Maintitle

Copyrights

José Manuel Salazar-Xirinachs

Executive Secretary

Javier Medina

Deputy Executive Secretary a.i.

Raúl García-Buchaca

Deputy Executive Secretary

for Management and Programme Analysis

Alberto Arenas de Mesa

Chief, Social Development Division

Rolando Ocampo

Chief, Statistics Division

Simone Cecchini

Chief, Latin American and Caribbean Demographic

Centre (CELADE)-Population Division of ECLAC

Ana Güezmes García

Chief, Division for Gender Affairs

Sally Shaw

Chief, Documents and Publications Division

The Social Panorama of Latin America and the Caribbean is a publication prepared annually by the Social Development Division of the  Economic Commission for Latin America and the Caribbean (ECLAC), led by Alberto Arenas de Mesa, and by the ECLAC Statistics Division, headed by Rolando Ocampo, with the collaboration of the Latin American and Caribbean Demographic Centre (CELADE)-Population Division of ECLAC, headed by Simone Cecchini, and the Division for Gender Affairs of ECLAC, headed by Ana Güezmes García.

The preparation of the 2023 edition was coordinated by Alberto Arenas de Mesa with the support of Daniela Trucco, who worked on the drafting together with Carmen Álvarez, Camila Barón, Alejandro Canales, Marcela Cerrutti, Helena Cruz Castanheira, Fabiana Del Popolo, Andrés Espejo, Nincen Figueroa, Álvaro Fuentes, Raúl Holz, Mariana Huepe, Carlos Kröll, Carlos Maldonado, Xavier Mancero, María Luisa Marinho, Jorge Martínez, Rodrigo Martínez, Claudia Robles, Jorge Rodríguez, Lucía Scuro, Zulma Sosa and Pablo Villatoro. Mario Acuña, Lenin Aguinaga, Haydee Alonzo, Catalina Alviz, Edmundo Caillaux, David Candia, Miguel Castillo, María Paz Collinao, Andrés Espejo, Ernesto Espíndola, Álvaro Fuentes, Pablo Herrera, Carlos Howes, Isabel Jacas, Rocío Miranda, Tamara Vaz de Moraes Santos and Pablo Villatoro worked on the data collection and statistical processing. Valuable contributions and comments relating to different sections of the document were received from Jorge Cadenasso, Verónica Cano, María Castro, Simone Cecchini, Diego Collado, Macarena Contreras, Felipe Correa, Miguel del Castillo Negrete, Ernesto Espíndola, Daniela González, Ana Güezmes, Daniela Huneeus, Marco Llinás, Diego Olivares, Amalia Palma, Javiera Ravest, Raquel Santos Garcia and Marisa Weinstein.

The United Nations and the countries it represents assume no responsibility for the content of links to external sites in this publication.

United Nations publication

ISBN: 978-92-1-122133-6 (print) • ISBN: 978-92-1-002248-4 (pdf) • ISBN: 978-92-1-358664-8 (ePub)

Sales No.: E.23.II.G.5 • LC/PUB.2023/18-P/Rev.1 • Distribution: G • Copyright © United Nations, 2023 • All rights reserved

Printed at United Nations, Santiago • S.23-01205

Explanatory notes:

Three dots indicate that data are not available or are not separately reported.

A dash indicates that the amount is nil or negligible.

A full stop is used to indicate decimals.

The word “dollars” refers to United States dollars, unless otherwise specified.

A slash between years (e.g. 2022/2023) indicates a 12-month period falling between the two years.

Individual figures and percentages in tables may not always add up to the corresponding total because of rounding..

This publication should be cited as: Economic Commission for Latin America and the Caribbean (ECLAC), Social Panorama of Latin America and the Caribbean, 2023 (LC/PUB.2023/18-P/Rev.1), Santiago, 2023.

Applications for authorization to reproduce this work in whole or in part should be sent to the Economic Commission for Latin America and the Caribbean (ECLAC), Documents and Publications Division, publicaciones.cepal@un.org. Member States and their governmental institutions may reproduce this work without prior authorization, but are requested to mention the source and to inform ECLAC of such reproduction.

Contents

Maintitle

Copyrights

Introduction

Chapter I

Income inequality and poverty and their links to labour inclusion

Chapter II

From access to inclusion: key considerations for reducing inequality and informality in the labour market

Chapter III

Labour inclusion amid the challenges of gender equality in care work and international migration in the region

Chapter IV

Institutional frameworks and social spending: challenges for labour inclusion

Introduction

A. From labour market access to labour inclusion: a priority challenge for the region

B. Slow-motion crisis in labour inclusion: employment growth falls to historical lows, with high levels of informality

C. The increase in labour income contributed to reducing poverty and inequality, in a context of extremely concentrated wealth

D. The design of labour inclusion policies must target reducing social inequality

E. Gender inequalities in labour inclusion can only be eradicated with comprehensive strategies

F. Labour inclusion policies are conditioned by population ageing

G. Social spending is declining relative to GDP, but remains above pre-pandemic level

H. There is an urgent need to increase investment in labour inclusion policies with a life-cycle focus

I. Labour inclusion policies as a key axis of inclusive social development

J. Labour inclusion is closely linked to social protection systems and requires comprehensive actions

K. Presentation and summary of the key messages of the four chapters

Bibliography

A. From labour market access to labour inclusion: a priority challenge for the region

On 5 May 2023, the World Health Organization (WHO) announced the end of the global public health emergency caused by the coronavirus disease (COVID-19) pandemic (United Nations, 2023), marking a milestone in recent world history. However, Latin America and the Caribbean still faces structural challenges in a context of great uncertainty owing to economic, climatic, technological and geopolitical shocks, compounded by other ongoing transformations. The region is beset by the consequences of cascading crises that have created a protracted social crisis, particularly in health and education (as highlighted in previous years in the Social Panorama of Latin America and the Caribbean), food and energy insecurity, and a rise in the cost of living (ECLAC, 2022a). In addition, the care crisis and gender inequalities have intensified.

Compounding this situation, late 2023 marks the end of a decade begun in 2014 during which the region’s average growth has been extremely slow, at only 0.8%, less than half the average growth rate for the “lost decade” of the 1980s (ECLAC, 2023a). Aside from the recent cascading crises, these 10 years of lacklustre growth have resulted in cumulative vicious circles, which have led the region into a double trap of low growth and high levels of inequality. Combating this situation requires policy strategies to drive a development pattern based on higher, sustained, inclusive and sustainable growth (Salazar-Xirinachs, 2022 and 2023).

Despite the aforementioned negative trends, some more positive indicators can also be noted, in particular, a fall in rates of poverty and extreme poverty in 2022, a reduction in income inequality as measured by the Gini index, an increase in labour participation and employment rates, and a drop in unemployment. In addition, inflation is trending down, although it is likely to remain above pre-pandemic levels (ECLAC, 2023b). However, growth in Latin America and the Caribbean is likely to remain sluggish in 2023, with an estimated GDP expansion of 1.7%, significantly lower than the 3.8% recorded in 2022, and possibly as little as 1.5% in 2024 (ECLAC, 2023a and 2023b).

In this context, sustained progress in eradicating poverty and reversing the development crisis will depend on the efforts made by countries to transform a series of structural conditions underlying these phenomena.

Given the role that employment and labour markets play in household and individual well-being, this edition of Social Panorama of Latin America and the Caribbean is devoted to the challenges and opportunities of labour inclusion. This is a priority area for advancing successful strategies towards inclusive social development, because labour markets can either transmit and reproduce inequality, inequity and discrimination, and thus be corrosive for social cohesion, or else they can function as major engines of social mobility, increased income, fulfilment of labour rights and higher living standards, and thus contribute to well-being and social cohesion.

The Economic Commission for Latin America and the Caribbean (ECLAC) has argued that employment and the buoyancy of labour markets is a master key to tackling inequality and strengthening social mobility and social cohesion, while playing a fundamental role in personal development (ECLAC, 2010, 2012 and 2014). Moreover, not just any form of labour market access or employment is sufficient for this to be achieved. It is necessary to advance a strategy that addresses the structural heterogeneity of the economies and confronts a reality in which a large proportion of workers are employed in informal jobs, with low productivity and insufficient pay. This calls for labour inclusion policies that act on persistent income inequality, structural deficits in social protection and the unequal sexual division of labour in the region.

Labour inclusion is a central component of inclusive social development, which seeks to ensure that all labour force participants have access to decent jobs that guarantee adequate levels of pay and social protection coverage. This is a dynamic process that must be addressed in its complexity. Labour inclusion consists, in a complementary manner, of labour market access and the working conditions obtained (see diagram 1). Labour inclusion policies must also address the entry barriers and obstacles that most affect certain population groups, which are linked to the structural axes of the region’s social inequality matrix. This, in turn, is conditioned by the capacity of labour institutions and the production structure of the different countries.

Diagram 1

Labour inclusion

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

The countries of the region need to strengthen their labour inclusion policies to confront the challenges of the current social and economic situation, and pursue a strategy of inclusive social development, promoting the achievement of the 2030 Agenda for Sustainable Development, in particular Sustainable Development Goal (SDG) 8, on decent work and economic growth, in conjunction with regional commitments in this area. This is made all the more urgent by transformations that are currently under way that will affect labour markets, including rapid population ageing, the care crisis and migratory dynamics, the climate crisis and the challenges of a just transition, as well as technological revolutions. Against this backdrop, it is essential to anticipate adverse and destructive impacts and respond with policies that offset them and turn vicious circles into virtuous ones, the very essence of development processes.

B. Slow-motion crisis in labour inclusion: employment growth falls to historical lows, with high levels of informality

In the labour dimension, Latin America and the Caribbean has been living through a slow-motion crisis since 2010, as can be seen in various labour indicators. As happened with the GDP growth rate, the number of people employed grew by just 1.26% during the 2014–2023 decade, less than half of the 3.2% recorded in the “lost decade” of the 1980s (see figure 1). The COVID-19 pandemic accentuated this trend and triggered the deepest crisis in Latin American and Caribbean labour markets since 1950. In 2020, job creation actually declined for the first time in 70 years.

Although certain dimensions of labour markets improved between 2020 and 2022, this reflects a cyclical recovery of economic growth, or rebound effect after the 2020 contraction, which is unsustainable (ECLAC/ILO, 2023) and a labour market recovery that has been incomplete and uneven (ECLAC, 2022b and 2022c). In 2022, the labour participation rate increased for the second consecutive year, and unemployment dropped sharply, as workers rejoined the labour force after abandoning it in large numbers during the pandemic shock.

Figure 1

Latin America and the Caribbean (21 countries):a growth rate of the number of employees, 1951–2023

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of ECLAC, Economic Survey of Latin America and the Caribbean, 2023, (LC/PUB.2023/11-P), Santiago, 2023; and official figures from the University of Groningen and the International Labour Organization (ILO).

Note: Figures for 2023 correspond to estimations presented in ECLAC (2023b).

a Argentina, Belize, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Trinidad and Tobago, and Uruguay.

Projections for 2023 show that the rate of recovery of these variables has tended to stall (ECLAC, 2023b). On average, in 2023, the labour participation rate is estimated still to be slightly below pre-pandemic levels (63% in 2023 compared to 63.3% in 2019). The data show unemployment dropping below pre-pandemic levels, from 8% in 2019 to 6.8% in 2023, thus moderating the decline observed until 2022, when it had reached 7% (see figure 2). Nonetheless, the labour market recovery has not been associated with a narrowing of the gaps between men and women that have existed historically (ECLAC, 2022b, 2022c and 2023b).

The effects that the crisis has had on the most vulnerable populations and the low growth rates forecast for 2023 and 2024, raise doubts as to the possibility for improvement in the region’s labour indicators in the next two years (ECLAC, 2023a). The lacklustre growth of the regional economy projected for 2023 will likely result in less vigorous job creation, while the estimated 1.9% increase in employment in 2023 is well below the 5.4% growth recorded in 2022 (ECLAC, 2023b).

Employment surveys in 12 of the region’s countries estimate that 49% of workers were employed informally in the fourth quarter of 2022. Although this is slightly less than in the first quarter of 2019, representing a progressive reduction since the fourth quarter of 2021, its magnitude demands priority attention for the implementation of a regional agenda focused on labour inclusion. This phenomenon is reflected in 54.3% of the economically active population in Latin America not contributing to pension systems in 2021, which signifies a very significant gap in their present and future access to social protection (Arenas de Mesa, Robles and Vila, 2023). It should also be noted that 17% of the employed were living in poverty and 36.8% had labour incomes below the minimum wage in 2022, according to information from household and employment surveys in 14 of the region’s countries.

Figure 2

Latin America and the Caribbean (20 countries):a labour participation and unemployment rates, 2019–2023

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of ECLAC, Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago, 2023; regional employment surveys and projections.

Note: The 2020 and 2021 data may have problems of comparability with the 2019 data, owing to adjustments in statistical processes that the statistical and census institutes have implemented because of the situation generated by the COVID-19 pandemic.

a Argentina, Barbados, Belize, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Trinidad and Tobago, and Uruguay.

b Values for 2023 estimated in ECLAC (2023b).

In view of the above, this edition of Social Panorama of Latin America and the Caribbean reiterates that labour market access alone is not sufficient to advance towards inclusive social development; and that it is crucial to promote labour inclusion based on a more dynamic labour market, anchored in productive development policies in growth-driving sectors, and ensuring not only greater job creation, but also an adequate level of pay and social protection coverage, thus addressing the region’s structural problems in this area.

C. The increase in labour income contributed to reducing poverty and inequality, in a context of extremely concentrated wealth

Changes in the labour market during 2022, in the wake of economic recovery following the COVID-19 pandemic, led to increases in both labour income and total household income in most countries. However, these gains were partially eroded by high inflation, especially in households living in conditions of poverty and vulnerability, which spend all, or most, of their income on essential goods and services. In 2022, the real income of households in the first quintile outpaced that of the richest quintile in most of the countries analysed. Compared to 2019, individuals in the first quintile saw their incomes rise by 0.8% more than inflation, while those in the richest quintile saw their incomes fall by 1.8%, thus resulting in a reduction in inequality. The Gini inequality index, estimated on the basis of household surveys, fell by 1.1% per year, on average, between 2019 and 2022, a steeper fall than recorded between 2014 and 2019 (-0.2% per year). In nine out of 12 countries with information comparable to that of 2019, the Gini index in 2022 was lower than it was three years earlier.

Despite these improvements, income disparities in the countries of the region remain very wide. These are manifested not only in total income, but also in labour income, which is the main resource for households in all income strata. In the 13 countries that have data up to 2022, the total amount of income from paid work captured by the richest decile was 2.7 times that received by the four poorest deciles, while in terms of total income captured, the multiple was 2.4 times.

Owing to the large share of labour income in total income, the changes in both income streams in each quintile between 2019 and 2022 were of similar sign and magnitude; in other words, most of the distributional changes originated in the labour market. In some countries, non-labour income also contributed to narrowing the gaps between extreme quintiles, although in most cases its share was small. This is not to deny that non-contributory public transfers play an important role in preventing greater inequality. In 2022, this source of income resulted in the Gini index being 3.4% lower than it would have been in its absence. In 2020, the year in which exceptional transfers were put in place to mitigate the effects of the pandemic, this percentage was 5.6%.

The economic inequalities manifested by income gaps are magnified by the concentration of wealth. Along with income inequality, the extreme concentration of capital is one of the most obvious expressions of inequality and is strongly influenced by the economic and social structure. Advantageous positions in the social structure tend to be transmitted from generation to generation. There is evidence not only of a negative correlation between wealth inequality and intergenerational social mobility (Fisher and others, 2016; Yang and Zhou, 2022; CAF, 2022), but also that the transmission of socioeconomic status between generations is stronger in the upper part of the distribution (OECD, 2018; Waldenström, Adermon and Lindahl, 2016).

The wealth of billionaires[1] in the region has fluctuated widely in recent years, reflecting economic turbulence. The total wealth of the 105 billionaires in Latin America and the Caribbean amounted to US$ 453 billion at current prices in 2022, US$ 4.6 billion more than a year earlier. However, inflation caused the real capital of Latin American and Caribbean billionaires to fall by 6.5% in 2022 compared to 2021. Nonetheless, in 2021, the capital held by of Latin American billionaires accounted for 3.6% of the wealth of the entire Latin American and Caribbean population; and, between 2020 and 2021, the total wealth of Latin American billionaires grew by much more, relatively, than the wealth of the rest of the population in their countries. Inheritance has a decisive influence on the wealth of billionaires in the region, since 54% of the super-rich included in the 2021 Forbes list obtained their capital partially or totally through inheritance. All of these data highlight the need to address the concentration of wealth and its implications for growth, mobility and social stability in the region.

At the other extreme, both poverty and extreme poverty retreated in the region, with rates falling by 3.6 and 1.8 percentage points, respectively, on average in Latin America in 2022 (see figure 3). These figures suggest a recovery from the impact of the pandemic and even a slight improvement since 2019.

In most of the countries analysed, the reduction in poverty in 2022 is a consequence of real growth in labour incomes. In the countries reporting the largest reductions, income from employment, both wage-earning and self-employed, explains most of the increase in total income in low-income households. Moreover, in most of the countries, the share of State transfers in low-income households tended to decrease, as part of the process of closing down the emergency income protection programmes implemented in response to the pandemic. The chief exception is Brazil, where, in addition to labour income, both State transfers and other income, including contributory pensions, helped to reduce poverty (see figure 4).

Figure 3

Latin America (18 countries):a poverty and extreme poverty rates, 1990–2022 and projections for 2023

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Weighted average of the following countries: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

b Projections.

Figure 4

Latin America (6 countries): annual variation in total per capita income among low-income households, by income source, 2022

(Percentages, annualized figures)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: Countries with a poverty reduction of 2 percentage points or more, in order of the intensity of reduction. Data correspond to each source’s contribution to the variation in total income between 2021 and 2022, except in Chile and Mexico (2020– 2022). The size of the lowest-income group is indicated by the percentage indicated in parentheses, as follows: Brazil (29%), Chile (19%), Dominican Republic (28%), Ecuador (34%), Mexico (42%) and Uruguay (10%).

a Other income includes contributory pensions, private transfers, property income and imputed rent.

A slight uptick in both poverty and extreme poverty is projected for 2023, which calls into question the sustainability of the recovery in these indicators in 2022. Achieving a sustained and sustainable reduction in poverty will therefore require implementing a coordinated and robust strategy for inclusive social development, with a major emphasis on labour inclusion policies and social protection systems.

D. The design of labour inclusion policies must target reducing social inequality

The social inequality matrix of Latin America consists of a set of structuring axes that represent long-standing socioeconomic, gender, age, ethnic and racial, territorial and other inequalities. These axes intertwine, strengthen and interlink mutually throughout the life cycle; and they condition the exercise of fundamental rights, including the right to work in equitable and satisfactory conditions (ECLAC, 2016). This results in some populations, groups and individuals in the region facing higher entry barriers and structural obstacles to labour inclusion, in other words the capacity to access jobs under decent working conditions. In general, individuals who are at the intersections of the structural axes of the social inequality matrix, such as young people, Afrodescendants, members of Indigenous Peoples, persons with disabilities and migrants, among others, are overrepresented in sectors with lower productivity and higher rates of informality. In each of these groups or populations, glaring gender gaps persist, with women suffering relatively greater exclusion.

Young people confront greater obstacles in accessing the labour market than adults; and, when they are able to enter the market, they are overrepresented in informal employment, so their labour inclusion is incomplete. In most of the region’s countries, the youth unemployment rate is nearly three times the adult rate. For example, in the fourth quarter of 2022, the unemployment rate for young males averaged 9.4% in 12 Latin American countries, 5.7 percentage points higher than the equivalent rate for adult men. In the case of women this rate was 13.5% and the gap was 8.1 percentage points. Moreover, according to the latest available statistics, the informality rate among young people aged 15–29 years in the region is 53.4%, 12 percentage points higher than that of adults aged 30–64 years. The complex challenges of labour inclusion in the youth population were revealed more clearly during the COVID-19 pandemic, when young Latin Americans aged 15–29 years were more likely to lose their jobs than the adult population.

The large proportion of young people who are neither studying nor gainfully employed (about 23%) is particularly worrying. Nearly 16% of adolescents (15–17 years old) do not attend school. More than 70% of young people who are neither studying nor employed in the labour market are women, a situation that is heavily influenced by the level of household income, territoriality and ethnic-racial status; and it is related to the unequal division of unpaid work that prevails from the earliest stages of the life cycle. Maternity and gender inequalities in the distribution of paid and unpaid work can cause significant breaks in women’s educational pathways and in the transition to the labour market, particularly in the absence of comprehensive care policies and systems.

Accordingly, when reviewing the labour inclusion of young people, it is essential to consider diverse and non-linear school-work transitions, involving entries and exits from the labour market, sometimes overlapping with participation in educational or training systems, with the possibility of lifelong training and education, along with gender inequalities, the sexual division of labour and the family dimension. In this context, the role of labour inclusion policies is central; and their design must include a gender and care perspective, together with an approach that respects young people’s different life paths.

Although the participation rates of Afrodescendent populations and Indigenous Peoples do not differ significantly from those of the non-Afrodescendent or non-indigenous populations, they do display differentiated patterns. Indigenous People enter the labour market sooner and remain in it for longer than non-indigenous and non-Afrodescendent people, both men and women, and they have lower unemployment rates (Pedrero, 2023). Conversely, Afrodescendants —particularly Afrodescendent women— face greater obstacles in job search, which is reflected in higher unemployment rates than their non-indigenous and non-Afrodescendent peers (Huepe, 2023a).

Both Afrodescendants and Indigenous Peoples face major obstacles in gaining labour inclusion, as they are disproportionately represented in low-productivity jobs and in the informal economy; they are also less likely to be affiliated and contributing to social security systems than their non-Indigenous and non-Afrodescendent counterparts. For example, 43.3%, of employed Afrodescendants aged 15 years or older were affiliated or contributing to a pension system, in the six countries with available information in 2021, compared to 51.9% in the case of employed people of neither indigenous nor Afrodescendent origin (Huepe, 2023a; Pedrero, 2023). Even when controlling for education, their average labour income is lower than the average income of the employed population that is neither Afrodescendent nor indigenous. There is also a general tendency for wage gaps to widen as the level of schooling rises. These differences are explained, partly, by the different characteristics of the jobs they perform in the occupational structure, compounded by the presence of barriers, social norms and discrimination that restrict their access to positions of higher pay and status, and by the shorter average working day, in the case of Afrodescendent workers, especially women (Holz, Huepe and Rangel, 2022). In short, the Afrodescendent population and the Indigenous Peoples of the region suffer horizontal and vertical discrimination in the labour market, so labour inclusion policies need to target these populations specifically.

Given the prejudices that surround the impact of migrants on labour markets and, in particular, the claim that immigrants take jobs away from the native population, it is more important than ever to review the empirical evidence to gain an objective understanding of the effects of migration. Migrants contribute greatly to their destination societies, not only economically, but also sociodemographically and culturally (Martínez Pizarro and Cano Christiny, 2022; ECLAC, 2020). Their labour contribution, in particular, occurs through two mechanisms: the propensity to migrate as young adults and a greater propensity to participate in the labour force. Migrant workers contribute large amounts of labour to GDP, a contribution that varies according to the business cycle, the level of productivity and the buoyancy of the economic sectors in which they participate.

The analysis shows that characteristics and profiles of migrant workers in the region vary widely, basically in terms of their educational characteristics. The contexts in which migrants are received condition their job opportunities, although their positioning relative to local workers depends on other factors, such as their undocumented status. Occupational opportunities are more restricted and highly segmented in the case of women, who work longer hours on average, and much more frequently in informal conditions, than their non-migrant peers. These conditions generate greater obstacles to labour inclusion for migrants, who earn lower incomes than their native-born counterparts. Moreover, in most cases, migrant women are the most disadvantaged. For example, controlling for age, years of education and hours worked, in four of the seven countries analysed in Latin America, migrant men earn between 7% and 28% less than their native peers, In five of the seven countries, the equivalent percentages for women range from 6% to 41%. Consequently, it is essential to address the challenges of achieving labour inclusion for the migrant population. In particular, social protection systems need to address the specific vulnerabilities of migrants throughout the different phases of the migration cycle that characterize each country (Maldonado, Martínez and Martínez, 2018).

To confront these challenges, labour inclusion policies need to define differentiated and specific strategies to address the structural barriers and inequalities that affect certain population groups more intensively, especially those identified in the social inequality matrix.

E. Gender inequalities in labour inclusion can only be eradicated with comprehensive strategies

Unfair and inefficient structural inequalities have been identified as one of the main critical obstacles to advancing inclusive social development in Latin America and the Caribbean (ECLAC, 2019). Confronting gender inequalities and achieving women’s autonomy in the region implies overcoming the structural challenges[2] that perpetuate these inequalities. These structural challenges, which are intertwined and mutually reinforcing, and prevent women from exercising all of their rights, need to be tackled by public policy with a comprehensive and intersectional approach. Eradicating gender inequalities in women’s labour inclusion is a persistent challenge for Latin America and the Caribbean, which manifests itself in various dimensions. Between 2001 and 2019, the female participation rate increased slowly; but during the pandemic it was set back by 18 years. Although women’s labour force participation has risen by 4.3 percentage points since 2020 to reach 51.9% in 2022, the gap between male and female participation remains wide: in 2022, one in every two women were not participating in the labour force, compared to one in four men; and the figures have not changed significantly over the past 20 years. These gaps in labour market access in the region contrast with women’s achievements in terms of years of schooling, even surpassing the average number of years of schooling attained by men.

One of the main reasons for the persistence of the gender gap in labour participation is the unequal distribution of unpaid work. Despite an increase in paid work time, women continue to devote a substantially larger proportion of their time to unpaid work than men. The sexual division of labour is shown clearly by the labour participation of women who care for children. Parenting often overlaps with crucial stages in women’s careers and leads many to interrupt or postpone them. This situation is exacerbated in the lower income quintiles, with a gap of almost 9 points in the labour participation of women aged 20–44 years in households with and without children of up to 5 years of age. In the highest income quintile this gap is less than 3 percentage points, which is possibly explained by the fact that higher-earning women can hire care services in the market more easily (see figure 5).

The COVID-19 pandemic highlighted the central place of care in people’s lives, and the crucial importance of its organization at the societal level. School closures, excess demands on health systems and the difficulties faced by families in obtaining support for domestic and care tasks revealed the extent to which society and the economy depend on health, education and care work, both paid and unpaid. Although these jobs vary significantly in terms of type of task, working conditions and labour market status, they represent a heterogeneous group in terms of occupational category, remuneration and social valuation; and they have a direct impact on the burden of care that households have to assume and on women’s autonomy. The existing sexual division of labour means that it is women who undertake most of the care work.

Figure 5

Latin America (15 countries):a labour participation of individuals aged 20–44 years, by gender and according to the presence of children aged 0–5 years in the household, and by household per capita income quintile, 2022b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Weighted average of the following countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay.

b In the cases of Colombia, Honduras and the Plurinational State of Bolivia, the data refer to 2021.

In the region, 26.7% of women are employed in the extended care sector; they also account for 69.9% of persons employed in education, 73.5% of those working in the health sector and 92.8% of domestic employment (Baron and Scuro, 2023). In some cases, low wages result in women living in poverty despite being employed and earning an income. This situation applies to domestic workers in particular, of whom one in every four lives in poverty. Moreover, registration or the signing of contracts is very infrequent in most countries, which results in these workers being excluded from social security. This situation reveals the obstacles that women confront in terms of labour inclusion. In the face of the care crisis, exacerbated by population ageing, and compounded by changes in epidemiological trends and the effects of climate change, a sustained increase in the demand for labour in the care sector and a reduction in the time and number of people available to provide care can be expected (ECLAC, 2022b). At the same time, no reduction in jobs in this sector is anticipated as a result of automation, mainly owing to the human and physical dimensions of care work, which cannot be completely replaced.

This could represent a twin opportunity —for creating new jobs and for reducing unpaid work time in households. In particular, the digital transformation could open up new opportunities for the paid domestic work and care sector, by creating digital platforms that connect the supply of work with the care needs of households. It could also facilitate the professionalization and certification of female workers, which would lead to such work being accorded greater social and economic value. However, the current situation raises alerts in relation to existing working conditions and the potential precarity of work in this sector. Among other issues, there is still no clarity about the employment relationship in platform work, and there is a risk of biases arising in algorithmic management of time calculation, task assignment and performance. The advantages that the digitalization of this sector could generate for the labour inclusion of women depend, largely, on the regulatory and supervisory capacity of the public institutions that are tasked with enforcing labour regulations. In addition, the adoption of these technologies by countries, in accordance with existing anti-discrimination laws, in the context of respect for labour rights, human rights and citizen participation, could make the creation of decent jobs more efficient and effective.

The current situation thus presents both challenges and opportunities for addressing structural gender inequalities related to women’s labour inclusion. This approach requires recognizing care not only as a driving sector of the labour market and the economy at large, but also as a potential axis for reorganizing societies under the principles of gender equality and sustainability in the framework of the care society (ECLAC, 2022a). Among other actions, this will require the implementation of labour inclusion policies linked to comprehensive care policies, in addition to an expansion of the supply of early childhood education and care services.

F. Labour inclusion policies are conditioned by population ageing

In order to analyse labour markets and develop recommendations for labour inclusion policies, it is essential to consider how population dynamics, among other factors, affect the labour supply and profile of workers in the region.

Young people and adults currently represent the largest age cohorts in Latin America and the Caribbean, which means that the region is experiencing —and will continue to experience in the coming years— a population pressure that needs to be recognized in labour inclusion policies. In less than 40 years, the 15–64 year-old population has doubled (from 220.2 million in 1983 to 442.6 million in 2022); and it will continue to climb towards a peak in 2042. The largest population group in 2022 was the 20–24 year age group, whereas in 1950 it was the under-fives.

The rapid demographic transition that is unfolding in the region entails a shift from high to low (or even very low) levels of fertility and mortality, and by a considerable increase in life expectancy. In 1950–2022, the total fertility rate in the region dropped from 5.80 to 1.85 live births per woman, and life expectancy rose from 48.6 to 73.8 years (United Nations, 2022). These two main factors caused the age structure of the population to change significantly, with the median age rising from 18.3 years in 1950 to 30.6 in 2022 (United Nations, 2022). Despite this increase, the region is still one of the world’s youngest, with the lowest average age after Africa (which was 18.73 years in 2022).

Although the countries of the region are converging towards low fertility rates and longer life expectancy at birth, there are differences in the levels of these phenomena and their rates of change, which are expressed in varied demographic transitions and age compositions. In relation to the world of work, this heterogeneity can be analysed through the demographic dependency ratio; that is the number of people aged under 15 and over 65 years relative to the working-age population (15–64 year-olds). When a country’s dependency ratio starts to fall (mainly because of a reduction in the population aged 0–14 years), the country is considered to have entered a period of demographic bonus, because a large proportion of working-age people can drive economic growth and reduce expenditure on dependants. When the dependency ratio rises again (mainly because of an increase in the population aged 65 and over), the country is considered to have exited this bonus phase. This, among other factors, may increase the care needs highlighted in section E.

The duration of the demographic bonus varies widely among Latin American and Caribbean countries: while the demographic window of opportunity is expected to end by 2027 for the region as a whole, 13 countries had already completed this stage by 2022 (see figure 6). To take advantage of the bonus, it is crucial to promote full labour inclusion in the region, with a labour market that provides access to decent jobs, with adequate pay and social protection coverage.

Figure 6

Latin America and the Caribbean (38 countries and territories): demographic bonus —start, end and duration, 1950–2060

(Years)

Source: Latin American and Caribbean Demographic Centre (CELADE) -Population Division of the Economic Commission for Latin America and the Caribbean (ECLAC), 2022 revision, and United Nations, World Population Prospects, 2022 [online] https://population.un.org/wpp/.

Demographic trends vary between age groups and genders. Although the labour force participation of men between the ages of 25 and 64 years has remained stable at around 90% and is projected to remain so in the future, the participation rates among men aged 15–19 and 20–24 have declined in the last decade. So also has that of men aged 65 or older. In contrast, female labour force participation has increased in all age groups, albeit with a slight dip among 15–19 year-olds over the last decade (see figure 7). However, although the labour force participation of women aged 25–64 years is projected to continue increasing, if historical trends persist, it will reach 73% in 2050, still almost 20 points below the equivalent male rate. This scenario again reinforces the need to promote labour inclusion policies that anticipate the implications of this transition and can address issues such as the gender inequalities prevailing in the labour market.

Figure 7

Latin America and the Caribbean: labour force participation by sex and age group, 1980–2050

(Percentages of the total population in each age group)

Source: Latin American and Caribbean Demographic Centre (CELADE)-Population Division of the Economic Commission for Latin America and the Caribbean (ECLAC), 2022 revision, and United Nations, World Population Prospects, 2022 [online] https://population.un.org/wpp/.

G. Social spending is declining relative to GDP, but remains above pre-pandemic level

The cascading crisis that is unfolding in the region and worldwide, with its economic, social and environmental effects, has exerted and continues to exert pressure on fiscal policy to respond with sustainable, inclusive and sufficient measures that not only alleviate the impact of the shocks, but also make it possible to resume progress towards the Sustainable Development Goals (ECLAC, 2023c). The impacts on the region’s labour markets intensify these pressures, which need to be anticipated with a view to advancing towards a social and fiscal compact.

In 2022, central government social spending relative to GDP in Latin America decreased for a second straight year, following substantial growth in 2019–2020 owing to the emergency social protection and health measures implemented in response to the COVID-19 pandemic. In 2022, central government social spending represented 11.5% of GDP, 2.2 percentage points lower than in 2020. While not falling back to 2019 levels, social spending relative to GDP is only 0.3 percentage points higher than in that year. The reduction averaged 5.1% in real terms (in dollars at constant 2018 prices). In the five Caribbean countries for which information is available, the trend in central government social spending was broken in 2022, as it dropped to 11.5% of GDP from the peak of 13.8% attained in 2021 (see figure 8). In both the Latin American and the Caribbean countries, the share of social spending in total central government expenditure has decreased.

Figure 8

Latin America and the Caribbean (22 countries): central government social spending, 2000–2022

(Percentages of GDP and of total public expenditure)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: Coverage in the case of the Plurinational State of Bolivia corresponds to central administration and that of Peru to general government. Data for the Plurinational State of Bolivia correspond to 2021 and for Panama they refer to 2020. Simple average of 17 Latin American countries and five Caribbean countries. Latin America includes Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay. The Caribbean includes Bahamas, Barbados, Guyana, Jamaica, and Trinidad and Tobago.

In the coming years, it will be essential to ring-fence and increase social investment, particularly given the observed trend of returning to the 2019 levels and structures of social spending, both in the functional and institutional classification and with respect to investment in labour inclusion programmes, as will be seen in section H. The current situation requires public policy actions to achieve fiscal sustainability, in order to address the consequences of the cascading crises that are unfolding, and enhance the financial sustainability of social spending to meet the challenge of achieving the Sustainable Development Goals.

H. There is an urgent need to increase investment in labour inclusion policies with a life-cycle focus

In line with the need to redouble investment in labour inclusion policies, a programmatic analysis of public expenditure on labour policies in the region is crucial. However, as figure 9 shows, spending on these policies is not only extremely low, but has declined for the second consecutive year, dropping to 0.42% of GDP in 2022. This was 0.55 percentage points lower than in the first year of the pandemic as a result of the closure of programmes implemented in response to the health crisis. Figure 9 also shows that the institutional distribution of spending on labour inclusion policies is similar to before the COVID-19 pandemic: ministries of labour, ministries of social development and decentralized training institutions jointly account for 73% of total spending (representing 0.15%, 0.10% and 0.06% of GDP in 2022, respectively). In addition, ministries of economy or finance executed expenditure averaging the equivalent of 0.32% of GDP in 2020 to address the effects of the pandemic.

Figure 9

Latin America (15 countries):a public spending on labour inclusion policies, by executing entity, simple average, 2018–2022

(Percentages of GDP)

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

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Panama, Paraguay, Peru and Uruguay.

Labour inclusion policies are key to achieving full social inclusion in the region. Strengthening these policies will make it possible to reduce unemployment, increase labour participation, narrow the gender and inequality gaps that affect various population groups in this dimension, and generate effective mechanisms to support employment and protect against unemployment, including in the case of technological change (ECLAC, 2021a). Labour inclusion, and its policies, require coordinated social and labour institutions to be strengthened, to guarantee basic levels of protection and well-being in response to labour informality and other critical challenges that hinder inclusive social development in the region.

I. Labour inclusion policies as a key axis of inclusive social development

There are various policy options and instruments that can be considered to make sustained progress in achieving labour inclusion in the region. These should aim to increase levels of labour market access under decent working conditions, paying special attention to the most vulnerable populations with a view to reducing their obstacles to labour market inclusion.

In terms of design, the rationale of these policies should be to structurally transform the barriers to labour inclusion. This means considering implementation times and a formulation aligned with the support needed by different population groups, and also close coordination with productive development policies and strategies in the countries. It is also necessary to anticipate their adaptation to the different crises that may arise, such as that generated by the COVID-19 pandemic.

During the pandemic, the countries reacted swiftly to the crisis by adopting employment and worker protection measures, adjusting pre-existing active and passive labour market policies. These adjustments included increased funding for programmes and expanded coverage, with countries announcing a variety of modifications (ECLAC, 2021a and 2022c). In addition, new specific measures were created for the most vulnerable, such as informal workers (Velásquez Pinto, 2021). Although these measures were important, they were insufficient to contain the profound impacts of the pandemic.

Labour inclusion plays a key role in upholding the social and economic rights of workers and their families, including access to an adequate level of income and to social protection systems, and thus in attaining inclusive social development. A deterioration in labour inclusion entails losses that transcend labour market access of workers at a given time, which helps to explain the prolonged social crisis that the region has experienced. Accordingly, a fundamental task facing the countries is to anticipate labour inclusion policies to be able to respond to future crises.

The region must make headway in the design, expansion and coordination of active and passive labour market policies. Active policies seek to strengthen possibilities for accessing higher quality employment, with higher pay and better working conditions; and they include efforts to develop and update workers’ skills and competencies (Espejo and others, 2023). These policies include increasing labour supply through technical and vocational training, along with formal education levelling and school retention, among other programmes, prioritizing population groups that face the greatest barriers to entering the labour market and accessing decent working conditions. They also include policies to stimulate the demand for labour by supporting self-employment and both direct and indirect job creation programmes.

Lastly, they include job placement policies, which connect job seekers with potential employers, and with entities that provide support and guidance services in job search and recruitment (Abramo, Cecchini and Morales, 2019). In contrast, passive labour market policies guarantee income replacement for the unemployed and include unemployment insurance, individual unemployment saving accounts, severance pay, and cash entitlements targeted to workers in the most vulnerable situations.

The success of labour inclusion policies depends on the buoyancy of the labour market, which is determined by economic growth, investment rates and the scale and impact of productive development policies to influence the pace and nature of the economic transformation. It is impossible to create a better work future without creating a better production future, and vice versa (Salazar-Xirinachs, 2022). Thus, there is a close relationship and multiple synergies between labour inclusion and productive development policies.

In this context, it is essential that the region strengthen its labour institutional framework, including the set of legal provisions related to guaranteeing rights and working conditions. However, the financial sustainability of labour inclusion policies is more challenging in the current regional scenario, characterized by low economic growth rates, high inflation and frequently changing government priorities (Abramo, 2021; Mazzucato, 2023). A more efficient and effective approach by the Government would help to build trust among the various actors and make labour inclusion initiatives more sustainable (Huepe, 2023b).

Sustainable funding is a central requirement for a socio-labour institutional framework that can meet the challenges of advancing towards inclusive social development. It is therefore not enough for labour inclusion policies merely to be sustainable financially, since deficits in the other two dimensions (coverage and adequacy of entitlements), will render the system unsustainable (Arenas de Mesa, 2023). Consequently, to strengthen labour inclusion as a key development strategy, States need to invest not only in labour policies, but also in production development policies; and they need to ensure that such actions are framed within a social and fiscal compact. This will make it possible, through social dialogue, to strengthen labour institutions and achieve better pay and productivity conditions, while also reducing informality and inequality.

J. Labour inclusion is closely linked to social protection systems and requires comprehensive actions

Labour inclusion is both an objective and a component of social protection systems, since one of the functions of social protection policies is to eradicate the risk of living in poverty and to reduce inequalities (ECLAC, 2020). Labour inclusion gaps in the region influence and challenge the structural deficits of social protection systems. Low levels of social security contributions are related to the high prevalence of labour informality, which is compounded by new risks associated with the ongoing transformations in the world of work and new employment modalities. This poses major challenges in terms of the financial sustainability and segmentation of these systems. In addition, the levels of coverage and adequacy of non-contributory social protection entitlements, which are still limited, hinder guaranteed access to social protection for large groups of workers. In this context, it is crucial to strengthen comprehensive and multidimensional measures that reinforce the interactions between social protection and labour inclusion policies (Robles and others, 2023).

At least four policy areas can be identified for promotion in this context. Firstly, it is essential to strengthen mechanisms to broaden the contributory coverage of social protection systems. At the very least, this entails linking this objective with strategies to reduce labour informality, so that workers’ access to social protection forms a central part of this agenda. This can be embodied in initiatives and policies that make it possible to incorporate self-employed and informal workers into social protection systems, include them in pension system reform processes, or adjust the eligibility requirements for accessing contributory social protection coverage. During the pandemic there were some outstanding examples of this, in which some of the region’s countries made the mechanisms for accessing unemployment insurance more flexible. Along the same lines, labour inclusion policies need to incorporate mechanisms that guarantee access to social protection for the most vulnerable populations, for example through direct and indirect job creation and job placement policies. It is also essential to bolster labour regulations and institutions, by reducing social security evasion and avoidance and guaranteeing appropriate working conditions for all people (Robles and others, 2023). In the case of migrant workers, documented status is a necessary but insufficient condition for their labour inclusion and social protection. Mechanisms are also needed to make social security contributions portable, and thus strengthen migrant workers’ access to social security in their destination countries.

Secondly, the income protection dimension needs to be strengthened, especially in light of the challenges posed by changes in the world of work, the climate crisis, disasters and the just transition. This can be done by harmonizing cash transfer policies with existing labour inclusion policies. It can also be included in emergency response policies, both during and after the occurrence of the event (Robles and others, 2023). A complementary need is to strengthen interaction between active labour market policies and comprehensive care policies and systems, and thus help reduce gender inequalities in labour inclusion. This could include policies to make parenting compatible with paid work, and the design of job training policies that consider access to care services in their various phases.

Thirdly, training to develop skills that will enable the population to participate in the benefits of development and contribute to the leap required to transform the region’s production structure remains a challenge for the countries of the region —despite progress in the education system in terms of access and coverage. It is crucial to analyse the quality and relevance of the education provided, and to focus on competencies and skills that enable individuals to adapt both to lifelong learning and retraining processes and to an increasingly technological and changing world (ECLAC/OEI, 2020; ECLAC, 2022b). It is essential to make progress in detecting, anticipating and addressing training deficits among the population, and in reducing inequality gaps.

Short technical education and vocational orientation programmes are crucial for strengthening the connection between the education sector and labour and productive development opportunities in the countries. They also support labour inclusion, facilitating the school-to-work transition. However, this type of educational offering faces major challenges in terms of coordinating with needs in the different sectors of production. In the region, it is unusual for strong relationships to be established between training centres and employers, which prevents students from being trained in the workplace and does not encourage employers to participate systematically in the design of training programme curricula. Nor are skill certification processes sufficiently developed, which are a crucial channel for promoting training pathways that recognize the multiple routes that the new generations take to learn throughout the life cycle (which includes self- directed learning, and not necessarily training in formal institutions or jobs).

To address shortcomings in conditions for accessing education and training, it is crucial to strengthen the interaction with social protection, particularly with household income support and care policies. Scholarships and food services, policies to prevent school dropout and child labour, along with care services, have been fundamental tools in supporting progression through, and permanency in, the education system. They contribute to strengthening the link between students and school, alleviate household income needs, and reduce school dropout motivated by the need to work (Rossel and others, 2022; ECLAC, 2022b).

Fourthly, health is an element that conditions an individual’s capacity to participate in the labour force, and is therefore closely related to labour inclusion. Individuals in poor health or with health problems face greater difficulties in finding and holding on to quality jobs, which makes it more likely that they will work in precarious employment. It is therefore essential to guarantee the right of access to timely and quality health care for the entire population (Marinho, Dahuabe and Arenas de Mesa, 2023). Similarly, working conditions are considered an important social determinant of health, because they have a direct impact on the physical and mental well-being of the population. More precarious working conditions, such as informal work, can generate higher levels of stress and cardiovascular diseases, for example, which lead to increased absenteeism and premature deaths (Wilkinson and Marmot, 2003).

A very clear demonstration of this relationship was provided during the COVID-19 pandemic. First, the health crisis triggered an economic crisis, with a profound impact on the labour market from which the region has not yet fully recovered. Second, it exposed the specific vulnerability, in terms of health, of persons who work informally, with higher levels of excess mortality occurring in countries with higher rates of labour informality (Cid and Marinho, 2022). These disparities between countries are explained both by the health inequalities associated with informality that existed before the pandemic, and by the fact that it was impossible for informal workers to respect the quarantine measures, owing to the lack of income protection and the limited coverage of social protection systems (ECLAC, 2022c).

K. Presentation and summary of the key messages of the four chapters

In Social Panorama of Latin America and the Caribbean, 2023, ECLAC stresses the urgent need to advance a policy agenda for labour inclusion that focuses on reducing informality and inequalities and contributes to inclusive social development in the region. To this end, it is not sufficient merely to promote higher levels of employment; it is also essential to confront the structural problems of the labour market in the region, ensuring that employment is of quality and productive, and that it provides sufficient income to lead a decent life with guaranteed social protection coverage. Labour inclusion is a cornerstone of the virtuous relationship between growth and equality. Investing in labour inclusion policies, prioritizing the most disadvantaged individuals, groups and populations, means investing in the most important asset that countries have for advancing towards inclusive social and economic development: namely their people. With these considerations in mind, the key messages of each chapter are summarized below.

As in previous editions, chapter I reviews the trend of certain indicators, including GDP per capita, employment, inflation and household income distribution. It also reports on the trends and levels of poverty and extreme poverty, highlighting improvements in these indicators in 2022, while noting that a slight increase is projected for 2023 in both cases. It also draws attention to the trend of extreme wealth and its implications in terms of income concentration in the region. Lastly, the chapter reviews recent changes that have occurred in social stratification, with a special focus on labour inclusion. It analyses labour participation based on a typology of occupational status by stratum, highlighting the insufficiency of labour income in each case.

Chapter II addresses the slow-motion labour market crisis through which the countries of Latin America and the Caribbean are living, noting that it has been aggravated by multiple factors, such as the impacts of the COVID-19 pandemic, high inflation and the economic slowdown, compounded by pre-existing problems and ongoing transformations. The chapter discusses various labour market indicators and the challenges of labour inclusion as a central axis of inclusive social development. In particular, it addresses the labour inclusion challenges among various population groups that face greater barriers, such as women, young people, Afrodescendent populations, Indigenous Peoples, persons with disabilities, and older persons. It makes an in-depth analysis of various manifestations of labour informality and its implication for the well-being of households in the region. Lastly, it highlights the role of labour inclusion policies, including active and passive policies, as well as the social institutional framework and financial sustainability in this area.

Chapter III addresses the challenges of labour inclusion for women and migrants in the region. It firstly highlights the major gender deficits and inequalities faced by the region in terms of women’s labour participation. The main reasons for this situation include the unequal distribution of paid and unpaid work and the low level of access to comprehensive care policies, which operate to the detriment of women. It also addresses working conditions in education, health and domestic work —sectors related to care in which women are employed more intensively. It draws attention to labour conditions in the paid domestic work sector, which is characterized by high rates of informality and precarious working conditions. Although the rise of the platform economy could open up new opportunities, it could also generate new risks and barriers to women’s inclusion in the labour market unless regulated appropriately. The chapter also notes the significant increase in intraregional migration over the last two decades and the importance of understanding this phenomenon as a contribution to both origin and destination countries. Migrants help reduce structural shortages in the labour force and stimulate economic growth, especially when migration occurs on a documented basis and with rights protected. From this standpoint, the chapter discusses the main obstacles and challenges for inclusion of the migrant population in the labour market.

Lastly, chapter IV discusses the social institutional framework of social development policies and its links to labour inclusion and the trend of social spending in the region. The chapter recognizes progress made in all dimensions of social spending as well as its increasing importance in the countries, given its critical role as a necessary condition for generating quality social policies. The chapter emphasizes the importance of having a robust social institutional framework, with transparent governance of the decision-making process, so that the rights-based approach can be embedded in public policies. It also identifies key challenges, including the need to consolidate the legal and regulatory bases and strengthen the capacities of agencies involved in social development, investing in human, technological and financial resources and in information systems for decision-making, and consolidating monitoring and evaluation systems with greater strategic planning and foresight capacity. The chapter also reviews the trend and levels of central government social spending in the region, noting that, in 2022, there is a tendency to regress to the 2019 levels and structures of social spending, in terms of functional and institutional classification and in the types of programmes in the labour market. It highlights the significant differences that persist in spending on labour policies, both in the countries of the region and in Europe, identifying a declining trend in investment in labour inclusion policies in Latin American countries, which absorb an average of 0.42% of GDP. In conclusion, the chapter reiterates that the current situation calls for sustainable fiscal policy measures to deal with the consequences of the cascading crises that are currently unfolding, and regain the path of increasing resources to achieve the Sustainable Development Goals.

Bibliography

Abramo, L. (2022), “Policies to address the challenges of existing and new forms of informality in Latin America”, Social Policy series, No. 240 (LC/TS.2021/137), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Abramo, L., S. Cecchini and B. Morales (2019), Social programmes, poverty eradication and labour inclusion: lessons from Latin America and the Caribbean, ECLAC Books, No. 155 (LC/PUB.2019/5-P), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Arenas de Mesa, A. (2023), “Protección social universal, integral, sostenible y resiliente para erradicar la pobreza, reducir la desigualdad y avanzar hacia un desarrollo social inclusivo”, CEPAL Review, No. 141, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Arenas de Mesa, A., C. Robles and J. Vila (2023), “El desafío de avanzar hacia la sostenibilidad de los sistemas de pensiones en América Latina”, Social Policy series, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Barón, C. and L. Scuro (2023), “Los nudos estructurales de la desigualdad de género y los desafíos para la autonomía de las mujeres en el futuro del trabajo”, Desigualdades, inclusión laboral y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

CAF (Development Bank of Latin America and the Caribbean) (2022), Desigualdades heredadas: el rol de las habilidades, el empleo y la riqueza en las oportunidades de las nuevas generaciones, Bogotá.

Cid, C. and M. L. Marinho (2022), “Dos años de pandemia de COVID-19 en América Latina y el Caribe: reflexiones para avanzar hacia sistemas de salud y de protección social universales, integrales, sostenibles y resilientes”, Project Documents (LC/TS.2022/63), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

ECLAC (Economic Commission for Latin America and the Caribbean) (2023a), Public debt and development distress in Latin America and the Caribbean (LC/TS.2023/20), Santiago.

____(2023b), Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago

____(2023c), Halfway to 2030 in Latin America and the Caribbean: progress and recommendations for acceleration (LC/FDS.6/3/Rev.1), Santiago.

____(2022a), Towards transformation of the development model in Latin America and the Caribbean: production, inclusion and sustainability (LC/SES.39/3-P), Santiago.

____(2022b), Social Panorama of Latin America and the Caribbean, 2022 (LC/PUB.2022/15-P), Santiago.

____(2022c), Social Panorama of Latin America, 2021 (LC/PUB.2021/17-P), Santiago.

____(2021a), Social Panorama of Latin America, 2020 (LC/PUB.2021/2-P/Rev.1), Santiago.

____(2021b), Economic Survey of Latin America and the Caribbean, 2021 (LC/PUB.2021/10-P/Rev.1), Santiago.

____(2020), Regional Agenda for Inclusive Social Development (LC/CDS.3/5), Santiago.

____(2019), Critical obstacles to inclusive social development in Latin America and the Caribbean: background for a regional agenda (LC/CDS.3/3), Santiago.

____(2017), Montevideo Strategy for Implementation of the Regional Gender Agenda within the Sustainable Development Framework by 2030 (LC/CRM.13/5), Santiago.

____(2016), The social inequality matrix in Latin America (LC/G.2690(MDS.1/2)), Santiago.

____(2014), Compacts for Equality: Towards a Sustainable Future (LC/G.2586(SES.35/3)), Santiago.

____(2012), Structural Change for Equality: An Integrated Approach to Development (LC/G.2524(SES.34/3)), Santiago.

____(2010), Time for Equality: Closing Gaps, Opening Trails (LC/G.2432(SES.33/3)), Santiago.

ECLAC/ILO (Economic Commission for Latin America and the Caribbean/International Labour Organization) (2023), “Towards the creation of better jobs in the post-pandemic era”, Employment Situation in Latin America and the Caribbean, No. 28 (LC/TS.2023/70), Santiago.

ECLAC/OEI (Economic Commission for Latin America and the Caribbean/Organization of Ibero-American States for Education, Science and Culture) (2020), “Educación, juventud y trabajo: habilidades y competencias necesarias en un contexto cambiante”, Project Documents (LC/TS.2020/116), Santiago.

Espejo, A. and others (2023), “Desafíos y recomendaciones para la inclusión laboral de jóvenes en América Latina”, Desigualdades, inclusión laboral y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Fisher, J. and others (2016), “Inequality and mobility using income, consumption, and wealth for the same individuals”, RSF: Russell Sage Foundation Journal of Social Sciences, vol. 2, No. 6, October.

Holz, R., M. Huepe and M. Rangel (2022), “El futuro del trabajo y la población afrodescendiente en América Latina en el marco del COVID-19 y la recuperación transformadora con igualdad”, Project Documents (LC/TS.2022/81), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Huepe, M. (2023a), “Desafíos y recomendaciones para la inclusión laboral de la población afrodescendiente”, Desigualdades, inclusión laboral y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

____(2023b) “Políticas de inclusión laboral: una estrategia integrada, sostenible y con enfoque territorial” Desigualdades, inclusión laboral y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Maldonado, C., J. Martínez and R. Martínez (2018), “Protección social y migración: una mirada desde las vulnerabilidades a lo largo del ciclo de la migración y de la vida de las personas”, Project Documents (LC/TS.2018/62), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Marinho, M. L., A. Dahuabe and A. Arenas de Mesa (2023), “Salud y desigualdad en América Latina y el Caribe: la centralidad de la salud para el desarrollo social inclusivo y sostenible”, Social Policy series, No. 244 (LC/TS.2023/115), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Martínez Pizarro J. and M. Cano Christiny (eds.) (2022), “Sobre las contribuciones de la migración al desarrollo sostenible: estudios en países seleccionados”, Project Documents (LC/TS.2021/195), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Mazzucato, M. (2023), Transformational change in Latin America and the Caribbean: a mission-oriented approach (LC/TS.2022/150/Rev.1), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

OECD (Organisation for Economic Co-operation and Development) (2018), A Broken Social Elevator? How to Promote Social Mobility, Paris, OECD Publishing.

Pedrero, M. (2023), “Los Pueblos Indígenas de América Latina-Abya Yala: la centralidad de los derechos colectivos para una recuperación económica transformadora”, Desigualdades, inclusión laboral y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Robles, C. and others (2023), “Apuestas estratégicas hacia el futuro de la protección social: avanzar hacia sistemas universales, integrales, resilientes y sostenibles”, El futuro de la protección social ante la crisis prologada en América Latina: claves para avanzar hacia sistemas universales, integrales, resilientes y sostenibles, Social Policy series, C. Robles and R. Holz (coords.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Rossel, C. and others (2022), “Transferencias monetarias no contributivas y educación: impacto y aprendizajes”, Project Documents (LC/TS.2021/202), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Salazar-Xirinachs, J. M. (2023), “Prólogo”, Desigualdades, inclusión laboral y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

____(2022), “Estrategias y políticas para la reconstrucción con transformación pospandemia en América Latina y el Caribe”, Project Documents (LC/TS.2022/22), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

United Nations (2023), “WHO chief declares end to COVID-19 as a global health emergency”, UN News, 5 May [online] https://news.un.org/en/story/2023/05/1136367.

____(2022), World Population Prospects 2022: Online Edition [online] https://population.un.org/wpp/.

Velásquez Pinto, M. (2021), “La protección social de los trabajadores informales ante los impactos del COVID‐19”, Project Documents (LC/TS.2021/37), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Waldenström, D., A. Adermon and M. Lindahl (2016), “Intergenerational wealth mobility and the role of inheritance: evidence from multiple generations”, CEPR Discussion Paper, No. 11456, Paris and London, Centre for Economic Policy Research (CEPR).

Wilkinson, R. and M. Marmot (eds.) (2003), Social determinants of health: the solid facts, 2nd edition, Denmark, World Health Organization (WHO).

Yang, X. and P. Zhou (2022), “Wealth inequality and social mobility: a simulation-based modelling approach”, Journal of Economic Behavior & Organization, vol. 196, April.

1. [1] Individuals whose net worth exceeds US$ 1 billion.

2. [2] The Montevideo Strategy for Implementation of the Regional Gender Agenda within the Sustainable Development Framework by 2030 (ECLAC, 2017) defines the following structural challenges: (i) socioeconomic inequality and the persistence of poverty; (ii) discriminatory, violent and patriarchal cultural patterns and the predominance of a culture of privilege; (iii) the sexual division of labour and the unfair social organization of care, and (iv) the concentration of power and hierarchical relations in the public sphere.

Chapter I

Income inequality and poverty and their links to labour inclusion

Introduction

A. Income inequality and extreme wealth

B. Poverty, middle-income strata and links to labour inclusion

C. Final comments

Bibliography

Annex I.A1

Introduction

The recovery from the economic crisis caused by the coronavirus disease (COVID-19) pandemic continued in 2022, with varying strength, in virtually all the Latin American countries. It brought both an increase in labour force participation and employment and a decline in unemployment. These changes in the labour market meant that earnings and household incomes rose in most of the countries, although inflation remained high, affecting lower-income households most severely.

The per capita GDP growth rate moderated from 6.1% in 2021 to 3% in 2022 (see figure I.1). Real per capita GDP was 1% higher in 2022 than in 2019, making 2022 the first year in which the pre-pandemic level was exceeded. The economies of Panama, Colombia and Uruguay grew the most, by 5% or more. In three other countries, Costa Rica, the Dominican Republic and Argentina, growth exceeded the regional average. In 11 countries, per capita GDP growth was between 1.7% and 2.7%, while Paraguay and Haiti recorded declines of 1.1% and 3.2%, respectively.

Figure I.1

Latin America (19 countries): annual changes in per capita GDP at constant prices, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of ECLAC, Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago, 2023.

Per capita GDP growth in the Caribbean averaged 12.6% in 2022. This exceptionally high value was affected by the strong growth in Guyana due to the exploitation of the oilfields discovered a few years ago. If median growth is taken, the value is somewhat lower at 7.4% for the year. The countries where per capita GDP growth exceeded this value were Guyana (61.5%), Saint Lucia (15.8%), the Bahamas (13.8%), Belize (10.7%), Barbados (9.8%) and Antigua and Barbuda (7.8%). The lowest growth was in Suriname (0.1%) and Trinidad and Tobago (2.1%) (ECLAC, 2023).

