 88.0 ... 85.0 ... 73.0 74.0 ... ... ... … 99.0 82.0 96.0 65.0 70.0 ... ... 85.0 ... 99.0 ... 96.0 75.0 96.0 ... ... 96.0 ... 98.0 ... 96.0 76.0 ... ... ... … 99.0 94.0 99.0 85.0 91.0 ... ... Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, U Economic Commission for Latin America and the Caribbean, August 2010. a The indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 71.2 71.2 35.0 ... 73.3 18.7 104.9 35.8 40.4 69.0 ... ... ... ... ... 72.6 87.0 ... 164.0 ... ... 60.1 ... ... 0.0 ... ... 0.0 ... ... ... ... ... 0.0 ... 112.5 95.0 12.8 ... ... ... ... ... ... 184.3 ... ... 0.0 66.9 66.9 43.7 ... 77.2 18.2 75.6 19.1 46.5 86.3 ... ... ... ... ... 57.2 76.5 ... 127.3 ... ... 56.8 88.3 100.0 100.0 ... 99.0 100.0 83.8 100.0 ... 99.9 ... 99.0 ... 95.0 79.0 ... 100.0 ... ... 99.4 99.7 99.3 91.0 97.9 ... ... 78.3 78.1 95.8 37.8 81.0 99.4 93.7 97.0 99.8 92.4 66.3 52.0 35.0 23.0 40.5 83.8 61.0 85.8 66.0 52.5 99.6 95.3 95.2 100.0 99.9 ... 99.0 100.0 95.8 100.0 ... 99.0 ... 100.0 ... 83.3 96.7 ... 100.0 ... ... 100.0 100.0 100.0 89.8 97.8 ... ... 88.9 88.8 99.4 65.8 97.0 99.8 96.4 98.5 99.9 97.8 99.1 92.4 41.4 26.1 66.9 93.4 73.7 91.0 77.1 71.0 99.6 95.0 62.8 ... ... ... ... ... 46.7 ... ... ... ... 54.3 ... 38.2 62.0 ... ... ... 77.7 ... ... ... 48.0 38.2 ... ... 59.5 59.4 ... 45.3 ... 60.7 66.1 75.0 73.3 56.4 56.8 53.3 31.4 18.0 46.7 63.1 54.5 ... 48.4 59.0 ... 58.0 Level 1990-2001 67.1 43.0 ... ... ... ... 34.3 ... ... ... ... 54.3 ... 34.2 69.0 ... ... ... 84.1 ... ... ... 42.1 42.5 ... 78.4 69.6 69.7 65.3 60.6 76.7 64.2 78.2 80.0 72.6 72.9 72.7 72.5 43.3 32.0 65.2 70.9 72.4 ... 79.4 71.3 77.0 70.3 Level 1990-2008 Indicator 5.3 Contraceptive prevalence rate 79.2 43.4 82.5 57.0 67.6 55.1 135.2 28.3 88.7 105.5 ... 99.4 ... 94.8 93.6 ... 53.6 55.5 75.4 82.1 99.9 96.7 74.8 58.3 ... 73.6 77.5 77.5 68.3 96.0 53.2 64.8 92.0 91.1 79.7 115.0 101.0 102.0 119.6 79.0 136.0 97.8 158.0 88.0 107.0 68.0 64.7 104.6 Level 1990-1995 57.1 40.1 66.8 43.0 44.2 47.7 94.1 43.2 58.7 51.0 ... 52.9 ... 90.0 58.2 ... 33.7 40.0 60.0 68.1 52.7 57.4 63.4 32.0 ... 53.9 70.4 70.7 62.6 88.0 56.0 48.8 96.2 62.7 41.7 98.0 100.0 67.0 92.1 68.6 107.9 82.1 108.5 84.8 65.0 59.0 61.0 91.3 Level 1994-2006 Indicator 5.4 Adolescent birth rate 94.6 ... 82.0 ... 98.0 100.0 95.9 ... ... 90.0 ... 100.0 ... 80.9 99.0 ... ... ... ... 100.0 100.0 91.8 91.0 92.4 ... ... 83.6 83.4 95.0 52.5 85.7 ... 82.7 95.0 100.0 96.9 74.7 68.7 52.5 67.7 87.8 ... 71.5 ... 83.9 63.9 94.0 ... Level 1990-2006 92.1 ... 100.0 ... 98.0 100.0 94.0 ... ... 100.0 ... 100.0 ... 81.4 90.5 ... ... ... ... 100.0 99.2 95.0 89.9 95.7 ... ... 95.0 95.0 99.2 77.0 97.4 95.0 93.5 91.7 100.0 99.0 84.2 94.0 84.3 84.5 91.7 86.1 90.2 72.2 96.0 91.0 97.1 94.1 Level 1993-2008 Indicator 5.5 Antenatal care coverage (at least one visit) ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 77.6 77.6 ... ... 75.9 ... ... ... ... 93.5 ... 71.2 ... ... ... ... 71.6 ... 78.8 87.0 ... ... Level 1996-2004 ... ... ... ... ... ... 76.4 ... ... ... ... ... ... ... 87.2 ... ... ... ... ... ... ... ... ... ... ... 87.2 87.2 89.3 72.1 87.0 ... 83.1 86.0 ... 94.5 66.5 78.6 65.9 53.8 80.8 ... 77.8 ... 78.7 91.6 ... ... Level 1991-2008 Indicator 5.5 Antenatal care coverage (at least four visits) Target 5.B Achieve, by 2015, universal access to reproductive health Goal 5 Improve maternal health ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 12.9 12.9 ... 26.1 ... ... 7.7 ... ... 12.5 10.0 14.2 24.3 ... 18.0 ... 14.7 ... 19.2 12.1 ... ... Level 1995-1999 ... ... ... ... ... ... ... ... ... ... ... ... ... ... 12.7 ... ... ... ... ... ... ... ... ... ... ... 10.4 10.4 ... 22.7 7.3 ... 5.8 ... ... 10.9 7.4 8.9 27.6 39.8 11.2 14.2 14.6 ... 6.6 8.8 ... ... Level 1995-2005 Indicator 5.6 Unmet need for family planning a The Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, Economic Commission for Latin America and the Caribbean, U August 2010. indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands Latin America and the Caribbean b Latin America b Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela (Bolivarian Republic of) Country or territory Target 5.A Reduce by three quarters, between 1990 and 2015, the maternal mortality ratio Indicator 5.2 Indicator 5.1 Proportion of births Maternal mortality ratio attended by skilled health personnel Level Level Level Level 2000-2001 2002-2008 1984-2005 1999-2008 Table A-19 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) Social Panorama of Latin America • 2010 247 0.6 ... ... ... 