Maintitle

Copyright

Alicia Bárcena

Executive Secretary

Mario Cimoli

Deputy Executive Secretary

Raúl García-Buchaca

Deputy Executive Secretary

for Management and Programme Analysis

Simone Cecchini

Officer in Charge, Social Development Division

Rolando Ocampo

Chief, Statistics Division

Paulo Saad

Chief, Latin American and Caribbean Demographic Centre

(CELADE)-Population Division of ECLAC

Ana Güezmes

Chief, Division for Gender Affairs

Sally Shaw

Officer in Charge, Documents and Publications Division

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

The preparation of the 2020 edition was coordinated by Simone Cecchini, who also worked on the drafting together with Bernardo Atuesta, Helena Cruz Castanheira, Fabiana Del Popolo, Ernesto Espíndola, Álvaro Fuentes, Raúl Holz, Carlos Maldonado Valera, Xavier Mancero, María Luisa Marinho, Rodrigo Martínez, Beatriz Morales, Claudia Robles, Jorge Rodríguez, Lucía Scuro, Zulma Sosa, Varinia Tromben, Daniela Trucco, Heidi Ullmann and Iliana Vaca Trigo. Camilo Acuña, Mario Acuña, Nicole Araya, Bernardo Atuesta, Amparo Bravo, José Henrique Costa Monteiro da Silva, Claudia de Camino, Federico Dorin, Marta Duda-Nyczak, Ernesto Espíndola, Consuelo Farías, Fabiola Fernández, Álvaro Fuentes, Carlos Howes, Carlos Kroll, Felipe López, Isabel Loyola, Maria Maroso, Alexandra Martínez, Vivian Milosavljevic, Rocío Miranda, Beatriz Morales, Francisca Orellana, Daniel Pailañir, Amalia Palma, Martha Tovar, Daniel Valencia and Carolina Zúñiga worked on the data collection and statistical processing. Valuable contributions and comments relating to different sections of the document were received from Alberto Arenas de Mesa, Catarina Camarinhas, Verónica Cano, Catalina Cea, José Henrique Costa Monteiro da Silva, Catalina de la Cruz, Miguel del Castillo Negrete, Sonia Gontero, Daniela González, Jorge Martínez, Carolina Miranda, Javiera Muñoz, Malva-marina Pedrero, Leandro Reboiras, Humberto Soto, Soledad Villafañe, Fernando Villanueva, Pablo Villatoro, Jürgen Weller and Pablo Yanes.

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. 2013/2014) 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.

United Nations publication

ISBN: 978-92-1-122069-8 (print)

ISBN: 978-92-1-004759-3 (pdf)

ISBN: 978-92-1-358304-3 (ePub)

Sales No.: E.20.II.G.5

LC/PUB.2021/2-P

Distribution: G

Copyright © United Nations, 2021

All rights reserved

Printed at United Nations, Santiago

S.20-00149

This publication should be cited as: Economic Commission for Latin America and the Caribbean (ECLAC), Social Panorama of Latin America, 2020 (LC/PUB.2021/2-P), Santiago, 2021.

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

Copyright

Introduction

Chapter I

Poverty and inequality: recent trends and expected impacts of the coronavirus disease (COVID-19) pandemic

Chapter II

Labour market: structural gaps during the pandemic

Chapter III

Social protection in response to COVID-19: pre-existing gaps and emerging responses

Chapter IV

Recent social spending trends and commitments in terms of emergency social protection

Chapter V

The care economy: a sector of strategic importance for reactivation with equality

Chapter VI

Social unrest: keys for a new social compact

Introduction

A. Risk factors: urbanization and metropolitanization, overcrowding and lack of access to basic services

B. The weakness of health systems and the multiple effects on the health of the population

C. School closures, distance learning and the digital divide

D. Increasing poverty and inequality

E. Deterioration of labour indicators

F. Social protection gaps and responses

G. Increased public social spending and emergency spending

H. The care economy as a strategic sector for reactivation with equality

I. Social unrest in highly unequal societies

J. Social policy scenarios and recommendations for a transformative recovery with equality

Bibliography

This edition of the Social Panorama of Latin America examines the social impact of an unprecedented crisis. The effects of the coronavirus disease (COVID-19) pandemic have spread to all areas of human life, altering the way we interact, crippling economies and bringing about profound changes in societies. The pandemic has highlighted and exacerbated the major structural gaps in the region, and “[t]imes are highly uncertain, with clarity on neither the route out of the crisis nor the speed at which it may be achieved” (ECLAC, 2020h, p. 13). It is clear that the costs of inequality have become unsustainable and that it is necessary to rebuild with equality and sustainability, aiming for the creation of a true welfare state, long overdue in the region (ECLAC, 2020h).

This document analyses the social trends that preceded the pandemic and seeks to measure its socioeconomic impacts in 2020, especially with regard to poverty and inequality, along with paid and unpaid work. It also examines public social spending trends in the countries of the region, the social protection measures adopted by the governments of Latin America and the Caribbean in response to the effects of the pandemic and the social unrest in the region prior to the crisis. In view of the unequal effects of the pandemic on women and men, there is also a call to invest in the care economy as a strategic sector for reactivation with equality.

On 30 January 2020, the World Health Organization (WHO) declared COVID-19 a public health emergency of international concern. The first case in the region was detected in Brazil on 25 February 2020 and, following the reporting of cases that reflected community transmission on all continents, WHO declared on 11 March that the COVID-19 outbreak could be characterized as a pandemic. Although the pandemic is constantly evolving, the available data show that Latin America and the Caribbean has been one of the regions hit hardest by the coronavirus, in terms of both the number of cases and the number of deaths. Despite the fact that the region was home to just 8.4% of the world’s population in 2020, it accounted for 18.6% of cumulative COVID-19 infections and 27.8% of COVID-19 deaths as of December 2020.[1]

The countries of Latin America and the Caribbean face challenges on several fronts to control the pandemic. The spread of COVID-19 and its economic and social effects are exacerbated by the region’s structural problems: primarily, high levels of inequality, labour informality, lack of social protection, poverty and vulnerability. The region is also characterized by weak and fragmented health and social protection systems and growing marginalized urban settlements that lack access to basic services. In addition, it is affected by considerable migratory flows and population displacement, as well as conflicts of various kinds, and suffers disproportionately from the consequences of the climate crisis.

COVID-19 emerged in a region marked by a social inequality matrix structured by axes such as socioeconomic stratum, gender, life cycle stage, ethnicity or race, territory, disability and migratory status. These give rise to multiple, often simultaneous, scenarios of exclusion and discrimination that lead to greater vulnerability to the health, social and economic effects of the disease. In terms of health, these inequalities are manifested in coverage, effective access, health service performance, and the basic health conditions of people and communities (ECLAC/PAHO, 2020). However, they are often obscured by problems relating to data availability. For example, in Latin America and the Caribbean, only Brazil and Colombia report confirmed cases and deaths from COVID-19 among people of African descent.[2] Shedding light on inequality and factoring it into the pandemic response is key. In the current context, and from the perspective of the social determinants of health, the deterioration in the economic conditions of households, with the resulting increase in food insecurity (FAO/ECLAC, 2020), could give rise to a vicious circle of poverty and poor health for large swathes of the population, which will have long-term repercussions on societies. In particular, in times of crisis, social protection deficiencies can have a catastrophic impact on the comprehensive development of children and adolescents, with critical impacts on the exercise of their rights and human capacity development. Although children, adolescents and young people are not the most affected by the disease in terms of health, they may end up being among the biggest victims of the crisis, owing to the effects of the temporary closure of schools and the socioeconomic crisis affecting their households.

The effects of the pandemic on the population’s living conditions are compounded by the gradual increase in poverty and extreme poverty and the slowdown in the reduction of inequality in the five years prior to the coronavirus crisis. Despite the progress made in the reduction of poverty and inequality and the expansion of the middle-income strata between 2002 and 2014, the region’s economic and social progress was already showing clear signs of stagnation before the pandemic, and public discontent was growing. From 2014 to 2019, GDP for Latin America and the Caribbean rose by an average of just 0.3% per year (ECLAC, 2020a). In Latin America, the percentage of extreme poverty increased from 7.8% to 11.3% of the population and that of poverty rose from 27.8% to 30.5% (see figure 1). Similarly, the reduction in the Gini coefficient had slowed from an average of 1.1% per year from 2002–2014 to 0.5% per year from 2014–2019. Moreover, from the end of 2019, citizens of several countries had expressed their unease, discontent and dissatisfaction with the political system and its players in large protests in which they demanded greater social justice.

It is also important to recognize the specific challenges facing the countries of the Caribbean. Before the pandemic, these countries had high levels of public debt owing to their need for financing to recover and rebuild their production structures in the face of recurrent climate disasters, which has limited their fiscal capacity to respond to the pandemic (ECLAC, 2020d). The knock-on effects of the pandemic in the tourism sector, relating to employment, household income and government revenue, are greatest in the Caribbean, where the sector employs some 2.4 million people and accounts for 15.5% of GDP. This is compounded by heavy dependence on imported food and other goods, which threatens supply chains in these countries (ECLAC/PAHO, 2020).

Figure 1

Latin America (18 countries):a poverty and extreme poverty, 1990–2020

(Percentages and millions of people)

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

a Weighted average for 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, Plurinational State of Bolivia and Uruguay.

b The figures for 2020 correspond to projections that take into account the effect of emergency transfer programmes.

In 2020, projections relating to economic and social indicators in Latin America and the Caribbean outline a very complex scenario, linked to both internal and external factors. In order to curb the spread of the coronavirus, prevent health systems from being overwhelmed and reduce human losses, governments have adopted quarantine and physical distancing measures. In many cases the population has been confined to their homes as a way of minimizing contact, especially at close range or in closed environments, which has been shown to increase the likelihood of contracting the virus (ECLAC, 2020b). Thus, entire sectors of the economy have had their activity curtailed or temporarily reduced to zero as a result of the measures taken. Moreover, demand for the region’s exports has dropped sharply because of the adoption of similar measures in the rest of the world. As a result, ECLAC has estimated that the GDP of the economies of Latin America and the Caribbean as a whole will fall by 7.7%, and that the unemployment rate will rise by 2.6 percentage points (ECLAC, 2020a). This severe economic recession implies a worsening of living conditions, with substantial increases in unemployment, poverty and inequalities.

What follows is the discussion of three issues that must be examined in order to understand the development of the pandemic in the region: the risk factors linked to urbanization and metropolitanization, and their effects on health and education. Subsequently, the main findings of this edition of the Social Panorama of Latin America are presented with respect to poverty and inequality, the labour market, social protection, social spending, the care economy and social unrest. Finally, the main public policy messages of this report are outlined.

A. Risk factors: urbanization and metropolitanization, overcrowding and lack of access to basic services

In Latin America and the Caribbean, 81% of the population lives in areas classified as urban according to national definitions, making it the most urbanized developing region in the world (United Nations, 2019a).[3] The region also stands out for its metropolitanization, as 35% of the population lives in cities of 1 million or more inhabitants and there are five megacities with 10 million or more inhabitants (Buenos Aires, Mexico City, Lima, Rio de Janeiro and São Paulo) (United Nations, 2019a; ECLAC, 2020f). This is an important risk factor, because COVID-19 spreads more rapidly in densely populated areas such as urban and metropolitan areas. As of July 2020, it was estimated that urban areas accounted for more than 90% of reported cases of coronavirus worldwide (United Nations, 2020a).

The region’s metropolitan areas reflect a pattern of overconcentration of COVID-19 infections and deaths, although there are exceptions. Figure 2 shows the overconcentration of infections and deaths in major administrative divisions, where the most populated cities in Latin America are located. This is especially the case in countries where 30% or more of the population lives in major administrative divisions —such as Argentina, Chile, Costa Rica, Guatemala, Paraguay and Peru— although there are also exceptions, such as Panama and Uruguay.

The region’s cities and metropolises reflect an accumulation of various types of deficiency that represent significant COVID-19 risk factors, such as overcrowding, lack of access to water and sanitation services, electricity and the Internet, and the precariousness and saturation of public transport. Owing to the high level of residential segregation in Latin American cities, these deficiencies are unevenly distributed within them, between rich and poor neighbourhoods, and, therefore, between the high-income and low-income strata of the population. The combination of a high level of urbanization and accumulated deficiencies not only influences the magnitude and impact of the pandemic, but also its differentiated effect on population groups, as the low- and lower-middle-income population is hit the hardest.

Figure 2

Latin America (17 countries): population, COVID-19 infections and COVID-19 deaths in major administrative divisions relative to countries’ total populations, 2020

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official data from the countries systemized by the Pan American Health Organization (PAHO).

Overcrowding is notable for its close link to the spread of the virus —because of the risk of infection associated with sharing a room and the difficulties of complying with quarantine and confinement measures—, as well as its link to socioeconomic status. In 2019, based on the threshold of more than two people per bedroom, 30% of the region’s urban households and over 50% of poor households were overcrowded (see figure 3).

Figure 3

Latin America (11 countries):a overcrowded urban households, based on overcrowding thresholds and poverty status, 2019

(Percentages)

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

a The countries included are: Argentina (urban areas), Brazil, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Panama, Paraguay, Peru and Uruguay.

The deficiencies in access to services and in living conditions, which prevent an optimal response to the pandemic, intersect with and reinforce the various axes of the social inequality matrix, placing at a particular disadvantage the indigenous population of 58 million people (ECLAC/FILAC, 2020) and the Afrodescendent population of 134 million people (ECLAC, 2020i).

The structural inequalities of a political, economic, social, environmental and health nature that affect indigenous peoples create a scenario of greater vulnerability and risk in relation to COVID-19 among traditional communities and large groups of indigenous people living in urban areas, and complicate the mitigation of the socioeconomic impact. In five countries that account for 80% of the region’s indigenous population and for which recent census data are available (Chile, Colombia, Guatemala, Mexico and Peru), more than eight million indigenous people lack access to drinking water in their homes, making it impossible for them to practice frequent handwashing, which is essential to prevent infection. In addition, large segments of the indigenous population have limited access to basic sanitation services in the home.[4] Similarly, there is a higher level of overcrowding among indigenous populations, which makes it extremely difficult to adopt preventive measures for safe confinement. Based on the combination of these three variables that are crucial to the prevention of infection, a vulnerability index has been estimated at the municipal level that systematically demonstrates the inequalities affecting indigenous peoples. In the five countries analysed, the proportion of the indigenous population living in municipalities with high or critical levels of vulnerability is much higher than that seen among the non-indigenous population, with Colombia and Guatemala reflecting the most extreme situations (see figure 4).

Figure 4

Latin America (5 countries): distribution of the indigenous and non-indigenous population by level of vulnerability in living conditions at the municipal level, 2015–2018

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special processing of census microdatabases.

The Afrodescendent population must also face the pandemic in a scenario of deep social inequalities determined by structural and institutional racism and expressed, for example, in high levels of poverty, unequal access to education, precarious housing conditions, more limited access to health services and greater participation in informal employment, among other indicators. Not only do the pre-existing socioeconomic conditions of Afrodescendants make it very difficult for them to follow physical distancing recommendations, but also, the high prevalence of health problems among this population group, such as hypertension and diabetes, makes them very vulnerable to the effects of COVID-19.

Unequal access to health systems, institutional discrimination and the lack of an intercultural perspective in health services represent a considerable barrier to equal access to the health system for people of African descent and indigenous peoples. In view of this situation, it is important to implement communication strategies with an intercultural approach to inform about the virus and implement prevention measures, testing and treatment (ECLAC, 2020i).

B. The weakness of health systems and the multiple effects on the health of the population

Public spending on health in the region remains far from the target of 6% of GDP recommended by the Pan American Health Organization (PAHO), and there are problems relating to the allocation of resources. Funding for primary care does not reach the recommended benchmark of at least 30% of public health expenditure, and in countries where this does occur, the absolute amounts are extremely low (Cid and others, 2020). All this is detrimental to the efficiency and quality of the health system, and households face a high level of financial vulnerability that impoverishes them by forcing them to make large out-of-pocket payments when they access the system (ECLAC/PAHO, 2020).

Although significant efforts have been made in recent decades to strengthen health systems in the countries of the region, these systems remain weak and their capacity to manage the pandemic is very uneven (Burki, 2020). The challenges range from the lack of access to drinking water and personal protective equipment to the scarcity of respirators or beds in intensive care units (ECLAC, 2020e). Responses to these challenges are provided through complex organizational systems that each country has developed according to its history, resources and priorities (Möller, 2020). There are segmentation problems that have given rise to several subsystems within the same country, with dissimilar results in terms of equity. The various characteristics of health systems may favour or curb the spread of COVID-19. Also, once the disease is contracted, the health service response may play a decisive role in patients’ prognoses.

In the countries of the region, there are large barriers to access to health services and limitations in terms of the availability of human resources (PAHO, 2017) and health infrastructure (see figure 5). When infection levels are high, countries with fewer beds and health workers have less capacity to respond to severe cases and little room to reorganize their available resources. The figure also shows the situation of three countries —Italy, Spain and the United States— which, although not in the region, faced considerable pressure on their health systems because of COVID-19. Although these countries have more hospital beds and health personnel per capita than many of those in Latin America and the Caribbean, they still recorded some of the highest rates of deaths owing to COVID-19 in the world (Möller, 2020). This supports the notion that the fight against the pandemic is as much a matter of containment and mitigation outside the hospital setting —with actions at the primary level and in communities— as it is in hospitals, which must be prepared and have sufficient staff, equipment and supplies.

Figure 5

Latin America and the Caribbean (33 countries), Italy, Spain and the United States: number of hospital beds and medical and nursing staff, latest available year

Source: S. Möller, “Intervenciones sociosanitarias y uso de las tecnologías de la industria 4.0 para enfrentar la enfermedad por coronavirus (COVID-19) en América Latina y el Caribe”, Social Policy series, No. 234 (LC/TS.2020/87), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2020.

The pandemic has increased mortality in the region. At 31 December, there were around 507,000 deaths owing to COVID-19 in Latin America and the Caribbean, which will most likely affect mortality and life expectancy in the countries (ECLAC, 2020e).[5] The impact on life expectancy will depend on a number of factors, such as the duration of the pandemic, the prevalence and lethality of the disease in each country, and the population’s access to vaccines when they become available, among others. Also, while mortality is the most dramatic outcome of COVID-19, the long-term health effects for people who have recovered from the virus are still unknown.[6]

Although measuring the COVID-19 fatality rate is a major challenge,[7] the probability of dying after contracting the virus is higher for older persons (Baqui and others, 2020; Meyerowitz-Katz and Merone, 2020) and people with pre-existing chronic diseases (Hanlon and others, 2020, Nepomucene and others, 2020). People over 60 years of age thus account for a substantial proportion of COVID-19 deaths, as can be seen in the analysis of mortality rates by age (see figure 6).

With regard to the impact of the pandemic on the total fertility rate,[8] much will depend on access to sexual and reproductive health services, particularly contraceptive methods, and on the duration of the crisis. This rate may decline depending on the impact of the pandemic on reproductive decisions and on the postponement of childbearing owing to the economic uncertainties associated with the crisis. In principle, even with fluctuations, the downward trend in fertility levels recorded in the region would not be affected. In times of crisis, for example during the Zika virus epidemic in Brazil in 2016 (Castro and others, 2018; Marteleto and others, 2020), the number of live births declines some time after the start of the outbreak —usually nine months—, but later returns to the expected level.[9]

Figure 6

Latin America (4 countries): age-specific mortality rate of coronavirus disease (COVID-19), to 31 October 2020

(Cumulative number of deaths per 1,000 persons)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Demographic Observatory Latin America and the Caribbean, COVID-19 mortality: Evidence and scenarios, on the basis of United Nations, “2019 Revision of World Population Prospects”, 2019 [online] https://population.un.org/wpp/; Ministry of Health of Brazil, “Painel Coronavirus” [online] https://covid.saude.gov.br; Department of Health Statistics and Information (DEIS), Chile [online] https://deis.minsal.cl; National Institutes of Health, “Situación de COVID-19 en Colombia” [online] https://sig.sispro.gov.co/SituacionCovid; Ministry of Health of Peru, “Sala Situacional COVID-19 Perú” [online] https://covid19.minsa.gob.pe/sala_situacional.asp.

It should also be noted that the effects of the pandemic on health are not limited to those directly related to the virus. The pandemic has caused a shift in the control of communicable and non-communicable diseases: in the region’s weak and underfunded health systems, care has been postponed or interrupted owing to the need to reassign budgets and health workers to cope with the onslaught of the pandemic (ECLAC/PAHO, 2020). Many people also choose, when they can, not to seek medical services for fear of infection in health-care facilities. As a result, the control of chronic non-communicable diseases such as diabetes and hypertension has been particularly affected (ECLAC/PAHO, 2020), although there are also limitations in access to sexual and reproductive health, maternal and child health and mental health services. Thus, the pandemic is having profound indirect repercussions, with potentially long-lasting effects on the health of the population of Latin America and the Caribbean.

C. School closures, distance learning and the digital divide

In 2020, the pandemic led to the mass closure of education institutions to prevent and curb the spread of the disease. In total, 32 countries closed their education institutions, which affected more than 165 million students at all levels (see figure 7). Most countries have established forms of distance learning through various modalities, such as the Internet, television or radio (ECLAC/UNESCO, 2020). Subsequently, education authorities began to prepare or implement the return phase, which involved adapting protocols and spaces, and designing protection measures and plans to support the emotional well-being of the education community and for the recovery of teaching processes.[10]

Figure 7

Latin America and the Caribbean (33 countries):a adoption of measures to suspend classes and students affected, by date, 2020

(Number of countries and millions of students)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations Educational, Scientific and Cultural Organization (UNESCO).

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

While the pandemic has presented an opportunity in terms of adaptation and innovation in education systems, through digital media and distance education, prolonged school closures may lead to a learning crisis and constitute a “generational catastrophe”, which could jeopardize decades of progress and deepen existing inequalities (United Nations, 2020b). The disruption or interruption of curricula and education processes increases gaps in learning and skills, in academic progression and in the completion of different levels of education, particularly from secondary education onward and, to a greater extent, in higher education.

The interruption of the school cycle mainly affects students who were disadvantaged prior to the pandemic, as it has worsened education gaps related to gender, age, socioeconomic status, area of residence or disability status. The effects on learning are expected to be greater in children under eight years of age, who do not yet have the necessary tools to be able to adapt to distance learning processes, especially those from more disadvantaged backgrounds with fewer cultural resources at home.[11] Similarly, school closures affect boys and girls differently. Given the distribution of care roles in our societies, girls are at greater risk of being overburdened with domestic and care work that may hinder the continuity of their education. They are also more vulnerable to domestic and sexual violence while in confinement. It is therefore essential to strengthen protection strategies with a gender perspective.

The crisis is expected to increase the risk of vulnerable students dropping out of school, given that the interruption of face-to-face classes decreases the attachment to school and the motivation of students and their families, and this is compounded by the greater economic difficulties they face. According to UNESCO estimates (2020), approximately 24 million students at all levels of education around the world (180 countries) are at risk of not resuming their education after the crisis. In Latin America and the Caribbean, it is estimated that around three million students face this risk (see figure 8). The greatest impact in proportional terms is expected on tertiary-level students, owing to the higher cost associated with this level of studies, and on pre-primary level students, given the difficulty of continuing distance learning for children of these ages.

Figure 8

Latin America and the Caribbean (30 countries):a students at risk of not resuming their education, projections as of June 2020b

(Thousands of students and percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations Educational, Scientific and Cultural Organization (UNESCO), “How many students are at risk of not returning to school?”, UNESCO COVID-19 education response. Advocacy paper, 30 July 2020 [online] https://unesdoc.unesco.org/ark:/48223/pf0000373992.

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

b Projections based on International Monetary Fund (IMF) data on the decline in per capita GDP, historical enrolment, and gender parity index in education. The methodological details can be found in UNESCO (2020).

Students in countries and households with more limited access to digital technologies are expected to suffer more in terms of education. Despite advances in the last decade, a large proportion of students have poor access to the virtual world from home and little or no skills to take advantage of this resource. In addition, there are gaps in the capacities of teachers and parents or guardians to support adaptation and facilitate the continuity of learning processes through these platforms.

Internet access has expanded rapidly in the region in recent years thanks mainly to mobile connectivity. The expansion of mobile connectivity has provided many people with freer and more permanent Internet access from almost anywhere, but at the same time, has made the diversity of situations and opportunities for digital inclusion more complex (Trucco and Palma, 2020). In addition, access to mobile connectivity does not guarantee a good-quality connection, since most users only have access to prepaid plans, with tight restrictions on the type of activity possible. Available data indicate that most students connect to the Internet via mobile phones, and that the socioeconomic gaps in Internet access are significant, even for people with these phones (ECLAC/UNESCO, 2020) (see figure 9).

Figure 9

Latin America (7 countries): 15-year-old students with access to Internet at home, by connection type and socioeconomic and cultural quartile, 2018

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Organization for Economic Cooperation and Development (OECD), Programme for International Student Assessment (PISA), 2018 cited in United Nations Educational, Scientific and Cultural Organization (UNESCO), “How many students are at risk of not returning to school?”, UNESCO COVID-19 education response. Advocacy paper, 30 July 2020 [online] https://unesdoc.unesco.org/ark:/48223/pf0000373992.

Data collected within the framework of the Programme for International Student Assessment (PISA) also show how prepared students in some countries in the region were to do some of their schoolwork using digital media in 2018. These data indicate that these students used digital media for school activities in different subjects outside the classroom to a greater extent than inside the classroom, in contrast to students in OECD countries, who used them in about the same proportion in both cases. Socioeconomic gaps are reflected in each school activity undertaken by students outside of school (see figure 10).

The results of PISA 2018 reveal students’ own perception of their digital skills (self-efficacy). As in the case of other skill sets, the perception of self-efficacy differs based on the socioeconomic and cultural status and gender of the students (see figure 11).[12] Perceived proficiency in the use of digital media increases in students of higher socioeconomic and cultural status, but so does the gender gap, to the disadvantage of women. These figures confirm the risk of increased learning outcome gaps among students because of the pandemic.

The school closures in the region also have consequences for the health and nutrition of students, particularly for adolescents and young people, and have a greater impact on women (ECLAC/UNESCO, 2020). The suspension of classes has affected school feeding programmes (despite the fact that 21 of the 33 countries of the region maintained these programmes in various forms) and mental health programmes, along with comprehensive sexual education programmes and the provision of sexual and reproductive health services, including the distribution of contraceptives. Of particular concern are the mental health risks arising from increased exposure to the Internet and social isolation. School closures also limit measures for the detection and prevention of cases of violence against children and adolescents in the home (ECLAC/UNICEF/Office of the Special Representative of the Secretary-General on Violence against Children, 2020).

Figure 10

Latin America (7 countries):a 15-year-old students carrying out activities via Internet, by activity type and socioeconomic and cultural quartile, 2018

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Organization for Economic Cooperation and Development (OECD), Programme for International Student Assessment (PISA), 2018 cited in United Nations Educational, Scientific and Cultural Organization (UNESCO), “How many students are at risk of not returning to school?”, UNESCO COVID-19 education response. Advocacy paper, 30 July 2020 [online] https://unesdoc.unesco.org/ark:/48223/pf0000373992.

a Brazil, Chile, Costa Rica, Dominican Republic, Mexico, Panama and Uruguay.

In response to the new demands that have arisen during the crisis, teachers and education staff have had to re-plan and adapt teaching processes, including adjusting methodology, reorganizing curricula, designing new materials, and diversifying communication channels through the use of digital resources. At the same time, they have had to become involved in activities to support the families of their students through the distribution of food, health products and school materials, among others, and to contribute to their socio-emotional well-being. This has resulted in an excessive workload, as these tasks come on top of the care and domestic work they have had to carry out in their own homes and with their own families, with insufficient capacities and resources, especially in more vulnerable areas (ECLAC/UNESCO, 2020).[13]

According to the results of PISA 2018, 58% of students who participated in the study, on average, felt that teachers in their schools had the technical and pedagogical skills needed to integrate digital devices into teaching. Similarly, participants in the latest Teaching and Learning International Survey (TALIS) (OECD, 2019) reported that the percentage of teachers that had received training in ICT for teaching in their formal education or training was 64% in Brazil, 77% in Chile, 75% in Colombia, 77% in Mexico and 53% in the City of Buenos Aires. However, teachers in these countries believe that they urgently need training in this area and a high percentage of principals (59% in Brazil, 64% in Colombia, 44% in Mexico and 39% in the City of Buenos Aires) reported the shortage or inadequacy of digital technology for instruction (ECLAC/UNESCO, 2020).

Parents and caregivers have also had to face a situation involving an excessive workload and few resources to support their children in educational tasks, without access to pedagogical or digital tools, according to surveys carried out in Argentina[14] and Mexico.[15] The pandemic has highlighted the importance of care for the sustainability of life, as well as the unfair distribution of care work to the detriment of women, who are mainly responsible for these tasks, which now include helping their children to continue their studies (ECLAC, 2020c).

D. Increasing poverty and inequality

Because of the pandemic, and despite the emergency social protection measures taken to curb it, poverty and extreme poverty are expected to reach levels not seen for 12 and 20 years, respectively, and distribution is projected to deteriorate in most countries. The extreme poverty rate and the poverty rate are forecast at 12.5% and 33.7%, respectively, for 2020. This indicates a total of 209 million people living in poverty at the end of 2020, 22 million more than the previous year. Of this total, 78 million people were estimated to be living in extreme poverty, 8 million more than in 2019 (see figure 1).

Figure 12

Latin America (18 countries):a population by per capita income strata, 2019 and 2020

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Household Survey Data Bank (BADEHOG). Figures adjusted for population projections of World Population Prospects, 2019 revision, and estimated poverty trends in countries for which figures are not available for the years indicated.

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

The increase in poverty and extreme poverty levels would be even greater if measures to transfer emergency income to households had not been implemented. Projections that consider only the impact of the pandemic on employment and labour income show that the poverty rate in 2020 would have increased by 6.7 percentage points, representing 37.2% of the total population, while the extreme poverty rate would have increased by 4.4 percentage points to 15.8% of the total population.

The contraction in economic activity owing to the pandemic, and the resulting job losses and reduction in labour income, are also expected to lead to growth in the low-income strata overall, and to downward mobility in the middle-income strata. This is because families in the middle-income strata and the upper level of the low-income strata earn their income mainly through work, mostly wage employment, and are not usually targeted by social protection policies and programmes.

Between 2019 and 2020, it is estimated that the low-income strata increased by 4.5 percentage points (about 28 million additional people), compared with a similar contraction in the middle-income strata (4.1 percentage points, or 25 million fewer people) (see figure 12). Of a total of around 59 million people who belonged to the middle-income strata in 2019 and who likely experienced downward economic mobility in 2020, just over 25 million are estimated to have remained in the middle-income strata, while just over 3 million are estimated to have fallen directly into poverty or extreme poverty, and the remainder into the low-income stratum which does not fall below the poverty line.

Regarding the effect of the pandemic on the distribution of household income, the first factor to consider is the loss of labour income owing to the interruption of employment. According to projections, the increase in the number of people who stopped earning labour income in the first quintile (based on 2019 income) is 5.7 percentage points, and this figure is projected to decrease noticeably in the subsequent quintiles. In the fifth quintile, the number of people with no income is expected to increase by 0.7 percentage points. The second factor is the decline in labour income for those who remained in employment during the pandemic. The significant decrease in demand and in the possibilities of performing the usual labour tasks are estimated to have resulted in a 15% contraction in the average labour income per employed person. As a result of these dynamics, for people in the first quintile (of 2019), the decline in labour income is estimated to have been 42%, while for those in the fifth quintile, the expected average decrease is around 7% (see figure 13).