The recovery from COVID-19 has continued in the region’s labour markets, as evidenced by a variety of indicators such as the participation rate, the unemployment rate, the employment rate and the numbers in work. These indicators have improved somewhat relative to the 2020–2021 biennium and are broadly back to or close to the figures seen prior to the health crisis. However, progress is perceived to have slowed, and structural problems remain, such as high levels of informal employment and marked gender inequalities (see chapters II and III, where labour inclusion is discussed in more detail).

The average labour force participation rate in Latin America increased slightly in 2022 to 64.0%, 0.3 percentage points higher than the 63.7% observed in 2021.[1] Labour market participation in 2022 was still below the average for 2019, before the health emergency (64.7%). In parallel, the average unemployment rate decreased by 1.5 percentage points, from 8.1% in 2021 to 6.6% in 2022. The 2022 rate was similar to the 2019 rate of 6.7%. In line with the increase in participation and the slight fall in unemployment, the average regional employment rate rose. Specifically, the average rate in Latin America climbed from 58.6% in 2021 to 59.8% in 2022, but did not reach the pre-pandemic value (60.5% in 2019).

Gender gaps in the participation, unemployment and employment indicators narrowed in 2022 after a period in which women suffered more severely from the labour market effects of the pandemic. In figures, average female labour force participation in the region increased by 1.2 percentage points over 2021, while male participation remained constant.[2] At the same time, the female unemployment rate fell by 1.4 percentage points, or 0.3 percentage points more than the male rate. Lastly, the female employment rate increased by 1.9 percentage points, compared with an increase of 0.6 percentage points for men. Despite this favourable trend, large gaps between men and women persisted. For example, the female employment rate was 49.1% in 2022, 22 percentage points less than the male rate (71.1%). Similarly, the unemployment rate for women (8.4%) was 1.5 times that for men (5.6%), while women’s labour force participation in 2022 (53.5%) remained well below that of men (75.9%).

Consistently with the increase in employment, earnings per person rose by more than inflation in 9 of the 12 countries surveyed (see figure I.2).[3] In Chile, Mexico, Peru and Uruguay, earnings measured in poverty lines grew by between 5% and 8% in 2022, while in Brazil, the Dominican Republic, Ecuador and Paraguay the increase was between 3.1% and 4.5%, and in El Salvador it was 1.0%.[4] In turn, per capita household income grew in all the countries mentioned, partly as a consequence of rising earnings, except in El Salvador. In Panama, it increased in a context of falling earnings.[5] Argentina and Costa Rica were the only countries with data available for 2022 where labour income and total per capita household income fell significantly.

Lastly, inflation remained high in 2022 compared to the pre-pandemic years. In early 2020, the region’s median 12-month inflation rate was below 2%, but it increased to 6.6% in December 2021 and again to 8.5% in 2022. Inflationary pressure appeared to ease in the first half of 2023 owing to the international situation and the various monetary tightening measures adopted by central banks, among other reasons. Thus, annualized inflation as of July 2023 stood at around 4.5%.

Price increases did not affect all households equally, owing to the different compositions of consumption baskets. In 2022, in fact, consumer prices increased by between 0.4 and 1.5 percentage points more for the lowest-income households than for the highest-income households (see figure I.3). This difference was due to disproportionate increases in the price of food, which accounts for a larger share of the consumption basket of lower-income households. The situation continued in the early months of 2023 despite declining inflation and most significantly affected the purchasing power of the poorest women, given their larger share of the population aged 15–59 living in such households.

Figure I.2

Latin America (12 countries): annual changes in per capita earnings and household income measured in poverty lines, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: Includes countries with information for 2022, ranked by the change in earnings. In the cases of Chile and Mexico, the values are annualized changes between 2020 and 2022.

Figure I.3

Latin America (17 countries):a year-on-year changes in the consumer price index (CPI), selected quintiles, 2021–2023

(Percentage points)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of CEPALSTAT [online] https://statistics.cepal.org/portal/cepalstat/index.html?lang=en and the Household Survey Data Bank (BADEHOG).

Note: The change in the CPI is calculated as the median of the year-on-year changes in the CPI for each quintile in the set of countries mentioned. The median is used rather than the mean to minimize the impact of extreme values in some countries. The quintiles represent groups comprising 20% of the population, ranked by the per capita income of the households they belong to. The bottom and top quintiles of the distribution were selected for the chart: quintile I, representing the lowest-income 20% of the population, and quintile V, representing the highest-income 20%.

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

Labour inclusion, which is the central theme of this edition of the Social Panorama of Latin America and the Caribbean, is closely related to the issues discussed in the rest of the chapter. The main way for people to obtain income is in the labour market, through remuneration for work. Thus, opportunities to participate in that market and to have an occupation that meets certain quality standards largely determine the likelihood of individuals and their household members being poor or not. Adult women are the most likely to be non-participants in the labour market and thus to have no income of their own, and they are overrepresented in poor households. Similarly, low-quality jobs with unreliable pay are one cause of large income gaps and a lack of resources for people to meet their basic needs. Determined efforts to achieve greater labour inclusion are therefore essential if the region is to make significant progress with the commitment to reduce inequality and eradicate poverty established in the 2030 Agenda for Sustainable Development.

Against this background, the following sections analyse the recent situation with regard to income inequality, poverty and the links between social strata and labour inclusion. Following the normal practice in this publication, the latest household surveys available in the Latin American countries, from 2022 in this case, are used. The information on household income from this source, which provides a basis for calculating various inequality and poverty indicators, is supplemented with Forbes data for extreme wealth, which is taken to mean ownership of assets worth more than US$ 1 billion.

A. Income inequality and extreme wealth

In 2022, income inequality declined to levels lower than before the onset of the pandemic. The Gini inequality index was lower than in 2019 in 9 of 12 Latin American countries: from that year to 2022, the index declined by an average of 1.1% annually. This progress occurred in a context of very high inequality, with the top decile receiving 21 times as much income as the bottom decile. Wealth was even more concentrated than income: in 2021, the assets of the region’s 105 billionaires represented 4% of the wealth of the entire population, a higher percentage than in 2019 or 2020.

1. Income inequality declined to below its pre-pandemic level

The various manifestations of inequality, especially inequality in income distribution, are very important in Latin America because of the different economic, social and political implications they entail. From an economic perspective, the higher the level of inequality is, the smaller the prospects for growth, since inequality means that certain population groups have less access to education and job opportunities, which reduces opportunities to innovate and increase productivity. In addition, inequitable income distribution has a negative impact on aggregate demand and on the distribution of investments in services and infrastructure (ECLAC, 2018b).

In the social sphere, income inequality influences the dynamics between different socioeconomic groups and leads to gaps in labour inclusion, perceptions of justice and social cohesion. Politically, high inequality could present challenges for governance and the democratic process, and potentially affect institutional stability (ECLAC, 2022a).

As is traditional, income inequality and its evolution are estimated from the household surveys of the region’s countries.[6] According to the most recent figures, if the population is ranked by per capita household income and 10 groups with the same number of people in each (deciles) are constructed, the highest-income group captures between 29% and 45% of total income in each country, while the lowest-income group captures between 0.4% and 2.5%. Taking a simple average of the 15 countries in the region for which data are available to 2021 or 2022, the tenth decile receives 34.9% of total income, 21 times as much as the first decile (1.7%) (see figure I.4).

Figure I.4

Latin America (15 countries): income received by deciles I, I to IV and X, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a The figures for Honduras and the Plurinational State of Bolivia are from 2021.

b Simple averages.

Another measure of the gap between the incomes of the highest- and lowest-income groups is the Palma ratio, which is defined as the ratio between the income received by the highest decile and the sum of the income received by the first four deciles.[7] The average value of this index is 2.4 for the 15 countries of the region with recent data, while the individual country values range from 1.6 to 4.9.

Complementarily, inequality can be represented by synthetic indices that capture the incomes of the entire population and not only those of the groups at the extremes. The Gini index, one of the most widely used measures of inequality, takes values between 0 and 1, with a higher value representing higher income concentration. In 2022, this index ranged from 0.38 to 0.56 in 13 countries for which recent information was available (see figure I.5). Argentina, the Dominican Republic, El Salvador and Uruguay were the countries where the index was lowest (0.40 or below), and Brazil, Colombia, Costa Rica and Panama were the countries where it was highest (0.48 or above).

Figure I.5

Latin America (13 countries): Gini index of inequality, 2014–2022

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The Gini index of inequality takes values from 0 to 1, where 0 means no inequality and 1 maximum inequality. The chart shows the countries for which data were available up to 2022, ranked by that year’s Gini index. The 2014 figures are actually from 2013 for Chile and 2016 for Brazil and Mexico. The 2019 and 2021 figures are from 2017 and 2020 for Chile and from 2018 and 2020 for Mexico, respectively. Incomes equal to 0 were taken into account in calculating the Gini index.

a The 2014 figures were adjusted for the difference between the National Household Survey (PNAD) and the Continuous National Household Survey (PNAD Contínua) in 2014, to make them comparable with those of later years.

b The 2014 and 2019 figures were adjusted for the difference resulting from the updating of the Large Integrated Household Survey (GEIH) sampling frame in 2021 (1.08), to make them comparable with the 2021 and 2022 figures.

c Simple averages.

Considering the 13 countries for which data were available up to 2022, the regional average Gini index stood at 0.45 that year, almost 3% lower than in 2021. This represented a fall of 1.1% per year over the period 2019–2022, a larger decline than was observed between 2014 and 2019 (0.2%) for that set of countries.

Between 2019 and 2022, the Gini index fell in 9 of the 12 countries with comparable information for the period. In annualized terms, the largest fall was in the Dominican Republic (4.1%), followed by Argentina (2.2%) and Brazil (1.5%). In six other countries (Mexico, Chile, Peru, Costa Rica, Ecuador and Panama), inequality declined at an annual rate of between 1.3% and 0.6%. In the cases of El Salvador and Paraguay, there was no significant change over the period, while Uruguay was the only country where the Gini index increased, at a rate of 0.8% per year.

Real changes in mean income (measured in poverty lines) by income quintile allows changes in inequality in each of the countries to be understood. In general, an improvement in the incomes of households at the bottom of the distribution relative to those at the top will lead to a decline in income inequality. Such an improvement can occur both in contexts of growth and in contexts where average income is falling in the country. Thus, the distribution might improve because the incomes of the bottom quintiles grow more than the rest, or because they fall less.

In all nine countries where inequality fell between 2019 and 2022, the income of the first quintile improved relative to the income of the fifth quintile. In the Dominican Republic, Argentina and Costa Rica, this was because the incomes of the poorest households remained unchanged in real terms, while those of the highest-income quintile declined. In Brazil, Panama and Peru, the incomes of the first quintile increased significantly, while incomes in the rest of the quintiles fell, with higher-income households most affected. In Chile, Ecuador and Mexico, lastly, the incomes of the poorest quintile grew along with those of almost all the other quintiles, but at a faster rate than in the highest-income quintile (see figure I.6).

Figure I.6

Latin America (12 countries): annualized changes in average income, in poverty lines, by per capita income quintile, 2019–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The chart shows the countries for which data were available up to 2022, ranked by the annualized change in the Gini index between 2019 and 2022. Colombia is excluded, since the 2022 figure is not comparable with the 2019 figure. The starting year is 2019, except in Chile, where it is 2017, and Mexico, where it is 2018.

In the cases of El Salvador, Paraguay and Uruguay, the three countries where the Gini index changed very little or increased, average household income fell in all quintiles. However, in contrast to the group of countries where the Gini index declined, the incomes of the poorest quintile fell the most in El Salvador and Uruguay, while in Paraguay the fall was similar across all groups.

These changes in household income depend on the behaviour of the different sources composing it: earnings, retirement pensions, public and private transfers, property income, imputed rent and other income. The share of these sources differs depending on the position of individuals in the overall income distribution.

The bulk of people’s resources come from earned income (a regional average of 70%), and its share increases as total income rises. The composition of this income source varies with occupational status. Thus, in the first quintile, the share of wage income is similar to that of self-employment income and other employment income. In the intermediate quintiles, the contribution of wage employment increases, while that of self-employment decreases. In the fifth quintile this trend is reversed, with the income share of wage employment being lower and that of self-employment higher than in the fourth quintile (see figure I.7).

Non-contributory public and private transfers account for a large share of the income of the poorest groups. In fact, slightly more than one fifth of the income of the first quintile comes from this source, whose share decreases as household income rises, until it represents around 4% in the fifth quintile. The opposite is true for pensions, which account for a very small share of the income of the poorest households and represent just over 10% of the total income of the top quintile. As might be expected, income from asset ownership only has an appreciable share in the fifth quintile, although the share of this source is underestimated in surveys. Lastly, the share of imputed rent is relatively stable across the distribution, since the majority of households own their home.[8]

Figure I.7

Latin America (15 countries):a shares of income sources in per capita income, by quintile, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The figures for Honduras and the Plurinational State of Bolivia are from 2021.

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

Earnings are distributed more unequally than total income. This means that the proportion of earnings concentrated in a few hands is greater than that of total income, which is made up of earnings and other types of income derived from asset ownership and contributory and non-contributory transfers received by households.

If the Palma index is considered in relation to the economic returns on labour, the richest decile captured 2.7 times as much in 2022 as the poorest four deciles combined; for total income, the multiple was 2.4. Earnings and total income levels and gaps across different population groups vary by country. For example, according to the Palma index, the distribution of earnings is similar to that of total income in Colombia, El Salvador, Peru and Uruguay, while earnings are significantly more unequal than total income in Argentina, Brazil, Chile and Panama. Of the set of countries with information available for 2022, only in Mexico was total income more unequally distributed than earnings (see figure I.8).

The income changes presented in figure I.6 can be analysed according to the changes in earnings and total income in the top and bottom quintiles of the distribution (see figure I.9). Between 2019 and 2022, earnings improved more (or worsened less) in the first quintile than in the highest-income quintile in most of the countries analysed, meaning that distribution improved. The improvements were greatest in Argentina, Mexico, Panama and the Dominican Republic, but also occurred in Brazil, Costa Rica and Peru. In these countries, earnings contributed to the distributional improvement mentioned above. In Chile and Ecuador, earnings changed in similar proportions in the first and fifth quintiles, so that their effect on the gap between the two groups was neutral. In Uruguay and El Salvador, lastly, changes in earnings tended to widen the gap between the first and fifth quintiles.

Figure I.8

Latin America (13 countries): Palma index for total income and earnings, 2022

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The Palma index is defined as the ratio of the total cumulative income of the tenth decile to the sum of the total incomes of the first four deciles.

Figure I.9

Latin America (12 countries): real annual changes in average earnings and total income, by per capita income quintile, 2019–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The countries were ranked by the difference between the changes in the earnings of the first quintile and the fifth quintile. The starting year is 2019, except in Chile, where it is 2017, and in Mexico, where it is 2018.

Because earnings are such a large share of total income, it is to be expected that changes in the two types of income by quintile will be of similar sign and magnitude, which is to say that most distributional changes will originate in the labour market. Broadly speaking, this is the behaviour observed in most of the countries included in figure I.9, with a few exceptions. Unearned income narrowed the gaps between the top and bottom quintiles by increasing more in the first quintile, especially in Brazil, Ecuador and Panama, or by falling in the fifth quintile, as in Argentina and El Salvador. In Mexico and Paraguay, unearned income partly offset the distributional improvement resulting from earnings.

Of the different types of unearned income, special mention should be made of non-contributory State transfers as a factor offsetting the inequalities that arise in the labour market. Their effect can be illustrated by comparing the value obtained when the Gini index for total income is calculated with and without these transfers. On average, State transfers brought the Gini index down by 2.8% in 2019, 3.7% in 2021 and 3.4% in 2022 compared to the value that would have been obtained if they had not been included. In 2020, when governments put in place large packages of extraordinary transfers to mitigate the effects of the pandemic, their impact was greater and resulted in the Gini index being 5.6% lower than it would have been without them.

The impact on inequality of the extraordinary transfers made in 2020 varied from country to country, reducing the Gini index by between 6% and 9% in Costa Rica, Argentina, Brazil and Chile and by between 4% and 5.6% in Ecuador, Peru, Paraguay, the Dominican Republic and Uruguay. Since emergency transfer programmes were wound down after the pandemic, their effect on inequality also declined. In 2022, public transfers brought the Gini index down by between 2% and 5% in that set of countries. In the case of El Salvador, the distributional impact of transfers was minimal (around 0.3%), except in 2020, when it was 1.4% (see figure I.10).

Figure I.10

Latin America (12 countries): changes in the Gini index for per capita income when non-contributory State transfers are included in income, 2019–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: Incomes equal to 0 were taken into account in calculating the Gini index. The countries are ranked by the 2022 figures. The 2019 figures are actually from 2017 for Chile and from 2018 for Mexico.

The analysis was carried out by aggregating the incomes received by all household members and does not take account of inequalities between individuals in their opportunities to obtain income of their own, either by participating in the labour market or through transfers. Lack of independent income, which especially affects women, is an important indicator for the analysis of women’s economic autonomy and the characterization of gender inequalities (ECLAC, 2022a).

Taking the simple average of the 13 countries for which information was available in 2022, 23% of women aged 15 and over and 9.7% of men aged 15 and over had no income of their own (see figure I.11). The gender gap that this indicator illustrates manifests itself across the entire income distribution, as the proportion of women with no income of their own far exceeds that of similarly placed men in all quintiles. In keeping with these results, non-participation in paid employment, which is one factor in the lack of independent income, mainly affects women and is most prevalent in the lower-income strata, as discussed below in the section on social stratification.

Figure I.11

Latin America (13 countries): population aged 15 and over with no independent income, by sex and per capita income quintile, 2022a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: Simple average of countries with information available for 2022.

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Mexico, Panama, Paraguay, Peru and Uruguay.

In conclusion, although various income distribution indicators show that inequality decreased in most of the countries analysed in 2022, this decrease does not represent a significant change in the large structural gaps that characterize Latin American societies and constitute an obstacle to economic and social development. Many of these gaps arise in the labour market, resulting in high inequality of earnings. While transfers play an important role in narrowing these gaps, there are other types of income that tend to aggravate them, such as income derived from financial and non-financial assets. As has been noted in previous editions of the Social Panorama, capital income tends to be underrecorded in household surveys, with alternative measures that apply procedures to correct this underrecording revealing much greater inequality than described here (ECLAC, 2022a).

2. The region has extreme levels of wealth concentration

Previous editions of the Social Panorama have shown that income inequality is greater than household surveys typically indicate (ECLAC, 2019 and 2022a), and where information on the personal distribution of wealth has been obtained, this has been found to be substantially more concentrated than income. For example, the data provided by Chancel and others (2022) on four Latin American countries in or around 2021 show that the top decile in these countries concentrated considerably more wealth than income, with the difference between the shares taken of each ranging from 15 to 21 percentage points (see figure I.12). These statistics highlight the importance of looking more thoroughly at the unequal concentration of wealth in the region’s countries.

Figure I.12

Latin America (4 countries): shares of total wealth and income taken by the top decile, 2021

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of L. Chancel and others (coords.), World Inequality Report 2022, World Inequality Lab, 2022 [online] https://wir2022.wid.world/download/.

Note: For more details on the methodology used, see F. Bajard, L. Chancel and R. Moshri, “World Inequality Report 2022: Technical Notes for Figures and Table”, 2021 [online] https://wir2022.wid.world/methodology/. The share of the top decile is the portion of income or wealth taken by the 10% of the population with the highest income or wealth in the country’s distribution. Income inequality at the national level is measured on the basis of the distribution of pre-tax income among the whole population, excluding social assistance transfers. Data sources include household surveys, national accounts and tax records. Wealth inequality is assessed on the basis of net household wealth. Financial and non-financial assets are added together and debts are subtracted. Data sources include official national accounts and International Monetary Fund (IMF) and Organisation for Economic Co-operation and Development (OECD) data on pension wealth and foreign assets and liabilities, among others.

Extreme asset concentration is one of the most evident expressions of inequality. Wealth is less susceptible to labour market fluctuations than income and tends to persist more robustly over time (ECLAC, 2022a). Measuring and monitoring extreme wealth provides a proxy for how some of the most important factors reproducing inequality are working. Wealth accumulation is influenced by the economic and social structure, and positions of advantage tend to be passed down through the generations; there is evidence not only that wealth inequality correlates negatively with intergenerational social mobility (Fisher and others, 2016; Yang and Zhou, 2022),[9] but also that socioeconomic status persists more strongly in the upper part of the distribution (OECD, 2018; Waldenström, Adermon and Lindahl, 2016).

Excessive wealth concentration can also have negative effects on economic growth and increase public distrust of elites and institutions. These problems are compounded when billionaires’ wealth arises or grows because of their political connections or their links to the State apparatus, which can lead to questions about the legitimacy of their assets and fuel social tensions. Another reason to monitor extreme wealth is that a great concentration of assets provides opportunities to collect permanent, progressive tax revenues that can be used for public policies to guarantee social rights (ECLAC, 2022a).

In view of the lack of official sources for measuring the incidence of extreme wealth in the countries of Latin America and the Caribbean, the information compiled in the annual Forbes list of billionaires was used. Despite the limitations of these data, they are the most comprehensive source for measuring extreme wealth in the region.[10] [11] The Forbes list includes all individuals in the world with a verified personal net worth of US$ 1 billion or more, excluding those who derive income from illegal activities.[12] [13] Personal net worth is calculated as the sum of financial and non-financial assets minus debts at current prices.

The wealth of Latin American and Caribbean billionaires totalled US$ 453 billion in 2022, US$ 4.6 billion more than in 2021 and US$ 56.3 billion more than in 2019 (see figure I.13). However, owing to inflation, which had a strong international impact in 2021 and 2022, the real wealth of Latin American and Caribbean billionaires fell by 6.5% in 2022 from 2021. In real terms, the wealth of the region’s billionaires in 2022 was very close to what it had been in the year immediately before the pandemic, and 4.4% lower than in 2012.

Figure I.13

Latin America and the Caribbean: net worth of billionaires, 2012–2022

(Billions of dollars)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of K. A. Dolan and C. Peterson-Withorn, “Forbes World’s Billionaires list”, Forbes [online] https://www.forbes.com/billionaires-2022/ and CEPALSTAT [online database] https://statistics.cepal.org/portal/cepalstat/index.html?lang=en.

Note: Net worth estimated by Forbes for 2022 on the basis of equity prices and exchange rates as of 11 March that year. Personal wealth data prior to 2022 are Forbes estimates published each year on the magazine’s website and compiled and systematized by ECLAC for Latin America and the Caribbean. The billionaires who appeared on the Forbes list at least once between 2012 and 2022 were citizens of one of the following 11 countries: Argentina, Barbados, Belize, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Mexico, Peru, Saint Kitts and Nevis and Uruguay. Wealth is measured in constant 2012 dollars deflated by the United States urban consumer price index (CPI) (see [online] https://www.minneapolisfed.org/about-us/monetary-policy/inflation-calculator/consumer-price-index-1913-).

Thus, the evolution of the wealth of the super-rich in Latin America and the Caribbean has been very consistent with the performance of the aggregate economy: the correlation between regional GDP and the wealth of billionaires was 0.65 between 2012 and 2022. As for the more recent years, billionaires’ wealth contracted in 2020, largely because of the pandemic-related crisis, then recovered strongly in 2021 in line with the economic upswing resulting from expansionary monetary and fiscal policies, before falling in real terms in 2022 because of inflation.

In 2021, the wealth of 105 citizens in eight countries of the region accounted for 3.6% of the total wealth of the population of all the Latin American and Caribbean countries included in the report by Credit Suisse Research Institute (2022). The concentration of extreme wealth was greater in 2021 than in 2020 and 2019 and matched the 2018 level. In 2021, however, billionaires’ share of the total wealth of the Latin American and Caribbean population was lower than it had been between 2013 and 2015, when the super-rich’s share of the region’s personal wealth exceeded 4% (see figure I.14).

Figure I.14

Latin America and the Caribbean: wealth of Latin American and Caribbean billionaires as a share of the population’s total wealth, 2012–2021

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of K. A. Dolan and C. Peterson-Withorn, “Forbes World’s Billionaires list”, Forbes [online] https://www.forbes.com/billionaires-2022/ and Credit Suisse Research Institute, Global Wealth Databook 2022: Leading Perspectives to Navigate the Future, 2022 [online] https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html.

Note: The region’s wealth is taken to be that of all the Latin American and Caribbean countries included in Credit Suisse Research Institute (2022). Personal net worth is the total value of financial and non-financial assets minus debts. Credit Suisse compiles and produces wealth estimates in a variety of ways, e.g., through direct measurements based on surveys or balance sheets, regressions and imputations. Values in brackets indicate the number of billionaires in the year concerned. Billionaires who appeared on the Forbes list at least once between 2012 and 2021 were citizens of one of the following 10 countries: Argentina, Barbados, Belize, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Mexico, Peru and Saint Kitts and Nevis.

Thus, the concentration of extreme wealth in the region is considerable and may even be underestimated: although not all countries in Latin America and the Caribbean are included in the report by Credit Suisse Research Institute (2022),[14] the Forbes estimates not only fail to capture the assets of billionaires whose obvious source of wealth are illegal businesses,[15] but may also be less likely to capture wealth held in offshore bank accounts subject to financial secrecy or in opaque trust mechanisms (Collins and Hoxie, 2015).[16]

When the situation is analysed by country, the greatest concentration of extreme wealth in 2021 was in Brazil, where billionaires owned 6.4% of the country’s wealth, followed by Chile (5.4%) and Argentina (4.7%) (see table I.1). Billionaires’ share of national wealth increased systematically in Argentina between 2012 and 2021, mainly owing to the decline in the wealth of the general population.[17] In Chile, concentration increased in 2021 from 2020, but without reaching the levels observed between 2012 and 2015, when values exceeded 6%. In Brazil, concentration in 2021 was the highest since 2016, while in Mexico the concentration of extreme wealth was lower in the last three years than in the years prior to 2019, as billionaires’ wealth grew more slowly than that of the general population between 2012 and 2021.

Table I.1

Latin America (6 countries): billionaires’ wealth as a share of the wealth of the country’s total population, 2012–2022

(Percentages)

2012

2014

2015

2016

2017

2018

2019

2020

2021

Argentina

1.1

1.3

1.3

1.9

2.1

3.7

3.6

3.4

4.7

Brazil

4.9

6.1

7.6

4.6

4.4

4.9

4.7

4.2

6.4

Chile

6.4

6.2

6.2

4.4

5.7

5.4

4.8

2.8

5.4

Colombia

5.5

6.2

3.9

3.1

3.0

2.8

2.7

2.3

4.3

Mexico

4.6

5.1

5.5

4.1

4.0

4.5

3.7

2.7

3.3

Peru

1.5

4.4

3.1

1.3

2.2

2.8

2.5

1.2

2.4

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of K. A. Dolan and C. Peterson-Withorn, “Forbes World’s Billionaires list”, Forbes [online] https://www.forbes.com/billionaires-2022/ and Credit Suisse Research Institute, Global Wealth Databook 2022: Leading Perspectives to Navigate the Future, 2022 [online] https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html.

Note: Excludes countries for which adequate series are not available or for which total national wealth data are not provided in Credit Suisse Research Institute (2022).

Between 2020 and 2021, the total wealth of Latin American billionaires grew incomparably more strongly than that of the rest of the population in their respective countries (see figure I.15). The largest differences were in Colombia and Chile, where the wealth of the super-rich grew at rates 29.8 and 28.1 times as high as the wealth of the rest of the population, respectively. Between 2019 and 2020, the total worth of billionaires fell by more in relative terms than the total worth of the rest of the population. However, the relative magnitude of the contraction in the assets of the extremely wealthy in the first year of the pandemic was much smaller than the scale of the recovery in 2021.

Figure I.15

Latin America (6 countries): relative changes in the total wealth of billionaires and the rest of the population, 2012–2021

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of K. A. Dolan and C. Peterson-Withorn, “Forbes World’s Billionaires list”, Forbes [online] https://www.forbes.com/billionaires-2022/ and Credit Suisse Research Institute, Global Wealth Databook 2022: Leading Perspectives to Navigate the Future, 2022 [online] https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html.

Note: Percentage changes in current dollars in the total wealth of each group (billionaires and the rest of the population) in period t + 1 relative to period t. For the period 2012–2019, rates are annualized. Current values are used because of the difficulty of finding an inflation rate applicable to the two groups being compared. Wealth is distributed across different geographical areas (and currencies) that are subject to local inflation, which makes it very difficult to estimate a consumer price index (CPI) applicable to billionaires by country, since it would be necessary to calculate a deflator for each (and have information on the geographical distribution of wealth). Changes in total rather than average wealth are analysed because an increase in the number of people with wealth of US$ 1 billion or more is associated with a decrease in the average wealth of billionaires. If average wealth were taken, it might be concluded that the proportion of total wealth taken by billionaires was falling, when in fact this is not the case. Excludes countries for which adequate series are not available or for which total national wealth is not reported in Credit Suisse Research Institute (2022).

The distribution of wealth among the region’s billionaires is also highly concentrated. In 2022, seven Latin Americans with personal fortunes of US$ 10 billion or more accounted for 41% of the total wealth of the region’s billionaires, and their fortunes represented about 3.2% of the GDP of Latin  America as a whole (see figure I.16).[18] In 2022, the wealth of billionaires with fortunes of US$ 10 billion or more represented a smaller share of regional GDP than in 2021 (3.8%) but a larger share than in 2019 or 2020.

In 2022, the sectors of activity in which most of the real assets of Latin American billionaires were concentrated were finance and investment, telecommunications, food and beverages, and mining and metals, in that order (see figure I.17). Compared with 2021, the largest relative increase in billionaires’ wealth was in the sectors denominated “other”, “diversified” and “media and entertainment”; the largest declines were in the technology, health care, and fashion and retail sectors.

Figure I.16

Latin America: wealth of Latin Americans with assets of US$ 10 billion or more as a share of regional GDP, 2012–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of K. A. Dolan and C. Peterson-Withorn, “Forbes World’s Billionaires list”, Forbes [online] https://www.forbes.com/billionaires-2022/ and CEPALSTAT [online database] https://statistics.cepal.org/portal/cepalstat/index.html?lang=en.

Note: The figures in brackets are the number of people with assets worth US$ 10 billion or more. The people who appeared on the Forbes list at least once between 2012 and 2022 as owning assets of that amount were nationals of Brazil, Mexico, Chile and Colombia.

Figure I.17

Latin America and the Caribbean: billionaires’ assets by sector of activity, 2019–2022

(Billions of dollars)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of K. A. Dolan and C. Peterson-Withorn, “Forbes World’s Billionaires list”, Forbes [online] https://www.forbes.com/billionaires-2022/.

Note: Assets in constant 2019 dollars deflated by the United States urban consumer price index (CPI) (see [online] https://www.minneapolisfed.org/about-us/monetary-policy/inflation-calculator/consumer-price-index-1913-).

Comparing the real wealth of billionaires in 2022 with that in 2019 reveals a large increase in the following sectors: health care (51%), diversified (34%), mining and metals (26%) and energy (22%). In the health sector, the increase occurred mainly in 2021, as the wealth of the super-rich in this sector remained almost unchanged during the first year of the pandemic (2020), in contrast to the other sectors, where it contracted. Between 2019 and 2022, the steepest relative declines in wealth were in the following sectors: media and entertainment (36%), manufacturing (25%), other (23%), food and beverages (18%) and fashion and retail (17%). The wealth of billionaires in the food and beverage sector, and especially in manufacturing, declined mainly in 2020.

Lastly, it has been pointed out that inheritance diminishes social mobility and reproduces inequality over time (OECD, 2018; Waldenström, Adermon and Lindahl, 2016; Palomino and others, 2022). It might be supposed that inheritance does not play as large a role in modern meritocratic economies as in the past, but the share of intergenerational transfers in the total wealth of some developed countries has increased in recent decades (Piketty, 2011; Piketty and Zucman, 2015; Alvaredo, Garbinti and Piketty, 2017).[19]

As regards the importance of inheritance for billionaires, a study of Forbes list members between 1996 and 2015 found that the percentage of billionaires who had become so by their own efforts had increased, especially in emerging markets (Freund and Olivier, 2016). In 2019, 2020 and 2021, however, inheritance played a quite important role in the fortunes of the Latin American super-rich, with just over half having obtained all or part of their wealth in this way. These figures are very similar to those in Western Europe and India, and well above the levels observed in the United States and Canada, China and the rest of the world (see figure I.18).

Figure I.18

World: billionaires whose wealth is partly or wholly inherited, 2019, 2020 and 2021

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of K. A. Dolan and C. Peterson-Withorn, “Forbes World’s Billionaires list”, Forbes [online] https://www.forbes.com/billionaires-2022/.

Note: The Forbes list of the world’s billionaires differentiates between the super-rich who have built their fortunes entirely by their own efforts, those whose wealth is inherited and those whose wealth is inherited and growing. The percentages presented here are the sum of the latter two categories. In compiling the list of the 400 richest United States citizens, Forbes uses an ordinal scale from 1 to 10 on which these individuals are ranked by the degree to which they have earned their wealth through their own efforts. For more information, see [online] https://www.forbes.com/sites/kerryadolan/2018/07/13/heres-what-forbes-means-by-self-made-from-bootstrappers-to-silver-spooners/?sh=69a7a22e1ca3. No analysis was performed to determine the share of inherited assets in the total wealth of billionaires because the information provided by Forbes does not distinguish the portion derived from inheritance.

a Includes the special administrative regions of Hong Kong (China) and Macao (China).

b Excludes the countries of the former Soviet Union and Eastern Europe.

B. Poverty, middle-income strata and links to labour inclusion

In 2022, the percentage of people living in poverty in the region fell back to pre-COVID-19 levels, even though poverty remains higher than in 2019 in more than half the countries. The chances of moving out of poverty and into the middle or upper socioeconomic strata are heavily dependent on labour inclusion. Most people in the low-income stratum work in low-productivity activities or do not participate in employment.

1. Poverty has fallen, but progress towards eradication is too slow

Overcoming poverty is a prerequisite for greater development and has been set as the first of the 17 Goals of the 2030 Agenda for Sustainable Development. Poverty is associated with situations of deprivation in a number of areas of well-being that societies consider essential, depriving people of the basic capabilities they need to live a fulfilling life and constituting a violation of human rights. Lack of an income sufficient to acquire a basic set of goods and services is one of the most obvious characteristics of poverty and one of the usual yardsticks for quantifying it.[20] The results presented in this section are based on the premise that people are poor when their per capita household income is less than the cost of a basic basket of food and other goods and services (see box I.1).

Box I.1

Income poverty measures of the Economic Commission for Latin America and the Caribbean (ECLAC)

ECLAC calculates the poverty and extreme poverty figures presented in this chapter on the basis of a common methodology designed to provide a regional overview that is as comparable as possible, given the heterogeneity of the different countries’ measurement instruments and data collection procedures.

The approach taken by ECLAC to poverty estimation consists of classifying a household and its members as poor when their income is below the poverty line. The poverty line represents the level of income needed for each household to meet the basic needs of all its members. The basic food basket for poverty measurement is constructed by taking a selection of foodstuffs that includes everything needed to cover the nutritional needs of the population, considering physical activity levels, consumption habits, the actual availability of foodstuffs and prices in each country and geographical area.

To the value of this basic food basket, known as the “extreme poverty line”, the amount households require to meet basic non-food needs is added in order to calculate the total value of the poverty line. This is done by multiplying the extreme poverty line by a factor (the Orshansky coefficient) representing the ratio between total expenditure and food expenditure for a benchmark population, which takes different values in each country and in urban and rural areas.

The value of the poverty and extreme poverty lines is updated annually by the cumulative change in the consumer price index (CPI): the extreme poverty line is updated by the change in the food CPI, while the non-food part of the poverty line is updated by the change in the non-food CPI. Thus, the Orshansky coefficient implicit in the poverty line varies from year to year with the relative evolution of prices. The use of different price deflators for the two components of the poverty line means that in periods when food inflation is higher than inflation for other goods, extreme poverty increases by more than poverty.

The percentages of households and the population in poverty and extreme poverty were obtained by contrasting the value of the two lines with the total per capita income of each household. A household’s total income is obtained by adding together the incomes received by its members (in cash and in kind) and includes earnings, income from retirement and other pensions and other transfers, income from asset ownership, imputed rent and other income.

Poverty lines are calculated on the basis of the household expenditure surveys conducted every 5 to 10 years in most of the region’s countries. Household income is estimated from employment or multipurpose surveys, usually available annually or biennially. Both data sources are included in the ECLAC Household Survey Data Bank (BADEHOG), a repository of household surveys whose variables are harmonized to produce estimates that are comparable across countries, insofar as the characteristics of the instruments themselves allow.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Income poverty measurement: updated methodology and results, ECLAC Methodologies, No. 2 (LC/PUB.2018/22-P), Santiago, 2019.

In 2022, 29.0% of Latin America’s population was living in poverty and 11.2% in extreme poverty. These percentages are appreciably lower than in 2021, when the figures were 32.6% and 13.0%, respectively. They also reflect a more favourable situation than in 2019 (30.2% and 11.3%, respectively), the year before the onset of the COVID-19 pandemic (see figure I.19).

Despite recent progress, in 2022 more than 180 million people in the region did not have enough income to cover their basic needs, and 70 million of these did not have enough income to buy a basic food basket. Poverty figures in 2022 were similar to those at the beginning and end of the last decade, showing that insufficient progress has been made at the regional level towards the goal of eradicating poverty. Matters are even less encouraging where extreme poverty is concerned, with the latest figures showing that over 20 million more people are in this situation than 12 years ago.

As of 2023, no appreciable improvement in the living conditions of the poor is anticipated. In a context of low economic growth, poverty and extreme poverty figures are likely to remain broadly unchanged at the regional level, although some countries could show substantial changes.

Figure I.19

Latin America (18 countries):a poverty and extreme poverty rates and numbers of people living in poverty and extreme poverty, weighted averages, 1990–2022 and projections for 2023

(Percentages and millions of people)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

b Projections.

Of the 13 countries with information available for 2022, poverty fell by at least 1 percentage point from 2021 (or 2020, in the cases of Chile and Mexico) in 9 of them. Brazil was the country where poverty fell the most over this period (-4.8 percentage points), from 24.4% to 19.6%. However, it was the only country where poverty increased in 2021, so the level achieved was only slightly lower than that of 2019. Poverty also contracted sharply in Mexico and Chile (-4.4 and -2.9 percentage points per year, respectively), although in their case the comparison is with 2020, the year in which the pandemic had the greatest impact. These countries also saw the largest declines in extreme poverty (see figure I.20).

Figure I.20

Latin America (13 countries): extreme poverty and poverty rates and changes, 2021 and 2022

(Percentages and percentage points)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: Includes countries with data available for 2022, ranked by the percentage point change between 2021 and 2022 (shown in the chart). The figures for Chile and Mexico give the annualized change between 2020 and 2022.

Other countries whose poverty rates declined by at least 1 percentage point were Colombia, the Dominican Republic, Ecuador, Panama and Peru. Of the countries with data available for 2022, Argentina was unique in that poverty but not extreme poverty increased, while Paraguay was the only one where extreme poverty increased significantly.[21]

Although the average poverty rate in the region fell to a level somewhat below that observed before the onset of the pandemic, this was not the case in more than half the countries analysed. Of 12 countries, only Brazil, Chile, El Salvador, Mexico and Panama had lower poverty rates in 2022 than in 2019. In Argentina, the Dominican Republic, Paraguay, Peru and Uruguay, poverty was at least 1.4 percentage points higher than in 2019. The picture is similarly diverse for extreme poverty, with only three countries (Brazil, Ecuador and Mexico) ending the period with rates at least 0.5 percentage points lower than in 2019.

The heterogeneity between countries described above is also evident in the comparison with 2014, when the regional poverty rate reached its lowest value since 1990, marking the end of a period of uninterrupted poverty reduction at the regional level that had begun in the early 2000s. Since then, some countries, such as the Dominican Republic, El Salvador and Mexico, have registered large declines in poverty and extreme poverty indicators, while others, such as Argentina and Honduras (as of 2021), face a more unfavourable situation than at the beginning of the period. In most cases, the overall picture for the full period is one of a gradual improvement in poverty indicators, with decreases of around 0.5 percentage points per year. Of course, this does not mean that the indicators have evolved so gradually from year to year; in particular, there were large increases in poverty in virtually all the countries in 2020 after the onset of the pandemic, partially offset by declines the following year (see figure I.21).

The poverty (and inequality) situation in the English-speaking Caribbean is more difficult to assess because of the lack of recent information. Box I.2 presents the estimates available for 18 countries in the subregion, only a few of which are later than 2018. However, by drawing on complementary sources of information, it can be inferred that poverty presented a cycle similar to that described for Latin America, with sharp increases during the pandemic and a return to values closer to those of 2019 in 2021 or 2022.

Figure I.21

Latin America (15 countries): extreme poverty and poverty rates, 2014–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a The figures are from a new series based on the 2018 National Population and Housing Census sampling frame and are not comparable with those of earlier years.

Box I.2

Poverty and inequality in the English-speaking Caribbean

There is relatively little information available on poverty and inequality levels in the Caribbean countries over the last decade. Poverty assessments were conducted for many countries under the Caribbean Development Bank’s Country Poverty Assessment programme, and by 2012 most of the countries had carried out at least two living conditions surveys or poverty assessments. The pause in the implementation of this programme and the difficulties caused by the coronavirus disease (COVID-19) pandemic have meant that only a few countries have recent poverty data. Jamaica is the only Caribbean country that measures poverty annually, or almost annually. Apart from Jamaica, the countries that conducted poverty assessments in the 2010s were Barbados, Belize, Grenada and Saint Lucia.

The following table presents the most recent estimates available for 18 countries in the English-speaking Caribbean from the 2000s onward. Although the figures are for very different years, ranging from 2002 to 2019, and are not necessarily comparable, they suggest that the situation is at least as heterogeneous as in Latin America. Two countries have poverty rates below 10%, four countries have rates above that threshold and below 20%, seven countries are in the 20% to 30% range, and another five countries have poverty rates ranging from 30% to 52%. The Gini inequality index, calculated for consumption rather than income, also varies significantly between countries, although values close to 0.4% predominate.

The Caribbean (18 countries): poverty and inequality indicators, latest year available

Country

Year

Poverty rate

(Percentages)

Extreme poverty rate

(Percentages)

Poverty line

(Dollars per year)

Extreme poverty line

(Dollars per year)

Gini index (consumption)

Anguilla

2008–2009

5.8

0.0

6 055

964

0.39

Antigua and Barbuda

2006

18.3

3.7

2 366

917

0.48

Bahamas

2013

12.5

...

4 247

...

0.41

Barbados

2010

19.3

9.1

3 931

1 985

0.47

2016–2017

25.7

...

3 855

1 784

0.32

Belize

2009

41.3

15.8

1 715

1 003

0.42

2018–2019

52.0

9.0

3 981

1 341

0.49

British Virgin Islands

2002

22.0

<0.5

6 300

1 700

0.23

Cayman Islands

2007

1.9

...

3 319

...

0.40

Dominica

2008–2009

28.8

3.1

2 307

902

0.44

Grenada

2008

37.7

2.4

2 164

887

0.37

2018–2019

25.0

3.5

2 512

1 074

0.40

Guyana

2006

36.1

18.6

...

...

0.35

Jamaica

2010

17.6

6.3

...

...

0.39

2019

11.0

4.0

...

...

0.37

Montserrat

2008–2009

36.0

3.0

5 333

1 754

0.39

Saint Kitts and Nevis

Saint Kitts

2008

23.7

1.4

2 714

961

0.38

Nevis

2008

15.9

0.0

3 625

1 086

0.38

Saint Lucia

2006

28.8

1.6

1 905

588

0.42

2016

25.0

1.3

2 386

786

0.43

Saint Vincent and the Grenadines

2008

30.2

2.9

2 046

906

0.40

Surinamea

2008

51.3

...

...

...

0.44

Trinidad and Tobago

2005

16.7

1.2

...

...

0.39

Turks and Caicos Islands

2012

21.6

0.0

6 650

2 000

0.36

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the national living conditions surveys, household budget surveys and Millennium Development Goal (MDG) progress reports of Guyana and Suriname.

a Urban areas only.

For countries with a recent survey-based poverty estimate, the World Bank, in its Macro Poverty Outlook, estimated how poverty was likely to have been affected by the latest economic data (World Bank, 2023). In Jamaica, poverty was estimated to have increased from 11% in 2019 to over 20% in 2020, before declining to 16.8% in 2021 and 12.6% in 2022. In Grenada, where the poverty rate was 25.0% in 2018–2019, it was estimated to have increased to 31.7% in 2020. In Saint Lucia, about 25% of Saint Lucians were poor in 2019, a figure that increased to over 30% in 2020 and then dropped back to around 25% in 2022. In Barbados, poverty had declined since the COVID-19 pandemic, but was estimated to still be above the level recorded before the health crisis, last measured in 2016 (25.7%). In Belize, the pre-COVID-19 pandemic poverty rate was estimated to be 52% in 2018–2019, and it was judged that the pandemic may have had a “severe social impact”, presumably worsening an already dire situation.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of F. Jones, “Population and development in the Caribbean (2018–2023): accelerating implementation of the Montevideo Consensus”, forthcoming, 2023.

One way of analysing the factors behind changes in poverty is to decompose changes in the income of the poorest households by source,[22] much as in the analysis carried out in section A for the gaps between quintiles. This procedure indicates that the poverty reduction observed in several countries of the region in 2022 relative to 2021 (except in Chile and Mexico, where the comparison is with 2020) was mainly due to an increase in household incomes from both wage and own-account work. In the six countries where the poverty rate declined by 2 percentage points or more, earnings grew by more than total income in Uruguay and accounted for almost the entirety of the growth in total income in Chile and the Dominican Republic and around 80% in Ecuador and Mexico. In Brazil, exceptionally, earnings accounted for only 50% of the change in total income.

Non-contributory cash transfers to low-income households tended to decline, as part of the winding down of pandemic-related emergency income protection programmes. They fell in five of the six countries mentioned above, the only exception being Brazil, where they contributed to poverty reduction. Growth in all other sources of income in most of the countries listed, albeit modest, also contributed to poverty reduction in this period (see figure I.22).

Figure I.22

Latin America (6 countries): annual changes in total per capita income among low-income households, by income source, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: Countries where poverty fell by two percentage points or more in 2022, ranked by the magnitude of the reduction. The figures are for the contribution of each source to the change in total income between 2021 and 2022, except for Chile and Mexico (2020 to 2022). The change in total per capita income is calculated from the sum of the contributions of each income source. The size of the lowest-income group is the percentage of people shown in brackets: Brazil (29%), Chile (19%), the Dominican Republic (28%), Ecuador (34%), Mexico (42%) and Uruguay (10%).

From a complementary perspective of analysis, changes in the poverty rate can be disaggregated into two factors: the growth of average household income and the change in the distribution of that income (see box II.2 in ECLAC, 2019). The two factors have had varying degrees of influence on the evolution of poverty over the past 15 years. In the period from 2014 to 2022, characterized by moderate poverty reduction in a large set of countries, income distribution played an important role in supporting low levels of average household income growth (as in the Dominican Republic and Mexico) or counteracting declines (as in Brazil, Costa Rica, Paraguay and Peru). Average income growth was the main factor behind poverty reduction in a few cases, including Chile, El Salvador and Panama.

These results contrast with those recorded some years earlier, between 2008 and 2014, a period characterized by significant reductions in poverty rates driven mainly by growth in average income. In that period, the contribution of distributional improvements to poverty reduction was relatively minor.

The data reaffirm the importance of income growth if significant progress is to be made towards poverty eradication, while also showing that income redistribution plays an important role in boosting poverty reduction in contexts of high average income growth and, above all, in bringing down poverty in periods of low average income growth (see figure I.23).

Figure I.23

Latin America (15 countries): annual changes in poverty and relative contributions of changes in average income and changes in distribution, 2008–2014 and 2014–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: Countries ranked by the rate of poverty reduction. The figures in figure A are for 2008–2014, except in the cases of Chile (2009–2015), El Salvador and Honduras (2009–2014). The figures in figure B are for 2014–2022, except in the cases of Brazil (2016–2022), Chile (2015–2022), Colombia and Honduras (2014–2021).

The magnitude and severity of poverty vary by the attributes of individuals and their households. Personal characteristics, such as sex, age, ethnicity or race and area of residence, affect the likelihood that a person will be poor (ECLAC, 2022a). Figure I.24 uses aggregate regional poverty figures to illustrate some of the main differences between groups.

Figure I.24

Latin America (18 countries):a people in poverty and extreme poverty, by area of residence, age and ethnicity or race, weighted averages, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

b Average of eight countries: Brazil, Colombia, Ecuador, Guatemala, Nicaragua, Panama, Peru and Uruguay.

c Average of 11 countries: Brazil, Chile, Colombia, Ecuador, Guatemala, Mexico, Nicaragua, Panama, Peru, the Plurinational State of Bolivia and Uruguay.

One of the main manifestations of gender inequality in Latin America is the higher incidence of poverty among women than among men at the ages of greatest participation in the labour market (20–59). On average, while 20.3% of men in this age group are poor, 23.9% of women are. This gender gap persists for households in extreme poverty, with women registering 1.1 percentage points more extreme poverty than men.

The femininity index of poverty is the ratio of female to male poverty in the age range indicated (20 to 59). All countries with information available as of 2021 or 2022 have values greater than 1.0 for this index, i.e., poverty is greater among women than among men (see figure I.25).

Compared to 2014, the femininity index has remained relatively stable on average across 15 selected Latin American countries, rising from 1.17 that year to 1.21 in 2022. In nine countries, however, this indicator increased by at least two tenths of a percentage point. The largest increases were in the Dominican Republic, the Plurinational State of Bolivia, El Salvador and Argentina, in that order.

Figure I.25

Latin America (15 countries): femininity index of poverty, 2014 and 2022

(Index values)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The countries are ranked by the femininity index of poverty in the most recent period. The 2014 figures are for 2013 in Chile. The 2022 figures are for 2021 in Colombia, Honduras and the Plurinational State of Bolivia.

a Simple average.

Age is a factor strongly associated with the risk of poverty. Children and adolescents face much higher poverty rates than the rest of the population. In 2022, 42.5% of those aged 17 and under were poor, while for the population aged 35–44, the rate was 26.7% (see figure I.24).

Between 2014 and 2022, the gap between people under the age of 18 and the rest of the population grew in six countries (the Dominican Republic, Costa Rica, Mexico, Panama, the Plurinational State of Bolivia and El Salvador, in that order) and narrowed in six others (mainly Uruguay, Brazil and Argentina). The lack of visible progress in reducing the gap between child and adolescent poverty and adult poverty is a cause for concern, owing to the impact that a lack of basic resources has on the development of the youngest, their pathways towards inclusion in society and the intergenerational reproduction of poverty. This makes it necessary to consider social protection policies and income transfers that prioritize this population group (see figure I.26).

The ethnic or racial origin of the population is another crucial determinant of people’s chances of being poor. In 2022, the poverty rate of the self-identified indigenous population (43.1%) was more than double that of the non-indigenous and non-Afrodescendent population (21.4%). A subset of countries with information available on the Afrodescendent population register similar gaps, translating into a poverty rate that is 1.2 times as high as that of the non-indigenous and non-Afrodescendent population at the regional level and twice as high in certain countries such as Brazil and Uruguay (see figure I.24).

Figure I.26

Latin America (15 countries): ratios between the poverty rates of people aged 0 to 17 and those aged 18 and over, 2014 and 2022

(Index values)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The countries are ranked by the ratio between age groups in the most recent period. The 2014 figures are for 2013 in Chile. The 2022 figures are for 2021 in Colombia, Honduras and the Plurinational State of Bolivia.

a Simple average.

2. The employment and occupational participation of the low-income strata remains very fragile

The processes of change experienced by Latin American societies in recent decades highlight the need for a more comprehensive view of economic and social stratification in the region’s countries that is not limited to analysis of the top and bottom of the distribution and that gives an insight into the impact of these changes on the social and economic structure. More needs to be done to conceptualize and measure the middle classes, taking into account the lack of statistical information on these segments but also their importance in the effort to strengthen democracy and construct social and fiscal covenants that can ensure financial sustainability and create the conditions for progress with basic economic, social and cultural rights (ECLAC, 2019 and 2022a).

In view of the multidimensionality of well-being and the wide variety of perspectives used to approach it, the different social strata and classes have been measured by examining different aspects of living conditions, among them income, occupation, education levels, spending and consumption patterns, different types of capital (cultural, social) and even subjective perceptions.[23] These aspects have been supplemented by analysis of various structural factors, such as disparities related to gender, ethnicity or race and position in the life cycle (Martínez and others, 2022).

Given the difficulty of obtaining classifications based on labour market status that are comparable across countries, and considering that income provides a simple and comparable proxy for well-being,[24] ECLAC (2019 and 2022a) has been using a classification of the Latin American population by per capita household income strata whereby the population is grouped on the basis of thresholds set with reference to the absolute poverty line. Three broad strata have been identified, low-income, middle-income and high-income, in turn containing subgroups.[25]

The application of this stratification to 18 countries of the region between 2002 and 2022 shows substantial growth in the middle-income strata (the sum of the lower-middle, intermediate-middle and upper-middle-income population) as a share of the regional population. The middle-income strata went from being less than a third of Latin America’s population in 2002 (27%) to 41.8% in 2022. The low-income population declined from 70.7% in 2002 to 54.9% in 2022, mainly because of the fall in non-extreme poverty (see figure I.27).

Figure I.27

Latin America (18 countries):a evolution of the population by per capita income strata, 2002–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

The middle strata grew at a much faster rate between 2002 and 2008, a period that coincided with the commodity boom and the strengthening of social protection systems in the region, than between 2008 and 2019. In the first period, the size of the middle strata as a share of the total increased at a rate of 6% per year, while in the second time period the figure was 1.1% per year. The contraction in the income of the population during the first year of the pandemic led to a sharp decline in the middle strata, whose share fell by 6.3% in 2020. In 2021, the population share of the middle strata remained almost unchanged, and in 2022 it strongly resumed its upward trend, increasing by 7.8%, with the largest relative increases in the upper-middle and intermediate-middle income strata, in that order.

The stratification of the population by household income provides a valuable context for understanding the forms of labour inclusion and exclusion in the region, which is the central theme of this edition of the Social Panorama. To analyse the link between strata and labour inclusion, a classification of the population by employment and occupational status is proposed.[26] The classification distinguishes those employed in low-productivity activities,[27] a fundamental issue for a region characterized by a highly heterogeneous production structure, and includes those engaged in unpaid work, an activity in which women are overrepresented owing to the sexual division of labour[28] (see chapter III for more details).

In the region, 41.2% of the population in the low-income strata are engaged on low-productivity activities.[29] Among those employed in low-productivity activities who belong to the low-income strata, own-account workers represent the largest share (22.1%), followed by employees (19.1%). People outside the labour force and the unemployed represent 35.2% of the low-income strata, with the former group accounting for much the larger share. Those engaged in medium- or high-productivity activities account for 23.6%, which shows that participation in the formal sector is not always enough to lift people out of the low-income strata (see figure I.28).

In the intermediate strata (people with medium-low and intermediate-middle incomes), 49.6% are employed in medium- or high-productivity activities. Non-professional employees are the main occupational category (30.5%) in these strata, followed by professional and technical workers in medium- and high-productivity activities (19.1%). Those in low-productivity activities account for 34.7% of the intermediate strata, while the unemployed and those outside the labour force account for 15.7%.

Figure I.28

Latin America (17 countries):a population grouped by occupation and by per capita income strata,b ages 15–59, around 2022c

(Percentages within the strata)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

b Low-income strata: people living in extreme poverty, people living in non-extreme poverty and non-poor people with low incomes. Intermediate-income strata: lower-middle and intermediate-middle incomes. Upper-middle and high-income strata: upper-middle and high incomes. The strata are constructed on the basis of per capita household income. The total area of each of the strata is not an accurate representation of size.

c Figures for 2022, except in the cases of Colombia and the Plurinational State of Bolivia (2021), Honduras (2019), Guatemala and Nicaragua (2014). The Bolivarian Republic of Venezuela is not included.

d Includes medium- and high-productivity employers.

e Aggregates all occupational groups other than those engaged in medium- or high-productivity activities.

The upper-middle and high-income strata are the most homogeneous in their composition by occupational groups. Professionals in medium- and high-productivity occupations make up the majority of those in these strata (53.3%). Non-professional employees are a distant second (16.1%). Summing the two categories together, those employed in medium- and high-productivity activities account for almost 70% of the upper-middle and high strata.

The relationship between employment and occupational status and the socioeconomic strata is not identical for men and women. Among men, poor consumption opportunities are more closely linked to poor job quality. In the lower strata, 49.5% of men are employed in low-productivity jobs, 2.1 times the incidence in the upper-middle and high-income strata (23.1%). For women, the ratio is 1.8 (34.1% in low-productivity jobs in the lower strata compared to 19.2% in the upper-middle and high strata). Thus, the gradient of employment in low-productivity activities by income strata is steeper for men than for women (see figure I.29).

Figure I.29

Latin America (17 countries):a occupational groups by per capita income strata and sex,

population aged 15–59, around 2022b

(Percentages within the strata)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

b Figures for 2022, except in the cases of Colombia and the Plurinational State of Bolivia (2021), Honduras (2019), Guatemala and Nicaragua (2014).

c Includes medium- and high-productivity employers.

d Includes employees and own-account workers engaged in low-productivity activities in urban areas and own-account workers in rural areas.

Women are excluded from the paid labour force to a much greater extent than men, especially in the lower-income strata (see chapter III for more details on women’s inclusion in or exclusion from the labour market). In the low-income strata, 34.6 million women are not in the paid labour market, equivalent to 41.4% of all women in those strata. The rate is lower in the middle strata, but still high (13.1 million women do not participate in the paid labour market, equivalent to 20.1% of the total), and the proportion in the upper-middle and high strata is 12.5%. In the male population, those outside the labour force represent only 8.5% of the lower strata, 3.8% of the middle strata and 2.9% of the upper stratum.

Thus, inclusion in and exclusion from paid work, both in the present and in the past, have a major impact on a household’s consumption opportunities. The situation where all potential earners in a household receive earnings or pensions is substantially less prevalent in the strata with the lowest consumption capacity (see figure I.30). Among those in extreme poverty, for example, the proportion of people living in households where all potential earners have labour or pension income is only 9.9% (3.9 million out of 39.4 million people). Among those in non-extreme poverty and those who have low incomes but are not poor, the figures are 15.3% and 25.4%, respectively. Only with the intermediate-income strata does the proportion rise to close to 50%, while in the upper-middle and high-income strata it increases to 68.7%.

Figure I.30

Latin America (17 countries):a recipients of earnings or pensions in the householdb by income strata, population aged 15 to 59, around 2022c

(Millions of people and percentages within the strata)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

b All household members aged 15 and over are treated as potential recipients of labour or pension income.

c Figures for 2022, except in the cases of Colombia and the Plurinational State of Bolivia (2021), Honduras (2019), Guatemala and Nicaragua (2014).