3.8 0.5 0.1 ... ... ... ... ... ... 1.3 0.3 ... ... ... ... ... ... ... 0.1 0.2 ... ... The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands 1.8 ... ... ... 3 1.2 2.1 ... ... ... ... ... ... 2.5 1.6 ... ... ... ... ... ... ... 2.4 1.5 ... ... 0.5 0.5 0.5 0.2 0.6 0.3 0.6 0.4 0.1 1.1 0.3 0.8 0.8 2.2 0.7 0.3 0.2 1.0 0.6 0.5 0.6 ... Level 2007 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 18.6 18.6 ... ... ... ... ... ... ... 19 ... ... ... 30 ... ... ... ... ... 15 ... ... Level 1996-2000 ... ... ... ... ... ... ... ... ... ... ... 52 ... 56 53 ... ... ... ... ... 39 52 ... ... ... ... 29.2 29.2 44 ... ... 18 ... 11 33 33 ... ... ... 21 32 ... 19 ... ... 31 65 ... Level 2001-2007 Indicator 6.2 Condom use at last high-risk sex (women) ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 19.9 19.9 ... ... ... ... 22 ... ... 9 ... ... ... 21 ... ... ... ... ... ... ... ... Level 1996-2000 ... ... ... ... ... ... ... ... ... ... ... 68 ... 53 67 ... ... ... ... ... 48 62 ... ... ... ... 22.2 22.6 48 ... ... 30 31 15 41 42 ... ... ... 34 38 20 ... ... ... ... 69 ... Level 2003-2007 Indicator 6.2 Condom use at last high-risk sex (men) 53.0 ... ... ... ... ... ... ... ... ... ... ... ... 53 ... ... ... ... ... ... ... ... ... ... ... ... 27.4 25.9 ... ... ... ... ... ... ... 36 ... ... ... 15 ... ... ... ... ... ... ... ... Level 2000-2006 50.0 ... ... ... ... ... 40 ... ... ... ... ... ... 50 60 ... ... ... ... ... ... ... 41 54 ... ... 38.1 37.6 ... 15 ... ... ... ... 52 41 ... ... ... 34 30 ... 22 ... ... 19 ... ... Level 2000-2007 Indicator 6.3 Proportion of population aged 15-24 years with comprehensive correct knowledge of HIV/AIDS (women) ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 25.3 25.3 ... ... ... ... ... ... ... 23 ... ... ... 28 ... ... ... ... ... ... ... ... Level 1996-2000 ... ... ... ... ... ... ... ... ... ... ... ... ... 47 ... ... ... ... ... ... ... ... ... ... ... ... 36.8 36.8 ... 18 ... ... ... ... ... 34 ... ... ... 40 ... ... ... ... ... ... ... ... Level 2003-2007 Indicator 6.3 Proportion of population aged 15-24 years with comprehensive correct knowledge of HIV/AIDS (men) ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 0.9 0.9 ... 0.82 ... ... ... ... ... 0.96 ... ... ... 0.76 ... ... 0.81 ... ... ... ... ... Level 1994-1998 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 0.8 0.8 ... 0.74 0.96 ... 0.85 ... ... 0.77 ... ... ... 0.86 1.08 ... 1.06 ... ... 0.85 ... ... Level 1996-2006 Indicator 6.4 Ratio of school attendance of orphans to school attendance of non-orphans aged 10-14 years a The Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, Economic Commission for Latin America and the Caribbean, U August 2010. indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. 0.3 0.3 0.2 0.1 0.4 0.1 0.1 0.1 0.1 0.6 0.1 0.1 0.1 1.2 1.3 0.2 0.1 0.4 0.1 0.1 0.1 ... Level 1990-2006 Latin America and the Caribbean b Latin America b Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela (Bolivarian Republic of) Country or territory Indicator 6.1 HIV prevalence among population aged 15-24 years (series available for persons aged 15 to 49) Target 6.A Have halted by 2015 and begun to reverse the spread of HIV/AIDS Goal 6 Combat HIV/AIDS, malaria and other diseases Table A-20 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) 248 Economic Commission for Latin America and the Caribbean (ECLAC) Caribbean b 44.5 ... ... ... ... 67 42 ... ... ... ... ... ... 37 33 ... ... ... ... ... ... ... 35 53 ... ... 46.5 47.1 71 18 78 68 34 95 95 24 24 46 31 26 41 54 26 42 25 42 55 ... Level 2006 52.2 ... ... ... ... 73 49 ... ... ... ... ... ... 45 43 ... ... ... ... ... ... ... 45 58 ... ... 52.9 53.2 73 22 80 82 38 95 95 38 42 51 37 41 47 57 30 56 22 48 56 ... Level 2007 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... … … ... ... ... ... ... ... ... ... ... ... ... 11.7 ... ... 1.8 ... ... ... ... ... Level 2000-2001 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... … … ... ... ... ... ... ... ... ... ... ... ... 5.1 ... ... ... ... ... ... ... ... Level 2006 Indicator 6.5 Indicator 6.8 Proportion of population Proportion of children with advanced HIV infection under 5 with fever who are with access to treated with appropriate antiretroviral drugs anti-malarial drugs 15.2 24 10 ... 44 7 40 19 7 15 ... 5 ... 27 7 ... 9 14 11 10 16 27 66 11 ... 19 87.8 89.5 60 255 84 38 53 18 25 114 167 82 74 306 98 61 108 47 60 317 28 35 Level 1990 21.6 22 5 ... 