Figure 13

Latin America (18 countries): labour income per employed person (multiples of the poverty line) and variation, by quintile (from 2019), 2019 and 2020a

(Percentages)

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

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

As a result of these trends, total per capita income inequality is projected to reflect an increase in 2020, resulting in an average Gini index 5.6% higher than that recorded in 2019. However, if the transfers made by governments to mitigate the loss of labour income, whose distribution tends to be concentrated in low- and middle-income groups, are included, the expected increase in the average Gini index for the region would be 2.9%.

E. Deterioration of labour indicators

Since 2015, labour market indicators have been showing adverse trends in the region, reflecting a gradual increase in unemployment and a worsening of the quality of employment (ECLAC/ILO, 2020; Weller, 2020; ECLAC, 2019c). This is compounded by the profound effects of the pandemic, which have led to a sharp contraction in employment. The severity of these effects varies from country to country (see figure 14) and depends on, among other factors, the type, extent and effectiveness of health restrictions implemented to curb the pandemic and measures to protect employment relationships, as well as the level of dependence of individual economies on sharply contracting external demand.

Available data show that the crisis has had a disproportionate impact on informal workers and women, as they represent a larger share of the workers in some of the hardest-hit economic sectors, and the burden of unpaid care in households has increased as a result of school closures, in a region that already reflected a significant deficit in this area (ECLAC/UN-Women, 2020; ILO, 2020a and 2020b). Young people, and especially young women —who represent a larger share of the persons excluded from the labour market and the education system— are particularly vulnerable to the aggregate effects of deterioration in the labour market. It is also possible that, in the future, the labour market will provide fewer opportunities for older persons, whose participation in the labour force is crucial for their well-being in the absence of universal social protection systems (ECLAC/ILO, 2018). In addition, ethnic and racial inequalities, along with those linked to territory, disability or migratory status, are likely to worsen in the labour market in the time of COVID-19.

Figure 14

Latin America and the Caribbean (12 countries): year-on-year variation in employment, unemployment and participation rates, by sex, April–June quarter (2020/2019)a

(Percentage points)

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

a In Colombia and Jamaica, hidden unemployment is included. For more information on limitations in comparability between 2019 and 2020 data see annex table A.II.1 in chapter II.

b Includes data for 31 urban centres.

c Urban areas.

d Figures as of July.

e Figures as of May.

F. Social protection gaps and responses

Social protection, which aims to guarantee adequate income, promote access to social services and foster decent work for the entire population, is a right recognized in numerous national and international legal instruments and is key to eradicating poverty and significantly reducing inequalities.

Despite the efforts made in the region over the past two decades to expand social protection coverage (ECLAC, 2019d), the countries are facing the pandemic with wide gaps and large unprotected population groups, which highlights the fragmentation and inequalities of their social protection systems and the historical weakness of the welfare state in the region (ECLAC, 2010). Before the crisis, because of high levels of labour informality, only 47.2% of employed persons were affiliated with or contributed to pension systems, and 60.5% were affiliated with or contributed to health systems. Also, in 2019, one quarter of people aged 65 and over did not receive a pension. That same year, conditional transfer programmes covered an average of 18.5% of the population in the countries of Latin America and the Caribbean.

In the absence of truly universal and comprehensive social protection systems that guarantee a basic level of consumption and well-being throughout the life cycle, governments have responded to the pandemic with an unprecedented set of emergency social protection programmes aimed mainly at households in situations of poverty or at greater risk of falling into poverty, such as those with informal workers (ECLAC, 2020b).

Containment and quarantine measures adopted to flatten the curve of infection and prevent the collapse of health systems cannot be sustained over the long term without maintaining household incomes. This is why emergency social protection programmes are essential for controlling and mitigating the pandemic and reactivating the economy (ECLAC/PAHO, 2020), as they allow the implementation of the more or less strict strategies needed to contain COVID-19 without condemning a significant share of the population to poverty (Filgueira and others, 2020).

In 2020, 263 non-contributory social protection measures, including cash transfers, food and medicine deliveries and the provision of basic services, were adopted in 32 countries. It is estimated that cash and in-kind transfers reached, on average, 49.4% of the population in the countries of the region (see figure 15). These programmes, which vary in coverage and effectiveness, have been aimed at maintaining consumption and guaranteeing basic living conditions by adapting and extending existing cash and in-kind transfers and creating new instruments.

Figure 15

Latin America and the Caribbean (28 countries): persons in households benefiting from emergency cash and in-kind transfers (2020) and conditional transfer programmes,a simple average by subregion (latest year available)b

(Percentages of the total population)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries; COVID-19 Observatory in Latin America and the Caribbean [online] https://www.cepal.org/es/temas/covid-19 and Observatory on Social Development in Latin America and the Caribbean, “Social Development and COVID-19 in Latin America and the Caribbean” [online] https://dds.cepal.org/observatorio/socialcovid19/listamedidas.php.

a Coverage of conditional transfer programmes or other permanent cash transfer programmes in the last year with information available in the Non-contributory Social Protection Programmes Database in Latin America and the Caribbean [online] https://dds.cepal.org/bpsnc/cct. Non-contributory Social Protection Programmes Database Latin America and the Caribbean.

b South America includes: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Plurinational State of Bolivia and Uruguay; Central America includes: Costa Rica, Dominican Republic, El Salvador, Guatemala, Haiti, Honduras, Mexico and Panama; and the Caribbean includes: Antigua and Barbuda, Bahamas, Barbados, Belize, Guyana, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines and Trinidad and Tobago.

G. Increased public social spending and emergency spending

The pandemic has directly affected decisions on public spending in general and on social spending in particular. In Latin America, public social spending up to 2019 shows that the investment of central government resources in social policies maintained the upward trend seen in the last two decades. On average in Latin America, public social spending by the central government as a percentage of GDP has risen by 36% overall since 2000, albeit with a relative stabilization in recent years, accounting for 11.5% of GDP in 2019. Meanwhile, in five English-speaking Caribbean countries, where central government social spending accounted for 11.9% of GDP in 2019, there has been some stability over the past five years.

Spending levels are very heterogeneous across the region, where eight countries allocate less than 10% of GDP to central government social spending and three exceeded 17% in 2019, with amounts ranging from less than US$ 200 to more than US$ 2,500 per capita per year. These amounts increase in countries that report institutional coverage greater than that of the central government, but the challenge of expanding the availability of these data to allow for better comparability throughout the region remains.

In 2020, non-contributory social protection spending in the countries of Latin America and the Caribbean increased in response to the pandemic, with 73% of committed resources used between March and August, owing to the urgency of protecting the income and consumption of affected families. Among the wide variety of non-contributory measures adopted to protect the income of households affected by the crisis, cash and in-kind transfers stand out. The effort in terms of additional resources and budgetary adjustments by the countries of Latin America and the Caribbean to finance these measures is estimated at about US$ 86.214 billion in 2020. In simple average terms, this expenditure is equivalent to US$ 78 per capita, with significant differences between subregions (see figure 16), and represents 1.25% of GDP in 2019, 1.9 times the average proportion of GDP resources spent on conditional transfer and social pension programmes in 2018.

The amounts committed for emergency measures reveal the countries’ capacity to respond to the impact of the crisis. However, it is also necessary to take into account the installed capacity for social protection, which has made it possible to contain and mitigate the social effects of the pandemic. For example, the non-contributory social protection programmes implemented prior to the pandemic that provided cash transfers to families living in poverty and vulnerable conditions are also crucial to protecting the population from the effects of the pandemic.[16]

Considering regional spending on ongoing non-contributory social protection programmes and on conditional transfer programmes and social pensions, as well as emergency spending by the countries of the region in 2020 to deal with the pandemic, it is possible to estimate the additional cost of implementing cash transfers equivalent to a per capita poverty line proposed by ECLAC (2020b and 2020g) to deal with the socioeconomic impacts of the crisis, satisfying basic needs and sustaining household consumption (see figure 17).

Figure 16

Latin America and the Caribbean (28 countries): estimated average per capita expenditure on emergency cash and in-kind transfers, March–December 2020a

(Dollars at current prices) b

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries; COVID-19 Observatory in Latin America and the Caribbean [online] https://www.cepal.org/es/temas/covid-19 and Observatory on Social Development in Latin America and the Caribbean, “Social Development and COVID-19 in Latin America and the Caribbean” [online] https://dds.cepal.org/observatorio/socialcovid19/listamedidas.php.

a The 28 Latin American and Caribbean countries are divided into two groups: 18 Latin American countries and 10 Caribbean countries (Antigua and Barbuda, Bahamas, Barbados, Belize, Guyana, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines and Trinidad and Tobago). The Latin American countries are divided into two subgroups: 10 South American countries (Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Plurinational State of Bolivia and Uruguay) and 8 countries from the group including Central America (Costa Rica, Dominican Republic, El Salvador, Guatemala, Honduras and Panama), the Dominican Republic, Haiti and Mexico. The total population by country in 2020 corresponds to that published in CEPALSTAT [online] https://estadisticas.cepal.org/cepalstat/Portada.html.

b The average monthly exchange rate from March to October 2020 published by the International Monetary Fund (IMF) [online] https://data.imf.org/regular.aspx?key=61545862) was used, except for the Bolivarian Republic of Venezuela, for which the average daily exchange rate published by the Central Bank of Venezuela [online] http://www.bcv.org.ve/estadisticas/tipo-cambio-de-referencia-smc) was used.

Figure 17

Latin America (18 countries):a estimated additional expenditure on transfers equivalent to a poverty line complementary to permanent and emergency measures,b targeting the entire population living in poverty, for six months or twelve months

(Percentages of GDP in 2019)

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

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

b The same amount of resources is considered for 6 and 12 months.

H. The care economy as a strategic sector for reactivation with equality

The current sexual division of labour and social organization of care remain one of the structural challenges of inequality in the region (ECLAC, 2018) and can be expected to worsen in the context of the pandemic, threatening the full exercise of women’s rights and autonomy. In addition, they give rise to a series of economic and social inefficiencies with negative externalities for society as a whole and violate the rights of both caregivers and care recipients.

The care economy comprises all unpaid work within households, mainly by women, as well as paid domestic and care work in the labour market, also primarily by women (ILO, 2018) (see diagram 1). Paid care work includes, in particular, the provision of goods and services for households by paid female domestic workers, whose employment conditions continue to reflect the undervaluation of care tasks carried out in the commercial sphere (ECLAC, 2019b).

Diagram 1

The care economy

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Women’s autonomy in changing economic scenarios (LC/CRM.14/3), Santiago, 2019.

The care economy involves care at the micro level, through the observation of the tasks undertaken in households and communities that are fundamental for the reproduction of the labour force. It also involves the dynamics of care as regards markets and employment, or in the delivery of public services, the provision of infrastructure and the formulation of public policies. By relating the way in which societies organize the care of their members and the economic system, the concept of care is linked to the economic value it generates (which is often invisible or unrecognized) (Montaño and Calderón, 2010).

Care is a social function that involves both recipients and providers and should be understood as a right, specifically: to provide care, to be cared for, not to provide care and to self-care. The care provider takes responsibility for the other person and makes different kinds of physical, mental, and emotional efforts. Fulfilling this responsibility creates an emotional bond between the caregiver and the care recipient (ECLAC, 2019b).

In turn, the social organization of care refers to the way in which reproduction is socially organized. In other words, the way in which families, the State, the market and community organizations, in an interrelated manner, produce and distribute care (Rodríguez Enríquez, 2015). For example, the provision of public or private services that are accessible and of high quality, influences the redistribution of responsibilities from households to the State and the private sector, which frees up women’s time and helps to improve their economic autonomy (ECLAC, 2019b).

In the face of the pandemic, there is a need to reflect on the benefits of the responses that integrate a gender perspective and emphasize the care economy. Even before the pandemic, the rigid sexual division of labour in the region, along with the lack of integrated care policies, had major implications in terms of the equality gap between men and women, between women of different socioeconomic levels and between countries and territories.

The pandemic has revealed the enormous cost to the countries of the region of not having an integrated system of care that is comprehensive, defeminized and of high quality. This is why it is urgent to invest in this sector to face the crisis, to guarantee the right to care for others and to receive care, and to reactivate the economy from a perspective of equality and sustainable development. This investment would be less than the cost of inaction that affects various groups in society: in terms of the 2030 Agenda for Sustainable Development, investment in the care economy contributes, among other things, to eliminating poverty and implementing appropriate social protection systems and measures for all people (SDG 1), ensuring healthy lives (SDG 3), achieving gender equality (SDG 5), promoting inclusive and sustainable economic growth (SDG 8) and reducing inequalities (SDG 10) (ECLAC, 2019b).

I. Social unrest in highly unequal societies

There is growing social unrest in the region related to the main dimensions that structure social life. Prior to the pandemic, there was considerable dissatisfaction with the persistent inequality in the distribution of resources and a perception of lack of protection from multiple risks, especially labour and economic risks, sometimes in contexts of high levels of household indebtedness. There was also dissatisfaction with the functioning of politics and its actors, and a growing distrust of institutions and the functioning of democracy, despite the fact that democracy is still valued by the majority as the best form of government. In a context of social relations marked by distrust and discrimination, all this has led to demands for greater equality and non-discrimination, and in some cases, to processes of social mobilization and protests that demand substantive transformations to build fairer and more inclusive societies.

Social unrest (see diagram 2) is a subjective experience which manifests in multiple ways and is inseparable from the objective and material conditions that characterize daily life (UNDP, 2012). In its different manifestations, unrest can be a factor of transformation and social progress, giving rise to social movements and demands for change shared by broad sectors. However, it can also result in apathy or political disaffection, without a structured expression of discontent through specific demands. The lack of response by governments and institutions to unrest, or responses that are not sustainable over time, can lead to significant tensions, conflict and instability.

Diagram 2

Analytical dimensions of social unrest

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

The expansion of the middle-income strata and the consolidation of a citizenry that is more demanding and less tolerant of inequalities and corruption, and more demanding of spaces for participation, undoubtedly contributed to mobilization and protests. In the region, citizens increasingly question the patterns of discrimination and inequality that permeate institutions and social relations, and which are crystallized in the culture of privilege of colonial origin that normalizes deep socioeconomic, gender, ethnic and racial inequalities, among others (ECLAC, 2018).

Currently, both because of structural problems of a social and economic nature and the pandemic, the region is experiencing a sharp deterioration in living conditions, as evidenced by rising unemployment, poverty and inequalities. These objective indicators are reflected in subjective expressions of discontent, both individually and collectively. The social and economic impacts of the pandemic threaten to deepen this malaise, at a time when transforming the prevailing development model and consolidating a new common project is more urgent than ever. Addressing the factors that give rise to unrest, moving towards social policies focused on the enjoyment of rights, equality, recognition and dignified treatment, together with the formation of social compacts aimed at building fairer, more inclusive and cohesive societies, is therefore essential to avoid increasing levels of conflict, expressions of violence and crises of representation and democratic legitimacy that hinder economic performance (ECLAC, 2018).

J. Social policy scenarios and recommendations for a transformative recovery with equality and sustainability

The pandemic has exposed the failures and inadequacies of social protection systems and welfare systems. However, at the same time, the role of public policy is being reassessed and the State is being recognized as a key and indispensable actor to respond to current challenges. The pandemic thus represents an opportunity to take a new public policy direction in order to build more egalitarian and resilient societies through the implementation of universal, redistributive and solidarity-based policies with a rights-based approach (ECLAC, 2020b).

In particular, it is hoped that in the region the crisis will help to generate a consensus on the need to build a true welfare state, as well as sustainable models of production and consumption. In order to overcome the crisis, the development model must be rethought and the three dimensions of sustainable development —social, environmental and economic— must be consolidated. Although the expected social and economic setbacks seriously threaten the achievement of the Goals of the 2030 Agenda for Sustainable Development, the pandemic has clearly also illustrated the importance of the Agenda’s core principles: the comprehensive nature of development and the interdependence of its dimensions, as well as the principle to “leave no one behind”.

Social policies have a central role to play as the vanguard of change in the development model. From health, nutrition, cash transfers and social protection in general, social policies have been the protagonists of public action to mitigate shortages and meet the needs of the population in a context of health and economic crises. Once the emergency is over, they will play a key role in the reconstruction process. In order to rebuild and transform with equality and sustainability, it is essential to move towards decent work, foster co-responsibility for care and promote universal social protection, ensuring, among other things, access to high-quality public health and pension systems (ECLAC, 2020j).

In many ways, the pandemic has shaken the status quo and the current crisis can be seen as a “critical juncture”, that is, an exceptional moment that redefines what is possible, even what is conceivable. This is because, in the face of extreme pressures, losses or risks, most actors become more willing than before to change the status quo, thus opening windows of political opportunity for social, economic and political change (Weyland, 2007 and 2008). For example, not so long ago, universal basic income was a controversial and experimental policy instrument. Today, its feasibility, scope and role within social protection systems have entered the mainstream of discussions. In the context of the pandemic and its aftermath, it is becoming easier to argue that all people need access to a basic level of welfare and income, regardless of their individual situation and characteristics.

1. Towards a new social compact in times of unrest and the pandemic

In the face of an exceptional situation such as the pandemic and citizens’ demands for a more egalitarian society with the full guarantee of rights, there is an opportunity for change. However, in order to move beyond wishful thinking, it is important to urgently raise the need for a new social compact as a political instrument for real structural change. Politics must be restored as an instrument of change, as a mechanism to deliberate, dissent and agree, and to generate public goods and lasting compacts.

As a process, the compact should be an explicit, representative and participatory attempt to address issues that have not been resolved through the usual channels, thus building new bridges between society and the State. Analytically, there are two major components of a social compact. On the one hand, there is the redistribution of resources and material opportunities to access welfare, and on the other hand, the recognition of the identities and rights of specific population groups that are excluded or discriminated against in the various spheres of social life (Martínez Franzoni and Sánchez Ancochea, 2020). Depending on the context, a compact may contain elements of both dimensions, or it may focus specifically on one of them.

The social compact is a political instrument that serves to build consensus and agreements for the medium and long term. It is based on broad and participatory dialogue, with the population as a whole playing a strong role. This dialogue today must start from the common space imposed by the pandemic, namely, universal vulnerability to a health, economic and social crisis, which requires universal protection and mitigation mechanisms.

The compact assumes that the actors will make a contribution and even that some of the powerful actors will make important concessions in relation to their immediate interests, with a view to achieving a more stable, beneficial, legitimate and sustainable situation for society as a whole. History indicates that powerful actors are indispensable interlocutors —though they are by no means the only ones— who must be actively involved and committed to the outcomes. The main social movements and sectors, from workers to the most marginalized sectors of society, must also be actively involved. It is essential to listen to the voice of civil society, whose organizations are often at the forefront in pushing for citizens’ demands, as well as for greater accountability on the part of the State and political actors in general. Within this group, young people are a source of change and transformation, including in the critical moments of the pandemic. Recognizing this group’s value, potential and concrete contribution is fundamental to advance in societies truly oriented towards a new model of development and a welfare state.

Lastly, a new social compact must open up discussions and address issues that have been neglected or even omitted by the main economic and political actors, with solidarity-based responses to costs and financing, which requires fiscal covenants that promote progressive and sustainable taxation, ensuring constant and sufficient resources for the well-being and resilience of the population.

2. Welfare state and universal social protection

The emergency social protection responses adopted by countries, which are needed to address the most acute manifestations of the crisis, must be harmonized with measures aimed at strengthening the welfare state. In the short term, there is a need to offset the loss of sources of labour income and to support demand while at the same time facilitating access to health. Crucial actions include the establishment of an income guarantee, especially for people living in poverty and informal and precarious workers, as well as universal access to medical care for all who need it, basic services and adequate food.

From a rights perspective and in order to avoid a serious deterioration in living conditions in the medium and long term, it is imperative to rethink the architecture of welfare in our societies. To avoid another lost decade, the key is to build a welfare state that ensures universal, quality public services —education (see box 1), health, transport, environmental services— and expands access to them, reducing welfare gaps. The guarantee of income must be constant, should be granted to more people than those living in poverty and cover broad strata of the population that are highly vulnerable to falling into poverty, such as the low-income non-poor and the lower-middle income strata. This would make it possible to move towards a universal basic income that could be implemented gradually over a period suited to each country’s situation (ECLAC, 2020b).

Box 1

Rethinking education: innovations and risks during the pandemic

The pandemic has highlighted the large inclusion gaps in education and has posed major challenges for education systems (ECLAC/UNESCO, 2020).

The suspension of face-to-face classes has shown that the organizational structure of school, with its rigid schedules and content, must be transformed and made more flexible in order to accommodate the diversity of experiences over the course of a person’s life, and to ensure that education takes place in multiple spaces and not only in school. It has also shed light on the importance of parental and community participation in education processes, which should be maintained after the crisis, seeking more formal channels of participation.

Innovation in teaching processes may represent a milestone in the shift from traditional pedagogical models, in which the teacher presents the content unilaterally and students listen passively, to the presentation of digital educational content, with the accompaniment and guidance of the teacher. Increased exposure to digital media may widen the gaps between students, but it is also an opportunity to develop digital skills and digital citizenship (Buchholz, Dehart, & Moorman, 2020). Adults who accompany students in the process must have digital skills and tools to train in a comprehensive manner, promoting self-care of children and adolescents in the face of increased exposure to digital technologies.

As with any traumatic event, the sudden and unexpected interruption of face-to-face school activities, as well as isolation from social life and, in many cases, economic constraints that threaten subsistence, have significant effects on mental health. In the recovery period, it will be very important to focus on the well-being and socio-emotional skills of students and teaching staff, as these skills allow them to approach traumatic situations calmly and with emotional stability (ECLAC/UNESCO, 2020). They also make it possible to strengthen critical thinking in order to make informed decisions (UNESCO, 2020).

The return to the classroom and the recovery of education processes also require the coordination and harmonization of planning and implementation in the education sector with that of other sectors, particularly with regard to health, nutrition and social protection. It will be very important to build partnerships across different sectors to create an integrated, student- and teacher-centred system. Until the permanent return to face-to-face classes, it is essential to shed light on social services that the school system provides to children and adolescents and that are important to resume or maintain, such as feeding programmes, sexual and reproductive health programmes and services, and the monitoring of rights violations such as domestic violence, among others.

Finally, the crisis is expected to affect education financing, with a disproportionate impact on low-income countries and marginalized populations. It is therefore important to safeguard education financing to protect national systems from the exacerbation of inequalities in access to education and of the learning crisis (ECLAC/UNESCO, 2020). Owing to the decline in GDP, there is a real risk of a decrease in the education budget, which may affect teachers’ wages or raise families’ co-payments (UNESCO, 2020). It is estimated that the amount of resources available for education in 25 countries of the region could decrease by more than 9% in 2020 alone (ECLAC/UNESCO, 2020).

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of “Digital citizenship during a global pandemic: moving beyond digital literacy”, Journal of Adolescent & Adult Literacy, vol. 64, No. 1, June 2020; ECLAC/United Nations Educational, Scientific and Cultural Organization (UNESCO), “Education in the time of COVID-19”, COVID-19 Report ECLAC-UNESCO, Santiago, August 2020; UNESCO, “Nurturing the social and emotional wellbeing of children and young people during crises”, Issue Note, Nº 1.2, 2020; UNESCO, “Anticipated impact of COVID-19 on public expenditures on education and implication for UNESCO work”, UNESCO COVID-19 Education Response Education Sector issue notes. Issue note, No. 7.2, April 2020 [online] https://unesdoc.unesco.org/ark:/48223/pf0000373276_spa/PDF/373276spa.pdf.multi.

Universal social protection systems sensitive to differences are central to the reduction of inequalities, progress towards social inclusion and inclusive growth, and make it possible to address the situations faced by different population groups, such as informal workers, the most vulnerable age groups such as children (see box 2) and older persons, rural dwellers, indigenous peoples and Afrodescendants, persons with disabilities and migrants, among others. Similarly, in the face of overcrowding and lack of basic services made visible by the pandemic, large-scale public investments in affordable and adequate housing and the upgrading of slums are needed so that all individuals and families can live in places where they enjoy good physical and mental health. There is also a need to invest in expanding the coverage of water and sanitation services (United Nations, 2020a).

Box 2

Universal transfers for children

Faced with the severe social effects of the pandemic, children and adolescents are overrepresented in the poor and vulnerable population. Without taking into account the potential effect of social protection measures adopted in countries, in 2020 51.3% of children and adolescents in Latin America would have been living in poverty. Safeguarding their well-being and comprehensive development should be a priority of countries’ policy agendas, both in the face of an emergency and in the recovery period. This implies strengthening intersectoral and comprehensive interventions and strategies to ensure full access of this population to key social services such as health and quality education, with a view to preventing and reversing school dropout; access to basic services; special protection in situations of grave violations and violence, and household income protection (ECLAC/UNICEF, 2020 and ECLAC/UNICEF/Office of the Special Representative of the Secretary-General on Violence against Children, 2020). While all these measures are necessary, in a critical scenario such as the current one, the discussion on the provision of a universal transfer for children takes on urgency.

Under the pillar of universal and comprehensive social protection systems, the lines of action of the Regional Agenda for Inclusive Social Development (ECLAC, 2020), adopted in 2019 in the framework of the Regional Conference on Social Development in Latin America and the Caribbean, include the imperative of creating a universal guarantee of basic income, including benefits and transfers for children and their families. Among other possible instruments, the gradual and progressive introduction of a universal transfer for children is being assessed. In line with the approach of the Secretary-General of the United Nations, the creation of a universal transfer for children could be seen as a first step towards a permanent universal basic income policy (United Nations, 2020).

Chapter IV of this edition of Social Panorama estimates the total cost of an annual cash transfer for all children and adolescents aged 0 to 17 in Latin America, which amounts to 5.5% of GDP for a transfer equivalent to one poverty line and 2.6% of GDP for a transfer equivalent to one extreme poverty line. The social impact of these transfers would be very positive: transferring the equivalent of one poverty line to the entire population aged 0 to 17 in Latin America for one year would reduce poverty in the region by 17 percentage points, and transferring the equivalent of one extreme poverty line would represent an impact of 7 percentage points. In the first case, the Gini coefficient in the region would decrease from 0.484 to 0.402, and in the second to 0.434.

These transfers would help prevent the serious effects of poverty on the cognitive and psychological development and health of children and adolescents (Save the Children, 2020). Data also show that benefits with broader coverage produce better results in terms of reducing poverty and inequality (ODI/UNICEF, 2020), and that universal transfers also entail lower administrative costs (Ortiz and others, 2017) and fewer errors of inclusion and exclusion of potential recipients (Coady, Grosh and Hoddinot, 2004; Bastagli, 2009; and ODI/UNICEF, 2020). While universal transfers to children alone would not eradicate poverty and reduce inequality, they can be considered a key component of universal social protection systems. The commitment to universal cash transfers would be similar to some long-established policies in developed countries, where universal family benefits, whether contributory or non-contributory (Filgueira and Rossel, 2017), are one of the crucial links in the policies of mature welfare states.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of, F. Bastagli, “From social safety net to social policy? The role of conditional cash transfers in welfare state development in Latin America”, IPC-IG Working Paper, No. 60, 2009; ECLAC/United Nations Children’s Fund (UNICEF), “Social protection for families with children and adolescents in Latin America and the Caribbean: An imperative to address the impact of COVID-19”, COVID-19 Report ECLAC-UNICEF, Santiago, 2020; ECLAC/UNICEF/Office of the Special Representative of the Secretary-General on Violence against Children, “Violence against children and adolescents in the time of COVID-19”, COVID-19 Report ECLAC - UNICEF - Office of the Special Representative of the Secretary-General on Violence against Children, November 2020; ECLAC, Regional Agenda for Inclusive Social Development (LC/CDS.3/5), Santiago, 2020; United Nations, Policy Brief: The Impact of COVID-19 on Latin America and the Caribbean, New York, 2020; D. Coady, M. Grosh and J. Hoddinott, Targeting of Transfers in Developing Countries: Review of Lessons and Experience, Washington, D.C., World Bank, 2004; F. Filgueira and C. Rossel, “Confronting inequality: social protection for families and early childhood through monetary transfers and care worldwide”, Social Policy series, No. 226 (LC/TS.2017/139), Santiago, CEPAL, 2017; Overseas Development Institute (ODI)/UNICEF, Universal Child Benefits: Policy Issues and Options, New York, 2020; I. Ortiz and others, “Universal social protection floors: costing estimates and affordability in 57 lower income countries”, EES Working Paper, No. 58, Geneva, Social Protection Department, International Labour Organization (ILO), 2017; Save the Children, Universal Child Benefits (UCBs): A foundation to end child poverty, 2020.

3. Closing gaps, fighting discrimination and focusing on rights

Given the trends analysed in this Social Panorama of Latin America, closing inequality gaps and fighting discrimination are essential. Social unrest is strongly linked to the perception that gross inequalities in all areas are the result of an unfair and biased social and economic system that prevents most people from accessing the opportunities and benefits of economic growth and technological progress (see box 3). Moreover, discrimination is considered one of the main mechanisms contributing to this state of affairs. In addition to people’s subjective perceptions, the evidence of how gender, race, territory and age, among other factors, interact to generate large inequality gaps in all spheres leads us to consider the role of social policies as one of the most important instruments for responding to people’s expectations of change.

Box 3

Digital gaps and digital inclusion

The pandemic has shown the opportunities provided by technology to address its effects on health, work and education. It has also revealed the existing gaps in terms of access to and use of digital technologies.

Although digital technologies can be a crucial instrument for post-pandemic recovery and for supporting a just transition to sustainable development, technological changes —which are advancing at an ever-increasing speed and whose economic or social effects cannot be predicted with certainty— can widen gaps, especially in the short term, as the costs of technologies are often initially very high and restrict access for the most disadvantaged sectors of the population (Martínez, Palma and Velásquez, 2020).

This determines the need to address the challenges of digital inclusion, respecting human rights in the digital environment (digital rights) (ECLAC, 2020a) and considering both physical accessibility and skills and the exercise of rights, so that no one is left behind when leveraging the opportunities offered by technologies. According to ECLAC (2020b, p.2), “[c]onnectivity is one of the conditions necessary for leveraging the value created by digital technologies”. It is therefore necessary to expand fixed broadband coverage, improve connection quality and make progress in universalizing access to devices and the Internet, so that the entire population can take advantage of the opportunities and benefits of being connected. Social inclusion goals must also be incorporated into technological innovation policies, to close access and skills gaps. People must be placed at the centre of digital development, with an emphasis on the digital inclusion of women, indigenous peoples, Afrodescendants, persons with disabilities, older persons, young people and residents of rural areas, among others.

There is an urgent need to strengthen the coordination mechanisms of the different government entities involved in the development and implementation of digital technology plans and policies. Progress is required in developing joint digital, social and economic strategies, with a participatory approach that involves all relevant actors, so that barriers and gaps are addressed from an intersectoral perspective. This implies considering social inclusion as an objective of technological development strategies and including digital elements in social policy. During the pandemic, for example, many services and benefits provided by the State have had to be digitized, without replacing traditional channels.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of R. Martínez, A. Palma and A. Velásquez, “Revolución tecnológica e inclusión social: reflexiones sobre desafíos y oportunidades para la política social en América Latina”, Social Polícy series, No. 233 (LC/TS.2020/88), Santiago, CEPAL, 2020; ECLAC, Building a New Future: Transformative Recovery with Equality and Sustainability (LC/SES.38/3-P/Rev.1), Santiago, 2020a; ECLAC “Universalizing access to digital technologies to address the consequences of COVID-19”, Special Report COVID-19, No. 7, Santiago, August, 2020b.