The incidence of households with no recipients of earnings or pensions is highest among those living in extreme poverty (30.1%), while the category “some potential recipients have income” exhibits the highest levels among those living in non-extreme poverty (78.1%) and then among the low-income non-poor (72%). These data reinforce the need to design initiatives to promote the incorporation of women into the paid labour market (see chapters II and III for a more in-depth analysis of this issue), especially in the low-income strata, and most urgently in the case of those living in poverty, but also in the other groups.

A final exercise was to compare the incidence of the various occupational situations within the different strata, grouping countries by per capita GDP. The rationale for this exploration was that aggregate regional-level analyses might mask differences associated with the heterogeneity of the countries’ development levels. Although GDP is an imperfect proxy for economic and social development,[30] it is a measure that is widely available, comparable and fairly well correlated with other development indicators,[31] and that allows countries to be ranked.

This analysis showed that, although employment in low-productivity activities continues to be much more prevalent in the low-income strata, its incidence in all strata tends to fall as countries’ per capita GDP rises (see figure I.31). This result was to be expected, since urbanization,[32] the creation of infrastructure, the expansion of financing channels, the spread of technology and increased education among the population, among many other factors associated with higher per capita GDP levels, should all tend to reduce employment in low-productivity activities, while higher productivity can also be growth-promoting.[33]

Figure I.31

Latin America (17 countries): occupational situations by income strata and country groups,a population aged 15–59, around 2022b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG) and CEPALSTAT [online database] https://statistics.cepal.org/portal/cepalstat/index.html?lang=en.

a Group of countries with low GDP (less than US$ 9,000 per capita in constant dollars): Colombia, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Nicaragua, Paraguay, Peru and the Plurinational State of Bolivia. Group of countries with medium GDP (between US$ 9,000 and US$ 12,500 per capita in constant dollars): Argentina, Brazil and Mexico. Group of countries with high GDP (over US$ 12,500 per capita in constant dollars): Chile, Costa Rica, Panama and Uruguay.

b Figures for 2022, except in the cases of Colombia and the Plurinational State of Bolivia (2021), Honduras (2019), Guatemala and Nicaragua (2014).

Although the cross-sectional information does not allow conclusions to be drawn about trends over time, it may be suggested that, as countries attain higher levels of economic growth, employment in low-productivity activities could be progressively replaced by lack of paid employment as the main cause of income insufficiency in the low-income strata. In countries with low per capita GDP, the most common situation in the low-income strata is employment in low-productivity activities (50.4%), ahead of unemployment and non-participation in the paid workforce (33%). In countries with medium per capita GDP, the two categories account for very similar shares in the low-income strata. Conversely, for those in the low-income strata in countries with high per capita GDP, the ratio is the reverse of that in the countries with low per capita GDP: taken together, non-participation in the labour force and unemployment outweigh employment in low-productivity activities by 11.5 percentage points (see figure I.31).

In turn, the incidence of medium- or high-productivity professionals in the high-income stratum tends to increase with countries’ per capita GDP. In countries with low per capita GDP, 49.6% of people in the upper-middle and high strata are professional and technical workers. This proportion rises to 53.1% in countries with medium GDP and peaks at 61.1% in countries with high GDP. In turn, the share of non-professional employees with medium or high productivity is largest in the intermediate-income strata, and this incidence increases with countries’ per capita GDP.

C. Final comments

Recent changes in the distribution and level of household income reflect the ongoing labour market recovery following the COVID-19 pandemic. Rising participation and employment and falling unemployment have driven up earnings and household incomes in most Latin American countries, although inflation remains high and has hit the most disadvantaged households the hardest.

The Gini index of inequality has fallen below its levels of 2019, prior to the pandemic, in 9 of 12 countries in the region. Despite this progress, the top decile receives 21 times as much income as the lowest-income decile, indicating very high inequality. Wealth is even more concentrated than income: in 2021, the assets of the region’s 105 billionaires represented almost 4% of the wealth of the entire population and surpassed their levels of 2019 and 2020.

In 2022, the average incidence of poverty in the region fell back below pre-pandemic levels, although it remained above its 2019 levels in more than half the countries. Earnings played a preponderant role in this outcome and in the reduction of inequality. Thus, the prospects of sustainably overcoming poverty are heavily conditioned by labour inclusion, the central theme of this edition of the Social Panorama. The majority of the population in the low-income strata, including the low-income non-poor, are engaged in low-productivity activities or do not participate in employment, a situation that disproportionately affects women.

On a longer-term perspective, the favourable trends of 2022 are not sufficient for substantial progress to be made towards the poverty eradication and reduction of inequality committed to in the context of the 2030 Agenda for Sustainable Development. In practice, the region continues to be characterized by large structural gaps that hinder inclusive economic and social development. Income inequality remains very high and has declined only slowly, with the pace of progress being slacker in recent years than between 2002 and 2014. Poverty figures, meanwhile, have not progressed at all compared to the beginning and end of the last decade. In the case of extreme poverty, the latest figures show that the number of people in this situation is more than 20 million higher than 12 years ago.

For substantial progress to be made in reducing inequality and eradicating poverty, then, it is especially important to tackle the gaps now existing in the labour market by implementing labour inclusion policies that address not only the great inequality of the incomes generated in this market, but also the level of earnings, which can be inadequate to meet essential needs (see chapter II). Although public transfers play an important role in reducing inequalities and providing emergency social protection so that people can cope with income shortfalls and economic crises, higher levels of development that are sustainable in the medium term can only be achieved by improving labour inclusion through access to quality jobs and the reduction of structural gaps in the labour market.

Bibliography

Abramo, L. (2022), “Policies to address the challenges of existing and new forms of informality in Latin America”, Social Policy series, No. 240 (LC/TS.2021/137), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Acciari, P., F. Alvaredo and S. Morelli (2021), “The concentration of personal wealth in Italy 1995–2016”, Working Paper, No. 2021/14, World Inequality Lab.

Alvaredo, F., B. Garbinti and T. Piketty (2017), “On the share of inheritance in aggregate wealth: Europe and the USA, 1900–2010”, Economica, vol. 84, No. 334, April.

Alvaredo, F. and others (2022), “Desigualdad del ingreso en la República Dominicana 2012-2019: una revisión a partir de la combinación de fuentes de datos”, Project Documents (LC/TS.2022/75), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Bajard, F. and others (2022), “Global wealth inequality on WID.world: estimates and imputations”, Technical Note, No. 2021/16, World Inequality Lab.

Chancel, L. and others (coords.) (2022), World Inequality Report 2022, World Inequality Lab [online] https://wir2022.wid.world/download/.

Collins, C. and J. Hoxie (2015), Billionaire Bonanza Report: the Forbes 400… and the Rest of Us, Washington, D.C., Institute for Policy Studies (IPES).

Corak, M. (2013), “Income inequality, equality of opportunity, and intergenerational mobility”, Journal of Economic Perspectives, vol. 27, No. 3.

Credit Suisse Research Institute (2022), Global Wealth Databook 2022: Leading Perspectives to Navigate the Future [online] https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html.

ECLAC (Economic Commission for Latin America and the Caribbean) (2023), Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago.

____(2022a), Social Panorama of Latin America, 2021 (LC/PUB.2021/17-P), Santiago.

____(2022b), Towards transformation of the development model in Latin America and the Caribbean: production, inclusion and sustainability (LC/SES.39/3-P), Santiago.

____(2019), Social Panorama of Latin America, 2019 (LC/PUB.2019/22-P/Rev.1), Santiago.

____(2018a), Income poverty measurement: updated methodology and results, ECLAC Methodologies, No. 2 (LC/PUB.2018/22-P), Santiago.

____(2018b), The Inefficiency of Inequality (LC/SES.37/3-P), Santiago.

____(2012), Social Panorama of Latin America, 2011 (LC/G.2514-P), Santiago.

ECLAC/ILO (Economic Commission for Latin America and the Caribbean/International Labour Organization) (2023), “Towards the creation of better jobs in the post-pandemic era”, Employment Situation in Latin America and the Caribbean, No. 28 (LC/TS.2023/70), Santiago.

Fisher, J. and others (2016), “Inequality and mobility using income, consumption, and wealth for the same individuals”, RSF: Russell Sage Foundation Journal of Social Sciences, vol. 2, No. 6, October.

Freund, C. and S. Olivier (2016), “The origins of the superrich: the billionaire characteristics database”, Working Paper Series, No. WP16-1, Peterson Institute for International Economics.

Fuentes, A. (2022), “Desigualdad del ingreso en la República Dominicana 2012-2019: resumen metodológico y resultados comparados”, Project Documents (LC/TS.2022/155), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Jones, F. (2023), “Population and development in the Caribbean (2018–2023): accelerating implementation of the Montevideo Consensus”, forthcoming.

Martínez, R. and others (2022), “Estratificación y clases sociales en América Latina: dinámicas y características en las dos primeras décadas del siglo XXI”, Project Documents (LC/TS.2022/214), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

OECD (Organisation for Economic Co-operation and Development) (2018), A Broken Social Elevator? How to Promote Social Mobility, Paris, OECD Publishing.

Our World in Data (2023), “Self-reported life satisfaction vs. GDP per capita, 2022” [online] https://ourworldindata.org/grapher/gdp-vs-happiness.

____(2022), “Human Development Index vs. GDP per capita, 2021” [online] https://ourworldindata.org/grapher/human-development-index-vs-gdp-per-capita.

Palma, J. G. (2011), “Homogeneous middles vs. heterogeneous tails, and the end of the ‘inverted‐U’: it’s all about the share of the rich”, Development and Change, vol. 42, No. 1, January.

Palomino, J. and others (2022), “Wealth inequality, intergenerational transfers, and family background”, Oxford Economic Papers, vol. 74, No. 3, July.

Piketty, T. (2011), “On the long-run evolution of inheritance: France 1820‒2050”, The Quarterly Journal of Economics, vol. 126, August.

Piketty, T. and G. Zucman (2015), “Wealth and inheritance in the long run”, Handbook of Income Distribution, vol. 2, A. B. Atkinson and F. Bourguignon (eds.), Elsevier.

Portes, A. and K. Hoffman (2003), “Latin American class structures: their composition and change during the neoliberal era”, Latin American Research Review, vol. 38, No. 1, February.

Rawls, J. (1971), A Theory of Justice, Cambridge, Massachusetts, Harvard University Press.

Sen, A. (1992), Inequality Reexamined, Cambridge, Massachusetts, Harvard University Press.

Solís, P., E. Chávez Molina and D. Cobos (2019), “Class structure, labor market heterogeneity, and living conditions in Latin America”, Latin American Research Review, vol. 54, No. 4, December.

Task Justice Network (2023), “Financial secrecy index 2022” [online] https://fsi.taxjustice.net/.

Waldenström, D., A. Adermon and M. Lindahl (2016), “Intergenerational wealth mobility and the role of inheritance: Evidence from multiple generations”, CEPR Discussion Paper, No. 11456, Paris and London, Centre for Economic Policy Research (CEPR).

World Bank (2023), Macro Poverty Outlook, Washington, D.C., April.

Yang, X. and P. Zhou (2022), “Wealth inequality and social mobility: a simulation-based modelling approach”, Journal of Economic Behavior & Organization, vol. 196, April.

Zucman, G. (2019), “Global wealth inequality”, Annual Review of Economics, vol. 11, August.

Annex I.A1

Table I.A1.1

Latin America (18 countries): household surveys used to estimate inequality and poverty

Country

Survey

Geographical coverage

Years

Survey period

Argentina

Permanent Household Survey (EPH)

Urban areas

2000–2017

Fourth quarter

Permanent Household Survey (EPH)

Urban areas

2018–2022

Second half

Bolivia (Plurinational State of)

Household Survey

National

2002

November

to December

Continuous Household Survey (ECH)

National

2004–2021

November

Brazil

National Household Survey (PNAD)

National

2001–2015

September

Continuous National Household Survey (PNAD Contínua)

National

2016–2022

Annual

Chile

National Socioeconomic Survey (CASEN)

National

2003–2022

November

to January

Colombia

Continuous Household Survey (ECH)

National

2002–2008

Annual

Large Integrated Household Survey (GEIH)

National

2008–2022

Annual

Costa Rica

Multipurpose Household Survey

National

2000–2009

July

National Household Survey (ENAHO)

National

2010–2022

July

Dominican Republic

National Labour Force Survey (ENFT)

National

2001–2015

October

Continuous National Labour Force Survey (ENCFT)

National

2016–2022

Annual

Ecuador

National Survey on Employment, Unemployment and Underemployment (ENEMDU) in urban and rural areas

National

2001–2022

2021 and 2022

December

Annual

El Salvador

Multipurpose Household Survey

National

2001–2022

Annual

Guatemala

National Survey of Living Conditions (ENCOVI)

National

2002, 2006 and 2014

Different periods

Honduras

Permanent Multipurpose Household Survey

National

2001–2019

May or June

Mexico

National Household Income and Expenditure Survey (ENIGH)

National

2002–2006

Third quarter

Socioeconomic Conditions Module of ENIGH (MCS-ENIGH)

National

2008–2014

August to November

National Household Income and Expenditure Survey (ENIGH) New Series

National

2016–2022

August to November

Nicaragua

National Household Survey on the Measurement

of Living Standards

National

2005, 2009 and 2014

Different periods

Panama

Labour Market Survey

National

2001–2013

August

Multipurpose Survey

National

2014–2019, 2022

March

Labour Market Survey

National

2021

October

Paraguay

Integrated Household Survey

National

2001 and 2002

November

to December

Permanent Household Survey

National

2003–2016

October to December

Permanent Household Survey

National

2017–2022

Annual

Peru

National Household Survey - Living Conditions and Poverty

National

2001–2003

Fourth quarter

National Household Survey - Living Conditions and Poverty

National

2004–2022

Annual

Uruguay

Continuous Household Survey (ECH)

Urban areas

2001–2005

Annual

Continuous Household Survey (ECH)

National

2007–2020, 2022

Annual

Continuous Household Survey (ECH)

National

2021

Second half

Venezuela (Bolivarian Republic of)

Household Sample Survey

National

2001–2014

Second half

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Table I.A1.2

Latin America (15 countries): extreme poverty and poverty rates according to estimates by the Economic Commission for Latin America and the Caribbean (ECLAC) and official country estimates, 2019–2022a

(Percentages)

ECLAC estimates

Extreme poverty

Total poverty

2019

2020

2021

2022

2019

2020

2021

2022

Argentinab

3.9

6.1

4.0

3.9

26.0

33.0

28.3

30.1

Bolivia (Plurinational State of)

12.0

13.5

9.9

…

30.9

32.3

29.0

…

Brazilc

5.8

5.1

8.3

5.3

20.2

18.4

24.3

19.5

Chile

…

4.5

…

2.1

…

13.9

…

8.1

Colombia

12.4

19.2

16.8d

16.9d

30.4

39.8

36.6d

34.5d

Costa Rica

3.4

4.0

3.7

3.3

16.5

19.4

17.3

16.6

Dominican Republic

3.9

5.6

5.2

5.1

19.0

21.8

22.5

20.4

Ecuadore

7.6

10.8

7.6

6.9

25.7

30.6

28.5

25.7

El Salvador

5.6

8.3

8.4

8.7

30.4

30.7

30.3

29.8

Honduras

20.0

…

34.4

…

52.3

…

67.8

…

Mexico

…

9.2

…

6.2

…

37.4

…

28.6

Panama

6.6

…

5.7

6.5

14.6

…

15.6

14.3

Paraguay

6.2

6.0

6.0

7.9

19.4

22.3

20.9

21.1

Peru

3.0

8.6

3.9

3.3

15.4

28.4

18.6

17.2

Uruguay

0.1

0.3

0.1

0.3

3.0

5.0

4.8

4.3

Official country estimates

Extreme poverty

Total poverty

2019

2020

2021

2022

2019

2020

2021

2022

Argentinab

8.0

10.5

8.2

8.1

35.5

42.0

37.3

39.2

Bolivia (Plurinational State of)

12.9

13.7

11.1

...

37.2

39.0

36.4

...

Brazilc

6.8

5.7

8.4

...

25.9

24.1

29.4

...

Chile

...

4.3

...

2.0

...

10.7

...

6.5

Colombia

9.6

15.1

13.7d

13.8d

35.7

42.5

39.7d

36.6d

Costa Ricaf

5.8

7.0

6.3

6.4

21.0

26.2

23.0

23.0

Dominican Republic

2.7

3.5

3.1

3.0

20.9

23.4

23.9

21.8

Ecuadore

8.9

15.4

10.5

8.3

25.0

33.0

27.7

25.2

El Salvadorf

4.5

8.6

7.8

...

22.8

26.2

24.6

...

Hondurasf

25.2

...

32.5

...

48.0

...

59.2

...

Mexicog

...

17.2

...

12.1

...

52.8

...

43.5

Panama

10.0

...

...

...

21.5

...

...

...

Paraguay

4.0

3.9

3.9

5.6

23.5

26.9

26.9

24.7

Peru

2.9

5.1

4.1

5.0

20.2

30.1

25.9

27.5

Uruguay

0.2

0.4

0.3

0.3

8.8

11.6

10.6

10.0

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG), official figures and, for Brazil, Brazilian Institute of Geography and Statistics (IBGE), “Síntese de indicadores sociais: uma análise das condições de vida da população brasileira 2022”, Estudos e Pesquisas, No. 49, Rio de Janeiro, 2022.

a Countries for which ECLAC poverty estimates are available from 2019 onward.

b Urban areas.

c Brazil does not have an official poverty estimate. The data are estimates made by the Brazilian Institute of Geography and Statistics (IBGE), as indicated in the source, on the basis of the thresholds used by the World Bank for low- and lower-middle-income countries.

d The 2021 and 2022 figures are from a new series based on the 2018 National Population and Housing Census sampling frame and are not comparable with those of earlier years.

e The ECLAC measure uses the cumulative annual sample since 2021. Official figures are based on the sample for December each year.

f Official national measurement reported as percentages of households.

g Mexico’s official figures represent a multidimensional measure of poverty. Accordingly, the estimates published by the National Council for the Evaluation of Social Development Policy (CONEVAL), denominated “population below the minimum welfare line” and “population below the welfare line”, are taken as an unofficial national benchmark and equated here to “extreme poverty” and “total poverty”, respectively.

Table I.A1.3

Latin America (18 countries): poverty and extreme poverty indicators, 2014–2022a

(Units of the relevant indices)

Country

Year

Povertyb

Extreme poverty

Households

Individuals

Households

Individuals

Headcount (H)

Headcount (H)

Gap

(PG)

Gap squared (FGT2)

Headcount (H)

Headcount (H)

Gap

(PG)

Gap squared (FGT2)

Argentinac

2014

17.5

24.9

7.2

3.4

3.0

3.3

1.4

1.0

2019

18.4

26.0

8.0

4.0

3.2

3.9

1.6

1.1

2020

24.3

33.0

10.8

5.7

5.1

6.1

2.6

1.8

2021

21.2

28.3

8.8

4.4

3.5

4.0

2.0

1.5

2022

22.6

30.1

8.8

4.2

3.5

3.8

1.7

1.1

Bolivia (Plurinational State of)

2014

28.6

33.7

13.9

8.1

12.5

14.9

6.5

4.0

2019

24.8

30.9

11.2

6.0

9.2

12.0

4.6

2.6

2020

27.4

32.3

12.7

7.2

11.0

13.5

5.6

3.3

2021

23.1

29.0

10.2

5.3

7.5

9.9

3.9

2.1

2022

…

...

...

...

...

...

...

...

Brazil

2014d

12.6

16.5

5.5

2.9

3.0

3.3

1.4

1.0

2019

16.0

20.2

7.8

4.6

5.3

5.8

2.7

1.9

2020

14.5

18.4

7.0

4.3

4.8

5.1

2.8

2.3

2021

19.7

24.3

9.9

6.1

7.5

8.3

4.0

2.9

2022

15.5

19.5

7.1

4.0

4.8

5.3

2.4

1.8

Chile

2013

12.8

16.2

4.8

2.3

1.9

2.0

0.9

0.6

2015

10.7

13.7

3.9

1.8

1.6

1.8

0.8

0.5

2017

8.4

10.7

3.0

1.5

1.5

1.4

0.7

0.6

2020

12.4

14.2

5.8

3.8

4.9

4.5

2.8

2.2

2022

6.9

8.1

2.9

1.8

2.5

2.1

1.2

1.0

Colombia

2014

24.8

29.9

11.7

6.5

9.6

11.2

4.3

2.5

2019

24.9

30.4

12.1

6.8

10.4

12.4

4.8

2.8

2020

34.0

39.8

18.3

11.7

16.9

19.2

9.1

6.2

2021e

30.0

36.6

15.6

9.3

13.7

16.8

7.1

4.3

2022e

28.6

34.5

14.4

8.4

14.3

16.9

6.9

4.1

Costa Rica

2014

14.4

17.5

6.4

3.5

3.7

4.1

1.9

1.2

2019

13.0

16.5

5.6

2.9

2.8

3.4

1.3

0.8

2020

15.4

19.4

6.8

3.7

3.3

4.0

1.8

1.3

2021

13.5

17.3

5.9

3.1

3.0

3.7

1.5

0.9

2022

12.8

16.6

5.6

2.9

2.6

3.3

1.3

0.8

Dominican Republic

2014h

27.0

32.9

11.5

5.6

7.4

9.7

2.8

1.3

2019

14.0

19.0

5.4

2.3

2.7

3.9

1.0

0.5

2020

16.1

21.8

6.5

2.9

4.0

5.6

1.6

0.8

2021

16.8

22.5

6.4

2.7

3.7

5.2

1.4

0.6

2022

15.0

20.4

5.8

2.5

3.6

5.1

1.3

0.5

Ecuador

2014

19.2

23.4

7.0

3.1

4.7

5.9

1.7

0.8

2019

19.4

25.7

8.1

3.7

5.4

7.6

2.1

1.0

2020

23.8

30.6

10.5

5.1

7.6

10.8

3.3

1.5

2021f

22.7

28.5

8.7

3.9

5.7

7.6

2.0

0.9

2022f

20.3

25.7

7.8

3.5

5.3

6.9

1.9

0.9

El Salvador

2014

38.0

44.5

16.4

8.1

9.1

11.7

3.3

1.3

2019

25.3

30.4

9.6

4.3

4.4

5.6

1.4

0.6

2020

27.2

30.7

11.3

6.2

7.8

8.3

3.4

2.1

2021

26.4

30.3

11.4

6.3

7.6

8.4

3.6

2.3

2022

26.5

29.8

11.2

6.2

8.1

8.7

3.6

2.3

Guatemala

2014

43.1

50.5

22.4

13.0

11.8

15.4

5.3

2.7

Honduras

2014

50.0

55.3

22.9

12.3

17.1

19.2

5.5

2.5

2018

51.1

55.7

23.6

13.2

17.3

19.4

6.4

3.3

2019

48.0

52.3

23.7

13.9

18.9

20.0

7.0

4.0

2021

63.9

67.8

36.6

25.0

31.8

34.4

17.0

11.8

Mexico

2014g

67.8

45.2

17.6

9.3

10.2

13.0

4.2

2.0

2016

36.6

37.6

12.9

6.2

6.3

8.4

2.4

1.1

2018

25.0

35.5

11.8

5.6

5.8

7.7

2.2

1.0

2020

31.8

37.4

12.9

6.3

6.9

9.2

2.7

1.3

2022

34.4

28.6

8.9

4.1

4.4

6.2

1.7

0.8

Nicaragua

2014

17.0

46.3

18.7

10.2

16.1

18.3

6.6

3.5

Panama

2014

11.8

18.5

7.1

3.8

5.2

8.0

2.9

1.5

2018

10.6

14.6

5.7

3.2

4.3

6.8

2.5

1.3

2019

10.4

14.6

5.6

3.0

4.4

6.6

2.3

1.2

2021

11.3

15.6

5.4

2.7

3.8

5.7

1.9

0.9

2022

9.9

14.3

5.5

3.0

4.2

6.5

2.3

1.2

Paraguay

2014

18.5

22.3

8.2

4.2

6.3

7.7

2.4

1.2

2019

16.2

19.4

6.4

3.0

5.0

6.2

1.5

0.6

2020

18.5

22.3

7.1

3.2

5.0

6.0

1.6

0.7

2021

17.0

20.9

6.5

2.9

4.9

6.0

1.5

0.7

2022

18.7

21.1

7.5

3.9

7.1

7.9

2.6

1.4

Peru

2014

16.7

19.5

6.4

3.1

4.2

5.1

1.5

0.6

2019

13.1

15.4

4.6

2.0

2.4

3.0

0.8

0.4

2020

23.9

28.4

10.8

5.9

7.0

8.6

3.3

1.9

2021

15.7

18.6

5.7

2.6

3.2

3.9

1.2

0.6

2022

14.4

17.2

5.1

2.3

2.6

3.3

1.0

0.5

Uruguay

2014

2.6

4.5

0.9

0.3

0.2

0.2

0.1

0.0

2019

1.8

3.0

0.6

0.2

0.1

0.1

0.1

0.1

2020

3.1

5.0

1.0

0.3

0.3

0.3

0.1

0.1

2021

3.1

4.8

0.9

0.3

0.2

0.1

0.1

0.1

2022

2.7

4.3

0.9

0.3

0.2

0.3

0.1

0.1

Venezuela (Bolivarian Republic of)

2014

24.0

28.3

9.3

4.6

10.3

12.0

3.7

2.0

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a H = headcount index; PG = poverty gap; FGT2 = Foster, Greer and Thorbecke index squared.

b Includes individuals and households living in extreme poverty.

c Urban total.

d The 2014 figure is based on the National Household Survey (PNAD) and is not comparable with those of later years, which are based on the Continuous National Household Survey (PNAD Contínua).

e The 2021 and 2022 figures are from a new series based on the 2018 National Population and Housing Census sampling frame and are not comparable with those of previous years.

f The 2021 and 2022 figures are for the full year (data prior to December).

g The 2014 figure is not comparable with those of later years, which are based on a new series of the National Household Income and Expenditure Survey (ENIGH).

h The 2014 figure is based on the National Labour Force Survey (ENFT) and is not comparable with those of later years, which are based on the Continuous National Labour Force Survey (ENCFT).

Table I.A1.4

Latin America (18 countries): extreme poverty and poverty lines, 2014–2022

(National currency and current dollars)

Country

Year

National currency

Exchange ratea

Dollars

Urban areas

Rural areas

Urban areas

Rural areas

Extreme poverty

Poverty

Extreme poverty

Poverty

Extreme poverty

Poverty

Extreme poverty

Poverty

Argentina

2014

900.0

2 061.1

…

…

8.1

111.4

255.1

…

…

2019

3 786.3

9 132.0

…

…

48.2

78.6

189.7

…

…

2020

5 327.0

12 770.5

…

…

70.5

75.5

181.0

…

…

2021

8 143.4

19 350.5

…

…

95.0

85.7

203.7

…

…

2022

15 187.5

35 644.0

…

…

130.6

116.3

272.9

…

…

Bolivia (Plurinational State of)

2014

375.0

746.6

341.5

539.1

6.9

54.3

108.1

49.4

78.0

2019

468.0

878.0

426.0

644.0

6.9

67.7

127.1

61.7

93.2

2020

443.0

859.0

403.0

625.0

6.9

64.1

124.3

58.3

90.4

2021

446.0

866.0

406.0

629.0

6.9

64.5

125.3

58.8

91.0

2022

…

…

…

…

…

…

…

…

…

Brazil

2014

147.3

333.8

121.0

240.9

2.3

62.7

142.0

51.5

102.5

2019

192.6

437.7

158.2

315.8

3.9

48.9

111.1

40.2

80.2

2020

210.0

459.1

172.6

332.7

5.2

40.7

89.0

33.4

64.5

2021

235.9

503.2

193.8

365.6

5.4

43.8

93.4

36.0

67.8

2022

264.2

555.1

217.1

404.0

5.2

51.2

107.6

42.1

78.3

Chile

2013

42 049.0

97 665.0

38 275.0

71 862.0

495.0

84.9

197.2

77.3

145.1

2015

48 246.0

108 305.0

43 917.0

80 186.0

654.0

73.8

165.6

67.1

122.6

2017

51 309.0

113 958.0

46 705.0

84 538.0

649.0

79.1

175.6

72.0

130.3

2020

57 572.0

124 593.0

52 406.0

92 879.0

793.0

72.6

157.2

66.1

117.2

2022

73 348.0

152 398.0

66 766.0

114 503.0

873.0

84.0

174.5

76.4

131.1

Colombia

2014

117 571.0

242 075.0

101 735.0

162 802.0

2 002.0

58.7

120.9

50.8

81.3

2019

154 229.0

308 841.0

133 455.0

209 290.0

3 282.0

47.0

94.1

40.7

63.8

2020

162 634.0

320 565.0

140 728.0

218 191.0

3 693.0

44.0

86.8

38.1

59.1

2021

175 838.0

337 100.0

152 154.0

231 250.0

3 744.0

47.0

90.0

40.6

61.8

2022

215 286.0

387 291.0

186 288.0

270 654.0

4 256.0

50.6

91.0

43.8

63.6

Costa Rica

2014

35 085.0

80 709.0

31 682.0

66 736.0

538.3

65.2

149.9

58.8

124.0

2019

37 357.0

85 794.0

33 734.0

70 949.0

587.3

63.6

146.1

57.4

120.8

2020

37 119.0

85 562.0

33 519.0

70 738.0

584.9

63.5

146.3

57.3

120.9

2021

37 886.0

87 318.0

34 211.0

72 191.0

620.8

61.0

140.7

55.1

116.3

2022

43 927.0

97 442.0

39 666.0

80 783.0

647.1

67.9

150.6

61.3

124.8

Dominican Republic

2014

2 354.1

4 611.6

2 281.2

3 944.7

43.5

54.1

105.9

52.4

90.6

2019

2 791.2

5 096.9

2 704.0

4 402.9

51.3

54.4

99.4

52.7

85.8

2020

2 967.1

5 327.2

2 874.4

4 613.3

56.5

52.5

94.3

50.9

81.6

2021

3 255.6

5 788.3

3 153.8

5 019.7

57.2

56.9

101.2

55.1

87.7

2022

3 607.5

6 346.9

3 494.9

5 513.2

55.1

65.4

115.1

63.4

100.0

Ecuador

2014

54.5

100.2

47.9

79.7

1.0

54.5

100.2

47.9

79.7

2019

57.9

106.5

50.8

84.7

1.0

57.9

106.5

50.8

84.7

2020

58.3

106.6

51.2

84.9

1.0

58.3

106.6

51.2

84.9

2021

57.8

106.1

50.7

84.5

1.0

57.8

106.1

50.7

84.5

2022

60.5

110.2

53.0

87.8

1.0

60.5

110.2

53.0

87.8

El Salvador

2014

50.5

108.8

44.9

92.3

1.0

50.5

108.8

44.9

92.3

2019

52.0

111.0

46.3

94.3

1.0

52.0

111.0

46.3

94.3

2020

52.9

111.2

47.1

94.4

1.0

52.9

111.2

47.1

94.4

2021

53.8

114.1

47.9

96.9

1.0

53.8

114.1

47.9

96.9

2022

60.0

123.6

53.5

105.1

1.0

60.0

123.6

53.5

105.1

Guatemala

2014

295.3

725.7

254.1

630.4

7.7

38.2

93.9

32.9

81.6

Honduras

2014

1 075.0

2 301.9

859.9

1 790.1

21.0

51.2

109.7

41.0

85.3

2018

1 183.9

2 615.9

947.0

2 032.8

23.9

49.5

109.4

39.6

85.1

2019

1 214.0

2 734.1

971.1

2 123.7

24.5

49.5

111.6

39.6

86.7

2021

1 324.3

2 983.4

1 059.3

2 317.3

24.0

55.1

124.2

44.1

96.5

Mexico

2014

986.2

2 177.9

809.1

1 629.1

13.3

74.2

163.9

60.9

122.6

2016

1 067.0

2 314.0

875.2

1 733.0

18.7

57.2

124.0

46.9

92.9

2018

1 194.0

2 578.0

979.7

1 932.0

19.2

62.1

134.0

50.9

100.4

2020

1 342.0

2 787.0

1 101.0

2 095.0

21.5

62.5

129.7

51.2

97.5

2022

1 606.0

3 220.0

1 318.0

2 429.0

20.1

79.8

160.0

65.5

120.7

Nicaragua

2014

1 183.1

2 371.0

979.9

1 733.8

26.0

45.6

91.3

37.8

66.8

Panamá

2014

59.0

117.9

56.0

90.9

1.0

59.0

117.9

56.0

90.9

2018

61.5

121.4

58.4

93.8

1.0

61.5

121.4

58.4

93.8

2019

62.0

121.3

58.9

93.9

1.0

62.0

121.3

58.9

93.9

2021

62.9

122.5

59.7

94.9

1.0

62.9

122.5

59.7

94.9

2022

66.0

126.1

62.7

98.2

1.0

66.0

126.1

62.7

98.2

Paraguay

2014

221 069.0

452 135.0

211 337.0

373 930.0

4 462.2

49.5

101.3

47.4

83.8

2019

268 709.0

536 487.0

256 880.0

445 306.0

6 240.7

43.1

86.0

41.2

71.3

2020

274 254.0

546 425.0

262 180.0

453 697.0

6 771.1

40.5

80.7

38.7

67.0

2021

308 838.0

594 043.0

295 243.0

495 931.0

6 774.2

45.6

87.7

43.6

73.2

2022

344 109.0

650 464.0

328 960.0

544 532.0

6 982.8

49.3

93.2

47.1

78.0

Peru

2014

128.8

283.4

107.2

188.6

2.8

45.4

99.8

37.7

66.4

2019

147.1

323.4

122.3

215.2

3.3

44.0

96.8

36.6

64.4

2020

149.9

329.3

124.7

219.2

3.5

42.9

94.4

35.7

62.8

2021

156.9

342.6

130.5

228.4

3.9

40.4

88.3

33.6

58.8

2022

175.3

373.0

145.8

250.0

3.8

45.7

97.1

38.0

65.1

Uruguay

2014

1 808.4

4 016.6

1 893.9

3 927.9

23.3

77.8

172.8

81.5

168.9

2019

2 722.9

5 912.6

2 851.7

5 789.7

35.3

77.2

167.7

80.9

164.2

2020

3 064.6

6 503.5

3 209.4

6 377.1

42.0

72.9

154.8

76.4

151.8

2021

3 338.6

7 142.7

3 496.4

7 000.4

43.5

76.7

164.0

80.3

160.7

2022

3 619.4

7 655.3

3 790.5

7 508.0

41.2

87.9

185.9

92.1

182.4

Venezuela (Bolivarian Republic of)b

2014

1 309.0

2 014.0

…

…

6.3

208.4

320.7

…

…

Source: Economic Commission for Latin America and the Caribbean (ECLAC) and International Monetary Fund (IMF).

a Annual average exchange rate.

b The extreme poverty and poverty lines apply at the national level.

Table I.A1.5

Latin America (18 countries): personal income distribution indicators, 2014–2022a

(Units corresponding to each index)

Country

Year

Atkinson indexb

Gini indexc

Theil indexb

(e = 0.5)

(e = 1.0)

(e = 1.5)

Population with incomes below 50% of the median

(Percentages)

Argentinad

2014

0.391

0.264

0.121

0.224

0.317

12.8

2019

0.404

0.295

0.132

0.242

0.339

13.5

2020

0.395

0.273

0.124

0.230

0.327

12.4

2021

0.391

0.265

0.120

0.225

0.332

11.9

2022

0.378

0.252

0.114

0.212

0.300

10.7

Bolivia (Plurinational State of)

2014

0.471

0.403

0.185

0.350

0.507

22.7

2019

0.430

0.326

0.152

0.288

0.421

18.3

2020

0.449

0.349

0.165

0.314

0.457

20.5

2021

0.418

0.305

0.143

0.274

0.400

18.6

2022

…

…

…

…

…

…

Brazil

2014e

0.514

0.526

0.217

0.370

0.486

21.6

2019

0.538

0.574

0.236

0.403

0.529

23.4

2020

0.519

0.535

0.219

0.371

0.489

20.8

2021

0.537

0.555

0.231

0.395

0.521

22.9

2022

0.514

0.507

0.212

0.363

0.478

21.6

Chile

2013

0.476

0.441

0.185

0.316

0.420

14.5

2015

0.462

0.427

0.177

0.304

0.404

14.5

2017

0.462

0.427

0.177

0.303

0.404

14.5

2020

0.488

0.460

0.192

0.339

0.476

16.9

2022

0.445

0.371

0.160

0.284

0.393

14.6

Colombia

2014

0.534

0.571

0.236

0.405

0.539

22.6

2019

0.529

0.552

0.231

0.399

0.532

22.7

2020

0.552

0.588

0.245

0.424

0.569

23.9

2021f

0.569

0.648

0.267

0.452

0.591

23.3

2022f

0.563

0.629

0.260

0.441

0.578

22.9

Costa Rica

2014

0.498

0.440

0.197

0.356

0.488

21.1

2019

0.495

0.443

0.196

0.350

0.475

20.4

2020

0.490

0.424

0.190

0.342

0.468

20.0

2021

0.501

0.437

0.196

0.352

0.479

20.7

2022

0.484

0.417

0.187

0.336

0.459

19.9

Dominican Republic

2014i

0.449

0.351

0.160

0.293

0.404

18.3

2019

0.432

0.346

0.149

0.263

0.355

15.4

2020

0.405

0.297

0.133

0.240

0.331

14.4

2021

0.395

0.286

0.127

0.230

0.318

13.9

2022

0.381

0.260

0.118

0.217

0.302

14.2

Ecuador

2014

0.449

0.391

0.165

0.288

0.387

16.5

2019

0.456

0.382

0.167

0.297

0.404

18.1

2020

0.466

0.434

0.181

0.313

0.418

16.8

2021g

0.466

0.443

0.180

0.307

0.407

15.7

2022g

0.447

0.377

0.163

0.289

0.392

16.5

El Salvador

2014

0.434

0.340

0.151

0.273

0.373

17.6

2019

0.406

0.298

0.134

0.245

0.338

16.1

2020

0.421

0.305

0.141

0.267

0.391

17.5

2021

0.406

0.284

0.135

0.262

0.396

18.6

2022

0.402

0.281

0.133

0.257

0.387

18.3

Guatemala

2014

0.535

0.664

0.248

0.407

0.533

22.2

Honduras

2014

0.481

0.428

0.185

0.325

0.435

19.0

2018

0.481

0.427

0.187

0.334

0.457

21.0

2019

0.494

0.406

0.185

0.339

0.471

23.2

2021

0.535

0.495

0.221

0.406

0.579

26.0

Mexico

2014h

0.502

0.511

0.209

0.357

0.475

19.1

2016

0.491

0.448

0.186

0.320

0.425

16.8

2018

0.464

0.444

0.182

0.312

0.415

16.5

2020

0.452

0.401

0.169

0.297

0.401

16.6

2022

0.441

0.388

0.163

0.284

0.382

15.7

Nicaragua

2014

0.495

0.511

0.207

0.355

0.476

19.9

Panama

2014

0.502

0.465

0.206

0.372

0.511

24.2

2018

0.501

0.457

0.206

0.377

0.522

23.7

2019

0.506

0.459

0.206

0.374

0.516

23.8

2021

0.519

0.498

0.217

0.382

0.510

23.4

2022

0.496

0.449

0.201

0.366

0.505

22.4

Paraguay

2014

0.522

0.542

0.219

0.372

0.493

21.5

2019

0.473

0.412

0.180

0.320

0.432

20.3

2020

0.452

0.371

0.165

0.298

0.411

19.6

2021

0.447

0.372

0.163

0.291

0.397

18.6

2022

0.471

0.427

0.183

0.322

0.437

18.6

Peru

2014

0.446

0.369

0.165

0.303

0.424

21.5

2019

0.429

0.332

0.151

0.278

0.390

19.6

2020

0.464

0.396

0.178

0.329

0.469

21.2

2021

0.423

0.327

0.147

0.271

0.382

17.3

2022

0.414

0.315

0.141

0.260

0.369

16.6

Uruguay

2014

0.392

0.271

0.124

0.229

0.319

16.3

2019

0.392

0.270

0.123

0.226

0.314

16.2

2020

0.397

0.277

0.127

0.233

0.323

16.7

2021

0.402

0.286

0.129

0.235

0.323

16.4

2022

0.401

0.285

0.129

0.236

0.326

16.8

Venezuela (Bolivarian Republic of)

2014

0.378

0.242

0.112

0.210

0.300

14.8

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Calculated on the basis of per capita income distribution in the country as a whole.

b The Theil and Atkinson indices were calculated without including values close to 0 or the three highest per capita incomes (to mitigate the effect of extreme values).

c Includes people with income equal to 0.

d Urban total.

e The 2014 figure is based on the National Household Survey (PNAD) and is not comparable with those of later years, which are based on the Continuous National Household Survey (PNAD Contínua).

f The 2021 and 2022 figures are from a new series based on the 2018 National Population and Housing Census sampling frame and are not comparable with those of earlier years.

g The 2021 and 2022 figures are for the full year (data prior to December).

h The 2014 figure is not comparable with those of later years, which are based on a new series of the National Household Income and Expenditure Survey (ENIGH).

i The 2014 figure is based on the National Labour Force Survey (ENFT) and is not comparable with those of later years, which are based on the Continuous National Labour Force Survey (ENCFT).

1. [1] The average labour force participation rate was calculated as a simple average for 16 countries for which full information on participation, employment and unemployment rates in 2022 was available. These countries were Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay (ECLAC, 2023, statistical annex).

2. [2] The regional average was calculated as a simple average for the following 15 countries: Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay (ECLAC 2023, statistical annex).

3. [3] Calculated as income changes expressed in multiples of the poverty line, which is used as a proxy indicator for price changes over the period.

4. [4]4 In the cases of Mexico and Chile, the annualized change is for the period from 2020 to 2022, while for the rest of the countries mentioned it is for the period from 2021 to 2022.

5. [5] Per capita household income is the variable used in this publication for poverty and inequality measurements. It is the ratio of total household income from different sources (work, asset ownership, transfers and imputed rent) to the number of persons in the household. The same ratio is used for earnings, but with reference only to income from work, the largest source of household income.

6. [6] Household surveys are the best source available in the region for the timely monitoring of household income and distributional trends. However, this source does not adequately capture the incomes of the highest earners and may result in gaps being underestimated. Recent estimates of income inequality using a combination of data sources can be found in Alvaredo and others (2022) and Fuentes (2022).

7. [7] The Palma ratio is presented as an alternative to synthetic indicators of inequality and focuses on the differences between the incomes at the top and bottom of the distribution: the highest-income 10% and the lowest-income 40%. The index is based on the regularity observed by Palma, who found that, in most countries, the income share of the middle 50% (i.e., those between the poorest 40% and the richest 10%) tended to be fairly constant, at about 50% of total income. This means that inequality largely derives from the distribution between the groups at either end of the distribution.

8. [8] Imputed rent is income attributed to owner-occupier households for the housing services provided by their home. It is an imputed item whose purpose is to equate the welfare situation of households that own their own homes with those that do not.

9. [9] This negative correlation has also been observed in relation to income (Corak, 2013) and is often referred to in the literature as the Great Gatsby curve.

10. [10] Forbes methods have been criticized for their lack of transparency and the difficulty of replicating results (Chancel and others, 2022; Acciari, Alvaredo and Morelli, 2021). However, given the shortcomings of surveys and records when it comes to capturing the top end of the distribution, researchers often use Forbes data to supplement information from other sources and estimate the total wealth share of the most affluent (see, for example, Credit Suisse Research Institute, 2022; Chancel and others, 2022; Bajard and others, 2022; Zucman, 2019).

11. [11] There are other sources of data on large fortunes, such as Bloomberg (see [online] https://www.bloomberg.com/billionaires/) and Altrata/Wealth-X (see [online] https://altrata.com/reports/billionaire-census-2023). Bloomberg has more limited coverage than Forbes, as it focuses on the top 500 billionaires worldwide, which diminishes its usefulness for Latin America. Wealth-X, for its part, charges a fee to access individual billionaires’ information (ECLAC, 2022a).

12. [12] In some specific cases, Forbes records family wealth. See Freund and Olivier (2016) for more information.

13. [13] For some billionaires included in the list the legality of their fortunes could not be established.

14. [14] Wealth data are not provided for Honduras, Guatemala, the Dominican Republic and Cuba (see Credit Suisse Research Institute, 2022).

15. [15] The assets of some of the region’s drug cartel heads could be considerable. For example, “El Chapo” (Joaquín Guzmán Loera), head of the Sinaloa cartel, was estimated to have a net worth of US$ 1 billion between 2009 and 2012 (see [online] https://www.forbes.com/profile/joaquin-guzman-loera/?sh=419836ad6778). Other media estimates put “El Chapo’s” wealth much higher, at over US$ 12 billion at its peak in 2010 (see [online] https://www.foxbusiness.com/features/el-chapo-sentenced-forfeit-fortune-what-to-know).

16. [16] See Task Justice Network (2023) for an index of countries ranked by their level of financial secrecy.

17. [17] Average personal wealth in Argentina fell by 67% between 2012 and 2021 in current values (Credit Suisse Research Institute, 2022).

18. [18] The wealth of these seven individuals as a share of the total wealth of the region’s billionaires declined between 2012 and 2022, probably because of inflation. Wealth of US$ 1 billion in current 2012 dollars does not equate to the same figure in 2022: since inflation lowers the bar for joining the billionaires’ club in real terms, the number of billionaires should tend to increase (e.g., figure I.14 shows that the number of billionaires rose from 66 to 105 between 2012 and 2021). Notwithstanding all this, it was decided to use absolute thresholds because of their symbolic value.

19. [19] Piketty (2011) indicates that the concentration of wealth and the share of inherited in total wealth are an increasing function of , where r is the rate of return on assets (net of tax) and g is the economic growth rate. Thus, slowing population growth and declining productivity ought to increase the likelihood that upward trends in the wealth-to-income ratio and in the concentration of wealth will be sustained in the long run.

20. [20] In modern market-based economies, income is the main means of accessing the goods and services essential for material well-being. The different normative theories of social and economic order recognize a central role for income, either because it is the main mechanism for satisfying preferences (in utilitarianism), because it is among the essential primary goods (in Rawls’ (1971) theory of justice) or because it is an important means of achieving the functionings that people value (in Sen’s (1992) theory of functionings and capabilities) (ECLAC, 2018a).

21. [21] The trends described match those indicated by official national figures in most countries, with a few minor exceptions (see table I.A1.2 in the annex).

22. [22] Changes in per capita income from each income source between the initial and final year, expressed as a function of total income in the initial year, for a group of households of constant size. The size of the group of households is given by the poverty rate of the year (initial or final) in which this rate was highest, plus five percentage points.

23. [23] See Portes and Hoffman (2003) and Solís, Chávez Molina and Cobos (2019) for information on efforts to construct stratifications based on labour market status that are comparable across Latin American countries. See Martínez and others (2022) for a recent ECLAC study in this area that aims to supplement stratification by income.

24. [24] The concept of well-being here refers to consumption opportunities and living standards.

25. [25] The thresholds are as follows. Extreme poverty: per capita household income below the extreme poverty line; non-extreme poverty: per capita household income greater than or equal to the extreme poverty line and below the poverty line; low income but not poverty: per capita household income greater than or equal to the poverty line and less than 1.8 times the poverty line; lower-middle income: per capita household income greater than or equal to 1.8 times the poverty line and less than 3 times the poverty line; intermediate-middle income: per capita household income greater than or equal to 3 times the poverty line and less than 6 times the poverty line; upper-middle income: per capita household income greater than or equal to 6 times the poverty line and less than 10 times the poverty line; high income: per capita household income greater than or equal to 10 times the poverty line.

26. [26] This is not a direct measure of stratum or class. There is not necessarily a hierarchical relationship between the categories of employment and occupation, nor is there a strict attempt to define classes on the basis of relations of production or the like.

27. [27] Employment in low-productivity activities is used as a proxy for informal employment. Employers and employees (professional and technical or otherwise) working in microenterprises (enterprises with up to five employees), domestic service workers and unskilled self-employed workers, including own-account workers and unpaid family workers without professional or technical qualifications (ECLAC, 2012), are considered to be engaged in low-productivity activities.

28. [28] Martínez and others (2022) argue that stratification exercises based on occupation tend to be limited to employed people and do not take into account the implications of the sexual division of labour within households.

29. [29] The sum of employees engaged in low-productivity activities, own-account workers engaged in low-productivity activities in urban areas and own-account workers in rural areas.

30. [30] Higher GDP will not always translate into higher levels of development, not only owing to of lags, but also because countries with the same level of economic growth may have different welfare regimes and environmental protection policies, which may lead to different social and environmental outcomes.

31. [31] See Our World in Data (2022 and 2023).

32. [32] Abramo (2021) observes that, as of around 2019, rates of employment in low-productivity activities were much higher in rural areas than in urban areas in 16 countries of the region.

33. [33] The relationship between growth and productivity can run both ways. However, this is a correlational exercise that does not attempt to establish causal relationships.

Chapter II

From access to inclusion: key considerations for reducing inequality and informality in the labour market

Introduction

A. Labour market crisis and widening inequalities

B. Labour informality in Latin America and the Caribbean: emerging and existing barriers to labour inclusion

C. Strategies to promote labour inclusion: implementing labour policies to move towards inclusive social development

D. Concluding remarks

Bibliography

Annex II.A1

Annex II.A2

Introduction

The labour market in Latin America and the Caribbean is in a slow-moving crisis, compounded by cascading crises that have struck the region since 2020, including the coronavirus disease (COVID-19) pandemic, the inflationary spiral and the economic slowdown. These added to existing tensions caused by major technological transformations and various environmental and demographic trends, which have widened historic gaps. Their cumulative impact, in particular on the most vulnerable individuals and groups, is without precedent (ECLAC, 2022a; OECD and others, 2021; Salazar-Xirinachs, 2016).

Labour inclusion encompasses both entry into the labour market and the conditions of the work towhich access is gained (Arenas de Mesa and Espejo, 2023) (see diagram II.1). Labour market entry alone is not enough to achieve inclusive social development and sustainable development, as the conditions under which paid work is performed are equally crucial. Universal decent work is essential for sustaining a minimum quality of life and access to various social services (ECLAC, 2007; Cecchini and Martínez, 2011). The region’s labour market has historically been characterized by a heterogeneous productive structure with a high proportion of its employed population working in low-productivity sectors, resulting in high levels of income inequality among households (ECLAC, 2016). Given its impact on incomes and social protection coverage, employment is the key to reducing inequalities in Latin America and the Caribbean (ECLAC, 2010 and 2016).

Diagram II.1

Labour inclusion

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

The strength of the labour market was pivotal in reducing poverty and inequality between 2002 and 2014. During that period, unemployment decreased and employment, income, labour market formality and women’s labour market participation increased, and the number of households earning labour income grew as a result (ECLAC, 2014 and 2016). These circumstances were shaped by labour supply and demand, which was influenced by public policy measures both in the labour market (minimum wage, increased formal employment, stronger labour inspection) and beyond (expansion of social protection systems, increased education coverage) (ECLAC/ILO, 2014; ECLAC, 2014).

In the past decade, however, key labour market indicators have shown signs of deterioration, no doubt the result of lower economic growth and the COVID-19 crisis, which impeded inclusive social development in the region. According to the Economic Commission for Latin America and the Caribbean (ECLAC, 2022a), 2014–2023 was the lowest-growth decade since 1950, with an average growth rate of 0.8%. Thus, the general sluggishness of the economy in the years following the global financial crisis (2008–2009) translated into weak job growth over the following decade (see figure II.1). The number of employed increased by just 1.26% during the period. These circumstances converged to create a labour market that was highly vulnerable and insecure prior to the pandemic, culminating in a record 8.2% contraction in the number of people employed in 2020, the only reduction registered in the last 70 years (ECLAC, 2023a).

The marked slowdown in job creation between 2014 and 2023 coincided with a deterioration in the quality of jobs created. The incidence of labour market informality has risen, from 48.1% in 2014 to 50.4% in 2020, breaking with the strong trend towards greater formalization of employment in the region seen in the 2000s (Espejo, 2022; ECLAC, 2022b). Although the pandemic brought the main challenges and weaknesses of the region’s labour market to the forefront of public and political discourse, these are not new problems, but rather ones that had lingered for a decade prior to their intensification in 2020. It is worrying that this trend is moving away from the targets of Sustainable Development Goal (SDG) 8 (Decent work and economic growth) and the second axis of the Regional Agenda for Inclusive Social Development, on policies to promote social and labour inclusion (ECLAC, 2020).

Owing to its specific characteristics, the labour market can generate inequality or, conversely, help to reduce the region’s deep divides. Data show that unfair disparities in opportunities for labour market participation and quality of employment on the basis of ethnicity and race, area of residence, stage of the life cycle and gender persist in Latin America and the Caribbean (Cecchini, Holz and Soto de la Rosa, 2021). Access to precarious forms of employment has a negative impact on careers and on individual and household incomes in the medium and long term, as well as on the well-being of older persons owing to sporadic or non-existent social security contributions (Abramo and others, 2021; ECLAC/ILO, 2019). Paid work is a central pillar of household income in the region; as discussed in chapter I, employment income accounted for 68.6% of household income in 2022. However, as will be further explored in this chapter, entry in the labour market per se is not enough to reduce inequality (ECLAC, 2019). It is the characteristics of that entry, along with the conditions of the work that it represents, that will be key to achieving social inclusion. Tackling inequality and making progress towards inclusive and sustainable social development requires not only robust, broad-scale employment but also higher levels of labour inclusion.

Inclusive social development expands on the concept of social development —historically anchored in ideas of well-being and improved living conditions— by linking it to the need for a systemic approach to inequality and exclusion and understanding social development as a matter of human rights. Labour inclusion is one component of inclusive social development. It seeks to ensure that all members of the labour force have access to decent work that provides adequate pay and social protection coverage. However, the levels of labour inclusion are uneven across the countries of the region, reflecting the difficulties inherent to the social inequality matrix, weak institutions and labour market policies, and the productive structure of the region (see diagram II.2).

Diagram II.2

Latin America and the Caribbean: labour inclusion challenges

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

First, as discussed in section A of this chapter, women, young people, persons with disabilities, people living in poverty, Afrodescendent populations, Indigenous Peoples and other groups at the structural nexus of social inequality (ECLAC, 2016) face greater obstacles and barriers to labour inclusion owing to difficulties in entering the labour market and increasingly precarious employment, due mainly to informality (see sect. B). Viewed through the lens of the social inequality matrix, labour inclusion problems are closely linked to high levels of inequality, as well as an intergenerational lack of access to a variety of resources and opportunities, and low-productivity jobs (Weller, 2023).

Second, labour market inclusion is largely contingent upon the institutional framework and labour market policies; their design and implementation have a direct impact on the prospects of achieving labour inclusion. As discussed in section C of this chapter and in chapter IV, the implementation of a solid institutional framework and well-designed labour market policies can foster a labour environment that reduces inequality and informality in the region.

Third, the productive structure, as mentioned previously, is heterogeneous and perpetuates deep income inequality in Latin America and the Caribbean, as the majority of the employed population is concentrated in low-productivity sectors (ECLAC, 2016).

In the midst of a development crisis and facing substantial and complex change in the areas of technology, population, environment, global politics and international trade, the region is at a crossroads; the policies implemented now will determine the course of countries’ development in the future (Salazar-Xirinachs, 2023). Labour inclusion, a central component of social inclusive development, provides a possible way out of the crisis as it can help to advance economic development by increasing productivity, technology transfer and innovation in the economy, thereby helping to address structural heterogeneity and boost the creation of quality jobs, incomes and social inclusion (Amarante and Infante, 2016). Moreover, labour inclusion as a development strategy lends itself to a comprehensive approach to labour inclusion opportunities in Latin America and the Caribbean and a broader understanding of factors that drive social inclusion beyond employment alone, which was the predominant driver in the second half of the twentieth century. It is access to jobs that provide sufficient income for households to overcome poverty and improve their well-being but also enable them to avoid unhealthy work environments and excessive or irregular hours and ensure their access to social protection that will encourage labour inclusion. This, in turn, encourages social inclusion, underpinned by participation in social life and the enjoyment of social rights, such as education, health, pensions and care, as well as basic services, such as infrastructure and material resources (ECLAC, 2016). Thus, labour inclusion breeds dual inclusion by reducing inequality and nudging countries back onto the path of inclusive social development.

Amid increasing uncertainty and risk-restructuring (Robles and Holz, 2023), labour inclusion should be strengthened as an effective development strategy for a more productive, inclusive and sustainable future. To that end, in addition to investing in labour market policies, in the form of direct and indirect job creation, training programmes and labour intermediation services, States should take complementary policy measures at the sectoral level as part of a broader social and fiscal compact. Doing so would facilitate social dialogue, leading to stronger institutional frameworks, improved wages and reduced informality in the labour market. The COVID-19 pandemic offered an opportunity to recognize the role States could play in the labour relations of the future, with regard to both inclusive social policymaking and sectoral capacity-building. It also demonstrated the crucial role of States in driving inclusive social development and designing labour market policies to reduce informality. With seven years remaining to implement the 2030 Agenda for Sustainable Development, and in view of the post-pandemic outlook, innovative labour and social protection policies, are required.

This chapter is centred on labour inclusion as a key strategy for reducing inequality and informality amid multiple crises. Following this introduction, the chapter is divided into four sections. In section A, the changes in key labour market indicators from 2019 to the first quarter of 2023 are analysed on the basis of employment surveys from the region,[1] and the populations that were hardest hit by each phase of the crisis are identified. Section B contains an assessment of labour market informality, which affects approximately 50% of workers in the region, making them more vulnerable to crises and to the global labour market changes brought about by the fourth technological revolution, among other factors. Section C presents States’ main efforts to foster labour inclusion between 2019 and 2023, with a particular emphasis on the trends in and adaptation and flexibility of active labour market policies targeting priority population groups; the strengthening of labour institutions; financial sustainability; and lessons learned. Lastly, section D contains final thoughts on the urgent need to strengthen labour inclusion policies to advance inclusive social development.

A. Labour market crisis and widening inequalities

The labour markets of Latin America and the Caribbean are in a slow-moving crisis of consistently low rates of growth in gross domestic product (GDP) and employment. The COVID-19 pandemic had an enormous impact on labour inclusion. It generated the worst labour crisis to hit the region since 1950 and caused significant setbacks in the job market, with unequal effects across population groups. The gradual recovery in the region’s labour market following the pandemic has not sufficed to create decent jobs or overcome the inequalities affecting women, young people, older persons, persons with disabilities, Afrodescent populations and Indigenous Peoples, among other population groups. This persistent set of circumstances and their accumulated effects have intensified the urgent need for labour inclusion policies that reduce inequality and informality and drive productivity and inclusive social development strategies.

Latin America and the Caribbean is in a slow-moving crisis, characterized by years of languid GDP and employment growth. In view of the accumulated effects of this crisis, the design and implementation of labour inclusion policies are more critical than ever to reducing inequality and informality and driving productivity and inclusive social development strategies.