44 4 40 10 4 13 ... 4 ... 122 7 ... 8 7 4 9 14 25 116 11 ... 10 49.1 49.6 31 155 48 12 35 11 6 69 101 40 63 306 59 20 49 47 58 126 22 34 Level 2007 Indicator 6.9 Incidence associated with tuberculosis 74.5 ... ... ... ... ... 16 ... ... ... ... ... ... 200 5.2 ... ... ... 1.4 ... ... ... 150 ... ... ... 122.8 124.3 74 290 98 11 59 35 62 350 310 70 120 280 140 130 130 44 13 450 9.8 32 Level 1990 86.5 ... ... ... ... ... 43 ... ... ... ... ... ... 110 7.9 ... ... ... 1.4 ... ... ... 270 ... ... ... 37.1 37.2 22 170 29 3.6 37 2.9 1.8 95 110 18 110 290 79 8.4 26 14 40 46 12 34 Level 2008 Indicator 6.9 Prevalence associated with tuberculosis 8.8 ... ... ... ... ... 3.1 ... ... ... ... ... ... 22 1 ... ... ... 1 ... ... ... 17 ... ... ... 14.7 14.8 9.1 37 12 3 7.5 4 7.1 39 36 8.8 14 28 17 15 17 5.7 3.7 53 1.8 4.3 Level 1990 10.0 ... ... ... ... ... 5.1 ... ... ... ... ... ... 15 0.5 ... ... ... 0.5 ... ... ... 29 ... ... ... 4.8 4.9 3.1 22 3.8 0.5 4.6 0.5 0.5 12 13 2.7 12 32 9.5 1.4 4.1 2.8 5.4 8.7 1.7 4.3 Level 2008 Indicator 6.9 Death rates associated with tuberculosis 62.5 ... 44 ... 67 118 98 ... 130 94 ... ... ... 11 92 ... 0 ... 72 165 113 18 ... ... ... ... 32.1 32.0 4 39 4 73 30 31 82 9 5 46 43 2 2 13 72 12 14 102 76 73 Level 1994-2001 55.7 ... 284 ... 52 173 89 0 129 61 ... ... ... 39 83 ... 393 ... 77 155 139 49 ... ... ... 73 72.7 72.8 76 71 69 105 81 120 109 66 46 65 40 49 87 99 97 98 58 93 95 68 Level 1996-2007 82.2 ... 50 ... 72 100 88 ... 100 100 ... ... ... 91 67 ... 0 ... 68 25 67 86 ... ... ... ... 78.8 78.8 55 66 91 83 74 81 86 81 82 77 62 73 93 75 81 51 46 81 83 68 Level 1994-2003 68.4 ... 100 ... 75 100 75 ... 0 50 ... ... ... 68 41 ... 0 ... 80 100 80 86 ... ... ... 50 76.1 76.1 63 83 72 85 71 88 90 78 74 91 47 82 86 80 89 79 83 78 87 82 Level 1995-2006 Indicator 6.10 Indicator 6.10 Proportion of tuberculosis Proportion of tuberculosis cases detected under cases cured under directly directly observed treatment observed treatment short course short course Target 6.C Have halted by 2015 and begun to reverse the spread of malaria and other diseases Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, Economic Commission for Latin America and the Caribbean, U August 2010. a The indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands Latin America and the Latin America b Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela (Bolivarian Republic of) Country or territory Target 6.B Achieve, by 2010, universal access to treatment for HIV/AIDS for all those who need it Goal 6 Combat HIV/AIDS, malaria and other diseases Table A-21 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) Social Panorama of Latin America • 2010 249 80.8 71.40 20.46 2.20 51.45 4.65 72.50 24.70 48.40 66.67 91.80 11.77 49.40 76.73 31.86 43.90 35.00 1.50 45.50 13.89 27.87 23.08 94.72 45.81 80.00 35.00 The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands 80.8 71.40 20.46 2.20 51.45 4.65 72.50 24.40 48.40 61.33 91.80 11.77 47.20 76.73 31.30 43.90 35.00 1.50 46.00 13.89 27.87 28.21 94.72 44.06 80.00 27.90 44 569 ... 301 1 841 1 951 1 074 312 48 253 59 814 121 1 294 1 140 7 964 2 068 33 6 215 ... 66 165 81 1 811 16 958 ... ... Level Level 2005 1990 45.6 1 078 371 44.9 1 033 802 12.07 112 607 54.17 5 504 56.47 208 875 21.53 35 486 58.47 57 336 46.83 2 955 24.70 33 337 28.44 9 570 39.20 16 834 14.38 2 618 36.32 5 086 3.81 994 41.54 2 592 33.66 384 659 42.74 2 644 57.69 3 135 46.50 2 262 53.71 21 164 8.60 3 993 54.09 122 151 67 736 51 425 2 310 2 138 1 338 818 99 517 117 876 242 2 141 1 507 12 151 1 870 70 4 312 ... 136 381 198 2 438 33 601 ... ... Level 2006 1 513 117 1 445 381 173 536 11 403 352 524 60 100 63 422 7 854 29 627 20 357 31 328 6 461 11 766 1 811 7 194 436 150 4 334 6 428 3 986 38 643 6 864 171 593 Indicator 7.2 CO2 emissions (total, in thousands of metric tons of CO2) 6.2 ... 4.86 28.91 7.64 3.96 1.68 2.89 9.62 0.85 6.99 1.26 3.31 1.56 3.36 5.74 3.07 32.60 ... 1.62 1.20 0.74 4.50 13.86 ... ... Level 1990 2.5 2.4 3.46 0.83 1.40 2.69 1.64 0.96 3.14 1.31 1.64 0.51 0.57 0.14 0.53 4.58 0.64 1.30 0.53 0.97 1.29 6.19 8.8 4.12 5.06 22.26 6.53 4.57 2.90 4.44 11.13 1.74 4.44 2.29 4.85 2.04 4.50 4.71 12.03 22.83 ... 2.73 2.34 1.65 5.36 25.29 ... ... Level 2006 3.3 2.6 4.43 1.22 1.86 3.65 1.39 1.79 2.63 2.12 2.37 0.96 0.90 0.19 1.03 4.14 0.78 1.96 0.66 1.40 2.06 6.31 Indicator 7.2 CO2 emissions (in metric tons of CO2, per capita) 0.8 ... 0.38 ... ... ... 0.39 ... ... 