The enjoyment of rights, recognition and dignified and equal treatment must be the ultimate and explicit objectives of social policies. To that end, the targets of social policies and programmes must be considered rights-holding citizens. It is also necessary to actively promote mechanisms for accountability and transparency of social policies. These mechanisms should be accessible to participants and civil society in general, and should be actively disseminated by the very bodies that implement them. Otherwise, social policies can easily become mired in the mistrust that engulfs government institutions and their policies, or be subject to the vagaries of fake news, which undermine their legitimacy and effectiveness. The perception that such policies are susceptible to political manipulation and corruption and are even a simulation and thus not intended to address people’s real needs undermines their legitimacy in the eyes of participants and the general public. This in turn contributes to weakening their financing and implementation in the long term.

4. The care economy as a factor of reactivation

From the perspective of gender equality, it is essential that public policies establish mechanisms that institute the right to care and to be cared for, emphasizing the best interests of children, the right to a dignified life for older persons and the right to independent living for persons with disabilities. In addition to strengthening women’s autonomy, the inclusion of the care economy in crisis mitigation and recovery plans will lead to increased economic growth.

Today, more than ever, there is a favourable climate in the countries of the region for developing policies to distribute care work. In January 2020, at the fourteenth session of the Regional Conference on Women in Latin America and the Caribbean, the countries adopted the Santiago Commitment, a guide for countries to implement policies for sustainable reactivation with care at the centre.[17] On the basis of this and other agreements, the following recommendations have been made:

•Measure the multiplier effects of the care economy in terms of women’s labour market participation, well-being of the population, redistribution of income and time, economic growth and higher tax receipts.

•Counter the increasing precariousness of jobs related to this sector, improving working conditions and formalization.

•Encourage the incorporation of new technologies, training and certification of skills in the care sector.

•Guarantee the right to care for persons who need it throughout the life cycle, and the rights of caregivers, whether they are paid or unpaid.

•Universalize the coverage of care services and implement comprehensive care systems that include a collection of interconnected policies on time, resources, benefits and services related to the many care needs of the population.

•Incorporate a gender perspective into the design of programmes to overcome poverty, avoiding the use of conditionalities that place an excessive burden on women’s time.

•Foster the principle of co-responsibility between men and women and between the State, the market and families, and improve the supply of quality care services so that they reach the poorest sectors without relying on unpaid work by women.

•Expand coverage of social protection instruments to address the circumstances of precariously employed, informal, domestic female workers, those of women with no income of their own, those of women living in poor households and those of women with dependents.

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[1] Data available at 31 December 2020 (see [online] https://covid19.who.int/).

[2] In Brazil, at 7 December 2020, 203,107 people of African descent had been hospitalized with COVID-19 (38.3% of the total) and 73,333 had died from the virus (42.3% of the total). See [online] https://www.gov.br/saude/pt-br/media/pdf/2020/dezembro/11/boletim_epidemiologico_covid_40-1.pdf. In Colombia, at 14 September 2020, the Ministry of Health and Social Protection had reported 21,944 confirmed cases of COVID-19 (3% of the total) and 885 deaths from the virus among the Afrodescendent population. See [online] https://www.datos.gov.co/Salud-y-Protecci-n-Social/Casos-positivos-de-COVID-19-en-Colombia/gt2j-8ykr.

[3] Using the criterion of the population living in towns of 20,000 or more inhabitants, this percentage is around 70% for 15 Latin American countries (ECLAC, 2020f).

[4] This situation affects 7 out of 10 indigenous people in Guatemala, 6 out of 10 in Peru, 50% of indigenous people in Colombia and 20% in Mexico, proportions that are much higher than those recorded for non-indigenous people in each of these countries.

[5] Before the pandemic, a total of 4.2 million deaths were expected in Latin America and the Caribbean, based on the average annual estimate for the period 2015–2020 (United Nations, 2019b).

[6] Carfi and others (2020) and Yelin and others (2020) report on neurological, cardiovascular, respiratory, psychiatric and other sequelae.

[7] While the COVID-19 mortality rate refers to the number of deaths owing to the virus in relation to the total population, lethality refers to deaths from COVID-19 among those infected with the virus. Lethality is much more difficult to estimate, because it is hard to specify the size of the infected population (symptomatic and asymptomatic). Most countries concentrate their testing on symptomatic people and do not conduct universal or random testing on the general population (Peto, 2020).

[8] The total fertility rate is the average number of children that would be born to a woman belonging to a hypothetical cohort of women who during their fertile lives had children in accordance with the fertility rate by age over a specific study period and were not exposed to mortality risks from the time of their births to the end of their childbearing years.

[9] This was also found in studies such as that of Stone (2020) in relation to other epidemic outbreaks and those of Adsera and Menendez (2011) and Lee (1990) in relation to periods of economic crisis.

[10] As of June 2020, some countries in Latin America and the Caribbean began reopening schools gradually. In the Plurinational State of Bolivia, the government decided to end the school year early, in July, given the limited access to the Internet in households and the resulting difficulty of continuing the teaching process.

[11] The World Bank (2020) estimates that in Brazil, the loss of a quarter of the school year will result in an increase of 6% in the number of 10-year-old children in learning poverty (i.e. approximately 84,000 additional people). The losses associated with basic cognitive skills (such as reading and mathematics) are expected to be the easiest to quantify, but the costs related to learning other skills, such as socio-emotional skills, will likely be more difficult to estimate.

[12] Figure 11 shows the results of an index based on 15 self-efficacy indicators. For example, “if I need new software, I install it by myself”; “if I have a problem with digital devices I start to solve it on my own”; “if my friends and relatives have a problem with digital devices, I can help them”.

[13] In a survey of 7,734 teachers across Brazil, 83.4% said that they did not feel prepared for remote teaching. Even teachers with experience and training in technology and distance education said they had been caught off guard by the situation. The survey was conducted by the Peninsula Institute from 23 March–4 April and from 13 April–14 May 2020. See [online] https://institutopeninsula.org.br/apos-seis-semanas-de-isolamento-professores-brasileiros-nao-receberam-suporte-suficiente-para-ensinar-a-distancia-nem-suporte-emocional-das-escolas/.

[14] According to a survey of 500 households conducted from 7–10 May 2020 in the city and suburbs of Buenos Aires, 60% of households reported that they did schoolwork every day, 28% said they did it less frequently and 12% were unable to because they did not know how. In households with workers in the lowest occupational strata, only 51% did schoolwork, in contrast to households with workers in the non-professional and professional middle strata, where 73.8% said they did schoolwork. See the EDSA-COVID19 special telephone survey, Observatorio de la Deuda Social Argentina de la Universidad Católica Argentina [online] http://wadmin.uca.edu.ar/public/ckeditor/Observatorio%20Deuda%20Social/Presentaciones/2020/2020_OBSERVATORIO_EDSA%20COVID19_INFANCIA-V.pdf.

[15] In Mexico, according to a survey conducted in May 2020 via calls to mobile phone numbers selected randomly, which included a sample of 1,680 people aged 18 and over, only 21.4% of households with children and adolescents said they had no problems continuing their education. Among those who reported difficulties, these were the most frequently mentioned: 48.5% highlighted the lack of access to a computer or the Internet; 31.4%, the absence of teacher support; 21%, students’ difficulty in concentrating; 17%, lack of knowledge, and 14.9%, lack of books and teaching aids. See the Follow-up survey on the effects of COVID-19 on the well-being of children and adolescents [online] https://www.unicef.org/mexico/sites/unicef.org.mexico/files/2020-07/MAYO%20ENCOVID19Infancia-Presentaci%C3%B3n.pdf.

[16] For example, in Uruguay, the family allowances (under the Equity Plan) cover around 11% of the population at a cost equivalent to 0.33% of GDP, while the Uruguay Social card covers some 12% of the population and costs the equivalent of 0.15% of GDP (ECLAC, 2020g). In Mexico, starting in 2019, the coverage of cash transfers was expanded significantly, universalizing pensions for older persons and scholarships for high school students and persons with disabilities, among other measures.

[17] See [online] https://conferenciamujer.cepal.org/14/sites/crm14/files/20-00087_crm.14_santiago_commitment.pdf.

Chapter I

Poverty and inequality: recent trends and expected impacts of the coronavirus disease (COVID-19) pandemic

Introduction

A. Evolution of poverty, social stratification and inequality before the pandemic

B. Poverty, social stratification and inequality in times of COVID-19

Bibliography

Annex I.A1

Annex I.A2

Introduction

The COVID-19 crisis found Latin America in a period of low growth which, coupled with the worldwide economic downturn and the necessary mobility restrictions imposed by governments to minimize the public health effects of the pandemic, resulted in a sharp decline in activity, employment and income from work. In the countries of the region for which up-to-date information is available, the increase in unemployment was smaller than expected given the extent of the contraction in activity. This was the result of two factors: on the one hand, many of those who lost their jobs stopped looking for a new job; and on the other hand, a number of people stopped working but retained their employment contracts. According to current definitions, no one in either of these situations is counted as an unemployed person (see chapter II).

For 2020, the Economic Commission for Latin America and the Caribbean (ECLAC, 2020a) projected a 7.7% fall in gross domestic product (GDP) in Latin America (see table I.1). This would translate into a per capita GDP reduction of 8.5% for the region, signifying a decline to levels similar to those recorded in the mid-2000s, as well as an increase in poverty and inequality. The pandemic has also had a major impact on the economies of the Caribbean, mainly due to the collapse of the tourism sector (see box I.1).

In most countries in the region, governments have implemented a variety of programmes aimed at mitigating the effects of the pandemic and the contraction of economic activity on household incomes. These include employment protection programmes through payroll subsidies, pre-existing contributory social protection programmes and non-contributory social protection programmes. It was in the context of the last that multiple emergency transfers were established. Those transfers, which have mitigated the impact of the pandemic on poverty and extreme poverty, are analysed in detail in chapters III and IV. Therefore, the projected poverty and extreme poverty rates for 2020 take into account both the decline in household incomes and the partial compensation through extraordinary contributions made by the State.

Table I.1

Latin America(20 countries): projected change in GDP, 2020

(Percentages)

Country

Change in GDP

Country

Change in GDP

Argentina

-11.5

Costa Rica

-4.8

Bolivia (Plurinational State of)

-8.0

Cuba

-8.5

Brazil

-5.2

Dominican Republic

-5.5

Chile

-5.9

El Salvador

-8.6

Colombia

-7.1

Guatemala

-2.5

Ecuador

-9.0

Haiti

-3.0

Paraguay

-1.6

Honduras

-8.0

Peru

-13.4

Mexico

-9.0

Uruguay

-4.5

Nicaragua

-5.5

Venezuela (Bolivarian Republic of)

-28.0

Panama

-11.0

South America

-7.3

Central America and Mexico

-8.5

Central America

-6.6

Latin America

-7.7

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Preliminary Overview of the Economies of Latin America and the Caribbean (LC/PUB.2020/17-P), Santiago, 2020.

Box I.1

Economic impact of the COVID-19 pandemic in the Caribbean

The Economic Commission for Latin America and the Caribbean (ECLAC) believes that the Caribbean subregion will be severely impacted economically by the COVID-19 pandemic, with a fall in GDP of 7.9%. In a context of high vulnerability to external shocks and high levels of indebtedness —on average, debt represented 68% of gross domestic product (GDP) in 2019, with the highest percentages in Barbados (120%), Belize (99.7%) and Jamaica (92.2%)— fiscal consolidation remains a challenge for Caribbean economies in terms of the post-pandemic recovery process and ensuring key aspects of the 2030 Agenda for Sustainable Development.

The pandemic has dealt a severe blow to Caribbean countries due to the collapse of key sectors, in particular the tourism (including hotel and catering), the engine of most of these economies. The closure of tourism affected other sectors, including construction and some distribution and agricultural activities linked to tourism. It also resulted in reduced incomes for a significant number of people, including in the informal sector. Job losses in the tourism sector will disproportionately affect women, as, on average, 10.5% of the female labour force in the Caribbean works in accommodation and food services, compared with 4.6% for men.a

Added to all this is the Caribbean’s heavy exposure to the effects of climate change. The annual impacts of hurricanes and sargassum blooms on beaches cyclically affect a region still struggling to manage the social protection response implemented in response to recent disasters. The cost of recovery for Antigua and Barbuda, Dominica, the British Virgin Islands and St. Maarten following Hurricanes Irma and Maria in 2017 is estimated at more than US$ 7.7 billion. More recently, Hurricane Dorian struck the Bahamas, causing damage estimated at US$ 2.5 billion, an estimated US$ 717.3 million in losses, and additional costs of up to US$ 220.9 million.

The Caribbean (13 countries): projected change in GDP, 2020

(Percentages)

Country

Change in GDP

Country

Change in GDP

Antigua and Barbuda

-18.3

Jamaica

-9.0

Bahamas

-14.5

Saint Kitts and Nevis

-15.1

Barbados

-16.0

Saint Vincent and the Grenadines

-6.3

Belize

-15.5

Saint Lucia

-26.6

Dominica

-15.4

Suriname

-10.1

Grenada

-12.4

Trinidad and Tobago

-6.8

Guyana

30.9

The Caribbean

-7.9

The Caribbean (excluding Guyana)

-10.8

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Preliminary Overview of the Economies of Latin America and the Caribbean (LC/PUB.2020/17-P), Santiago, 2020.

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

a See International Labour Organization (ILO), ILOStat [online database] https://www.ilo.org/ilostat/.

A. Evolution of poverty, social stratification and inequality before the pandemic

After more than a decade of progress in reducing poverty and extreme poverty, both began to increase again in 2015. Regionwide, in 2019, poverty and extreme poverty increased by 0.7 and 0.9 percentage points, respectively; the gaps between men and women also widened. However, both trends and levels of poverty and extreme poverty vary greatly from country to country. With regard to income inequality, the pace of decline of the Gini index slowed considerably between 2014 and 2019, to around 0.5% per year.

1. Increase in poverty and extreme poverty and associated factors

In 2019, 30.5% of the population of Latin America, approximately 187 million people, were living in income poverty. Of those, 70 million, representing 11.3% of the population, were living in extreme poverty. This represented a 0.7 percentage point increase in poverty compared to 2018 and resumed the rate’s upward progress that started in 2015 and plateaued between 2016 and 2018. The extreme poverty rate rose by 0.9 percentage points over 2018, continuing a steady increase that also began in 2015, at an average rate of 0.7 percentage points per year (see figure I.1).

Figure I.1

Latin America (18 countries): poverty and extreme poverty rates and people living in poverty and extreme poverty, 2002–2019a

(Percentages and millions of people)

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

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

With regard to gender differences among the working-age population, which are reflected in the femininity index of poverty, poverty and, in particular, extreme poverty affect women much more than men. In 2019, the poverty rate was 12.7% higher in working-age women than in similarly aged men. This gap has remained relatively constant since 2014, when the poverty femininity index reached a value of 113.0. The gap between men and women is greater where extreme poverty is concerned. In 2019, the extreme poverty femininity index reached a value of 115.3, which, though lower than in 2014, was 1.3 percentage points higher than in 2018 (see figure I.2).

Figure I.2

Latin America (17 countries): poverty and extreme poverty femininity index, 2014–2019a

(Units)

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

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

Box I.2

Income poverty measurements by the Economic Commission for Latin America and the Caribbean (ECLAC)

The poverty and extreme poverty figures presented in this chapter are calculated by ECLAC on the basis of a common methodology, which is intended to provide a regional perspective that is as comparable as possible, taking into account the heterogeneity of the measurement tools and compilation procedures of each country’s own data.

The approach used by ECLAC to estimate poverty consists of classifying a person as “poor” when the per capita income of his or her household is below the poverty line.

The poverty lines represent the level of income that enables each household to meet the basic needs of all its members. The basic basket for measuring poverty is formed from a selection of food, including the goods required to meet the nutritional needs of the population, taking into account their level of physical activity, consumption habits, effective availability of food and food prices in each country and geographical area.

To the value of this basic food basket, known as the “extreme poverty line”, is added the amount required by households to satisfy basic non-food needs, in order to calculate the total value of the poverty line. To do this, the extreme poverty line is multiplied by a factor (called the Orshansky coefficient), which is the ratio of total spending to food spending for a reference population, and which has different values in each country and for urban and rural areas.

The extreme poverty and poverty lines are updated annually according to the cumulative variation in the consumer price index (CPI): the extreme poverty line is updated according to the variation in the CPI for food, while the part of the poverty line corresponding to spending on non-food is updated according to the variation in the CPI for non-food goods.

The percentages of households and of the population living in extreme poverty and poverty were obtained by contrasting the value of both poverty lines with the total per capita income of each household. Total household income is obtained by calculating the total income of household members (in cash and in kind) and includes income from work, income from retirement, pensions and other transfers, income from ownership of assets and other income (which includes imputed rent as part of total income).

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

Great heterogeneity in the levels of poverty and extreme poverty remains a feature of the region’s countries. Based on the latest ECLAC estimates for 14 countries (with data up to 2019), there are at least three identifiable groups of countries. The first group, consisting of Chile and Uruguay, has low levels of poverty (around 10% or lower), with extreme poverty below 2%. A second group of countries, with medium poverty levels, has poverty rates of around 20% and extreme poverty rates of around 5%. This second group comprises Argentina, Brazil, Costa Rica, the Dominican Republic, Ecuador, Panama, Peru and El Salvador. The third and last identifiable group of countries with higher levels of poverty, where the poverty rate is at or above 30% and the extreme poverty rate is over 10%, is made up of Bolivia, Colombia, Mexico, Honduras and the Plurinational State of Bolivia (see figure I.3).

Figure I.3

Latin America (15 countries): extreme poverty rate and poverty rate, 2019a

(Percentages)

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

a Data refer to 2019 except in the case of Chile (2017) and Mexico (2018).

According to ECLAC estimates, 5 of the 13 countries in the region with a household survey for 2019 showed a reduction in poverty of more than 1 percentage point compared with 2018. This is the case of El Salvador, with a decline of 4.1 percentage points, Honduras (-3.4 percentage points), the Plurinational State of Bolivia (-2.1 percentage points), the Dominican Republic (-1.9 percentage points) and Peru (-1.4 percentage points). In four other countries, poverty levels remained stable between 2018 and 2019, with changes close to 0. In this situation are Brazil (-0.2 percentage points), Paraguay (-0.1 percentage points), Panama (0 percentage points) and Uruguay (increase of 0.1 percentage points). The remaining four countries recorded rises in poverty: Costa Rica (0.4 percentage points), Ecuador (1.5 percentage points), Colombia (1.8 percentage points) and Argentina (2.8 percentage points) (see table I.2).

The variations seen in extreme poverty were smaller in magnitude. Only the Plurinational State of Bolivia and El Salvador recorded significant decreases (-2.6 and -2.0 percentage points, respectively), while Peru and the Dominican Republic recorded a drop of 0.7 points, and Costa Rica, 0.6 points. Four other countries recorded very slight variations, close to 0. This is the case for Paraguay (-0.3 percentage points), Panama (-0.2 percentage points), Uruguay (0 percentage points) and Brazil (increase of 0.1 percentage points). Slight increases were observed in Argentina (0.6 percentage points) and Honduras (0.6 percentage points), and more pronounced ones in Ecuador (1.1 percentage points) and Colombia (2.0 percentage points).

The variations recorded are similar to those found in official poverty estimates. As noted in previous editions of the Social Panorama of Latin America, the ECLAC estimates and the official estimates for each country tend to coincide in terms of tendency (positive or negative) and are quite close in magnitude. Considering all 12 countries for which both estimates are available, the tendency of the changes in the poverty rate and the extreme poverty rate between 2018 and 2019 coincides in 11 and 9 of them, respectively.[1]

Table I.2

Latin America (15 countries): poverty and extreme poverty rates according to estimates by ECLAC and official national figures, 2014–2019a

(Percentages)

ECLAC estimates

Extreme poverty

Total poverty

2014

2017

2018

2019

2014

2017

2018

2019

Argentinab

3.3

2.8

3.6

4.2

24.9

18.7

24.4

27.2

Bolivia (Plurinational State of)

14.9

16.4

14.7

12.1

33.7

35.1

33.2

31.1

Brazilc

3.3

5.5

5.4

5.5

16.5

20.3

19.4

19.2

Chile

2.0d

1.4

...

...

16.3d

10.7

...

...

Colombia

12.0

10.9

10.8

12.8

31.1

29.8

29.9

31.7

Costa Rica

4.1

3.3

4.0

3.4

17.5

15.4

16.1

16.5

Dominican Republice

9.7

6.3

5.0

4.3

32.9

25.0

22.2

20.3

Ecuador

5.9

7.0

6.5

7.6

23.4

23.6

24.2

25.7

El Salvador

11.7

8.3

7.6

5.6

44.5

37.8

34.5

30.4

Honduras

19.2

...

19.4

20.0

55.3

...

55.7

52.3

Mexico

13.0

...

10.6

...

45.2

...

41.5

...

Panama

9.2

6.9

6.8

6.6

19.7

15.6

14.6

14.6

Paraguay

7.7

6.0

6.5

6.2

22.3

21.6

19.5

19.4

Peru

5.1

5.0

3.7

3.0

19.5

18.9

16.8

15.4

Uruguay

0.2

0.1

0.1

0.1

4.5

2.7

2.9

3.0

Official estimates by countries

Extreme poverty

Total poverty

2014

2017

2018

2019

2014

2017

2018

2019

Argentinab

...

4.8

6.7

8.0

...

25.7

32.0

35.5

Bolivia (Plurinational State of)

17.1

18.4

15.3

12.9

39.1

42.2

39.9

37.2

Brazilc

4.5

6.4

6.5

6.5

22.8

26.0

25.3

24.7

Chile

4.5d

2.3

...

...

14.4d

8.6

...

...

Colombiaf

9.9

8.4

8.2

9.6

36.2

35.2

34.7

35.7

Costa Ricag

6.7

5.7

6.3

5.8

22.4

20.0

21.1

21.0

Dominican Republice

7.7

3.8

2.9

2.7

34.8

25.6

22.8

21.0

Ecuador

7.7

7.9

8.4

8.9

22.5

21.5

23.2

25.0

El Salvadorg

7.6

6.2

5.7

4.5

31.8

29.2

26.3

22.8

Hondurasg

39.7

40.7

38.7

36.7

62.8

64.3

61.9

59.3

Mexicoh

20.6

...

16.8

...

53.2

...

48.8

...

Panama

10.8

9.8

...

...

25.6

20.7

...

...

Paraguay

5.5

4.4

4.8

4.0

27.2

26.4

24.2

23.5

Peru

4.3

3.8

2.8

2.9

22.7

21.7

20.5

20.2

Uruguay

0.3

0.1

0.1

0.1

9.7

7.9

8.1

8.8

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG) and official figures; for Brazil: Brazilian Institute of Geography and Statistics (IBGE), “Síntese de indicadores sociais: uma análise das condições de vida da população brasileira 2020”, Estudos e Pesquisas, No. 43, Río de Janeiro, 2020.

a Countries for which ECLAC poverty estimates are available from 2016 onward.

b ECLAC estimates refer to the fourth quarter of each year. The official estimates refer to the second half of each year.

c Brazil does not have an official poverty estimate. The data refer to estimates from the Brazilian Institute of Geography and Statistics (IBGE) mentioned in the source on the basis of the lines used by the World Bank for low- and medium-low-income countries.

d Corresponds to 2013.

e The ECLAC figures for the Dominican Republic are based on the continuous national labour force survey (ECNFT) and refer to September of each year. The official annual estimates from 2016 onward are based on the national labour force survey (ENFT).

f New poverty series published in October 2020.

g Official national measurement reported as a percentage of households.

h In the case of Mexico, whose official figures are based on a multidimensional approach to poverty, measurements published by the National Council for the Evaluation of Social Development Policy (CONEVAL), the comparison uses as a non-official reference point the figures for “population below the minimum welfare line” (for extreme poverty) and “population below the welfare line” (for total poverty). https://repositorio.cepal.org/bitstream/handle/11362/44920/1/S1900554_en.pdf.

Taking as a benchmark the period 2014-2019, most of the countries analysed saw a decrease in poverty and extreme poverty. According to ECLAC, the poverty rate went down in 11 countries. The most significant decreases in absolute terms were observed in El Salvador (-2.8 percentage points per year), the Dominican Republic (-2.5 percentage points per year), Chile (-1.4 percentage points per year) and Panama (-1.0 percentage points per year). In relative terms, four countries, namely Chile (10%), the Dominican Republic (9.2%), Uruguay (7.8%) and El Salvador (7.3%), reduced poverty by more than 7% per year by 2019 compared with the 2014 figure.[2] In the case of Uruguay, although the reduction in absolute terms was low (-0.3 percentage points per year), poverty fell by one third of its original value (from 4.5% in 2014 to 3.0% in 2019). In Argentina, Brazil and Ecuador, the poverty rate increased by around 0.5 percentage points per year, while in Colombia it rose by 0.2 percentage points per year.

With regard to extreme poverty, reductions of at least 0.5 percentage points per year were recorded in five countries: El Salvador (-1.2 percentage points), the Dominican Republic (-1.1 percentage points), Bolivia (Plurinational State of) (-0.6 percentage points), Mexico (-0.6 percentage points) and Panama (-0.5 percentage points). Extreme poverty increased in five countries: Brazil (0.4 percentage points), Ecuador (0.3 percentage points) and Argentina, Colombia and Honduras (0.2 percentage points). In relative terms, the extreme poverty rate fell by more than 10% per year in El Salvador, the Dominican Republic, Peru and Uruguay, and increased by 10.8% per year in Brazil (see figure I.4).

Figure I.4

Latin America (15 countries): poverty rate, relative and absolute annualized variations, 2014–2019a

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

a The relative variation refers to the percentage variation in the poverty rate between the initial and end year. The absolute variation is the percentage-point difference between the two years. The data refer to the variations between 2014 and 2019, except for Chile (2013 and 2017) and Mexico (2014 and 2018). In the case of Brazil, the 2014 data correspond to the national household survey (PNAD) and the 2019 data to the continuous national household survey (PNAD Contínua).

The variations in poverty rates over time are linked to changes in average household income and in the distribution of income among households. Thus, a reduction in average household income will lead to a greater increase in the poverty rate when it is associated with a simultaneous process of income concentration, compared with a situation in which such a concentration does not occur. Likewise, an increase in average income in tandem with a reduction in inequality will lead to a greater reduction in the poverty rate than would be the case for each of the factors alone. Under these conditions, the evolution of poverty can be analysed by breaking down the variation in rate into two elements: the effect of the variation in average income (also known as the “growth effect”) and the effect of the variation in distribution.[3]

The relative variations observed in countries can be classified into three groups: marked reduction in poverty indicators (annual decrease of 5% or more), moderate reduction (annual decrease of less than 5%) and increase. In three of the four countries with marked reductions in poverty (Chile, Dominican Republic and El Salvador), the growth effect was the main explanation for poverty reduction. In Chile it accounted for 88% of the variation in the poverty rate, while in El Salvador it accounted for 78%, and in the Dominican Republic 68%. The fourth country in this group (Uruguay) the distribution effect was prevalent, accounting for 70% of the reduction in poverty in the period analysed (see figure I.5).

Figure I.5

Latin America (15 countries): annual variation in poverty rate and relative contribution of growth and distribution effects, 2014–2019a

(Percentages)

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

a Data refer to 2014–2019 except in the case of Chile (2013–2017) and Mexico (2014–2018). In the case of Brazil, the 2014 data correspond to the national household survey (PNAD) and the 2019 data to the continuous national household survey (PNAD Contínua).

In the group of countries with moderate poverty reduction (less than 5 per cent), the distribution effect was the most important factor. In four of the seven countries in this group (Peru, Paraguay, Mexico and the Plurinational State of Bolivia), income redistribution accounted for more than half of the variation. In two of them (Paraguay and the Plurinational State of Bolivia), the improvement in distribution even offset a decline in average household income, while in Panama the worsening of distribution lessened the strong positive effects of growth in average income. Lastly, in the group of countries for which poverty increased, this was due to a worsening of distribution, which, in the cases of Argentina and Ecuador, coincided with a reduction in income, while in Brazil it was barely offset by a slight increase in average income.

The entry into or exit from poverty experienced by households over time is fundamentally associated with changes in income that occur at the bottom of the distribution. Thus, a strong increase in the income of these households in real terms will result in a reduction in poverty. In an ideal situation, the determination of the income flows that affect these movements should be carried out on the same households at different periods by means of longitudinal surveys. Given that this type of monitoring is not possible with the information available in the region, an approximate procedure is used, which consists of analysing the changes between 2014 and 2019 for the same percentage of households in both years, even if they are not strictly the same households.[4]

The income streams analysed correspond to (i) labour income, which includes wages and income from self-employment; (ii) income from public and private transfers, which include retirement and contributory pensions, non-contributory transfers and other transfers (including remittances); and (iii) other income, consisting of income from assets (rents, interest, dividends and profits) and, fundamentally, imputed rent for the use of one’s own home.[5]

Among the countries with the largest reductions in poverty (5% or more), labour income was the main driver of income growth for the poorest households in Chile, the Dominican Republic and El Salvador. In the case of Uruguay, the fastest-growing items among the poorest households were public and private transfers (see figure I.6).

Figure I.6

Latin America (15 countries): annual variation in total per capita income among lower-income households, by source of income, 2014–2019a

(Annualized figures)

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

a Countries in order of scale of poverty reduction. Data refer to 2014–2019 except in the case of Chile (2013–2017) and Mexico (2014–2018).

b In Brazil, it is not possible to disaggregate transfers further for the entire period. Public and private transfers are therefore presented in the “other income” stream.

Among the countries with moderate poverty reduction, increases in labour income were the most important factor in Panama, Peru, Mexico and the Plurinational State of Bolivia. In Paraguay and Costa Rica, income from public and private transfers predominated, while in Honduras the largest increase was in the “other income” category. In the case of Honduras and Colombia, income from public and private transfers fell, owing to the contraction in non-contributory transfers. In the group of countries in which poverty increased between 2014 and 2019, with the exception of Colombia, there was a sharp decline in labour income, which was only partially offset by income from other transfers in the case of Ecuador.

In addition, the variations in the labour income of poor households can be disaggregated into two components: salaries and self-employed income. In most of the countries, the first component accounts for most of the variation in labour income, with the exception of the Plurinational State of Bolivia, Colombia, Honduras, Panama and Uruguay, where both components showed similar variations or there was a greater change in self-employed income (see figure I.7).

Figure I.7

Latin America (14 countries): annual variation in per capita labour income among lower-income households, by source of income, 2014–2019a

(Annualized figures)

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

a Countries in order of magnitude of poverty reduction. Data refer to 2014–2019 except in the case of Chile (2013–2017) and Mexico (2014–2018).

Although to a lesser extent, transfers were also important in the variation in income of poor households in some countries. In particular, changes in transfers from other households and non-profit institutions (international remittances, family support, scholarships, etc.) had an impact in terms of increasing the income of the poorest households in Chile, the Dominican Republic, El Salvador and Ecuador. In Panama, the decline in this source of income was more than offset by the increase in non-contributory transfers. The latter meant higher incomes among the poorest households in Paraguay and Costa Rica and income reductions in Honduras and Colombia. Given the low participation in this group of households, the increase in retirement pensions only resulted in a positive variation in the income of poor households in Uruguay and Panama (see figure I.8).