As discussed in the introduction, in 2020, COVID-19 unleashed the greatest labour market crisis in Latin America and the Caribbean since 1950, leading employment creation to decline for the first time in 70 years. Estimates place the rate of growth in the number of employed persons at 1.26% for the period 2014–2023, compared to 3.2% during what was called the lost decade of the 1980s. The improvement in labour markets from 2020 to 2022 is due to a cyclical recovery in economic growth and, thus, will not last (ECLAC/ILO, 2023). Indeed, ECLAC (2023a) projects that the regional economy will grow at a rate of 1.7% for 2023, which will undoubtedly lead to less buoyant job creation. Meanwhile, employment growth is projected at less than 2% in 2023, compared to 5.3% in 2022 (see figure II.1).

The rapid response to the public health crisis and the implementation of economic, social and labour market policies helped to stimulate the post-pandemic recovery but were not enough to create decent jobs or sustain recent improvements in the region’s labour market indicators, owing to the considerable accumulated effects of the crisis on the most vulnerable groups, such as women and young people (ECLAC, 2023b). In 2022, people of working age accounted for 77% of the total regional population. More than 37% of those (approximately 189 million), a majority of whom were young people and women (see sect.A.2 (a)), were not in the labour market (see diagram II.3). Their absence is an indication of the significant barriers to entry that these groups must overcome if labour inclusion is to advance. Meanwhile, the economically active population stands at 314 million. Although 93% are employed, almost half of them are in the informal labour market and lack access to social protection, which is indispensable to decent employment. A regional study of household and employment surveys (from around 2022) shows that 17% of the employed population are living in poverty, 36.8% earn below the minimum wage established by each country (see sect. II.A.2 (f)) and nearly 54% do not contribute to pension systems (Arenas de Mesa, Robles and Vila, 2023).[2] Thus, labour access through paid work, though necessary, does not automatically translate into labour inclusion.

Figure II.1

Latin America and the Caribbean (21 countries):a rate of growth in the number of employed persons, 1951–2023

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of ECLAC, Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago, 2023; and official data from the University of Groningen and the International Labour Organization (ILO).

Note: Figures for 2023 are based on ECLAC estimates (2023b).

a Argentina, Belize, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Trinidad and Tabago and Uruguay.

Diagram II.3

Latin America and the Caribbean (29 countries):a population structure, 2022

(Millions of people and percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of International Labour Organization (ILO), ILOSTAT [online database] https://ilostat.ilo.org/data/.

Note: The working-age population comprises individuals age 15 years or older.

a Argentina, Bahamas, Barbados, Belize, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, the Dominican Republic, Ecuador, El Salvador, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago and Uruguay.

Despite the return of key labour market indicators and labour market composition to pre-pandemic levels, the region’s structural labour problems remain, including substantial equality gaps in terms of gender, age, ethnicity/race and disability status, and high levels of informality, among others.

1. Setbacks and historic gaps in the post-COVID-19 labour market

The impact of the COVID-19 pandemic on Latin American labour markets was profound and immediate. The second quarter of 2020 ushered in an intense contraction in the supply and demand of labour, together with rising unemployment and a considerable decline in labour force participation rates in all countries in the region (ILO, 2021). Notwithstanding the gradual recovery in the region’s labour market since 2021, it has nevertheless been incomplete and uneven (ECLAC, 2021 and 2022a). In 2022, the labour force participation rate rose for the second consecutive year, albeit not to pre-pandemic levels, and the unemployment rate fell substantially as people rejoined the labour force. According to 2023 estimates based on employment surveys from 20 countries of the region, the pace of recovery of these variables has tended to stall, and structural gaps remain (ECLAC, 2023b). The average labour force participation rate for 2023 is expected to remain just below pre-pandemic levels (63% in 2023 compared to 63.3% in 2019). Meanwhile, the unemployment rate has dropped below pre-pandemic levels (see figure II.2) but is projected to increase between 2023 and 2024, from 6.3% to 7.1% (ECLAC, 2023b).

Figure II.2

Latin America and the Caribbean (20 countries):a labour force participation and unemployment rates, 2019–2023

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of ECLAC, Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago, 2023; regional employment surveys and projections.

Note: Data for 2020 and 2021 may present comparability problems with respect to the data for 2019, owing to adjustments to statistical processes made by national statistical and census offices in response to the COVID-19 pandemic.

a Argentina, Barbados, Belize, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Trinidad and Tobago, and Uruguay.

b Figures for 2023 are based on estimates in ECLAC (2023b).

It is worth noting that the unemployment rate in the first quarter of 2023 decreased year-on-year in eight of the nine countries for which data are available. It decreased most in Costa Rica, Brazil and Paraguay, by more than two percentage points (2.9, 2.3 and 2.1, respectively); Chile was the only country for which data are available that saw a year-on-year increase (1%).

According to a number of ECLAC reports (2022c, 2022d and 2023b), the recovering labour market has failed to close historic gaps between men and women. As shown in figure II.3, the pandemic reduced the labour force participation rate among men and women alike, but women’s labour force participation has recovered more slowly. The COVID-19 crisis wiped out a decade’s worth of progress in terms of women’s participation (ECLAC, 2021). In the fourth quarter of 2020, the lagging participation rate among women picked up, leading to a slow narrowing of the gender gap which, nevertheless, remains wide. In the first quarter of 2023, the gender gap in the labour force participation rate was 22.2 percentage points, similar to the figure recorded in the fourth quarter of 2019 (ECLAC, 2023b).

Figure II.3

Latin America and the Caribbean (20 countries):a labour force participation and unemployment rates, by sex, 2019–2023

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of ECLAC, Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago, 2023; regional employment surveys and projections.

Note: Data for 2020 and 2021 may present comparability problems with respect to the data for 2019, owing to adjustments to statistical processes made by national statistical and census offices in response to the COVID-19 pandemic.

a Argentina, Barbados, Belize, , Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Trinidad and Tobago, and Uruguay.

b Figures for 2023 are based on estimates in ECLAC (2023b).

At the country level, between the first quarter of 2022 and the first quarter of 2023, the unemployment rate among men rose only in Argentina and Chile (0.2 and 1.2 percentage points, respectively), while it decreased in Costa Rica and Paraguay (2.6 and 2.7 percentage points, respectively). Among women, the unemployment rate decreased most in Brazil, from 13.7% in the first quarter of 2022 to 10.7% in the first quarter of 2023. It also fell in Costa Rica, by three percentage points. Only in Chile did the unemployment rate among women increase, from 8.7% in the first quarter of 2022 to 9.5% in the first quarter of 2023. For a brief analysis of the labour situation in the Caribbean countries, see box II.1.

Box II.1

The Caribbean (5 countries): labour market indicators

In the Caribbean, as in the rest of the region, both the severity of the pandemic’s effects on employment and the post-pandemic recovery varied from country to country. In Jamaica, between 2019 and 2020, the employment rate fell by three percentage points, but in 2022, both the employment and unemployment rates had improved relative to pre-pandemic levels. Trinidad and Tobago and Barbados also recorded significant improvements in the employment and unemployment rates, but unemployment was still higher in 2022 than in 2019. Meanwhile, in Belize and Saint Lucia, the most recent available data (2021) indicate that employment and unemployment have a long way to go to reach pre-pandemic levels, and the unemployment rate in 2021 (over 20%) was even higher than in 2020, constituting a major challenge for labour market recovery.

The Caribbean (5 countries): labour market indicators, 2019–2022

(Percentages)

2019

2020

2021

2022

Employed

Unemployed

Employed

Unemployed

Employed

Unemployed

Employed

Unemployed

Barbados

57.60

9.60

51.10

15.60

52.60

14.10

57.60

8.40

Belize

62.00

9.10

47.60

13.70

53.00

21.10

Jamaica

59.70

5.00

56.60

6.60

57.90

5.20

60.40

3.90

Saint Lucia

59.00

16.80

53.90

21.70

53.70

23.10

Trinidad

and Tobago

54.90

4.30

53.90

4.70

51.90

5.40

55.00

4.90

Labour market indicators in the selected Caribbean countries were especially problematic for certain population groups, in particular women and young people. Before the COVID-19 pandemic, approximately one quarter of young people in the Caribbean were unemployed (three times the rate for adults). These levels persisted or, in some cases, deteriorated during the public health crisis. Meanwhile, the pandemic may have had an unintentional equalizing effect in terms of the employment gap between men and women. Although the gap narrowed in Barbados, Jamaica, and Trinidad and Tobago, this was due to the considerable increase in the unemployment rate among men and, possibly, the increased number of people outside the labour market during the pandemic (see sect. II.A.2).

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of ECLAC, The Caribbean Outlook. Summary. Recovery and resilience – repositioning the Caribbean post COVID-19 (LC/TS.2022/161), Santiago, 2022; Economic Commission for Latin America and the Caribbean/International Labour Organization (ECLAC/ILO), “Towards the creation of better jobs in the post-pandemic era”, Employment Situation in Latin America and the Caribbean, No. 28 (LC/TS.2023/70), Santiago, 2023.

A quarterly analysis, by age group, of the change in the employment rate between 2019 and 2022 shows considerable variation in the effects of the crisis, which women, young people and older persons suffered disproportionately. Overall, the decrease in employment rates in 2020 was greater —and the subsequent recovery slower— for women than for men (see figure II.4). Young people and older persons were also disproportionately affected by reduced employment relative to other age groups. Between the first quarter of 2019 and the second quarter of 2020, among young people aged 15–29, the employment rate fell by 20.5% for men and 22.5% for women. Older persons (age 65 and over) were worse off, with the employment rate falling by 27.6% for men and 31.3% for women between 2019 and 2020. The recovery in employment following the pandemic also varied by age group and sex: rates recovered faster for young people, returning to pre-pandemic levels in the third quarter of 2021 and surpassing them by a significant margin by the end of 2022. Meanwhile, rates among older persons have yet to fully recover, down 3.6% for men and 5.8% for women compared to the first quarter of 2019.

Figure II.4

Latin America and the Caribbean (12 countries):a change in the employment rate, by sex, age group and quarter, 2019–2023

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of regional employment surveys.

Note: Data for 2020 and 2021 may present comparability problems with respect to the data for 2019, owing to adjustments to statistical processes made by national statistical and census offices in response to the COVID-19 pandemic.

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Mexico, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

2. Disparate effects of recent crisis on labour inclusion: compounding inequalities

(a) Widening of gender gaps in the labour market

In Latin America and the Caribbean, various barriers continue to block access to paid work. Women are one of the worst-affected groups, with one out of two excluded from the labour market. The COVID-19 pandemic made things worse, owing to women’s overrepresentation in job categories affected by the crisis and the unequal share of the caregiving burden that fell on their shoulders (ECLAC, 2022a).

Women already faced major challenges prior to the pandemic in terms of labour force participation and access to employment, and they were overrepresented in lower-wage, insecure jobs (see chap. III). In 2020, the initial impact of the pandemic was harder on women’s labour force participation than on men’s, wiping out more than a decade’s worth of progress in this area (ECLAC, 2021). Because many women stopped searching for work in the early months of the pandemic, the unemployment rate— normally the main indicator of labour market strength— lost a measure of its usefulness, and the percentage of the population outside the labour market became more relevant (ECLAC, 2022a).

According to the International Labour Organization (ILO, 2023a), exclusion from the economically active population can have positive and negative aspects. It can be positive for young people and older persons alike, to the extent that it allows young people to dedicate the majority of their time to their education and enables older persons to enjoy the right to a dignified retirement. However, it tends to be a negative indicator in the region, where it reflects the scarcity of job opportunities, job-seeking fatigue, gender discrimination and other limiting factors.

According to ECLAC data based on employment surveys from 11 countries of the region, approximately 93 million people (28.6% of the population aged 15–59) were outside the labour market in the second quarter of 2022. The fact that women accounted for 65 million (70%) of their number demonstrates their overrepresentation in the region’s economically inactive population. More detailed information on barriers to women’s labour inclusion is presented in chapter III. It should be noted that the economically inactive population aged 15–59 had risen to 121 million in the second quarter of 2020, but the mass exodus from the labour market during that period caused a modicum of improvement in the gender gap (see figure II.5).

The composition of population outside the labour market shows marked differences by sex and age group. Women account for 70% of the economically inactive population aged 15–59. Further disaggregation into three age groups shows that young women account for half of the total. For men making up the remaining 30% of that population, unemployment is highest among young people (see figure II.6). In the 11 selected countries, in the fourth quarter of 2022, more than 70% of men aged 15–29 who were outside the labour force indicated that they were engaged in studies, compared to 50% of women.

Figure II.5

Latin America and the Caribbean (11 countries):a population aged 15–59 outside the labour force, by sex, second quarter of 2019–second quarter of 2022

(Millions of people)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of regional employment surveys.

Note: Data for 2020 and 2021 may present comparability problems with respect to the data for 2019, owing to adjustments to statistical processes made by national statistical and census offices in response to the COVID-19 pandemic.

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Mexico, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

Figure II.6

Latin America and the Caribbean (11 countries):a population aged 15–59 outside the labour market, by sex and age group, second quarter of 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of regional employment surveys.

Note: Data for 2020 and 2021 may present comparability problems with respect to the data for 2019, owing to adjustments to statistical processes made by national statistical and census offices in response to the COVID-19 pandemic.

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Mexico, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

(b) Outsize impact of the crisis on young people

Young people in Latin America and the Caribbean are facing particularly challenging circumstances both in labour market access and inclusion and in charting successful careers (Gontero and Albornoz, 2022). The challenges became more apparent with the outbreak of the COVID-19 pandemic, in particular in the region’s labour market, where employment losses were greater in the population ages 15 to 24 relative to the adult population (Espejo and others, 2023a). Young workers tend to be harder hit by crises in general. Firms often respond to declining demand and the need to downsize by retaining their more experienced workers or those with more training or higher productivity, while laying off workers with less seniority, for whom the severance costs are lower (ECLAC/ILO, 2019). During the pandemic, there were additional contributing factors, such as the high numbers of young people in informal employment and their overrepresentation in occupations that were severely affected by the lockdown measures, including restaurant and hotel services and retail (ECLAC, 2021; ECLAC/ILO, 2019).

According to ECLAC data based on employment surveys from 12 countries, in the second quarter of 2020, the employment rate fell year-on-year by 11.3 percentage points in the 15–29 age group and by 10.6 percentage points in the 30–64 age group (see figure II.7). This translated to approximately 15 million young people losing their jobs at the height of the public health and lockdown measures. Employment data also reveal the emergence of a substantial gender gap among workers at an early age in the region: throughout the period, the gender gap hovered around 18 percentage points in the 15–29 age group.

Figure II.7

Latin America (12 countries):a employment rates among young people (aged 15–29) and adults (aged 30–64), by sex, first quarter of 2019–fourth quarter of 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of regional employment surveys.

Note: Data for 2020 and 2021 may present comparability problems with respect to the data for 2019, owing to adjustments to statistical processes made by national statistical and census offices in response to the COVID-19 pandemic.

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Mexico, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

Although labour indicators have improved, the long-term effects of the crisis on youth labour inclusion remain unknown. As stated in the previous Social Panorama of America and the Caribbean (ECLAC, 2022d), between 2020 and 2022, youth access to training and employment was limited, resulting in an increase in the already high number of young people who found themselves outside the labour market, and at a critical age. While this could be a temporary phase, it is likely that the time lost in terms of training and work experience will have a negative impact on the gainful employment of young people in the future.

This crisis has highlighted the need to identify the keys to ensuring access to opportunities and protection mechanisms for the implementation of effective measures, with a view to achieving productive and satisfying labour inclusion for young people. One key aspect is the strengthening of mechanisms to ensure access to formal employment (see section II.B.2). In general, young people in the region are heavily represented in informal employment, which perpetuates their vulnerability with regard to social protection, labour rights and decent working conditions (Espejo and Espíndola, 2015).

(c) The right to work in old age: the particular challenges of labour inclusion for older persons

There are particular challenges for the labour inclusion and continuance of older persons in the labour market compared with other population groups, including young people, women and persons with a disability. The majority of older persons who work in Latin America and the Caribbean do so pressured by the need for income, especially in the case of women, owing to the lack or insufficiency of pensions and the lack of other sources of income (ECLAC, 2022e and 2022f).

In 2022, 21.7% of the population aged 65 and over was employed, and there was a significant gender gap: the employment rate of men was more than double that of women. Information from the first and second quarters of 2020 shows that the employment rate for the population aged 65 and over fell considerably for both sexes as a result of the COVID-19 pandemic, although the decline was steeper for men (9 percentage points) than for women (4.5 percentage points) (see figure II.8). Beginning in the third quarter of 2021, employment rates began to rise slightly, then approached pre-pandemic levels in the last quarter of 2022 (see figure II.8).

Figure II.8

Latin America and the Caribbean (12 countries):a unemployment rate among the population aged 65 and over, by sex, 2019–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of regional employment surveys.

Note: Data for 2020 and 2021 may present comparability problems with respect to the data for 2019, owing to adjustments to statistical processes made by national statistical and census offices in response to the COVID-19 pandemic.

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Mexico, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

Economic security in old age through decent and sufficient pensions is a right, as is the participation in the labour market of older persons who wish to continue working. However, the labour market has not been sufficiently inclusive for older persons. As people age, the likelihood of becoming unemployed or moving to informal and very precarious employment increases, a situation that is compounded by stigmatization and discrimination. Data show that in the last quarter of 2022, the informality rate of employed persons aged over 65 was 72.7% (76.6% for men and 70.6% for women), compared with 49% among the employed population aged 15 years and over. Higher levels of informality among older persons may result from the fact that it is often impossible to continue receiving a pension while formally employed and from the high prevalence of self-employed employers and workers, in particular in the agriculture sector (ECLAC, 2019).

In light of the foregoing, employment should be an option rather than a burdensome obligation that affects older people’s quality of life, and they should be able to secure decent work. Labour inclusion policies based on the rights of older persons should therefore take the following into account: (i) rapid population ageing; (ii) human rights and the high incidence of age-related discrimination; (iii) the distinction between involuntary and voluntary work, with a view to addressing the factors that determine the former and facilitating the latter; (iv) broadening and consolidating social security regimes and minimum social protection thresholds; (v) changes in women’s labour participation, occurring in the context of the gradual increase in women’s labour market participation; and (vi) options to combine paid work and pensions for voluntary labour participation (ECLAC/ILO, 2018).

(d) The challenge of labour market inclusion for persons with a disability

The right of persons with a disability to an inclusive and accessible workplace was ratified in article 27 of the Convention on the Rights of Persons with Disabilities, in which States Parties recognize and agree to safeguard and promote the realization of the right of persons with disabilities to work on an equal basis with others (United Nations, 2007). The Convention also protects the right of persons with disabilities to just, favourable, safe and healthy working conditions, including the exercise of labour and trade union rights. It therefore advocates not only for the labour access of persons with a disability but also for their meaningful inclusion.

Despite the commitment of States Parties to guarantee the right to work of persons with a disability, they continue to be confronted by a wide range of labour inclusion barriers in Latin America and the Caribbean (Marinho and Espejo, 2023). As shown in figure II.9, the unemployment rates pertaining to persons with a disability are higher than those of persons without a disability. In fact, in the five countries for which information is available, more than half of the population of persons with a disability are not employed. In some cases, the rate is over 60%, reflecting extreme levels of exclusion. A comparative analysis of pre-pandemic data and data updated as at 2022 shows that the employment rate recovered to reach 2019 levels in only three of the five countries studied, while the figures in the other two (Mexico and the Plurinational State of Bolivia) illustrate the problems that this population group faces in accessing the labour market.

Among the barriers faced by persons with a disability in participating in the workforce are education gaps related to exclusion from formal education and training, a lack of accessibility and reasonable accommodations in the workplace, and attitudinal barriers, which are reflected in discrimination and prejudice (Bietti, 2023; ECLAC, 2022d). Although the countries of Latin America have adopted a variety of measures to ensure the right to work of persons with a disability, such as establishing quotas to reserve job positions, providing incentives to employers, and implementing technical and professional training programmes, challenges remain (Bietti, 2023). In addition, when persons with a disability are hired, their jobs are usually informal, unstable, precarious and poorly paid (ECLAC, 2021). The fact that these barriers are higher based on factors that include gender, ethnic and racial status, place of residence and age is evidence of the intersectionality of the social inequality matrix in the region (ECLAC, 2016).

Figure II.9

Latin America (5 countries): employment rate, by disability status, 2019 and 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Household Survey Data Bank (BADEHOG).

Note: Owing to the different ways in which countries measure disability, the recommendation of the Washington Group on Disability Statistics on constructing a comparable dichotomous variable is followed in order to standardize the surveys. For more information, see Washington Group on Disability Statistics (2020).

The COVID-19 pandemic raised these barriers and placed even more obstacles in the way of persons with a disability seeking work, including through its negative repercussions on the informal labour market. Given that many persons with a disability work in informal jobs, the impacts of the pandemic crisis for this population segment were worse (RIADIS and others, 2022). Their labour vulnerability in the face of different types of crises is evidence of the need to ensure their labour participation and also foster their labour inclusion, not only by encouraging them to seek employment but also by ensuring their right to decent work on an equal basis with the rest of the population. Ensuring the labour inclusion of persons with a disability is both a duty of States Parties to the Convention on the Rights of Persons with Disabilities and a key aspect of inclusive social development.

(e) Labour inclusion for Afrodescendent and Indigenous populations: intractable exclusionary obstacles

In Latin America and the Caribbean, ethnic and racial status are a driving force in the social inequality matrix, a situation that is reflected in the features of the labour inclusion of Afrodescendants and Indigenous Peoples. Both populations face a variety of labour market inequalities stemming from the various expressions of racism, discrimination, prejudice and stereotyping that they have historically faced.

Although the labour participation rates of Afrodescendent and Indigenous persons do not differ significantly from those of their peers, there are differences in the characteristics of that participation, in particular in the presence or absence of obstacles to accessing decent jobs, meaning labour inclusion. While the unemployment rates for Afrodescendants are significantly higher than those of their non-Indigenous and non-Afrodescendent peers, the contrary is true for Indigenous Peoples (see table II.1). Analysis of this indicator between 2019 and 2022 shows a variety of situations in the countries for which data are available, but generally speaking, the variations recorded can largely be attributed to labour market trends rather than to any increase or decrease in racial and ethnic divides.

Table II.1

Latin America (9 countries): unemployment,a by ethinicity and race, around 2019 and 2022

(Percentages)

2019

2022

Bolivia (Plurinational State of)

Non-Indigenous

3.6

4.1

Indigenous

1.4

2.2

Brazil

Neither Afrodescendent nor Indigenous

6.1

4.8

Indigenous

7.5

7.5

Afrodescendent

8.8

6.9

Chile

Non-Indigenous

5.1

6.1

Indigenous

5.5

6.8

Colombia

Neither Afrodescendent nor Indigenous

7.1

8.7

Indigenous

5.3

6.2

Afrodescendent

8.4

10.7

Ecuador

Neither Afrodescendent nor Indigenous

2.2

2.7

Indigenous

0.8

1.4

Afrodescendent

5.8

4.7

Mexico

Non-Indigenous

2.1

2.2

Indigenous

1.5

1.6

Panama

Neither Afrodescendent nor Indigenous

3.9

5.3

Indigenous

3.1

4.2

Afrodescendent

4.6

7.1

Peru

Neither Afrodescendent nor Indigenous

2.2

3.3

Indigenous

1.6

2.0

Afrodescendent

2.3

2.6

Uruguay

Neither Afrodescendent nor Indigenous

5.5

5.0

Indigenous

6.0

6.9

Afrodescendent

8.0

8.3

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Household Survey Data Bank (BADEHOG).

a Unemployed persons aged 15 and over.

Both Afrodescendants and Indigenous persons are overrepresented in jobs characterized by low productivity, low pay and higher rates of informality. As a consequence, the rates of social security enrolment and contribution of both populations are lower than those of their non-Afrodescendent, non-Indigenous peers (see box II.2) (Huepe, 2023; Pedrero, 2023). As shown in figure II.10, Indigenous workers are overrepresented in the lowest labour income quintiles in comparison with the rest of the population. The situation of the Afrodescendent population varies from country to country.

Box II.2

Indigenous Peoples and their economies

The right to self-determination of Indigenous Peoples presupposes that they may freely pursue their own economic and social development. By virtue of this, Indigenous Peoples have demanded in multiple international forums that their economies be considered as a central component of a counter-hegemonic revisioning of civilization that has the potential to confront the structural causes of the major problems affecting humanity today.

The economies of Indigenous Peoples aim to guarantee the harmonious co-existence of all beings that share Indigenous lands, through consensual social, political, symbolic, residential and productive relationships.

Although these economies are grounded in the ancestral lands of Indigenous Peoples, their influence extends beyond the limits of those lands through mechanisms that facilitate trade, cooperation and reciprocal relations with other Indigenous communities. More or less regularly, these economies also form part of local, regional or national commercial networks and can draw from the material contributions of those who have emigrated to cities to sustain the productive systems of communities of origin.

Some of the additional resources that flow into Indigenous economies can originate from the participation of community members in foreign labour markets that are established or operate in Indigenous territories, with or without the consent of local Indigenous organizations, and without community oversight.

To ensure participation in trade or market circuits, Indigenous Peoples’ economies provide parallel services, such as transportation, storage and intermediation, internally or through external providers.

One of the greatest problems faced by Indigenous Peoples in the development of their own economies is the weakness of the mechanisms for the protection of their territorial rights. This allows various stakeholders, both State and private, to dispute territorial control over communities, either under the protection of domestic regulations and policies or, in many cases, by intentionally breaking the law, while governments tacitly consent or turn a blind eye.

In this context, for Indigenous economies to develop, progress must be made in two parallel processes: the recognition, protection, collective titling, demarcation and rehabilitation of Indigenous territories; and the establishment of the political and institutional conditions that enable Indigenous Peoples to exercise the right to self-government in their territories and to manage the natural resources located therein.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of M. Pedrero, “Hacia una recuperación económica transformadora de América Latina-Abya Yala: desafíos para garantizar los derechos colectivos de los pueblos indígenas”, Project Documents (LC/TS.2023/35), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2023; and Ford Foundation.

Figure II.10

Latin America (7 countries):a distribution of male and female workers, by ethnicity and race and lowest and highest income quintile, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Household Survey Data Bank (BADEHOG).

This is explained in part by horizontal and vertical labour market discrimination —which determines the concentration of Afrodescendent and Indigenous people employed in low-paid and low-quality jobs and economic sectors, at lower levels of the organizational hierarchy compared to their non-Afrodescendent and non-Indigenous peers— and by the shorter average working day in the case of employed Afrodescendent people (especially women) (Holz, Huepe and Rangel, 2022).

(f) The role of the minimum wage in fostering labour inclusion

Along with hours worked, remuneration is the aspect of working conditions that has the most direct and tangible impact on workers’ daily lives. The minimum wage in particular is essential for protecting people from inappropriately low wages and thus guaranteeing that they receive decent income for their work.[3] Without wage regulations, employed persons can be exploited at work and may not be able to meet their basic needs.

The minimum wage must be designed and set up to complement and strengthen other social and labour policies aimed at establishing decent working conditions, such as collective bargaining policies. A minimum wage can also be an essential part of strategies to combat poverty, reduce inequality gaps and address gender-based income disparities. This integration of labour and wage policies is fundamental for the establishment of a more just and equitable labour environment and for fostering labour inclusion and therefore inclusive social development.

Despite the importance of the issue, it is estimated that the wages of some 92 million workers in 14 countries in the region were below the official minimum in 2022, either because their occupation was unregulated —as in the case of informal workers— or because of non-compliance with regulations. Notably, this figure was up from pre-pandemic levels, having risen from 32.6% in 2019 to 36.8% in 2022 (the equivalent of 13 million more workers over the age of 15) (see table II.2). Women outnumber men among workers earning below the minimum wage in the region (44.1% compared with 31.4%, respectively, in 2022), and the situation affects young and older people in particular.

Table II.2

Latin America (14 countries):a employed persons aged 15 and over whose labour income is below the minimum wage, around 2019 and 2022

(Percentages)

Year

Total

Sex

Age group

Men

Women

15–29 years

30–64 years

65 years and over

2019

32.6

27.0

40.2

38.3

28.2

59.7

2022

36.8

31.4

44.1

43.2

32.4

63.2

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Household Survey Data Bank (BADEHOG).

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Mexico, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

There is a worrisome wage disparity between occupational categories that highlights the sectors in which precarious labour is predominant. In 2022, 63.1% of domestic employees, mostly women, were paid less than the established minimum wage (see chapter III). Next came workers who were self-employed, of whom 58.5% were in the same situation. Lastly, 22.2% of wage earners were also in this situation, reflecting a problem that transcends individual employment modalities (see table II.3).

Table II.3

Latin America (14 countries):a employed persons aged 15 and over whose labour income is below the minimum wage, by occupational category and formality status, around 2019 and 2022

(Percentages)

Year

Wage earners

Self-employed workers

Domestic employees

Formality status

Formal

Informal

2019

14.6

52.0

60.9

9.9

53.3

2022

22.2

58.5

63.1

14.9

59.6

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Mexico, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

Analysing the percentage of workers who receive less than the minimum wage by employment formality also reveals significant differences. Data from 14 countries in the region show that in 2022, 60% of informal sector workers earned less than the stipulated minimum wage, compared with 15% of those employed in the formal sector (see table II.3). This gap highlights the urgent need to implement labour inclusion policies that not only promote the formalization of employment, but also guarantee decent wages in line with minimum welfare standards for all workers, regardless of their employment status.

B. Labour informality in Latin America and the Caribbean: emerging and existing barriers to labour inclusion

Almost half of the workers in Latin America and the Caribbean are in informal employment. Informality is a structural and enduring characteristic of the region’s labour markets that hinders labour inclusion by putting workers in a vulnerable position in terms of income, working conditions, labour rights and social protection. Informal employment has a more pronounced impact on young people, less skilled workers, and women, perpetuating the inequality that already existed before the crisis caused by the COVID-19 pandemic, centred around the structural axes of the region’s social inequality matrix. Likewise, new non-standard forms of employment related to changes in the labour market and ongoing technological transformations are creating new challenges that must be overcome to reduce the informality and inequality that hamper labour inclusion.

Informality is a structural and enduring characteristic of Latin American and Caribbean labour markets (Salazar-Xirinachs and Chacaltana, 2018). According to ECLAC estimates based on employment surveys in 12 countries in the region, 49% of workers (121 million people) were in informal work in the fourth quarter of 2022 (see annex II.A2).

Informality encompasses all occupations and forms of production performed by people who are not covered or regulated by a legal framework, do not make required tax payments, have no social protection coverage and lack employment-related entitlements (ECLAC, 2022b; ILO, 2021). This situation puts workers in a highly vulnerable position in terms of income, working conditions, access to labour rights and social protection (Espejo, 2022; ILO, 2022a). Generally speaking, informality is not the result of a preference for self-employment or workers’ economic rationale. Instead, it is often the only possible means of joining the labour market (ECLAC, 2008 and 2022b). The limited capacity of higher-productivity sectors to absorb labour by creating formal jobs leads to highly segmented access to high-quality employment and social protection, considerable household income inequality and deep-rooted sexual division of labour (Abramo, 2021; Infante, 2011).

1. The impact of informality on households

In the 2000s, there was gradual formalization in the region, amid faster economic growth, higher demand for labour and specific public policies to foster formal work (ECLAC/ILO, 2014). In the 2010s, formalization slowed —and even reversed in some cases— in a new context of economic stagnation and weakening labour indicators. The informality rate in the region, which in 2012 stood at almost half of all workers, remained at a similar level over the 2017–2019 period; therefore, the labour outlook was already bleak before the health crisis caused by COVID-19 (Maurizio, 2021; ILO, 2021).

While both informal and formal employment declined considerably with the onset of the pandemic, the fall in the former was larger. In Argentina, Mexico and Paraguay, for example, the drop in informal jobs accounted for more than 80% of the overall decline in employment in the first half of 2020 (ILO, 2021). When formal employment falls, informal employment generally rises, playing a countercyclical role, but for the first time in an economic crisis in the region, informal employment was neither an employment buffer nor a haven for those who lost their wage employment (Acevedo and others, 2021; Maurizio, 2021; ILO, 2021). This decline in informal employment affected young people, less skilled workers and women to a greater degree.

According to ECLAC data based on employment surveys from 12 countries in the region, the average informal employment rate was around 50% between 2019 and 2022, but it fell by roughly 1 percentage point from 50.1% in the fourth quarter of 2021 to 49% in the same quarter of 2022. Figure II.11 shows how the informal employment rate has changed, taking 2019 as a baseline. There was an initial decline between the first and second quarters of 2020 and a subsequent recovery to pre-pandemic levels by the end of 2021, before the drop of almost 1 percentage point in 2022.

Figure II.11

Latin America (12 countries):a change in the informal employment rate, first quarter 2019–fourth quarter 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of regional employment surveys.

Note: Weighted average.

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Mexico, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

Problems related to informality extend beyond individuals, affecting households as well. According to ILO and the Organisation for Economic Co-operation and Development (OECD, 2019; OECD and others, 2023), whether those in a household are in formal or informal employment may have repercussions for the dependent members of the household, as social security systems often cover the spouse or children of the person paying into the system, meaning that households with only informal workers are more vulnerable than those with both formal and informal workers. Therefore, traditional indicators based on individual workers or firms do not capture, on their own, the extent of the impact of informality (OECD/ILO, 2019).

According to data from employment surveys in the region, prior to the pandemic (second quarter of 2019), 50.2 million households (39% of the total) —17.8 million headed by women— depended entirely on informal employment and 25.5 million households (20% of the total) had members in both the formal and informal sectors. This means that, in Latin America and the Caribbean, 75.8 million households (58% of the total) depended entirely or partially on informal employment, and another 54.4 million households (the remaining 42%) depended entirely on formal employment. As previously mentioned, the fall in informal employment in 2020 led to fewer households —a drop of around 16 million— depending entirely or partially on informal employment. Data for the second quarter of 2022 show numbers and rates similar to those recorded before the pandemic (see figure II.12).

Figure II.12

Latin America (11 countries):a number and composition of households by type of occupation of household members, second quarter 2019–second quarter 2022

(Millions of households)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Household Survey Data Bank (BADEHOG).

a Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Mexico, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

The rate of informality for households also varies from country to country. The proportion of households that depend entirely on work in the informal sector ranges from 14.3% in Uruguay to 74% in the Plurinational State of Bolivia, while the percentage of households that depend on both informal and formal work ranges from 13.9% in the Plurinational State of Bolivia to 28.5% in Paraguay.

An analysis of the distribution of dependants by type of household reveals the harmful repercussions of informality for the well-being of the non-working population.[4] Most children aged under 15 and people aged 65 and over (61.2%) live in households that depend solely on informal work or households that depend on a mix of formal and informal work, while the rest (38.8%) live in households that rely entirely on formal work.

2. Changes in the composition of informal employment reflect the COVID-19 pandemic and enduring unequal distribution

In the region, informality is intermeshed with inequality and there are severe gender, socioeconomic, age-related, ethnic and racial, and territorial inequalities. These structural axes of the inequality matrix are intertwined, feed into each other and string together over the life cycle. Ultimately, they influence other areas of well-being and rights, in addition to levels of access to decent work (ECLAC, 2016).

Between 2019 and 2022, informality rates increased for men and for urban areas, while those for women decreased. According to ECLAC (2023a), this could be a result of the sharper rise in women’s wage employment in the private sector, which was offset by a significant drop in employment in domestic work and as contributing family workers. However, women are overrepresented in the most vulnerable jobs in the informal economy, for example, as domestic workers, contributing family workers or digital platform workers providing services in private households (see chapter III) (OECD/ILO, 2019; Berg, 2016). Indeed, although some countries in the region have made progress in formalizing such employment, there are still many workers, particularly women, who work under informal arrangements outside the scope of State regulation and labour inspection (ILO, 2016).

Informality rates fell in rural areas overall, as a result of the significant reduction in the indicator for women (3.1 percentage points), which far outweighed the increase for men (0.8 percentage points). Conversely, informality rates climbed slightly in urban areas, because the increase among men (1.1 percentage points) was greater than the drop among women (0.7 percentage points). Despite the larger increase in informal employment in urban areas, gaps remain to the detriment of rural areas, where levels of informal employment are higher. According to ECLAC estimates for the fourth quarter of 2022, the percentage of people employed in informal jobs in Latin America was higher in rural areas than in urban areas (71.1% compared to 44.1%) (see figure II.13).

Figure II.13

Latin America (12 countries):a labour informality rate, by sex, age group and geographic area, fourth quarter 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Household Survey Data Bank (BADEHOG).

a Argentina, Bolivia (Plurinational State of), Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Paraguay, Peru and Uruguay.

The prevalence of informal employment varies across the different stages of the life cycle and it has a disproportionate impact on young people and older workers. The resulting pattern is a U-shaped curve (Espejo, 2022). Thus, while more than 50% of young people and 70% of older workers are in informal employment, 43% of people aged 30–44 are in the same situation (see figure II.13). Informality in the countries of the region, particularly among young people and older persons, often takes the form of self-employment, which in fact accounts for most of the employment in this segment and tends to offer limited opportunities to transition to formal work. Workers and employers, in contrast, tend to have more formalization opportunities, which increase progressively over the life cycle up to retirement age and then decline (Chacaltana, Bonnet and Leung, 2021).

Informal workers are four times more likely than formal workers to belong to low-income households. On average, in the six countries for which comparable data are available in 2022 (Argentina, Brazil, Dominican Republic, Ecuador, El Salvador and Peru), the proportion of workers in the poorest income quintile is around 4.1% for formal workers and 18.9% for informal workers (see figure II.14).

Figure II.14

Latin America (6 countries):a distribution of formal and informal workers by household income quintile, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Argentina, Brazil, Dominican Republic, Ecuador, El Salvador and Peru.

The sizeable wage gap between formal and informal workers explains, in part, the higher proportion of informal workers in the first few income quintiles. On average, in the six countries for which data is available, the average wage of formal workers is 3–4 times the average wage of informal workers (only considering salaries and wages), revealing a considerable wage disadvantage related to informality. Lower levels of education, less social protection coverage, lower productivity and overrepresentation in occupations or sectors with lower wages are some of the distinguishing characteristics of informal workers when compared to formal workers.

3. Informality on digital labour platforms: deepening inequalities and opening up new gaps

Factors such as changes in the labour market and technological transformations have created new non-standard forms of employment that change the context in which informality and its relationship with labour inclusion and social protection are analysed, by widening existing access gaps and creating new ones. These emerging jobs include those referred to in the literature as “digital platform work” or the “gig economy”. Increased use of digital technologies (such as laptops, tablets, and smartphones) —a process that accelerated during the COVID-19 pandemic— has created the conditions for growth in a wide range of services offered through digital platforms, connecting supply with demand (Huepe, 2023).

These digital environments can be classified as global platforms, if services are delivered digitally or in the cloud, or location-based platforms, if services are provided locally (ECLAC/ILO, 2019). The two most common examples of location-based services are home delivery and passenger transport. The different types of location-based platforms share some characteristics, such as not having a standard full-time or part-time working day, flexible working hours, a working day comprising paid and unpaid (waiting) hours, and variable income.

This new form of employment has gradually expanded worldwide. Some estimates suggest it accounts for the work of around 10% of the labour force in European countries and approximately 9.4% in Latin America[5] (Eurofound, 2020; Aibar, 2019; Álvarez and others, 2020). According to ILO (2021), the number of digital platforms quintupled between 2010 and 2020, reflecting the rapid growth in demand for these new jobs, their swift development to date, and the future potential they represent for the labour market.

Data from various surveys that characterize this type of worker show that they are generally young (aged 35–40 years) and primarily men. Women represent between 10% and 33% of platform workers, approximately (Berg and others, 2019; ILO, 2021) (see chapter III). Most platform workers have some form of higher education (Berg and others, 2019; Azuara, González, and Keller, 2019; Álvarez and others, 2020) and face changeable work schedules and highly variable income, especially when including unpaid hours. Lastly, available information on platform workers shows limited access to social protection. Based on an international survey of 3,500 workers in 2017, Berg and others (2019) found that 39% had no health insurance and 65% had no pension coverage (for disability, old age or death). Similarly, in Latin America just one-third of workers offering transport services through digital platforms contribute to a pension system, and less than half contribute to a health system (Azuara, González and Keller, 2019).

The ever-faster expansion of digital platform work poses significant challenges to be overcome to ensure decent work and labour inclusion. This form of work also creates new challenges for social protection systems (Robles, Tenenbaum and Jacas, 2023). First, changeable hours lead to job insecurity and income instability, as total paid hours and the amount of remuneration are both uncertain (Forde and others, 2017). Second, the lack of consensus on how to categorize the labour relationship between the platform and the worker, in particular whether or not such workers can be considered employees, can lead to considerable conflict and vulnerability for the workers themselves (Berg, 2016; Forde and others, 2017; OECD, 2019; ECLAC/ILO, 2021a). In the vast majority of cases, workers on digital platforms are considered to be freelancers or self-employed, even though their work is supervised and there is an employment relationship with respect to the customer, in terms of receipt of payments and evaluation and possible unilateral termination by the platform (ILO, 2016). One crucial result of not recognizing the labour relationship is that platforms are not responsible for workers’ safety or social protection. The situation is even more alarming in the region, as digital platform work represents workers’ main job in many Latin American countries for which information is available (ECLAC/ILO, 2021a).

C. Strategies to promote labour inclusion: implementing labour policies to move towards inclusive social development

Countries have a set of tools to respond to crises that affect labour markets and hinder labour inclusion. Labour inclusion policies in Latin America and the Caribbean have aimed to increase the rates at which the most vulnerable groups of the population join the labour market, through measures to reduce barriers to access (such as training and capacity-building for workers), make it easier to find work, and ensure access to job opportunities. These policies also aim to ensure labour inclusion of the most vulnerable population groups through access to decent working conditions. Between 2020 and 2022, as a result of the crisis caused by the COVID-19 pandemic, passive labour market policies where first implemented, focusing on income protection, then in 2021 active policies were prioritized, centred around job creation. Lastly, in 2022, policy sought to protect incomes from inflation and foster job creation, including through public employment programmes. To ensure that labour inclusion policies are financially sustainable —in a situation still characterized by challenges derived from the crisis— a sound institutional framework for labour policy is needed, together with comprehensive regulations and the capacity to comply with those regulations. This will strengthen the institutional capacity at the national and subnational levels of government in terms of technical capabilities, resources and decision-making.

In response to the multiple crises that have afflicted the region in the past, countries have implemented social programmes to foster labour inclusion, especially for those living in poverty or vulnerable situations and those who are affected by social exclusion. In some cases, the programmes have attempted to address the repercussions of economic crises, as was the case of the direct employment programmes designed in the wake of the debt crisis of the 1980s (Abramo, Cecchini and Morales, 2019) or, more recently, the measures adopted in response to the COVID-19 pandemic (Atuesta and Van Hemelryck, 2022; Velásquez, 2021a). In this context of the pandemic-induced crisis, some countries in the region implemented differentiated and comprehensive labour inclusion policies to bolster social protection for the most vulnerable. These strategies included new measures, efforts to adapt existing measures or make them more flexible, and expanded coverage of ongoing labour inclusion programmes to address the changes caused by the cascading crises (Robles and others, 2023).

Implementation of labour policies between 2020 and 2022 can be divided into three phases (ECLAC/ILO, 2021b and 2023; ILO, 2023b). The first phase, in 2020, focused on adoption of passive labour market policies, centred around supporting formal employment and incomes by easing unemployment insurance requirements, and programmes to provide financial security for families and informal workers. The second phase, in 2021, was one of active policies, emphasizing job creation and income protection, paying special attention to the most vulnerable groups, such as women and youth. The third phase, in 2022, was characterized by more planning and focused on protecting incomes from inflation and encouraging job creation, including through public employment programmes.

Design and implementation of these labour inclusion policies form part of efforts to meet target 8.3 of Goal 8 of the 2030 Agenda for Sustainable Development. That Goal is to “promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all”. Labour inclusion policies in the region have therefore pursued two main objectives. The first is to increase labour market access for the most vulnerable population groups. Programmes therefore aim to remove or reduce labour market access barriers through measures that improve training and capacity-building for workers, make it easier to find work, and ensure access to job opportunities. Ultimately, the goal is to counteract the effects of the structural axes of the social inequality matrix and the transformations underway in multiple dimensions.

These policies also aim to ensure labour inclusion of the most vulnerable population groups through access to decent working conditions. This entails ensuring workers have access to social protection, health coverage and other benefits that protect them against occupational risks. Access to the labour market is expected to be through productive jobs, which is to say those that provide a suitable income —at least above the poverty line— and in which workplace safety is guaranteed (protection of workers against occupational accidents, occupational diseases and other health and safety risks in the workplace).

The areas of action of the labour inclusion programmes implemented by the countries can be classified as shown in diagram II.4. First, there are active labour market policies that generally aim to increase the chances of obtaining employment, receiving higher labour income, working in higher quality jobs in terms of formality, hours and duration of employment, and to foster development and updating of workers’ skills and competencies (Espejo and others, 2023b).

Diagram II.4

Types of labour inclusion policies and programmes

Source: A. Espejo and others, “Políticas activas de mercado de trabajo en América Latina: desafíos para la inclusión laboral con protección social”, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2023, in press; on the basis of Economic Commission for Latin America and the Caribbean/International Labour Organization (ECLAC/ILO), “Conditional transfer programmes and the labour market”, Employment Situation in Latin America and the Caribbean, No. 10 (LC/L.3815), Santiago, 2014; and S. Ruesga and others, Economía del trabajo y política laboral, Madrid, Ediciones Pirámide, 2014.

This group of initiatives can be subdivided into supply-side, demand-side and labour intermediation policies. Programmes to improve labour supply include those that provide technical and vocational training to individuals, thus boosting their learning and development of transferable skills and competencies. This area of action also covers programmes of adult education or academic levelling studies for adults and those to promote school retention, from primary to tertiary education. Programmes to boost labour demand include those that promote self-employment through financial support, microcredit or in-kind transfers to start or expand freelance activities or microenterprises. Programmes also exist that create jobs directly through public employment plans at different levels, generally on a temporary basis or as part of development plans for public works or infrastructure projects. This area also encompasses programmes to create jobs indirectly, whereby governments offer financial subsidies for hiring people outside the labour force (Abramo, Cecchini and Morales, 2019) and labour market access is linked to social security access through measures such as employment subsidies to cover a portion of wages or social security contributions. The third group of active labour market policies relate to labour intermediation services, which provide information to job seekers and recruiters, and to those who offer support and guidance to either (for example, preparing for interviews or writing résumés).

The second type of policies comprises passive labour market measures, which provide income replacement, particularly for the unemployed. These measures are a vital part of social protection systems, as they safeguard workers by reducing and mitigating risks related to a lack of labour inclusion. Among the main measures are income support for unemployed people, which may take the form of unemployment insurance, individual unemployment savings accounts, severance pay or income protection in the event of dismissal, focusing on the most vulnerable groups.

Lastly, it is important to consider policies on institutional frameworks for labour policy, which usually fall under the authority of ministries of labour and social security and comprise different legal provisions related to guaranteeing rights and working conditions. These include policies on minimum wages, mandatory benefits, social security, occupational health and safety, job security, non-discrimination, prohibition of child labour and regulation of adolescent labour, the right to strike, and all the regulatory and institutional aspects that govern this area (Samaniego, 2002).

1. Strengthening active labour policies to move from labour market access to labour inclusion

Active labour market policies are government actions (sometimes in conjunction with the private sector) that generally aim to expand employment opportunities, increase labour income and improve job quality of in terms of formality, hours and duration of employment, and to foster development and updating of workers’ skills and competencies (Espejo and others, 2023b). Information from the Non-contributory Social Protection Programmes Database - Latin America and the Caribbean[6] shows a marked rise in active labour inclusion programmes in 22 countries over the past decade, primarily overseen by labour ministries and ministries of social development (see more information in chapter IV). Between 2010 and 2019, such programmes increased in number from 70 to a high of 121. There was a slight decline from 2019 to 2022, characterized by some programmes being shut down, new ones being created and, in Argentina, actions being unified through flagship programmes (see figure II.15).[7]

Figure II.15

Latin America and the Caribbean (22 countries):a labour inclusion programmes, 2010–2022

(Numbers)

Source: N. Figueroa and R. Holz, “Las persistentes brechas de protección social en la región”, El futuro de la protección social ante la crisis prolongada en América Latina: claves para avanzar hacia sistemas universales, integrales, resilientes y sostenibles, Social Policy series, C. Robles and R. Holz (coords.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2023, in press; on the basis of ECLAC, Non-contributory Social Protection Programmes Database in Latin America and the Caribbean [online] https://dds.cepal.org/bpsnc/lpi.

Note: The estimate includes conditional transfer programmes that allow recipients to access entitlements from labour inclusion programmes. In particular, Mexico’s Prospera (2014–2019) programme, the Dominican Republic’s Progresando con Solidaridad (in place since 2012) and El Salvador’s Comunidades Solidarias (2005–2016) are included. The estimate does not include the new COVID-19 pandemic emergency cash and in-kind transfer measures with labour inclusion components.

a Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Saint Vincent and the Grenadines, Trinidad and Tobago and Uruguay.

Labor inclusion policies in Latin America and the Caribbean are aimed at different stages of the life cycle, and particularly at the unemployed and those in informal employment. In 2022, 31 of the 120 programmes identified (around a quarter) aimed to foster inclusion of young people in the labour market. Despite the extent of the programmes aimed at this population segment, further efforts must be made to improve labour market inclusion of young people, given the significant gaps they face in labour market access, as noted in the second section of this chapter (see section 2.b). Some programmes have the purpose of meeting the needs of specific population groups that face multiple barriers to labour market entry. As shown in figure II.16, 19 of the programmes in place in 2022 fostered labour inclusion of persons with disabilities, 15 prioritized or focused solely on labour inclusion of women, 13 focused on Indigenous Peoples, and 4 programmes related to inclusion of Afrodescendants. In addition, 7 programmes were aimed at people living in rural areas and 5 at those living in urban areas. Although this demonstrates that the countries take into account the structural axes of the social inequality matrix when designing measures, more affirmative actions must be pursued to break down barriers to entry and thus ensure the labour inclusion of population groups that experience multiple forms of inequality, discrimination and exclusion (Espejo and others, 2023b).

Technical training and support for self-employment are the most common types of initiative in the region. Of 117 labour inclusion programmes recorded in 2022, 79 (39%) provided technical and vocational training and 48 were measures to support self-employment (23%). Indirect job creation programmes were next (21 programmes, or 10%), followed by adult education and initiatives to encourage students to remain in school (10 programmes, or 5%) and direct job creation initiatives (9 programmes, or 4%). There were 38 programmes (19%) that included labour intermediation services (see figure II.17). This distribution suggests that although technical and vocational training is the main focus of programmes to improve labour market access and working conditions, other strategies are recognized and valued.

Figure II.16

Latin America and the Caribbean (22 countries):a labour inclusion programmes by population group, 2022

(Number of programmes)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Non-contributory Social Protection Programmes Database in Latin America and the Caribbean [online] https://dds.cepal.org/bpsnc/lpi.

a Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Saint Vincent and the Grenadines, Trinidad and Tobago and Uruguay.

b These programmes are solely for the labour inclusion of women, rural residents and urban residents.

Figure II.17

Latin America and the Caribbean (21 countries):a components of labour inclusion programmes, 2022

(Percentages and number of programmes)

Source: N. Figueroa and R. Holz, “Las persistentes brechas de protección social en la región”, El futuro de la protección social ante la crisis prolongada en América Latina: claves para avanzar hacia sistemas universales, integrales, resilientes y sostenibles, Social Policy series, C. Robles and R. Holz (coords.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2023, in press; on the basis of ECLAC, Non-contributory Social Protection Programmes Database in Latin America and the Caribbean [online] https://dds.cepal.org/bpsnc/lpi.

a Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Guatemala, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Saint Vincent and the Grenadines, Trinidad and Tobago and Uruguay.

The information in figure II.18 shows that the focus of labour inclusion programmes varies depending on the age group that they target (Espejo and others, 2023b). The main component of programmes aimed solely at young people is technical and professional training, the focus of 42% of the programmes intended for this population segment. Labour intermediation services are next (24%), followed by indirect job creation (19%) and initiatives to support self-employment (8%). While 5% of programmes involve flexible learning and initiatives to encourage students to remain in school, direct job creation accounts for just 2%. In the case of programmes aimed at both adults and young people, technical and professional training is also prevalent, although less so (37%). In this group of programmes, support for self-employment accounts for 29%,[8] followed by labour intermediation services at 16%. While the indirect job creation component accounts for 7%, flexible learning, initiatives to encourage students to remain in school and direct job creation account for 5% each. These data suggest that despite the variety of labour market inclusion approaches, technical and professional training are key for both age groups. This shows that interventions need to be tailored to the skills required in the labour market and that a life-cycle approach is also important. Knowing what skills are in demand in the productive sector and what labour market demand will look like in the future is also key for designing and implementing programmes in order to anticipate priority areas for training, while mainstreaming the gender perspective.

Figure II.18

Latin America and the Caribbean (21 countries):ᵃ components of labour inclusion programmes, by target population, programmes in effect in 2022

(As a percentage of programmes)

Source: N. Figueroa and R. Holz, “Las persistentes brechas de protección social en la región”, El futuro de la protección social ante la crisis prolongada en América Latina: claves para avanzar hacia sistemas universales, integrales, resilientes y sostenibles, Social Policy series, C. Robles and R. Holz (coords.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2023, in press; on the basis of ECLAC, Non-contributory Social Protection Programmes Database in Latin America and the Caribbean [online] https://dds.cepal.org/bpsnc/lpi.

a Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, Guatemala, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Saint Vincent and the Grenadines, Trinidad and Tobago and Uruguay.

2. The role of passive employment policies and challenges in coordinating them with active policies and coverage for informal workers

Passive labour market policies are strategies aimed at maintaining the income of unemployed persons. They are implemented in various ways in the region: (i) unemployment insurance; (ii) individual unemployment savings accounts; (iii) severance pay; and (iv) money transfers to unemployed persons. Historically, these measures have focused on formal workers. These instruments are considered comprehensive if they are able to guarantee a transfer that compensates for loss of income during a given period of unemployment and, if possible, supports the unemployed person to return to work (Tromben, Villanueva and Caillaux, 2023). Since employment income is an essential part of family budgets, they also cushion employees and their families from the worst consequences of unemployment (Velásquez, 2021a).

Despite their importance, only 10 of the 33 countries of Latin America and the Caribbean have unemployment insurance.[9] In terms of coverage, there are wide gaps between OECD countries, where these systems cover 61.3% of unemployed persons, and countries in the region, where only 10.6% are covered (Asenjo and Pignatti, 2019). This low coverage is a result of both the design of unemployment insurance systems, which exclude certain workers because they do not meet all requirements (for example not having made the minimum number of contributions), and the structure of labour markets, in which informality and self-employment hinder the ability to cover all unemployed persons (Weller and Gontero, 2016).

There is no question that the pressure placed on social protection systems by unemployment intensified considerably during the COVID-19 pandemic emergency, in particular in 2020. The responses of the seven countries in the region that have mandatory social protection systems for unemployment focused not only on increasing the number of recipients but also on paying out larger sums. The coverage provided by unemployment insurance systems during the pandemic was expanded in both absolute and relative terms in all countries studied except Brazil (see table II.4). More than 8.3 million workers were covered, 600,000 more than in 2019, leading to an 8% rise in the value of benefits. However, the increase in the number of recipients varied widely from one country to another. Chile saw the largest spike in the number of participants, adding 115,000 in 2020. In Uruguay, 66,000 more users were recorded, up by 147% from 2019, and the figures were similar in Ecuador. In Barbados, the number of recipients was up 370%, from 11,000 to 52,000. Regionally, of the seven countries studied, growth was lowest in Argentina (in both absolute and relative terms), while Brazil was the only country in which the number of participants fell in 2020. In 2021 and 2022, the number of recipients has fallen as labour indicators have improved.

Table II.4

Latin America and the Caribbean (7 countries): unemployment insurance recipients, 2019–2022

(Thousands of persons)

Country

Recipients

2019

2020

2021

2022

Argentina

110

125

138

47

Bahamas

11

52

20,3

8

Barbadosa

16

-

-

-

Brazil

7 351

7 294

6 841

6 921

Chile

189

304

337

178

Ecuador

18

461

447

-

Uruguay

45

111

66

-

Total

7 741

8 347

7 849

7 154

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official data from the respective countries.

a Number of applications during the year.

Informal workers with no unemployment insurance make up the so-called “missing middle”: their income is not low enough for them to be considered poor and access social programmes, but they also have no formal social security protection, leaving them completely exposed in the event of a crisis (Atuesta and Van Hemelryck, 2022).[10] Faced with this situation, informal workers received social protection during the pandemic through emergency money transfers using public funds. This was a design innovation compared with traditional social protection programmes, as it covered a population usually excluded because they were not in social security registries or had limited or non-existent ties to tax and social security systems (Velásquez, 2021b).

Many of the emergency measures for informal workers aimed to expand the social protection programmes in place prior to the pandemic, through conditional or unconditional money transfers, using digital platforms and technologies to identify the target population (Atuesta and Van Hemelryck, 2022). Although these transfers were initially conceived of as one-time payments or payments for up to three months, the seriousness of the crisis meant that they were extended in several cases.

Only in Colombia and Guatemala did the programmes targeting informal workers combine in-kind transfers with cash transfers. Honduras also made in-kind transfers without combining them with money transfers, while the rest of the countries only provided money transfers (see table II.5) (Atuesta and Van Hemelryck, 2022).

Table II.5

Latin America and the Caribbean (13 countries): emergency unemployment measures prioritizing informal workers, 2020 and 2021

Country

Description or name of the programme

Target population

Argentina

Emergency Family Income Programme

Households in which all members are unemployed or in the informal economy

Programme for new registrants

Private household workers and employers who register a new employment relationship

Brazil

Emergency assistance

Workers over 18 years of age, without a formal contract,

who do not receive social security or welfare entitlements

and have a monthly income below the established threshold

Chile

Universal Emergency Family Income

Social Registry of Households (RSH) that includes informal workers

Colombia

Solidarity Income

Highly vulnerable households, informal workers, furloughed workers, and 43,000 soldiers and police auxiliaries

Ecuador

Health Emergency Family Protection Grant because of COVID-19 in Ecuador

Families with members who are underemployed, with incomes

of less than US$ 400 per month

Grenada

Income support for workers in the informal sector

Persons who worked in a business in the informal sector prior

to the COVID-19 pandemic

Guatemala

Support for small local businesses

Informal vendors

Haiti

Transfers to informal workers

Population in situations of vulnerability working

in the informal sector

Paraguay

Pytyvõ

Informal self-employed workers or employees of micro-, small-

or medium-sized businesses

Peru

Grant for independent workers

Vulnerable households whose members are own-account and informal workers not on public- or private-sector payrolls

Saint Vincent and the Grenadines

Provisional assistance for workers in the informal sector

Informal workers

Uruguay

Operativo Canasta

Informal workers not covered by social security

Venezuela (Bolivarian Republic of)

“Discipline and Solidarity”grant

Informal sector workers

Source: B. Atuesta y T. Van Hemelryck, “Emergency social protection against the impacts of the pandemic in Latin America and the Caribbean: evidence and lessons learned for universal, comprehensive, sustainable and resilient social protection systems”, Project Documents (LC/TS.2022/143), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2022.

In short, the measures presented offer new possibilities for extending social protection in the event of unemployment for workers in sectors that are traditionally excluded. In that regard, experiences on the mechanisms adopted to address high unemployment should be studied to extract lessons that can guide the design and implementation of these programmes in the immediate future (Velásquez, 2021b).