0.14 ... 0.25 ... 1.04 0.65 ... ... ... ... 0.19 0.18 0.17 0.85 1.36 ... ... Level 1990 0.4 0.4 0.46 0.27 0.19 0.41 0.29 0.15 ... 0.39 0.30 0.13 0.17 0.09 0.20 0.46 0.34 0.21 0.13 0.22 0.18 0.65 0.9 ... 0.28 ... ... ... 0.43 ... ... 0.22 ... 0.34 ... 0.85 0.73 ... ... ... ... 0.21 0.25 0.24 0.76 1.20 ... ... Level 2006 0.3 0.3 0.38 0.32 0.21 0.29 0.19 0.19 ... 0.36 0.34 0.18 0.22 0.18 0.30 0.32 0.33 0.20 0.17 0.20 0.21 0.59 1 256 ... 426 ... 66 26 23 ... ... 2 ... 4 ... 19 431 ... ... ... ... 7 12 3 43 197 ... ... Level 1990 77 140 75 884 1 515 77 39 337 1 016 2 153 549 978 288 649 426 361 171 115 21 489 87 270 240 893 465 4 809 68 ... 1 ... 6 5 3 ... ... 0 ... 0 ... 1 3 ... ... ... ... 1 0 0 3 46 ... ... Level 2007 7 446 7 378 1 200 7 1 915 270 470 282 104 74 151 51 303 9 305 1 918 4 44 27 43 56 146 Indicator 7.2 Indicator 7.3 CO2 emissions Consumption of ozone(in kg of CO2 for each depleting substances dollar of GDP, 2000(in metric tons) constant dollars) 9.1 ... 3.3 ... ... ... 0.6 ... ... ... ... ... ... 0.6 9.6 ... ... ... 11.2 ... ... ... ... 7.7 ... ... Level 1990-1995 3.1 2.9 3.5 ... 0.7 ... 0.4 5.1 13.6 39.7 4.0 2.9 ... 7.0 ... ... ... ... ... 1.0 ... ... 11.2 ... 0.0 ... ... 112.5 0.8 ... ... ... ... ... ... 0.7 4.4 ... ... ... 12.1 ... ... ... 0.5 8.1 ... ... Level 2000 5.2 5.1 3.6 0.2 0.7 1.4 0.5 2.4 21.5 16.0 4.0 5.1 1.8 7.1 0.9 17.0 0.7 0.6 0.1 1.1 2.3 0.7 Indicator 7.5 Proportion of total water resources used 2.7 ... 0.7 ... 0.4 0.1 14.8 ... ... 3.7 ... 0.1 ... 0.0 1.7 ... ... ... ... 0.8 2.2 0.3 3.9 8.4 ... ... 5.9 ... 1.2 ... 1.0 0.1 30.2 ... ... 4.4 ... 0.1 ... 2.2 7.1 ... ... ... ... 0.8 2.4 0.3 13.2 8.5 ... ... 0.95 ... 0.94 ... 0.93 0.94 0.96 ... ... 0.94 ... 0.92 ... 0.98 0.87 ... ... ... ... 0.94 0.93 0.94 0.98 0.96 ... ... 0.7 ... 0.45 ... 0.73 0.50 0.59 ... ... 0.57 ... 0.47 ... 0.80 0.56 ... ... ... ... 0.75 0.65 0.60 0.75 0.86 ... ... Target 7.B Reduce biodiversity loss, achieving, by 2010, a significant reduction in the rate of loss Indicator 7.6 Indicator 7.7 Indicator 7.7 Proportion of Proportion Proportion terrestrial and of species of species marine areas threatened threatened protected with extinction with extinction (disaggregated) (animals) (plants) Level Level Level Level 1990 2008 2008 2008 9.5 21.1 0.93 0.7 9.7 21.6 0.93 0.7 5.0 6.2 0.93 0.74 8.9 21.2 0.97 0.68 9.0 28.9 0.93 0.64 13.6 14.0 0.92 0.55 24.5 30.3 0.92 0.61 16.3 22.9 0.94 0.66 12.9 15.5 0.85 0.50 ... ... 0.86 0.58 4.4 15.1 0.91 0.60 1.0 1.0 0.96 0.71 26.1 31.0 0.92 0.65 0.1 0.1 0.84 0.53 10.8 16.1 0.93 0.46 2.6 8.8 0.86 0.65 3.7 15.3 0.96 0.65 12.9 18.5 0.95 0.65 3.1 6.0 0.97 0.83 4.7 13.2 0.94 0.66 0.3 0.3 0.93 0.89 41.6 65.7 0.95 0.77 a The Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, Economic Commission for Latin America and the Caribbean, U August 2010. indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. Level 1990 49.1 48.4 12.89 57.91 61.47 20.38 59.15 50.22 18.74 28.44 49.91 18.10 43.79 4.21 66.00 36.16 53.86 58.79 53.25 54.81 5.17 58.98 Indicator 7.1 Proportion of land area covered by forest Latin America and the Caribbean b Latin America b Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela (Bolivarian Republic of) Country or territory Target 7.A Integrate the principles of sustainable development into country policies and programmes and reverse the loss of environmental resources Goal 7 Ensure environmental sustainability Table A-22 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) 250 Economic Commission for Latin America and the Caribbean (ECLAC) Social Panorama of Latin America • 2010 251 Table A-23 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a (Percentages) Goal 7 Ensure environmental sustainability Target 7.C Halve, by 2015, the proportion of people without sustainable access to safe drinking water and basic sanitation Country or territory Indicator 7.8 Proportion of population using an improved drinking water source (national) Indicator 7.9 Proportion of population using an improved sanitation facility (national) Target 7.D By 2020, to have achieved a significant improvement in the lives of at least 100 million slum dwellers Indicator 7.10 Proportion of urban population living in slums Level 1990-1995 Level 2000-2006 Level 1990-1995 Level 2000-2006 Level 1990 Level 2001-2005 Latin America and the Caribbean b Latin America b Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela (Bolivarian Republic of) 84.2 84.1 94.0 72.0 83.0 91.0 89.0 96.0 91.0 84.0 73.0 69.0 79.0 52.0 72.0 88.0 70.0 90.0 52.0 75.0 100.0 89.0 91.0 91.0 96.0 86.0 91.0 95.0 93.0 98.0 91.0 95.0 95.0 84.0 96.0 58.0 84.0 95.0 79.0 92.0 77.0 84.0 100.0 83.0 68.0 67.8 81.0 33.0 71.0 84.0 68.0 94.0 98.0 68.0 71.0 73.0 70.0 29.0 45.0 56.0 42.0 72.0 60.0 55.0 100.0 83.0 77.8 77.7 91.0 43.0 77.0 94.0 78.0 96.0 98.0 79.0 84.0 86.0 84.0 19.0 66.0 81.0 48.0 74.0 70.0 72.0 100.0 68.0 37.1 37.2 30.5 70.0 45.0 4.0 26.0 11.9 ... 