Figure I.8

Latin America (14 countries): annual variation in per capita transfer income among lower-income households, by source of income, 2014–2019a

(Annualized figures)

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

a Countries in order of magnitude of poverty reduction. Data refer to 2014–2019 except in the case of Chile (2013–2017) and Mexico (2014–2018).

2. Population groups with the highest poverty estimates

The estimates of poverty and extreme poverty are higher among women of working age, in rural areas, among indigenous people and the Afrodescendent population, children and adolescents, people with fewer years of schooling, and single-parent and extended households.

The higher incidence of poverty in rural areas is a structural characteristic of the region’s countries, owing mainly to low wages and incomes of the self-employed and the low coverage of social security and social assistance systems in those areas. In 2019, the poverty rate in rural areas was 45.7%, almost 19 percentage points above the value recorded in urban areas (26.9%). Likewise, extreme poverty in rural areas was 21.2%, more than 12 percentage points higher than the rate recorded in urban areas (9.0%).

In addition, the levels of poverty and extreme poverty among indigenous and Afrodescendants are higher compared to the rest of the population. In 2019, the poverty rate for indigenous people was 46.7% and the extreme poverty rate was 17.3%, equivalent to twice (2.1 times) and three times (3.1 times) the respective rates for the non-indigenous and non-Afrodescendent population in the nine countries overall. Likewise, the levels of poverty and extreme poverty in the Afrodescendent population greatly exceed those of the non-indigenous and non-Afrodescendent population in the group of six countries that include this characteristic, with rates among people of African descent being approximately 60% higher than those of the non-indigenous and non-Afrodescendent population (see figure I.9).

Figure I.9

Latin America (9 countries): incidence of poverty and extreme poverty by ethnicity and race, 2019

(Percentages)

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

a Weighted average for Bolivia (Plurinational State of), Brazil, Chile, Colombia Ecuador, Mexico, Panama, Peru, and Uruguay. The ethnicity indicator is constructed on the basis of ethnicity as reported by respondents and is not strictly comparable across countries.

b Weighted average for Brazil, Colombia, Ecuador, Panama, Peru, and Uruguay. The ethnicity indicator is constructed on the basis of ethnicity as reported by respondents and is not strictly comparable across countries.

In terms of age groups, poverty, especially extreme poverty, most affected the youngest population, particularly children and adolescents up to the age of 14. At the regional level, the probability of being in poverty and extreme poverty decreases as people age: the lowest values for both are observed in the 65-and-over age group. In 2019, the poverty rate in the group aged 14 and under was more than three times higher than in the group aged 65 and over, while the same ratio was four times higher for the extreme poverty rate (see figure I.10).

Figure I.10

Latin America (18 countries): incidence of poverty and extreme poverty by age group, 2019a

(Percentages)

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

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

The differences observed by age group are closely related to the forms of family organization. Indeed, poverty rates in single-person households and in households consisting of a head and spouse without children (characteristic of older persons or young adults) are, on average, three times lower than in other types of arrangements, which include two generations (two-parent households with children, single-parent households) or which may include three or more generations (extended) or persons without kinship ties (composite). In the case of the extreme poverty rate, the highest value is observed in single-parent households, most (85%) of which are headed by women who are responsible for children and adolescents.[6] In 2019, one in three single-parent households were in poverty, and almost half of those were in extreme poverty. This undermines the chances that the children and the adults in charge of them will lead a full life (see figure I.11).

Figure I.11

Latin America (18 countries): incidence of poverty and extreme poverty by type of household, 2019a b

(Percentages)

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

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

b Single-person households comprise only one person; Households with a childless head and spouse are made up of persons with a partner and no children present in the household; two-parent household with children corresponds to households made up of the head of household, their spouse and the children of one or both members of the couple; extended households are made up of members of three different generations (e.g. head, children and grandchildren); composite households include members who declare themselves to be “non-relatives” of the head of household.

Lastly, the educational attainment of the head of household (as an approximation of the educational level of the adults in the household) is also a differential factor when analysing poverty and extreme poverty estimates in the population. Of all the dimensions analysed in 2019, it is here that the greatest differences are recorded, with poverty rates in households whose heads did not complete primary education 12.4 times those of households whose heads completed tertiary education. Likewise, the incidence of extreme poverty was 13.5 times higher in the former than the latter. In turn, it is only in the group of households whose heads have completed secondary education that the incidence of poverty and extreme poverty is somewhat lower than average. Only in households whose heads have attained or completed tertiary education are these levels low in relation to the overall figure (see figure I.12).

Figure I.12

Latin America (18 countries): incidence of poverty and extreme poverty, by educational attainment of household head, 2019a

(Percentages)

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

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

3. Vulnerability of the middle-income sectors

In this scenario of increased poverty and inequality, broad sectors of the Latin American population live in chronic conditions of economic insecurity and high vulnerability to the loss of wage income. In 2019, 76% of the region’s population (467 million people) belonged to low or lower-middle income sectors; their per capita income was up to three times the poverty line and they lacked sufficient savings to cope with a crisis (ECLAC, 2020b).

The following is a brief analysis of recent changes in stratification by per capita income, with an emphasis on the low-income and middle-income strata. A strong and prosperous middle class is crucial to any successful economy and cohesive society, as it accounts for a significant share of consumption and spending on education, health and housing, and plays a key role in supporting social protection systems through tax contributions. However, the middle-class strata are particularly vulnerable to economic crises because their level of well-being largely depends on the jobs of their working-age members, and their access to social protection systems is limited.[7]

In Latin America, in line with the significant improvement in per capita household incomes since 2002, there has been not only a considerable reduction in poverty, but also in the size of low-income strata in general, with a resulting swelling of the middle class. In 2002, the lower strata comprised 71% of Latin Americans. That proportion fell by 10 percentage points between then and 2008 and declined more slowly over the next 11 years, reaching 56 per cent of the population in 2019.[8] At the same time, the middle sectors became increasingly important, increasing in size from 27% of the population in 2002 to 37% in 2008 and 41% in 2017 and 2019 (see figure I.13). This suggests that the gradual improvements in per capita household income led to a process of economic mobility that allowed about 15% of people to move into the next-highest income strata. However, that process of mobility has come to a halt in the last two years.

While part of the improvement in well-being in the lower strata, particularly among the poor and extremely poor, had to do with expansion of social protection systems and efforts to allocate public resources to poverty alleviation programmes, in the case of the middle class the improvements were more concerned with better working conditions, higher earned incomes, and increased female labour participation. Thus, the middle strata benefited mainly from the increase in the number of work income earners in households.

Figure I.13

Latin America (18 countries): a population by per capita income strata, around 2002, 2008, 2017 and 2019

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of the Household Survey Data Bank (BADEHOG), figures adjusted for population projections of United Nations, World Population Prospects 2019, New York, 2019 [online] https://population.un.org/wpp/ and estimated poverty trends in countries for which figures are not available for the years indicated.

a The countries included are: Argentina, Bolivia (Plurinational State of), Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay and Venezuela (Bolivarian Republic of).

4. Slow reduction in income inequality

Social inequality in Latin America is the result of a complex matrix of determinants that reflects the structural heterogeneity of its production systems and is sustained by a culture of privilege, perpetuated by public and private institutional arrangements that either favour that culture or are insufficient to significantly reduce gaps. Inequality is expressed in various dimensions, such as income and productive resources, work and employment, education, health care, housing and basic services, information and communication technologies, food security, social protection, possibilities of living a life free of violence, participation and agency, among others (ECLAC, 2019). Among them, income distribution is particularly important because income largely determines people’s access to the different goods and services necessary for life and to opportunities to develop and achieve the life to which they aspire.

Income gaps in the population are usually summarized in inequality indices, such as the Gini index, in which a value of 0 represents no inequality and 1 denotes maximum inequality. According to that indicator, income inequality, as measured by household surveys, declined significantly between 2002 and 2014 in the 15 countries analysed, at a rate of 1.1% per year. While that trend continued between 2014 and 2019, the rate of decline in inequality slowed considerably, to 0.5% per year (see figure I.14).

Figure I.14

Latin America (15 countries): Gini inequality index, 2002–2019a

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

Note: For details of the figures by country presented in the figure, see table I.A2.3 in annex.

a The Gini index is calculated including incomes equal to zero.

b Urban total.

c The figures for 2002 and 2014 were adjusted for the difference between the national household survey (PNAD) and the continuous national household survey (PNAD Continua) of 2014, to enable their comparison with 2018 figures.

d Figures from 2010 onward are not comparable with those of previous years.

e Figures for 2016 and 2018 are not comparable with those of previous years.

f Figures for 2017 and 2019 are not strictly comparable with those of 2002 to 2014.

g Figures for 2002 refer to urban areas.

h Simple average based on the data available for the nearest year for each of the 15 countries.

The way in which national income is distributed among households is conditioned by various structural factors, which limit the possibility of generating profound changes in short periods of time. Rather than a true reflection of a change in income distribution, the changes observed in inequality indicators over a short period of time are often the result of the characteristics of the household survey. Even so, the recent increase in indicators in several countries is striking, reversing the trend of narrowing inequality that has characterized the region for several years. Using information from the 2017 and 2019 household surveys as a reference, four countries showed a decrease in the Gini index (between 4% and 6%), three showed no change and seven registered an increase (between 1% and 3%) (see figure I.15). These results imply that, even without considering the expected reversal in the context of the pandemic, the region is not making significant progress in reducing inequality in income distribution. This not only narrows the possibility of meeting Sustainable Development Goal (SDG) 10, but also diminishes the feasibility of reducing poverty and extreme poverty. Meeting the goal of eradicating extreme poverty is not feasible without visible progress in reducing income gaps, especially in a context of low growth in average household income.

Figure I.15

Latin America (14 countries): Gini inequality index, 2017 and 2019a

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

a The Gini index is calculated including incomes equal to zero. Pink dots represent a cumulative decrease of 3% or more in the Gini index. Blue dots represent an increase of 3% or more in the same indicator.

Inequality trends become even less favourable when, in addition to household surveys, other data sources, such as tax records and national accounts, are taken into account (see box I.3).

Box I.3

Income inequality estimated based on combined data sources

Various editions of the Social Panorama of Latin America have drawn attention to the underestimation of income inequality measured exclusively on the basis of household surveys. This is due to the limitations of this type of source in capturing information on the largest income earners, particularly with respect to income from asset ownership. To capture income inequality more fully, a number of studies have combined information from household surveys with information from income tax records, which generally better captures the situation of the highest income earners, and with national accounts, which provide a benchmark for the total amount of income received by households.

A recent study uses available information from 10 countries in the region to estimate income inequality by combining data from standardized surveys of the Household Survey Data Bank (BADEHOG) of the Economic Commission for Latin America and the Caribbean (ECLAC), administrative records and national accounts (De Rosa, Flores and Morgan, 2020). The use of supplementary sources allows for various corrections to the income measured on the basis of the surveys. Each of the processes applied results in a further increase in inequality: correcting the data for the richest recipients based on information from tax records; increases the Gini coefficient by an average of 6% (across all countries and years of the study); scaling the corrected values from the survey to the household income totals by source obtained from the national accounts generates an additional increase in the Gini index of 5% on average; and, finally, the imputation of missing income (above all, undistributed corporate earnings) to arrive at the concept of national income represents a further 4% increase in the Gini index (see figure).

Latin America (10 countries): effect of combining household survey data with information from administrative records and national accounts on the Gini index, 2000-2018

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of M. De Rosa, I. Flores and M. Morgan, “Inequality in Latin America revisited: insights from distributional national accounts”, Technical Note, No. 2020/02, World Inequality Lab, 2020.

The results of the application of this methodology show that, in some countries, the reduction in inequality since 2000 is not as pronounced when the Gini index is estimated using a combination of these sources, as compared with estimates obtained using household surveys alone, particularly in Chile and Peru. Moreover, in cases such as Brazil and Mexico, inequality not only did not decrease, but actually increased, thus generating a new call for a closer look at the processes of effective income distribution in the countries of the region.

While the application of this new methodology helps to complement the perspective on household income distribution, it should not be overlooked that both national accounts and tax records have different types of limitations. Generating more accurate estimates of income distribution requires continuous improvement of household surveys to adequately capture different income sources. It is also essential to examine in detail the assumptions used to estimate household income in national accounts and to establish the source of discrepancies with the amounts reported in surveys. Finally, it is necessary to promote the disclosure of tax information in the countries of the region and generate better background information for its joint use with other data sources.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of M. De Rosa, I. Flores and M. Morgan, “Inequality in Latin America revisited: insights from distributional national accounts”, Technical Note, No. 2020/02, World Inequality Lab, 2020.

The inequality in income distribution is evident when comparing the proportion of total income received by households in the highest and lowest income groups. The income share of the first three quintiles is lower than their share of the population (i.e. 60%). The first quintile receives only between 3% and 6% of total income, while that proportion does not exceed 10% in the second quintile. Only the income share of the fourth quintile, between 18% and 22%, is similar to its share of the total population. In contrast, the highest-income quintile accounts for between 46% and 58% of total income (see figure I.16).

Figure I.16

Latin America (15 countries): share of total income, by quintile, 2019a

(Percentages)

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

a Household quintiles organized by per capita income. Countries ordered according to share of fifth quintile. Information for 2019 or most recent year.

Some of the sources of income received by individuals are distributed across quintiles in a similar way to total income. In the regional average, this is true for earned income and imputed rent (the value assigned to households that own the dwelling in which they reside). In Latin America, the first quintile receives on average 3% of wages and 5% of own-account income, while the richest quintile receives 51% and 53% of those sources, respectively. Likewise, insofar as retirement pensions (contributory old-age pensions) are linked to the trajectory of people’s labour income, they are as or more concentrated than labour income. On average, the first quintile receives only 1% of the total amount from this source, while the fifth quintile receives 68%. The most unequally distributed source of income is property income, which is practically non-existent in the first two quintiles, compared with 82% for the fifth quintile.

Cash transfers made by governments as part of their social protection programmes stand out as the only source of income with the highest share among low-income households. On average, the first two quintiles capture a little more than 50% of this source. Households also receive transfers from other households (particularly remittances from abroad) and institutions. Although to a lesser extent than labour income, most of these transfers also occur in the upper quintiles (see figure I.17).

Figure I.17

Latin America (15 countries): distribution of income from each source among quintiles, 2019a

(Percentages)

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

a Household quintiles organized by per capita income. Simple average of 15 countries in the region, with information as of 2019 or the most recent year. Sources of income ranked by their share of total income. The countries included are: Argentina, Bolivia (Plurinational State of), Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru and Uruguay.

On average, most household income comes from paid work, whether as a dependent employee (48%) or self-employed (23%). The rest of the income corresponds to imputed rent for home ownership (12%), even though this is not freely available monetary income; contributory pensions (retirement pensions) (8%); public and private transfers (7%) and property income (2%).

This structure has some particular characteristics depending on the level of income received. In the first quintile, 60% of income comes from paid work, in practically equal parts for salaried employment and self-employment. Public transfers and transfers from other households each account for about 10% of income, while contributory pensions and income from asset ownership together account for barely 3% of total income in the first quintile.

In contrast, in the fifth quintile, 70% of income comes from employment, two thirds of which corresponds to income from dependent work. In this case, the sum of private transfers (4%) and public transfers (less than 1%) has a lower share than contributory pensions (10%). Property income represents 4% of total income, according to household surveys, although this value is underestimated.[9] Imputed rent is also a significant source of income for the fifth quintile, with a 12% share (see figure I.18).

Figure I.18

Latin America (15 countries): composition of income by quintile and source of income, 2019a

(Percentages)

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

a Household quintiles organized by per capita income. Simple average of 15 countries in the region, with information as of 2019 or the most recent year. The countries included are: Argentina, Bolivia (Plurinational State of), Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru and Uruguay.

B. Poverty, social stratification and inequality in times of COVID-19

Due to the effects of the pandemic, and despite social protection measures to address it, poverty and extreme poverty will reach levels not seen for 12 and 20 years, respectively, and there will be a deterioration in distribution in most countries. The low-income strata grew by 4.5 percentage points (61% of the population), while the middle-income strata contracted by a similar amount. About 115 million people are in a worse economic situation, 59 million of whom were in the middle-income strata in 2019.

1. Regionwide increase in poverty and extreme poverty

The job losses and reduction in labour income suffered by households as a result of the COVID-19 pandemic have particularly affected the region’s lower income strata. Projections made in order to estimate the impact of the pandemic on incomes in 2020 suggest that the crisis will lead to a sharp increase in poverty and extreme poverty in the countries of the region.

The poverty projections are based on the model whose methodology is detailed in Annex I.A1 and update those previously presented by ECLAC in 2020 (2020b, 2020d and 2020e). On this occasion, the simulation model also considers monetary transfers to households to cope with the reduction in labour income (see chapters III and IV). These have been granted with very different criteria in each country, so some simplifying assumptions were adopted for their inclusion in the projections. In particular, the monthly amount of non-contributory cash transfers received per person in each country was estimated and distributed among individuals according to the quintile to which they belonged (based on their 2019 per capita income).

In 2020, the extreme poverty rate is projected to reach 12.5% and the poverty rate 33.7%. This would mean a total of 209 million poor people at the end of 2020, 22 million more than the previous year. Of that total, 78 million people would be in extreme poverty, 8 million more than in 2019 (see figure I.19).

Figure I.19

Latin America (18 countries): rates of poverty and extreme poverty and people living in poverty and extreme poverty, 2019-2020a

(Percentages and millions of people)

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

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

b 2020 values based on projections that do not take into account the effect of emergency cash transfer programmes.

c 2020 values based on projections that take into account the effect of emergency cash transfer programmes.

In terms of poverty rates, it is necessary to go back to 2008 to find a similar rate (33.5%), which implies a 12-year reversal for the region. That reversal is even greater in the case of extreme poverty, for which one has to go back 20 years, to 2000, to find a similar rate (12.4%). The projected number of people living in poverty in 2020 is at a similar level to that of 2005 (210 million). For people in extreme poverty, the estimate for 2020 is the highest in the series, exceeding the previous peak recorded in 2019. All this puts at risk the achievement of the first Sustainable Development Goal (see box I.4).

The increase in poverty and extreme poverty would have been greater had measures to transfer emergency income to households not been implemented. Projections that only take into account the impact of the pandemic on employment and labour income show that the poverty rate for 2020 was 37.2% of the population, with 15.8% in extreme poverty. That would mean a total of 230 million poor people by the end of 2020, 21 million more than projected, taking into account cash transfer programmes. Similarly, the total number of people living in poverty would have reached 98 million, 20 million more than projected, taking into account the transfer programmes.

Box I.4

Perspective and impact on the implementation of Sustainable Development Goal (SDG) 1

The projected increase in extreme poverty and poverty due to the COVID-19 pandemic has implications not only in 2020, but also in the years that follow. This is particularly relevant in the context of the Sustainable Development Goals (SDGs) adopted by UN Member States in 2015, one of the targets of which is to eradicate extreme poverty by 2030.

It is possible to estimate the level of extreme poverty in the region in 2030 by applying different combinations of average household income growth and distributional change to the 2020 projections. One scenario, with per capita income growth of 1% per year and no change in income concentration, would only see the extreme poverty rate pushed back to 11.5%, a proportion even higher than in 2019.

Assuming the same annual per capita GDP growth rate (1%), but projecting a decline in inequality equivalent to a reduction in the Gini coefficient of 1% per year, the estimated incidence of extreme poverty in 2030 would be 9.6%. The importance of adopting policies that improve income distribution to help lower poverty is evident, as a small reduction in the Gini index would reduce projected extreme poverty by almost 2 percentage points by 2030.

In contrast to what was observed up to 2019, even annual GDP growth of 5% and a 1.5% annual reduction in the Gini index –which would have been sufficient to achieve the expected target for 2030 (assumed to be 3% for the practical purposes of the simulation)– would not be enough to eradicate extreme poverty, the incidence of which would be 5.7% (see figure).

Latin America (18 countries):a projected extreme poverty rate in 2030 with different scenarios of per capita GDP growth and changes in income distribution

(Percentages)

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

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

If, before the pandemic, the goals of eradicating extreme poverty and halving total poverty already required higher levels of GDP growth and reduced inequality than have been recorded in the region in recent years, the current situation has significantly increased the challenge. However, the positive effects of direct cash transfer programmes in recent months show the potential of this type of public policy action to fill the income gaps that enable poverty and extreme poverty to be overcome and make achieving SDG 1 more feasible.

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

2. Downward social mobility

The contraction of economic activity due to the COVID-19 pandemic and the resulting job losses and reduction in labour income will lead to an increase not only in poverty and extreme poverty, but also in the size of the population in low-income strata and in downward mobility in the middle and upper-middle strata (poor people who are not in extreme poverty and low-strata households above the poverty line). This is because middle-sector and upper-middle-sector families primarily earn their income through work, mostly salaried labour, and are often not beneficiaries of social protection policies and programmes.

It is estimated that, between 2019 and 2020, the low-income strata will have increased by 4.5 percentage points (about 28 million additional people), at the expense of a contraction in the middle sectors by a similar proportion (-4.1% and -25 million people, respectively).[10] Out of a total of around 59 million people who in 2019 belonged to the middle sectors and who in 2020 are experiencing a process of downward economic mobility, just over 25 million people have done so without falling out of the middle sectors, while just over 3 million have fallen directly into poverty or extreme poverty and the rest have moved into the lower stratum above the poverty line. Although, generally speaking, emergency social protection measures mainly targeted those in poverty or with a high probability of falling into poverty, those measures were able partially to contain the contraction of the middle-income strata. In short, between 2019 and 2020, the vulnerable population living on incomes up to three times the poverty line increased by 3.3 percentage points, equivalent to 20 million people (see figure I.20).

Figure I.20

Latin America (18 countries):a population by per capita income strata, 2019 and 2020

(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), figures adjusted for population projections of United Nations, World Population Prospects 2019, New York, 2019 [online] https://population.un.org/wpp/ and estimated poverty trends in countries for which figures are not available for the years indicated.

a The countries included are: Argentina, Bolivia (Plurinational State of), Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay and Venezuela (Bolivarian Republic of).

b Owing to the use of different population frameworks, the figures included here may not coincide with those presented in figure I.19.

Given that there is no clear likelihood of a rapid and full recovery of the labour market in the short term, attention should be given to economic recovery processes and to effectively increasing and maintaining the coverage of emergency social protection programmes implemented by the vast majority of countries in the region. These should include sufficient transfers or other measures, such as freezing basic expenditures or deferring debt, to prevent a large proportion of vulnerable households from suffering significant asset losses and, ultimately, a long-term decline in their level of well-being. In the medium and long term, it is also necessary to move towards the construction of comprehensive and universal social protection systems.

3. Deterioration of income distribution

Forecasting the effect of the COVID-19 pandemic on household income distribution is not a simple exercise, due to the multiplicity of factors involved in determining income distribution, the great dynamism of events and the high uncertainty. However, it is of interest to assess the results of the simulation model described in Annex I.A1 and to see to what extent they suggest a distributional deterioration in 2020.

The simulation model for 2020 assumes that household income will fall by the same amount as projected output per person. In order to distribute this reduction among individuals, a differentiated impact is applied among them, according to the sector of economic activity in which they work and the characteristics of their employment.

A first important factor is the loss of labour income due to an interruption of employment. According to the projections made, the proportion of people who would stop earning labour income in the first quintile (based on 2019 incomes) would increase by 5.7 percentage points, a value that decreases considerably in the subsequent quintiles. In the fifth quintile, the proportion of people with no income is estimated to increase by 0.7 percentage points.[11]

A second element is the fall in labour income of those who have remained in employment during the pandemic. As a result of the significant slump in demand and the decline in possibilities for people to carry out their work activities as normal, there was a 15% contraction in the average labour income of employed persons. For people in the first quintile (for 2019), the reduction was 42%, while for those in the fifth quintile, the estimated average reduction is about 7% (see figure I.21).

Figure I.21

Latin America (18 countries): unemployment rate and average income per employed person, by quintile (for 2019), 2019 and 2020a

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

a In the projection model, the unemployment rate includes all persons who have lost their jobs, without distinguishing whether they looked for a new job (and are therefore unemployed) or not (and are therefore out of the labour force). The countries included are: Argentina, Bolivia (Plurinational State of), Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay and Venezuela (Bolivarian Republic of).

As a result of the labour income trends described above, one would expect total per capita income inequality to increase in 2020, resulting in an average Gini index 5.6% higher than that recorded in 2019. However, if one includes transfers made by Governments to mitigate the loss of labour income, whose distribution tends to be concentrated in low- and middle-income groups, the average increase in the Gini index for the region would be 2.9%.

These results do not take into account other factors of great significance for income distribution. One of them is remittances from abroad, which have behaved differently than expected. In April 2020, ECLAC warned that remittance flows to Latin America and the Caribbean could contract by 10%–15% in 2020 (ECLAC, 2020e). Nevertheless, the most recent data show an increase in remittances with respect to 2019 in the case of Mexico and some Central American countries (Fundación BBVA Bancomer/CONAPO, 2020; BCRD, 2020; BCR, 2020).

Another element that affects income distribution is income from ownership of physical and financial assets. Although the region’s stock markets experienced a significant fall in the second quarter of 2020, the subsequent recovery could lead to an increase in this type of income, which is concentrated among wealthier households (see box I.5 for an illustration of the importance of property income).

Box I.5

Distribution of property income and wealth: recent evidence from Mexico

Income from asset ownership is the least equally distributed source of income and is a particularly important source for the wealthiest households. Given the limitations of household surveys in adequately reflecting income from asset ownership, the information available in the national accounts, in particular the household sector account, offers a better appreciation of the share of this source in household income. Likewise, the concentration of physical assets provides additional information for better understanding economic inequality.

According to the national accounts of Mexico, 47% of national household income (i.e., market resources, before transfers, that families have for consumption and spending) is self-generated, as resources for their own consumption or through family businesses; 30% corresponds to wages, of which slightly more than half comes from private sector jobs; and 23% is property rental income (see figure 1).

Figure 1

Mexico: allocation of primary income to households, by source, 2018

(Percentages of national household income)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of National Institute of Statistics and Geography (INEGI), “Cuentas por sectores institucionales: saldos contables por sector institucional, base 2013”, 2018 [online database] https://www.inegi.org.mx/temas/si/.

According to the same source of information, in 2018, about 18 million private sector workers received 2.7 trillion pesos in remunerations, which amounts to approximately US$ 630 per month. In contrast, just over 215,000 families received 3.4 trillion pesos in dividends, about US$ 27,000 per month.

Also in 2018, the resources that residents in Mexico had invested in equity holdings and investment funds amounted to 25 trillion pesos (US$ 1.3 trillion), a sum equivalent to 110% of national income. That wealth (financial assets) is also highly concentrated. According to information from the National Banking and Securities Commission (CNBV), in 2018 there were only 270,000 contracts in the country to manage resources in brokerage firms, 81.9% of which corresponded to amounts of less than 15 million pesos. At the other extreme, more than two-thirds of the total amount of assets (70.2%) was concentrated in about 23,000 contracts (8.5% of the total). This resulted in a very high Gini coefficient of 0.75. In 2019, distribution improved slightly, as the share of contracts for less than 15 million pesos increased to 83.6%. However, the Gini coefficient remained virtually unchanged at 0.74 (see figure 2).

Figure 2

Mexico: amount invested in brokerage firms, by investment range in millions of pesos, 2017–2019

(As a percentage of total)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of National Banking and Securities Commission, “Portafolio de información” [online] www.cnbv.gob.mx/Paginas/PortafolioDeInformacion.aspx.

This distribution generates profound inequality in Mexico. The majority of families whose income depends on work receive a small proportion of the value added generated, while a minority that owns financial assets concentrates a high proportion of the value generated, through the dividends paid by companies.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of National Institute of Statistics and Geography (INEGI), “Cuentas por sectores institucionales: saldos contables por sector institucional, base 2013”, 2018 [online database] https://www.inegi.org.mx/temas/si/and National Banking and Securities Commission, “Portafolio de información” [online] www.cnbv.gob.mx/Paginas/PortafolioDeInformacion.aspx.

Bibliography

BCR (Central Reserve Bank of El Salvador) (2020), “Remesas y comercio exterior a octubre 2020”, November [online] https://www.bcr.gob.sv/bcrsite/uploaded/content/category/876923494.pdf.

BCRD (Central Bank of the Dominican Republic) (2020), “Banco Central informa que continúa mejorando el flujo de divisas: remesas crecen 37.1 % en septiembre de 2020 con respecto a septiembre de 2019”, 13 October [online] https://www.bancentral.gov.do/a/d/4931-banco-central-informa-que-continua-mejorando-el-flujo-de-divisas-remesas-crecen-371--en-septiembre-de-2020-con-respecto-a-septiembre-de-2019.

DGEEC (Department of Statistics, Surveys and Censuses) (2020), Boletín Trimestral de Empleo: EPHC 2do. Trimestre 2020, Asunción, August.

ECLAC (Economic Commission for Latin America and the Caribbean) (2020a), Preliminary Overview of the Economies of Latin America and the Caribbean, 2020 (LC/PUB.2020/17-P), Santiago.

____(2020b), “The social challenge in times of COVID-19”, COVID-19 Special Report, No. 3, Santiago, May.

____(2020c), “Sectors and businesses facing COVID-19: emergency and reactivation”, COVID-19 Special Report, No. 4, Santiago, July.

____(2020d), “Addressing the growing impact of COVID-19 with a view to reactivation with equality: new projections”, COVID-19 Special Report, No. 5, Santiago, July.

____(2020e), “Measuring the impact of COVID-19 with a view to reactivation”, COVID-19 Special Report, No. 2, Santiago, April.

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

ECLAC/IPEA/UNDP (Economic Commission for Latin America and the Caribbean/Institute of Applied Economic Research/United Nations Development Programme) (2002), Meeting the millennium poverty reduction targets in Latin America and the Caribbean, ECLAC Books, No. 70 (LC/G.2188-P), Santiago, February.

Fundación BBVA Bancomer/CONAPO (National Population Council) (2020), Anuario de Migración y Remesas: México 2020, Mexico City, August.

IBGE (Brazilian Institute of Geography and Statistics) (2020a), “Síntese de indicadores sociais: uma análise das condições de vida da população brasileira 2020”, Estudos e Pesquisas, No. 43, Rio de Janeiro.

____(2020b), “Junho 2020: Pesquisa PNAD COVID 19 IBGE”, Rio de Janeiro, 23 July [online] https://agenciadenoticias.ibge.gov.br/media/com_mediaibge/arquivos/8aa598ff96d7b31bd752c988f2e39572.pdf.

ILO (International Labour Organization) (2020), “Monitoring labour markets amid lockdowns to contain the COVID-19 virus: essential labour force survey content and treatment of special groups”, Technical Note, April.

____(2013), “Resolution concerning statistics of work, employment and labour underutilization”, nineteenth International Conference of Labour Statisticians, Geneva, October [online] https://www.ilo.org/wcmsp5/groups/public/---dgreports/---stat/documents/normativeinstrument/wcms_230304.pdf.

INE of Chile (National Institute of Statistics of Chile) (2020), Boletín Estadístico: Empleo Trimestral, No. 261, Santiago, 31 July.