3. Social institutional frameworks and the financial sustainability of labour inclusion policies

Analysis of the labour inclusion programmes implemented in the countries of Latin America and the Caribbean illustrates the diversity of strategies and the many responsibilities at play with this type of intervention. Technical and professional training is the most important strategy for offering high-quality instruction focusing on the skills in highest demand in the labour market. Clearly, it will also be important to adopt other approaches that consider the region’s growing and shifting structural risks. To achieve this, it should be borne in mind that even though encouraging self-employment could provide a path towards short-term labour inclusion, it is not a guarantee of steady income and decent working conditions. These programmes should provide continuous support to develop the skills and experience of participants (Abramo, Cecchini and Morales, 2019). With regard to job creation programmes, although they can be useful where demand for labour is low, they are not a medium-term solution for enhancing labour inclusion (Velásquez, 2021b).

With respect to the target population for job creation, labour inclusion strategies must take into account factors that relate to stage of life and affect demand. The characteristics and needs of the target population must be taken into consideration in designing and implementing labour inclusion programmes. This entails the adaptation of programmes based not only on the life-cycle approach but also on a universalist approach that is sensitive to differences. These programmes are managed by different entities, from ministries (such as labour or social development ministries) to social investment funds and other bodies. Studying programme implementation shows that ministries of labour and social development play a key role, although other subnational entities and institutions also contribute significantly. Accordingly, implementing labour inclusion policies requires a high level of coordination between agencies and between the public (local government) and private sectors.

Previous experience confirms that labour inclusion policies are needed to confront the current challenges (see table II.6). The region’s experience prior to the pandemic in fostering labour inclusion to meet social protection coverage challenges illustrates the versatility of countries in devising such policies. Despite differences in approaches and responsibilities, all these programmes share a common goal that should be the focus of countries’ management efforts: cooperating to improve job opportunities and working conditions for target populations. In that regard, these programmes share a commitment to promote the labour inclusion of the region’s most vulnerable populations, one that should deepen in the coming decades in the context of major transformations. In light of the aforementioned panorama, a set of public policy recommendations can be made to strengthen labour inclusion.

Table II.6

Public policy recommendations to strengthen labour inclusion

Area

Policy category

Policy or instrument

Objective

Active policies

Demand

Job creation incentives

Hiring subsidies

Higher job market participation

Support for establishing businesses

and for self-employment

Labour supply

Job search and retention incentives

Employment-linked entitlements

and subsidies

More people working and fewer quitting;

encouraging closer ties with the labour market and providing income support

Conditional activation and entitlements

Higher job market participation

Affirmative action policies to specifically address the needs of populations facing structural barriers and inequalities

Training and skill-building

On-the-job training

More people working, higher productivity and job fitness

Labour intermediation services

Adaptation to the job market

Help with job-seeking

More people working, more efficient job search processes and job fitness

Guidance and oversight

Intermediation between job seekers

and employers

Passive policies

Economic security for unemployed persons

Unemployment or redundancy insurance (contributory)

Providing temporary financial support

for workers who are laid off

Cash transfers for unemployed persons

Providing temporary income protection

Labour-related institutional frameworks

Labour inspections

Labour inspections and audits

Guaranteeing compliance with labour and safety regulations at work and protecting worker rights and working conditions

Working conditions

Minimum wage

Improving and guaranteeing a decent level

of income sufficient to cover basic needs

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of A. Brown and J. Koettl, “Active labor market programs - employment gain or fiscal drain?”, IZA Journal of Labor Economics, No. 4, Berlin, Springer, 2015; A. Espejo and others, “Políticas activas de mercado de trabajo en américa latina: desafíos para la inclusión laboral con protección social”, Santiago, ECLAC, 2023, in press; International Labour Organization (ILO), World Employment and Social Outlook: Trends 2022, Geneva, 2022; Organisation for Economic Co-operation and Development (OECD), “Designing active labour market policies for the recovery”, OECD Policy Responses to Coronavirus (COVID-19), Paris, 2021 [online] https://www.oecd.org/coronavirus/policy-responses/designing-active-labour-market-policies-for-the-recovery-79c833cf/; C. Robles and R. Holz (coords.), “El futuro de la protección social ante la crisis prolongada en América Latina: claves para avanzar hacia sistemas universales, integrales, resilientes y sostenibles”, Social Policy series, Santiago, ECLAC, 2023, in press.

The challenge of ensuring the financial sustainability of labour inclusion policies in the region is steeper at this juncture, which is characterized by sluggish economic growth, high inflation and frequent changes in government priorities (Abramo, 2021; Mazzucato, 2023). The adoption by States of a more efficient and effective approach will help to build trust among the various stakeholders, enhancing the sustainability of labour inclusion initiatives (Huepe, 2023).

Sustainable financing is key for establishing a social and labour institutional framework that is equal to the challenge of progressing towards inclusive social development. It is not enough for labour inclusion policies to be financially sustainable, because if the other two dimensions of the system (coverage and adequacy of payments) are deficient, it will not be sustainable. Labour inclusion policies must therefore dovetail with other policy areas to ensure the availability of the requisite funding for public policy and the effective, efficient, progressive, transparent and sustainable use thereof.

None of this is possible without implementing concrete actions to build the institutional capacity of national and subnational governments with regard to technical skills, resources and decision-making power. As such, the success of labour inclusion policies requires ministries to build capacity in the following areas: (i) exercising foresight and planning ahead, in particular as regards the future of work; (ii) strategic planning to set goals and develop action plans to support labour inclusion; (iii) dialogue, leadership and negotiation to establish broad-ranging, cross-cutting and sustainable agreements; (iv) management, in order to coordinate different sectors and levels of government to efficiently allocate available resources; and (v) assessment and reporting, to enhance transparency and ensure that goals are achieved.

D. Concluding remarks

Multiple factors have worsened the slow-motion crisis of the labour market in the countries of Latin America and the Caribbean, including the repercussions of the COVID-19 pandemic, high inflation and the economic slowdown. These problems are compounded by pre-existing tensions, including technological changes and environmental and demographic trends that are particularly burdensome for vulnerable groups and threaten the achievement of the commitments of the 2030 Agenda for Sustainable Development and the Regional Agenda for Inclusive Social Development.

In a region characterized by yawning labour market divides and high levels of informality, economic and labour indicators will need to recover, but this will not guarantee labour inclusion. In fact, as noted in this chapter, of the 500 million working-age people in 2022, more than 37% (some 189 million people, mostly women and young people) were not participating in the labour market. Although 93% of the 314 million economically active people were employed, nearly half were working in informal jobs, many below the minimum wage, and living in poverty or not making pension contributions. This shows that the work done by countries on labour policies (examined in detail in chapter IV) is as yet insufficient to address this significant problem. On average, the region’s countries allocate 0.34% of their GDP to the issue.

This chapter has underscored that labour inclusion is a critical and foundational part of inclusive social development and that decent work is a pillar of social inclusion, which includes social participation, access to social rights —such as education, health and care—, basic infrastructure services and access to well-being. While labour inclusion is part of an inclusive social development strategy, it also reduces the inequalities characteristic of Latin America and the Caribbean. Having access to decent work that provides income to enable households to overcome poverty and ensure social protection contributes significantly to reducing labour informality and progressing from labour market access to labour inclusion, leaving no one behind.

The chapter thus provides evidence confirming the urgent need to invest in labour inclusion policies that can extend to 77% of the region’s population, equivalent to all people of working age. The countries of the region must invest significantly in labour inclusion, recognizing its importance for the successful implementation of inclusive social development strategies that have an impact on inequality and labour informality, two structural phenomena that are hindering the sustainable development of Latin America and the Caribbean. In short, ECLAC is calling for investment in labour inclusion, which translates into investing in inclusive social development and in the most important asset that countries have: people.

Bibliography

Abramo, L. (2021), “Policies to address the challenges of existing and new forms of informality in Latin America”, Social Policy series, No. 240 (LC/TS.2021/137), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Abramo, L., S. Cecchini and B. Morales (2019), Social programmes, poverty eradication and labour inclusion: Lessons from Latin America and the Caribbean, ECLAC Books, No. 155 (LC/PUB.2019/5-P), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Abramo, L. and others (2021), “Jóvenes y familias: políticas para apoyar trayectorias de inclusión”, Social Policy series, No. 241, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Acevedo, I. and others (2021), “Informalidad en los tiempos del COVID-19 en América Latina: implicaciones y opciones de amortiguamiento”, Documento de Trabajo del BID, No. 1232, Washington, D.C., Inter-American Development Bank (IDB).

Aibar, J. (2019), “El trabajo en las plataformas digitales: relación con los sistemas de seguridad social”, Brussels, International Social Security Association (ISSA) [online] https://www.issa.int/sites/default/files/documents/events/3-TGSS-TC-CCC-263219.pdf.

Álvarez, F. and others (2020), RED 2020: los sistemas de pensiones y salud en América Latina. Los desafíos del envejecimiento, el cambio tecnológico y la informalidad, Caracas, Development Bank of Latin America and the Caribbean (CAF).

Amarante, V. and R. Infante (eds.) (2016), Hacia un desarrollo inclusivo: el caso del Uruguay (LC/L.4219), Santiago, Economic Commission for Latin America and the Caribbean/International Labour Organization (ECLAC/ILO).

Arenas de Mesa, A. (2023), “Protección social universal, integral, sostenible y resiliente para erradicar la pobreza, reducir la desigualdad y avanzar hacia un desarrollo social inclusivo”, CEPAL Review, No. 141, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

____(2019), Los sistemas de pensiones en la encrucijada: desafíos para la sostenibilidad en América Latina, ECLAC Books, No. 159 (LC/PUB.2019/19-P), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Arenas de Mesa, A. and A. Espejo (2023), “La inclusión laboral en América Latina y el Caribe”, Memoria del Tercer Seminario Regional de Desarrollo Social: Promover la Inclusión Laboral como una Forma de Superar las Desigualdades y la Informalidad en América Latina y el Caribe, Seminars and Conferences series, A. Espejo and V. Cortínez (eds.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Arenas de Mesa, A., C. Robles and J. Vila (2023), “El desafío de avanzar hacia la sostenibilidad de los sistemas de pensiones en América Latina”, Social Policy series, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Asenjo, A. and C. Pignatti (2019), “Unemployment insurance schemes around the world: evidence and policy options”, Research Department Working Paper, No. 49, Geneva, International Labour Organization (ILO).

Atuesta, B. and T. Van Hemelryck (2022), “Emergency social protection against the impacts of the pandemic in Latin America and the Caribbean: evidence and lessons learned for universal, comprehensive, sustainable and resilient social protection systems”, Project Documents (LC/TS.2022/143), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Azuara, O., S. González and L. Keller (2019), “Who drives on ride-hailing platforms in Latin America? A profile of Uber drivers in Brazil, Chile, Colombia and Mexico”, Technical Note, No. 1779, Washington, D.C., Inter-American Development Bank (IDB).

Berg, J. (2016), “Income security in the on-demand economy: findings and policy lessons from a survey of crowdworkers”, Conditions of Work and Employment Series, No. 74, Geneva, International Labour Organization (ILO).

Berg, J. and others (2019), Digital Labour Platforms and the Future of Work: Towards Decent Work in the Online World, Geneva, International Labour Organization (ILO).

Bietti, M. (2023), “Personas con discapacidad e inclusión laboral en América Latina y el Caribe: principales desafíos de los sistemas de protección social”, Project Documents (LC/TS.2023/23), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Brown, A. and J. Koettl (2015), “Active labor market programs - employment gain or fiscal drain?”, IZA Journal of Labor Economics, No. 4, Berlin, Springer.

Cecchini, S. and R. Martínez (2011), Inclusive Social Protection in Latin America: a comprehensive, rights-based approach, ECLAC Books, No. 111 (LC/G.2488-P), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Cecchini, S., R. Holz and H. Soto de la Rosa (coords.) (2021), A toolkit for promoting equality: the contribution of social policies in Latin America and the Caribbean (LC/TS.2021/55), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Chacaltana, J., F. Bonnet and V. Leung (2021), “The youth transition to formality”, Is the future ready for youth? Youth employment policies for evolving labour markets, J. Chacaltana and S. Dasgupta (eds.), Geneva, International Labour Organization (ILO).

ECLAC (Economic Commission for Latin America and the Caribbean) (2023a), Preliminary Overview of the Economies of Latin America and the Caribbean, 2022 (LC/PUB.2022/18-P/Rev.1), Santiago.

____(2023b), Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago.

____(2022a), Economic Survey of Latin America and the Caribbean, 2022 (LC/PUB.2022/9-P/Rev.1), Santiago.

____(2022b), Towards transformation of the development model in Latin America and the Caribbean: production, inclusion and sustainability (LC/SES.39/3-P), Santiago.

____(2022c), Social Panorama of Latin America, 2021 (LC/PUB.2021/17-P), Santiago.

____(2022d), Social Panorama of Latin America and the Caribbean, 2022 (LC/PUB.2022/15-P), Santiago.

____(2022e), Ageing in Latin America and the Caribbean: inclusion and rights of older persons (LC/CRE.5/3), Santiago.

____(2022f), The sociodemographic impacts of the COVID-19 pandemic in Latin America and the Caribbean (LC/CRPD.4/3), Santiago.

____(2021), “The economic autonomy of women in a sustainable recovery with equality”, COVID-19 Special Report, No. 9, Santiago.

____(2020), Regional Agenda for Inclusive Social Development (LC/CDS.3/5), Santiago.

____(2019), Social Panorama of Latin America, 2018 (LC/PUB.2019/3-P), Santiago.

____(2016), Inclusive social development: the next generation of policies for overcoming poverty and reducing inequality in Latin America and the Caribbean (LC.L/4056(CDS.1/3)), Santiago.

____(2014), Compacts for Equality: Towards a Sustainable Future (LC/G.2586(SES.35/3)), Santiago.

____(2010), Time for Equality: Closing Gaps, Opening Trails (LC/G.2432(SES.33/3)), Santiago.

____(2008), Social Panorama of Latin America, 2007 (LC/G.2351-P), Santiago.

____(2007), Cohesión social: inclusión y sentido de pertenencia en América Latina y el Caribe (LC/G.2335), Santiago.

ECLAC/ILO (Economic Commission for Latin America and the Caribbean/International Labour Organization) (2023), “Towards the creation of better jobs in the post-pandemic era”, Employment Situation in Latin America and the Caribbean, No. 28 (LC/TS.2023/70), Santiago.

____(2021a), “Decent work for platform workers in Latin America”, Employment Situation in Latin America and the Caribbean, No. 24 (LC/TS.2021/71), Santiago.

____(2021b), “Policies to protect labour relations and hiring subsidies amid the COVID-19 pandemic”, Employment Situation in Latin America and the Caribbean, No. 25 (LC/TS.2021/163), Santiago.

____(2019), “The future of work in Latin America and the Caribbean: old and new forms of employment and challenges for labour regulation”, Employment Situation in Latin America and the Caribbean, No. 20 (LC/TS.2019/31), Santiago.

____(2018), “Labour market participation of older persons: needs and options”, Employment Situation in Latin America and the Caribbean, No. 18 (LC/TS.2018/39), Santiago.

____(2014), “Conditional transfer programmes and the labour market”, Employment Situation in Latin America and the Caribbean, No. 10 (LC/L.3815), Santiago.

Espejo, A. (2022), “Informalidad laboral en América Latina: propuesta metodológica para su identificación a nivel subnacional”, Project Documents (LC/TS.2022/6), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Espejo, A. and E. Espíndola (2015), “The master key to the social inclusion of young people: education and employment”, Youth: realities and challenges for achieving development with equality, ECLAC Books, No. 137 (LC/G.2647-P), D. Trucco and H. Ullmann (eds.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Espejo, A. and others (2023a), “Desafíos y recomendaciones para la inclusión laboral de jóvenes en América Latina”, Desigualdades, inclusión y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

____(2023b), “Políticas activas de mercado de trabajo en américa latina: desafíos para la inclusión laboral con protección social”, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Eurofound (2020), New Forms of Employment: 2020 Update, Luxembourg, Publications Office of the European Union.

Figueroa, N. and R. Holz (2023), “Las persistentes brechas de protección social en la región”, El futuro de la protección social ante la crisis prolongada en América Latina: claves para avanzar hacia sistemas universales, integrales, resilientes y sostenibles, Social Policy series, C. Robles and R. Holz (coords.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Forde, C. and others (2017), The Social Protection of Workers in the Platform Economy, Brussels, European Parliament.

Gontero, S. and S. Albornoz (2022), “Desigualdades en la transición de la escuela al trabajo entre los jóvenes latinoamericanos”, CCK Revista, No. 16, Barcelona, Kreanta Foundation.

Holz, R., M. Huepe and M. Rangel (2022), “El futuro del trabajo y la población afrodescendiente en América Latina en el marco del COVID-19 y la recuperación transformadora con igualdad”, Project Documents (LC/TS.2022/81), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Huepe, M. (2023), “Desafíos y recomendaciones para la inclusión laboral de la población afrodescendiente”, Desigualdades, inclusión y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

ILO (International Labour Organization) (2023a), World Employment and Social Outlook: Trends 2023, Geneva.

____(2023b), 2022 Labour Overview of Latin America and the Caribbean, Lima.

____(2022a), 2021 Labour Overview of Latin America and the Caribbean, Lima.

____(2022b), World Employment and Social Outlook: Trends 2022, Geneva.

____(2021), World Employment and Social Outlook 2021: The role of digital labour platforms in transforming the world of work, Geneva.

____(2017), World Social Protection Report 2017-19: Universal social protection to achieve the Sustainable Development Goals, Geneva.

____(2016), Non-standard employment around the world: Understanding challenges, shaping prospects, Geneva.

Infante, R. (2011), “América Latina en el ‘umbral del desarrollo’: un ejercicio de convergencia productiva”, Documento de Trabajo, No. 14, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Marinho, M. and A. Espejo (2023), “La exclusión del sistema educativo y el mercado laboral de las personas con discapacidad en América Latina: barreras para el ejercicio del derecho a la educación y al trabajo decente”, Pódium: Revista Iberoamericana de educación e innovación para la productividad, No. 11, Madrid, Organization of Ibero-American States for Education, Science and Culture (OEI).

Maurizio, R. (2021), “Employment and informality in Latin America and the Caribbean: an insufficient and unequal recovery”, Labour Overview Series Latin America and the Caribbean 2021, Lima, International Labour Organization (ILO).

Mazzucato, M. (2023), Transformational change in Latin America and the Caribbean: a mission-oriented approach (LC/TS.2022/150/Rev.1), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Ministry of Labour, Employment and Social Security of Paraguay (2020), “Exposición de motivos: proyecto de ley seguro de desempleo”, Asunción [online] https://www.mtess.gov.py/application/files/2116/2204/2021/Borrador_Proyecto_Desempleo_Consejo_Consutivo_v30_18_09.pdf.

OECD (Organisation for Economic Co-operation and Development) (2021), “Designing active labour market policies for the recovery”, OECD Policy Responses to Coronavirus (COVID-19), Paris [online] https://www.oecd.org/coronavirus/policy-responses/designing-active-labour-market-policies-for-the-recovery-79c833cf/.

____(2019), OECD Employment Outlook 2019: The Future of Work, Paris.

OECD/ILO (Organisation for Economic Co-operation and Development/International Labour Organization) (2019), Tackling Vulnerability in the Informal Economy, Paris.

OECD and others (Organisation for Economic Co-operation and Development and others) (2023) Latin American Economic Outlook 2022: Towards a Green and Just Transition (LC/PUB.2022/14), Paris, OECD Publishing.

____(2021), Latin American Economic Outlook 2021: Working together for a better recovery (LC/PUB.2021/12), Paris, OECD Publishing.

Pedrero, M. (2023), “Los Pueblos Indígenas de América Latina-Abya Yala: la centralidad de los derechos colectivos para una recuperación económica transformadora”, Desigualdades, inclusión y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

RIADIS and others (Latin American Network of Non-Governmental Organizations of Persons With Disabilities and their Families and others) (2022), Informe sobre el impacto de la pandemia de la COVID-19 en la vida de las personas con discapacidad de América Latina y el Caribe, Quito.

Robles, C. and R. Holz (coords.) (2023), “El futuro de la protección social ante la crisis prolongada en América Latina: claves para avanzar hacia sistemas universales, integrales, resilientes y sostenibles”, Social Policy series, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Robles, C. and others (2023), “Un enfoque renovado de articulación entre las políticas de protección social e inclusión laboral”, El futuro de la protección social ante la crisis prolongada en América Latina: claves para avanzar hacia sistemas universales, integrales, resilientes y sostenibles, Social Policy series, C. Robles and R. Holz (coords.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Robles, C., V. Tenenbaum and I. Jacas (2023), “Los desafíos para la protección social de los trabajadores de plataformas: reflexiones para América Latina”, Project Documents (LC/TS.2023/116), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Ruesga, S. and others (2014), Economía del trabajo y política laboral, Madrid, Ediciones Pirámide.

Salazar-Xirinachs, J. (2023), “Prólogo”, Desigualdades, inclusión y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

____(2016), “Una crisis en cámara lenta”, Geneva, International Labour Organization (ILO), 17 May [online] https://www.ilo.org/americas/sala-de-prensa/WCMS_482410/lang--es/index.htm.

Salazar-Xirinachs, J. and J. Chacaltana (eds.) (2018), Políticas de formalización en América Latina: avances y desafíos, Lima, International Labour Organization (ILO).

Samaniego, N. (2002), “Las políticas de mercado de trabajo y su evaluación en América Latina”, Macroeconomics of Development series, No. 19 (LC/L.1836-P), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Schlogl, L. and A. Sumner (2014), “How middle class are the ‘emerging middle’ or ‘scooter class’ in Indonesia? A household asset approach to social stratification”, Working Papers in Economics and Development Studies, No. 201407, Bandung, Padjadjaran University.

Tromben, V., F. Villanueva and E. Caillaux (2023), “Estimación del gasto público en políticas laborales en América Latina (2014-2021)”, Project Documents (LC/TS.2023/48), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

United Nations (2007), Convention on the Rights of Persons with Disabilities (A/RES/61/106), New York.

Velásquez, M. (2021a), “La protección ante el desempleo: medidas aplicadas durante la crisis del COVID-19”, Project Documents (LC/TS.2021/214), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

____(2021b), “La protección social de los trabajadores informales ante los impactos del COVID‐19”, Project Documents (LC/TS.2021/37), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Washington Group on Disability Statistics (2020), “An introduction to the Washington Group on Disability Statistics question sets”, Hyattsville [online] https://www.washingtongroup-disability.com/fileadmin/uploads/wg/The_Washington_Group_Primer_-_English.pdf.

Weller, J. (2023), “Principales tendencias globales y su impacto en la inclusión laboral”, Desigualdades, inclusión y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Weller, J. and S. Gontero (2016), “Creating effective, efficient and inclusive national systems of technical and vocational education and training in Latin America”, Protection and training: Institutions for improving workforce integration in Latin America and Asia, ECLAC Books, No. 140 (LC/G.2687-P), A. Isgut and J. Weller (eds.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Annex II.A1

Table II.A1.1

Latin America (12 countries): employment surveys standardized by ECLAC and used for labour market analysis

Country

Survey used

2019

2020

2021

2022

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

Argentinaa

Permanent Household Survey (EPH)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Bolivia (Plurinational State of)

Continuous Employment Survey (ECE)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Brazil

Continuous National Household Survey

(Continuous PNAD)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Chile

National Employment Survey (ECE)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Colombia

Large Integrated Household Survey (GEIH)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Costa Rica

Continuous Employment Survey (ECE)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Dominican Republic

Continuous National Labour Force Survey (ENCFT)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Ecuadorb c

National Survey on Employment, Unemployment

and Underemployment (ENEMDU)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Mexicod

National Survey of Occupation

and Employment (ENOE)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Peru

National Household Survey (ENAHO)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Paraguay

Permanent Continuous Household Survey (EPHC)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Uruguaye

Continuous Household Survey (ECH)

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of regional employment surveys.

Note: Data gathered after the onset of the COVID-19 pandemic may present comparability problems with respect to the data for 2019, owing to adjustments in sampling and weighting by national statistical offices.

a Urban population only.

b The information for the second quarter of 2020 refers to May and June.

c The information for the third quarter refers to September.

d The information for the second quarter of 2020 refers to the simple average of the Occupation and Employment Telephone Survey (ETOE) for April, May and June.

e Owing to changes in survey methodology, the simple monthly averages are used for each quarter beginning in 2020.

Annex II.A2

Table II.A2.1

Latin America (12 countries): definitions of labour informality

Country

Definition

Argentina

Proportion of the employed population in the following categories: own-account worker or employees or employers

in the informal sector; unpaid family employees; wage earners who do not receive social security.

Bolivia (Plurinational State of)

Proportion of the employed population in the following categories: private sector employees working in unregistered companies; private wage earners with no written contract; unpaid family workers or domestic employees.

Brazil

Proportion of the employed population in the following categories: own-account worker or employees or employers

in the informal sector; unpaid family employees; wage earners who do not contribute to social security.

Chile

Employees who do not make health and social security contributions as a result of their employment relationship with an employer are deemed to be informally employed. Employers and self-employed workers are deemed to be informally employed if the firm, business or activity in which they work belongs to the informal sector. All unpaid family members (performing domestic work) are informally employed by definition, given their relationship with the economic unit in which they work.

Colombia

Proportion of the employed population in the following categories: own-account worker or employees or employers

in the informal sector; unpaid family employees; wage earners not covered for health care through social security.

Costa Rica

Informal employment includes all jobs with the following characteristics, according to the person’s position: wage earners who are not registered with social security through their employers; unpaid assistants; self-employed workers and employers with unincorporated businesses (firms that are not registered in the National Property Registry

and do not keep formal accounts).

Dominican Republic

Population working in the following categories: own-account worker or employees or employers in the informal sector; unpaid family employees; wage earners who are not enrolled or do not know whether they are enrolled

in health insurance or a pension plan.

Ecuador

Proportion of the employed population in the following categories: own-account worker or employees or employers

in the informal sector; unpaid family employees; wage earners with no social security or medical coverage.

Mexico

Proportion of the employed population comprising the sum, without double counting, of employed persons whose jobs are precarious owing to the nature of the economic unit for which they work and those who are not considered employed owing to the source of their work.

Paraguay

Proportion of the employed population: in the informal sector; not contributing to a pension fund or unaware of whether they contribute; have no annual holidays or are unaware of whether they do. The informal sector means private sector enterprises that are not registered as businesses.

Peru

Proportion of the employed population in the following categories: own-account worker or employees or employers

in the informal sector; unpaid family employees; wage earners not directly covered by social security.

Uruguay

Proportion of the employed population not contributing to a pension fund and with no annual paid vacation

or paid days off.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of regional employment surveys.

1. [1] See annex II.A.1 for the list of employment surveys used in this chapter.

2. [2] Information based on administrative records data from 17 Latin American countries.

3. [3] Most countries have a single minimum wage. However, in some economies the minimum wage is differentiated by sector or by occupation, in which case the lowest minimum wage of the industry is used as the reference value (ILO, 2023b).

4. [4] Of an age to be considered dependent, which is to say persons aged under 15 or 65 and over.

5. [5] According to Alvarez and others (2020), surveys conducted in Latin American countries give an estimated proportion of 9.4% of active platform workers. Another 6.7% of workers were registered with platforms but were not actively providing services. Therefore, digital platform workers could represent around 16% of the workforce (Álvarez and others, 2020).

6. [6] The Non-contributory Social Protection Programmes Database - Latin America and the Caribbean of the Economic Commission for Latin America and the Caribbean (ECLAC) gathers information on labour inclusion programmes in the countries of the region, aimed at people living in poverty, or in situations of vulnerability or social exclusion. See [online] https://dds.cepal.org/bpsnc/home. The countries covered are Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Saint Vincent and the Grenadines, Trinidad and Tobago and Uruguay. This section includes information on programmes recorded through to December 2022.

7. [7] Seven programmes ended over the course of 2019 and 2020: the Plurinational State of Bolivia’s Economic Inclusion for Rural Families and Communities Programme (ACCESOS), Chile’s Más Capaz programme to increase the employability of vulnerable groups, El Salvador’s JóvenES con Todo programme to improve youth labour market access, Costa Rica’s Proyecto Emprende programme to promote entrepreneurship (National Women’s Institute), and in Mexico the Jóvenes con Prospera social inclusion programme (formerly Jóvenes con Oportunidades 2003–2014), the Temporary Employment Programme, and the National Programme of Financing for Microentrepreneurs and Women in Rural Areas (PRONAFIM). Four programmes were launched in 2020: Argentina’s Potenciar Trabajo labour programme, Colombia’s Empléate Sin Fronteras programme to provide migrants with employment opportunities, Haiti’s Temporary Social Security and Skills Network for Youth and Saint Vincent and the Grenadines’ Promoting Youth Micro Enterprises (PRYME) programme. Over the course of 2021 and 2022, five other programmes ended: the Plurinational State of Bolivia’s Mi Primer Empleo Digno decent work programme and its Programme to Improve the Employability and Labour Income of Young People (PMEIL), Peru’s Impulsa Perú National Programme to Boost Labour Opportunities (formerly Vamos Perú) and Uruguay’s Compromiso Educativo education programme and its Jóvenes en Red programme for young people. Three others were created over the same period: Argentina’s Fomentar Empleo employment programme, Brazil’s Emprega + Mulheres programme to support women’s labour market access and Uruguay’s Accesos capacity-building programme. Argentina has also made progress on flagship programmes, such as the Potenciar Trabajo National Programme for Social and Productive Inclusion and Local Development, which brings together the Hacemos Futuro and Salario Social Complementario programmes, and the Fomentar Empleo strategy, which includes recipients of Training and Employment Insurance and the Jóvenes con Más y Mejor Trabajo programme for youth.

8. [8] Although promoting self-employment can be an immediate solution for labour inclusion, it does not always guarantee a steady income or optimal working conditions (Abramo, Cecchini and Morales, 2019). Gender biases are often observed in training and there is not enough of a focus on providing access to financial services and credit. The latter is a significant barrier for vulnerable populations and needs to be prioritized in public policy frameworks (Espejo and Espíndola, 2015).

9. [9] This section covers the countries in the region that have a mandatory system of unemployment insurance or individual savings accounts for workers: Argentina, Bahamas, Barbados, Brazil, Chile, Ecuador and Uruguay. In Colombia, there also are private and voluntary unemployment insurance plans. Although the Bolivarian Republic of Venezuela also has unemployment insurance plans of this nature, it was not possible to obtain information on them. Although information on its recipients broken down by year is unavailable in Honduras, it is estimated that the system paid entitlements to 307,618 people between 2017 and 2022. In Paraguay, a bill was drafted to create unemployment insurance and submitted to Parliament for debate in September 2020 (Ministry of Labour, Employment and Social Security of Paraguay, 2020).

10. [10] The “missing middle” refers to the lack of protection for middle-income earners, most of whom are not protected by a social security system or by contributory or tax-funded social assistance (ILO, 2017; Schlogl and Sumner, 2014).

Chapter III

Labour inclusion amid the challenges of gender equality in care work and international migration in the region

Introduction

A. Labour inclusion and care: challenges and opportunities for women’s autonomy

B. Labour inclusion and international migration: opportunities and challenges

C. Summary

Bibliography

Annex III.A1

Introduction

Latin America and the Caribbean is a region with deep structural inequality that has been perpetuated and reproduced even in periods of economic growth and prosperity. Inequality is an impediment to development and a major obstacle to poverty reduction, the expansion of citizenship and rights, social cohesion and democratic governance. Historically, the region’s production matrix has been marked by sharp structural heterogeneity that has helped to produce great social and gender inequality. The lack of diversification and the highly uneven production structures (with unproductive sectors providing around 50% of employment) are key factors driving inequality in the economic sector. The labour market, in particular, is a key link in the relationship between productive structures and the resulting inequality in household income and stratified access to social protection (ECLAC, 2010, 2012 and 2014).

ECLAC has argued that, to move forward with strategies for action aimed at reducing inequality, it is important to recognize inequality as a complex and multidimensional phenomenon that goes far beyond inequality of means (income, property, financial and productive assets) and that it is rooted in the concepts of equal rights, capabilities, autonomy and recognition (ECLAC, 2014 and 2017a). Thus, other political, social and cultural factors add to the income inequality shaped by opportunities for labour inclusion, as do discriminatory mechanisms that are repeated in various socioeconomic areas outside of work, such as health, education, culture, and political and civic participation. These inequalities are the determinants of poverty and the main obstacles to ending it (ECLAC, 2016a).

In addition to socioeconomic level, gender inequalities, ethnic and racial inequalities, gaps associated with the different stages of the life cycle, territorial inequalities and migratory status are other axes of the matrix of social inequality in Latin America. These axes are structural because of their heavy impact on the reproduction of inequalities in different areas of development and the exercise of rights (ECLAC, 2016a).

The 2030 Agenda for Sustainable Development proposes to address and reduce inequalities in the different dimensions of development and move towards more inclusive societies, and makes the call to leave no one behind. The region has also produced the Regional Gender Agenda (ECLAC, 2022f), comprising the commitments that the member States of ECLAC have assumed over the last 45 years in the framework of the sessions of the Regional Conference on Women in Latin America and the Caribbean. This Agenda offers a road map to overcome the structural challenges of gender inequality and progress towards a new model of development and organization of society, namely the care society. The Regional Gender Agenda is in synergy with the Montevideo Consensus on Population and Development, which was adopted 10 years ago at the first session of the Regional Conference on Population and Development in Latin America and the Caribbean, and is geared towards the realization of the rights of all population groups, including international migrants. These commitments contribute to the design and implementation of comprehensive public policies able to transform intersectional inequalities in the region.

As described in chapter II, the impact of recent crises has generated more inequality and widened gaps in the labour market. The analysis in the present chapter focuses on two of these axes, which are crucial and must be brought into the open in order to advance labour inclusion and inclusive social development. First, it examines how the sexual division of labour and the social organization of care continue to constitute one of the structural challenges of gender inequality in the region and represent one of the main barriers to women’s labour inclusion. It also analyses the expanded care sector and, in particular, paid domestic work, a sector plagued by high rates of informality. The second section analyses the growing migration processes in the region and the challenges that migrant populations face in terms of labour inclusion. This chapter also looks at situations where the various axes of the social inequality matrix are linked over the life cycle, so that they concatenate and exacerbate each other, giving rise to a multiplicity of factors of inequality or discrimination that impact individuals or certain population groups (ECLAC, 2016a). This is the case of migrant women devoted to paid domestic work. The chapter closes with a summary of the main findings and a series of recommendations on how to move towards the labour inclusion of women and migrants.

A. Labour inclusion and care: challenges and opportunities for women’s autonomy

Over the past decade, the rise in women’s labour participation has slowed and gaps persist in relation to gender inequality. Equally, women’s presence in the labour market has not signified either a reduction in their participation in unpaid domestic and care work or a significant rise in men’s participation in this kind of work. This impasse constitutes an obstacle to women’s labour, which is compounded by rising demand for care, exacerbated by population ageing, changes in epidemiological trends and the effects of climate change. The unprecedented effects of the coronavirus disease (COVID-19) pandemic highlighted the critical role of paid and unpaid care work in sustaining life, as well as the increased labour exclusion of women during emergencies and crises. Care work is carried out mainly by women, either unpaid in the home, or in informal working conditions. Despite regulatory advances aimed at promoting the labour inclusion of domestic workers, this sector still typically shows a higher level of informality and challenges to full inclusion. In order to address the challenges of achieving women’s labour inclusion, it is essential to design public policies on gender that respond to present and future care needs, and thus end the current sexual division of labour. ECLAC has proposed working on areas that are particularly promising to promote structural change: one of these is the care economy, as a key economic sector that could, among other factors, enhance the labour inclusion of women (ECLAC, 2022b).

1. The key link between paid and unpaid work for women’s labour inclusion

Female labour inclusion is closely linked to the need to achieve women’s autonomy and gender equality in Latin America and the Caribbean, which implies overcoming the structural challenges that perpetuate inequalities between men and women.[1] These challenges intersect, reinforce each other and prevent women from enjoying all rights, which is why they must be addressed through public policy with a comprehensive and intersectional approach. Moving towards the labour inclusion of women, that is, towards access to decent jobs that ensure adequate pay and social protection coverage (Espejo and Cortínez, 2023) is essential for breaking down these challenges and achieving women’s economic autonomy.

As described in chapter II, women are particularly affected by labour market entry barriers.

Women’s labour market participation rose slowly between 2001 and 2019, but the massive job losses caused by the COVID-19 pandemic in 2020 disproportionately affected women and set the female labour force participation rate back by 18 years (ECLAC, 2022d).

Thus, between 2001 and 2022, women’s labour force participation shows a gradual rise in almost all countries in the region, reaching an average of 51.9% in 2022. However, a wide gap remains between the rates for men and women: in 2022, one in two women was outside the labour force, compared to one in four men. These figures have not changed significantly in the past 20 years (see figure III.1).

Figure III.1

Latin America and the Caribbean (18 countries): labour force participation rate of persons aged over 14, by country and sex, 2003 and 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago, 2023 and CEPALSTAT.

Note: The weighted average for Latin America and the Caribbean overall for 2003 includes the following 24 countries: Argentina, Bahamas, Barbados, Belize, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Trinidad and Tobago, and Uruguay. The weighted average for 2022 includes the following 20 countries: Argentina, Barbados, Belize, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Trinidad and Tobago, and Uruguay.

These gaps in terms of labour market integration contrast with the achievements of women in the region in terms of years of education, in which they have even surpassed the average for men. In 2020, 67.4% of women aged between 20 and 24 years in 18 Latin American countries had completed secondary education, compared to 60.9% of men of the same age (ECLAC, 2022a). The proportion of women accessing and completing higher education has also exceeded that of men, on average. Despite these advances in education, the gender gap in labour participation has not closed: the participation rates of women and men in 2022 showed a difference of 23.8 percentage points in 2022 (ECLAC, 2022a). This makes it clear that the obstacles women face to labour market entry, as well as to better jobs and pay once in the market, do not reflect differences in years of schooling.

The unequal distribution of unpaid work is one possible reason why the labour participation gap persists. The total workload, expressed in average weekly hours of paid and unpaid work, is similar among women and men, or higher. Although obtaining a regional average is precluded by the differing characteristics of the countries’ information collection processes, a clear pattern emerges regarding the proportion of time that men and women devote to each type of work. While men allocate more than half of their working time to the labour market, women devote approximately a third. In the case of unpaid work, the proportion is reversed: women allocate more than half of their working time to unpaid work, while in some countries men devote even less than a third (see figure III.2).

Figure III.2

Latin America (16 countries): total time that the population aged 15 years and older spends per week on paid and unpaid work on average, by sex, latest year available

(Hours)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Repository of information on time use in Latin America and the Caribbean.

a Preliminary data.

This disparity reflects the gender inequalities that persist in the region in terms of the distribution of domestic and care tasks, and represents the main barrier to women’s labour participation (ECLAC, 2019a). It is thus essential to strengthen care systems to ensure women’s right to work.

2. Childcare: a barrier to women’s labour inclusion

The sexual division of labour, which leads to the tasks relating to care for others (children, persons with disabilities and dependent older persons, among others) being shouldered to a greater extent by women, is one of the main barriers to women’s inclusion in the labour force and gives rise to gaps in labour market integration and opportunities to access decent work throughout life. Barriers to integration become especially evident in the labour force participation of women who have children in their care. The care work associated with raising children aged between 0 and 5 years demands a great deal of time, usually overlapping with the years in which the caregivers are beginning and consolidating their careers. The unequal social distribution of this work and the lack of comprehensive care systems is reflected in the labour participation rates of women; faced with motherhood or child-rearing, they are forced to interrupt, postpone or suspend their professional careers.

Among other things, childcare entails devoting time and resources, which generates tension between care and women’s potential labour inclusion. This conflict often turns into a considerable barrier to women’s labour inclusion and thus a loss of autonomy and limitation of opportunities.

Furthermore, this situation unfolds unequally, since it disproportionately affects women in socioeconomically disadvantaged situations. The disparity in women’s labour participation is sharper in the lowest income quintiles, compared to the participation of women in the richest quintiles. This difference is even greater in homes with children under age 5. In the lowest income quintile, there is a gap of almost 9 percentage points between the labour participation of women aged between 20 and 44 in households with and without children under age 5 (see figure III.3). In the highest income quintile, this gap is less than 3 percentage points, which partly reflects the ability of higher-income women to hire private services to ease the burden of domestic and care work, an option that is less accessible to women in the lowest income quintiles. These differences remain observable in employment rates, which are double for women in the highest quintile compared to women in the lowest quintile, both when there are children aged between 0 and 5 years (80.1% and 34.5%, respectively), and when there are none (82.1% and 38.9%, respectively) (see figure III.4).

Figure III.3

Latin America (15 countries):a labour participation rate of persons aged between 20 and 44 years, by sex and presence of children aged between 0 and 5 years in the home, by household per capita income quintile, 2022b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Weighted average for the following countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay.

b In the case of Colombia, Honduras and the Plurinational State of Bolivia, the data refer to 2021.

Figure III.4

Latin America (15 countries):a employment rate of persons aged 20–44 years, by sex and presence of children aged between 0 and 5 years in the home, by household per capita income quintile, 2022b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a Weighted average for the following countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay.

b In the case of Colombia, Honduras and the Plurinational State of Bolivia, the data refer to 2021.

In addition, the more children they have, the lower women’s labour participation. Based on census information on the number of children in the household, women with at least one child show lower employment rates than those with no children living with them. In the case of women with three children or more, labour market participation is one third or less than in the case of women with no children. The younger the women, the stronger this inverse relationship between number of children and labour force participation (see figure III.5). Studies carried out in six countries in the region show that the labour market participation of women who have children before the age of 20 is 25% lower than that for women who have children at a later age, an exclusion effect that could persist into the adult lives of women who have children during adolescence (UNFPA, 2020).

Figure III.5

Latin America (5 countries): employed women, by number of children and single ages, latest year available

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special processing of population and household census data with REDATAM.

Analysis of the labour market integration of women by number of children and educational level shows that, for women of all educational levels, a greater number of children is associated with systematically lower labour participation. However, in some countries, women with one child and only primary education or a lower level of education show a higher rate of labour force participation than women without children, which may reflect the need for income (see figure III.6).

To analyse the link between motherhood and different dimensions linked to women’s labour inclusion, a series of multivariate analysis models were developed based on household surveys in the region (see annex III.A1). The results show that the probability of women between 25 and 50 years of age being in paid work, regardless of age, education and area of residence, is significantly lower the more children they have. In Guatemala, for example, the probability of women with a child having a paid job is half that of women without children. Having more children reduces the probabilities even further and, in all the countries analysed, women with five children are 60% less likely to have paid work than women without children (see annex table III.A1.1). At the same time, the analysis shows a positive correlation between the number of children and devotion to unpaid work (see annex table III.A1.2).

Figure III.6

Latin America (5 countries): women aged 30 years in paid work, by educational level and number of children, latest year available

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special processing of population and household census data with REDATAM.

Similar models were explored to estimate the relationship between the number of children and working conditions, in particular the level of labour income and the existence of an employment contract. In all cases, a correlation was seen between the number of children and the deterioration of working conditions, either because hourly income or the probability of working under a contract decreases significantly with each additional child.[2]

It is essential to promote labour inclusion policies that are closely coordinated with care policies and comprehensive care systems, as well as with other areas of social protection, and that help strike a balance between paid and unpaid work, since this is one of the main barriers to women’s labour market integration. Such policies, if applied in a coordinated manner and with a rights-based approach, will reduce the excess care burden that falls largely on women. To achieve this, it is necessary to foster both gender co-responsibility between men and women and social co-responsibility between the State, the market, communities and families.

3. Labour inclusion and the care economy

The care economy includes all domestic and care work that is carried out without pay, as well as paid care work in the labour market (ECLAC, 2019a). In a broad sense, the concept covers all work related to health, education and domestic and care work carried out with or without pay in the market, the home or the community. From the perspective of care, there is a flow of continuity between educational and health services and the care provided in the household, family or community. This must be taken into account when designing policies for the redistribution of responsibilities from households to the State and the private sector.

The COVID-19 pandemic, among other factors, showed how central care is in people’s lives and how crucial its organization at a social level, as well as the vulnerability of women’s labour inclusion in situations of crisis and emergency. The health measures aimed at preventing the spread of the virus, added to the saturation of health systems, the closure of educational establishments and the difficulties of families in finding support for domestic and care work, showed the extent to which society and the economy depended on health, education and care work, both paid and unpaid (ECLAC, 2020). In relation to the labour market, although jobs in the health sector, education and domestic work are very dissimilar in terms of type of tasks and working conditions, they share an important characteristic: they have a direct impact on the care burden that households must assume and on the autonomy of women, to the extent that they continue to be primarily responsible for care work.

In view of the care crisis, exacerbated by population ageing, changes in epidemiological trends and the effects of climate change, a sustained increase in the demand for care work and a reduction in the time and number of people available to provide it are expected, (ECLAC, 2022b). In demographic terms, the region faces a twofold challenge: meeting the increased demand for care for older persons without having yet resolved childcare. Unlike in other sectors, although the uptake of new technology has led to some productivity gains, the total demand for labour in the care sector is expected to increase (ECLAC, 2022b; ILO, 2019). This could offer a twofold opportunity in terms of both creating new jobs and reducing unpaid work time in the household.

(a) The feminization of the care sector

In 2021, 26.7% of women in paid work in Latin America were in care-related sectors (7.6% in the health sector, 9.2% in education and 9.9% in paid domestic work). Women represent 69.9% of workers in the teaching sector, 73.5% in the health sector and 92.8% in the domestic employment sector (Baron and Scuro, 2023).

Workers in care-related sectors and occupations share some characteristics: in addition to being mostly women, they perform jobs that require knowledge and skills that are not always valued. The fact that they often maintain relationships over time with people receiving care implies an emotional burden that is hard to measure, but is essential for sustaining life and social well-being (Vaca Trigo and Baron, 2022). This is nevertheless a very heterogeneous group, in terms of both occupational category, pay and working conditions, and the value and status it is afforded by society. The health and education sectors still show large wage gaps and evidence of the glass ceiling phenomenon, while the paid domestic work sector suffers from lack of basic labour rights and even wages below the poverty line.

The health sector has a highly heterogeneous workforce and marked occupational segregation, which is evidence of persistent gender gaps: in 2020 the sector showed a gender wage gap of 39.2%, the largest of all the paid sectors of the care economy (ECLAC, 2022b).

Detailed distribution by type of occupation shows that 25.5% of men employed in the health sector are medical professionals, compared with only 10.3% in the case of women. The majority of women (30.1%) are in mid-level occupations related to nursing and midwifery, which accounts for the gender stratification evident in the qualifications, functions and earnings of occupations in the sector. Indeed, the hourly wage of medical professionals is, on average, 4.9 times higher than that of the mid-level nursing and midwifery occupations (ECLAC, 2022b).

The education sector is highly feminized and segmented. More pronounced feminization of education-related jobs is typical of the preschool and primary levels of education, which entail precisely more intensive, direct care tasks. While 83.4% of the teaching staff at the primary and preschool levels is made up of women, that proportion decreases to 58.8% at the secondary level. At the tertiary level of education the composition is reversed: the majority of the teaching population is made up of men, and women represent 45.1% of employment (ECLAC, 2022b).

In addition to guaranteeing the right to formal education, the education system plays a key role in the provision of care for children and adolescents and, like the health sector, affords continuity of care with households. Educational institutions often provide food, medical and dental care and vaccinations, among other services, in addition to emotional assistance and support to children and adolescents. These are just some of the reasons why, when children attend an educational institution or a childcare centre, the time spent on their care at home is significantly reduced. On comparing the differences in time spent on care between households where children attend a childcare facility and households where they do not, the impact on women’s autonomy is clear. Owing to traditional gender roles and low levels of co-responsibility for care within households, the reduction of time for men is negligible (ECLAC, 2022b).

Among the paid sectors of the care economy, domestic work has the poorest working conditions and is often called upon to make up for the lack of educational and health services. Latin America and the Caribbean is the world region where paid domestic work represents the highest proportion of employment for women: on average, 1 in 10 employed women is in domestic work, and women represent 92.8% of those working in the sector. According to the International Labour Organization (ILO, 2023), of all the women working in domestic employment around the world, one in five is in Latin America and the Caribbean.

Given the fragility of income in the domestic work sector, one in four (23.5%) of the women employed in it live in poverty. Following the crisis caused by the pandemic, employment in the sector appears to have become even more precarious and has been slower to recover than in other sectors of the labour market (ECLAC, 2022b; Baron and Scuro, 2023). Domestic work is also one of the sectors with the highest levels of informality, which manifests in poor social security coverage and often an absence of a signed or registered contract (Valenzuela, Scuro and Vaca Trigo, 2020). Added to the feminization and low pay associated with domestic work are inequalities and discrimination on ethnic and racial grounds and arising from workers’ immigration status, as will be described in greater detail in section B.

Paid domestic work has historically been performed in large proportion by Afrodescendent, Indigenous and rural migrant women; in recent decades, national origin has been added to the factors of inequality existing in the household employers sector as women from other countries have joined this labour force (Valenzuela, Scuro and Vaca Trigo, 2020). In 2015, ILO estimated that there were 4.3 million migrant workers in Latin America and the Caribbean, and that 17.2% of them were employed in paid domestic work. By 2019, 35.3% of those working in this occupation were migrants (ILO, 2021b). The feminization of migrations around the world has led to the formation of global care chains (Ehrenreich and Russell, 2003; Salazar, 2001) and a transnational transfer of care (ECLAC, 2020). Estimates for 2021 in three countries with high migratory flows show the burden of paid domestic work on female migrant workers. In Argentina, 19% of all employed migrant women were in this line of work; in Chile, 10%, and in Costa Rica, 18%. By contrast, among employed women born in the country, 12% were in paid domestic work in Argentina, 5% in Chile and 13% in Costa Rica (Gontero and Velásquez, 2023).

The care economy sectors are not expected to experience major risks of automation and job losses in the short term, mainly owing to the human, physical and bodily dimension of these jobs, which cannot be completely replaced. Unlike in other sectors, even if labour productivity grows, the total demand for labour in the care economy is expected to increase in pace with demographic changes and the environmental crisis (ECLAC, 2022b; ILO, 2019).

As noted earlier, Latin America and the Caribbean has a twofold opportunity both in terms of new job creation in the care economy (among other sectors) and in relation to the reduction of unpaid working time in the household. However, without the appropriate policies, this scenario could reproduce historical gender inequalities and deepen the precariousness already affecting some of the women employed in the expanded care sector. The time devoted to work on caring for children, older persons, and persons with disabilities depends directly on access to health, educational and domestic work services, their quality and the development of professional home and community care, which is still incipient in the region. In Latin America and the Caribbean, middle- and high-income households often compensate for the weak or absent public provision of these services by buying them in the market. However, for low-income households, poor access to these services leads to a spiral of income and time impoverishment. Furthermore, the households in the lowest income deciles have the largest number of members and the greatest relative proportion of children and persons with disabilities. This means that women in these households have less time and face greater barriers to entering the labour market. A vicious circle thus forms between monetary poverty and scarcity of time, which translates into an urgent need to apply policies to foster women’s labour inclusion and quality care services in order to break this spiral (ECLAC, 2016b).

(b) Paid domestic work: the most informal sector

Although there are marked differences between countries, domestic work represents one of the main avenues into the labour market for women in the region: the percentage of women employed in this sector ranges from 4.3% in the Plurinational State of Bolivia to 14.5% in Argentina (see figure III.7). Improvement of working conditions in this sector is a debt that the region’s democracies owe to women, especially migrants, Afrodescendants and Indigenous Peoples, who make up a majority of paid domestic workers (Valenzuela, Scuro and Vaca Trigo, 2020).

Figure III.7

Latin America (14 countries): proportion of employed women working in the households as employers sector, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: In the case of the Plurinational State of Bolivia and Colombia, the data refer to 2021, and in Honduras, to 2019. “Households as employers” corresponds to the 20th category of the International Standard Industrial Classification of All Economic Activities (ISIC) revision 4: activities of households as employers; undifferentiated goods- and services-producing activities of households for own use.

In 2011, ILO adopted the Domestic Workers Convention, 2011 (No. 189) and published the Domestic Workers Recommendation, 2011 (No. 201), which marked a significant milestone in the promotion of standards and policies aimed at improving the working conditions of domestic workers.[3] Convention No. 189 recognizes those engaged in domestic work as being entitled to the same rights and protections as other workers, regardless of origin or immigration status, and seeks to ensure these rights and protections. This international regulatory framework urges States to guarantee a minimum wage for domestic work, set in accordance with national systems and without discrimination by sex. The Convention underlines the importance of transparency regarding conditions of employment, working hours, hours of rest, pay and the guarantee of occupational safety and health. In addition, it suggests that payments in kind be limited and, where they exist, they should not be deducted from the minimum wage. The framework also establishes that domestic workers must have access to the country’s social security systems under conditions that are not less favourable than those applicable to workers generally. In addition to working conditions, Convention No. 189 emphasizes protection against abuse, harassment and violence. Uruguay was the first country in the world to ratify this Convention, and currently 18 countries in the region have done so. This approach is reinforced by the ILO Violence and Harassment Convention, 2019 (No. 190) and the Violence and Harassment Recommendation, 2019 (No. 206), which identify domestic work as a sector particularly vulnerable to situations of violence and harassment, especially in employer-provided accommodation.

The Regional Gender Agenda draws on and contributes to the international and regional legal framework to protect, respect and ensure all the human rights of women, adolescents and girls in all their diversity, as well as non-discrimination and the achievement of equality. Specifically, in the Buenos Aires Commitment, approved at the fifteenth session of Regional Conference on Women in Latin America and the Caribbean, the countries agreed to “adopt measures to promote and effectively protect the human rights of all women domestic workers, as established in Convention No. 189 of the International Labour Organization, and urge governments that have not yet done so to ratify and apply the Convention” (ECLAC, 2023b, p. 8).

Accordingly, most countries in the region have already set minimum wages for domestic workers in accordance with national systems, although there are some exceptions, such as Honduras and El Salvador, where domestic work is not yet subject to the national minimum wage. On the other hand, in countries with multiple wage-setting systems, such as Panama and Costa Rica, the minimum wage for domestic work may be lower than that for other job categories. By contrast, the experiences of collective bargaining systems aimed at establishing differentiated minimum wages, such as those of Argentina and Uruguay, do not necessarily imply disadvantages compared to the wages established for other occupations (ILO, 2021a).[4]

Despite progress, paid domestic workers in Latin America receive considerably lower incomes than employed women generally: half, on average. In some countries, the difference is even greater (see figure III.8). Several countries have pursued legal reforms to reduce wage gaps or discrimination in the legislation.[5]

In addition, domestic workers often experience longer working hours than the standards agreed upon within the ILO framework. In 2019, only 39.9% of domestic workers in the region worked between 35 and 48 hours per week, in contrast to 63.9% for the rest of wage-earners. Although regulatory reforms have been implemented in some countries to address these irregularities, in countries such as Honduras, El Salvador, Nicaragua, Peru and Guatemala, there are still high percentages of female workers whose working days exceed 60 hours per week (ILO, 2021a).

Figure III.8

Latin America (14 countries): women’s average monthly labour income, by sector and country, 2022

(PPP dollars)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The weighted average for Latin America includes the 14 countries shown in the figure. In the case of the Plurinational State of Bolivia and Colombia, the data refer to 2021, and in the case of Honduras, to 2019. In PPP (purchasing power parity) dollars based on the year corresponding to the data used for each country.

Similarly to the situation with income, and despite recent advances in international agreements and regulations, the household employer sector continues to be one of those with the highest informality rates. Although some countries have made major progress in the formalization of domestic work in the past 20 years (Gontero and Velásquez, 2023),[6] in all countries, except Chile and Uruguay, over 60% of women working in private households are not affiliated or contributing to social security. The Latin American average is 76.8%, in other words, three of every four women in the domestic work sector lack basic labour rights (see figure III.9).

In addition to the adverse working conditions that characterize the sector and hinder women’s labour inclusion is the crisis caused by the COVID-19 pandemic, which had a severe impact, due to both the loss of jobs and the drop in wages. Employment levels of domestic workers fell almost 20% between 2019 and 2020, and the proportion of these women living in poverty went from 20.7% in 2019 to 23.5% in 2021 (Baron and Scuro, 2023). This, in turn, reveals the level of job precariousness and insecurity experienced by paid domestic workers.

The analysis of paid domestic work in the region is crucial, since it is an important sector of employment for women in situations of greater vulnerability. As seen in table III.1, almost 60% of domestic workers have fewer than 10 years of schooling, compared with only 32.2% of all employed women. While 15.5% of all employed women belong to single-parent households, [7] this percentage rises to 19.4% among domestic workers: one in five is the main or sole breadwinner of a household with at least one child.

Figure III.9

Latin America (14 countries): paid female domestic workers not affiliated or contributing to a social security system, by sector and country, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The weighted average for Latin America includes the 14 countries shown in the figure. In the case of the Plurinational State of Bolivia and Colombia, the data refer to 2021, and in the case of Honduras, to 2019.

Table III.1

Latin America (14 countries):a characterization of employed women, by sector of economic activity, 2022

Sector of activity

Women working in the household employer sector

Total employed women

Average age

43.5

40.0

Percentage distribution of employed women by level of schooling

0–5 years

19.8

11.2

6–9 years

39.5

21.0

10–12 years

34.6

33.7

13 years or more

6.2

34.1

Total

100.0

100.0

Percentage distribution of employed women by type of household

Two-parent with children

30.4

36.8

Single-parent

19.4

15.5

Two-parent without children

9.7

10.8

Extended

32.6

29.9

Otherb

7.8

6.9

Total

100.0

100.0

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

a The data shown represent the weighted average for Latin America calculated on the basis of 14 countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Peru, Plurinational State of Bolivia and Uruguay. In the case of the Plurinational State of Bolivia and Colombia, the data refer to 2021, and in the case of Honduras, to 2019.

b This category includes single-person households (which account for 6.4% of women employed in the household as employers sector and 5.3% of all employed women), composite households (which account for 1.2% of women in both cases) and non-nuclear households (which account for 0.3% of women employed in the household as employers sector and 0.4% of all employed women).

In recent years, the average age of women employed in the paid domestic work sector has risen and concern remains over women who are unable to leave paid work at advanced ages because they lack a pension system that would allow them to retire. There is also ongoing concern over paid domestic work performed by girls. Moreover, studies show that the health status of women in the sector is deteriorating owing to the physical and mental demands involved in the related tasks (responsibility for looking after people) (MTEySS/OISS/SRT, 2020; Correa, 2021).

As well as the challenges posed by poor wages and low rates of social security affiliation or contribution in domestic work, the tasks included in it are often very diverse. The ILO Domestic Workers Convention, 2011 (No. 189) describes domestic work as “work performed in or for a household or households” (ILO, 2011, art. 1). This may include activities such as cleaning, cooking, washing, ironing, caring for dependants, gardening and guard duty, driving for a family and caring for pets.