56.4 28.1 44.7 65.8 84.9 24.0 23.1 80.7 30.8 36.8 60.4 ... 40.7 25.5 25.4 26.2 50.4 29.0 9.0 17.9 10.9 ... 17.6 21.5 28.9 42.9 70.1 34.9 14.4 45.5 23.0 17.6 36.1 ... 32.0 The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands 90.2 60.0 91.0 100.0 96.0 100.0 91.0 98.0 ... 97.0 84.0 95.0 98.0 83.0 92.0 ... 100.0 ... ... 99.0 98.0 ... 91.0 88.0 100.0 ... 93.8 60.0 91.0 100.0 97.0 100.0 91.0 98.0 ... 97.0 84.0 95.0 98.0 93.0 93.0 ... 100.0 ... ... 99.0 98.0 ... 92.0 94.0 100.0 ... 83.5 99.0 96.0 ... 100.0 100.0 47.0 100.0 ... 83.0 78.0 97.0 64.0 69.0 83.0 ... 96.0 ... ... 96.0 89.0 ... 92.0 93.0 96.0 ... 85.2 99.0 95.0 ... 100.0 99.0 47.0 100.0 ... 84.0 78.0 97.0 64.0 81.0 83.0 ... 96.0 ... ... 96.0 89.0 ... 82.0 92.0 96.0 ... 23.7 40.6 6.9 ... ... ... 54.2 ... ... 16.6 12.9 6.9 6.9 4.9 29.2 2.0 ... ... ... ... 11.9 ... 6.9 34.7 ... ... 43.3 36.7 4.8 ... ... ... 47.3 ... ... 14.0 10.5 6.0 5.4 33.7 60.5 1.6 ... ... ... ... 11.9 ... 3.9 24.7 ... ... Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, U Economic Commission for Latin America and the Caribbean, August 2010. a The indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. 252 Economic Commission for Latin America and the Caribbean (ECLAC) Table A-24 Latin America and the Caribbean: PROGRESS TOWARDS THE MILLENNIUM DEVELOPMENT GOALS a Goal 8 Develop a global partnership for development Target 8.F In cooperation with the private sector, make available the benefits of new technologies, especially information and communications technologies Country or territory Indicator 8.14 Telephone lines per 100 population Indicator 8.15 Cellular subscribers per 100 population Level 1990-1992 Level 2001-2007 Level 2000 Latin America and the Caribbean b Latin America b Argentina Bolivia (Plurinational State of) Brazil Chile Colombia Costa Rica Cuba Dominican Republic Ecuador El Salvador Guatemala Haiti Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela (Bolivarian Republic of) 6.2 6.0 9.3 2.7 6.3 6.6 6.9 9.2 3.2 4.8 4.8 2.5 2.1 0.7 1.8 6.4 1.2 9.0 2.7 2.6 13.4 7.5 17.8 17.7 24.0 7.1 20.5 20.7 17.2 32.2 9.3 9.3 13.5 15.8 10.5 1.1 11.6 18.5 4.4 14.8 6.4 9.6 28.9 18.4 12.1 12.1 17.6 7.0 13.3 22.1 5.4 5.4 0.1 8.5 3.9 11.8 7.7 0.7 2.4 14.1 1.8 13.9 15.0 4.9 12.3 22.3 The Caribbean b Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cayman Islands Dominica French Guiana Grenada Guadaloupe Guyana Jamaica Martinica Montserrat Netherlands Antilles Puerto Rico Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Suriname Trinidad and Tobago Turks and Caicos Islands United States Virgin Islands 17.0 30.5 25.2 28.2 27.4 28.1 9.3 39.3 46.9 16.2 ... 15.8 ... 2.2 4.4 ... 34.5 24.7 27.8 23.9 12.4 12.0 9.1 13.6 24.8 45.6 23.8 47.0 45.7 37.2 40.1 50.0 11.8 55.3 92.9 26.7 ... 26.7 ... 14.7 13.6 ... 71.7 46.1 26.2 59.3 32.6 19.0 18.0 23.1 14.8 64.1 15.9 19.3 28.8 16.3 10.5 10.7 6.9 ... 27.0 1.5 ... 4.2 ... 5.4 14.2 ... 12.5 … 24.2 3.0 1.6 2.0 9.5 12.6 ... 31.6 Level 2002-2007 Indicator 8.16 Internet users per 100 population Level 2000 Level 2002-2007 66.7 66.3 102.2 34.2 63.1 83.7 73.5 33.8 1.8 56.5 75.6 89.5 76.0 26.1 58.9 62.5 37.9 90.1 76.6 55.3 90.0 86.1 3.9 3.8 7.1 1.4 2.9 16.5 2.1 5.8 0.5 4.0 1.5 1.1 0.7 0.3 1.2 5.1 1.0 6.6 0.7 3.1 10.5 3.4 25.8 25.6 25.9 10.5 35.2 31.0 26.2 33.6 11.6 17.2 13.2 11.1 10.2 10.4 6.0 20.8 2.8 22.3 8.7 27.4 29.0 20.7 87.5 107.0 135.4 140.4 112.9 87.8 41.1 37.8 76.6 53.3 ... 44.6 ... 37.5 98.9 ... 89.0 110.6 84.8 23.7 65.7 91.8 70.8 113.2 99.6 71.8 7.2 22.3 6.5 15.2 4.4 3.8 6.2 ... 44.4 7.7 ... 4.1 ... 6.7 3.1 ... ... 1.1 10.4 6.7 5.2 3.0 2.7 7.8 ... 13.5 32.9 34.0 72.3 23.1 36.2 59.4 11.1 18.9 46.6 37.2 ... 21.8 ... 25.8 55.3 ... 30.0 ... 25.1 34.7 66.7 47.3 9.6 16.0 ... 