INE of Uruguay (National Institute of Statistics of Uruguay) (2020), “Actividad, empleo y desempleo: junio 2020”, Boletín Técnico, Montevideo, 21 August.

INEGI (National Institute of Statistics and Geography) (2020), “Encuesta Nacional de Ocupación y Empleo (Nueva Edición) (ENOEN): resultados de julio 2020”, September [online] https://www.inegi.org.mx/contenidos/programas/enoe/15ymas/doc/enoe_n_presentacion_ejecutiva_0720.pdf.

Ravallion, M. and G. Datt (1992), “Growth and redistribution components of changes in poverty measures”, Journal of Development Economics, vol. 38, No. 2, Amsterdam, Elsevier, April.

Annex I.A1

Methodology used by ECLAC to project the impact of the COVID-19 pandemic on poverty

The poverty and inequality estimates presented in this chapter are based on information provided by household surveys collected by national statistics offices and other public agencies in the countries of the region and compiled in the Household Survey Data Bank (BADEHOG) of the Economic Commission for Latin America and the Caribbean (ECLAC).

For years in which a household survey is not available, ECLAC usually estimates poverty by means of a model that modifies the income measured in the most recent household survey available, using two parameters that represent the rate of income growth and the expected distributional change, respectively.

Per capita income for period t+1 is simulated using the following expression (ECLAC/IPEA/UNDP, 2002):

yit+1 = (1 + β) [(1 − α) yit + αμt] (1)

where yit is the income per person of each household i in year t, mτ the average income per person of all households in year t, α a parameter that expresses the percentage reduction in the Gini index and β the parameter that accounts for the growth rate of income per person. Projected incomes make it possible to determine the number of poor people in period t+1 and to calculate the new poverty rate.

The parameter β corresponds to the variation projected by ECLAC in per capita GDP (in constant 2010 dollars) for the corresponding year. Since the growth rate is expressed in real terms, the value of the poverty line remains constant. The parameter α is assumed to be equal to 0 in periods of economic growth and a distributive deterioration is assumed in periods of economic contraction.

To project the impact of the pandemic on income in 2020, some modifications were made to the model to first simulate changes in individual labour income and then reconstruct household income. The model maintains the principle that household income per person varies in the same proportion as GDP per capita. The difference lies in the way in which this variation in income is distributed among individuals and households, which no longer depends on a single parameter, but is simulated on the basis of different steps that include estimates of the risk of job loss, the consequent extent of the reduction in income and the contributions made by Governments in the form of cash transfers. These three elements have an impact on household income, and their consideration is based on various studies that suggest a greater decline in employment and income among salaried and self-employed workers who work in the informal sector, in low-productivity occupations and in certain sectors of activity.

To do this, based on the 2019 household survey data (or the most recent available), each person classified as employed is assigned a score for their “risk” of job and income loss, between 0 and 100, considering three criteria:

i)Sector of economic activity: a higher risk (70 points) is assigned to persons employed in the commerce, hotel and restaurant, and transport and communications sectors. A medium risk (50 points) is assumed for the manufacturing, construction, financial intermediation and public administration sectors. A low risk (30 points) is assumed for the primary sector, agriculture, mining and the electricity, gas and water sector.[12]

ii)Employment productivity: a higher risk (between 5 and 15 additional points) is assigned to non-professional and non-technical workers who are self-employed or salaried workers in establishments of up to five persons (i.e., the criteria used to define the indicator for low-productivity jobs).

iii)Labour income: a higher risk (between 5 and 15 additional points) is assigned to employed persons whose labour income is below the median for the sector in which they work, as a predictor for occupations that typically offer lower social protection.

A normal distribution is assumed for each of the three risk-score categories in order to introduce a random element into the assignment.

Once the risk scores have been assigned, the following steps are performed:

–Change the activity status from employed to unemployed, so that the unemployment rate matches the projected rate implied in ECLAC (2020a).

–Modify the average labour income of employed persons, according to the level of risk estimated above.

–Modify transfer income. Other non-labour income (pensions, other transfers, capital income, imputed rent) is assumed to remain at the same levels as in 2019.

–Iteratively calculate the final variation in average labour income so that the variation in per capita household income is equal to the projected variation in per capita GDP (ECLAC, 2020a).

Because public transfers granted to alleviate income losses have been applied with varying criteria in each country, the simulation of this component adopts some simplifying criteria. In particular, the monthly amount per person corresponding to these transfers in each country is estimated on the basis of the information presented in chapters III and IV and that obtained from the COVID-19 Observatory in Latin America and the Caribbean and the Social Development and COVID-19 portal of the Observatory on Social Development in Latin America and the Caribbean. This amount is distributed to all people according to the quintile to which they belong, considering their 2019 per capita income. The amount per person is adjusted in each quintile so that the transfer amount received by each quintile corresponds to the following distribution: first quintile, 30 per cent; second quintile, 30%; third quintile, 20%; fourth quintile, 15%, and fifth quintile, 5%.[13]

Annex I.A2

Table I.A2.1

Latin America (18 countries): poverty and extreme poverty indicators, 2000–2019a

(In units of the corresponding indices)

Country

Year

Povertyb

Extreme poverty

Households

Individuals

Households

Individuals

Incidence (H)

Incidence (H)

Poverty gap (PG)

Poverty gap squared (FGT2)

Incidence (H)

Incidence (H)

Poverty gap (PG)

Poverty gap squared (FGT2)

Argentinac

2002

52.8

62.4

31.0

21.3

17.3

21.1

12.1

9.4

2008

19.5

27.1

8.6

4.4

3.3

4.3

1.8

1.2

2014

17.5

24.9

7.2

3.4

3.0

3.3

1.4

1.0

2017

13.3

18.7

5.5

2.7

2.4

2.8

1.2

0.8

2018

17.6

24.4

7.6

3.8

2.9

3.6

1.6

1.1

2019

19.3

27.2

8.4

4.1

3.4

4.2

1.7

1.1

Bolivia (Plurinational State of)

2002

59.9

66.8

37.7

26.5

29.8

35.1

19.2

13.6

2008

39.6

46.5

21.4

13.2

17.0

21.4

9.7

6.2

2014

28.6

33.7

13.9

8.1

12.5

14.9

6.5

4.0

2017

30.6

35.1

15.0

9.1

13.9

16.4

7.5

4.8

2018

27.8

33.2

13.3

7.6

12.3

14.7

6.1

3.6

2019

24.9

31.1

11.3

6.1

9.2

12.1

4.7

2.7

Brazil

2002

30.1

37.8

14.4

7.6

4.8

6.2

2.7

1.9

2008

19.4

25.3

8.9

4.7

3.8

4.3

2.0

1.5

2014

12.6

16.5

5.5

2.9

3.0

3.3

1.4

1.0

2017d

15.9

20.3

7.6

4.4

5.1

5.5

2.5

1.8

2018d

15.1

19.4

7.5

4.4

5.0

5.4

2.5

1.8

2019d

15.1

19.2

7.5

4.4

5.1

5.5

2.6

1.8

Chile

2003

33.4

40.0

15.3

8.1

4.6

5.6

2.2

1.4

2009

23.7

29.0

9.6

4.9

3.6

3.8

1.8

1.3

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

Colombia

2002e

46.3

53.8

25.2

15.4

19.8

23.8

10.1

6.0

2008

37.3

44.6

20.3

12.5

16.8

20.7

9.1

5.7

2014

25.4

31.1

12.4

6.9

9.9

12.0

4.7

2.7

2017

24.2

29.8

11.3

6.2

9.0

10.9

4.1

2.4

2018

24.2

29.9

11.5

6.3

8.9

10.8

4.2

2.5

2019

25.7

31.7

12.7

7.1

10.6

12.8

5.0

2.9

Costa Rica

2002e

25.2

28.0

10.3

5.9

4.9

5.4

2.8

2.2

2008e

17.7

20.1

6.6

3.4

3.5

3.6

1.7

1.2

2014

14.4

17.5

6.4

3.6

3.7

4.1

1.9

1.2

2017

12.8

15.4

5.4

2.9

3.0

3.3

1.5

1.0

2018

13.1

16.1

6.0

3.4

3.4

4.0

1.8

1.2

2019

13.0

16.5

5.6

2.9

2.8

3.4

1.3

0.8

Dominican Republic

2002

28.0

33.6

13.2

7.3

9.2

11.5

4.1

2.4

2008

34.2

41.6

16.0

8.2

11.5

15.0

4.4

1.9

2014

27.0

32.9

11.5

5.6

7.4

9.7

2.8

1.3

2017f

19.2

25.0

8.0

3.8

4.7

6.3

2.0

1.1

2018f

16.8

22.2

6.6

3.0

3.7

5.0

1.4

0.7

2019f

15.2

20.3

6.0

2.7

3.2

4.3

1.4

0.8

Ecuador

2001

48.0

53.5

21.8

11.9

18.0

20.2

6.7

3.6

2008

29.4

34.7

12.1

6.1

9.0

10.8

3.6

1.9

2014

19.2

23.4

7.0

3.1

4.7

5.9

1.7

0.8

2017

19.1

23.6

7.4

3.5

5.4

7.0

2.2

1.1

2018

18.6

24.2

7.4

3.4

4.8

6.5

2.0

1.0

2019

19.4

25.7

8.1

3.7

5.4

7.6

2.1

1.0

El Salvador

2001

44.2

50.6

23.2

14.1

15.8

19.1

8.0

4.9

2009

43.0

50.1

20.8

11.4

13.5

17.1

5.5

2.6

2014

38.0

44.5

16.4

8.1

9.1

11.7

3.3

1.3

2017

32.1

37.8

12.9

6.0

6.5

8.3

2.2

0.9

2018

28.9

34.5

11.6

5.5

5.6

7.6

1.9

0.8

2019

25.3

30.4

9.6

4.3

4.4

5.6

1.4

0.6

Guatemala

2000

46.9

53.6

28.9

19.8

14.4

16.9

8.8

5.9

2006

34.9

42.7

19.5

11.6

7.7

10.4

3.4

1.7

2014

43.1

50.5

22.4

13.0

11.8

15.4

5.3

2.7

Honduras

2001

51.3

57.4

26.3

15.3

23.6

27.3

9.5

4.8

2009

44.8

51.0

21.0

11.2

16.1

19.6

5.7

2.4

2014

50.0

55.3

22.9

12.3

17.1

19.2

5.5

2.5

2016

48.3

53.2

22.5

12.6

16.7

18.8

6.4

3.2

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

Mexico

2002

38.2

46.4

18.1

9.4

7.3

10.4

2.8

1.2

2008

36.1

43.1

17.2

9.4

9.2

11.8

4.0

2.0

2014

38.1

45.2

17.6

9.3

10.2

13.0

4.2

2.0

2016g

36.4

43.7

16.2

8.2

9.1

11.7

3.5

1.6

2018g

34.2

41.5

14.9

7.4

8.3

10.6

3.2

1.4

Nicaragua

2001

57.4

65.1

33.0

21.0

29.3

35.8

15.2

9.1

2009

51.0

58.3

24.8

13.9

18.6

23.1

8.1

4.1

2014

40.9

46.3

18.7

10.2

16.1

18.3

6.6

3.5

Panama

2002

27.7

34.0

15.7

9.5

12.2

16.2

6.7

3.8

2008

20.5

26.8

11.5

6.6

8.8

12.8

5.0

2.6

2014

13.5

18.5

7.1

3.8

5.2

8.0

2.9

1.5

2017

11.4

15.6

6.1

3.3

4.6

6.9

2.7

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

Paraguay

2002

39.9

47.9

22.3

13.6

13.2

17.6

7.2

4.2

2008

28.1

35.0

13.2

6.9

9.2

12.1

3.8

1.9

2014

18.5

22.3

8.2

4.2

6.3

7.7

2.4

1.2

2017

18.4

21.6

6.9

3.1

5.0

6.0

1.5

0.6

2018

16.3

19.5

6.6

3.2

5.3

6.5

1.8

0.8

2019

16.2

19.4

6.4

3.0

5.0

6.2

1.5

0.6

Peru

2002

37.4

43.3

18.2

10.2

12.1

14.9

5.6

3.0

2008

27.5

31.8

12.4

6.6

9.1

10.8

3.6

1.7

2014

16.7

19.5

6.4

3.1

4.2

5.1

1.5

0.6

2017

16.3

18.9

6.1

2.8

4.0

5.0

1.4

0.6

2018

14.3

16.8

5.1

2.3

2.9

3.7

1.0

0.4

2019

13.1

15.4

4.6

2.0

2.4

3.0

0.8

0.4

Uruguay

2002

13.9

20.7

8.2

4.8

3.3

4.3

2.4

1.8

2008

8.6

14.2

3.9

1.5

0.7

1.1

0.2

0.1

2014

2.6

4.5

1.0

0.3

0.2

0.2

0.1

0.0

2017

1.5

2.7

0.5

0.2

0.1

0.1

0.0

0.0

2018

1.7

2.9

0.5

0.2

0.1

0.1

0.0

0.0

2019

1.8

3.0

0.6

0.2

0.1

0.1

0.1

0.1

Venezuela (Bolivarian

Republic of)

2002

45.3

51.7

19.9

10.6

6.8

7.2

3.5

2.6

2008

20.8

24.7

7.6

3.6

4.5

4.7

1.6

1.0

2014

24.0

28.3

9.3

4.6

10.3

12.0

3.7

2.0

2018

1.7

2.9

0.5

0.2

0.1

0.1

0.0

0.0

2002

45.3

51.7

19.9

10.6

6.8

7.2

3.5

2.6

2008

20.8

24.7

7.6

3.6

4.5

4.7

1.6

1.0

2012

17.6

20.9

6.7

3.4

4.6

5.1

1.9

1.3

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 Household Survey Data Bank (BADEHOG).

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

b Includes individuals and households living in extreme poverty.

c Urban total.

d From 2016 onward continuous national household survey (PNAD Contínua) data, not comparable with previous years (based on the National Household Survey (PNAD)).

e Data not comparable with subsequent years.

f Annual data based on the continuous national labour force survey (ENCFT) and not comparable with previous years, which were based on the national labour force survey (ENFT).

g Figures estimated on the basis of the 2018 statistical model for continuation of the social conditions module of the national household income and expenditure survey (MCS-ENIGH) conducted by the National Institute of Statistics and Geography (INEGI).

Table I.A2.2

Latin America (17 countries): poverty and extreme poverty projections, 2020

(Percentages)

2019

Extreme poverty,

without transfers, 2020

Extreme poverty,

with transfers,

2020

2019

Poverty,

without transfers, 2020

Poverty,

with transfers,

2020

Argentinaa

4.2

8.1

5.4

27.2

38.8

37.0

Bolivia (Plurinational State of)

12.1

17.0

14.7

31.1

39.0

37.5

Brazil

5.5

8.0

1.4

19.2

24.1

16.3

Chile

1.4b

3.0

1.6

10.7b

14.7

10.9

Colombia

12.8

19.1

16.9

31.7

38.7

37.5

Costa Rica

3.4

5.5

4.4

16.5

21.0

18.9

Dominican Republic

4.3

6.8

4.6

20.3

25.5

21.8

Ecuador

7.6

13.0

12.8

25.7

33.6

33.5

El Salvador

5.6

9.8

8.0

30.4

38.0

36.4

Guatemala

15.4c

23.5

18.7

50.5c

51.6

50.9

Honduras

20.0

26.1

26.1

52.3

58.6

58.6

Mexico

10.6d

18.4

18.3

41.5d

50.6

50.6

Nicaragua

18.3c

21.3

21.3

46.3c

50.7

50.7

Panama

6.6

10.9

6.4

14.6

21.2

17.8

Paraguay

6.2

6.9

6.2

19.4

21.5

19.7

Peru

3.0

7.3

3.5

15.4

26.0

21.9

Uruguay

0.1

0.4

0.3

3.0

5.3

5.1

Latin America

11.3

15.8

12.5

30.5

37.2

33.7

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

a Urban areas.

b Data refer to 2017.

c Data refer to 2014.

d Data refer to 2018.

Table I.A2.3

Latin America (18 countries): indicators of individual income distribution, 2001–2019a

(In units corresponding to each index)

Country

Year

Gini indexb

Theil indexc

Atkinson indexc

Population with incomes below 50% of the median

(percentages)

(e=0.5)

(e=1.0)

(e=1.5)

Argentinad

2002

0.498

0.405

0.178

0.321

0.444

25.8

2008

0.413

0.292

0.134

0.250

0.357

13.8

2014

0.391

0.264

0.121

0.224

0.317

12.8

2017

0.388

0.263

0.121

0.225

0.324

13.6

2018

0.396

0.286

0.127

0.233

0.329

13.3

2019

0.400

0.284

0.128

0.236

0.333

13.2

Bolivia (Plurinational State of)

2002

0.612

0.734

0.314

0.552

0.740

29.2

2008

0.513

0.492

0.219

0.402

0.567

24.2

2014

0.471

0.403

0.185

0.350

0.507

22.7

2017

0.461

0.372

0.177

0.346

0.518

23.6

2018

0.438

0.333

0.159

0.309

0.459

21.6

2019

0.430

0.327

0.152

0.289

0.423

18.4

Brazil

2002

0.570

0.650

0.262

0.432

0.548

21.7

2008

0.536

0.574

0.234

0.394

0.510

21.1

2014

0.514

0.526

0.217

0.370

0.486

21.6

2017e

0.533

0.561

0.232

0.394

0.516

22.7

2018e

0.540

0.582

0.239

0.405

0.530

23.0

2019e

0.538

0.576

0.237

0.403

0.529

23.1

Chile

2003

0.507

0.514

0.211

0.359

0.478

18.7

2009

0.478

0.453

0.188

0.323

0.434

15.8

2013

0.466

0.424

0.178

0.306

0.408

14.2

2015

0.453

0.408

0.170

0.293

0.392

14.1

2017

0.454

0.417

0.172

0.295

0.394

14.1

Colombia

2002f

0.567

0.663

0.266

0.447

0.586

23.5

2008f

0.572

0.652

0.268

0.456

0.600

25.1

2014

0.540

0.577

0.240

0.412

0.547

23.0

2017

0.511

0.515

0.216

0.375

0.504

21.5

2018

0.520

0.537

0.224

0.386

0.516

21.8

2019

0.529

0.549

0.230

0.398

0.530

22.6

Costa Rica

2002f

0.497

0.462

0.198

0.349

0.475

20.0

2008f

0.491

0.461

0.195

0.339

0.451

18.7

2014

0.498

0.440

0.197

0.356

0.488

21.1

2017

0.496

0.445

0.197

0.351

0.478

20.1

2018

0.493

0.430

0.193

0.348

0.478

20.5

2019

0.495

0.443

0.196

0.350

0.475

20.4

Dominican Republic

2002

0.498

0.461

0.197

0.342

0.453

20.5

2008

0.489

0.452

0.193

0.335

0.445

20.0

2014

0.449

0.351

0.160

0.293

0.404

18.3

2017g

0.433

0.354

0.151

0.266

0.362

15.8

2018g

0.441

0.344

0.147

0.260

0.352

15.3

2019g

0.432

0.342

0.147

0.261

0.354

15.6

Ecuador

2001

0.538

0.643

0.244

0.395

0.502

18.1

2008

0.496

0.461

0.196

0.340

0.452

18.9

2014

0.449

0.391

0.165

0.288

0.387

16.5

2017

0.444

0.370

0.161

0.287

0.394

17.6

2018

0.454

0.386

0.167

0.296

0.401

17.8

2019

0.456

0.382

0.167

0.297

0.404

18.1

El Salvador

2001

0.514

0.481

0.209

0.371

0.503

23.3

2009

0.478

0.428

0.186

0.327

0.440

19.9

2014

0.434

0.340

0.151

0.273

0.373

17.6

2017

0.399

0.295

0.131

0.239

0.332

16.2

2018

0.405

0.289

0.132

0.244

0.340

16.9

2019

0.406

0.298

0.134

0.245

0.338

16.1

Guatemala

2000

0.636

0.883

0.341

0.558

0.714

27.0

2006

0.558

0.608

0.253

0.432

0.567

25.5

2014

0.535

0.664

0.248

0.407

0.533

22.2

Honduras

2001

0.532

0.526

0.226

0.392

0.519

23.2

2009

0.502

0.480

0.204

0.353

0.467

21.3

2014

0.481

0.428

0.185

0.325

0.435

19.0

2016

0.480

0.424

0.187

0.336

0.462

20.9

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

Mexico

2002

0.506

0.489

0.209

0.362

0.476

20.7

2008

0.513

0.535

0.219

0.376

0.498

20.8

2014

0.502

0.511

0.209

0.357

0.475

19.1

2016h

0.491

0.448

0.186

0.320

0.425

16.8

2018h

0.464

0.444

0.182

0.312

0.415

16.5

Nicaragua

2001

0.568

0.536

0.231

0.408

0.561

22.5

2009

0.463

0.400

0.175

0.314

0.440

19.9

2014

0.495

0.511

0.207

0.355

0.476

19.9

Panama

2002

0.572

0.622

0.270

0.472

0.623

27.3

2008

0.528

0.518

0.229

0.410

0.553

24.9

2014

0.502

0.465

0.206

0.372

0.511

24.2

2017

0.505

0.489

0.212

0.379

0.520

23.8

2018

0.501

0.457

0.206

0.377

0.522

23.7

2019

0.506

0.460

0.206

0.375

0.516

23.8

Paraguay

2002

0.584

0.648

0.259

0.439

0.584

24.7

2008

0.516

0.564

0.224

0.377

0.494

21.1

2014

0.522

0.542

0.219

0.372

0.493

21.5

2017

0.503

0.500

0.202

0.341

0.447

19.4

2018

0.474

0.421

0.183

0.324

0.437

20.1

2019

0.473

0.412

0.180

0.320

0.432

20.3

Peru

2002

0.544

0.610

0.248

0.422

0.560

24.4

2008

0.495

0.450

0.201

0.364

0.500

24.7

2014

0.446

0.369

0.165

0.303

0.424

21.5

2017

0.448

0.368

0.165

0.303

0.422

20.9

2018

0.439

0.345

0.157

0.290

0.406

20.0

2019

0.429

0.332

0.151

0.278

0.390

19.6

Uruguay

2002

0.474

0.393

0.177

0.322

0.448

21.1

2008

0.453

0.382

0.166

0.295

0.397

18.7

2014

0.392

0.271

0.124

0.229

0.319

16.3

2017

0.390

0.272

0.123

0.225

0.311

15.8

2018

0.391

0.269

0.123

0.225

0.312

15.6

2019

0.392

0.270

0.123

0.226

0.314

16.2

Venezuela (Bolivarian Republic of)

2002

0.418

0.317

0.140

0.253

0.355

13.7

2008

0.379

0.248

0.114

0.212

0.298

13.9

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 Household Survey Data Bank (BADEHOG).

a Calculated from the distribution of personal per capita income in the country as a whole.

b Includes those with zero income.

c To reduce the effect of extreme values, the Theil and Atkinson indices were calculated excluding values close to 0 and the three highest per capita incomes.

d Urban total.

e From 2016 onward, data from the PNAD Continua survey are not comparable with those of previous years.

f Data for 2002 and 2008 are not comparable with those of later years.

g Annual data based on the continuous national labour force survey (ENCFT) and not comparable with previous years, which were based on the national labour force survey (ENFT).

h Figures are not comparable with previous years.

[1] The linear correlation coefficient for variations in the official and ECLAC poverty rates for all ten countries is 0.95, and 0.70 for variations in the extreme poverty rate.

[2] The absolute variation is the variance between the poverty estimates in the final and initial years, divided by the number of years between the two. The relative variation is the percentage change in the poverty rate over that period, annualized by raising the value to (1/number of years elapsed).

[3] According to Ravallion and Datt (1992), a poverty indicator can be calculated using the initial-period income distribution and the average income level of the end period. The difference between this indicator and the initial-period poverty rate can be interpreted as a growth effect on average income. It is also possible to calculate the poverty rate that corresponds to the average income of the initial period, but with an income distribution similar to that of the end period. The difference between this indicator and the initial poverty rate is the distribution effect. Both effects can also be calculated by exchanging the initial and end periods.

[4] To set the threshold in income distribution, for each country the poverty rate for the year in which the rate was highest was used —either the initial or end year— and 5 percentage points were added, to include households that are just above the poverty line. As an example, if the poverty rate in a country in 2014 and 2019 was 30% and 25%, respectively, the set of households belonging to the lowest 35% of income earners is selected as the reference group.

[5] The variations analysed here are calculated in value terms, that is, they take into account the joint effect of changes in the number of recipients and the average income received by each recipient.

[6] See Economic Commission for Latin America and the Caribbean (ECLAC), CEPALSTAT, “Type of households, by sex of head of household and geographical area” [online] https://cepalstat-prod.cepal.org/cepalstat/tabulador/ConsultaIntegrada.asp?idIndicador=2465&idioma=i.

[7] See ECLAC (2019, box I.2) for operational criteria for defining the strata.

[8] This, despite the gradual deterioration of the registered labour market since 2015, which led to setbacks in some countries.

[9] Household surveys, the main source of information for the analysis of income distribution, do not adequately reflect the incomes of better-off individuals and significantly underreport income received from asset ownership. By way of reference, the property income reported in the household account of the national accounts of some countries in the region can exceed the value recorded in household surveys by 10 times or more.

[10] The middle sectors did not shrink by exactly the same proportion and number because there is also an estimated reduction in the number of people in the upper sectors and because population growth between the two years has mainly concentrated in the lower sectors.

[11] Although dismissals of paid workers are usually reflected in the unemployment rate, a significant portion of those who found themselves in this situation during the pandemic became part of the population outside the labour force, owing to difficulties seeking employment (a necessary condition for being classified as unemployed) (see chapter II). For simplicity, the model assumes that all job losses are reflected in the unemployment rate.

[12] For simplicity, the classification is made at the highest level of the International Standard Industrial Classification of All Economic Activities (ISIC), according to the version used in each country. For the allocation of intensity by sector, an approximation based on ECLAC (2020c) was used.

[13] This distribution corresponds roughly to that reported in the June 2020 PNAD COVID19 national household survey in Brazil (IBGE, 2020b).

Chapter II

Labour market: structural gaps during the pandemic

Introduction

A. Labour market gaps prior to 2019

B. Labour markets in the context of the COVID-19 pandemic

C. Concluding remarks

Bibliography

Annex II.A1

Introduction

Since 2015, labour market indicators have been evolving negatively, with a gradual increase in unemployment and a deterioration in the quality of work (ECLAC/ILO, 2020a; Weller, 2020; ECLAC, 2019). This is exacerbated by the far-reaching effects of the health, economic and social crisis caused by the COVID-19 coronavirus disease pandemic, which have led to a sharp contraction in employment in the region’s countries. The extent of that impact varies from one country to the next, depending on such factors as the effectiveness, type and scope of the health restrictions put in place to tackle the pandemic, the measures implemented to protect employment and the level of dependence of the economy in question on declining external demand.

The evidence shows the disproportionate impact of this crisis on informal workers and women, because of their greater presence in some of the economic sectors most badly hit by the crisis and because of the heightened burden of unpaid care in households caused by school closures, in a region that already had a significant deficit in that area (ECLAC/UN-Women, 2020; ILO, 2020e and 2020f). Young people and, in particular, young women —who are more often outside the labour market and the education system— are particularly vulnerable to the cumulative effects of worsening conditions in the labour market. Similarly, even more limited job opportunities can be expected for older persons, for whom labour insertion is of great importance in ensuring well-being (ECLAC/ILO, 2018) in the absence of universal social protection systems. During the COVID-19 pandemic, an increase in ethnic and racial inequalities in the labour market is also likely, as are heightened inequalities related to territorial conditions, disabilities or migration status.

In addition to this introduction, the chapter is divided into three sections. The first analyses the trends and gaps that characterized the labour market insertion of various population groups before the pandemic, paying particular attention to informal workers, women and young people, while the second examines the effects of the crisis on employment. The third and final section offers some concluding remarks.

A. Labour market gaps prior to 2019

Since 2015, Latin American economies have been reporting weakened economic growth rates and, consequently, a slowdown in the pace of new job creation. This has resulted in reduced labour participation, increased unemployment and labour insertion in low-productivity sectors characterized by precarious working conditions.

After more than a decade of relatively rapid growth in the region —on account of various factors, including the commodity supercycle— during which labour participation rose and unemployment and informal work fell, there has been a sustained slowdown in the region’s economies since 2015. This has had an impact on labour markets, where indicators have deteriorated due to their progressive inability to absorb the labour supply and to create formal jobs with higher, more stable incomes and social protection coverage.

1. Rising labour insertion in low-productivity sectors

The trend towards a gradual decline in the proportion of workers in low-productivity sectors recorded since the beginning of the century suffered a reversal between 2014 and 2019. As a result, the level reported in 2019 (49.7% of workers) was higher than in 2010 (48.7%). Although the reversal of the trend was more pronounced among male workers (2.8 percentage points between 2015 and 2019) than among women, female workers have higher rates of participation in low-productivity sectors. The increased insertion in low-productivity sectors was also more pronounced in rural areas and among workers with incomplete primary education, so that gaps in access to quality jobs widened with respect to skilled workers (see figure II.1A).

In 2019, more than 122 million workers in a group of 15 Latin American countries were employed in low-productivity sectors characterized by low wages, scant social protection and high job instability, a situation that made them particularly vulnerable to the effects of the COVID-19 crisis. Of those, 68 million were independent workers without professional or technical qualifications, 32.8 million were wage-earners without professional qualifications employed in microenterprises, 11.7 million were employed in domestic service and 9.8 million were microentrepreneurs (see figure II.1B).

Figure II.1

Latin America (15 countries):a workers employed in low-productivity sectors, by sex, broad age groups, geographic area and level of schooling, around 2010, 2014 and 2019

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

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

b Low-productivity sectors include microenterprise employers, workers without professional or technical qualifications employed in microenterprises or independently, and domestic service workers.

2. Inequalities in labour participation

At the start of the century, the labour participation rate began to increase gradually but steadily, with a slight downward trend in male participation and a steady increase in female participation. From 2015 onwards, the decline in male participation and the increase in female participation sped up and, as a result, the labour participation rate remained stable between 2014 and 2019. However, an examination of a group of 15 countries around 2019 reveals the persistence of a pronounced gender gap: with a total participation rate of 64.9%, male participation stood at 77%, compared to around 54% for female participation. There was also a slight increase in the participation of adults aged 30 to 64 and of those based in urban areas. In contrast, labour participation fell in rural areas and among the population with incomplete secondary schooling (see figure II.2).

The participation rate fell by more than one percentage point in Brazil (-2.8%), Costa Rica (-2.0%), the Plurinational State of Bolivia (-1.5%) and Uruguay (-2.5%). In general, those drops were due to decreases in both male and female participation. In contrast, labour participation increased by three percentage points or more in the Dominican Republic, Mexico and Paraguay, particularly because of rising female labour participation (see annex table II.A1).

Figure II.2

Latin America (15 countries):a evolution of the labour participation rate among persons aged 15 and over, by sex, broad age groups, geographical area and level of schooling, around 2010, 2014 and 2019

(Percentages)

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

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

b Weighted average of 14 countries.

3. Increased unemployment

In a group of 15 of the region’s countries, the unemployment rate decreased by an average of 0.5 percentage points between 2010 and 2014 and increased by 1.3 between 2014 and 2019.[1] The increased unemployment during the latter period affected women to a greater extent, with the rate rising from 7.4% in 2014 to 9.4% in 2019, while among men the increase was 1.2 percentage points, to reach 6.7%. Similarly, the increase in unemployment between 2014 and 2019 had a striking impact on young people: three percentage points among both 15–19 year olds and 20–24 year olds.