In this connection, several countries in the region have begun to clarify and delimit the responsibilities of female workers, in order to establish their labour rights and guarantees based on the distinction between strictly domestic work and more care-related work, which often involves heavier demands and responsibilities. In Chile, for example, domestic work contracts must specify the tasks to be performed, and must indicate whether these include the care of dependent persons.[8] The Ministry of Social Development and Family of Chile has also created a platform to identify caregivers and provides them with priority access to certain services. In Argentina, the National Commission for Work in Private Households (CNTCP) has set wage categories based on the tasks and modalities of work registered in the Federal Public Revenue Administration (AFIP).[9]

It is essential to clarify the tasks and responsibilities required and to invest in information systems for the design of labour inclusion policies specifically for paid domestic workers devoted mainly to caregiving. For example, providing preferential access to public institutions, or offering opportunities for continuous training, specialization or certifications will enable them to acquire or build on caregiving skills.

4. Digital platforms for domestic and care work: challenges for labour inclusion

The digital revolution is giving rise to a new era in which patterns of consumption, business and production are being transformed. This is driven by the adoption of advanced digital technologies, expansion of digital infrastructure and massification of access devices (ECLAC, 2022a). As described in chapter II, platform-based jobs in Latin America and the Caribbean have increased significantly in recent years, and these jobs often contribute to informality and are performed in precarious working conditions, giving rise to new challenges in relation to labour inclusion. Digital platforms for domestic and care work have emerged as innovative tools to link the supply of labour for domestic and care tasks with households’ needs. The dissemination of technology and access to mobile devices and the Internet opens new possibilities for a sector that has traditionally been based on personal relationships of recommendation and trust (Cebollada, 2021). These digital platforms act as bridges between people who need specific services, such as housework, ironing, and care, among other tasks, and those who perform these jobs. Emerging technologies facilitate intermediation services, traditionally provided by employment agencies, combined with the digital platform economy. Unlike other platforms of this type that foster remote or distance work, these platforms focus on jobs that are inherently location-based, since they require direct physical interaction in the home or place of residence of the person hiring the service (ILO, 2021c).

These platforms have also enabled the emergence of new services, such as administrative arrangements for hiring domestic workers, in particular contract formalization, registration in social security systems, administration of payment and vacations, and tools to facilitate online payments. These advances can even make it easier for households to fulfil their responsibilities as employers and ultimately contribute to the formalization of labour relations (Pereyra, Poblete and Tizziani, 2023).

Although platforms may afford opportunities to improve working conditions in the sector, it is crucial to be alert to the ways in which they can make paid domestic work even more precarious, especially considering that this sector is one of the main avenues of employment for women in the region. Unlike home delivery or transportation services, domestic and care services were not widely consumed as on-demand services before the advent of digital platforms.

In the case of domestic and care work, the proliferation of digital platforms coincided with the change in consumer habits associated with online and home delivery services that proliferated during the COVID-19 pandemic. It also coincided with the crisis caused by the pandemic in the domestic work sector, as described in the previous section, in terms of the destruction of jobs and the fall in wages, which left female workers with less bargaining power than usual.

The characteristics of the platform economy —where employment relationships tend to become blurred, employers become clients and labour is an on-demand service— merit particular attention in the case of the domestic and care services sector, given that it already faces enormous challenges in relation to reducing job insecurity and guaranteeing a decent income.

(a) Changes in paid domestic work with the emergence of digital platforms

Although there are as yet no data to ascertain precisely the percentage of domestic workers hired over digital platforms, the trend is increasing and will continue to do so if its evolution elsewhere in the world is anything to go by (Hunt and Machingura, 2016). There are active platforms in at least 12 countries in the region, and the largest number are found in Colombia, Chile and Brazil. Colombia is the country in which online platforms that hire workers are most common, while in Chile and Brazil the main services are selection and connection between employers and employees, i.e. tasks similar to those previously performed by employment agencies. In the first case, the online platforms actually employ the workers, while in the second, the hiring is done by the person requesting the service. Most platforms also offer e-payment services and offer digitalized management of the workers hired (Pereyra, Poblete and Tizziani, 2023).[10]

A new development is the offer of on-demand services, where the employment relationship tends to become ambiguous. Messages are seen promoting services, such as: “Why wait? When you can have it NOW! “Housework NOW”, and “Last minute emergency?”

Although working conditions and regulatory frameworks vary from one country to another, in general platforms charge a commission and set service fees without defining working hours. These rates are published on the platform or negotiated privately by clients and workers. This negotiation is touted as a benefit for customers, using expressions such as “you set the price”. Although no platforms were found to state explicitly that offers below the legal minimum wage would be acceptable, there were cases in which the company stated that it would intervene in the negotiation if “the price is well above or well below the market price” (Blanchard, 2023). Some public testimonies on online platforms suggest that workers sometimes do not receive proper information about, for example, the size of the houses they are supposed to clean. Per-service setting, along with generally one-way evaluation systems, can expose workers to the risk of becoming committed without full information and, as a result, receiving negative feedback or working more hours than had been agreed upon (Kalla, 2022).

New forms of platform-based intermediation can also affect working conditions. Although some platforms assume responsibilities as employers, others adopt a role primarily as technological intermediaries. Service contracts, which are usually similar in format to independent contractor arrangements, may include clauses of exclusivity with the platform company, provisions on the acceptance or rejection of work, and performance evaluation protocols, among other things.[11] This contract modality can affect labour rights such as social security, labour protections and the minimum wage. Despite the progress that has been made at the national and international level in adapting labour regulations to ensure decent work, significant challenges remain (ILO, 2021c).

Access to new paid work opportunities and the promise of labour flexibility offered by digital platforms have given rise to irregular working hours, fluctuating income and poor coverage of pension systems, in addition to the presumption of permanent availability. At the same time, labour income is affected by the payment of commissions to platform companies or possibly by the rejection of work (ILO, 2021c).

Despite the promise of greater autonomy, digital platforms can significantly limit the employment opportunities of female workers through algorithmic management of task allocation and evaluation mechanisms, among other factors. Algorithmic performance management redefines work relations and the daily experience of people offering their labour over the platform. Algorithms, based on data generated by workers themselves, often lack transparency and can lead to decisions that do not always properly reflect their actual performance. For example, a poor rating from someone who has contracted a service and feels dissatisfied owing to factors beyond the worker’s control can adversely affect her reputation on the platform and, therefore, her future job opportunities. This results in a much higher level of exposure than the job references used in traditional hiring modalities. Algorithmic design can also exacerbate sources of discrimination and introduce biases along the lines of existing inequalities (ILO, 2021c; ECLAC/ILO, 2019). The lack of control by workers over mechanisms for assigning services, the exposure of their profiles and one-way evaluation systems can limit their autonomy and become another expression of the concentration of power in hierarchical relationships, as described in relation to the structural challenge of gender inequality (ECLAC, 2017b).

Regarding the services that are published, platforms usually establish a principal division between cleaning work and care tasks and, among the latter, between the care of children and care of older persons. Some platforms also offer home repairs and specific cleaning tasks (windows, floors, upholstery) and, as an effect of the COVID-19 pandemic, special disinfection services. In this respect, platforms are ahead of the regulations of countries that, for the most part, do not distinguish between the diverse activities carried out in households and performed in the domestic work sector. Many platforms also provide paid or free training and certifications for female workers through their applications or websites.

Although most of the initiatives in this arena are private and profit-seeking, public entities too are making incipient efforts to connect the demand and supply of paid domestic work via digital platforms (see box III.1). Conversely, although there are a number of projects involving cooperatives or trade unions that provide intermediation services or employment exchanges, no platform initiatives have been identified in this sector (Cebollada, 2021).

Box III.1

Federal Map of Care in Argentina

Since its establishment, the Ministry of Women, Genders and Diversity of Argentina has been pursuing a broad and profound strategy to set up a comprehensive care system. One of the pillars of this strategy is the Federal Map of Care.

The dashboard of the Federal Map of Care carries information on the supply of public, private and community institutions providing care services to various populations across the country, training for workers in the sector and estimates of demand for of care at the local level.

The map is the product of close collaboration between the Ministry and the ECLAC office in Argentina, through the Early Childhood and Comprehensive Care System programme of the United Nations Sustainable Development Goals Fund. The objective of this collaboration was to create a platform and carry out studies that would contribute to the definition of public policies linked to the various spheres of care in Argentina.

The Map has an external interface for public use, consisting of a web portal and a mobile phone application, which provides georeferenced information on the care services available. The public map provides information about the following: (i) the supply of care services provided by public and private institutions, and social and community organizations, and (ii) the supply of training for caregivers and their certification. The system supports a search function and the use of various filters, and takes a rights-based approach to ensure accessibility for persons with disabilities and for people who have only old computer equipment, telephones with limited functions, or little or no connectivity.

The Map also has an internal interface in a visualization panel for policy management, with a dashboard providing information about care service supply and demand based on the visualization and analysis of spatial and statistical data. This interactive tool yields information on the social organization of care in the territory, the distribution of care facilities and care-related training, potential demand and areas in which coverage is satisfactory or poor, among other data. The mapping also serves to prepare a catalogue of care facilities and services at the territorial level, in order to identify areas that are critical or lacking sufficient care institutions at the territorial level, a task that was carried out with the support of ECLAC. On the basis of this information, it was estimated that care demand intensity was “high or very high”, in 6 of 10 households with unmet basic needs; double the average for all households. It was also concluded that, of the more than 550,000 single-parent households with children under 15, 47% showed a “high or very high” intensity of demand for care (see map).

Argentina: departmental average of household care work demand intensity, adjusted by the potential caregiving population,a 2022

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the National Institute of Statistics and Censuses (INDEC).

Note: Data processed using Redatam+SP and mapped in QGIS.

The boundaries and names shown on this map do not imply official endorsement or acceptance by the United Nations.

a The intensity of the demand for unpaid care work in households evaluates the need for care at the household level, weighting the hours of unpaid care that each individual requires by age group, following the methodology of Durán (2012), adjusted according to information from the 2013 Annual Urban Household Survey. The index is calculated by adding the score of all the weighted hours of the household members, then this figure is normalized by the number of potential caregivers (PPC) in the household. This index serves to identify geographical areas with different intensities of demand for care.

The existing structure also supports the provision of information to connect those working in the sector with potential sources of demand, as well as data on care-related training provided by the Ministry of Labour, Employment and Social Security or the Ministry of Social Development in order to certify specific workers. These data could be georeferenced in different parts of the territory and could include contact information, as a strategy that could help to drive decent work creation in the sector.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of National Institute of Statistics and Censuses (INDEC); Economic Commission for Latin America and the Caribbean/Ministry of Women, Genders and Diversity of Argentina (ECLAC/MMGyD), “Mapa Federal del Cuidado en la Argentina: construcciones conceptuales y usos”, Project Documents (LC/TS.2022/173-LC/BUE/TS.2022/18), Santiago, 2022; Ministry of Women, Genders and Diversity of Argentina (MMGyD), “Mapa Federal del Cuidado” [online] https://mapafederaldelcuidado.mingeneros.gob.ar/; M. Á. Durán, El trabajo no remunerado en la economía global, Fundación BBV, 2012.

(b) The regulation of platform work to promote women’s labour inclusion: the future of domestic and care work

The digital transformation has opened up new opportunities for the paid domestic work and care sector, because it allows those offering this type of labour to connect with those who require it. However, the structural inequality that exists in Latin America and the Caribbean threatens to limit access to these opportunities and even to accentuate existing gaps. In the case of digital platforms for domestic and care work, it is important both to protect workers’ labour rights and to prevent the creation of a segmented market where those who have access to technology receive services with different standards and prices to those received by people lacking that access. Thus, public policies are increasingly important to ensure that digitalization improves the lives of all and prevents gaps from widening in a region already marked by great inequality (ECLAC, 2021b).

An exercise that compiled public information from over 70 digital platforms in 12 countries in the region served to identify practices that could exacerbate the structural challenges of gender inequality. Socioeconomic inequality and the persistence of poverty could be worsened by the casualization of work caused by low commissions and pay, and by asymmetric evaluation systems biased towards employers. The illustrations of care-related and cleaning work on websites tend to show a majority of women and to use terms such as “help” or “assistance”, which perpetuates the sexual division of labour, reinforces patriarchal cultural patterns and gender stereotypes, and obscures the employment relationship. Finally, one-way evaluation systems and workers’ lack of control over the allocation of services can limit their autonomy and reflect the concentration of power and hierarchical relationships inherent in gender inequality. Worker representation becomes all the more important in relation to this last point, especially evaluation by trade unions of the way platforms operate.

Without proper regulation, there is a risk of employment becoming even more precarious (ILO, 2021a). It is thus essential to consolidate regulatory frameworks to protect the rights of domestic workers and those working in the care sector. Platforms also have an unavoidable responsibility to ensure safe, fair working conditions in the framework of social co-responsibility between the State, the market or the private sector, households and families, and communities. In this context, social dialogue is a crucial tool for facilitating the creation of strategies to ensure the rights of female workers and recognize domestic and care work as essential for the sustainability of life.

Regulation of these technologies by the State in accordance with current non-discrimination legislation and within the framework of respect for labour rights, human rights and public participation could lead to more efficient and effective progress in decent work creation, in improving the well-being of those requiring domestic and care work, in the professionalization and certification of workers, and in the allocation of social value to these tasks. In this regard, the national care systems now being discussed, designed and implemented in several countries in the region have at their disposal a powerful tool to advance in the recognition, redistribution and reduction of domestic and care work, and to accelerate the growth and revitalization of a sector of the economy that is fundamentally important for the sustainability of life (ECLAC, 2019a; ILO, 2019).

B. Labour inclusion and international migration: opportunities and challenges

Migration in the region has increased and become more diversified in recent decades, and it has become more prevalent in countries that had no previous tradition of migration. These changes open up opportunities and can make valuable contributions to receiving countries, but they also create pressure and pose significant challenges in terms of labour inclusion. The arrival of large numbers of migrants within a short period of time can make it particularly difficult for migrants to regularize their administrative status and render them more vulnerable to abuse and discrimination. It may also force them to find work in the informal sector, take jobs for which they are overqualified or work under exploitative conditions. The heterogeneity and the many different sociodemographic profiles (in terms of education, gender, ethnicity or race and other factors) of the migrant population, combined with the highly dynamic nature of labour markets, influence labour inclusion processes in receiving countries. In order to ensure that the migrant labour force can make a positive contribution to host countries, labour inclusion policies need to be developed that promote migrants’ ability to exercise their rights and their access to formal employment that provides them with social protection.

1. The intensification of migration flows has hindered the labour inclusion of migrants

Migration in the region has become more diverse than it was in the past. While the number of persons migrating to developed countries (primarily the United States and Spain) remains very high, in the past two decades intraregional migration has increased sharply in terms of both numbers and territorial scope. Between 2000 and 2020, intraregional migration climbed by 72% in Latin America and the Caribbean, which was the steepest growth rate of any region in the world in relative terms (United Nations, 2020). In recent times, migration flows have also expanded to encompass countries that formerly had no tradition of immigration. The intensification of intraregional flows and the greater heterogeneity of the migrant population in terms of origin, destination and determining factors are associated with an increase in forced migration as well (Cecchini and Martínez, 2023).

These changes pose considerable challenges for Latin American and Caribbean societies, which must focus on achieving a sustainable economic recovery while also facilitating migrants’ social and labour inclusion (ECLAC, 2019a). The associated challenges intensified during the pandemic, which impacted migrants’ mobility and their ability to return to their home countries and altered their income-generating and employment opportunities. The participation of women and men as essential workers during lockdowns helped their host societies cope with the pandemic and contributed to those societies’ well-being, but these workers were nonetheless targets of stigmatization and discrimination in many countries (ECLAC, 2020).

Migrant worker and migrant entrepreneurship makes a valuable contribution to host societies by creating economic activities, providing jobs for non-migrants and transferring human capacity and innovations. Analyses of the labour inclusion of migrants and their economic contributions to their host societies should also consider their possible contribution to a rejuvenation of the workforce in countries where the population is rapidly ageing. In such countries, the expansion of the labour force through migration has a positive impact on economic growth and helps to ease structural worker shortages, especially if migrant women and men are employed in accordance with labour laws and provided with social protection.

Migrants’ contributions to their host countries may be undermined, however, when there is a massive inflow of migrants within a short period of time if receiving countries are unprepared to take advantage of those contributions, lack effective migrant regularization procedures and do not have the necessary information to take prompt, appropriate decisions and actions. In such situations, there is a greater likelihood that migrants will be subject to abuse, have to work in the informal sector and in jobs for which they are overqualified or be the object of blatant discrimination. Persons who come from less developed countries and markedly different cultures, persons who have been forced by circumstance to migrate and whose migration status is irregular, those who have few resources and persons from certain ethnic or racial groups are particularly vulnerable (ECLAC, 2020).

For centuries, the region was primarily a destination for large groups of migrants, but this changed dramatically in the second half of the twentieth century, when large numbers of people began to leave Latin America and the Caribbean for the United States and, later, for some European countries, such as Spain.[12] More recently, intraregional mobility has also increased sharply, all of which has redrawn the continent’s migration map.

According to United Nations estimates (2020), the Latin American and Caribbean region continues to experience net out-migration, although the rate has diminished, primarily because of the curbs on the emigration of Mexican citizens to the United States and the consequent reduction in that flow (see figure III.10).

Figure III.10

Latin America and the Caribbean (46 countries and territories): variation in the number of migrants, by regional origin and destination, 2000–2010 and 2010–2020

(Number of persons)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations, International Migration 2020 Highlights (ST/ESA/SER.A/452), New York, 2020.

Note: “Extraregional emigrants” are defined here as persons born in one of the 46 countries or territories covered in the figure who were residing in a country or territory outside Latin America and the Caribbean in the period in question. The term “extraregional immigrants” refers to persons born in a country or territory outside Latin America and the Caribbean who, during the period in question, resided in one of the 46 countries and territories covered in the figure. The category “regional migrants” refers to persons born in one of the 46 countries and territories of Latin America and the Caribbean who, during the period in question, were residing in a country or territory in the region other than their country or territory of birth. In all of these cases, the figures shown are the balance or variation in the number of such persons between the first and last year of the period in question.

As may be seen from the figure, the number of intraregional migrants has soared: between 2000 and 2010, their number rose by 1.57 million but, in the following decade, it climbed by over 5.9 million. The most influential factor in this increase was the upsurge in emigration from the Bolivarian Republic of Venezuela; in the space of just five years (from 2015 to 2020), more than 5.3 million persons left that country, and 80% of them moved to another Latin American nation. This flow has reshaped the region’s migration patterns and has resulted in some countries that did not attract any substantial number of migrants in the twentieth century receiving massive inflows of migrants during this period.

2. Migrants make a valuable contribution to inclusive social development

(a) Intraregional migration in Latin America and the Caribbean primarily takes the form of labour migration

In Latin America and the Caribbean, a majority of intraregional migrants are workers, i.e. persons of working age who are moving in search of a job that will enable them to improve their social and economic position. Labour migration, which entails a transfer of a portion of the workforce from countries of origin to countries of destination, has attracted a great deal of attention in production sectors (see box III.2).

Box III.2

The positive impact of migrant workers on private sector companies

Private-sector companies’ inclusion of migrant workers has sparked growing interest on the part of the business world. Three recent studies have documented the positive impact of labour inclusion in Colombia and Chile.

Semi-structured interviews conducted with a number of companies as part of a study carried out by the National Business Association of Colombia (ANDI), the largest employers’ association in that country, in cooperation with the United States Agency for International Development (USAID), Fundación Corona and ACDI/VOCA-Colombia led to the identification of seven specific benefits: (i) low staff turnover rates; (ii) high levels of staff qualifications; (iii) high effectiveness and productivity indicators; (iv) a strong sense of belonging in the company in question; (v) a stronger production chain and strategic partnerships; (vi) coverage of hard-to-fill vacancies; and (vii) creativity and innovation. With regard to the first point, the report notes that the low turnover rate may be associated with the precarious economic and social situation of migrant workers, who are therefore firmly committed and loyal to the people who have given them an opportunity to work. The high level of qualifications of such workers has to do with the human talent possessed by immigrants, mainly from the Bolivarian Republic of Venezuela. With respect to productivity, respondents mentioned that the inclusive employment strategy used by these firms entails providing training to the migrants they hire. One of the aspects that the respondent companies place a great deal of value on is that migrants will accept positions that Colombian workers are not interested in (ANDI and others, 2022).

Another study draws on the results of the National Labour Demand Study (ENADEL). That study was designed and coordinated by the Labour Observatories Network of the National Training and Employment Service (SENCE), which is attached to the Ministry of Labour and Social Security of the Government of Chile, in cooperation with a number of Chilean universities. The survey has been carried out every year since 2019 and is aimed at characterizing the workforce, detecting training preferences and forecasting companies’ demand for persons to fill certain types of positions and for certain types of skills based on regionally representative data. The survey is used to compile data on small, medium-sized and large companies in different sectors each year. One of the sectors surveyed in 2019 was the tourism industry. In the Santiago Metropolitan Region, 76% of the tourism agencies that were surveyed reported having difficulties in filling vacancies. Respondents underscored the contributions made by foreign workers to improvements in the quality of service and hospitality in the regional and national tourism industries. They also emphasized language competencies, which are needed and valued in the tourism business (SENCE, 2019).

A third study carried out in 2021 was conducted by the Chilean office of the International Organization for Migration (IOM). The aim of that study was to identify employment opportunities for migrants in the country. A total of 61 companies (78% of which were located in the Santiago Metropolitan Region) in different sectors in four regions of the country were interviewed. When asked about the attributes of migrant workers employed in those companies, the respondents’ answers indicated the following: 37.7% said that migrants’ productivity was above average, 27.7% said that they showed more initiative and 13.3% said that they had better social and emotional skills. The respondents’ answers to questions about the effects that migrant workers had had on their businesses indicated the following: 31.9% said that they had improved the work environment, 26.4% said that they had boosted productivity, 11.1% said that they had improved the companies’ satisfaction indicators and 9.7% said that they had improved customer relations. Employers’ recognition of the social and emotional skills of migrants is significant given the fact that, in this same survey —which was conducted between July and September 2021 at the height of the economic recovery and reactivation following in the wake of the COVID-19 pandemic— when employers were asked what worker skills were needed to overcome the crisis, 7 out of 10 of them said that those were the skills that were needed. That was far more than the 22% of employers who responded that technical skills were the ones required (Dehays, 2021).

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of National Business Association of Colombia (ANDI) and others, Inclusión laboral de migrantes, una apuesta del sector privado, Bogotá, 2022; National Training and Employment Service (SENCE), Encuesta Nacional de Demanda Laboral (ENADEL) 2019, Santiago, 2019; J. Dehays, “Oportunidades de inserción laboral para la población migrante y refugiada en Chile”, Cuadernos Migratorios, No. 13, Santiago, International Organization for Migration (IOM), 2021.

The percentage of international migrants in the labour force of seven countries of the region is substantial but varies considerably, ranging from 2.6% in Ecuador to 12.2% in Costa Rica (see figure III.11). In both Chile and Costa Rica —which are important destination countries for women migrants seeking employment in care work (see section III.A herein and ECLAC, 2019a)— and in Panama, migrant women outnumber migrant men, whereas just the opposite is true in the Dominican Republic.

Figure III.11

Latin America (7 countries): percentage of immigrants in the labour force, by sex, latest year available

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Census data illustrate the growth of the migrant labour force in some countries. In Chile, the percentage of migrants in the labour force rose from 1.6% in 2002 to 6.5% in 2017 and, in Colombia, between 2005 and 2018, that percentage increased from 0.3% to 2.5%. The proportion of migrants in the labour force continued to climb thereafter in both countries and in Peru, where it went from 0.3% in 2007 to 1.4% in 2017. Household survey data indicate that the percentage of migrant workers in the labour force in the Dominican Republic rose from 4.5% to 6.7% between 2016 and 2021 and that it expanded in Argentina from 5.3% in 2014 to 6.1% in 2019.

The migrant population’s contribution to the labour force is primarily accounted for by younger migrants, particularly in countries where large numbers of migrants have recently arrived.[13] As indicated by the data shown in figure III.12, migrants represent 12% of the members of the labour force between the ages of 20 and 29 in Chile and 13% of workers between the ages of 30 and 39. In Colombia, the largest proportions of migrant workers in the labour force (nearly 7%) are found in the two youngest age groups (up to 29 years of age). In countries with a longer-standing migration tradition, such as Argentina and Costa Rica, migrants also make a contribution to older segments of the workforce. In the Dominican Republic, for example, migrants make up 10% of the members of the labour force between the ages of 30 and 39.

Figure III.12

Latin America (7 countries): distribution of the labour force, by age and migration status, latest year available

(Number of workers)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The data are from 2019 for Argentina, Colombia and Panama, from 2020 for Chile and from 2021 for Costa Rica, the Dominican Republic and Ecuador.

(b) Length of residence and nationality of origin

Given the small size of the samples of international migrants in most of the household surveys (Gutiérrez and others, 2020), the data used here cannot be disaggregated for two key variables, namely country of origin and length of residence in the host country. The data compiled in the most recent population censuses carried out in Colombia, Chile and Peru (three countries with large, recently arrived immigrant populations) provide some information on both of these variables. In Colombia, a large proportion of the migrant workforce arrived in the country quite recently. In 2018, 85% of those migrants had arrived in the country within the last five years preceding the census, and most of them (94% of the recent arrivals) had come from the Bolivarian Republic of Venezuela.

In Peru, the latest census was conducted in 2017, when large-scale migration from the Bolivarian Republic of Venezuela was just beginning. The number of immigrants rose steeply after that time (see box III.3) but, even then, 54% of the migrant labour force was composed of recent arrivals and 44% of them were from the Bolivarian Republic of Venezuela.

Box III.3

Venezuelan migrants in Peru

Information from the National Migration Superintendency indicates that there were 1,347,000 foreign residents in Peru in 2021 and that 87% of them were Venezuelan nationals. In order to learn more about this population group, in 2018 the National Institute of Statistics and Informatics (INEI) carried out its first survey of the Venezuelan population in the country (ENPOVE I). It conducted another such survey (ENPOVE II) in 2022.

Data from that second survey indicate that the age profile of this group is quite young: 57.4% are between 20 and 49 years of age, 28.3% are between 0 and 14 years of age, 6.4% are between the ages of 15 and 19 and 7.7% are between the ages of 50 and 79. The composition of the migrant population in terms of sex is quite balanced (50.6% women and 49.4% men). Among those aged 18 years and over, 43.9% have a secondary education, 31.0% have a higher education, 14.4% have an advanced technical education, 9.6% have a basic technical level of instruction, 1% have a master’s or doctorate degree and 0.1% have no education. Among those with a university education, 22.9% followed engineering, industrial or construction-related courses of study, 19.0% specialized in education, 16.7% in administration, 5.9% in law, 5.9% in accounting and finance, 5.0% in nursing and 3.1% in medicine.

Interestingly, while 35.3% of the Venezuelan migrants in Peru do not have a visa, 82.0% of them are in the labour force and, of that 82.0%, 97.9% are employed (92.5% of men and 71.8% of women).

The ENPOVE II results also show that only 19.2% of the employed Venezuelan refugee and migrant population in Peru has an employment contract; 55.0% of that population is working in the service sector, 24.3% in commerce, 12.7% in manufacturing and 7.2% in construction.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of National Institute of Statistics and Informatics (INEI), “Segunda Encuesta Dirigida a la Población Venezolana que Reside en el País II ENPOVE 2022: informe”, Lima, 18 January [online] https://www.gob.pe/institucion/inei/informes-publicaciones/3352206-segunda-encuesta-dirigida-a-la-poblacion-venezolana-que-reside-en-el-pais-ii-enpove-2022.

In Chile, 58% of the members of the foreign labour force present in the country in 2017 were recent immigrants. By that time, Venezuelan migrants were beginning to arrive, but most of the migrants were from Peru (25%), the Plurinational State of Bolivia (19%), Colombia (14%), Argentina (9%) and Haiti (8%). Of the migrants who had arrived during the five-year period preceding the census, 17% were from Colombia, 17% were from the Bolivarian Republic of Venezuela and 13% from Haiti.

While recent census data are not available for the other countries in the region, all of them, but particularly Argentina and Costa Rica, have a long history of immigration and it is therefore fairly certain that the percentage of recent arrivals in their migrant populations is far smaller than it is in the countries mentioned above.

(c) Migrants’ contribution to GDP

Immigrants in receiving societies’ workforces make a positive contribution to GDP, with the size of that contribution varying depending on the specific sectors in which they work. In order to gauge this impact, a model has been used to measure GDP, disaggregated by the country of origin of the members of the workforce, in six receiving countries: Argentina, Chile, Colombia, Costa Rica, Dominican Republic and Ecuador. The model is outlined in box III.4 and the results are detailed in table III.2.

Box III.4

Method used to estimate migrants’ contribution to GDP

Migrants’ contribution to GDP has been estimated using a mathematical model for disaggregating annual GDP by the migrant and non-migrant components of the labour force using the following equation:

where: GDPLi is the GDP generated by migration category i of the labour force (non-migrants and, here, migrants);

OMeLj is the mean output per worker in economic sector j; and

Lij is the volume of workers in migration category i in sector j.

In order to carry out this calculation, a methodology is needed for equating the classifications of members of the working population by national origin and by sector of economic activity used in population censuses and household surveys in each country with the classifications of economic activities used by central banks to disaggregate national GDP by sector. This has been done using each country’s classification of economic activities, which is usually in line with international classification systems. For further information, see the study recently conducted by Canales (2022), who used this method to estimate the contributions of migrants in Chile, Costa Rica and Peru.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of A. Canales, “Evaluación cuantitativa de las contribuciones de las migraciones recientes al desarrollo sostenible: el caso de Chile”, Sobre las contribuciones de la migración al desarrollo sostenible: estudios en países seleccionados, Project Documents (LC/TS.2021/195), J. Martínez and M. Cano (eds.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2022.

These data can be used to calculate the contributions that migrants make to economic growth in terms of their contributions to GDP during economic booms, crises and recoveries.

The contributions made by migrants to countries’ GDP can be divided into three categories: situations in which they make a significant and continuously growing contribution to national GDP; those in which their contribution is somewhat less significant but is nonetheless steadily growing; and those in which migrants’ contribution to GDP has been stable.

The first group includes countries such as Chile and the Dominican Republic, where migrants contributed 11.5% and 8.7%, respectively, to GDP in 2022, whereas their contributions had been less than 2% up to 2011 and 6.1% in 2017 in Chile and 5.5% in 2010 in the Dominican Republic.

In Ecuador and Colombia, migrants’ contribution has also been on the rise, but less so than in the countries discussed earlier. In 2010, there were relatively few migrants in Colombia, and the migrant population accounted for just 0.4% of GDP. Since the latter half of the 2010s, however, with the growing inflow of Venezuelans, migrants’ contributions to GDP rose to 2.1% in 2018 and 4.8% in 2022. In Ecuador, migrants’ contribution to GDP climbed from just 1.1% in 2015 to 2.1% in 2020 and 2.5% in 2022.

The growth of migrants’ economic contributions to Chile, Colombia, the Dominican Republic and Ecuador is associated with the increase in labour immigration to those countries. In such countries as Argentina and Costa Rica, which have a long migration tradition, on the other hand, immigration has remained fairly stable over the last decade or has risen very slowly. This could also be the reason why migrants’ contribution to GDP has remained fairly flat, although it varies somewhat from country to country.

In Costa Rica, migrants’ contribution to GDP during the 2010s and up to the start of the COVID-19 pandemic fluctuated between 10% and 11%, falling to 8.9% in 2022. The situation was similar in Argentina, although migrants’ contribution was smaller (3.9% and 4.7% in 2013 and 2022, respectively).

Table III.2

Latin America (6 countries): gross domestic product, by migrant and non-migrant status of members of the labour force, 2009–2022

A. Volume

(Millions of dollars at constant 2018 prices)

Chile

Costa Rica

Dominican Republic

Colombia

Ecuador

Argentina

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

2009

215 172

211 376

3 796

44 175

51 980

239 769

81 652

435 081

2010

227 763

46 543

56 315

53 202

3 112

250 546

249 505

1 041

84 530

473 736

452 272

21 463

2011

241 939

237 066

4 873

48 592

43 583

5 009

58 079

267 953

91 181

505 089

483 936

21 153

2012

256 831

50 965

45 208

5 757

59 657

278 437

96 325

502 639

484 135

18 504

2013

265 328

257 408

7 921

52 236

46 949

5 287

62 566

292 732

101 090

512 316

490 328

21 987

2014

270 085

54 087

47 812

6 275

66 977

305 902

104 920

497 337

478 308

19 029

2015

275 897

265 080

10 817

56 062

50 323

5 739

71 616

68 162

3 455

314 945

105 024

103 826

1 198

509 686

2016

280 733

58 419

51 804

6 615

76 386

321 519

103 736

102 602

1 134

498 435

477 997

20 438

2017

284 545

267 141

17 404

60 848

54 477

6 370

79 950

74 648

5 303

325 889

106 193

105 041

1 152

512 465

492 184

20 281

2018

295 898

62 439

55 583

6 857

85 533

334 246

325 284

8 962

107 562

105 630

1 932

502 284

480 615

21 669

2019

298 097

63 949

56 907

7 042

89 854

344 898

331 994

12 904

107 575

105 513

2 062

484 550

461 724

22 826

2020

279 778

251 077

28 701

61 216

54 477

6 739

83 816

319 885

308 387

11 498

99 198

97 123

2 075

433 674

416 774

16 900

2021

312 617

276 199

36 418

65 979

59 310

6 669

94 101

355 124

338 181

16 943

103 399

100 681

2 718

483 331

464 275

19 056

2022

320 246

283 359

36 887

68 882

62 765

6 117

98 673

90 107

8 567

380 894

362 613

18 281

106 447

103 750

2 697

512 995

489 751

23 245

B. Relative value

(Percentages of total GDP)

Chile

Costa Rica

Dominican Republic

Colombia

Ecuador

Argentina

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

Total GDP

Non-migrants

Migrants

2009

100

98.2

1.8

100

100

100

100

100

2010

100

100

100

94.5

5.5

100

99.6

0.4

100

100

95.7

4.3

2011

100

98.0

2.0

100

89.7

10.3

100

100

100

100

95.7

4.3

2012

100

100

88.7

11.3

100

100

100

100

95.7

4.3

2013

100

97.0

3.0

100

89.9

10.1

100

100

100

100

95.7

4.3

2014

100

100

88.4

11.6

100

100

100

100

96.2

3.8

2015

100

96.1

3.9

100

89.8

10.2

100

95.2

4.8

100

100

98.9

1.1

100

2016

100

100

88.7

11.3

100

100

100

98.9

1.1

100

95.9

4.1

2017

100

93.9

6.1

100

89.5

10.5

100

93.4

6.6

100

100

98.9

1.1

100

96.0

4.0

2018

100

100

89.0

11.0

100

100

97.3

2.7

100

98.2

1.8

100

95.7

4.3

2019

100

100

89.0

11.0

100

100

96.3

3.7

100

98.1

1.9

100

95.3

4.7

2020

100

89.7

10.3

100

89.0

11.0

100

100

96.4

3.6

100

97.9

2.1

100

96.1

3.9

2021

100

88.4

11.6

100

89.9

10.1

100

100

95.2

4.8

100

97.4

2.6

100

96.1

3.9

2022

100

88.5

11.5

100

91.1

8.9

100

91.3

8.7

100

95.2

4.8

100

97.5

2.5

100

95.5

4.5

Source: Economic Commission for Latin America and the Caribbean (ECLAC) on the basis of Ministry of Social Development and Family of Chile. National Socioeconomic Characterization Survey (CASEN). 2009–2020; National Institute of Statistics of Chile. New National Employment Survey, 2020–2022; National Institute of Statistics and Census of Costa Rica. National Household Survey, 2011–2022; National Bureau of Statistics of the Dominican Republic. IX National Population and Housing Census, 2010; National Multipurpose Household Survey, 2015, 2017 and 2022; National Institute of Statistics and Censuses of Argentina (INDEC). Permanent Household Survey, 2010–2022; National Administrative Department of Statistics of Colombia (DANE), National Quality of Life Survey, 2010 and 2018–2022; National Institute of Statistics and Censuses of Ecuador, National Survey of Employment, Unemployment and Underemployment, 2015–2022; Economic Commission for Latin America and the Caribbean (ECLAC), CEPALSTAT [online database] https://statistics.cepal.org/portal/cepalstat/index.html?lang=en; and official data from the respective countries’ central banks.

Finally, in addition to their many other contributions, migrants help to strengthen their home countries’ economies through their remittances, which represent a large percentage of some nations’ GDP (see box III.5).

Box III.5

The contribution of remittances and their growth

Migrants contribute to their home countries and communities and to their families by transferring a portion of their incomes to them, thereby helping to meet the recipient households’ basic needs (ECLAC, 2019b). Mexico continues to be the largest recipient of remittances in the region, accounting for 42% of the total. As a percentage of GDP, however, remittances make a larger contribution in a number of other countries where they represent a fifth or more of GDP. Remittances represent 23.8% of GDP in El Salvador, 19.8% in Guatemala, 22.5% in Haiti, 21.2% in Jamaica and 19.9% in Nicaragua (World Bank, 2022; Cecchini and Martínez, 2023).

World Bank data for 2022 indicate that the percentage of total world remittances represented by the total remittances received by Latin American and Caribbean countries has increased steadily over the past decade. In addition, remittance flows proved to be quite resilient during the COVID-19 pandemic, climbing by 26% between 2020 and 2021 and by 9.3% between 2021 and 2022. It is projected that the region’s remittance receipts will represent 18% of total remittances worldwide in 2023.

Latin America and the Caribbean: remittances received, 2015–2023

(Billions of dollars and percentages of remittances worldwide)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of World Bank, “Remittances brave global headwinds. Special focus: climate migration”, Migration and Development Brief, No. 37, Washington, D.C., 2022.

Note: The figures for 2022 are estimates and those given for 2023 are projected.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of World Bank, “Remittances brave global headwinds. Special focus: climate migration”, Migration and Development Brief, No. 37, Washington, D.C., 2022; Economic Commission for Latin America and the Caribbean (ECLAC), Social Panorama of Latin America, 2019 (LC/PUB.2019/22-P/Rev.1), Santiago, 2019; S. Cecchini y J. Martínez, “Migración internacional en América Latina y el Caribe: una mirada de desarrollo y derechos”, CEPAL Review, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2023, in press.

3. Labour inclusion of migrants: obstacles to their inclusion, use of their capacities and protection of their labour rights

Analysing the processes involved in the labour inclusion of migrant populations in their host countries is a complex undertaking because, although the members of these population groups share the vulnerability associated with their status as migrants, they are also highly heterogeneous in terms of their sociodemographic backgrounds. The differing educational profiles, gender compositions and ethnic and/or racial identities of migrant groups influence the extent and nature of their economic integration. In addition to these factors, there are two others that must not be overlooked given their key importance in determining migrants’ labour inclusion: their access to rights as a condition for access to formal employment offering social protection; and the characteristics and dynamism of host countries’ labour markets.

(a) Migrants exhibit a greater propensity to join the labour force

Migrants, whose main motivation for leaving their home countries is, in most cases, to improve their living standards and quality of life, generally exhibit a greater propensity to join the workforce than non-migrants. As may be seen from figure III.13, the rates of economic activity for both male and migrant women are systematically higher than for non-migrants in some countries and notably so in the Dominican Republic, Costa Rica, Chile and Panama.

As the age profile of the non-migrant labour force is somewhat older, it could be argued that the differentials between the rates for the migrant and non-migrant workforces are a result of the two groups’ differing age structures. However, when the migrant population’s participation rates are re-estimated on the basis of the counterfactual supposition that its age structure is the same as the non-migrant population’s, it is seen that these differentials are robust, although somewhat narrower, and that they vary by sex. The standardized male participation rates for migrants in Argentina, Chile, Costa Rica, Colombia and the Dominican Republic are still higher, although somewhat less so. In the cases of Ecuador and Panama, however, the differentials almost disappear. The figures show that migrant women have a greater propensity to participate in the labour force than non-migrant women in Chile, Panama and Costa Rica but, when the rates are standardized, the differentials are not significant in the cases of Ecuador, the Dominican Republic and Argentina.

In sum, this exercise indicates that, with some exceptions, migrants’ participation in the labour force is greater than that of non-migrants even when it is assumed that the migrant and non-migrant populations have a similar age structure.

(b) Migrant populations’ unemployment levels tend to be lower

In the seven countries analysed, unemployment rates are lower for the migrant population than for non-migrants (see figure III.14). There may be various reasons for this, including greater employability, qualifications and skills, but it could also be attributable to migrants having less access to unemployment insurance or a greater willingness to forgo decent working conditions because of a greater need to obtain employment or some other source of income quickly (ECLAC/ILO, 2017). In Argentina, for example, this pattern is evident both during times of economic growth and during recessions and appears to be associated with greater flexibility on the part of migrants in adapting to ups and downs in demand and accepting less attractive working conditions (Cerrutti and Maguid, 2007).

Figure III.13

Latin America (7 countries): labour participation rates and standardized labour participation rates for the population aged 10 years and over, by migration status and sex, latest available data

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The standardized rate is calculated by adding the values obtained from multiplying the specific labour participation rates for each age group within the migrant population by the percentages of the total population represented by those same age groups in the non-migrant population.

Figure III.14

Latin America (7 countries): unemployment rates for migrants and non-migrants, by sex, latest year available

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Although, for the most part, migrants have lower unemployment rates than non-migrants do, the cases of Colombia and Ecuador are exceptions; this could be a consequence of the fairly sudden arrival of such large numbers of immigrants in these two countries and of the fact that recent immigrants, particularly women immigrants, have had difficulty in finding work or some other way to generate income, even in the informal sector.

(c) Educational profiles of migrant workers and their labour inclusion

The educational profiles of migrant workers are a key factor in determining their extent of labour inclusion, particularly with regard to job quality and income levels. The human capital perspective, which has been highly influential in the literature on differentiated inclusion and the migrant population’s wage gap, is based on a meritocratic concept as an explanation for inequalities. According to this line of thinking, differences in worker productivity (determined by the possession of different human capital endowments) account for such inequalities (Becker, 1964; Mincer, 1974). The indicator of educational attainment does not, however, provide a sufficient explanation for the differences in the labour inclusion of non-migrants and migrants. Other possible factors include the location where a person obtained his or her education (in the country of origin or destination) and the length of residence in the host country (which would correlate with the cumulative acquisition of experience in the host-country labour market and of greater social capital).

Migrants often encounter various types of barriers that hinder them from transferring their skills, whether because it is no easy matter to transfer prior experience to a labour market that has a quite different logic and dynamic or because degrees and educational credentials may not be officially recognized in the country of destination. These types of barriers may marginalize highly qualified members of the migrant workforce. In addition, persons with an irregular migration status may be barred from access to formal-sector employment and may be subject to open discrimination. Clearly, the underemployment of migrants as a result of these factors represents a loss for the host country, since it is not making full use of the skills and qualifications of these members of the workforce (Martínez and Cano, 2022).

Household survey data provide some of the inputs needed for an analysis of the educational levels of migrant workers.[14] A first observation that can be garnered from those data relates to the marked heterogeneity of immigrant populations, which reflects variations deriving from their countries of origin. Countries that have not traditionally been destinations for immigrants often have migrant populations that are more highly educated than the native-born population. This is the case of Venezuelan immigrants in Colombia and Ecuador, for example. The situation is somewhat similar in Chile, where 8 out of every 10 migrants who arrived in that country between 2010 and 2015 had a tertiary education (Carrasco and Suárez, 2018). On the other hand, in Costa Rica, which has traditionally been a destination for migrants from Nicaragua, the migrant population has a lower educational profile than the native-born population does.

In Argentina, the members of the immigrant population come from a wide range of countries and have widely differing educational profiles.[15] Immigrants from the Plurinational State of Bolivia and from Paraguay are, on the whole, less educated than native-born Argentines are, but those coming from Peru, Colombia, the Bolivarian Republic of Venezuela and countries outside the region are generally more educated (Cerrutti, 2018).[16] Panama and the Dominican Republic are at opposite ends of the spectrum. The immigrant population in Panama has a higher educational profile than the non-migrant population, whereas, in the Dominican Republic, the educational levels of the members of the immigrant population, most of whom come from Haiti, is substantially lower than that of the native-born population (see figure III.15).

Figure III.15

Latin America (7 countries): percentage distribution of the migrant and non-migrant labour force, by educational level, latest year available

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: The figures shown for Argentina, Colombia and Panama are from 2019, those given for Chile are from 2020 and those given for Costa Rica, Ecuador and the Dominican Republic correspond to 2021.

Recently arrived migrants, particularly from the Bolivarian Republic of Venezuela, have raised the educational profile of the migrant population in a number of host countries. This has been the case in Chile, where the percentage of migrants with a university degree or at least some tertiary education jumped from 39% in 2013 to 55% in 2020; in Argentina, where that percentage rose from 24% in 2014 to 30% in 2019; and in the Dominican Republic, where it climbed from 10% in 2016 to 13% in 2021. The opposite occurred in Panama, where the percentage of the migrant population with that level of education slipped from 45% to 37% between 2017 and 2019, while, in Costa Rica, the educational profile of the migrant population has remained virtually the same between 2014 and 2021.

(d) Labour inclusion: informality and the length of the workday

The fact that a larger portion of the migrant workforce tends to be employed in the informal sector is an important issue to be addressed by labour inclusion policies (ECLAC/ILO, 2017) (see chapter II). This disadvantageous situation has to do, on the one hand, with the concentration of migrant workers in occupations and sectors where informal working conditions are more prevalent (commerce, personal services, construction and small-scale workshops in the food and clothing industries) and, on the other, with the inherently more vulnerable position of migrants. International commitments concerning the protection of migrant workers notwithstanding (see box III.6), informal economic activities generally have lower entry barriers, and the influence exerted by situations of wage dependency falls outside the scope of labour regulations. In addition to the sectors where informal work has traditionally been common, new types of occupational informality are appearing, such as work performed on digital platforms, particularly transportation and delivery worker platforms, in addition to the domestic service work platforms discussed in section A of this chapter.

Box  III.6

International commitments concerning the protection of migrant workers

Public policies on labour inclusion should be guided by the commitments assumed under international agreements such as the Montevideo Consensus on Population and Development (2013), the Global Compact for Safe, Orderly and Regular Migration (2018) and the International Convention on the Protection of the Rights of All Migrant Workers and Members of Their Families (1990) and under International Labour Organization (ILO) conventions such as the Maintenance of Migrants’ Pension Rights Convention, 1935 (No. 48), the Migration for Employment Convention (Revised), 1949 (No. 97) and the Migrant Workers (Supplementary Provisions) Convention, 1975 (No. 143).

The aim of these instruments is to facilitate labour mobility, prevent migrants from finding themselves in an irregular situation, protect the right to decent work and social protection, and prevent discrimination. While the International Convention on the Protection of the Rights of All Migrant Workers and Members of Their Families is a binding instrument of international human rights law developed by the United Nations for the protection of all migrant workers and their families, the ILO conventions are more specific, targeted instruments focusing on upholding migrants’ rights to receive a pension (No. 48), promoting equal treatment for non-migrant workers and migrant workers with a regular migration status (No. 97) and promoting equal opportunities and treatment for migrant workers (No. 143).

Under the Global Compact for Safe, Orderly and Regular Migration, which has been ratified by the vast majority of countries in the region, States parties assume the following commitments, among others: minimize the adverse drivers and structural factors that compel people to leave their country of origin (objective 2); enhance availability and flexibility of pathways for regular migration (objective 5); facilitate fair and ethical recruitment and safeguard conditions that ensure decent work (objective 6); empower migrants and societies to realize full inclusion and social cohesion (objective 16); invest in skills development and facilitate mutual recognition of skills, qualifications and competences (objective 18); and cooperate in facilitating safe and dignified return and readmission, as well as sustainable reintegration (objective 21).

The States parties to the Montevideo Consensus on Population and Development recognize the important contributions made by migrants to their countries of origin and destination and express concern at the impact of the economic crisis on migrants’ living conditions and at the increasing complexity of migration. They also state that “…the global economic development process breeds inequalities and asymmetries which, in turn, generate an available workforce that is willing to work for minimum wages and in precarious conditions, and creates demand for highly flexible conditions that seek to extract the productive strength from these workers without respect for their human rights, in particular in the case of persons from less developed economies or living in dire poverty”. Under the Montevideo Consensus, the signatory countries agreed on 10 priority measures regarding the protection of the human rights of all migrants, including: to prepare comprehensive global and regional strategies to prevent infringement of the human rights of migrants, as well as to take advantage of the benefits and face the challenges arising from migration, including those relating to remittances and skilled migration in high-demand sectors, as well as the differential participation of men and women and the transnationalization of care (priority measure 68); to promote the signing of bilateral and multilateral social security conventions to enable migrant workers to accumulate years of service (priority measure 69); and to give priority, in each country, to strengthening coordination channels between sectors and between countries and to reinforcing intergovernmental cooperation mechanisms in order to guarantee the exercise of the human rights of all migrants, regardless of their migration status, from a gender-based perspective (priority measure 73).

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

A relatively unexplored aspect of the working conditions of the migrant labour force is the number of hours worked per day. The available information indicates that migrants work more hours per week than non-migrants. Even though the number of hours worked per week varies across countries, migrants work longer than non-migrants in all of them.

Unsurprisingly, men’s workdays are longer than women’s, since, despite migrant women’s higher labour force participation rate, they still bear most of the responsibility for care work (see section A of this chapter). Nevertheless, differentials between the number of hours worked by migrants and non-migrants are apparent both for men and women (see figure III.16). These differentials should be studied in greater depth, since they may be indicative of a number of factors, such as a greater dedication to work owing to more pressing economic needs (including the need to send remittances), a greater willingness to work longer days as a way of achieving greater job stability and pressure from employers, especially in highly informal employment situations.

Figure III.16

Latin America (7 countries): distribution of employed migrants and non-migrants, by number of hours worked per week and sex, latest available year

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

(e) Prominent features of migrants’ participation in the labour force

Occupational categories relate to workers’ positions in the labour market, i.e. whether they have a business of their own, are employed in a company or association, are manual workers or other types of employees or are family workers. These categories, in and of themselves, do not provide an indication of job quality or working conditions, although the direction of the occupational trends seen over the course of different national development processes has fuelled a debate around the dynamism of labour markets and their capacity to absorb workers into the formal sector in the region. The literature on Latin America has established a close link between certain own-account economic activities and the urban informal sector (ILO, 1987; Mezzera, 1987; Portes, 1990) and between such activities and dual or segmented labour markets. However, own-account work and microenterprise ownership encompass a wide variety of activities, ranging from independent professionals to street vendors, and this information therefore needs to be supplemented with information on the types of activities and working conditions involved.

As mentioned at the start of this chapter, the axes of the region’s social inequality matrix merge and intersect, creating cores of exclusion that make opportunities for social and labour inclusion far less accessible for some population groups. When the situation is viewed from this perspective, it becomes clear how barriers to inclusion may be greater for women migrants. Table III.3 shows that wage-based employment is less prevalent among migrant women than among other women but that this is not necessarily the case for migrant men. In Argentina, Costa Rica and Panama, a large number of women immigrants are employed in domestic work, as noted in the preceding section. In the Dominican Republic, many migrants are own-account workers or employed as domestic workers. A significant number of male immigrants are employers in Panama and are own-account workers in Argentina.

Female migrant workers tend to be employed in lower-skilled and lower-ranked occupations than non-migrant women (see table III.4). With the exception of Ecuador, the percentage of migrant women working in unskilled occupations exceeds the percentage of non-migrant women in such occupations; if, in addition, account is taken of women migrants employed in services or as vendors, it can be seen that nearly 70% of all employed migrant women work in these occupational categories. Similar percentages of migrant and non-migrant women are employed in highly skilled occupations only in Ecuador and Panama. In most cases, then, migrant women are subject to occupational segregation on two different counts: because they are women and because they are migrants. Apart from domestic service and care work (see section A), the few other available employment options are found in commerce and the hotel industry.[17]

Table III.3

Latin America (7 countries): employed migrant and non-migrant populations, by occupational category and sex, latest year available

(Percentages)

Sex and occupational category

Argentina, 2019

Chile, 2020

Colombia, 2019

Costa Rica, 2021

Ecuador, 2021

Panama, 2019

Dominican Republic,

2021

Migrants

Non- migrants

Migrants

Non- migrants

Migrants

Non- migrants

Migrants

Non- migrants

Migrants

Non- migrants

Migrants

Non- migrants

Migrants

Non- migrants

Men

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

Wage earners

63.5

70.5

76.1

69.1

50.3

48.4

73.1

71.4

56.9

51.4

56.1

60.9

29.4

49.0

Own-account workers

36.5

29.5

23.9

30.9

49.7

51.6

26.9

28.6

43.1

48.6

43.9

39.1

70.6

51.0

Women

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

Wage earners

34.9

61.3

66.8

67.5

40.8

43.9

49.7

66.9

43.3

31.2

42.4

55.5

27.5

57.0

Own-account workers

31.4

24.1

22.8

27.9

50.4

49.2

18.8

20.7

49.3

64.2

37.0

36.3

55.7

30.9

Domestic workers

33.7

14.6

10.3

4.7

8.8

6.9

31.5

12.5

7.4

4.7

20.6

8.1

16.8

12.1

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Table III.4

Latin America (6 countries): migrant and non-migrant populations, by occupational group and sex, latest year available

(Percentages)

Sex and occupational group

Argentina, 2019

Chile, 2020

Costa Rica, 2021

Ecuador, 2021

Panama, 2019

Dominican Republic, 2021

Migrants

Non- migrantes

Migrants

Non- migrantes

Migrants

Non- migrantes

Migrants

Non- migrantes

Migrants

Non- migrantes

Migrants

Non- migrantes

Men

Directors, professionals and technicians

20.8

27.1

28.1

28.7

9.4

23.6

11.9

9.9

31.7

17.8

7.0

11.3

Office workers

5.3

7.7

7.0

4.6

3.7

6.5

2.1

2.4

2.3

3.3

2.1

5.2

Crafts and related trades workers

45.7

32.0

29.5

32.2

26.9

25.0

25.4

25.0

30.7

32.5

37.5

39.6

Service workers and vendors

19.0

18.8

18.3

15.7

13.7

15.7

21.8

13.8

20.3

13.0

9.4

20.4

Unskilled workers

9.0

13.8

16.4

16.0

42.7

24.2

26.7

23.7

13.1

20.1

39.1

13.7

Other occupations

0.2

0.6

0.7

2.9

3.5

5.1

12.2

25.1

1.9

13.3

4.8

9.8

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

Women

Directors, professionals and technicians

16.4

34.6

26.5

39.2

11.6

33.2

17.6

15.0

24.6

30.5

10.7

22.1

Office workers

7.0

12.9

6.9

7.6

3.9

11.7

2.8

3.4

5.4

11.0

3.2

13.3

Crafts and related trades workers

5.5

6.1

4.9

6.4

6.8

7.4

6.5

6.1

4.8

8.0

2.2

6.2

Service workers and vendors

37.9

28.0

35.6

27.8

29.7

25.5

39.1

27.8

39.1

26.5

45.2

34.1

Unskilled workers

33.1

18.2

25.9

18.5

47.2

21.3

29.8

33.7

25.9

16.0

37.3

23.6

Other occupations

0.0

0.1

0.3

0.5

0.8

0.8

4.2

14.0

0.3

8.0

1.4

0.7

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

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Although migrant men generally have less access than non-migrants to more highly skilled jobs, there are exceptions. In Panama, a larger percentage of migrant workers hold such jobs and, in Chile, the percentages of migrant men and non-migrants holding decision-making, managerial and technical positions are similar. In Ecuador, the occupational profiles of the two groups do not differ from one another to any significant degree except that non-migrants have a greater presence in skilled agrarian work and relatively more migrants are employed as service workers and vendors.

In Argentina, Costa Rica and the Dominican Republic, migrants are generally more likely to be employed in low-skilled jobs or jobs requiring operator skills, in line with their skill profiles and their concentration in specific sectors of the economy.[18] In the Dominican Republic, nearly 40% of migrants are unskilled workers and more than another 30% are employed as crafts or related trades workers.

(f) Income gaps between migrants and non-migrants

An examination of the income gaps, i.e. the ratio of the average incomes that non-migrants as opposed to migrants derive from their main occupation, while taking into consideration their level of education and their sex, leads to three noteworthy findings. The first is that no general trend in terms of lower incomes for migrants is discernible (see table III.5). The situation varies a great deal across countries, between men and women, and depending on the workers’ level of education, all of which suggests that income differentials need to be studied with reference to a larger set of the variables that could play a role in that respect. Another finding that should be underscored is that the higher the educational level of the persons in question, the wider the gap between the higher incomes of non-migrants and the lower incomes of migrants. In other words, the income penalty is greater for more highly educated immigrants. This pattern is evident in five of the seven countries that were studied, with the exceptions being Panama (where migrants consistently have higher incomes than non-migrants) and Ecuador. The differentials between the incomes of low-skilled or unskilled migrant and non-migrant workers are smaller or, in some cases, are reversed, with the former group earning higher wages than the latter (clearly in the case of Chile and in that of women workers in Costa Rica).[19]

Table III.5

Latin America (7 countries): ratio of average incomes derived by non-migrants and migrants from their principal occupations, by level of education and sex, latest year available

(Percentages)

Country and sex

Completed

or incomplete primary education

Incomplete secondary education

Completed secondary education

Incomplete tertiary education

Completed tertiary education

Argentina, 2019

Men

100

125

103

123

120

Women

91

106

119

144

136

Chile, 2020

Men

80

91

109

127

172

Women

58

62

97

120

123

Colombia, 2019

Men

104

118

135

137

112

Women

101

113

129

146

186

Costa Rica, 2021

Men

109

114

106

139

121

Women

82

105

106

129

127

Dominican Republic, 2021

Men

102

108

98

95

125

Women

121

88

121

111

140

Ecuador, 2021

Men

99

101

112

131

97

Women

97

97

114

116

111

Panama, 2019

Men

41

63

91

52

67

Women

56

63

94

90

95

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: Scores of 100 indicate income equality between migrants and non-migrants. Figures over 100 signify that non-migrants’ incomes are higher, while values below 100 indicate that migrants’ incomes are higher. (For example, a score of 90 indicates that the average income of non-migrants is equivalent to 90% of the average income of migrants). The figures shown in bold are statistically significant.

There are many different factors that may play a role in these differentials and that should therefore be taken into account, such as the number of hours worked, the length of residency in the host country, migration status and the labour inclusion landscape. In order to look into the possibility of a migrant income penalty while controlling for some of the factors mentioned above, ordinary least squares linear multiple regression models were used to arrive at monthly income logarithms for the principal occupations for men and for women. The first model includes migration status and controls for age, years of formal education completed and the number of hours worked, while the second model also includes wage earners that are not covered by a pension system and independent workers whose level of educational attainment falls into the category of completed primary education or less (see table III.6).

For men, the results indicate that the income penalty for migrant workers remains in evidence in Costa Rica, Chile, Ecuador and Colombia even after controlling for those factors. These workers earn between 7% and 28% less than their non-migrant peers; with the exception of Chile, when the variables of the second model are factored in, then the effect of migrant status is slightly less. In Argentina and the Dominican Republic, the income penalty for migrant workers disappears once the controls are introduced, while, for Panama, the results indicate that migrants’ incomes are higher than those of non-migrants.