26.9 Source: nited Nations, Achieving the Millennium Development Goals with Equality in Latin America and the Caribbean: Progress and Challenges (LC/G.2460), Santiago, Chile, U Economic Commission for Latin America and the Caribbean, August 2010. a The indicators are presented in numerical order; those for which there is no information have not been included. b Weighted averages. Publicaciones de la CEPAL / ECLAC publications Comisión Económica para América Latina y el Caribe / Economic Commission for Latin America and the Caribbean Casilla 179-D, Santiago de Chile. E-mail: publications@cepal.org Véalas en: www.cepal.org/publicaciones Publications may be accessed at: www.eclac.org Revista CEPAL / CEPAL Review La Revista se inició en 1976 como parte del Programa de Publicaciones de la Comisión Económica para América Latina y el Caribe, con el propósito de contribuir al examen de los problemas del desarrollo socioeconómico de la región. Las opiniones expresadas en los artículos firmados, incluidas las colaboraciones de los funcionarios de la Secretaría, son las de los autores y, por lo tanto, no reflejan necesariamente los puntos de vista de la Organización. La Revista CEPAL se publica en español e inglés tres veces por año. Los precios de suscripción anual vigentes para 2010 son de US$ 30 para ambas versiones. El precio por ejemplar suelto es de US$ 15 para ambas versiones. Los precios de suscripción por dos años son de US$ 50 para ambas versiones. CEPAL Review first appeared in 1976 as part of the Publications Programme of the Economic Commission for Latin America and the Caribbean, its aim being to make a contribution to the study of the economic and social development problems of the region. The views expressed in signed articles, including those by Secretariat staff members, are those of the authors and therefore do not necessarily reflect the point of view of the Organization. CEPAL Review is published in Spanish and English versions three times a year. Annual subscription costs for 2010 are US$ 30 for both versions. The price of single issues is US$ 15 in both cases. The cost of a two-year subscription is US$ 50 for both versions. Informes periódicos institucionales / Annual reports Todos disponibles para años anteriores / Issues for previous years also available • • • • • • Balance preliminar de las economías de América Latina y el Caribe, 2009, 184 p. Preliminary Overview of the Economies of Latin America and the Caribbean, 2009, 166 p. Estudio económico de América Latina y el Caribe 2009-2010, 136 p. Economic Survey of Latin America and the Caribbean 2009-2010, 130 p. Panorama de la inserción internacional de América Latina y el Caribe, 2009-2010, 176 p. Latin America and the Caribbean in the World Economy, 2009-2010, 168 p. Panorama social de América Latina, 2009, 218 p. Social Panorama of Latin America, 2009, 208 p. La inversión extranjera directa en América Latina y el Caribe, 2009, 162 p. Foreign Direct Investment of Latin America and the Caribbean, 2009, 158 p. Anuario estadístico de América Latina y el Caribe / Statistical Yearbook for Latin America and the Caribbean (bilingüe/bilingual), 2010, 314 p. Libros de la CEPAL 110 Envejecimiento en América Latina. Sistema de pensiones y protección social integral, Antonio Prado y Ana Sojo (eds.), 304 p. 109 Modeling Public Policies in Latin America and the Caribbean, Carlos de Miguel, José Durán Lima, Paolo Giordiano, Julio Guzmán, Andrés Schuschny and Masazaku Watanuki (eds.), 322 p. 108 Alianzas público-privadas. Para una nueva visión estratégica del desarrollo, Robert Devlin y Graciela Moguillansky, 2010, 196 p. 107 Políticas de apoyo a las pymes en América Latina. Entre avances innovadores y desafíos institucionales, Carlos Ferraro y Giovanni Stumpo, 392 p. 106 Temas controversiales en negociaciones comerciales Norte-Sur, Osvaldo Rosales V. y Sebastián Sáez C. (compiladores), 322 p. 105 Regulation, Worker Protection and Active Labour-Market Policies in Latin America, Jürgen Weller (ed.), 2009, 236 p. 104 La República Dominicana en 2030: hacia una sociedad cohesionada, Víctor Godínez y Jorge Máttar (coords.), 2009, 582 p. 103 L’Amérique latine et les Caraïbes au seuil du troisième millénaire, 2009, 138 p. 102 Migración interna y desarrollo en América Latina entre 1980 y 2005, Jorge Rodríguez y Gustavo Busso, 2009, 272 p. 101 Claves de la innovación social en América Latina y el Caribe, Adolfo Rodríguez Herrera y Hernán Alvarado Ugarte, 2009, 236 p. 100 Envejecimiento, derechos humanos y políticas públicas, Sandra Huenchuan (ed.), 2009, 232 p. 99 Economía y territorio en América Latina y el Caribe. Desigualdades y políticas, 2009, 212 p. 98 La sociedad de la información en América Latina y el Caribe: desarrollo de las tecnologías y tecnologías para el