The largest increases in unemployment were recorded among low-income sectors. Thus, while unemployment among the 10% of the population with the lowest per capita incomes rose by 5.6 percentage points to 21.9%, the corresponding figure was only 2.4% among the richest decile (see figure II.3). However, an analysis by level of schooling suggests that the workers most affected by unemployment are those with intermediate qualifications: in 2019, unemployment stood at 11.2% among the active population with incomplete technical, vocational or university education, and 8.2% among those who had completed secondary school. In contrast, the unemployment rates among members of the active population with incomplete primary schooling and completed tertiary education (four years of higher education) were 4.1% and 5.5%, respectively.

Figure II.3

Latin America (15 countries):a unemployment rate among persons aged 15 and over, by per capita income deciles, around 2010, 2014 and 2019

(Percentages)

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

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

B. Labour markets in the context of the COVID-19 pandemic

The pandemic has impacted countries’ labour markets to different extents; the degree to which they have been affected depends on a series of factors, including the type and scope of the measures adopted in response to the spread of the new coronavirus. One of the most striking aspects of labour market dynamics in the early days of the crisis was the huge outflow of the working-age population from the labour force. The impact has also been uneven from one country to the next and, in general, it has been felt more harshly by women, informal workers, youth, people with low levels of education, people of African descent and migrants.

The employment and household surveys conducted in the region’s countries during 2020 make it possible to analyse, albeit partially, the COVID-19 pandemic’s impact on the world of work. Depending on the indicator in question, the information presented below covers up to 14 countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, Jamaica, Mexico, Nicaragua, Paraguay, Peru, Plurinational State of Bolivia and Uruguay.[2] While there are exceptions, such as Brazil (see box II.1), the surveys are often not strictly comparable: first, comparability between the countries is limited because the pandemic forced a change in the way information is collected due to restrictions on mobility and physical distancing measures; and, second, comparisons between countries are not always possible because they do not necessarily define labour indicators in the same way (see annex table II.A1.2).[3]

Box II.1

Brazil: changes in the workforce and wage bill during the pandemic

Brazil is one of the region’s countries where household survey data collection was not interrupted. As a result, comparisons can be made of the working-age population’s situation in different quarters both before and after the pandemic was declared. Thus, comparing the April to June quarters of 2019 and 2020, there was a year-on-year reduction in the labour force of almost 10 million people, due to the loss of that number of jobs. This occurred without a significant increase in the number of unemployed persons: most of those affected left the workforce and joined the potential workforce, which increased by 5.3 million people in the period under review, accounting for a significant portion of the year-on-year increase in the number of people out of the labour force, which rose by 13 million between the second quarters of 2019 and 2020. There was also an increase of just over 800,000 discouraged workers, i.e. those who feel it will be impossible for them to obtain a new job and give up the search.

Brazil: indicators of workforce underutilization, persons aged 14 and older, 2019–2020

(Thousands of people)

April–June

2019

January–March

2020

April–June

2020

Absolute change

April–June

2020/2019

Relative change

April–June

2020/2019

People in the labour force

106 108

105 073

96 138

-9 970

-9.4%

Employed

93 342

92 223

83 347

-9 995

-10.7%

Underemployed

7 355

6 467

5 613

-1 742

-23.7%

Unemployed

12 766

12 850

12 791

25

0.2%

People outside the labour force

64 756

67 281

77 781

13 025

20.1%

Potential workforce

8 284

8 303

13 542

5 258

63.5%

Discouraged workers

4 877

4 770

5 683

806

16.5%

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Brazilian Geographical and Statistical Institute (IBGE), “Indicadores IBGE: Pesquisa Nacional por Amostra de Domicílios Contínua. Divulgação Especial. Medidas de Subutilização da Força de Trabalho no Brasil, 2º trimestre de 2020”, August 2020 [online] ftp://ftp.ibge.gov.br/Trabalho_e_Rendimento/Pesquisa_Nacional_por_Amostra_de_Domicilios_continua/Trimestral/Novos_Indicadores_Sobre_a_Forca_de_Trabalho/pnadc_202002_trimestre_novos_indicadores.pdf.

In addition to the impact on employment, the job losses caused a sharp reduction in household incomes. Thus, an analysis of the actual variation in work income received by households reveals a year-on-year reduction of 11.8% for the April–June quarter of 2020 compared to 2019.

Brazil: income from employment, moving quarters, 2019–2020

(Billions of reais)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Brazilian Geographical and Statistical Institute (IBGE), “Indicadores IBGE: Pesquisa Nacional por Amostra de Domicílios Contínua. Divulgação Especial. Medidas de Subutilização da Força de Trabalho no Brasil, 2º trimestre de 2020”, August 2020 [online] ftp://ftp.ibge.gov.br/Trabalho_e_Rendimento/Pesquisa_Nacional_por_Amostra_de_Domicilios_continua/Trimestral/Novos_Indicadores_Sobre_a_Forca_de_Trabalho/pnadc_202002_trimestre_novos_indicadores.pdf.

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

1. Deteriorating labour indicators

A comparison of the year-on-year change in labour indicators during the second quarter for 14 of the region’s countries shows an increase in the unemployment rate of 2.6 percentage points and drops in the employment and participation rates of 10.0 and 9.5 percentage points, respectively. The increase in unemployment was lower than could have been expected in light of the contraction in activity, because many people of working age dropped out of the labour force (ECLAC/ILO, 2020b). Thus, the contraction in the labour force reduced the pressure on the job market.

The largest drops in the employment and participation rates were seen in Peru, where they fell by 28.1 and 26.7 percentage points respectively, while the smallest were in Uruguay: 3.0 and 3.4 percentage points. The unemployment rate rose in the vast majority of the countries, led by Costa Rica with an increase of 12.1 percentage points. The Dominican Republic, where the unemployment rate fell, was the only exception (see figure II.4).

Figure II.4

Latin America and the Caribbean (14 countries): year-on-year change in unemployment, employment and participation rates, April–June (2020/2019)a

(Percentage points)

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

a Hidden unemployment is included in Colombia, Ecuador and Jamaica. For more information on comparability between the 2019 and 2020 data, see annex table II.A1.2.

b 31 conurbations.

c Urban areas.

d Figures for June 2019 and May–June 2020.

e Figures for July 2020.

f Figures for May 2020.

Note that the individuals outside the labour force, not looking for work but interested in working represent potential entrants to the workforce once the mobility restrictions put in place to address the pandemic are lifted or expectations for finding employment improve. With the gradual reopening of economic activities in 2020, there were some signs of reactivation in labour markets. For example, Colombia’s employment rate showed a significant increase after April, while in the Plurinational State of Bolivia the recovery was less pronounced (see figure II.5). The data available for Mexico also suggest a recovery in employment from June onwards. In September, the labour participation rate rebounded from its lowest level recorded in May, after four consecutive months of increases, but still 4.5 percentage points below the September 2019 figure. The recovery dynamics, however, are not the same for men and women. While among men there was a sustained recovery until August, followed by a slight decline in September, the recovery in the women’s labour force participation was less dynamic, with an increase in September after two consecutive months of decline (see figure II.6).

To analyse the impact of the COVID-19 pandemic on the labour market in full, certain less commonly used labour indicators are also of use (see box II.2).

Figure II.5

Plurinational State of Bolivia and Colombia: evolution of the employment rate, January 2019 to August 2020

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of data from the National Institute of Statistics (INE) of the Plurinational State of Bolivia and the National Department of Statistics (DANE) of Colombia.

a Continuous Employment Survey, urban area, preliminary data for the 2015–2020 period.

b Continuous Household Survey, Comprehensive Survey of Households (GEIH), August 2020.

Figure II.6

Mexico: labour participation rate, by sex, September 2019 and April to September 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of National Institute of Statistics and Geography INEGI), “Encuesta Nacional de Ocupación y Empleo (Nueva Edición) (ENOEN): resultados de septiembre 2020”, October 2020 [online] https://www.inegi.org.mx/contenidos/programas/enoe/15ymas/doc/enoe_n_presentacion_ejecutiva_0920.pdf, and data from the National Occupation and Employment Survey (ENOE) and the Telephone Occupation and Employment Survey (ETOE).

a Based on three different surveys that are not strictly comparable. The August 2019 data are based on the National Occupation and Employment Survey (ENOE), which is face-to-face. The data for April–June 2020 come from the Telephone Occupation and Employment Survey (ETOE), and the data for July, August and September 2020 are from the National Occupation and Employment Survey (New Edition) (ENOEN), which combines face-to-face interviews with telephone surveys.

Box II.2

Labour market indicators for analysing the effects of the COVID-19 pandemic

Because of the changes seen in activity levels, an analysis of the COVID-19 pandemic’s impact on the labour market will benefit from studying —in addition to the unemployment rate— variations in the population outside the workforce, using the potential labour force indicator, and changes in underemployment arising from insufficient time and absent workers.

Working-age population by activity status: critical categories for analysis in times of COVID-19

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of International Labour Organization (ILO), “Resolution concerning statistics of work, employment and labour underutilization”, nineteenth International Conference of Labour Statisticians, Geneva, October 2013 [online] https://www.ilo.org/wcmsp5/groups/public/—dgreports/—stat/documents/normativeinstrument/wcms_230304.pdf.

ILO (2020, p. 17) defines the potential labour force as those “groups of persons who express interest in employment, but either are not available to start working or have not sought employment within the specified short reference periods”. For measurement purposes, beyond needing to assess availability and job search, the standards introduces the “desire to work” criterion as a way to ascertain interest in employment. During the second quarter of 2020, large increases in the potential labour force were observed in Chile, the Dominican Republic and Mexico (see figure 1).

In turn, absent workers are defined as those who did not work during the survey’s reference week but continue to have employment ties with a job or business, for reasons that include the nature of the work, sick leave, maternity or paternity leave, continued receipt of income and imminent return. In Chile, the Dominican Republic, Ecuador and Mexico, the numbers of absentees employed among the total employed population increased significantly in the second quarter of 2020 (see figure 2). In Chile, absent workers accounted for 18.1% of the total number of employed persons during the second quarter of 2020 after rising by 163.2% in 12 months, equivalent to 801,800 persons (INE, 2020).a

Figure 1

Latin America (4 countries): potential labour force as a proportion of the population outside the workforce, April–June (2020/2019)a

(Percentages)

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

a For more information on limitations in comparability between 2019 and 2020 data, see annex table II.A1.2.

b Figure for May. Telephone Occupation and Employment Survey (ETOE), results for May 2020. The May 2019 data are from the 2019 National Occupation and Employment Survey (ENOE), and the May 2020 data are from the ETOE. Potential labour force: classified by ETOE as persons temporarily absent from an activity or occupation and persons with the need or desire to work; in ENOE, these people were categorized among the “others” of the unavailable non-economically active population. Conceptually, they can be considered “persons available for work who are unable to look for work”.

Figure 2

Latin America (4 countries): absent workers as a proportion of the total number of employed persons, April–June (2020/2019)a

(Percentages)

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

a For more information on limitations in comparability between 2019 and 2020 data, see annex table II.A1.2.

b Figures for June 2019 and May–June 2020.

c Figures for May 2020.

The pandemic has also had different effects on the countries’ underemployment rates, which refers to workers who need to work longer than their current occupation demands and are available to do so. The dynamics of underemployment are linked to such factors as being able to continue working during the pandemic, receiving government assistance, the existence of unemployment programmes and the prevailing level of informality. While in Brazil, the Dominican Republic and Paraguay underemployment fell in year-on-year terms, in Costa Rica, Mexico and the Plurinational State of Bolivia it rose sharply (see figure 3).

Figure 3

Latin America (6 countries): underemployed workers as a proportion of the total number of employed people, April–June (2020/2019)a

(Percentages)

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

a For more information on limitations in comparability between 2019 and 2020 data, see annex table II.A1.2.

b Urban area.

c Figures for May 2020.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of International Labour Organization (ILO), “Monitoring labour markets amid lockdowns to contain the COVID-19 virus: essential labour force survey content and treatment of special groups (Rev.1)”, Technical Note, Geneva, April 2020; and National Institute of Statistics (INE), Boletín Estadístico: Empleo Trimestral, No. 261, Santiago, 31 July 2020.

a In Chile, this occurred because the absentee worker classification includes workers covered by the Employment Protection Act. See [online] https://www.afc.cl/ley-proteccion-al-empleo/.

2. Uneven effects on different population groups

The COVID-19 pandemic affects different population groups differently. The effects of the health measures adopted to contain the pandemic, including the necessary physical distancing measures (ECLAC/PAHO, 2020), have been uneven, tending to impact informal workers, women, young people, people with low educational attainment, people of African descent and migrants more severely.

On average, the fall in employment at the regional level was greater for women (18.1%) than for men (15.1%). Moreover, women’s exit from the labour market (15.4%) is higher than that of men (11.8%).[4] This situation has led to a bigger increase in the number of openly unemployed men (29.4%) than women (7.7%) (ECLAC/ILO, 2020b).

Beyond the regional averages, marked differences can be seen among the countries with available information. In 9 of the 12 countries examined, the year-on-year decline in the labour participation rate for women in the second quarter of 2020 was greater than for men, while the effects by sex on employment and unemployment rates are more heterogeneous (see figure II.7).

Figure II.7

Latin America and the Caribbean (12 countries): year-on-year changes in rates of employment, unemployment and participation, by sex, April–June quarter (2020/2019)a

(Percentage points)

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

a In Colombia and Jamaica hidden unemployment is included. For more information on comparability of 2019 and 2020 data, see table II.A1.2 in the annex.

b 31 urban centres.

c Urban areas.

d July 2020 data.

e May 2020 data.

The reduction in the number of employed persons by country confirms that women were hit harder by job losses than men. The evidence for 12 countries shows that the contraction of the employed population in the April–June quarter of 2020 compared with the same period of the previous year was greater for women than for men. Although the largest decline came in Peru for both men and women, the biggest gap occurred in Costa Rica, with 11.6 percentage points, and the smallest in Jamaica, with a difference of 0.7 percentage points (see figure II.8).

These results have to do with the fact that women are more precariously inserted in the labour market and a greater proportion of them participate in informal occupations (54.3% compared to 52.3% of men) (ILO, 2018). In addition, they have a greater presence in the economic sectors most affected by this crisis, such as hotel and restaurant services and domestic service. Of women working in the informal economy, 56.9% are in sectors considered to be at high risk of impact from the pandemic, compared to 40.6% of men. In addition, the pandemic has highlighted the crisis of care in Latin America, which is discussed in chapter V.

Figure II.8

Latin America and the Caribbean (12 countries): changes in the employed population, by sex, April–June quarter (2020/2019)a

(Percentages)

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

a For more information on comparability of 2019 and 2020 data, see table II.A1.2 in the annex.

b 31 urban centres.

c Urban areas.

d June 2019 and May–June 2020 data.

e July 2020 data.

f May 2020 data.

The widespread contraction of employment and outflows from the labour force have hit informal workers hardest, as they are often exposed to greater occupational instability and are less likely to be able to telework during the pandemic. The largest negative impact on the informally employed is reflected in the year-on-year changes between the April–June quarter of 2020 and the same period in 2019. For example, informal employment fell by 35.3% in Chile, 20.0% in Brazil, 31.4% in Costa Rica and 10.5% in Paraguay, while total employment contracted by 20.0%, 10.7%, 20.1% and 8.8% in those countries, respectively (INE, 2020b; IBGE, 2020a; INEC, 2020; DGEEC, 2020). This is confirmed by the high share of informally employed in the reduction in total employment, which is higher than their relative share in total employment. In Brazil, Costa Rica, the Dominican Republic, Mexico, Paraguay and Mexico, the reduction in informal employment accounted for more than 72% of the total drop in employment, and in Chile and Argentina, 48.8% and 53.0%, respectively (see figure II.9). However, in a context of economic recovery, informality is likely to increase. In Mexico, for example, the informality rate rose from 47.7% to 55.1% between April and August 2020, a period in which the employed population increased from 43.3 million to 50.4 million people. Moreover, in that country, informal employment has recovered faster than formal employment: the growth of informal employment accounted for 63.8% of the increase in total employment between May and June (INEGI, 2020).5

Figure II.9

Latin America (7 countries): share of informal workers in total employment reduction and informal employment rate, April–June quarter (2020/2019)a

(Percentages)

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

a For more information on comparability of 2019 and 2020 data, see table II.A1.2 in the annex.

b 31 urban centres.

c May 2020 data.

The impact of the pandemic among women and men in the informal sector has differed from country to country. In Chile, between April–June 2019 and the same quarter in 2020, the female informal employment rate fell by 6.3 percentage points to 22.5%, while the male informality rate declined by 4.5 percentage points to 22.2% (INE, 2020b). In 13 cities and metropolitan areas of Colombia, in the May–July 2020 quarter, the proportion of men employed in the informal sector increased by 1.9 percentage points, to 46.0%, while that of women fell by 2.5 percentage points, to 46.6%. In the same period the previous year, the proportion of informally employed persons was 44.1% for men and 49.1% for women (DANE, 2020b).

The COVID-19 crisis has also had different impacts depending on the age of workers, as it particularly affects young people. The pandemic not only destroys employment, but also disrupts the education and training of young people and poses major obstacles to finding a first job or changing jobs.[6]

An analysis of eight countries shows that in seven of them, the age group most affected by the slump in employment during the pandemic has been the youngest. Another age group that has seen a significant contraction in employment is the older population, which in Argentina is the worst affected age group, while in Chile, Colombia and Paraguay it is second only to young people. In the Dominican Republic, the second most affected group is employed persons aged 40 to 59 years (see figure II.10).

Likewise, age differences intersect with gender inequalities. In Costa Rica and Colombia, for example, a larger year-on-year contraction (April–June 2019 compared to the same quarter of 2020) is observed for women in all age groups. In Costa Rica, the drop in employment was 23.5% for men aged 15 to 24 and 38.8% for women in the same age group. In the 25–34 age group, men recorded a reduction of 20.8% and women one of 29.7% (INEC, 2020). In Colombia, there was a 37.2% decline in the employed female population and a 26.8% reduction in the employed male population in the youngest population group (10–24 years) (DANE, 2020a).

Figure II.10

Latin America (8 countries): changes in the employed population, by most affected age groups, April–June quarter (2020/2019)a

(Percentages)

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

a For more information on comparability of 2019 and 2020 data, see table II.A1.2 in the annex.

b 31 urban centres.

People with lower levels of education tend to have poorer working conditions and less access to decent work. Added to this is the fact that the pandemic has a greater impact among employed people with lower levels of education, who usually perform more routine and physical tasks than their peers with higher levels of education and are, therefore, less likely to be able to telework. Although in Argentina, Costa Rica and Peru (Metropolitan Lima) the employed population decreased across all education levels, it can be seen that the contraction increases as the educational attainment of workers decreases. The Dominican Republic is an exception in that, on the one hand, there is less variation between the different levels of education and, on the other, workers with secondary education are the worst affected (see figure II.11).

Figure II.11

Latin America (6 countries): changes in the employed population, by educational attainment, April–June quarter (2020/2019)a

(Percentages)

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

a Each tier includes incomplete and complete attainment. For more information on comparability of 2019 and 2020 data, see table II.A1.2 in the annex.

b 31 urban centres.

c Estimated educational attainment based on years of study.

d Refers to the Lima metropolitan area.

An analysis of the year-on-year variation by occupational category of the employed population in Argentina, the Dominican Republic, Chile, Colombia, Paraguay and the Plurinational State of Bolivia also showed that the largest declines came in the “employers” and “domestic service workers” categories (see figure II.12). Self-employed and unpaid family workers sustained significant reductions in Argentina, Chile, Colombia and the Dominican Republic. In the Plurinational State of Bolivia, workers in production cooperatives were the hardest hit.

With regard to the behaviour of the labour markets in urban and rural areas, a comparison of the year-on-year variation in employment between these areas in four countries (Costa Rica, Ecuador, Paraguay and Peru) revealed greater contractions in urban areas. While in Costa Rica and Ecuador there was little difference between urban and rural areas, in Paraguay the contraction was slightly greater in urban areas, and in Peru urban areas showed a contraction of 49%, compared with 6.5% in rural areas (see figure II.13). Some factors that explain the lower incidence of the pandemic in rural areas are that it started in urban areas, where density facilitates the spread of the disease, and that farming occupations have been less affected, due to the need to maintain food supplies during the pandemic (ECLAC/FAO, 2020). Nevertheless, rural areas in Latin America are characterized by persistently poorer working conditions than in urban areas, with higher rates of informality and a predominance of unpaid workers.[7]

Figure II.12

Latin America (6 countries): changes in the employed population, by occupational category, April–June quarter (2020/2019)a

(Percentages)

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

a For more information on comparability of 2019 and 2020 data, see table II.A1.2 in the annex.

b 31 urban centres.

c Urban areas.

Figure II.13

Latin America (4 countries): changes in the employed population, by geographical area, April–June quarter (2020/2019)a

(Percentages)

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

a For more information on comparability of 2019 and 2020 data, see table II.A1.2 in the annex.

b June 2019 and May–June 2020 data.

Other population groups that face structural discrimination in labour markets, such as indigenous peoples, people of African descent and migrants, are in a disadvantaged position and are particularly hard hit by the effects of the pandemic. In the case of Brazil, the year-on-year information for the second quarter of 2020 and the same period in 2019 showed that non-indigenous, non-Afrodescendent people suffered the smallest contraction in the employment rate, 6.2 percentage points, while the national average was 6.7 percentage points. According to additional information for June 2020, there is a gap of 8.5 percentage points with respect to the possibility of teleworking between employed persons of African descent (8.5%) and those who are not of indigenous or African descent (17.0%) (see box II.3). In the same month, the percentage of unemployed people who were not looking for work because of the pandemic or lack of work locally, but who would have liked to have worked during the previous week was 28.2% for Afrodescendants and 18.0% for non-indigenous, non-Afrodescendants (IBGE, 2020b).

Box II.3

Telework inequalities

Telework has been instrumental in maintaining some jobs and protecting workers from contracting coronavirus disease (COVID-19). However, the possibility of telecommuting varies across and within countries depending on the quality of digital infrastructure, productive structure and labour markets, among other factors. Jobs that can migrate to telework are positively related to gross domestic product (GDP) per capita and the higher degree of formality of occupations (ECLAC, 2020). Likewise, connectivity is lowest among the most vulnerable population: in 2018, half of households without an internet connection were in the lowest two quintiles in terms of the income distribution. In addition, there are marked disparities in Internet connectivity between households in rural areas (where 23% of the population has access) and urban areas (67% access) (ECLAC, 2020).

ECLAC (2020) estimates that about 21.3% of the employed in the region (average for 13 countries) could telework. This average varies according to the economic sector concerned: the probability of teleworking is over 80% for workers in professional, scientific and technical services, finance and insurance, which account for less than 20% of all employed people in the region. In contrast, those employed in wholesale and retail trade and agriculture have a 15% and 1% likelihood of teleworking, respectively.

The data for Brazil show that the possibilities for teleworking differ by economic sector and characteristics of the employed population. In June 2020, 8.7 million people worked remotely, a figure equivalent to 12.7% of the employed population. Women, non-indigenous persons and non-Afrodescendants and those with complete higher-education or postgraduate studies had the highest proportion of teleworkers (see figure). There were no major differences by age group, as the proportion of remote workers ranged from 11.0% for people aged 14–29 to 14.1% for those aged 60 and over (IBGE, 2020).

Brazil: employed people who telework, by sex, race and educational attainment, June 2020

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of ECLAC, “Universalizar el acceso a las tecnologías digitales para enfrentar los efectos del COVID-19”, Informe Especial COVID-19, No. 7, Santiago, August 2020; and Brazilian Institute of Geography and Statistics (IBGE), “Junho 2020: Pesquisa PNAD COVID 19 IBGE”, Rio de Janeiro, 23 July 2020 [online] https://agenciadenoticias.ibge.gov.br/media/com_mediaibge/arquivos/8aa598ff96d7b31bd752c988f2e39572.pdf.

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

The COVID-19 pandemic has also disproportionately affected international migrant workers, who tend to be more vulnerable due to the precariousness of their labour insertion, less access to social protection systems, lack of support networks such as those they have in their country of origin, discrimination, legal exclusion and lack of knowledge of administrative procedures (ECLAC, 2019).[8]

According to a survey on the impact of the COVID-19 pandemic conducted by the International Organization for Migration (IOM) (2020) on the migrant population in Central America and Mexico, 21% of migrants plan to return to their country of origin.[9] The main reason given for returning is lack of income and the high cost of living in the country of destination (50%), followed by a change of mind about their migration plans (32%) and unemployment (18%). Of the migrants surveyed, 51% lost their jobs because of the pandemic. Only 20% of the migrants who responded to the survey were working, most of them as wage earners (71%). Of those migrants who did not lose their jobs, 44% were working fewer hours, 26% were not affected, 20% switched to teleworking and 10% increased the number of hours worked. Aggregating the three categories whose earnings were affected shows that 53% of employed migrants in Central America and Mexico suffered a reduction in their labour income or did not receive payments because of the COVID-19 pandemic (see figure II.14).[10]

Figure II.14

Central America and Mexico: wage impact and employment loss among migrants due to the COVID-19 pandemic, May–June 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of International Organization for Migration (IOM), Efectos de la COVID-19 en la población migrante: principales hallazgos. Sondeo en América Central y México, San José, 2020.

a Migrants from Central America and Mexico residing within and outside the region; as well as extra-regional immigrants currently residing in the region.

C. Concluding remarks

According to ECLAC (2010, 2012, 2014 and 2016), work is critical to equality and the expansion of citizenship, as well as being a fundamental steppingstone for social inclusion, as it generates the bulk of the income of households in the region. The crisis, in an already highly unequal region, has great potential to increase disparity by deepening the gaps and vulnerabilities that, even before the crisis, were already evident in the world of work and in terms of access to social protection. All of this is taking place against a backdrop of profound ongoing transformations, including rapid ageing of the population, the fourth industrial revolution and the challenges of transitioning to an environmentally sustainable economy.

The effects of the pandemic entail a major regression in several labour indicators, including the contraction of employment, especially among women, young people and the most vulnerable groups, including people of African descent, migrants and people with lower levels of educational attainment, who have a large presence in the informal sector. These effects could lead to a critical deterioration in well-being, affecting people’s rights and the sustainability of societies from an intergenerational and gender perspective.

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Annex II.A1

Table II.A1.1

Latin America (18 countries): labour participation, unemployment and employment rates among persons aged 15 years or older, by sex, age group, and geographical area, around 2010, 2014 and 2019

(Percentages)

Year

Total

Sex

Geographical area

Age groups

Men

Women

Urban areas

Rural areas

15 – 29 years

30 – 64 years

65 years and over

Rate of participation

Rate of unemployment

Rate of employment

Rate of participation

Rate of unemployment

Rate of employment

Rate of participation

Rate of unemployment

Rate of employment

Rate of participation

Rate of unemployment

Rate of employment

Rate of participation

Rate of unemployment

Rate of employment

Rate of participation

Rate of unemployment

Rate of employment

Rate of participation

Rate of unemployment

Rate of employment

Rate of participation

Rate of unemployment

Rate of employment

Argentina (urban areas)

2010

60.6

7.3

56.2

74.9

6.2

70.2

48.0

8.9

43.7

60.6

7.3

56.2

…

…

…

52.7

14.7

45.0

77.0

4.4

73.7

14.8

5.7

13.9

2014

60.4

6.9

56.2

72.8

6.2

68.3

49.2

7.9

45.3

60.4

6.9

56.2

…

…

…

51.0

13.5

44.1

77.0

4.4

73.6

16.5

4.3

15.8

2019

60.5

8.9

55.1

71.4

8.5

65.4

50.7

9.5

45.9

60.5

8.9

55.1

…

…

…

51.3

17.8

42.2

79.2

6.1

74.4

17.5

3.2

17.0

Bolivia (Plurinational State of)