For women, the results also indicate that migrants have lower incomes than non-migrants. In Colombia, the former earn, on average, a full 40% less than the latter and, in Argentina, unlike the results for men, the calculations show that women migrants are subject to an income penalty. Panama and the Dominican Republic are anomalous cases, since the average incomes of migrants are higher than the average for non-migrants.

In sum, while, for the most part, the results of these calculations corroborate the hypothesis that migrants earn less than non-migrants, the varying differentials between income levels and the data that point to anomalous cases raise questions as to how labour market structures and the specific characteristics of demand for migrant workers may influence these outcomes. Length of residence and national origin surely play an important role as well but, unfortunately, the sample is too small to permit an examination of these variables.

Table III.6

Latin America (7 countries): coefficients for the migration status variable in ordinary least squares multiple linear regression models for predicting the natural logarithm of incomes from men’s and women’s primary occupation, latest year available

Country

Men

Women

Model 1*

Model 2**

Model 1*

Model 2**

Argentina, 2019

-0.0659

-0.00513

-0.145**

-0.118**

(0.0417)

(0.0410)

(0.0572)

(0.0559)

Number of cases

13.333

13.333

10.344

10.344

R squared

0.248

0.308

0.349

0.411

Chile, 2020

-0.176***

-0.172***

-0.0969**

-0.0951**

(0.0612)

(0.0594)

(0.0443)

(0.0441)

Number of cases

34.767

34.767

28.272

28.272

R squared

0.311

0.314

0.352

0.354

Dominican Republic, 2021

0.0225

0.0335

0.0602

0.132***

(0.0255)

(0.0261)

(0.0440)

(0.0437)

Number of cases

19.692

19.692

12.020

12.020

R squared

0.212

0.217

0.346

0.372

Colombia, 2019

-0.281***

-0.205***

-0.407***

-0.352***

(0.0137)

(0.0139)

(0.0200)

(0.0202)

Number of cases

177.762

177.762

139.506

139.506

R squared

0.350

0.370

0.466

0.473

Costa Rica, 2021

-0.0764***

-0.0578**

-0.0592*

-0.0480

(0.0262)

(0.0260)

(0.0330)

(0.0312)

Number of cases

7.556

7.556

4.696

4.696

R squared

0.419

0.451

0.570

0.600

Ecuador, 2021

-0.150***

-0.0953***

-0.132***

-0.0858***

(0.0239)

(0.0243)

(0.0308)

(0.0297)

Number of cases

85.477

85.477

57.228

57.228

R squared

0.336

0.354

0.475

0.482

Panama, 2019

0.138***

0.237***

0.0679

0.171***

(0.0377)

(0.0388)

(0.0414)

(0.0415)

Number of cases

11.083

11.083

6.978

6.978

R squared

0.459

0.496

0.559

0.586

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: Model 1 (*) controls for the following variables: age and age squared, years of education and hours worked. Model 2 (**) controls for those variables plus the variable of informal employment (Yes/No). ***: p < 0.01.

C. Summary

As noted in chapter II, labour inclusion is an aspect of inclusive social development, whose purpose is to ensure that all members of the labour force have access to decent work that will provide them with an adequate income and access to social protection. Thus, the concept of labour inclusion is not limited to entry into the workforce; it also has to do with working conditions. This year’s edition of the Social Panorama looks at the greater obstacles to certain population groups’ labour inclusion that are sited along the axes of the region’s social inequality matrix (ECLAC, 2016a). This chapter has focused on gender inequalities and the sexual division of labour as determinants of labour inclusion processes as they relate specifically to women. Special emphasis has also been placed on persons employed in domestic service positions, most of whom are women. Significant headway has been made in the development of laws and policies for guaranteeing their rights, but their labour inclusion is still being hindered by formidable obstacles. This chapter has also focused on international migrants, particularly women, as seen against the backdrop of a very large and fairly sudden increase in intraregional migration.

Section A of this chapter illustrates how the sexual division of labour and the social organization of care remain one of the structural challenges of gender inequality in the region. They also pose one of the main barriers to women’s labour inclusion and one of the main threats to their autonomy and the full exercise of their rights (ECLAC, 2021a). Consequently, a major challenge to be taken up in the region is the creation, for some countries, and the consolidation, for others, of policies and comprehensive care systems that will further the labour inclusion process, especially for women. Governments in the region have entered into a series of fundamental agreements concerning the design and application of care policies. These agreements are aimed at promoting co-responsibility between men and women and between the State, the market, communities and families (ECLAC, 2022b). These policies address both the needs of persons who require care —girls and boys, older adults and persons with disabilities who are in need of personal assistance— and the needs of those providing care.

These policies, which are an essential component of social protection systems, must make the relevant services available to those who need them. They also must strengthen the State’s role in providing those services and ensuring that they are accessible. This entails expanding the supply of care services, strengthening the regulation of these services and the working conditions of those providing care and setting up training programmes (ECLAC/UN-Women, 2022). It is also essential to provide for policies establishing leave and other regulations related to the time spent on care and to allocate resources to population groups in need of care and to the groups that provide that care, especially those who do so without pay. One key aspect to be taken into consideration when designing these policies is the necessary coordination and harmonization between comprehensive care policies, their accompanying regulatory instruments and underlying principles and the overall design of the entitlements under social protection systems.

Given the demographic shifts occurring in the region and the ways in which the overall population’s needs for care are changing, attention also has to be paid to the working conditions of those providing care. The growth in the demand for care work, combined with the fact that care is a female-dominated and undervalued activity, raises some troubling prospects regarding the impact that it will have on the labour market as a whole (ECLAC, 2022b). Promoting the labour inclusion of women employed as domestic workers will have a substantial influence on women’s employment situation in general and will help to narrow existing gender gaps, especially given the sizeable proportion of all paid work performed by women that this occupational category represents. Labour policies are an important tool for modifying the rigid sexual division of labour, not only by providing incentives for women to enter more formalized and higher-paying male-dominated sectors of activity but also by promoting the entry of men into traditionally female-dominated care sectors. This is an especially important approach for the creation of comprehensive care systems marked by an increasing degree of labour inclusion, particularly for women.

Section B of this chapter delves into the situation of the migrant population in the region and the challenges that its members face in terms of labour inclusion. There has been a striking increase in the scale of intraregional migration in Latin America and the Caribbean, both in countries with a long tradition of immigration and in others that, until recently, were primarily countries of origin. This poses significant challenges for countries of origin, transit, destination and return in terms of the labour inclusion of migrants and means of combating discrimination and prejudice. Migration can contribute to inclusive social development processes in receiving countries, especially if it occurs through regular channels as an informed option and if migrants’ rights are protected in accordance with the existing international instruments. Alongside the Montevideo Consensus on Population and Development, the 2030 Agenda and the Global Compact for Safe, Orderly and Regular Migration, it is essential for countries to reaffirm their commitment to the protection of migrants, regardless of their administrative status.

Household survey data from Argentina, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador and Panama have been used to gauge migrants’ impact on demographic and labour force variables, the specific ways they have entered the labour market and their contribution to GDP (with the exception, in respect of this latter estimate, of Panama). Migrants make a contribution to countries’ demographic profiles via two mechanisms: the propensity of young adults to migrate and migrants’ greater propensity to participate in the labour force. Most migrants have been educated in their countries of origin, so they represent a lower fiscal cost than non-migrants. Obviously, the higher the educational profile, the more they benefit their country of destination. Migrant workers also make a considerable contribution to GDP. The extent of that contribution varies depending on the stage reached at any given point in time in the business cycle, productivity levels, the dynamism of different economic sectors and migrants’ level of access to the labour market and labour inclusion.

The characteristics and profiles of migrant workers from the region vary a great deal, especially in the case of their educational profiles, as do the structures of the labour markets in which they participate. The ways in which they are received by their host countries largely determines the nature of their employment opportunities, although the way in which they are positioned relative to local workers also depends on other factors, such as whether their administrative status is regular or irregular. Job opportunities for migrants are more limited and are highly segmented in the case of women, who generally work longer hours than their non-migrant peers and are much more likely to be employed in the informal sector. As a result of these conditions, migrants earn less from their principal occupation, on average, than non-migrants do, with women migrants finding themselves in a more disadvantageous position than any other group.

In all of these cases, having a regular migration status is a basic (although not sufficient) condition for migrants to gain access to formal-sector employment and labour inclusion. In its absence, migrants cannot pay into the social security system or obtain the benefits associated with formal employment, such as protection from dismissal without cause, paid vacation time and all the other supplementary protections provided under national labour laws. Apart from the regularization of migration status, however, there are also other mechanisms for promoting the labour inclusion of migrants that would help to maximize their contribution to their host societies. In order to be in a position to carry out any initiative for furthering migrants’ employability, however, an in-depth understanding of the traits and needs of these communities is key. One important challenge is to find ways of taking advantage of the knowledge and educational credentials previously obtained by migrants in their home countries. In the case of qualifying professional degrees, expediting accreditation processes is an obvious answer, but skills certifications are another avenue that should be promoted. Appropriate information management is another aspect of the issue; promoting the labour inclusion of migrants entails formulating labour policies that provide such persons with specific information about job search procedures in the various countries, their labour rights and how to obtain justice if that becomes necessary. There is thus a need to look into the barriers to the labour inclusion of migrants. In addition, labour inclusion policies need to promote access for migrants to national or local employment programmes and incentives for business start-ups. A somewhat similar approach needs to be taken to professional training and skills certification. Targeted skills training can make an important difference in aligning the supply of migrant labour with demand. Another measure would be to develop suitable, effective job placement mechanisms that can help match up public- or private-sector labour supply and demand, thereby optimizing labour force placement and reducing job search costs. In sum, labour inclusion policies can make a big difference in terms of the rights and well-being of migrants and the contributions that they can make to inclusive, sustainable social development processes in the countries of the region.

Societies which have long had difficulties in achieving social and labour inclusion face considerable challenges. An effective approach for promoting inclusive, sustainable social development at the regional level is the application of public policies that protect gender equality and rights, that are aimed at promoting the inclusion of all persons without distinction as to their national origin, that provide for affirmative action to attain substantive equality and that promote the development of comprehensive care systems, decent forms of work and the full participation on an equal footing of women in strategic sectors of the economy.

This is a very valuable opportunity for honouring the commitments made in the Regional Gender Agenda, and particularly the recently proclaimed Buenos Aires Commitment and the Montevideo Consensus on Population and Development by ensuring that they are reflected in public policies that will improve people’s lives and promote labour inclusion, leaving no one behind.

Bibliography

Arias, K., P. Carrillo and J. Torres (2020), “Análisis del sector informal y discusiones sobre la regulación del trabajo en plataformas digitales en el Ecuador”, Project Documents (LC/TS.2020/75), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Baron, C. and L. Scuro (2023), “Los nudos estructurales de la desigualdad de género y los desafíos para la autonomía de las mujeres en el futuro del trabajo”, Desigualdades, inclusión laboral y futuro del trabajo en América Latina, Project Documents (LC/TS.2023/63), M. Huepe (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Becker, G. (1964), Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education, Chicago, University of Chicago Press.

Benencia, R. and A. Gazzotti (1995), “Migración limítrofe y empleo: precisiones e interrogantes”, Estudios Migratorios Latinoamericanos, vol.10, No. 31, Buenos Aires, Centre for Latin American Migration Studies (CEMLA).

Bensusán, G. (2020), “Ocupaciones emergentes en la economía digital y su regulación en México”, Macroeconomics of Development series, No. 203 (LC/TS.2020/28), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Blanchard, O. (2023), Las plataformas digitales de cuidados y sus servicios workertech en América Latina y el Caribe: análisis de un sector incipiente, Washington, D.C., Inter-American Development Bank (IDB).

Canales, A. (2022), “Evaluación cuantitativa de las contribuciones de las migraciones recientes al desarrollo sostenible: el caso de Chile”, Sobre las contribuciones de la migración al desarrollo sostenible: estudios en países seleccionados, Project Documents (LC/TS.2021/195), J. Martínez and M. Cano (eds.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Canales, A. and others (2013), Vidas vulnerables: migración, derechos humanos y políticas públicas en cinco zonas fronterizas de América Latina, Guadalajara, University of Guadalajara.

Carrasco, I. and J. Suárez (2018), “Migración internacional e inclusión en América Latina: análisis en los países de destino mediante encuestas de hogares”, Social Policy series, No. 231 (LC/TS.2018/57), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Cebollada, M. (2021), Mecanismos de intermediación laboral en el trabajo del hogar remunerado en la Ciudad de México, Mexico City, International Labour Organization (ILO).

Cecchini, S. and J. Martínez (2023), “Migración internacional en América Latina y el Caribe: una mirada de desarrollo y derechos”, CEPAL Review, No. 141, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Cerrutti, M. (2018) “Migrantes y migraciones: nuevas tendencias y dinámicas”, La Argentina en el siglo XXI: cómo somos, vivimos y convivimos en una sociedad desigual. Encuesta Nacional sobre la Estructura Social, J. Piovani and A. Salvia (coords.), Buenos Aires, Latin American Council of Social Sciences (CLACSO).

Cerrutti, M. and A. Maguid (2007), “Inserción laboral e ingresos de migrantes limítrofes y peruanos en el gran Buenos Aires”, Notas de Población, No. 83 (LC/G.2340-P), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Correa, M. (2021), “Los riesgos psicosociales en el trabajo doméstico y de cuidados”, Lex Social: Revista de los Derechos Sociales, vol. 11, No. 1, Sevilla, Pablo de Olavide University.

Damas de Matos, A. (2021), “The fiscal impact of immigration in OECD countries since the mid-2000s”, International Migration Outlook 2021, Paris, Organisation for Economic Co-operation and Development (OECD).

DNP (National Population Directorate) (2022), “Caracterización de la migración internacional en Argentina a partir de los registros administrativos del RENAPER”, Buenos Aires [online] https://www.argentina.gob.ar/sites/default/files/2022/12/caracterizacion_de_la_migracion_internacional_en_argentina_a_partir_de_los_registros_administrativos_del_renaper_dnp.pdf.

ECLAC (Economic Commission for Latin America and the Caribbean) (2023a), CEPALSTAT [online database] https://statistics.cepal.org/portal/cepalstat/index.html?lang=en.

(2023b), Buenos Aires Commitment (LC/CRM.15/6/Rev.1), Santiago.

(2022a), Social Panorama of Latin America and the Caribbean, 2022 (LC/PUB.2022/15-P), Santiago.

(2022b), The care society: a horizon for sustainable recovery with gender equality (LC/CRM.15/3), Santiago.

(2022c), Towards transformation of the development model in Latin America and the Caribbean: production, inclusion and sustainability (LC/SES.39/3-P), Santiago.

(2022d), Social Panorama of Latin America, 2021 (LC/PUB.2021/17-P), Santiago.

(2022e), Economic Survey of Latin America and the Caribbean, 2022 (LC/PUB.2022/9-P/Rev.1), Santiago.

(2022f), 45 years of the Regional Gender Agenda (LC/MDM-E.2022/4), Santiago.

(2021a), Social Panorama of Latin America, 2020 (LC/PUB.2021/2-P/Rev.1), Santiago.

(2021b), Digital technologies for a new future (LC/TS.2021/43), Santiago.

(2020), “The impact of COVID-19: an opportunity to reaffirm the central role of migrants’ human rights in sustainable development”, COVID-19 Report, Santiago.

(2019a), Women’s autonomy in changing economic scenarios (LC/CRM.14/3), Santiago.

(2019b), Social Panorama of Latin America, 2019 (LC/PUB.2019/22-P/Rev.1), Santiago.

(2017a), Linkages between the social and production spheres: gaps, pillars and challenges (LC/CDS.2/3), Santiago.

(2017b), Montevideo Strategy for Implementation of the Regional Gender Agenda within the Sustainable Development Framework by 2030 (LC/CRM.13/5), Santiago.

(2016a), The social inequality matrix in Latin America (LC/G.2690(MDS.1/2)), Santiago.

(2016b), Equality and women’s autonomy in the sustainable development agenda (LC/G.2686/Rev.1), Santiago.

(2014), Compacts for Equality: Towards a Sustainable Future (LC/G.2586(SES.35/3)), Santiago.

(2012), Structural change for equality: an integrated approach to development (LC/G.2524(SES.34/3)), Santiago.

(2010), Time for Equality: Closing Gaps, Opening Trails (LC/G.2432(SES.33/3)), Santiago.

ECLAC/ILO (Economic Commission for Latin America and the Caribbean/International Labour Organization) (2023), “Towards the creation of better jobs in the post-pandemic era”, Employment Situation in Latin America and the Caribbean, No. 28 (LC/TS.2023/70), Santiago.

(2019), “The future of work in Latin America and the Caribbean: old and new forms of employment and challenges for labour regulation”, Employment Situation in Latin America and the Caribbean, No. 20 (LC/TS.2019/31), Santiago.

(2017), “Labour immigration in Latin America”, Employment Situation in Latin America and the Caribbean, No. 16 (LC/TS.2017/30), Santiago.

ECLAC/MMGyD (Economic Commission for Latin America and the Caribbean/Ministry of Women, Genders and Diversity of Argentina) (2022), “Mapa Federal del Cuidado en la Argentina: construcciones conceptuales y usos”, Project Documents (LC/TS.2022/173-LC/BUE/TS.2022/18), Santiago.

ECLAC/UN-Women (Economic Commission for Latin America and the Caribbean/United Nations Entity for Gender Equality and the Empowerment of Women) (2022), Towards construction of comprehensive care systems in Latin America and the Caribbean: elements for their implementation (LC/TS.2022/26), Santiago.

Ehrenreich, B. and A. Russell (eds.) (2003), Global Woman: Nannies, Maids, and Sex Workers in the New Economy, New York, Henry Holt & Company.

Espejo, A. and V. Cortínez (2023), “Memoria del Tercer Seminario Regional de Desarrollo Social: Promover la inclusión laboral como una forma de superar las desigualdades y la informalidad en América Latina y el Caribe”, Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), forthcoming.

Gontero, S. and M. Velásquez (2023), “Trabajo doméstico remunerado en América Latina: claves para una ruta de formalización”, Project Documents (LC/TS.2023/82), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Gutiérrez, A. and others (2020), “Criterios de calidad en la estimación de indicadores a partir de encuestas de hogares: una aplicación a la migración internacional”, Statistical Studies series, No. 101, (LC/TS.2020/52), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Huepe, M. (ed.) (2023), “Desigualdades, inclusión laboral y futuro del trabajo en América Latina”, Project Documents (LC/TS.2023/63), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Hunt, A. and F. Machingura (2016), “A good gig? The rise of on-demand domestic work”, Working Paper, No. 7, London, Overseas Development Institute (ODI).

ILO (International Labour Organization) (2023), “Who are domestic workers” [online] https://www.ilo.org/global/topics/domestic-workers/who/lang--en/index.htm.

(2021a), El trabajo doméstico remunerado en América Latina y el Caribe, a diez años del Convenio núm. 189, Geneva.

(2021b), ILO Global Estimates on International Migrant Workers: Results and Methodology, Geneva.

(2021c), World Employment and Social Outlook 2021: the role of digital labour platforms in transforming the world of work, Geneva.

(2020), “COVID-19 and care workers providing home or institution-based care”, ILO Sectoral Brief, Geneva.

(2019), Care work and care jobs for the future of decent work, Geneva.

(2011), Domestic Workers Convention, 2011 (No. 189), Geneva.

(1987), Adjustment and Social Debt: A Structural Approach, Santiago.

Kalla, S. (2022), “Hacking platform capitalism: the case of domestic workers on South Africa’s SweepSouth platform”, Gender & Development, vol. 30, No. 3, Milton Park, Taylor & Francis.

Mármora, L. (1977), “Política e investigación en el proceso de planificación migratoria”, Santiago, Economic Commission for Latin America and the Caribbean/Programme of Social Research on Population in Latin America (ECLAC/PISPAL).

Marshall, A. (1977), “Inmigración, demanda de fuerza de trabajo y estructura ocupacional en el área metropolitana argentina”, Desarrollo Económico, vol. 17, No. 65, Buenos Aires, Institute of Economic and Social Development (IDES).

Martínez, J. and M. Cano (eds.) (2022), “Sobre las contribuciones de la migración al desarrollo sostenible: estudios en países seleccionados”, Project Documents (LC/TS.2021/195), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Mezzera, J. (1987), “Notas sobre la segmentación de los mercados laborales urbanos”, ILO Working Papers, Santiago, International Labour Organization (ILO).

Mincer, J. (1974), Schooling, Experience and Earnings, New York, National Bureau of Economic Research (NBER).

Ministry of the Interior of Argentina (2022), Caracterización de la migración internacional en Argentina a partir de los registros administrativos del RENAPER, Buenos Aires.

Morales, A., G. Acuña and K. Li Wing-Ching (2010), “Migración y salud en zonas fronterizas: Colombia y el Ecuador”, Population and Development series, No. 92 (LC/L.3247-P), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

MTEySS/OISS/SRT (Ministry of Labour, Employment and Social Security/Ibero-American Social Security Organization/Superintendence of Occupational Risks) (2020), “Condiciones de empleo, trabajo y salud de trabajadoras domésticas de casas particulares: resultados de la [ECETSS] 2018”, Buenos Aires [online] https://www.argentina.gob.ar/sites/default/files/informe_tdcp_-_ecetss_2018_0.pdf.

Pereyra, F., L. Poblete and A. Tizziani (2023), Plataformas digitales de servicio doméstico y condiciones laborales: el caso de Argentina, Buenos Aires, International Labour Organization (ILO).

Portes, A. (1990), La economía informal en los países desarrollados y en los menos avanzados, Buenos Aires, Editorial Planeta.

Salazar, R. (2001), Servants of Globalization: Women, Migration and Domestic Work, Stanford, Stanford University Press.

UNFPA (United Nations Population Fund) (2020), Socioeconomic consequences of adolescent pregnancy in six Latin American countries: implementation of the Milena methodology in Argentina, Colombia, Ecuador, Guatemala, Mexico and Paraguay, Panama City.

United Nations (2020), International Migration 2020 Highlights (ST/ESA/SER.A/452), New York.

Vaca Trigo, I. and C. Baron (2022), “Decentring GDP: well-being, care and time”, Project Documents (LC/TS.2022/80), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Valenzuela, M., L. Scuro and I. Vaca Trigo (2020), “Desigualdad, crisis de los cuidados y migración del trabajo doméstico remunerado en América Latina”, Gender Affairs series, No. 158 (LC/TS.2020/179), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

World Bank (2022), “Remittances brave global headwinds. Special focus: climate migration”, Migration and Development Brief, No. 37, Washington, D.C.

Annex III.A1

Table III.A1.1

Latin America (5 countries): odds ratios derived from logistic regressions with the dependent variable “performance of paid work” by women aged 25–50, latest available year

Variables

Countries and years

Bolivia (Plurinational State of), 2021

Chile, 2017

Guatemala, 2014

Mexico, 2020

Uruguay, 2021

1 child

0.714***

1.028

0.577***

0.819***

1.058

2 children

0.605***

0.729***

0.591***

0.577***

0.971

3 children

0.550***

0.665***

0.598***

0.559***

0.721**

4 children

0.605***

0.597***

0.480***

0.584***

0.572***

5 children or more

0.405***

0.532***

0.394***

0.636***

0.561***

Age

1.046***

1.017***

1.026***

1.016***

1.040***

Rural residence

2.011***

0.538***

0.475***

0.964

0.906

Secondary education

1.116

1.926***

1.688***

1.244***

2.417***

Tertiary education

2.084***

5.355***

2.806***

2.505***

9.419***

Constant

0.442***

0.654***

0.894

1.081

0.413***

Cases (numbers)

7 736

37 828

8 260

58 357

4 845

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: *** p < 0.01; ** p < 0.05; * p < 0.1. Estimated standard errors are robust and incorporate the effect of sample design except in the case of Guatemala.

Table III.A1.2

Latin America (5 countries): odds ratios derived from logistic regressions with the dependent variable “performance of unpaid domestic work” by women aged 25–50, latest available year

Variables

Countries and years

Bolivia (Plurinational State of), 2021

Chile, 2017

Guatemala, 2014

Mexico, 2020

Uruguay, 2021

1 child

5.152***

4.313***

1.871***

2.103***

2.620***

2 children

6.798***

7.746***

2.145***

3.182***

3.307***

3 children

8.140***

9.083***

2.157***

3.407***

4.292***

4 children

7.455***

10.30***

2.614***

3.223***

3.765***

5 children or more

10.38***

9.303***

3.064***

3.082***

5.478***

Age

0.961***

0.986***

0.972***

0.986***

0.980***

Rural residence

0.595***

2.258***

2.233***

1.152***

1.319

Secondary education

0.939

0.738***

0.526***

0.877***

0.461***

Tertiary education

0.360***

0.208***

0.262***

0.401***

0.0902***

Constant

0.327***

0.103***

0.853

0.384***

0.210***

Cases (numbers)

7 736

37 828

8 260

58 357

4 845

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG).

Note: *** p < 0.01; ** p < 0.05; * p < 0.1. Estimated standard errors are robust and incorporate the effect of sample design except in the case of Guatemala.

1. [1] As set forth in the Montevideo Strategy (ECLAC, 2017b), the structural challenges of inequality are the following: (i) socioeconomic inequality and the persistence of poverty; (ii) discriminatory, violent and patriarchal cultural patterns and the predominance of a culture of privilege; (iii) the sexual division of labour and the unfair social organization of care; and (iv) the concentration of power and hierarchical relations in the public sphere.

2. [2] This result was controlling for age, level of education and area of residence and, for the purposes of labour income, Heckman correction was applied to eliminate selection bias.

3. [3] Convention No. 189 has been ratified by the following Latin American and Caribbean countries: Antigua and Barbuda (2021), Argentina (2014), Brazil (2018), Chile (2015), Colombia (2014), Costa Rica (2014), Dominican Republic (2015), Ecuador (2013), Grenada (2018), Guyana (2013), Jamaica (2016), Mexico (2020), Nicaragua (2013), Panama (2015), Paraguay (2013), Peru (2018), Plurinational State of Bolivia (2013) and Uruguay (2012).

4. [4] Both the National Commission for Work in Private Homes (CNTCP) of Argentina and Group 21 of the Wage Council of Uruguay have tripartite representation (representatives of workers, employers and the government) to set a minimum wage for the sector and attach importance to the possibility of social dialogue.

5. [5] In Costa Rica, executive decree No. 43849-MTSS of the National Wage Council (CNS), of 2019, established an additional wage increase of 2.33962% to be afforded to domestic service over the following 15 years. In Paraguay, Act No. 5407 of 2015, which recognized pay for domestic work at equivalent to 60% of the legal minimum wage, was corrected in 2019 by Act No. 6338, which affords the legal minimum wage to workers devoted to various unspecified activities.

6. [6] For example, in Argentina, the percentage of pension contributors went from 6% in 2005 to 23.5% in 2021; in Peru, the percentage contributing to the pension system went from 3% in 2001 to 17.5% in 2021, and in Uruguay, the percentage contributing to the retirement fund rose from 33% in 2006 to 68.4 % in 2021 (Gontero and Velázquez, 2023).

7. [7] A single-parent household is one comprising a mother or father and at least one child.

8. [8] Act No. 20786 of 2014.

9. [9] Five wage categories are established: supervisors; personnel for specific tasks; caretakers; personal assistance and care, and staff for general tasks. Each category has a legal minimum hourly and monthly wage, and, if the activities performed correspond to more than one category, the minimum wage of the best-paid category applies.

10. [10] Some firms have even focused mainly on digitalizing administration, simplifying the formalization and affiliation procedures for social security systems. One example is Simplifica, in Colombia and Mexico.

11. [11] It may be debated whether platforms actually generate new occupations, how similar or different they are with respect to other, traditional forms of non-standard employment and, above all, whether those who perform them are subordinate or independent (or self-employed or own-account) workers (Bensusán, 2020, p. 9).

12. [12] According to the American Community Survey, 22.7 million persons from Latin America and the Caribbean were living in the United States in 2021. According to the Municipal Census of Spain, 3.3 million persons from Latin America and the Caribbean were living in that country in 2021.

13. [13] The term “recent migrant” is understood to refer to persons born in another country who arrived in their country of destination within the five years preceding the census or survey in question.

14. [14] While most of these surveys provide a way of identifying migrants, usually by means of some variable relating to length of residence, the number of cases is generally too small to serve as a basis for any conclusions that do not have a considerable margin of error.

15. [15] The countries of origin of immigrants in Argentina include, for example, Paraguay, the Plurinational State of Bolivia, Peru, Chile, Uruguay, Colombia and the Bolivarian Republic of Venezuela. There are also older immigrants from Europe and elsewhere.

16. [16] A study conducted in 2022 by the National Population Directorate (DNP, 2022) based on administrative data indicates that, of the 3,033,786 foreign residents in possession of a national identity card, 30% were born in Paraguay, 22% in the Plurinational State of Bolivia, 10% in Peru, 7% in the Bolivarian Republic of Venezuela and 7% in Chile.

17. [17] In Colombia, for example, 50% of women migrant workers are employed in this sector; in Ecuador, the percentage is 46%.

18. [18] In Argentina, 3 out of every 10 migrant workers are employed in the construction industry, while, in Costa Rica, 6 out of every 10 are employed in agriculture, construction, commerce or the hotel industry.

19. [19] The earnings gaps, disaggregated by migration status and sex, indicate that women systematically have lower average incomes than men, regardless of their educational level. A comparison of the earnings of non-migrant men with those of migrant women having with the same level of education shows that the former earn between 60% and 140% more than the latter.

Chapter IV

Institutional frameworks and social spending: challenges for labour inclusion

Introduction

A. A social institutional framework for social policy under construction with challenges for labour inclusion

B. Trend of public social spending in 2000–2022

C. Public investment in labour inclusion policies in Latin America

D. Closing remarks

Bibliography

Annex IV.A1

Introduction

The transformative capacity of social policies depends partly on their institutional underpinnings, in other words the relevance and legitimacy of their legal mandates, the consistency of these mandates with their organizational structure and their level of coordination, and their human, technical and financial capacities. Taking these elements into account, the Economic Commission for Latin America and the Caribbean (ECLAC) has highlighted four analytical dimensions for studying the institutional framework for social policy: (i) legal and regulatory; (ii) organizational; (iii) technical and operational; and (iv) financial, in order to follow up on the requirements and challenges facing the countries in achieving inclusive social development (ECLAC, 2015, 2016 and 2023a; Martínez, 2019). The consolidation of these four dimensions forms a central institutional framework for progressing towards inclusive social development. For this reason, the Regional Agenda for Inclusive Social Development, adopted by the region’s countries in 2019, defines a strengthened social institutional framework as one of its four axes, to serve as a key means of implementing the 2030 Agenda. Inclusive social development can only be achieved through State commitments, hand-in-hand with a solid institutional framework that gives policies and programmes continuity, coherence and legitimacy (ECLAC, 2020).

The current panorama of the institutional framework for social policy in Latin America and the Caribbean reveals several unresolved challenges. Approaches to addressing these challenges include the need to consolidate the legal and regulatory bases for advancing a rights-based approach, adopting a perspective of universalism that is sensitive to differences, and making objectives and legal mandates more consistent with the capacity of social policy institutions. In organizational terms, investment is needed in human and technological resources to secure results, and to improve efficiency through coordination, decentralization and participation. Strengthening the technical and operational dimension requires greater investment in information systems, the expansion of data scope and the dissemination of social information at the intersectoral and population levels, to reaffirm and consolidate the central role of inclusive social development. In addition, systems for monitoring and evaluating social policies and programmes need to be consolidated. Lastly, it is a priority to enhance financial sustainability in order to strengthen the institutional framework for social policy and thus eradicate poverty and reduce inequality (ECLAC, 2023a).

The function of public policies in the social domain includes actions to foster labour inclusion, both to enable people to gain employment and to ensure that they do so under decent working conditions. Public action in this area cannot be the exclusive responsibility of the region’s ministries of social development (or their equivalents). Other bodies are also involved, including ministries of labour and other State agencies, as well as separate entities that also have responsibility for social security. In this sense, the construction of a robust and efficient social institutional framework also means ensuring effective coordination between and among the different State entities involved in social protection and labour inclusion.

In view of the foregoing, this chapter describes elements of the current panorama of the institutional framework for social policy in Latin America and the Caribbean, with a focus on labour inclusion policies and the financial dimension, by making an analysis of the evolution and characteristics of social spending. The first section provides a brief review of the approval or ratification status of various important instruments and conventions, and of the governance of the social sector; the extent to which the mandates of the region’s social development ministries correspond to their organizational structure; and the degree to which they are coordinated to provide a comprehensive service to the target population, through access modalities such as the single window service. It also addresses the information systems and the entities that execute labour inclusion programmes and are responsible for them. The second section focuses on the financial dimension of social policy institutions, making a detailed analysis of central government social spending by function of government, as well as the countries’ investment in labour market policies.

A. An institutional framework for social policy under construction with challenges for labour inclusion

1. Progress in ratifying or acceding to international treaties of special relevance for inclusive social development

In the legal and regulatory domain, the region has a strong record of ratifying or acceding to international treaties that are relevant for inclusive social development. Of the region’s 33 countries, 30 have ratified or acceded to the International Covenant on Economic, Social and Cultural Rights (universal system), supervised by the Committee on Economic, Social and Cultural Rights; and all 33 have ratified the Convention on the Elimination of All Forms of Discrimination against Women. In the Inter-American system, the agreements with the largest number of ratifications or accessions are the American Convention on Human Rights (25 countries) and the Additional Protocol to the American Convention on Human Rights in the Area of Economic, Social and Cultural Rights, the Protocol of San Salvador (18 countries) (ECLAC, 2023a).

When considering the countries’ domestic legislation, the most widely recognized rights in national constitutions are those relating to social security (33 countries) and work (32 countries). However, this figure decreases when analysing laws that create or modify the ministries of social development or their equivalent entities. Only four out of 20 Latin American countries include work and the right to social security within the aforementioned laws (ECLAC, 2023a). This is despite their constitutional recognition and relevance for social protection and development in the region.

As an essential aspect of inclusive social development, the conventions of the International Labour Organization (ILO), founded on tripartite agreements, contribute to social dialogue and the protection of employment conditions and worker safety worldwide. The countries of Latin America and the Caribbean display high levels of ratification. These conventions include those of widest scope, such as the Discrimination (Employment and Occupation) Convention, 1958 (No. 111), the Abolition of Forced Labour Convention, 1957 (No. 105) and the Worst Forms of Child Labour Convention, 1999 (No. 182), which have been ratified by all 33 countries in the region. They are followed by the conventions on governance: the Labour Inspection Convention, 1947 (No. 81), the Tripartite Consultation (International Labour Standards) Convention, 1976 (No. 144) (both ratified by 28 countries) and the Employment Policy Convention, 1964 (No. 122) (22 countries), in addition to the Domestic Workers Convention, 2011 (No. 189) (18 countries) (see figure IV.1).

An analysis of conventions that are particularly relevant to labour inclusion and decent work reveals the commitment that countries have made to the fundamental principles and rights related to decent work. These include the recognition of collective bargaining, the elimination of forced and child labour, and the prohibition of discrimination in respect of employment and occupation. In addition, there is the commitment to create and strengthen entities responsible for supervising and monitoring compliance with labour regulations and the conditions under which work is performed, as promoted by the conventions on governance, which have a high level of ratification in the region. Although these regulatory advances are necessary because of their practical implications for labour inclusion, they are not sufficient. Their full implementation requires effective labour inspection and steps to address the challenges of informality and emerging forms of work that are arising as the fourth industrial revolution unfolds.

Figure IV.1

Latin America and the Caribbean (33 countries): ratification of, or accession to, ILO conventions related to inclusive social development

(Number of countries)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Institutional Frameworks for Social Policy in Latin America and the Caribbean: A Central Element in Advancing towards Inclusive Social Development (LC/CDS.5/3), Santiago, 2023.

Note: Updated to July 2023.

2. Social sector governance and coordination: the role of ministries of social development and their interaction in fostering labour inclusion

The countries of Latin America and the Caribbean have numerous intersectoral coordination mechanisms dedicated to social development. The institutions in question vary in origin, ranging from the Office of the President of the Republic down to private sector entities and civil society. Many of these participants also belong to the social domain, since their objectives include the upholding of social rights to ensure inclusive social development. Examples include sectoral social ministries (of social development, education, health, housing and others), and other important ministerial or equivalent entities such as the national machineries for the advancement of women,[1] labour unions and the private sector. An analysis of the institutions participating in the intersectoral coordination bodies in 15 of the region’s countries shows that 13 of them involve ministries of social development and education, 12 involve health ministries, 11 involve ministries of labour, eight involve housing ministries, and six involve those of social security. In addition, the Vice President of the Republic participates in three cases and the President of the Republic participates in two. Labour unions and the private sector participate in just one mechanism each, as also do trade associations and religious entities, respectively (see figure IV.2).

The ministries of social development are among the central actors of the institutional framework for social policy and play a key governance role. Since the late twentieth century, many social development ministries or equivalent entities have been created in the region. According to available official data, between 1980 and 2023 at least 70 social development institutions have existed in 26 countries, of which 59 are ministries of social development or equivalent, and 11 are agencies of other types, generally below ministerial rank (ECLAC, 2023a).

Figure IV. 2

Latin America and the Caribbean (15 countries):a participants in intersectoral coordination mechanisms dedicated to social development

(Number of countries)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

a Antigua and Barbuda, Argentina, Bolivarian Republic of Venezuela, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru and Uruguay.

This highlights two key characteristics of social development ministries in the region. First, it reveals their youth, especially when compared to other long-standing social ministries, such as those of health, education, labour or housing. Second, it reveals the organizational instability of social development ministries in Latin America and the Caribbean. Historical trajectories show an average of more than two changes per country, the most striking cases being those of Argentina, Brazil and Jamaica. In Latin America, Brazil has had eight ministries devoted to these issues, followed by Argentina; while in the Caribbean, Jamaica has had seven ministries in its history, including two in the same year (1980) (see figure IV.3). This weakness undermines the agencies responsible for the social sector, especially as regards their capacity to fulfil their legal mandates; and it creates a climate of uncertainty regarding the real possibility of generating long-term sustainable social change.

One way to approach the capacity for effective compliance with the legal mandates that create ministries of social development is to analyse the degree to which they correspond to the organizational structure; in other words, verify whether the functions assigned, or the population segments prioritized, are consistent with their organizational units. From the standpoint of specific human rights, the greatest correspondence is found in the case of the right to food. Of five countries in the region that have a mandate on this issue, four have formal units related to it. This occurs in two ministries in the case of the right to social security and in one in the case of the rights to education, housing, work and health, respectively. In contrast, some countries have specialized units working on these rights, even though they do not have a specific mandate in this regard (see figure IV.4).

Figure IV. 3

Latin America and the Caribbean (26 countries): evolution of ministries of social development and equivalent entities, 1980–2023

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Institutional Frameworks for Social Policy in Latin America and the Caribbean: A Central Element in Advancing towards Inclusive Social Development (LC/CDS.5/3), Santiago, 2023.

Figure IV.4

Latin America (20 countries):a correspondence between the legal mandates and organizational structures of ministries of social development for promoting human rights, 2023

(Number of countries)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The organizational structure is based on the official organization charts of the ministries of social development or equivalent entities in the countries.

a Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Suriname and Uruguay.

A review with respect to specific protection groups also reveals that organizational correspondence is most common in the cases of children and adolescents (seven countries), older persons (six countries) and the family (five countries). There is correspondence in three countries in the case of young people and persons with disabilities, two in the case of women, and one in the case of people living in poverty or extreme poverty. It should also be noted that some other groups mentioned in the mandates do not see their priority reflected in a responsible unit, and there are countries that do have thematic units despite the absence of a mandate that obliges them (see figure IV.5). Nonetheless this correspondence between mandate and organization only provides formal indications of engagement with the issues, without making it possible to conclude anything about the quality of work or the impact that each ministry has on the different issues and social groups prioritized.

Figure IV.5

Latin America (20 countries):a correspondence between the legal mandates and organizational structures

of social development ministries for specific population segments, 2023

(Number of countries)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Institutional Frameworks for Social Policy in Latin America and the Caribbean: a Central Element in Advancing towards Inclusive Social Development (LC/CDS.5/3), Santiago, 2023.

a Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Suriname and Uruguay.

3. Coordination and comprehensiveness: single-window facility and information systems for decision making

Progress towards providing comprehensive social services in the territory is one of the main challenges facing social policy. To achieve this, the highest possible levels of horizontal and vertical coordination need to be sought between the different State agencies and cooperating partners that deliver goods and services to the population (Cecchini and Martínez, 2011; Cunill-Grau, Repetto and Bronzo, 2015). Mechanisms are also needed to enable each entity’s actions to be shared, and to harmonize objectives and processes, thereby facilitating access to the universal exercise of people’s rights, taking into account the differences existing between different population groups (cross-wise approach) or throughout the life cycle (longitudinal approach) (Cecchini and Martínez, 2011).

An example of this is the single-window facility, which provides access to public programmes and services, concentrated in a single place, either physical or virtual. This mechanism is very useful, because the many social and labour inclusion programmes that exist, both at the sectoral level and between levels of government, require coordinated action that facilitates knowledge and participation by the population. The varied functions of the single-window facility include the following: (i) providing information on what is available; (ii) evaluating and determining applicant eligibility; (iii) helping to collect the necessary documentation; (iv) guiding applicants and following up on applications; (v) enrolling people in the programmes; and (vi) providing the service or social entitlement directly (GIZ, 2017). There are at least three main single-window formats. The first is the physical one, in which the range of social services are concentrated in a public establishment for face-to-face dealings. Second, there is the virtual format, through Internet sites or mobile applications. Lastly, the single window facility can also be taken into the territory. For example, the family support mechanism can be applied by visiting communities to inform the local population on how to access programmes and services. This format is a more personalized single window facility, in which supply goes in search of demand (ECLAC, 2023a).

In addition, effective and efficient management that facilitates data-driven decision-making requires reliable and timely information on the programmes that comprise social policy, along with their results and the characteristics and needs of the population. Social information systems are thus a central component of the technical and operational dimension of the institutional framework, since they are indispensable for achieving the comprehensiveness of social policies, basing decisions on data and making them more transparent. Information systems play a decisive role in all phases of social policy (diagnosis, design, approval, implementation and evaluation). In addition, the use of digital technologies offers great opportunities to improve these systems, make them more efficient and update them regularly and reliably. However, they also pose a challenge in terms of them public management of data protection, and access difficulties for certain sectors of the population, revealing the profound inequalities that persist in the region. Social information systems can also be an extremely useful tool for monitoring and evaluating social policy.

It is important that the organizational structure of the social development ministries include monitoring and evaluation entities, and that they act in a coordinated manner, since the two phases feed into each other. Integration and interoperability between entities and systems dedicated to evaluation and monitoring is also key to progress in this area. According to ECLAC (2023a), 14 ministries of social development in the region have been identified as having a monitoring and evaluation unit or department. Of these ministries, 12 have entities responsible for both functions, while Costa Rica only has an evaluation unit and Suriname has a monitoring unit.

Naturally, there are various approaches to implementing monitoring and evaluation systems in the region. Along with the need for rigour and technical capacity, a key issue is their independence and autonomy to facilitate transparent decision making. An example of this is Mexico’s National Council for the Evaluation of Social Development Policy (CONEVAL), which has autonomy and wide-ranging responsibilities. In addition to public institutions, its participants include civil society actors, such as NGOs, religious groups and trade associations.

The issues described above shine a light on some of the key elements of social institutional frameworks. Although necessary, however, they are not sufficient to guarantee substantive progress towards inclusive social development. Progress also needs to be made on issues such as the quality of supply, the characteristics of the management model, and the available human resources and capacities.

4. The entities that execute labour inclusion programmes and are responsible for them[2]

Along with the requirements for a solid institutional framework for social policy mentioned above, labour inclusion policies require an institutional framework that coordinates the actions of the different government agencies responsible for managing the corresponding policies. The entities that execute and are responsible for labour inclusion programmes are mainly ministries of labour, but also involve ministries of social development. In general, ministries of labour or their equivalent are responsible for implementing 30% of the total number of labour inclusion programmes, while the ministries of social development or equivalent are responsible for 24%. It is worth noting that 6% of the programmes are implemented by social investment funds and 4% by the Office of the President or Vice-President of the Republic.[3] An analysis of the differences between programmes that are currently operating and those that have been concluded, reveals an increase in participation by the ministries of labour as the entities responsible for programmes in operation (16% in these programmes compared to 5% in programmes that have concluded) (see figure IV.6A). Ministries of labour and social development also play a central role in labour inclusion programmes, executing 43% of them, while other institutions execute 31%. It is worth noting that 8% of the programmes are executed on an inter-ministerial or inter-agency basis, and are targeted mainly to the youth population and implemented jointly with ministries of education. This highlights the importance of inter-agency coordination for implementing actions in specific population groups (see figure IV.6B).

Figure IV.6

Latin America and the Caribbean (22 countries):a institutional framework of labour inclusion programmes, by responsible and executing entity, 2000–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Non-contributory Social Protection Programmes Database - Latin America and the Caribbean [online] https://dds.cepal.org/bpsnc/lpi.

a Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Saint Vincent and the Grenadines, Trinidad and Tobago, and Uruguay.

5. Labour institutional framework: regulations and the role of labour inspection in response to changes in the world of work

As noted in chapter II, one of the key aims of labour inclusion policies is to ensure that workers can exercise their rights, by applying standards and recognizing international treaties (see section A.1), and also by creating the capacity to monitor them. Although this is valid for all types of work and sectors of production, it is particularly relevant at a time of transformations and their effects on labour inclusion.

The labour institutional framework includes the rules that regulate the interaction between employers and workers. In general, the region has a wide variety of regulations designed to ensure labour conditions that are appropriate for addressing the risks of instability and lack of protection (Velásquez, 2016). These include labour legislation, minimum wage setting, mandatory entitlements, social security, occupational health and safety, job security, non-discrimination, prohibition of child labour and regulation of adolescent labour, the right to strike and a whole host of regulatory and institutional measures governing this matter (Samaniego, 2002). Labour inspection plays a key role, since it provides an institutional framework that makes a higher quality labour relationship viable for the actors in question and safeguards the rights of workers and fulfilment of their commitments to the employer (Martínez, 2023).

When analysing the new work modalities that are arising as a result of labour automation, particularly in the case of digital platform workers, Latin America lacks regulations to protect these workers except in certain specific cases.[4] Chile is currently the only country in the region that regulates the hiring of digital platform workers. It can also be inferred that other countries aim to legislate regulatory gaps, as in Argentina with Draft Law No. 5045-D–2022, and in Uruguay, with Draft Law No. 156520, among other examples. However, many of these projects are abandoned or take time to materialize (Contreras, 2023).

Integrating labour market regulations into the social protection system makes it possible to safeguard workers’ individual and collective rights. This is essential for reducing and mitigating the risks associated with the lack of labour inclusion in the region (Barrientos and Hulme, 2008). However, it is also important to consider that labour regulations in Latin America apply only to part of the working-age population, since roughly 50% of workers are employed informally (Espejo, 2022).

The labour institutional framework contains measures to balance bargaining power between employers and workers. These actions generally aim to improve the quality of employment; but they may also influence the functioning of the labour market and working conditions, owing to decisions related to innovation and technology adoption (Huepe, 2023). The new work patterns that have emerged following the arrival of digital platforms in the labour market have revitalized and challenged the role of labour inspections. This will require legislative changes to ensure freedom of association and union membership for workers in these atypical platform jobs that are often in grey zones, in other words halfway between self-employment and wage-earning work (Egaña del Sol and others, 2022) (see chapter II).

Labour inspection is usually the responsibility of the Ministry of Labour in each country, under a specific directorate or department (see table IV.1); and its main function is to supervise the behaviour of employers, making it essential to ensure that labour standards are actually enforced (Vega, 2009). The labour inspectorate has a combined structure, since it is firstly responsible for supervising and enforcing the law and, secondly, it provides information, training and advisory services. It is thus a specialized public entity that links the labour reality with the administration of work (Velásquez, 2016).

The number of annual inspections performed by these entities varies significantly, reflecting installed capacity in terms of the number of inspectors available and the number of visits made by each one, along with the size of the firms being inspected and the scope of the inspection. As shown in table IV.1, these variables are dispersed widely across the region.

In a context of high levels of informality and labour precarity in the region, in conjunction with the growth of the economy based on digital platforms, there is a need for a set of social and labour laws to ensure basic levels of protection and welfare for workers. As indicated in chapter II, regulations and labour inspection should pay special attention to two priorities: (i) reducing the size of the grey zone between self-employment and wage-earning work (for example the case of fee-earning workers); and (ii) extending protection to workers whose employment situation is genuinely ambiguous (Egaña del Sol and others, 2022).

Table IV.1

Latin America and the Caribbean (14 countries): institutional framework of labour inspection

Country

Institution

Number of inspectors for every 10,000 persons employed

Average number of annual labour inspection visits per inspector

Year of information

Argentina

National Labour Regularization Plan (PNRT)

0.18

88

2021

Belize

Labour Department

1.44

4

2021

Brazil

Labour Inspection Secretariat (SIT)

0.31

100

2013

Chile

Labour Directorate

0.93

101

2020

Colombia

Inspection, Surveillance, Control and Territorial Management Directorate

0.41

17

2017

Costa Rica

National Labour Inspection Directorate

0.61

38

2020

El Salvador

General Directorate of Labour Inspection

0.48

156

2020

Guatemala

Labour Inspection Services

0.25

155

2021

Mexico

General Directorate of Federal Labour Inspection

0.13

170

2018

Panama

General Labour Inspection Department

0.58

131

2021

Peru

National Superintendency of Labour Inspection (SUNAFIL)

0.25

91

2012

Paraguay

General Directorate of Inspection and Supervision

0.10

10

2015

Trinidad

and Tobago

Labour Inspectorate Unit (LIU)

0.19

71

2014

Uruguay

General Inspectorate of Labour and Social Security

0.63

162

2018

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of International Labour Organization (ILO), ILOSTAT [online database] https://ilostat.ilo.org/.

B. Trend of public social spending in 2000–2022

In 2022, a second year of declining outlays saw central government social spending average 11.5% of GDP, 2.2 percentage points down from the peak in 2020 in Latin American countries. While expenditure remains above the pre-pandemic level, the reduction is equivalent to an average of 5.1% in real terms (measured in dollars at constant 2018 prices). In the five Caribbean countries for which information is available, central government social spending also averaged 11.5% of GDP in 2022, representing a departure from the recent trend, following a peak of 13.8% of GDP in 2021. The functional distribution of expenditure maintains the profile of the last two decades. The heterogeneity of central government social spending continues to be a characteristic of the region, with three countries exceeding 14.5% of GDP, while another five remain at levels below 10%. There are also four countries that spend between US$ 2,560 and US$ 3,110 per capita per year, while six others spend less than US$ 600 per person annually.

Given the centrality of social spending in shaping the social institutional framework and improving the quality of the policies and programmes that are implemented, box IV.1 analyses the information available on public social spending in the countries of the region by function of government, as defined in the International Monetary Fund Government Finance Statistics Manual 2001 and Government Finance Statistics Manual 2014 (IMF, 2001 and 2014). For this purpose, official data for 2000–2022 are compared for central government coverage. Where the necessary information is available, this analysis is supplemented with broader institutional coverages (general government, the non-financial public sector and the public sector). Along with information for the 20 Latin American countries, data are also included for five English-speaking Caribbean countries (see box IV.1).

Box IV.1

Statistical information on public social spending

The data used to analyse public social spending in Latin America and the Caribbean consist of official information provided by each of the countries in the region, compiled annually by the Economic Commission for Latin America and the Caribbean (ECLAC) and available in the CEPALSTAT database and the ECLAC Database on Social Investment in Latin America and the Caribbean. Three indicators are presented as follows: (i) in national currency at current prices; (ii) in percentages of GDP; and (iii) in dollars at constant 2018 prices (the latter prepared by ECLAC, based on official information from the countries). In this edition of Social Panorama of Latin America and the Caribbean, the base year has been updated from 2010 to 2018 and is therefore the series used for the implicit GDP deflator. As a result, the estimates of per capita social spending in dollars at constant prices vary from those reported in previous editions of Social Panorama.

The following table displays the available data series for each of the countries by institutional coverage. A country’s public sector is analysed by subsector or institutional coverage: (i) central government, which comprises ministries, secretariats and public institutions that exercise authority throughout the country (whether some departments have their own legal authority and autonomy); (ii) general government, which consists of central government and subnational governments (first territorial subdivision and local governments), together with social security institutions; (iii) the non-financial public sector, which comprises general government and non-financial public corporations; and (iv) the public sector, which encompasses the non-financial public sector and financial public corporations. The comparative analysis is more complete at the general government level, since there are federal countries, or countries in which intermediate governments have high levels of collection and management autonomy, where a large part of social spending is also the responsibility of subnational authorities. However, information for this institutional coverage is not available for all of the region’s countries, so it is appropriate to compare data for central government, which are widely available and are linked to national budgetary processes.

Latin America and the Caribbean (25 countries): availability of information on public social spending, by functional classifier, institutional coverage and years available

Country

Central government

Other existing levels of coverage

General government

Non-financial public sector

Public sector

Latin America

Argentina

1993–2022

…

…

1990–2021

Bolivia (Plur. State of)

1990–2021a

1997–2020

…

…

Brazil

1995–2022

2000–2022

…

Chile

1990–2022

…

…

…

Colombia

1990–2022

2009–2021

…

…

Costa Rica

1993–2022

1990–2016

2019–2021

…

…

Cuba

2002–2020

1996–2020

…

…

Dominican Republic

1990–2022

2017–2022

…

…

Ecuador

2000–2022

…

…

…

El Salvador

1990–2022

…

…

2002–2021b

Guatemala

1995–2022

2014–2022

…

…

Haiti

2012–2014

…

…

…

Honduras

2000–2022

…

…

…

Mexico

1999–2022

…

2013–2022b

…

Nicaragua

1998–2022

…

…

…

Panama

2000–2021

…

…

…

Paraguay

2000–2022

2003–2022

…

…

Peru

…

1999–2022

…

…

Uruguay

1990–2022

…

…

…

Venezuela (Bol. Rep. of)

1997–2014

…

…

…

The Caribbean

Bahamas

1990–2022

…

…

…

Barbados

2006–2022

…

…

…

Guyana

2004–2022

…

…

…

Jamaica

1992–2022

…

…

…

Trinidad and Tobago

2008–2022

…

…

…

Source: Economic Commission for Latin America and the Caribbean (ECLAC), CEPALSTAT [online database] https://statistics.cepal.org/portal/cepalstat/index.html?lang=en; Database on Social Investment in Latin America and the Caribbean [online] https://observatoriosocial.cepal.org/inversion/en; Social Panorama of Latin America and the Caribbean, 2016 (LC/PUB.2017/12-P), Santiago, 2017; International Monetary Fund (IMF), Government Finance Statistics Manual 2014, Washington, D.C., 2014.

a Central administration.

b Subnational governments are not consolidated.

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

1. Trends in central government social spending in the region

Between 2000 and 2019, average central government social spending in Latin America remained broadly stable relative to GDP. There were two spikes in response to economic crises, followed by periods in which the increase was partially reversed. Following the onset of the COVID-19 pandemic, expenditure in the region attained a new peak in 2020 (ECLAC, 2022a and 2022b). The data for the three-year period 2020–2022 show a significant break in trend, with a cumulative reduction averaging 2.2 percentage points of GDP over the period. Although the levels prevailing in 2019 have not been regained, average expenditure is only 0.3 percentage points of GDP higher than in that year (see figure IV.7).

The historical average level of central government social spending in Latin American countries recorded in 2020 occurred at a time when the region’s economies were experiencing an also historical contraction of 6.8% of GDP (ECLAC, 2023b). Thus, the growth in social spending represented a response to the socioeconomic effects of the COVID-19 pandemic. In 2021, social spending declined relative to GDP, but the economies also expanded by 6.8%, so an increase was maintained in absolute terms. In contrast, as noted below, in 2022 the decrease in central government social spending relative to GDP reflects an absolute contraction. This is a warning sign regarding the financial sustainability of social policies in the region’s countries.

Figure IV.7

Latin America (17 countries): central government social spending, 2000–2022

(Percentages of GDP and of total public expenditure)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The figures shown correspond to the arithmetic mean of the following Latin American countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay. Coverage in the Plurinational State of Bolivia corresponds to central administration and that of Peru to general government. The data for Panama and the Plurinational State of Bolivia refer to 2021.

In 2022, the share of public social spending in total central government expenditure declined by an average of 2 percentage points, following the previous year’s 0.6 percentage point reduction. Nonetheless, public social spending remained the leading component of total public expenditure, with a share of 53.4%.

In the five English-speaking Caribbean countries for which comparable data are available (Bahamas, Barbados, Guyana, Jamaica and Trinidad and Tobago), a relatively similar trend to that of the Latin American countries was observed between 2008 and 2020. As noted by ECLAC (2022e), in 2021 the rising trend continued to generate average central government social spending equivalent to 13.8% of GDP. In 2022, however, the trend was broken, with the figure falling to 11.5% of GDP, on average, slightly higher than in 2019 and the average of the final years of the past decade. This is seen as the result of both a real decline in expenditure and a recovery in the countries’ GDP growth (see figure IV.8).

The average share of public social spending in total central government expenditure of the five Caribbean countries regained the 2018 levels.[5] In that group, a drop of 2.6 percentage points was recorded with respect to 2021, reflecting a further divergence (of 11.1 percentage points) from the average values recorded among Latin American countries.[6]

Figure IV.8

The Caribbean (5 countries): central government social spending, 2008–2022

(Percentages of GDP and of total public expenditure)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The figures shown correspond to the arithmetic mean of the following Caribbean countries: Bahamas, Barbados, Guyana, Jamaica, and Trinidad and Tobago. The fiscal calendar of some Caribbean countries differs from that of Latin American countries: Bahamas (July–June); Barbados, Jamaica (April–March), and Trinidad and Tobago (October–September). The published reference period corresponds to the calendar year of the closing month.

A comparison of the situation between the two subregions in 2022 shows that average total public social spending relative to GDP fell significantly more steeply in the Caribbean countries than in Latin American countries as a whole. While the former recorded a 1 percentage point increase in social spending in 2021, no differences were observed in 2022.

As shown in figure IV.9, the average of the South American countries is 13.2% of GDP, which is 2.3 percentage points of GDP lower than in 2021 and down by 3.1 points relative to 2020. Nonetheless, the subregion continues to report the highest average level of social spending relative to GDP. Heterogeneity between the different countries in the subregion persists, and Chile remains the country with the highest central government social spending relative to GDP in the region. Nonetheless, the 6.9 percentage point reduction recorded by this country also reduced heterogeneity in the subregion —from a range of 14.6 percentage points between the countries with the highest and lowest levels of social spending in 2021 to one of 8.2 percentage points in 2022. Paraguay continued to report the lowest level of central government social spending (9.7% of GDP) while Chile attained a level of 17.9% of GDP. Colombia and Uruguay are two other countries in the subregion in which this indicator fell sharply (by 3.2 and 2.2 percentage points, respectively).