desarrollo, Wilson Peres y Martin Hilbert (eds.), 2009, 388 p. 97 América Latina y el Caribe: migración internacional, derechos humanos y desarrollo, Jorge Martínez Pizarro (ed.), 2008, 375 p. 96 Familias y políticas públicas en América Latina: una historia de desencuentros, Irma Arriagada (coord.), 2007, 424 p. 95 Centroamérica y México: políticas de competencia a principios del siglo XXI, Eugenio Rivera y Claudia Schatan (coords.), 2008, 304 p. 94 América Latina y el Caribe: La propiedad intelectual después de los tratados de libre comercio, Álvaro Díaz, 2008, 248 p. Copublicaciones recientes / Recent co-publications Las clases medias en América Latina. Retrospectiva y nuevas tendencias, Rolando Franco, Martín Hopenhayn y Arturo León (eds.) Sesenta años de la CEPAL. Textos seleccionados del decenio 1998-2008, Ricardo Bielschowsky (comp.), CEPAL/Siglo Veintiuno, Argentina, 2010. El nuevo escenario laboral latinoamericano. Regulación, protección y políticas activas en los mercados de trabajo, Jürgen Weller (ed.), CEPAL/Siglo Veintiuno, Argentina, 2010. Internacionalización y expansión de las empresas eléctricas españolas en América Latina, Patricio Rozas, CEPAL/Lom, Chile, 2009. Gobernanza corporativa y desarrollo de mercados de capitales en América Latina, Georgina Núñez, Andrés Oneto y Germano M. de Paula (coords.), CEPAL/Mayol, Colombia, 2009. EnREDos. Regulación y estrategias corporativas frente a la convergencia tecnológica, Marcio Wohlers y Martha García-Murillo (eds.), CEPAL/Mayol, Colombia, 2009. Desafíos y oportunidades de la industria del software en América Latina, Paulo Tigre y Felipe Silveira Marques (eds.), CEPAL/Mayol, Colombia, 2009. ¿Quo vadis, tecnología de la información y de las comunicaciones?, Martin Hilbert y Osvaldo Cairó (eds.), CEPAL/Mayol, Colombia, 2009. O Estruturalismo latino-americano, Octavio Rodríguez, CEPAL/Civilização Brasileira, 2009. L’avenir de la protection sociale en Amérique latine. Accessibilité, financement et solidarité, CEPALC/Eska, France, 2009. Fortalecer los sistemas de pensiones latinoamericanos. Cuentas individuales por reparto, Robert Holzmann, Edward Palmer y Andras Uthoff (eds.), CEPAL/Mayol, Colombia, 2008. Competition Policies in Emerging Economies. Lessons and Challenges from Central America and Mexico, Claudia Schatan and Eugenio Rivera Urrutia (eds.), ECLAC/Springer, USA, 2008. Coediciones recientes / Recent co-editions Clases medias y desarrollo en América Latina, Alicia Bárcena y Narcís Serra (eds.), CEPAL/SEGIB/CIDOB, Chile, 2010. Innovar para crecer. Desafíos y oportunidades para el desarrollo sostenible e inclusivo en Iberoamérica, CEPAL/SEGIB, Chile, 2010. Espacios iberoamericanos. Iberoamérica frente a la crisis, CEPAL/SEGIB, Chile, 2009. Espaços Ibero-Americanos. A Ibero-América em face da crise, CEPAL/SEGIB, Chile, 2009. The United Nations Regional Commissions and the Climate Change Challenges, ECLAC/ECA/ECE/ESCAP/ESCWA, 2009. Hacia un desarrollo inclusivo. El caso de Chile, Osvaldo Sunkel y Ricardo Infante (eds.), CEPAL/OIT/Fundación Chile 21, Chile, 2008. Reformas para la cohesión social en América Latina. Panorama antes de la crisis, Alicia Bárcena y Narcís Serra (eds.), CEPAL/SEGIB/CIDOB, Chile, 2008. El envejecimiento y las personas de edad. Indicadores sociodemográficos para América Latina y el Caribe, CEPAL/UNFPA, 2009. Espacios iberoamericanos: la economía del conocimiento, CEPAL/SEGIB, Chile, 2008. Hacia la revisión de los paradigmas del desarrollo en América Latina, Oscar Altimir, Enrique V. Iglesias, José Luis Machinea (eds.), CEPAL/SEGIB, Chile, 2008. Por uma revisāo dos paradigmas do desenvolvimento na América Latina, Oscar Altimir, Enrique V. Iglesias, José Luis Machinea (eds.), CEPAL/SEGIB, Chile, 2008. Hacia un nuevo pacto social. Políticas económicas para un desarrollo integral en América Latina, José Luis Machinea y Narcís Serra (eds.) CEPAL/CIDOB, España, 2008. Cuadernos de la CEPAL 94 El cuidado en acción. Entre el derecho y el trabajo, Sonia Montaño Virreira y Coral Calderón Magaña (coords.), 2010, 236 p. 93 Privilegiadas y discriminadas. Las trabajadoras del sector financiero, Flavia Marco Navarro y María Nieves Rico Ibáñez (eds.), 2009, 300 p. 92 Estadísticas para la equidad de género: magnitudes y tendencias en América Latina, Vivian Milosavljevic, 2007, 186 pp. Cuadernos estadísticos de la CEPAL 38 Indicadores ambientales de América Latina y el Caribe, 2009. Solo disponible en CD, 2010. 