2011

72.1

2.6

70.3

82.5

2.1

80.8

62.3

3.2

60.3

66.8

3.6

64.4

84.2

0.6

83.7

60.0

4.8

57.1

85.4

1.5

84.1

51.0

1.0

50.5

2013

69.4

2.7

67.5

80.4

2.1

78.7

59.2

3.5

57.1

64.8

3.8

62.4

80.1

0.8

79.5

55.1

5.5

52.0

83.4

1.7

82.0

52.0

0.6

51.7

2018

67.9

3.7

65.4

79.1

2.9

76.8

57.4

4.8

54.6

63.0

5.2

59.7

79.8

0.9

79.1

50.9

7.6

47.0

82.9

2.5

80.9

50.9

0.8

50.5

Brazil

2011

66.1

6.7

61.7

78.3

4.9

74.5

54.9

9.1

49.9

65.6

7.4

60.8

68.9

2.6

67.1

66.6

12.5

58.3

74.7

4.0

71.8

19.4

1.3

19.1

2014

66.4

6.9

61.9

77.8

5.3

73.7

56.0

8.8

51.1

66.0

7.5

61.0

69.1

3.0

67.0

66.5

13.6

57.5

75.8

4.0

72.7

21.0

1.2

20.7

2019

63.6

11.6

56.2

73.7

9.6

66.6

54.4

14.1

46.8

65.3

11.9

57.5

52.8

8.8

48.1

65.1

21.6

51.0

73.9

7.8

68.2

15.6

3.2

15.1

Chile

2011

56.6

8.6

51.7

71.0

7.1

65.9

43.9

10.7

39.2

57.4

8.7

52.4

50.8

7.8

46.9

47.6

17.0

39.5

72.9

5.6

68.8

15.9

3.2

15.4

2013

57.9

7.8

53.4

71.4

6.8

66.6

46.1

9.1

41.9

58.8

7.8

54.2

51.5

7.4

47.6

48.2

16.0

40.5

74.5

5.1

70.7

18.3

3.3

17.7

2017

60.0

8.6

54.9

72.4

7.9

66.7

49.3

9.5

44.6

61.2

8.8

55.8

52.1

7.2

48.4

51.5

16.8

42.8

77.1

6.1

72.4

21.0

3.3

20.3

Colombia

2010

68.1

11.9

60.0

81.3

9.0

73.9

55.7

15.9

46.8

68.6

12.8

59.8

66.2

8.7

60.5

62.1

19.6

50.0

79.2

8.3

72.6

28.5

5.4

27.0

2014

69.3

9.2

62.9

81.6

7.0

75.9

57.7

12.1

50.7

70.2

10.1

63.1

65.9

5.8

62.1

63.5

15.5

53.6

80.5

6.4

75.4

29.7

4.2

28.5

2018

68.6

9.8

61.9

80.7

7.5

74.7

57.2

12.8

49.9

69.0

10.9

61.5

66.9

5.2

63.5

62.7

16.5

52.4

80.5

6.9

75.0

29.2

4.1

28.0

Costa Rica

2010

59.0

7.3

54.7

75.9

6.0

71.4

43.3

9.6

39.1

60.6

7.2

56.3

56.2

7.6

51.9

55.0

12.8

48.0

70.3

4.4

67.2

15.3

5.0

14.5

2014

59.3

8.6

54.2

74.9

7.2

69.5

45.0

10.7

40.1

60.7

8.5

55.5

55.6

8.8

50.7

53.7

15.9

45.1

72.4

5.4

68.5

15.6

3.7

15.0

2019

57.3

9.2

52.1

71.7

7.9

66.1

44.1

11.2

39.2

58.7

9.4

53.2

53.4

8.5

48.8

50.9

17.3

42.1

71.6

6.4

67.1

14.4

3.2

13.9

Dominican Republic

2010

56.9

5.1

54.0

72.0

4.1

69.0

42.4

6.8

39.5

57.6

5.6

54.3

54.9

3.7

52.9

47.8

8.7

43.6

70.9

3.5

68.4

20.8

1.2

20.6

2014

59.3

6.2

55.7

74.1

4.0

71.1

45.3

9.6

40.9

60.2

6.4

56.3

56.2

5.1

53.3

50.5

11.1

44.9

72.7

4.1

69.7

23.6

1.4

23.3

2019

65.3

6.5

61.1

78.6

4.2

75.3

52.9

9.7

47.8

65.7

6.8

61.3

63.3

5.0

60.1

56.5

13.2

49.0

79.3

4.0

76.2

30.2

0.2

30.1

Ecuador

2010

62.5

5.0

59.4

77.9

4.1

74.7

47.9

6.5

44.8

61.9

6.1

58.1

63.9

2.8

62.1

53.4

9.8

48.2

75.8

3.2

73.4

35.8

1.1

35.5

2014

64.1

3.3

62.0

79.5

2.8

77.2

49.7

4.0

47.8

62.6

4.0

60.2

67.4

1.8

66.2

50.9

6.6

47.6

77.9

2.0

76.3

38.1

0.5

37.9

2019

65.0

3.5

62.8

77.6

3.1

75.1

53.1

4.0

50.9

62.0

4.6

59.2

72.0

1.3

71.1

51.1

7.9

47.0

79.8

2.1

78.1

39.9

0.3

39.8

El Salvador

2010

60.9

7.1

56.6

78.7

8.4

72.1

46.0

5.1

43.6

62.6

6.8

58.3

57.9

7.6

53.6

53.2

11.4

47.1

74.0

4.6

70.6

31.5

5.8

29.7

2014

61.5

7.0

57.2

78.9

8.6

72.2

46.7

4.8

44.5

63.2

6.7

58.9

58.4

7.5

54.0

53.6

12.1

47.1

74.5

4.2

71.3

31.5

5.6

29.7

2019

61.1

6.3

57.2

79.1

7.0

73.6

46.0

5.4

43.5

62.7

6.1

58.9

58.3

6.7

54.3

54.3

11.1

48.3

74.0

3.8

71.2

29.6

6.3

27.7

Guatemala

2006

66.3

1.9

65.0

88.8

1.5

87.4

47.2

2.5

46.0

68.2

2.7

66.4

64.1

0.9

63.5

62.4

3.1

60.5

73.7

1.1

72.9

45.1

0.3

45.0

2014

62.3

2.4

60.8

85.8

2.1

84.1

41.2

3.0

40.0

64.9

3.2

62.8

59.4

1.4

58.6

58.1

4.1

55.7

70.3

1.1

69.5

39.9

1.0

39.5

Honduras

2010

61.7

4.1

59.1

82.5

3.4

79.7

42.7

5.5

40.4

61.0

6.6

56.9

62.3

1.8

61.2

55.5

7.1

51.5

72.1

2.3

70.5

40.4

0.7

40.2

2014

62.9

5.5

59.4

83.0

4.6

79.2

45.3

7.0

42.1

62.1

7.7

57.3

63.9

2.9

62.0

56.7

8.6

51.8

73.3

3.8

70.5

39.0

0.6

38.8

2019

63.1

5.9

59.4

83.7

4.4

80.0

45.2

8.4

41.4

63.1

8.1

58.0

63.2

3.1

61.2

58.7

10.4

52.6

72.2

3.6

69.6

39.0

0.9

38.6

Mexico

2010

60.6

6.6

56.6

80.4

7.7

74.3

42.4

4.7

40.4

61.4

6.9

57.2

57.7

5.6

54.4

54.8

10.8

48.8

70.4

4.5

67.2

27.6

4.1

26.5

2014

61.7

5.3

58.4

80.0

6.2

75.1

44.9

3.9

43.1

62.0

5.6

58.5

60.7

4.1

58.2

55.3

8.6

50.6

71.9

3.8

69.1

28.5

3.5

27.4

2018

65.6

3.0

63.6

81.5

3.5

78.6

51.1

2.2

50.0

65.0

3.3

62.9

67.4

1.9

66.1

58.7

5.2

55.6

76.3

2.0

74.8

33.5

2.0

32.9

Nicaragua

2005

63.0

3.8

60.6

83.6

3.5

80.7

43.8

4.5

41.8

63.1

5.3

59.8

62.8

1.7

61.7

58.2

5.7

54.9

72.7

2.6

70.7

36.6

0.4

36.5

2014

65.1

5.5

61.5

83.5

4.8

79.5

48.1

6.5

45.0

66.5

7.2

61.8

63.0

2.9

61.1

58.9

8.7

53.8

75.8

3.7

73.0

33.8

0.3

33.7

Panama

2010

61.5

4.1

59.0

79.0

3.8

76.0

45.2

4.6

43.1

62.9

5.0

59.7

58.8

2.1

57.5

53.7

9.1

48.8

74.6

2.3

72.9

22.4

0.7

22.2

2014

63.7

4.5

60.8

79.2

3.7

76.3

49.2

5.8

46.4

64.0

5.2

60.7

63.0

3.0

61.1

54.3

9.7

49.1

77.5

2.7

75.4

27.3

0.4

27.2

2019

65.7

6.1

61.7

78.3

4.7

74.6

53.8

7.9

49.5

65.4

7.0

60.8

66.4

3.9

63.9

56.7

14.0

48.8

80.7

3.3

78.0

28.4

1.4

28.0

Peru

2010

74.0

3.9

71.1

82.7

3.4

79.9

65.7

4.5

62.7

71.4

5.0

67.8

82.2

0.8

81.5

65.9

8.1

60.6

85.1

2.1

83.3

48.3

0.9

47.8

2014

71.8

3.3

69.4

80.9

3.1

78.4

63.3

3.6

61.0

69.3

4.2

66.4

80.3

0.8

79.7

62.3

7.8

57.5

84.1

1.6

82.7

46.0

1.2

45.4

2019

72.3

2.8

70.2

80.6

2.5

78.6

64.6

3.2

62.5

70.0

3.5

67.6

81.2

0.5

80.8

59.7

6.0

56.1

85.4

1.8

83.9

49.5

1.4

48.8

Paraguay

2010

68.9

5.8

64.9

84.3

4.5

80.5

53.2

7.7

49.1

68.8

6.9

64.0

69.1

4.0

66.3

63.5

10.6

56.8

78.9

2.8

76.6

34.6

2.1

33.9

2014

69.6

6.1

65.4

83.8

4.6

80.0

55.6

8.3

51.0

69.5

7.3

64.4

69.8

3.9

67.1

64.2

10.4

57.5

79.7

3.4

77.0

35.1

3.1

34.1

2019

72.6

5.7

68.5

84.8

4.1

81.3

60.7

7.8

55.9

72.4

6.3

67.9

72.9

4.6

69.6

66.3

10.3

59.5

83.2

3.2

80.5

38.5

2.4

37.6

Uruguay

2010

64.2

6.9

59.8

74.5

5.1

70.8

55.2

9.0

50.3

64.1

7.0

59.6

67.3

2.8

65.4

62.5

15.2

53.0

81.9

3.9

78.7

16.4

3.1

15.9

2014

65.9

6.5

61.6

75.7

5.0

71.9

56.9

8.3

52.2

65.7

6.8

61.2

68.9

2.4

67.2

63.8

14.4

54.6

82.8

3.7

79.7

16.4

2.1

16.0

2019

63.4

8.9

57.7

71.5

7.3

66.3

55.9

10.7

49.9

63.4

9.2

57.6

62.6

3.9

60.2

58.8

20.2

46.9

82.3

5.0

78.2

13.4

3.5

13.0

Venezuela (Bolivarian Republic of)

2010

64.8

8.5

59.3

79.2

7.8

73.0

50.4

9.5

45.7

…

…

…

…

…

…

53.9

14.4

46.1

78.4

5.7

73.9

25.8

5.4

24.4

2014

65.4

6.7

61.0

79.3

6.1

74.5

51.6

7.7

47.6

…

…

…

…

…

…

54.0

11.4

47.8

79.1

4.8

75.4

26.0

5.2

24.6

Latin Americaa

2010

64.5

6.8

60.1

78.9

5.9

74.3

51.3

8.3

47.0

64.6

7.5

59.7

65.3

4.0

62.7

60.5

12.3

53.1

74.9

4.3

71.7

24.7

2.5

24.0

2014

65.0

6.3

60.9

78.5

5.5

74.2

52.6

7.4

48.7

65.0

6.9

60.5

66.2

3.5

63.9

60.2

11.9

53.1

76.0

4.0

72.9

26.0

2.2

25.4

2019

64.9

7.9

59.8

77.0

6.7

71.8

53.8

9.4

48.8

65.5

8.6

59.9

63.6

4.3

60.8

60.4

14.5

51.6

76.6

5.3

72.6

25.1

2.4

24.6

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

a Weighted average of the following countries: Argentina (urban areas), Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay. Urban and rural averages exclude Argentina.

Table II.A1.2

Surveys used to analyse labour markets during the COVID-19 pandemic

Country

Survey

How the survey is conducted and definition of the working-age population

Argentina

Permanent Household Survey (EPH).

Labour market. Socioeconomic rates and indicators. Second quarter of 2020

Telephone data collection. In jurisdictions where the isolation conditions were eased during the quarter, field work was carried out, with the explicit authorization of the competent authority, for the exclusive purpose of contacting households whose telephone number was unknown, to ascertain their telephone number and then conduct the survey by telephone; and to (totally or partially) recover cases in which it was impossible to hold the telephone interview.

The working-age population encompasses individuals aged 14 years or older.

Brazil

Permanent National Household Survey (PNAD Contínua), rolling quarter April–June 2020

The Brazilian Institute of Geography and Statistics (IBGE), the agency responsible for conducting the PNAD, suspended field operations as from March 17 and switched to the telephone survey modality.

The working-age population comprises persons aged 14 and over.

Bolivia (Plurinational State of)

Continuous Employment Survey (ECE), second quarter 2020

Telephone and other media interviews as a data collection strategy for the second-quarter ECE.

The working-age population encompasses individuals aged 14 years or older.

Chile

National Employment Survey: results for the April–June 2020 quarter; Statistical bulletin: labour informality, Issue No. 11/5 of August 2020.

Data collection by telephone. If the respondent is unable to answer the survey by telephone, the interviewer offers the alternative of filling out the form over the Internet, through a self-administered questionnaire.

The working-age population encompasses individuals aged 15 years or older.

Colombia

Large-scale Integrated Household Survey (GEIH). Labour Market, June 2020

On 31 March it was decided that GEIH data would be collected by telephone, although in-person collection would continue in rural areas.

The working-age population comprises individuals aged 12 years or older in urban areas and 10 years or older in rural areas.

Costa Rica

Continuous Employment Survey (ECE), second quarter 2020

In the April-June 2020 quarter, it was possible to maintain continuous data collection by telephone during the 12 weeks in question.

The working-age population consists of the population aged 15 years and older.

Dominican Republic

Continuous National Labour Force Survey (ENCFT)

Data collection by telephone is being continued until it becomes possible to resume in-person interviews. The usual questionnaire is being implemented retroactively with additional reply options as from April 2020.

The working-age population encompasses individuals aged 15 years or older.

Ecuador

National Survey of Employment, Unemployment and Underemployment (ENEMDU) by telephone, May–June 2020

Survey conducted by telephone.

The working-age population encompasses individuals aged 15 years or older.

Jamaica

Labour Force Survey, July 2020

The April 2020 survey was suspended, and the survey was resumed for July 2020.

The working-age population encompasses individuals aged 14 years or older.

Mexico

Telephone Survey of Occupation and Employment (ETOE) and National Survey of Occupation and Employment (New Edition) (ENOEN), July 2020 and data from the 2019 National Survey of Occupation and Employment (ENOE).

The Telephone Survey of Occupation and Employment (ETOE) is a survey strategy that was implemented to collect information in the months of April, May and June. The National Survey of Occupation and Employment (New Edition) (ENOEN), which follows the ETOE, maintains the same conceptual, statistical and methodological design as the traditional ENOE, but the sample consisted of 72% in-person interviews and 28% telephone interviews.

The working-age population encompasses individuals aged 15 years or older.

Nicaragua

Employment Report (Informe de Empleo), Continuous Household Survey (ECH), second quarter 2020

The working-age population encompasses individuals aged 14 years or older.

Paraguay

Permanent Continuous Household Survey (EPHC), second quarter 2020

Data collection by telephone, with in-person interviews held with households that did not respond to the phone calls.

The departments of Boquerón and Alto Paraguay are excluded.

The working-age population encompasses individuals aged 15 years or older.

Peru

Permanent Employment Survey (EPE) - April–June quarter 2020, Labour Market Situation in Metropolitan Lima; and National Household Survey (ENAHO).

Telephone interviews nationwide. In the case of ENAHO, in-person visits were made in addition to telephone interviews.

The working-age population encompasses individuals aged 14 years or older.

Uruguay

Continuous Household Survey (ECH)

for the months of April, May and June.

In April, the Continuous Household Survey (ECH) started to be applied under a panel modality and switched from face-to-face interaction to a telephone interview.

The working-age population encompasses individuals aged 14 years or older.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the national statistics offices of the respective countries and ECLAC, “Recommendations for the publication of official statistics from household surveys in the context of the coronavirus disease (COVID-19) pandemic”, COVID-19 Reports, Santiago, April 2020.

Table II.A1.3

Latin America (8 countries): definitions of informality

Argentina

Wage earners without pension deduction: refers to the employed wage-earning population in jobs that do not make

a pension deduction.

Brazil

The following categories were taken into account to calculate the informality proxy variable:

- Private sector employees without employment contracts;

- Domestic employees without employment contracts;

- Employers not registered in the National Registry of Legal Entities (CNPJ);

- Self-employed workers not registered in CNPJ;

- Auxiliary family workers.

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 considered to have an informal occupation if the firm, business or activity in which they work belongs to the informal sector. Unpaid family or household members, all have an informal occupation by definition, given the conditions of their relationship with the economic unit in which they work.

Colombia

1. Private employees and labourers working in establishments, businesses or enterprises that employ up to five persons in all their agencies and branches, including the employer or partner;

2. Unpaid family workers in enterprises of up to five workers;

3. Unpaid workers in enterprises or businesses of other households;

4. Domestic employees in enterprises of up to five workers;

5. Day labourers or unskilled workers in enterprises of up to five workers;

6. Self-employed workers in establishments of up to five persons, except independent professionals;

7. Owners or employers of firms that have up to five workers. Government workers or employees are excluded.

Costa Rica

Informal employment consists of the total number of jobs with the following characteristics, according to the person’s position in the job:

(i) Wage earners who are not registered with social security through their employers;

(ii) Unpaid assistants;

(iii) 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

Informal employment: workers who do not have access to social security as a result of their employment relationship. The total number of informal workers consists of the sum of informal workers in the informal sector, persons employed informally

in domestic service (who do not have access to social security through their employment relationship), informal workers

in the formal sector and unpaid family workers working in the formal sector.

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 whose employment is not recognized by their work source.

Paraguay

Non-agricultural workers who do not contribute to a social security system.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official definitions used in employment and household surveys of the countries.

[1] This led to a slight drop in employment rates in 9 of the 15 countries analysed (see table II.A1.1).

[2] The analysis period is the quarter from April to June 2020, compared to the equivalent period in 2019. For Mexico and Uruguay, the data cover May 2019 and May 2020; those for Ecuador are from June 2019 and the two-month period from May to June 2020; and Jamaica’s figures are from July 2019 and July 2020.

[3] The health restrictions adopted in the countries required modifications in their data collection processes, with telephone interviews replacing some or all of the face-to-face interviews. As a result, the response rate fell. Likewise, questionnaires were modified and some methodological adjustments were made to address changes in completed survey return rates, to overcome various difficulties in ensuring a representative sample and to guard against the possibility of greater biases in some variables. The solutions adopted included adjustments for non-responses, the smoothing of expansion factors and calibrations by population groups or subnational areas. One example of the problems of cross-border comparability is the difference in how the working-age population is defined, with some countries not following the International Labour Organization (ILO) standard (“all persons aged 15 and over”).

[4] A comparison of the data for the April–June quarter of 2020 with the same period in 2019 shows that in Chile, the outflow from the labour force was 20.1% for women and 11.9% for men, while in Paraguay the percentages were 8.7% and 1.7%, respectively (INE, 2020a; DGEEC, 2020). In Colombia, for the same period, women accounted for 57% of the increase in the population outside the labour force (DANE, 2020a). In Metropolitan Lima, the female labour force shrank by 52.3%, while the reduction for men was 47.7% (INEI, 2020).

[5] The 2019 data were taken from the National Occupation and Employment Survey (ENOE), while the 2020 figures are from the Telephone Occupation and Employment Survey (ETOE).

[6] Before the pandemic, young people already had higher unemployment rates and lower-quality jobs than adults. According to ILO (2020c), in Latin America and the Caribbean, the youth (15–24 years) unemployment rate in 2019 was 17.9%, while 21.6% of young people were neither working nor enrolled in an education or training programme.

[7] According to ILO (2020d), 76% of rural workers were informally employed in 2017, compared to 44.8% of urban workers. In the same year, wage employment reached 45% of the total employed in rural areas and 67% in urban areas. Likewise, rural self-employed workers accounted for 39.4% of the total number of employed persons, while in urban areas they accounted for 25% of total employed persons.

[8] The main sectors of employment of migrant workers show significant differences by sex. In the case of women, paid domestic work predominates (33%), followed by occupations in the health and social services sectors (18%). Men are mainly employed in the service support sector, communication, finance, real estate or administration (14%), followed by construction (11%) or as transport workers (11%).

[9] The survey, which captured information between 28 May and 30 June 2020, was conducted among migrants from Central America and Mexico residing within and outside the region, as well as extraregional migrants currently residing in Central America and Mexico. The survey also collected information from nationals of Central American countries and Mexico who intended to migrate in the previous 12 months. Of this sample, 60% were people who considered themselves international migrants and the remaining 40% were people who had not migrated at the time of answering the questionnaire, but who had the intention of doing so in the previous 12 months. The main nationalities of respondents include, in descending order: Honduras (28%), El Salvador (23%), Nicaragua (15%), Guatemala (11%), Cuba (6%), Venezuela (Bolivarian Republic of) (4%), Colombia (3%), Mexico (3%), Costa Rica (2%), Haiti (1%) and Belize (1%).

[10] A survey on the situation of migrants conducted in June, July and August 2020 in Santiago confirmed the labour instability of migrants during the pandemic. Some 30.4% of migrants were dismissed, 21.4% had their contracts temporarily suspended, 18.2% had their working hours reduced and 12.1% reported difficulties working in a self-employed capacity (CENEM/University of Talca, 2020).

Chapter III

Social protection in response to COVID-19: pre-existing gaps and emerging responses

Introduction

A. Universal social protection: an urgent but still distant goal

B. Responses to the pandemic from the social protection systems

C. Concluding remarks

Bibliography

Annex III.A1

Introduction

Social protection, which aims to guarantee adequate incomes, improve access to social services and foster decent work for the entire population, is a right that is proclaimed in numerous national and international legal instruments.[1] It is also a key tool for eradicating poverty and significantly reducing inequalities, as recognized in the 2030 Agenda for Sustainable Development and in the Sustainable Development Goals (SDGs) on poverty eradication (Goal 1), gender equality (Goal 5) and reducing inequalities (Goal 10).

Over the past two decades, the region’s countries have made major efforts to expand the coverage of social protection (ECLAC, 2019) —through contributory schemes, linked to contributions made on the basis of workers’ labour market participation; and through non-contributory ones, financed exclusively through general taxes. Nonetheless, the countries are confronting the COVID-19 pandemic with major gaps and large groups of the population left unprotected. This highlights the fragmentation and inequalities that pervade their social protection systems, as well as the historical weakness of the welfare state in the region (ECLAC, 2010).[2] A large proportion of the population is either not affiliated to the pension and health systems, or else does not contribute to them —a phenomenon that is associated with the prevailing high levels of labour informality. Moreover, the benefits provided by continuous non-contributory social protection programmes are insufficient to guarantee well-being during the crisis and have limited coverage.

Given the shortage of truly universal and comprehensive systems to underpin a basic level of consumption and well-being throughout the life cycle, governments have responded to the COVID-19 pandemic with an unprecedented array of emergency social protection programmes, mainly targeted on poor households or those comprising individuals, such as informal workers, who are more likely to slip into poverty (ECLAC, 2020b). The programmes in question include the adaptation and extension of existing cash and in-kind transfers, as well as the creation of new instruments.

Social protection measures are fundamental both for controlling and mitigating the pandemic and for reactivating the economy (ECLAC/PAHO, 2020), since they make it possible to adopt and abandon the strategies of varying degrees of strictness that need to be implemented for epidemiological containment, without condemning a large part of the population to poverty (Filgueira and others, 2020). In particular, at times of crisis, social protection deficits can have catastrophic effects on the comprehensive development of children and adolescents, with critical impacts on the exercise of their rights and the development of human capacities.

Investing in social protection is, therefore, not only imperative from a rights perspective, but also efficient from an economic and productive standpoint (ECLAC, 2018a). The time has come for universal, redistributive and solidarity-based policies, driven by robust social and fiscal covenants, where the consolidation of universal social protection systems is placed at the centre of a new welfare regime in the region (ECLAC, 2020b and 2020d).

Section A of this chapter analyses the different social protection coverages prior to the crisis, while Section B examines their evolution during the COVID-19 pandemic.

A. Universal social protection: an urgent but still distant goal

The region is tackling the COVID-19 pandemic with social protection systems that suffer from major coverage gaps and show recent signs of deterioration. Prior to the crisis, only 47.2% of employed persons were affiliated or contributing to pension schemes, and 60.5% were affiliated or contributing to health systems. In 2019, a quarter of individuals aged 65 years or older were not receiving a pension. In the same year, conditional cash transfer programmes covered an average of 18.5% of the population of Latin American and Caribbean countries.

Advancing towards fulfilment of the right to social protection means universalizing access and designing benefits that take into account the specific discriminations, gaps and vulnerabilities faced by different populations. It also becomes imperative to encompass the various components of social protection, including the contributory and non-contributory elements, labour market regulations and care policies (ECLAC, 2020a).

This section provides an overview of the structural gaps that existed in access to social protection in the region prior to the COVID-19 pandemic.[3] It firstly describes the recent trend of pension and health-care coverage, and then examines the challenges in terms of access to non-contributory cash transfers that had already been foreseen.

1. Unequal and reduced access to pensions and health care

Access to the instruments of contributory social protection is associated with higher benefit levels and both guaranteed and stable protection for formal workers and their families, in accordance with international mandates linked to the right to social protection. Nonetheless, even before the pandemic, there was evidence of a widespread lack of protection for a wide range of workers. This is a worrying situation in the context of demographic transformations and changes in the world of work, not to mention the effects of COVID-19.

(a) Affiliation and contribution to pension systems

Despite persistent inequalities, between 2002 and 2015, the proportion of employed people who were affiliated or contributing to pension systems increased significantly in Latin America (ECLAC, 2018b and 2019). However, administrative records show that contributions to pension systems fell back in 2015–2017 (Arenas de Mesa, 2019).[4] Household survey data for 15 Latin American countries confirm this trend. Between 2014 and 2019, the proportion of all employed persons aged 15 and over who were affiliates or contributors fell by 1 percentage point from 48.1% to 47.2% (see table III.A1.1 of the annex). Moreover, over the same period, the effective coverage of these systems, that is the number of persons affiliated or contributing as a proportion of the labour force, slipped from a 13-country average of 43.4% in 2014 to 41.7% in 2019, thus returning to the levels prevailing in 2010.

In 2019, over half of all persons employed and nearly 60% of the population aged 15–64 who were in the labour force were neither affiliated nor contributing to a pension system. Despite the efforts made in some countries to extend coverage to own-account and informal workers, these figures largely reflect the widespread presence of labour informality and the weakness of mechanisms to control evasion and avoidance in respect of pension contributions.

There are multiple and persistent inequalities in rates of affiliation and contribution to pension systems. In 2019, the proportion of employed persons in the highest income decile who were either affiliated or contributing was 63 percentage points more than in the first decile; and the rate in the latter was just 8% and unchanged from 2010 (see figure III.1). There is also a wide gap in pension coverage between wage-earners and other workers; and affiliation or contribution to pension systems was considerably lower in rural areas than in urban ones.[5] Although this gap narrowed slightly between 2010 and 2019 (from 34 to 31 percentage points), information for 14 countries around 2019 shows that, on average, only 21.4% of employed persons in rural areas were affiliated or contributing, compared to 52.4% in urban zones. Moreover, employed young persons between 15 and 29 years of age have less coverage than those aged 30–64.[6]

Figure III.1

Latin America (15 countries): affiliation or contributions to pension systems among employed persons aged 15 and over, by income decile, area of residence, wage-earning status and age group, around 2010 and 2019a b

(Percentages)

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

a Weighted averages of income deciles, wage-earning status and age group. The countries included are: Argentina (urban areas), Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay. The averages for wage-earners and non-wage earners exclude Argentina and the Dominican Republic.

b Weighted averages of area of residence. The countries included are: Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

The lack of protection for workers becomes exacerbated by ethno-racial status, as can be seen in the case of own-account workers (see figure III.2). While in some countries (Mexico, Peru and the Plurinational State of Bolivia), practically all self-employed workers have no pension coverage, in others coverage has been expanded by applying simplified tax regimes to small-scale taxpayers; but large ethno-racial disparities persist.[7] This reflects the even more precarious labour market participation of indigenous and Afrodescendent workers, as well as the higher barriers they face in accessing social protection.

Figure III.2

Latin America (8 countries): affiliation or contribution to pension systems among own-account workers, by ethno-racial status, around 2019a

(Percentages)

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

a The figures for Ecuador and the Plurinational State of Bolivia are based on the pension system affiliation variable, while those for remainder of the countries refer to contribution to such systems.

(b) Access to pensions by older persons

In Latin America, the coverage of all contributory and non-contributory pensions among older persons expanded by nearly 10 percentage points between 2010 and 2019; and the large access gap between the lowest and highest income quintiles narrowed from 40 to 22 percentage points (see figure III.3). Nonetheless, a quarter of individuals aged 65 and over still did not have access to a pension in 2019.

Figure III.3

Latin America (15 countries): contributory and non-contributory pension coverage among persons aged 65 and over, by income quintile, gender, area of residence and total, around 2010 and 2019a

(Percentages)

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

a Weighted averages for 15 countries: Argentina (urban areas), Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay. The averages include the receipt of contributory and non-contributory pensions. The receipt of old-age, disability and survivors’ pensions is included in countries where their coverage is reported separately. The breakdown by area of residence does not include Argentina.

The main factor driving the progress in coverage is the expansion of non-contributory pensions, in which the amounts are much smaller than those paid by contributory regimes (ECLAC, 2018b).[8] Between 2010 and 2019, for seven countries in which it is possible to analyse the trend of both contributory and non-contributory pension coverage based on household surveys (Chile, Costa Rica, Ecuador, Mexico, Panama, the Plurinational State of Bolivia and Paraguay), non-contributory pension coverage increased in all cases except Ecuador. Mexico and Paraguay achieved increases of 15 and 37 percentage points, respectively. In four of the seven countries (Chile, Costa Rica, Paraguay and the Plurinational State of Bolivia), contributory coverage declined during the period.

In terms of the gender gap in access to pensions, in both 2010 and 2019 men aged 65 and over enjoyed greater coverage than women (see figure III.3). The difference is particularly large in the case of contributory pensions (access for men is 8.4 percentage points greater); but it is reversed in the case of non-contributory ones (a difference of 3.5 percentage points in favour of women) (see figure III.4). These different coverage rates partly explain the persistence of wide disparities in the pension amounts received by women and men (ECLAC, 2018b).[9]

Figure III.4

Latin America (11 countries): receipt of contributory and non-contributory pensions among persons aged 65 and over, by gender, area of residence, and extreme income quintiles, around 2019a

(Percentages)

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

a Weighted averages. Includes countries whose surveys allow a breakdown between contributory and non-contributory pensions. In the case of contributory pensions, it includes the receipt of old age, disability and survivors’ pensions. The non-contributory pensions identified are: Renta Dignidad Universal old-age income (Plurinational State of Bolivia); Continuous benefit programme (Brazil); Basic Solidarity Old-Age Pension and Basic Solidarity Disability Pension (Chile); Colombia Mayor (Colombia); Non-contributory pension regime (Costa Rica); Protection programme for old age in extreme poverty (Dominican Republic); Human Development Grant and Joaquín Gallegos Lara Allowance (Ecuador); Universal pension for older persons and other programmes for older persons (Mexico); 120 a los 65 Special programme of economic assistance for older persons and Guardian Angel programme (Panama); Food pension for older persons in a situation of poverty (Paraguay); and Pensión 65 National Solidarity Assistance Programme (Peru).

The apparent absence of gaps between the urban and rural population shown by an analysis of joint access to contributory and non-contributory pensions (see figure III.3) also conceals wide disparities in contributory and non-contributory coverage (see figure III.4).

(c) Affiliation and contribution to health-care systems

The COVID-19 pandemic exposes the urgent need to guarantee the right to health. Attaining this goal involves tackling the weaknesses of the region’s health systems, which are underfunded and fragmented and suffer from significant barriers to coverage, compounded by inequities in quality and effective access.

Data on affiliation or contribution to health systems in Latin America show that, in 2019, 40% of persons employed in the labour market in 13 of the subregion’s countries were not insured (see figure III.5). Between 2010 and 2019, coverage expanded by 4 percentage points, with increases in all income deciles. However, the gap between the lowest and highest income deciles remained unchanged throughout the period at 47 percentage points; and only from the fourth income decile onward does coverage exceed 50% of employed persons. There was also a slight increase in affiliation or contribution to health systems in rural areas, with a consequent reduction in the gap between urban and rural areas; and an increase in coverage among non-wage-earning workers, even though more than half of them remain excluded.

Figure III.5

Latin America (13 countries): affiliation or contribution to health systems by employed persons aged 15 or over, by income decile, area of residence and wage-earning status, around 2010 and 2019a

(Percentages)

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

a Weighted averages. The countries included are Argentina (urban areas), Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay. The breakdown by area of residence does not include Argentina.

The foregoing reveals the need to expand universal access to health care and strengthen health systems, focusing on primary care and prioritizing vulnerable populations. It is therefore essential to strengthen synergies between the healthcare and social protection systems (see box III.1).

Box III.1

Building bridges between the health and social protection sectors to promote comprehensive well-being among individuals and communities

Given their role in overcoming poverty and reducing inequality, social protection systems are one of the government responses that affect the social determinants of the population’s health, especially among the most vulnerable groups.

Contributory social protection directly alleviates the high costs involved in accessing health services; and it mitigates the impact of other indirect costs (such as lost income as a result of illness or disability) and non-medical expenses associated with the use of health services (such as transport, food and care). On average, households in the region finance more than one third (34%) of their health care through out-of-pocket expenses; and nearly 95 million people incur catastrophic health expenditures that leave them impoverished. Social protection can thus prevent households from falling into poverty or from worsening an existing poverty situation.