Figure IV.9

Latin America and the Caribbean (22 countries): central government social spending, by country and subregion, 2021 and 2022

(Percentages of GDP)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: Coverage in the Plurinational State of Bolivia corresponds to central administration and that of Peru to general government. The data for Uruguay do not include the Social Security Bank (BPS). The data for Panama and the Plurinational State of Bolivia correspond to 2021. The 2021 levels of public social spending are included as a reference for comparison purposes.

In the group formed by the six Central American countries, plus the Dominican Republic and Mexico, central government social spending averaged 9.5% of GDP in 2022, 0.8 percentage points lower than in the previous year, following a similar reduction in 2020. Heterogeneity among these countries also narrowed, to a range of 3.1 percentage points. In 2022, three countries reported central government social spending below 10% of GDP, namely the Dominican Republic, Guatemala and Honduras.

Among the five Caribbean countries with data available, the average of 11.5% of GDP recorded in public social spending in 2022 displays similar heterogeneity to the previous year, with a range of 6.9 percentage points between the countries with the highest and lowest levels of social spending, namely Guyana and Barbados. Only Jamaica recorded increases in public social spending relative to GDP (from 11.5% to 12.2%), while the other countries saw reductions of between 1.3 and 4.7 percentage points. It is worth noting the huge GDP growth experienced by Guyana since the end of 2019 when it started producing crude oil. Growth of 52% at constant prices is estimated for that country (ECLAC, 2023b).

Complementing the above, the region’s central government social spending continued to decline in 2022, with the Latin American countries recording a 5.1% reduction in dollars at constant 2018 prices. On average, the South American countries experienced the steepest fall in their growth rate (-6.3%), while Central America plus the Dominican Republic and Mexico reported a reduction of 3.9%. As figure IV.10 shows, 2022 was the only year in which these subregions posted negative growth. In the five Caribbean countries analysed, average growth remained positive, but was lower than in 2021 (0.7%).

Figure IV.10

Latin America and the Caribbean (22 countries): average annual real growth rates of central government social spending, by subregion, 2011–2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The Latin American figures shown correspond to the arithmetic mean of 17 countries, which are divided into two groups: nine from South America (Argentina, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Plurinational State of Bolivia and Uruguay) and eight from Central America (Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua and Panama) plus the Dominican Republic and Mexico. The Caribbean includes five countries (Bahamas, Barbados, Guyana, Jamaica and Trinidad and Tobago). Coverage in the Plurinational State of Bolivia corresponds to central administration and that of Peru to general government. The data for the Plurinational State of Bolivia and Panama correspond to 2021.

The annual growth of central government social spending varies considerably across the different countries and, in several cases, is the opposite of what occurred in 2021 (see figure IV.11). In South America, Chile experienced a contraction of 26.1% in 2022, following 38.4% growth in 2021, thereby accumulating growth of 2.3% relative to 2020 over the two years. With a similar trend, in the last year Colombia saw a drop of 15.3% in 2022, following the 5.4% expansion reported in 2021, as did Peru, which reported growth rates of 4.2% and 3.9%, respectively. Brazil, in contrast, displays the opposite situation, recording growth of 3.5% in 2022, as opposed to the 20.3% drop recorded in 2021. In contrast, Argentina, Paraguay and Uruguay recorded reductions in two consecutive years, with a cumulative drop of 14.7% in the biennium in the case of Uruguay.

Among the Central American countries, Honduras experienced the steepest fall in the growth rate of central government social spending in 2022 (-17.8%), in contrast to the 21.2% growth recorded in 2021, resulting in cumulative growth of 7.1% over the biennium. Similar situations occurred in Nicaragua, although less accentuated and with a negative cumulative balance, with growth rates of -8.6% and 17.2% in 2022 and 2021, respectively; and also in Costa Rica, where annual growth rates came in at -6.2% in 2022 and 3.3% in 2021. In contrast, Guatemala displays the opposite pattern, with growth of 5.8% in 2022, following a 12.6% decline in 2021, as does the Dominican Republic, which grew by 1.1% in 2022, after contracting by 19.2% in 2021.

Figure IV.11

Latin America and the Caribbean (22 countries): annual growth rates of central government social spending, by country and subregion, 2020 and 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The bars represent growth rates between 2021 and 2022, calculated as the change in expenditure in dollars at constant prices. The Latin American figures shown correspond to the arithmetic mean of 17 countries, which are divided into two groups: nine from South America (Argentina, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Plurinational State of Bolivia and Uruguay) and eight from the group made up of Central America (Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua and Panama) plus the Dominican Republic and Mexico. The Caribbean includes five countries (Bahamas, Barbados, Guyana, Jamaica and Trinidad and Tobago). Coverage in the Plurinational State of Bolivia corresponds to central administration and that of Peru to general government. The data for Uruguay do not include the Social Security Bank (BPS). The data for Panama and the Plurinational State of Bolivia correspond to 2021.

Of the five Caribbean countries, Guyana recorded lower social spending relative to GDP, but posted an increase of 20.8% in 2022, following the previous year’s 5.5% rise. These figures are associated with the major expansion of its economy in recent years, driven by oil. The most pronounced decline in growth among these countries occurred in the Bahamas (-11.8%). This country recorded growth of 27.1% in 2021, and a cumulative 12.1% in the biennium. It was followed by Barbados, where social spending contracted by 7.3% in 2022.

2. Trend of social spending per person

As a simple average of 22 countries in the region, per capita central government social spending, in dollar terms at constant 2018 prices, was US$ 1,251 in 2022, down by US$ 99, or 7.3%, on the previous year’s level.

Among the 17 Latin American countries, average central government social spending in 2022 amounted to US$ 1,048 per person, US$ 104 less than in the previous year, a reduction driven mainly by the South American countries. While the average of this subregion decreased by US$ 177 (-11.7%), in the group formed by the countries of Central America, the Dominican Republic and Mexico it decreased on average by US$ 21 (-2.8%). Thus, the South American countries spent an average of US$ 12 less per capita than in the year prior to the COVID-19 pandemic, while the Central American countries spent an average of US$ 34 more (see figure IV.12).

Figure IV.12

Latin America and the Caribbean (22 countries): per capita central government social spending, by subregion, 2000–2022

(Dollars at constant 2018 prices)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The Latin American figures shown correspond to the arithmetic mean of 17 countries, which are divided into two groups: nine from South America (Argentina, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Plurinational State of Bolivia and Uruguay) and eight from Central America (Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua and Panama) plus the Dominican Republic and Mexico. The Caribbean includes five countries (Bahamas, Barbados, Guyana, Jamaica and Trinidad and Tobago). Coverage in the Plurinational State of Bolivia corresponds to central administration and that of Peru to general government. The data for Uruguay do not include Social Security Bank (BPS). The data for the Plurinational State of Bolivia and Panama correspond to 2021.

In the English-speaking Caribbean, the five countries analysed also suffered cuts in per capita central government social spending in 2022, with an average reduction of US$ 83 (-4.1% relative to the previous year’s level). Compared to the average of the Latin American countries, this effect widens the gap between the two regions, making it 86% larger.

An analysis by country shows that in 2022, the central government of the Bahamas allocated the most resources per capita to social spending, at US$ 3,113, followed by Chile, at US$ 2,924. A second group of countries consisted of Uruguay, Barbados and Trinidad and Tobago, with per capita expenditure ranging from US$ 1,961 to US$ 2,597, followed by Argentina, Brazil, Costa Rica and Guyana (between US$ 1,390 and US$ 1,606). A group of eight countries, comprising Colombia, the Dominican Republic, Ecuador, El Salvador, Jamaica, Mexico, Paraguay and Peru, allocated between US$ 478 and US$ 966 per capita. Lastly, three Latin American countries (Guatemala, Honduras and Nicaragua) spent between US$ 198 and US$ 365 per person (see annex table IV.A1.1).

Complementing the above, and as noted in the previous section, Guyana was the country with the highest year-on-year variation in this indicator, with an increase of 20.2%. It was followed at a considerable distance by Guatemala (4.4%), Mexico (3.8%), Brazil (3%) and Jamaica (2.9%). The main reductions in the average per capita occurred in Chile (-26.5%), Honduras (-19%) and Colombia (-15.9%). Of concern are the steep falls in Honduras and Nicaragua (-9.9%), countries previously grouped as having the lowest levels of central government social spending.

There are two features of central government social spending that characterize the situation in the region. Firstly, the countries that face the greatest challenges in achieving the social goals of the 2030 Agenda for Sustainable Development, in relation to poverty, health, education, social protection and access to drinking water, electricity and sanitation, allocate less resources to social spending, both in absolute terms and in relation to population and GDP. Secondly, in these three indicators, the region’s countries lag far behind those of the Organisation for Economic Co-operation and Development (OECD) and the European Union.[7] This reaffirms the need to forge a new fiscal compact to strengthen and underpin the financial sustainability of social policies, and thus make progress in creating rights-based welfare states that will eradicate poverty and reduce inequalities in the region.

3. Social spending by function of government

The distribution of central government social spending between the six social functions of government is unchanged relative to the previous two decades. In Latin America, the social protection and education functions continue to report the highest levels of expenditure, both in absolute dollar amounts and relatively, averaging 4.3% and 3.7% of GDP, respectively (see figure IV.13). Expenditure on these two functions contracted in 2022: by 0.7 percentage points of GDP in social protection and by 0.2 points in education. The health function remains the third spending priority (2.6% of GDP on average), but also suffered a reduction (0.4 percentage points of GDP) while remaining above its historical level.

Figure IV.13

Latin America and the Caribbean (22 countries): central government social spending by function, 2000–2022

(Percentages of GDP)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The Latin American figures shown correspond to the arithmetic mean of 17 countries, which are divided into two groups: nine countries in South America (Argentina, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Plurinational State of Bolivia and Uruguay) and eight countries in the Central American group (Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua and Panama), plus the Dominican Republic and Mexico. The Caribbean includes five countries (Bahamas, Barbados, Guyana, Jamaica and Trinidad and Tobago). Coverage in the Plurinational State of Bolivia corresponds to central administration and that of Peru to general government. The data for the Plurinational State of Bolivia and Panama correspond to 2021.

The trend among South American countries is equivalent to that of Latin America as a whole, although with steeper rates of decline in the social protection function. Consequently, this is the subregion with the largest drop relative to GDP, with central government social spending falling back to its 2019 level. Meanwhile, among the Central American countries plus the Dominican Republic and Mexico, the fall was more moderate, and the level of social spending stayed above pre-pandemic levels.

As has been characteristic since the start of the data series analysed, the weight of the social protection function marks the difference between the two Latin American subregions. In 2022, average central government spending on social protection as a percentage of GDP in South American countries (6.3%) is almost three times the average of Central America, the Dominican Republic and Mexico (2.2%).

The education function absorbs the second largest share of central government social spending among Latin American countries, but has historically ranked first in the subregion comprising Central America, the Dominican Republic and Mexico, and with greater weight than in South America. In 2022, the trend persisted, with averages of 4.0% and 3.5% of GDP, respectively. However, in both cases the levels are below those prevailing in 2019, before the COVID-19 pandemic.

The average level of expenditure on the health function decreased in both subregions in 2022. In South America it fell to 2.8% of GDP and in the countries of Central America, the Dominican Republic and Mexico it dropped to 2.4% of GDP. In both cases, however, these rates are higher than in 2019, especially in the latter group of countries, where the average relative to GDP was one-third higher in 2021.

In terms of housing and community services, average expenditure remained stable at around 0.5% of GDP; and, in line with the established trend, the countries of Central America, the Dominican Republic and Mexico allocated more to this function than those of South America (0.7% versus 0.4% of GDP on average, respectively).

Analysis of the functional distribution in the five English-speaking Caribbean countries analysed reveals that, in 2022, the average variation reflects reductions in each of the social functions. The central government social protection function experienced the steepest fall of 0.8 percentage points of GDP, while the health function declined by a similar magnitude (0.7 percentage points of GDP). The education function, meanwhile, decreased somewhat less (0.6 percentage points of GDP), but hit its lowest level in the entire series since 2008, accumulating two years of significant reductions.

In the various subregions, the environmental protection and recreation, culture and religion functions maintained the average levels reported in 2022 relative to GDP. In these functions, the Caribbean countries allocate, on average, more resources than those of Latin America. The former subregion spends over three times more relative to GDP (0.42% and 0.11%, respectively), while Latin America on average spends more than twice as much (0.3% and 0.13% of GDP, respectively).

The foregoing analysis is complemented by the proportional distribution of central government social spending among the various social functions of government in each country, from which their priorities in the allocation of public resources can be estimated. Coinciding what has been indicated at the regional level and has been reported in previous editions of Social Panorama of Latin America (ECLAC, 2017, 2019a, 2019b, 2019b, 2021b and 2022a), in most countries the social protection, education and health functions absorb a large proportion of the resources disbursed in 2022. Nonetheless, significant differences in distribution persist (see figure IV.14 and annex table IV.A1.1). It should also be kept in mind that the distributions analysed here refer to official central government data in 2022. The amounts and distribution of outlays may vary significantly with broader institutional coverage, such as general government or the non-financial public sector. This is particularly relevant in countries with a federative structure; or in those with subnational governments that have high levels of autonomy, such as Argentina, Brazil, Colombia and Mexico, and also in countries where at least part, if not all, of social security resources are not recorded in central government, as is the case in Costa Rica, Ecuador and Uruguay, among others (see section B.4).

Figure IV.14

Latin America and the Caribbean (23 countries): distribution of central government social spending, by function, 2022

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: Coverage in the Plurinational State of Bolivia corresponds to central administration and that of Peru to general government. The data for Plurinational State of Bolivia and Panama correspond to 2021; those for Cuba refer to 2020.

The following paragraphs provide a brief description of central government social spending on each social function in the Latin American and Caribbean countries for which information is available for 2022.[8]

(a) Social protection

An analysis of expenditure on social protection policies considers outlays in respect of services and transfers to individuals and families, related to illness and disability, old age, survivors, family and children, unemployment, housing and social exclusion.9 10 Both the contributory and non-contributory social protection sectors are considered. This function includes policies and programmes aimed at covering the risks of income loss or increased expenses that can affect part or all of the population (related to illness, old age, care, disasters, economic and social crises[11] and unemployment), as well as those aimed at facilitating inclusion and protecting the population from the consequences of poverty and inequality (such as income or in-kind transfer programmes and non-contributory pension systems).

The countries of the region that allocated a higher proportion of GDP to the social protection function at the central government level in 2022 were Brazil (12.6%) and Argentina (10.8%), followed by Chile (7.3%), Uruguay (5.4%), Trinidad and Tobago and Colombia (both with 5.2%). In contrast, Nicaragua allocated less than 1% of GDP.

Despite the downward trend, 12 countries kept expenditure in this function above pre-pandemic levels. The countries with the largest increases in spending relative to GDP compared to the level in 2019 before the COVID-19 pandemic, include Ecuador (+1.8 percentage points), the Bahamas (+1.3 points), El Salvador (+1.2 points) and Chile (+1.1 points). In contrast, the countries with the steepest reductions over the period are Uruguay (-1.8 percentage points of GDP), Guyana (-0.7 points), Costa Rica (-0.5 points) and Colombia (-0.4 points). These variations represent a combination of real increases in expenditure and large changes in GDP growth in the different countries between the years mentioned.

The contrast between social protection expenditure and total central government social spending shows that in 2022 the number of countries allocating the largest share of their resources to this function decreased from 12 to 10. Argentina and Brazil allocated the largest share to this function (80% and 76%, respectively), followed by Cuba (71%)[12] and Mexico (47%). Five other countries report shares of between 40% and 44% in this function: Colombia, Ecuador, Uruguay, Chile and Trinidad and Tobago. In contrast, Honduras, Jamaica, Nicaragua and Panama allocated less than 10% of social spending to finance social protection (see figure IV.14 and annex table A1.1).

An analysis of the per capita amounts spent on social protection identifies a group of four countries with the highest expenditure (Argentina, Brazil, Chile and Uruguay), with figures ranging from US$ 1,073 to US$ 1,282 per person in 2022. In contrast, Jamaica, Guatemala, Honduras and Nicaragua spent less than US$ 62 per capita on this function. In relative terms, the year-on-year variations reveal some positive increases despite the trend in social spending. Ecuador, Mexico and Guyana increased their social protection funding by between 8.4% and 14%, followed by Brazil and Argentina (+5.3% and +3.5%, respectively). In contrast, three countries recorded sharp reductions, namely Honduras (-63%), Chile (-46%) and the Bahamas (-32%), following significant increases in 2021. Thus, despite these reductions, their expenditure in 2022 is still above the pre-pandemic levels of 2019 (see figure IV.15).

Figure IV.15

Latin America and the Caribbean (20 countries): central government per capita expenditure on social protection, by country and subregion, 2022

(Dollars at constant 2018 prices and year-on-year percentage variations)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The bars represent expenditure in dollars at constant 2018 prices. Increases are identified by upward-pointing triangles and reductions by triangles pointing downwards. Coverage for Peru corresponds to general government. The data for Uruguay do not include the Social Security Bank (BPS).

It should be recalled that in several countries, data from social security institutes can increase the indicated social protection expenditure and modify the trends described above. This is caused by the different institutional models and modes of resource administration, as some countries have management and accounting autonomy or favour private administration. These effects can be seen partially in the analysis of broader institutional coverage presented in section C.

(b) Education

The analysis of education expenditure considers all outlays deployed to finance education policies at the three levels of education (from preschool to tertiary), along with auxiliary services and research and development activities. To this end, the Education 2030 Framework for Action urges governments to allocate at least 4% to 6% of GDP, or at least 15% to 20% of public expenditure to education (UNESCO and others, 2016).

As in previous years, the countries that allocated the most central government funding to education, relative to GDP in 2022, were Costa Rica (5.7%) followed by Jamaica (5.4%).[13] A second group consists of Barbados, Honduras and Chile, with amounts between 4.5% and 5.0% of GDP, followed by El Salvador, Nicaragua, Peru, the Dominican Republic and Uruguay, which allocate between 3.7% and 4.3% of GDP to this item.

As noted above, education expenditure levels in 2022 are lower on average than in 2019, before the COVID-19 pandemic. Only six countries reported slight increases relative to GDP in this function: Argentina, Bahamas, Brazil, El Salvador, Jamaica and Peru (increases of between 0.07 and 0.2 percentage points each).

If central government expenditure alone is considered, only eight of the region’s countries attain or exceed the GDP share recommended by the United Nations Educational, Scientific and Cultural Organization (UNESCO), compared to 11 in 2019. In countries such as Argentina and Brazil education expenditure is underestimated in central government coverage, so they would join the list if broader coverage were considered. In addition, 16 countries meet the target of allocating over 15% of total expenditure to education.

The countries that allocated a higher proportion of central government social spending to this function in 2022 were Honduras and Costa Rica, with shares of 57% and 54%, respectively. They are followed by Jamaica (45%), the Dominican Republic (44%) and Guatemala (41%).

In terms of dollars per capita allocated to education, five countries spent between US$ 755 and US$ 885 in 2022, namely the Bahamas, Barbados, Chile, Costa Rica and Uruguay. In contrast, Guatemala, Honduras and Nicaragua spent less than US$ 151 per person. Figure IV.16 shows the real year-on-year variations between 2021 and 2022. Despite the average decline, a large group of countries report increases. These include Argentina, Brazil, the Dominican Republic, Guatemala, Guyana and Uruguay (with increases of between 5.8% and 13.5% each). The countries displaying reductions in expenditure are the Bahamas, Colombia, Costa Rica, El Salvador and Honduras (decreases of between 6.6% and 12.2%).

Figure IV.16

Latin America and the Caribbean (20 countries): central government per capita expenditure on education, by country and subregion, 2022

(Dollars at constant 2018 prices and year-on-year percentage variations)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The bars represent expenditure in dollars at constant 2018 prices. Increases are identified with upward-pointing triangles and reductions with downward-pointing triangles. Coverage for Peru corresponds to general government. The data for Uruguay do not include the Social Security Bank (BPS).

(c) Health

In order to progress towards universal health care, it is essential to allocate public expenditure equivalent to at least 6% of GDP to this function (PAHO, 2014). This is considered a benchmark for country performance in terms of the financial sustainability of the health system. In this context, the analysis of health expenditure considers all outlays on services provided to individuals and collective entities at different levels of health care, in both preventive and curative programmes.

Although in 2022 there was an average drop in spending on the health function, it has remained above the pre-pandemic levels of 2019. According to Social Panorama of Latin America 2022, the pandemic had a displacement effect in 2021, because health services that were normally in demand were interrupted. In 2022, the countries that spent the most on this function relative to GDP consisted of the Bahamas, Chile, Jamaica and Nicaragua (between 3.8% and 5.3% of GDP each). None of them attained the target of at least 6% of GDP agreed on by the member countries of the Pan American Health Organization (PAHO). Only Jamaica reported an increase relative to GDP, of 0.4 percentage points.

An analysis of these figures in relation to all social functions reveals that six countries allocated 30% or more of central government social spending to the health function, with the largest shares in Nicaragua and Jamaica (both 40%), the Bahamas (36%), Honduras (34%), Guyana (31%) and Chile (30%). Four other countries allocated between 25% and 30% of social spending to this function, namely El Salvador and Colombia (both 28%), and Peru and Paraguay (both 26%). In contrast, Argentina and Costa Rica allocated less than 10% of central government social spending to health. These data do not include the Costa Rican Social Security Fund (CCSS) in the central government figures; and Argentina’s accounting for health actions in the non-financial public sector also shows a smaller share of this function in central government.

In terms of the per capita amount of central government resources used to finance health care, the leading countries were the Bahamas (US$ 1,122), Chile (US$ 868), Barbados (US$ 513), Uruguay (US$ 473), Trinidad and Tobago (US$ 456) and Guyana (US$ 426) (see figure IV.17).

Figure IV.17

Latin America and the Caribbean (20 countries): central government per capita expenditure on health, by country and subregion, 2022

(Dollars at constant 2018 prices and year-on-year percentage variations)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The bars represent expenditure in dollars at constant 2018 prices. The bars represent spending in dollars at constant 2018 prices. Increases are identified by upward-pointing triangles and reductions by downward-pointing triangles. Coverage for Peru corresponds to general government. The data for Uruguay do not include the Social Security Bank (BPS).

Health expenditures decreased in most of the countries analysed. The only countries to report increases relative to 2021 were Guyana (+15.2%), Jamaica (+6.5%) and, to a lesser extent, El Salvador and Trinidad and Tobago (+2.6% and +2.4%, respectively).

As noted above, these estimates could vary when broader institutional coverage is considered and other entities included, such as social security funds and institutes or social security banks, which in some countries play an important role in health spending in the contributory system. For example, according to official data from Brazil, while per capita central government spending on health was US$ 168 in 2022, at the general government level it was US$ 512.

(d) Housing and community services

Public expenditure on housing and community services includes government funding for urbanization (which encompasses both the administration of urbanization issues and slum clearance related to housing construction and redevelopment, as well as the acquisition of land necessary for such construction), and also for community development, water supply, and street lighting.

In 2022, the countries in the region in which central government social spending on this function was greatest were Guyana and Barbados (both 1.6% of GDP), followed by Guatemala and Nicaragua (both 1.4% of GDP), and Trinidad and Tobago (1.3% of GDP).

As a proportion of central government social spending, the leading countries were Guyana (21%), Guatemala (18%), Nicaragua (13%) and Barbados (11%). Meanwhile, in dollars at constant 2018 prices, three Caribbean countries report the highest levels per capita: Guyana, Barbados and Trinidad and Tobago (between US$ 201 and US$ 297 each). They are followed at a distance by Uruguay and Mexico (US$ 110 and US$ 92, respectively).

(e) Recreation, culture and religion

This function covers the financing of recreational, cultural and religious activities, including sports and cultural activities, radio and television and religious services.

At the tenth Ibero-American Conference on Culture, held in Valparaíso, Chile, in July 2007, ministers and high authorities of culture proposed to allocate progressively, a minimum of 1% of the general budget of each State to the promotion of culture (ECLAC/OEI, 2014, p. 311).

In 2022, Barbados was the country with the highest level of expenditure on this function (0.7% of GDP), followed by Peru (0.3%), and Trinidad and Tobago and El Salvador (both with 0.24% of GDP). Barbados and Peru spent the most on this function relative to total central government expenditure, with amounts that exceed the indicated target (2.4% and 1.5%, respectively). Paraguay, Guatemala, Nicaragua and El Salvador, on the other hand, allocated between 1.1% and 1.21% of total central government spending to this function.[14]

In terms of per capita amounts in dollars at 2018 prices, again Barbados allocates the largest amount, equivalent to US$ 121, followed by three other Caribbean countries: Bahamas, Trinidad and Tobago and Guyana (with US$ 67, US$ 37 and US$ 34, respectively).

As in previous years, Argentina and the Plurinational State of Bolivia did not report central government public expenditure on this function.

(f) Environmental protection

As part of the social functions, expenditure on environmental protection includes waste and wastewater management, pollution abatement, protection of biodiversity and landscape, and research related to environmental protection.

The Bahamas reported the highest level of spending on this function in 2022 (1.2% of GDP), followed by Barbados and Peru (0.5% and 0.4% of GDP, respectively). The other countries did not attain a level of 0.3% of GDP.

The per capita analysis, in dollars at constant 2018 prices, shows that the Bahamas and Barbados concentrate the largest amount of resources, with US$ 372 and US$ 88, respectively. The other countries spend less than US$ 35 per person.

It should be kept in mind that in this function there are significant variations when broader institutional coverage is considered, including subnational levels of government (given their role in waste management) and public companies engaged in wastewater treatment. More detailed information in this area is provided by the data consolidation work contained in the corresponding satellite accounts. In addition to providing a more complete view of the resources allocated, accounts of this type record the actions carried out by different actors within the framework of environmental protection policies in the different countries.[15]

4. Public social spending with broader institutional coverage than central government: selected countries

As noted above, central government is the only institutional coverage for which the available information allows comparisons to be made between all countries in the region. However, as can be seen from the information contained in box IV.1, some Latin American countries generate aggregate reports on public social spending with broader institutional coverage than the central government (general government, non-financial public sector, or public sector). This section complements the analysis with information available for six countries that have reports up to 2022 (Brazil, the Dominican Republic, Guatemala, Mexico, Paraguay and Peru) and another four, Argentina, Colombia, Costa Rica and El Salvador, which have data up to 2021 (see table IV.A1.2 in the annex).[16]

As shown in figure IV.18, public social spending is considerably higher at institutional coverage that is broader than central government.[17] On average, among the nine countries (excluding Peru) that reported data on both coverage levels in 2021 or 2022, the difference amounts to 6.5 percentage points of GDP. In relative terms, the difference is between 18% and 96% of the amount spent at the central government level.

Figure IV.18

Latin America (10 countries): public social spending by institutional coverage, 2021–2022

(Percentages of GDP)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

Note: The extended coverage of Argentina and El Salvador corresponds to the public sector, while that of Mexico corresponds to the (federal) non-financial public sector. Mexico’s institutional coverage includes central government, social security institutions and state enterprises, but does not include incremental expenditures produced in subnational governments. For Peru, data are only available for general government coverage. The data for Argentina, Colombia, Costa Rica and El Salvador refer to 2021; data for Brazil, Dominican Republic, Guatemala, Mexico, Paraguay and Peru refer to 2022.

The distribution of public social spending by function also changes significantly in some countries when considering broader institutional coverage compared to that of the central government.[18] The data for the five countries that report information corresponding to 2022 for broader coverage than central government are presented below.

•In Brazil, data for 2022 show that consolidated general government social spending reached an amount equivalent to 28.6% of GDP, representing an increase of 0.9 points compared to 2021. Thus, the country as a whole allocated 12.1 percentage points of GDP more than indicated in the central government report. In terms of dollars per capita at constant 2018 prices, Brazil’s general government social spending amounted to US$ 2,690, 74% more than the US$ 1,546 reported for central government, one of the highest levels in the region.

•The structure of expenditure of broader coverage accounts for the increase in resources available for the health and education functions. These two functions account for 19% and 20%, respectively, of general government social spending, compared to 11% and 12% in the case of central government. Thus, with general government data, the amount of funding provided to the education function places Brazil among the countries that attain the target proposed for the region, with 5.6%. In the case of health, although Brazil does not achieve the target proposed by the Pan American Health Organization (PAHO), it comes close and is one of the countries with the highest level of health spending in the region, at 5.4% of GDP.

•Guatemala reported social spending equivalent to 9.5% of GDP at the general government level in 2022, 1.8 percentage points higher than at central government coverage. This represents a slight increase of 0.1 percentage points of GDP over the 2021 figure. Meanwhile, in terms of dollars per capita at 2018 prices its social spending amounted to US$ 450 in 2022, which is 23% more than the US$ 365 recorded for central government.

•The expanded coverage accounts for the resources available for the social protection and health functions. Thus, in 2022, social protection accounted for 27% of the general government’s social spending, as opposed to 17% at the central government level. The equivalent proportions for the health function were 25% and 19%, respectively.

•In Mexico, social spending in the (federal) non-financial public sector reached a level equivalent to 15.4% of GDP in 2022, 5.2 percentage points higher than the figure for central government.[19] This equates to US$ 1,459 per capita at constant 2018 prices, or 2.96 times the US$ 493 reported for central government.

•The distribution of resources by function is similar between the two institutional coverage levels. In the expanded coverage, the health and social protection functions report higher expenditure than for central government. While the latter reported spending 12% and 47% of total social spending on the health and social protection functions, the equivalent proportions are 18%

and 55%, respectively in the extended coverage.

•In Paraguay, consolidated general government social spending reached 12.8% of GDP in 2022, 3.1 percentage points higher than the corresponding figure for central government. Amounts in dollars at constant 2018 prices report social spending of US$ 779 per capita in 2022, 32% more than the US$ 592 recorded at the central government level.

•The distribution between the different functions is similar at both levels of institutional coverage; and, as was the case with Guatemala and Mexico, the expanded coverage reveals larger shares for the social protection and health functions —39% and 32% of spending, respectively, at the general government level, or 3.1 and 5.7 percentage points more than reported by central government in 2022.

•The Dominican Republic reported consolidated general government social spending equivalent to 10% of GDP in 2022, which represents 1.5 percentage points more than central government spending and a reduction of 0.4 percentage points of GDP on the previous year’s figure. In dollars at constant 2018 prices, the per capita value of social spending in 2022 was US$ 883.

•As in the other countries, both coverage levels have a similar distribution between the different functions. However, in proportional terms social spending on health by general government accounted for 30%, compared to 22% by central government.

C. Public investment in labour inclusion policies in Latin America

Weak growth and high inflation rates have continued to have a major impact on labour markets in Latin America and the Caribbean, as part of the cascading global crises that are currently unfolding. In this context, public expenditure on labour policies has shrunk, amounting to 0.42% of GDP on average in 2022. The distribution of these resources, according to the categories of the study, still vary greatly in terms of expenditure levels. Expenditure on policies to support the unemployed has dropped sharply, returning to pre-pandemic levels, mainly owing to the closure of several emergency programmes implemented between 2020 and 2021. Challenges remain in the region, including the need to strengthen the development of active labour market policies to improve labour inclusion and decent work, with greater female participation and increased formalization; and to mitigate the effects of the current crisis, with emphasis on the groups specially impacted. There is also a need to improve the availability of information from governments or policy makers in terms of spending, impact assessment and the application of tools to improve decision-making.

The economic slowdown and the global crisis have had consequences that include a major impact on the region’s labour markets. In this context, labour policies have become relevant as tools for economic reactivation and, in particular, for labour inclusion. Among other aims, labour inclusion policies seek to reduce unemployment and withdrawals from the labour force. They also strive to coordinate responses to broader problems, such as women’s labour participation, professional mobility, employment protection and the support needed to cope with technological transformations (ECLAC, 2021a).

This section returns to the work reported in previous editions of Social Panorama of Latin America (ECLAC, 2019a and 2022a), in relation to public spending on labour market policies and programmes in 15 of the region’s countries, for which comparable data are available at the central government level.[20] In these countries, public expenditure on labour market policies is estimated as averaging 0.42% of GDP in 2022, down by 0.06 percentage points from 2021 and a cumulative drop of 0.55 points since 2020.

At the country level, the general trend in recent years shows that spending on labour market policies returned to their pre-pandemic levels, except in Argentina, Chile, Costa Rica and Ecuador, where expenditure levels have remained higher than in 2019. Within this framework, the countries with the highest proportion of spending as a percentage of GDP in 2022 were Brazil, Chile and Ecuador, with amounts exceeding 0.7% of GDP.

In the following paragraphs, the available information is analysed from an institutional perspective, classifying labour market programmes according to the agency that executes the resources: ministries, other central government entities or decentralized institutions. The analysis is complemented on the basis of the destination of expenditure, based on the classification of the European Commission (2018), which was used in Social Panorama of Latin America, 2021 (ECLAC, 2022a).

1. Public spending on labour inclusion policies: an institutional perspective

The study of the entities that executed expenditure on labour inclusion policies in the region in 2022 shows that the largest share of funding was disbursed by ministries of labour, ministries of social development and decentralized training institutions. These three institutions executed 73% of spending on labour policies in the countries (representing 0.15%, 0.10% and 0.06% of GDP, respectively), so that overall they maintained levels similar to those of previous years, except in 2020 (see figure IV.19).

The ministries of economy or finance, which played a preponderant role in funding labour policies, in response to the labour market impact of the COVID-19 pandemic, have cut back sharply on expenditure in the last two years, from an average of 0.32% of GDP in 2020 to 0.01% in 2022.

The distribution of expenditure differs when the situation is analysed by subregion. Among the South American countries, the largest proportion of spending is executed by the ministries of labour and of social development, which accounted for 57% of these resources in 2022. The remaining expenditure is distributed heterogeneously, mainly among ministries of agriculture, decentralized training institutions and other government agencies, such as the Office of the President. In contrast, in the Central American countries, plus the Dominican Republic and Mexico, the largest share of expenditure was executed by decentralized training institutions, which accounted for 37% of the total in 2022, followed by ministries of agriculture, which accounted for 22%. In third place, in terms of proportion, are the ministries of labour, which accounted for an average of 21% of total spending (see figure IV.20).

Figure IV.19

Latin America (15 countries): public expenditure on labour inclusion policies, by executing entity, 2018–2022

(Percentages of GDP)

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

Note: The figures shown represent the simple average of the following Latin American countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Panama, Paraguay, Peru and Uruguay.

Figure IV.20

Latin America (15 countries): public expenditure on labour inclusion policies by ministry, 2018–2022

(Percentages of the total)

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

Note: South America includes Argentina, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru and Uruguay. Central America includes Costa Rica, Dominican Republic, El Salvador, Guatemala, Honduras, Mexico and Panama.

2. Public expenditure on the different types of labour inclusion policies

The 15 countries analysed display a relatively stable distribution of public expenditure across the eight types of labour inclusion programmes that receive funding, namely: (i) job placement services; (ii) vocational training; (iii) work incentives; (iv) protected and supported employment; (v) direct job creation; (vi) incentives for entrepreneurship; (vii) income support in situations of unemployment; and (viii) early retirement. In 2022, vocational training programmes absorbed the largest share of resources, averaging 0.11% of GDP, followed very closely by income support in situations of unemployment, at 0.10% of GDP (see figure IV.21).

A second tier of expenditure relative to GDP comprises programmes of work incentives (0.09%), entrepreneurship incentives (0.07%) and direct job creation (0.05%). Prior to the COVID-19 pandemic, expenditure on labour incentive and direct job creation programmes represented about 0.01% of GDP.

Comparing the different countries, the distribution between the categories varies widely. Two major country groupings can be distinguished: those that focus most of their expenditure on training programmes and incentives for entrepreneurship, such as Colombia, Costa Rica, the Dominican Republic, El Salvador, Guatemala, Honduras, Panama and Paraguay; and those that mainly target labour incentives or unemployment income support, such as Argentina, Brazil, Chile, Ecuador and Uruguay (see figure IV.22).

Figure IV.21

Latin America (15 countries): public expenditure on labour inclusion policies by type of programme, 2014–2022

(Percentages of GDP)

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

Note: The figures shown correspond to the arithmetic mean of the following Latin American countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Panama, Paraguay, Peru and Uruguay.

Figure IV.22

Latin America (15 countries) and Europe (25 countries):a distribution of public expenditure on labour inclusion policies, by programme type, 2022

(Percentages of the total)

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

a Europe (25 countries) includes Austria, Belgium, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Hungary, Italy, Kingdom of the Netherlands, Latvia, Lithuania, Luxembourg, Malta, Norway, Poland, Portugal, Slovakia, Slovenia, Spain and Sweden. The data for European countries refer to 2021.

A case in point is Mexico, which in recent years has shifted from concentrating its expenditure on incentives for entrepreneurship to dividing it between direct job creation and labour incentives. The main effects have been increased spending on the Sembrando Vida programme for sustainable communities and the creation, in 2019, of the Jóvenes Construyendo el Futuro programme for youth. In addition, initiatives such as Programa de Apoyos a Pequeños Productores to support small-scale producers were closed down, and expenditure on the Fondo Nacional Emprendedor fund for entrepreneurship was pared back.

Another country in which the distribution of spending on labour market policies has changed significantly is Argentina, which displays great variability over the years. In 2022, there was a significant increase in expenditure on direct job creation, associated with the major expansion registered in the Potenciar Trabajo work training programme.

Peru has also experienced changes in recent years. Whereas it used to target its spending on entrepreneurship incentives and vocational training programmes, now it is focusing on reducing expenditure on the former and increasing it in the labour incentives category, through its Recuperemos el Empleo Formal programme to boost formal employment.

A comparison of the situation of these 15 Latin American countries with the 25 in Europe reveals major differences between the two regions in the distribution of spending on labour market policies. While among the European countries, income support programmes for the unemployed are the main category, followed by intermediation services, in most Latin American countries these categories are relatively marginal.

D. Closing remarks

The consequences of the COVID-19 pandemic and the economic slowdown had a major impact on labour markets and work (both paid and unpaid) in Latin America and the Caribbean. The crisis has caused most economic indicators to deteriorate, with regional growth levels of 3.8% in 2022 and 1.7% in 2023 and estimates of around 1.5% for 2024 (ECLAC, 2023b). While labour markets have staged a recovery since the pandemic, the ongoing global instability and recent inflationary forces have continued to have a major impact on the region’s working population. Historically marginalized or at-risk populations have been affected disproportionately.

The information analysed in this chapter shows that, in attempting to cope with the impacts and vulnerabilities generated by this context of cascading crisis, the region’s countries have made progress and also faced major challenges in relation to the institutional framework for social policy. Positive developments include high levels of ratification or accession to the most important international treaties and regional agreements on inclusive social development, particularly the main global- and regional-scope treaties on economic, social, cultural and environmental rights. Nonetheless, challenges persist in terms of the way in which these instruments are reflected in national legislation and their comprehensive implementation. Ministries of social development are also playing an increasing role as social authorities, despite their recent creation and the institutional instability that has occurred in some countries. The need to advance in the harmonization of their mandates is another challenge. These are central to inclusive social development, but they have multiple functions to assume and priority groups to serve; and they do not always have sufficient organizational capacity and technological, personnel and financial resources for their implementation.

In addition to the above, there are challenges and opportunities in terms of coordination and harmonization from the central to the territorial level. In this regard, various single-window modalities are being developed in the different countries, accompanied by an ever-greater strengthening of information systems for decision-making, social and administrative records, and monitoring and evaluation systems. In these areas, the various ministries have different levels of technological development and data interoperability, as well as institutionalization in specialized organizational units. Thus, while major challenges persist, there are also ample opportunities arising from the current technological revolution, the capacity to manage large databases and the automation of processes.

Social development ministries are also playing a key role in relation to labour inclusion. Along with ministries of labour, they are the chief responsible entities and executing agencies of programmes in this field, which is an institutional manifestation of the link between social and labour market inclusion in the region. The institutional framework of labour inspection is a central component of labour inclusion policies, especially in the context of the changes unfolding in the world of work, alongside new technologies and automation. In this area, the emphasis is on the need to make legislative progress and on the challenge of expanding interaction between these entities and the social protection systems, in order to increase synergies in support of decent work, guaranteeing basic levels of social protection and well-being for workers, reducing informality and increasing women’s participation in the labour market.

In relation to social spending, the information available in the region reveals a reversal in the expansion of central government social spending since 2020. In both the Latin American countries and the five Caribbean countries for which comparable data are available, much of the growth in expenditure to address the social consequences of the COVID-19 pandemic has been reversed. There have been negative growth rates in most countries and, therefore, less funding available per person to finance social policies. This is particularly true in the case of social protection and education policies. While these remain the functions with the highest level of spending, they have dropped back to levels similar to those of 2019, both relative to GDP and in absolute terms. Expenditure levels continue to vary significantly between countries. These differences are particularly important in countries which, along with greater poverty and social inclusion challenges, have fewer resources to finance their social policies.

The data presented in this chapter also show that countries have reduced their expenditure on labour policies and have regressed to pre-pandemic levels, as large-scale emergency programmes have been shelved. In this context, there has been a change in the greater funding currently allocated to labour incentive and direct job creation programmes, the results of which will have to be evaluated in the coming years.

Work is the main income source for households living in poverty and vulnerability, so making progress in terms of social protection systems and labour inclusion policies is a priority challenge for achieving the Sustainable Development Goals (SDGs), with no one left behind. The characteristics of the social inequality matrix in the region and the emerging critical issues for social inclusion, such as those arising from climate change, migrations, ageing, crises arising from global conflicts (such as the war in Ukraine) and a high level of public debt in many of the region’s countries, make this all the more important. As ECLAC has noted in previous editions of Social Panorama, it is important to strengthen social policy institutions with appropriate legislation, consolidated organizational capacities, effective and efficient management models, integrated information systems and the financial capacity to make the design and implementation of social policies viable. In particular, there is an ongoing need to seek levels of financial sufficiency and sustainability that will enable new substantive leaps forward in the region and make it possible to regain the global path laid out in the 2030 Agenda for Sustainable Development, reaffirmed by the region’s countries in the Regional Agenda for Inclusive Social Development (ECLAC, 2019a).

Bibliography

Barrientos, A. and D. Hulme (eds.) (2008), Social Protection for the Poor and Poorest: Concepts, Policies and Politics, Oxford, Palgrave Macmillan.

Cecchini, S. and R. Martínez (2011), Inclusive Social Protection in Latin America: a comprehensive, rights-based approach, ECLAC Books, Nº 111 (LC/G.2488-P), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Contreras, M. (2023), “Nuevas formas de trabajo e institucionalidad laboral en Latin America”, Automatización e inclusión laboral en Latin America: impactos potenciales, vulnerabilidades y propuestas de política pública, Project Documents (LC/TS.2023/112), R. Martínez (coord.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Costa Rica, Government of (2017), Constitución Política de la República de Costa Rica, San José, Imprenta Nacional.

Cunill-Grau, N., F. Repetto and C. Bronzo (2015), “Coordinating sectors and institutions for building comprehensive social protection”, Towards universal social protection: Latin American pathways and policy tools, ECLAC Books, No. 136 (LC/G.2644-P), S. Cecchini and others (eds.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

ECLAC (Economic Commission for Latin America and the Caribbean) (2023a), Institutional Frameworks for Social Policy in Latin America and the Caribbean: a Central Element in Advancing towards Inclusive Social Development (LC/CDS.5/3), Santiago.

____(2023b), Economic Survey of Latin America and the Caribbean, 2023 (LC/PUB.2023/11-P), Santiago.

____(2022a), Social Panorama of Latin America and the Caribbean, 2021 (LC/PUB.2021/17-P), Santiago.

____(2022b), Preliminary Overview of the Economies of Latin America and the Caribbean, 2021 (LC/PUB.2022/1-P), Santiago.

____(2022c), Fiscal Panorama of Latin America and the Caribbean, 2022 (LC/PUB.2022/7-P), Santiago.

____(2022d), Economic Survey of Latin America and the Caribbean, 2022 (LC/PUB.2022/9-P), Santiago.

____(2022e), Social Panorama of Latin America and the Caribbean, 2022 (LC/PUB.2022/15-P), Santiago.

____(2021a), Disasters and inequality in a protracted crisis: towards universal, comprehensive, resilient and sustainable social protection systems in Latin America and the Caribbean (LC/CDS.4/3), Santiago.

____(2021b), Social Panorama of Latin America and the Caribbean, 2020 (LC/PUB.2021/2-P/Rev.1), Santiago.

____(2021c), Economic Survey of Latin America and the Caribbean, 2021 (LC/PUB.2021/10-P/Rev.1), Santiago.

____(2020), Regional Agenda for Inclusive Social Development (LC/CDS.3/5), Santiago.

____(2019a), Social Panorama of Latin America and the Caribbean, 2019 (LC/PUB.2019/22-P/Rev.1), Santiago.

____(2019b), Social Panorama of Latin America and the Caribbean, 2018 (LC/PUB.2019/3-P), Santiago.

____(2017), Social Panorama of Latin America and the Caribbean, 2016 (LC/PUB.2017/12-P), Santiago.

____(2016), Social Panorama of Latin America and the Caribbean, 2015 (LC/G.2691-P), Santiago

____(2015), Inclusive social development: the next generation of policies for overcoming poverty and reducing inequality in Latin America and the Caribbean (LC.L/4056(CDS.1/3)), Santiago.

ECLAC/ILO (Economic Commission for Latin America and the Caribbean/International Labour Organization) (2021), “Decent work for platform workers in Latin America”, Employment Situation in Latin America and the Caribbean, No. 24 (LC/TS.2021/71), Santiago.

____(2020), “Work in times of pandemic: the challenges of the coronavirus disease (COVID-19)”, Employment Situation in Latin America and the Caribbean, No. 22 (LC/TS.2020/46), Santiago.

____(2014), “Conditional transfer programmes and the labour market”, Employment Situation in Latin America and the Caribbean, No. 10 (LC/L.3815), Santiago.

ECLAC/OEI (Economic Commission for Latin America and the Caribbean/Organization of Iberoamerican States for Education, Science and Culture) (2014), Cultura y desarrollo económico en Iberoamérica, E. Espíndola (coord.), Madrid.

Egaña del Sol, P. and others (2022), “Futuro del trabajo: desafíos para el futuro del trabajo en Chile”, Chile tiene futuro desde sus territorios, G. Girardi and others (eds.), Santiago, Ediciones Biblioteca del Congreso Nacional de Chile.

Espejo, A. (2022), “Informalidad laboral en Latin America: propuesta metodológica para su identificación a nivel subnacional”, Project Documents (LC/TS.2022/6), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

European Commission (2018), Labour Market Policy Statistics: Methodology 2018, Brussels.

Gajardo, M. (2020), “Desarrollo educativo en Latin America. Tendencias globales. Desafíos regionales”, Documento de Trabajo, Santiago, Latin American Faculty of Social Sciences (FLACSO).

GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit) (2017), Ventanilla Única de Servicios para la Protección Social, Bonn.

Huepe, M. (ed.) (2023), Desigualdades, inclusión laboral y futuro del trabajo en Latin America (LC/TS.2023/63), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Huepe, M., A. Palma and D. Trucco (2022), “Education during the pandemic: an opportunity to transform education systems in Latin America and the Caribbean”, Social Policy series, No. 243 (LC/TS.2022/149), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

ILO (International Labour Organization) (2019), Work for a Brighter Future, Geneva.

IMF (International Monetary Fund) (2014), Government Finance Statistics Manual 2014, Washington, D.C.

____(2001), Government Finance Statistics Manual 2001, Washington, D.C.

Infante, R. (2018), “Crecimiento, cambio estructural y formalización”, Políticas de formalización en Latin America: avances y desafíos, J. Salazar-Xirinachs and J. Chacaltana (eds.), Lima, International Monetary Fund (IMF).

Izquierdo, A., C. Pessino and G. Vuletin (eds.) (2018), “Making spending count in education”, Better spending for better lives: how Latin America and the Caribbean can do more with less, Washington, D.C., Inter-American Development Bank (IDB).

Martínez, R. (coord.) (2023), “Automatización e inclusión laboral en Latin America: impactos potenciales, vulnerabilidades y propuestas de política pública”, Project Documents (LC/TS.2023/112), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

____(ed.) (2019), Institutional frameworks for social policy in Latin America and the Caribbean, ECLAC Books, N° 146 (LC/PUB.2017/14-P/Rev.1), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Martínez, R. and C. Maldonado (2019), “Institutional framework for social development”, Institutional frameworks for social policy in Latin America and the Caribbean, ECLAC Books, N° 146 (LC/PUB.2017/14-P/Rev.1), R. Martínez (ed.), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Martínez, R. and others (2022), “Estratificación y clases sociales en Latin America: dinámicas y características en las dos primeras décadas del siglo XXI”, Project Documents (LC/TS.2022/214), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Ministry of Social Development and Family (2021), “Informe Ingreso Familiar de Emergencia”, Santiago, November [online] https://www.desarrollosocialyfamilia.gob.cl/informacion-social/informe-ingreso-familiar-de-emergencia/descargar-informes-de-ingreso-familiar-de-emergencia.

OECD (Organisation for Economic Co-operation and Development) (2021), OECD Employment Outlook 2021: Navigating the COVID-19 Crisis and Recovery, Paris.

PAHO (Pan American Health Organization) (2014), Strategy for Universal Access to Health and Universal Health Coverage, Washington, D.C.

Rivas, F. (2021), El financiamiento de la educación en Latin America: investigaciones y estudios 2013-2019, Buenos Aires, United Nations Educational, Scientific and Cultural Organization (UNESCO).

Samaniego, N. (2002), “Las políticas de mercado de trabajo y su evaluación en Latin America”, Macroeconomics of Development series, No. 19 (LC/L.1836-P), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

UNESCO (United Nations Educational, Scientific and Cultural Organization) (2021), The RewirEd Global Declaration on Connectivity for Education, Paris.

____(2020), “Act now: reduce the impact of COVID-19 on the cost of achieving SDG 4”, Policy Paper, No. 42, Paris.

UNESCO and others (United Nations Educational, Scientific and Cultural Organization and others) (2016), Education 2030: Incheon Declaration and Framework for Action for the implementation of Sustainable Development Goal 4: Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all, Paris.

United Nations (2001), “Classifications of expenditure according to purpose”, Statistical Papers, series M, No. 84 (ST/ESA/STAT/SER.M/84), New York.

Velásquez, M. (2016), “Regulación del mercado de trabajo y protección social en países de Latin America”, Social Policy series, No. 218 (LC/L.4244), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC).

Annex IV.A1

Table IV.A1.1

Latin America and the Caribbean (24 countries): central government social expenditure, by function, 2021–2022

Country

Social spending

Distribution of social spending by function, 2022

(Percentages)

(Percentages of GDP)

(Dollars per capita at constant 2018 prices)

2021

2022

2021

2022

Social protection

Education

Health

Housing and community services

Recreation, culture and religion

Environmental protectiona

Total

Argentina

14.7

13.5

1 666

1 606

79.8

9.5

6.2

3.8

0.0

0.6

100

Bahamas

15.1

10.4

3 549

3 113

24.0

25.5

36.0

0.4

2.2

12.0

100

Barbados

17.1

14.6

2 806

2 597

27.1

34.1

19.7

11.0

4.7

3.4

100

Bolivia (Plur. State of)b

14.5

…

478

…

29.3

43.5

24.3

2.9

0.0

0.0

100

Brazil

16.3

16.4

1 501

1 546

76.5

12.0

10.8

0.3

0.1

0.2

100

Chile

24.8

17.9

3 977

2 924

40.6

26.2

29.7

1.9

1.1

0.5

100

Colombia

14.8

11.6

1 018

856

44.4

24.2

27.5

2.0

1.2

0.7

100

Costa Rica

11.6

10.5

1 489

1 390

34.2

54.3

6.8

2.6

1.1

1.0

100

Cuba

10.1

…

1 000

…

70.9

17.4

5.9

1.4

4.3

0.0

100

Dominican Rep.

8.9

8.6

751

752

24.1

43.6

21.9

7.3

1.6

1.4

100

Ecuador

11.0

11.0

639

649

42.3

32.0

23.4

0.8

0.9

0.6

100

El Salvador

12.3

10.8

531

478

33.0

35.1

28.4

0.9

2.2

0.4

100

Guatemala

7.6

7.7

350

365

16.9

41.4

19.0

17.8

2.1

2.8

100

Guyana

11.3

7.7

1 159

1 394

16.0

28.3

30.6

21.3

2.4

1.3

100

Haitic

3.0

…

42

…

11.0

56.8

16.1

0.9

8.7

6.4

100

Honduras

9.9

7.8

244

198

6.5

57.1

33.8

0.9

0.6

1.1

100

Jamaica

11.5

12.2

641

659

8.0

44.5

39.7

4.1

1.5

2.1

100

Mexico

10.0

10.2

930

966

46.9

30.4

11.6

9.6

0.8

0.7

100

Nicaragua

12.0

10.6

240

216

8.2

35.9

39.9

12.8

2.1

1.1

100

Panamá

11.4

…

1 441

…

8.1

38.1

31.9

18.0

1.6

2.3

100

Paraguay

10.1

9.7

620

592

36.1

32.4

25.9

2.2

2.1

1.3

100

Perud

12.2

11.5

844

801

25.9

33.1

26.2

8.2

2.9

3.8

100

Trinidad

and Tobago

14.1

12.8

1 986

1 961

40.5

24.1

23.3

10.3

1.9

0.0

100

Uruguaye

15.1

12.9

2 860

2 561

41.9

33.7

18.5

4.3

1.2

0.5

100

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

a Data on environmental protection may not coincide with estimates of environmental satellite accounts.

b Coverage corresponds to central government.

c Data are for 2014.

d Coverage corresponds to general government.

e Data do not include expenditures by the Social Security Bank (BPS).

Table IV.A1.2

Latin America (12 countries): social spending of broader institutional coverage than central government, by function, 2022

Country

Coverage

Public social spending

Distribution of public social spending by function, 2022

(Percentages)

(Percentages of GDP)

(Dollars per capita at constant 2018 prices)

Social protection

Education

Health

Housing and community services

Recreation, culture

and religion

Environmental protectiona

Total

Argentinab

Public sector

32.1

3 328

54.2

16.3

21.9

7.1

0.6

0.0

100

Bolivia (Plur. State of)c

General government

19.6

697

22.8

41.7

25.7

3.9

1.8

4.1

100

Brazil

General Government

28.3

2 583

54.5

18.1

21.4

3.8

0.6

1.6

100

Colombia

General Government

21.8

1 507

45.5

18.2

28.3

2.6

2.8

2.5

100

Costa Rica

General Government

20.2

2 588

39.8

27.1

27.3

1.9

0.8

3.1

100

Cubab

General government

36.3

2 850

24.8

31.8

33.5

3.2

6.7

0.0

100

Dominican Republicd

General government

7.8

654

20.8

51.7

19.4

2.8

2.3

3.0

100

El Salvador

General government

17.8

738

32.5

26.1

20.5

19.7

0.9

0.3

100

Guatemala

General government

9.5

420

26.5

34.7

25.9

6.2

2.9

3.8

...

Mexico

Non-financial public sector (federal)

15.0

1 347

53.5

21.3

17.7

6.5

0.6

0.4

100

Paraguay

General government

14.8

839

38.2

27.7

30.4

1.9

0.6

1.3

100

Peru

General government

12.3

854

30.1

30.9

25.3

3.8

1.7

8.3

100

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries.

a Data on environmental protection may not coincide with estimates of environmental satellite accounts.

b Data are for 2020.

c Data are for 2018.

d Data are for 2019.

1. [1] Ministries, national secretariats and institutes dealing with women’s issues or gender equality.

2. [2] For further details on labour programmes, see chapter II.

3. [3] Social investment funds may be sectorized as autonomous entities within ministries of social development.

4. [4] Examples include Mexico, with respect to amendments to the Federal Labour Law, and Argentina, which regulates teleworking through Law No. 27.555. For more detailed information, see Martínez (2023).

5. [5] This refers to the five Caribbean countries that publish information on functional expenditure. In contrast, the total central government expenditure published in the Economic Survey of Latin America and the Caribbean, 2023 (ECLAC, 2023b) considers 12 Caribbean countries.

6. [6] In some countries, this situation is explained by the large burden of interest payments —particularly in the case of Jamaica.

7. [7] Section B.4 discusses the magnitude of public social spending in OECD countries. For further information see Organisation for Economic Co-operation and Development (OECD), OECD.Stat [online database] https://stats.oecd.org/.

8. [8] The Bolivarian Republic of Venezuela and Haiti are not included owing to a lack of information.

9. [9] Expenditure associated with survivors represents social protection in the form of cash and in-kind entitlements to the descendants (in other words, the survivors) of a deceased person (such as spouse, former spouse, children, grandchildren, parents and other relatives).

10. [10] Expenditure associated with housing corresponding to this function refers to support to facilitate access to housing and includes: “provision of social protection in the form of entitlements in kind to help households meet the cost of housing (recipients of these entitlements are means-tested); Administration, operation, or support of such social protection schemes; Entitlements in kind, such as payments made on a temporary or long-term basis to help tenants with rent costs, payments to alleviate the current housing costs of owner-occupiers (which is to say, to help with paying mortgages or interest), and provision of low-cost or social housing” (IMF, 2014, p. 170).

11. [11] Such as the economic and social crisis caused by the COVID-19 pandemic. For a detailed analysis, see ECLAC (2022a), chapter III, section B.

12. [12] Information for 2020.

13. [13] Article 78 of the Political Constitution of Costa Rica provides that: public expenditure on state education, including higher education, shall not be less than 8% of gross domestic product per year, in accordance with the law, without prejudice to the provisions of Articles 84and 85 of this Constitution (Government of Costa Rica, 2017, p. 21).

14. [14] The countries mentioned attain the target when considering total central government expenditure. This does not exclude other countries that may meet the target when considering the distribution of total general government expenditure.

15. [15] For further details on this topic, see Economic Commission for Latin America and the Caribbean (ECLAC), “Regional Network of Environment and Climate Change Statistics” [online] https://comunidades.cepal.org/estadisticas-ambientales/en.

16. [16] In addition to the aforementioned countries, Cuba and the Plurinational State of Bolivia have data up to 2020. To obtain data series with a coverage greater than central government, a major effort is needed to consolidate public finances between different levels of government. For this reason, information is not available for all countries and, in some cases, the year of analysis differs. In the case of Peru, the series is the same as mentioned above, since data are only available for general government coverage.

17. [17] Central government data may include transfers to subnational entities that are then executed within public policies. For this reason, when consolidating total expenditure in the broader coverage, these items do not imply higher spending. The differences in amounts between the two coverages do not necessarily reflect all expenditure executed by subnational governments, public enterprises or other entities, but only indicate the aggregate amount.

18. [18] Peru only provides information at the general government level, which has already been considered in previous analyses, so no new description is included in this section.

19. [19] Mexico’s institutional coverage encompasses central government, social security institutions and State enterprises. It does not include incremental expenditures produced in subnational governments.

20. [20] The countries included are Argentina, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Panama, Paraguay, Peru and Uruguay.

Table of Contents

Maintitle

Copyrights

Contents

Introduction

Chapter I

Income inequality and poverty and their links to labour inclusion

Chapter II

From access to inclusion: key considerations for reducing inequality and informality in the labour market

Chapter III

Labour inclusion amid the challenges of gender equality in care work and international migration in the region

Chapter IV

Institutional frameworks and social spending: challenges for labour inclusion