37 América Latina y el Caribe: Series históricas de estadísticas económicas 1950-2008. Solo disponible en CD, 2009. 36 Clasificaciones estadísticas internacionales incorporadas en el Banco de Datos de Comercio Exterior de América Latina y el Caribe de la CEPAL (Revisión 3). Solo disponible en CD, 2008. 35 Resultados del Programa de Comparación Internacional para América del Sur. Solo disponible en CD, 2007. Observatorio demográfico ex Boletín demográfico / Demographic Observatory formerly Demographic Bulletin (bilingüe/bilingual) Edición bilingüe (español e inglés) que proporciona información estadística actualizada, referente a estimaciones y proyecciones de población de los países de América Latina y el Caribe. Incluye también indicadores demográficos de interés, tales como tasas de natalidad, mortalidad, esperanza de vida al nacer, distribución de la población, etc. El Observatorio aparece dos veces al año, en los meses de enero y julio. Suscripción anual: US$ 20.00. Valor por cada ejemplar: US$ 15.00. Bilingual publication (Spanish and English) proving up-to-date estimates and projections of the populations of the Latin American and Caribbean countries. Also includes various demographic indicators of interest such as fertility and mortality rates, life expectancy, measures of population distribution, etc. The Observatory appears twice a year in January and July. Annual subscription: US$ 20.00. Per issue: US$ 15.00. Notas de población Revista especializada que publica artículos e informes acerca de las investigaciones más recientes sobre la dinámica demográfica en la región, en español, con resúmenes en español e inglés. También incluye información sobre actividades científicas y profesionales en el campo de población. La revista se publica desde 1973 y aparece dos veces al año, en junio y diciembre. Suscripción anual: US$ 20.00. Valor por cada ejemplar: US$ 12.00. Specialized journal which publishes articles and reports on recent studies of demographic dynamics in the region, in Spanish with abstracts in Spanish and English. Also includes information on scientific and professional activities in the field of population. Published since 1973, the journal appears twice a year in June and December. Annual subscription: US$ 20.00. Per issue: US$ 12.00. Series de la CEPAL Comercio internacional / Desarrollo productivo / Desarrollo territorial / Estudios estadísticos y prospectivos / Estudios y perspectivas (Bogotá, Brasilia, Buenos Aires, México, Montevideo) / Studies and Perspectives (The Caribbean, Washington) / Financiamiento del desarrollo / Gestión pública / Informes y estudios especiales / Macroeconomía del desarrollo / Manuales / Medio ambiente y desarrollo / Mujer y desarrollo / Población y desarrollo / Políticas sociales / Recursos naturales e infraestructura / Seminarios y conferencias. Véase el listado completo en: www.cepal.org/publicaciones / A complete listing is available at: www.cepal.org/publicaciones Las publicaciones de la Comisión Económica para América Latina y el Caribe (CEPAL) y las del Instituto Latinoamericano y del Caribe de Planificación Económica y Social (ILPES) se pueden adquirir a los distribuidores locales o directamente a través de: Publicaciones de las Naciones Unidas 2 United Nations Plaza, Room DC2-853 Nueva York, NY, 10017 Estados Unidos Tel. (1 800)253-9646 Fax (1 212)963-3489 E-mail: publications@un.org Publicaciones de las Naciones Unidas Sección de Ventas Palais des Nations 1211 Ginebra 10 Suiza Tel. (41 22)917-2613 Fax (41 22)917-0027 Unidad de Distribución Comisión Económica para América Latina y el Caribe (CEPAL) Av. Dag Hammarskjöld 3477, Vitacura 7630412 Santiago Chile Tel. (56 2)210-2056 Fax (56 2)210-2069 E-mail: publications@cepal.org Publications of the Economic Commission for Latin America and the Caribbean (ECLAC) and those of the Latin American and the Caribbean Institute for Economic and Social Planning (ILPES) can be ordered from your local distributor or directly through: United Nations Publications 2 United Nations Plaza, Room DC2-853 New York, NY, 10017 USA Tel. (1 800)253-9646 Fax (1 212)963-3489 E-mail: publications@un.org United Nations Publications Sales Sections Palais des Nations 1211 Geneva 10 Switzerland Tel. (41 22)917-2613 Fax (41 22)917-0027 Distribution Unit Economic Commission for Latin America and the Caribbean (ECLAC) Av. Dag Hammarskjöld 3477, Vitacura 7630412 Santiago Chile Tel. (56 2)210-2056 Fax (56 2)210-2069 E-mail: publications@eclac.org