Non-contributory social protection, on the other hand, can help overcome the barriers to health-care access faced by various disadvantaged population groups. For example, conditional cash transfer programmes have revealed unsatisfied demand for health services in the poorest and most vulnerable communities. Non-contributory social protection also plays a central role in supporting the nutrition and healthy development of children belonging to vulnerable households. Comprehensive early childhood care programmes, aimed at reducing the risks faced by the child population, seek to guarantee adequate nutrition and access to health, education and care services, while also promoting the healthy cognitive, emotional and social development of this population group. This also has positive effects on their health and nutritional status, while helping to prevent health problems and reduce both short- and long-term inequalities in health and other domains. Social protection actions aimed at improving housing conditions and access to basic services also have a positive impact on the health of individuals and communities.

Examples of social protection mechanisms that can strengthen health

Social protection component

Social protection actions and their relationship to health

Non-contributory pillar

Conditional and unconditional cash transfers:

- Expand access to health services (particularly those related to mother-and-child health) for populations living in poverty and extreme poverty, synergistically addressing gender inequalities in their design.

- Transmit health information for promotion and prevention among participating families.

- Promote intersectoral coordination.

In-kind transfers (such as feeding or nutritional-supplementation programmes):

- Meet the nutritional needs of children, especially those living in poverty and extreme poverty.

Comprehensive early childhood care programmes and integrated care systems:

- Coordinate actions in the domains of health, nutrition, education and care targeted to early childhood and the various populations under care, with a view to promoting their full development.

- Foster intersectoral coordination.

Housing promotion and access programmes:

- Expand access to housing with basic services and reduce exposure to environmental health hazards.

Contributory pillar

Health insurance:

- Expand coverage and access to health services.

- Provide financial protection to households.

Leave (maternity/paternity and parental) and protection against dismissal during pregnancy and the postpartum period:

- Protect the physical and mental health of female workers during pregnancy; facilitate take-up of leave by mothers and fathers, as well as breastfeeding.

Source: L. Abramo, S. Cecchini and H. Ullmann, “Enfrentar las desigualdades en salud en América Latina: el rol de la protección social”, Ciência e Saúde Coletiva, vol. 25, No. 5, Río de Janeiro, Brazilian Association of Collective Health (ABRASCO), 2020.

2. Limited access to non-contributory cash transfers

Administrative data on the coverage of conditional cash transfer programmes and non-contributory old-age pensions (social pensions) provide an approximation to the level of access to cash transfers that prevailed pre-crisis for the most vulnerable populations (see figure III.6). These transfers are important for guaranteeing at least a basic level of consumption. In general, however, the cash benefits provided by these programmes are small relative to the value of both the poverty line and the income deficit of the population in poverty (the distance between their autonomous income and the poverty line), which means that households will not be able to escape poverty merely by receiving transfers (Abramo, Cecchini and Morales, 2019; Cecchini, Villatoro and Mancero, 2021).[10]

Administrative data show that the average coverage of conditional cash transfer programmes in Latin America and the Caribbean shrank by nearly 1 percentage point between 2010 and 2019. In contrast, the coverage of old-age social pensions has remained unchanged in the last five years and in 2019 reached 22.6% of people aged 60 years and older. Pensions for persons with disabilities covered 0.9% of the total population of 14 of the region’s countries in that year.

Figure III.6

Latin America and the Caribbean (27 countries): coverage of conditional cash transfer programmes and old-age social pensions, around 2010, 2014 and 2019a

(Percentage of total population and population aged 60 years and over)

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/sp.

a Simple averages. The coverage of conditional cash transfer programmes reflects programme information for Argentina, Belize, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Mexico, Panama, Paraguay, Peru, the Plurinational State of Bolivia, Trinidad and Tobago, and Uruguay. Old-age pension coverage includes information from Antigua and Barbuda, Argentina, the Bahamas, Barbados, Belize, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Ecuador, El Salvador, Guatemala, Guyana, Mexico, Panama, Paraguay, Peru, Saint Kitts and Nevis, Trinidad and Tobago, the Plurinational State of Bolivia and Uruguay. Mexico and Peru are excluded in the simple averages for around 2010 and 2014 owing to a lack of information.

Access to social protection by households with children and adolescents displayed significant disparities in the period leading up to the pandemic (see box III.2). Given the sharp increase expected in child monetary poverty as a result of COVID-19, this scenario could have devastating consequences for the comprehensive development of children and adolescents, who should be the priority focus of the countries’ recovery strategies (ECLAC/UNICEF, 2020).

Box III.2

Social protection gaps in households with children and adolescents

The Economic Commission for Latin America and the Caribbean (ECLAC) and the United Nations Children’s Fund (UNICEF) (2020) have warned that the economic and social crisis caused by COVID-19 could have serious consequences for the region’s children and adolescents. It has been predicted that 51.3% of this population, or one out of every two children and adolescents in Latin America, will be living in monetary poverty in 2020 because of the pandemic. This could affect their educational and learning trajectories, their access to adequate food and their health status; and it could even lead to an increase in child labour.a Thus, the need to consolidate universal and comprehensive child-sensitive social protection systems is more urgent than ever.

Following the analytical model proposed in ECLAC (2012a and 2012b), a typology was constructed that classifies the access of households with children and adolescents to contributory, non-contributory or combined social protection, or the lack of access thereto (ECLAC/UNICEF, 2020). For this purpose, household surveys in Latin American countries were used to identify households in which the main income-earner, or his/her spouse, was in the active phase of the life cycle (between 15 and 64 years of age in the case of men and between 15 and 60 in the case of women). Their affiliation or contribution to pension systems was then identified, to verify the household’s link to contributory social protection, as well as the receipt of public transfers and other non-contributory benefits.

Although with large differences between one country and another, around 2018 (before the crisis), 33% of households with children and adolescents were not receiving any of these benefits, while an estimated 41% had access through the contributory route only, 19% had non-contributory access and 6% had combined coverage.

Latin America (16 countries): distribution of households with children and adolescents whose head of household or spouse is in the active stage of the life cycle, by access to social protection, around 2018

(Percentages)

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

a The survey records the receipt of monetary assistance from the government, without identifying specific programmes.

b Weighted average. Data for Nicaragua correspond to 2014, those for Panama refer to 2016, and those for Argentina and Chile to 2017.

This exercise has its shortcomings. First, by focusing on coverage and benefits reported in household surveys, it only considers benefits that are covered by these surveys and can be clearly classified. Accordingly, the real coverage of the programmes in the different countries could be underestimated.b Second, access to contributory social protection is limited here to affiliation or contribution to pension systems, owing to the wider availability of this indicator at the regional level. This does not make it possible to assess the coverage of other highly relevant benefits, such as unemployment insurance or family allowances, which are reported less in the country surveys. Third, the exercise does not consider the sufficiency of the benefits in question, which would undoubtedly enrich the analysis of the major shortcomings that persist in the region’s social protection systems. The fourth limitation is that using the household as the unit of analysis conceals the differentiated access to social protection enjoyed by each of its members.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Social Panorama of Latin America, 2011 (LC/G.2514-P), Santiago, 2012; Eslabones de la desigualdad: heterogeneidad estructural, empleo y protección social (LC/G.2539), Santiago, 2012; Economic Commission for Latin America and the Caribbean/United Nations Children’s Fund (ECLAC/UNICEF), “Social protection for families with children and adolescents in Latin America and the Caribbean: an imperative to address the impact of COVID-19”, COVID-19 Report, Santiago, 2020; Economic Commission for Latin America and the Caribbean/International Labour Organization (ECLAC/ILO), “The COVID-19 pandemic could increase child labour in Latin America and the Caribbean”, Technical Note, N° 1, Santiago, 2020; P. Villatoro and S. Cecchini, “¿Cuál es el alcance de las transferencias no contributivas en América Latina? Discrepancias entre encuestas y registros”, Statistical Studies series, No. 96 (LC/TS.2018/46), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2018.

a Estimations contained in ECLAC/ILO (2020) for Chile, Mexico and Peru indicate that child labour could increase by at least 1 to 3 percentage points as a result of the pandemic, which means that between 109,000 and 326,000 children and adolescents would be added to the 10.5 million minors already engaged in child labour.

b See Villatoro and Cecchini (2018) for a review of the discrepancies in coverage reported through surveys and administrative records.

B. Responses to the pandemic from the social protection systems

To address the socioeconomic impacts of the COVID-19 pandemic, the governments of Latin America and the Caribbean have adopted social protection measures, as well as other forms of support targeted primarily on individuals and households living in situations of poverty and vulnerability. In addition to the set of contributory and social protection measures targeting formal workers, a total of 263 non-contributory measures have been adopted in 32 countries during 2020. These include cash transfers, food and medicine deliveries, and actions to ensure the provision of basic services. Cash and in-kind transfers are estimated to reach an average of 49.4% of the population in the region’s countries.

The countries of Latin America and the Caribbean have adopted various social protection measures in response to the economic and social consequences of the pandemic. Although the main trend in the region has been the implementation of non-contributory measures that provide cash transfers, food and basic services to poor and vulnerable populations, there are also measures to protect formal workers (see box III.3), as well as other forms of direct support for individuals and families (see table III.1). The countries have also adopted pension measures; and the crisis is having a major impact on pension systems, as discussed below. Social protection measures for the population living in poverty and vulnerability are subsequently reviewed, with emphasis on their coverage and adequacy.

Box III.3

Latin America and the Caribbean: unemployment insurance in the face of the COVID-19 pandemic

In response to the pandemic’s adverse employment consequences, the countries are implementing a series of measures to protect formal workers, such as guaranteeing their income in the event of dismissal or maintaining the employment relationship (ECLAC, 2020b; ECLAC/ILO, 2020). The measures include extending unemployment insurance coverage, improving the amount of benefits or lengthening the period during which they can be received.a In Chile, Law No. 21.227 allowed access to unemployment insurance benefits under Law No. 19.728 in exceptional circumstances, such as temporary business closure or agreements to suspend contracts or temporarily reduce working hours. Under this modality, the worker receives income from unemployment insurance, while the employer must continue to pay social security and health contributions (ECLAC/ILO, 2020). In the Caribbean subregion, the unemployment insurance schemes that have been operating in Barbados and the Bahamas since 1981 and 2009, respectively, have been supplemented during the crisis, to include temporary benefits for self-employed workers. In Barbados, a Business Cessation Benefit was implemented for self-employed workers who did not qualify for unemployment benefits, despite paying contributions to the National Social Security Service. In the Bahamas, the temporary unemployment benefit is targeted on own-account workers in the tourism sector. In Anguilla, a COVID-19 temporary unemployment benefit has been introduced which maintains full pay for insured workers and 80% of the full rate to those who are uninsured. Saint Kitts and Nevis and Saint Vincent and the Grenadines have also implemented new temporary unemployment benefits provided through the social security system, but limited to insured workers only.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of S. Austin, “Vulnerable programme put in place for families”, Cheapside, Barbados Government Information Service (BGIS), 9 April 2020 [online] https://gisbarbados.gov.bb/blog/vulnerable-programme-put-in-place-for-families/; Caribbean News Global, “Rising stronger from the ashes of COVID-19: part 2”, Amman, MENAFN, 30 March 2020 [online] https://menafn.com/1099935399/Rising-stronger-from-the-ashes-of-COVID-19-Part-2; K. Morgan, “COVID-19 Temporary Unemployment/Underemployment Assistance Benefit (UAB)”, CARICOM Today, 16 April 2020 [online] https://today.caricom.org/2020/04/16/covid-19-temporary-unemployment-underemployment-assistance-benefit-uab/; Economic Commission for Latin America and the Caribbean (ECLAC), “The social challenge in times of COVID-19”, COVID-19 Special Report, No. 3, Santiago, 2020; Economic Commission for Latin America and the Caribbean/International Labour Organization (ECLAC/ILO), “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, 2020; Government of Anguilla, “2020 Budget Address: Building a Dynamic Economy”, The Valley, 2020 [online] http://www.gov.ai/documents/2020%20Budget%20Address.pdf; Ministry of Foreign Affairs, “Statement on the fiscal and economic impact of COVID-19”, Nassau, 2020 [online] https://mofa.gov.bs/statement-on-the-fiscal-and-economic-impact-of-covid-19-2/; Social Security Administration (SSA), Social Security Programmes Throughout the World: The Americas, 2019, Washington, D.C., 2020; Saint Kitts and Nevis Social Security Board, “Social Security COVID-19 Emergency Relief Fund”, Basseterre, 1 April 2020 [online] https://socialsecurity.kn/press/press-releases-2020-press/social-security-covid-19-emergency-relief-fund/; United Nations, Regional data bank for statistical follow-up to the SDGs in Latin America and the Caribbean, 2021 [online database] https://agenda2030lac.org/estadisticas/regional-data-bank-statistical-follow-up-sdg-1.html?lang=en., 2020; Saint Kitts and Nevis Social Security Board, “Social Security COVID-19 Emergency Relief Fund”, Basseterre, 1 de abril de 2020 [en línea] https://socialsecurity.kn/press/press-releases-2020-press/social-security-covid-19-emergency-relief-fund/; Naciones Unidas, Banco de datos regional para el seguimiento de los ODS en América Latina y el Caribe, 2021 [base de datos en línea] https://agenda2030lac.org/estadisticas/banco-datos-regional-seguimiento-ods.html?lang=es.

a In 2016, only 12.2% of unemployed persons in 14 Latin American and Caribbean countries received some form of cash support for unemployment. See United Nations (2021).

Table III.1

Latin America and the Caribbean: social protection measures to address COVID-19

Cash transfersa

In-kind transfers

Supply of basic services

Social protection for formal workers

Other direct support to individuals and families

– New cash transfer programmes

– Extension of existing cash transfer programmes (advance payments, increase in amounts and expansion of coverage, etc.)

– Food

– Medicines

– Masks

– Toiletries

– Suspension of, or exemption from, payment of bills for:

- Water

- Electricity

- Gas

- ICT (telephone, internet, TV)

– Reduction of exposure to COVID-19 (teleworking)

– Income and job protection (unemployment insurance, leave of absence, prohibition of layoffs)

– Tax relief

– Facilities for payment of loans and mortgages

– Price controls

Source: Economic Commission for Latin America and the Caribbean (ECLAC), “The social challenge in times of COVID-19”, COVID-19 Special Report, No. 3, Santiago, 2020.

a Transfers to individuals and households in situations of poverty and vulnerability (includes informal workers).

1. Impact on contributions to pension systems

In the pensions domain, the countries have mainly applied four types of measure: (i) payment of special grants for retirees who receive the lowest pensions in the pension system (sometimes complemented with smaller grants for those receiving higher pensions); (ii) advance pension payments for a defined number of months; (iii) withdrawal of funds from individually funded accounts (see box III.4) and (iv) suspension of the payment of employer contributions (ECLAC, 2020b).

Box III.4

Chile and Peru: withdrawal of funds from individual capitalization accounts

In response to the crisis, Chile and Peru have implemented measures allowing pension fund affiliates to voluntarily withdraw funds from their individually funded accounts. In the case of Peru, Emergency Decree No. 034-2020 of 1 April 2020 allowed affiliates of the Private Pension System (SPP) who had not contributed for six months or more to withdraw up to 2,000 soles (US$ 563) (Office of the President of the Republic of Peru, 2020).a On 1 May 2020, Law No. 31.017 made it possible to withdraw up to 25% of the total balance of the individual capitalization account for all SPP affiliates, with a maximum withdrawal equivalent to 12,900 soles (US$ 3,633) and a minimum of 4,300 soles (US$ 1,211) (AS Perú, 2020).b In addition, Law No. 31,068 of 5 November 2020 approved a new withdrawal of up to four tax units (unidades tributarias), equivalent to 17,200 soles (US$ 4,845), for affiliates who had no record of contributions in their individual capitalization accounts for at least the 12 months up to 31 October 2020, or for those who suffer from diagnosed oncological diseases; or a withdrawal of up to one tax unit (4,300 soles or US$ 1,211) for those who had not contributed in the month of October 2020.c In the case of Chile, Law No. 21.248 of 30 July 2020 allowed for a once-only voluntary withdrawal of 10% of the individual capitalization funds, with a maximum withdrawal of 4.3 million pesos (US$ 5,559)d and a minimum of 1 million pesos (US$ 1,293) (or the total fund balance if less than 35 Unidades de Fomento).e Affiliates have a period of one year from the date of enactment of the law to make the withdrawal request. Subsequently, a second voluntary withdrawal of an additional 10% was approved.

Both the Central Reserve Bank of Peru and the Central Bank of Chile implemented measures to provide liquidity to facilitate the withdrawal of funds (Central Bank of Chile, 2020; Central Reserve Bank of Peru, 2020). The Central Bank of Chile (2020, p. 26) states that the volume of savings withdrawn, together with preliminary information from surveys and retail sales, is consistent with a significant —albeit transitory— boost to consumption. These resources are expected to provide significant relief to households that have lost their income sources and do not have access to social protection mechanisms to protect their consumption.f Nonetheless, it is also essential to consider the negative effects that these withdrawals may have on the future adequacy of pensions, which are already limited and unequal; and other mechanisms should be considered for protecting the consumption and well-being of individuals and households in the face of the crisis, such as the basic emergency income proposed by the Economic Commission for Latin America and the Caribbean (ECLAC).

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Central Bank of Chile, Informe de Política Monetaria: septiembre 2020, Santiago, 2020; Central Reserve Bank of Perú, “Las operaciones repo del BCRP a las AFP no son créditos y protegen los fondos de los afiliados”, Lima, 2020 [online] https://www.bcrp.gob.pe/docs/Transparencia/Notas-Informativas/2020/nota-informativa-2020-06-01.pdf; Presidency of the Republic of Peru, “Decreto de Urgencia que establece el retiro extraordinario del fondo de pensiones en el Sistema Privado de Pensiones como medida para mitigar efectos económicos del aislamiento social obligatorio y otras medidas”, El Peruano, Lima, 1 April 2020 [online] https://cdn.www.gob.pe/uploads/document/file/574665/DU_034-2020.pdf; AS Perú, “Retiro de AFP en Perú: ¿quiénes pueden retirar el 25% del dinero?”, Lima, 12 May 2020 [online] https://peru.as.com/peru/2020/05/12/actualidad/1589305517_121785.html; Congress of the Republic of Peru, “Ley que Establece Medidas para Aliviar la Economía Familiar y Dinamizar la Economía Nacional en el Año 2020”, El Peruano, Lima, 1 May 2020 [online] https://busquedas.elperuano.pe/download/url/ley-que-establece-medidas-para-aliviar-la-economia-familiar-ley-n-31017-1865958-1; Peruvian News Agency, “AFP: oficializan ley que faculta retiro de fondo de pensiones”, Lima,

18 November 2020 [online] https://andina.pe/agencia/noticia-afp-oficializan-ley-faculta-retiro-fondo-pensiones-821884.aspx; TúInfluyes, “10%, pensiones y coronavirus: radiografía de la crisis”, Santiago, 2020 [online] https://www.tuinfluyes.com/assets/estudios/ESTUDIO_TUINFLUYES_JULIO_2020.pdf.

a Based on information as of 23 September 2020, US$ 1 is equivalent to 3.55 soles.

b For persons who have less than one tax unit accumulated in their individual capitalization account, the law allows the withdrawal of 100% of the funds. See Congress of the Republic of Peru (2020).

c See [online] https://andina.pe/agencia/noticia-afp-oficializan-ley-faculta-retiro-fondo-pensiones-821884.aspx.

d On 23 September 2020, US$ 1 was equivalent to 773.40 Chilean pesos, according to the dólar observado exchange rate published by the Central Bank of Chile.

e The Unidad de Fomento (UF) is a unit of account that is indexed to Chilean inflation measured by the consumer price index. Based on the values of the UF and the dollar on 23 September 2020, as reported by the Central Bank of Chile, the amount indicated would be US$ 1,299.

f Survey data show that 44% of people in Chile said they would use the money withdrawn to pay debts and bills, while 21% stated that they would use it to buy food or basic necessities (see TúInfluyes, 2020).

Aside from the measures adopted, the effects of the crisis on the pension systems as a whole need to be considered, focusing particularly on affiliation or contribution, given the preliminary evidence of a reduction in the number of effective contributors to the pension systems owing to the employment effects of the pandemic. All countries for which information is available for the April–June 2020 quarter experienced year-on-year reductions in the number of contributors, ranging from 2.8% in Argentina to 6.8% in Chile (see table III.2). This scenario is expected to lead to a reduction in contribution density, potential pension gaps and lower contribution income, which will translate into reductions in benefits, the amount paid, or access. This situation is especially critical for members of funded schemes who are close to retirement (Arenas de Mesa, 2020).

Table III.2

Latin America (5 countries): variation in the number of contributors, April–June quarter 2019 and 2020 or latest available data

(Absolute numbers and percentages)

Country

Argentinaa

Chileb

Colombiac

Costa Ricad

Mexicoe

2019

12 141 148

5 512 964

6 360 230

1 116 649

20 368 666

2020

11 794 667

5 137 621

5 973 483

1 071 661

19 499 859

Year-on-year difference

-346 481

-375 343

-386 747

-44 988

-868 807

Year-on-year change

-2.8

-6.8

-6.1

-4.0

-4.3

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Ministry of Labour, Employment and Social Security, “Estudios y estadísticas laborales” [online] http://www.trabajo.gob.ar/estadisticas/; Superintendency of Pensions, “AFP” [online] https://www.spensiones.cl/apps/centroEstadisticas/paginaCuadrosCCEE.php?menu=sci&menuN1=cotycot&menuN2=afp; Financial Superintendence of Colombia, “Afiliados” [online] https://www.superfinanciera.gov.co/jsp/9110; Superintendency of Pensions, “Aportantes por entidad” [online] https://www.supen.fi.cr/aportantes-por-entidad; Center for the Study of Public Finances, “Análisis sobre la situación económica al segundo trimestre de 2020”, Mexico City, 2020 [online] https://www.cefp.gob.mx/publicaciones/documento/2020/cefp0282020.pdf.

a Data corresponding to June. Refers to registered workers, including private, public and private-household employees, self-employed, workers covered by the monotributo and monotributo social (single-tax and social single-tax) regimes, seasonally unadjusted.

b Corresponds to the number of active members and voluntary members who contributed in June in respect of pay earned in May and June.

c Data for June and only for private funds.

d Considers the information for contributors, that is affiliates who made a contribution to their individual account for the Obligatory Pension Regime during the reference month.

e Number of workers insured by the Mexican Social Security Institute (IMSS).

In the context of the pandemic, reviewing occupational pension coverage has limited analytical power owing to the large number of individuals who have left the labour force. Coverage of the working-age population, on the other hand, includes those who dropped out of the labour force as a result of the persistent labour market contraction caused by the pandemic. All countries for which data are available experienced reductions in the share of the working-age population who are contributors, ranging from -1.2 percentage points in Colombia to -3.2 percentage points in Chile (see figure III.7).

Figure III.7

Latin America

(5 countries): variation in the share of contributors in the working-age population, April–June quarter 2019 and 2020 or latest available data

(Percentage points)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), “Latin America and the Caribbean: population estimates and projections. Revision 2019”, Santiago, 2019 [online database] https://www.cepal.org/en/topics/demographic-projections/latin-america-and-caribbean-population-estimates-and-projections; United Nations, World Population Prospects 2019 [online database] https://population.un.org/wpp/; Ministry of Labour, Employment and Social Security, “Estudios y estadísticas laborales” [online] http://www.trabajo.gob.ar/estadisticas/; Superintendency of Pensions, “AFP” [online] https://www.spensiones.cl/apps/centroEstadisticas/paginaCuadrosCCEE.php?menu=sci&menuN1=cotycot&menuN2=afp; Financial Superintendence of Colombia, “Afiliados” [online] https://www.superfinanciera.gov.co/jsp/9110; Superintendency of Pensions, “Aportantes por entidad” [online] https://www.supen.fi.cr/aportantes-por-entidad; Center for the Study of Public Finances, “Análisis sobre la situación económica al segundo trimestre de 2020”, Mexico City, 2020 [online] https://www.cefp.gob.mx/publicaciones/documento/2020/cefp0282020.pdf.

a Data corresponding to June. Refers to registered workers, including private, public and private-household employees, self-employed, workers covered by the monotributo and monotributo social (single-tax and social single-tax) regimes, seasonally unadjusted.

b Corresponds to the number of active members and voluntary members who contributed in June in respect of pay earned in May and June.

c Data for June and only for private funds.

d Considers the information for contributors, that is affiliates who made a contribution to their individual account in the obligatory pension regime during the month in question.

e Number of workers insured by the Mexican Social Security Institute (IMSS)

2. Social protection for people living in poverty and vulnerability

The enormous difficulties that people living in poverty and vulnerability must already overcome to meet basic needs are compounded in times of pandemic. To address the effects of the crisis on these sectors of society by guaranteeing income, food security and access to basic services, since 1 March 2020 countries have rolled out various social protection measures, combining existing programmes with emergency programmes (ECLAC 2020b and 2020c).[11] These measures, depending on the country, are supported either by laws, or by executive decrees or ministerial regulations (Blofield, Giambruno and Filgueira, 2020). The number of countries implementing actions and the number of measures announced both increased almost daily during the second half of March. In mid-June, there was a second rise, as the health emergency had become more severe and was lasting longer. Countries not only extended the duration, instalments[12] and coverage[13] of the measures in force, but also announced further assistance.[14] By 6 November 2020, around 80% of these measures consisted of up to three instalments.

According to official information, by 6 November 2020, 32 countries of Latin America and the Caribbean had adopted 263 social protection measures aimed at the most vulnerable (see figure III.8). These measures are intended to support this population in coping with the loss of income caused by the pandemic. Of the total of 263 measures comprising cash or in-kind transfers or guaranteed access to basic services, 127 were adopted in South America, 74 in the Caribbean and 62 in Central America.

Figure III.8

Latin America and the Caribbean (32 countries): emergency social protection measures for the population living in poverty and vulnerability, from 1 March to 6 November 2020, by weeka

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official data from the countries; Economic Commission for Latin America and the Caribbean (ECLAC), COVID-19 Observatory in Latin America and the Caribbean [online database] https://www.cepal.org/es/temas/covid-19; “Social protection measures to confront COVID-19”, Social Development and COVID-19 in Latin America and the Caribbean [online database] https://dds.cepal.org/observatorio/socialcovid19/en/listamedidas.php.

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

Non-contributory emergency social protection measures consist mainly of cash transfers (a total of 147 measures in 30 countries), distribution of food and medicines (73 measures in 29 countries), and guaranteeing and facilitating access to basic services (water, energy, telephone and Internet) (43 measures in 26 countries) (see figure III.9).[15]

Figure III.9

Latin America and the Caribbean (32 countries): emergency social protection measures for the population living in poverty and vulnerability, by type of measure, 2020a

(Number of countries and measures, and percentage distribution)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official data from the countries; Economic Commission for Latin America and the Caribbean (ECLAC), COVID-19 Observatory in Latin America and the Caribbean [online database] https://www.cepal.org/es/temas/covid-19; “Social protection measures to confront COVID-19”, Social Development and COVID-19 in Latin America and the Caribbean [online database] https://dds.cepal.org/observatorio/socialcovid19/en/listamedidas.php.

a Includes measures announced between 1 March and 6 November 2020. The countries are Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, the Plurinational State of Bolivia, Peru, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago and Uruguay.

(a) Cash transfers

The cash transfers implemented to address the COVID-19 crisis have taken four different formats: (i) new cash transfers (100 measures); (ii) increases in the amount of existing transfers (26 measures);[16] (iii) advance payments under existing transfer programmes (12 measures);[17] and (iv) increased population coverage of existing transfer programmes (9 measures) (see figure III.9 and annex figures III.A1.3 and III.A1.4).[18]

Although new cash transfers have been the most frequent measure in the region (accounting for 38% of all measures adopted), it is also important to consider the adjustments made to existing programmes. Mexico is noteworthy in this regard, since before the pandemic, in 2019, it embarked on a policy of significantly expanding cash transfers (the most significant measures include a universal pension for the elderly, a universal allowance for students in the last few years of secondary school, an allowance for persons with disabilities, support for rural producers for reforestation, and support for young people to obtain work experience), which entailed social protection expenditure of 0.85% of GDP beyond that spent in previous years.[19] The fact that these transfers had been put in place in the year before the pandemic made it easier to bring forward payments from April 2020 onward, particularly for pensions for older persons and persons with disabilities.

It is also important to underscore that the pandemic has driven innovation in various aspects of cash transfer programmes, including increased use of electronic means of payment, changes to recipient registration systems and suspension of certain prerequisites.

Several countries have turned to digital technologies to facilitate delivery of cash benefits and avoid large gatherings (ECLAC, 2020c). Bank transfers are the most frequent method of delivery (90 measures), while 13 measures use digital transfers by mobile phone, such as the Bahamas’ Government Funded Unemployment Assistance for COVID-19, Guatemala’s Bono Familia (Family Allowance), Haiti’s social assistance transfer programme and Peru’s Universal Family Allowance. However, physical distribution of cash remains frequent (39 measures).

Countries have also faced difficulties in rapidly identifying recipients of emergency benefits based on pre-existing social information systems and registers of users.[20] In order to reach population groups that are not usually included in these records (such as informal and self-employed workers, or the middle-income strata that have been left without sources of income), means of applying directly have been launched, allowing information to be provided through digital platforms or by telephone, and subsequently checked against official records.[21] For some of the measures, recipients are also identified by cross-checking different records and sources of information (Berner and Van Hemelryck, 2020).[22]

In the case of ongoing cash transfer programmes for those living in poverty, conditional programmes have suspended control or monitoring of whether conditions are met because, for example, families have been unable to send their children to school (ECLAC, 2020a). Conditions have been specifically suspended for the following programmes: Brazil’s Bolsa Família (except for controls for pregnant women), Colombia’s Familias en Acción, Costa Rica’s Avancemos and Crecemos, and Guatemala’s Bono Social. Other adaptations of conditional cash transfer programmes relate to the benefits and services they offer. The Programme of Advancement through Health and Education (PATH) in Jamaica, for example, included an Internet data grant to enable recipients to access online learning (Linton, 2020). In addition, during the health emergency, under the Abrazo programme in Paraguay protocols were formulated for visiting and monitoring participating families (Agencia IP, 2020), while in Peru the National Programme of Direct Support for the Poorest (Juntos) launched the “Aló Juntos” strategy to continue providing family support for households with mobile phones and that included children aged under one year or pregnant women (Ministry of Development and Social Inclusion, 2020).

(b) In-kind transfers and access to basic services

Distribution of food and medicines accounts for 28% of the non-contributory measures implemented.[23] In many countries, food has been supplied through existing school feeding programmes, which have been maintained despite school closures and adapted by making cash transfers, distributing food vouchers or providing meals to be taken home (ready to eat or requiring preparation). Mixed approaches have also been taken.[24] Some of these measures have been implemented in collaboration with the private sector and civil society.[25]

With regard to access to basic services, measures include a ban on disconnection of services for the entire population (Antigua and Barbuda, Dominican Republic, Ecuador and Jamaica), reconnection after disconnection owing to arrears (Bahamas, Colombia and Honduras) and deferral of bills or payment agreements (Chile, Costa Rica, Panama, Paraguay, Saint Vincent and the Grenadines, among other countries).[26] Subsidies, meanwhile, have targeted the most vulnerable households (for example, in Guatemala, Peru and the Plurinational State of Bolivia).[27] Most of these measures have been aimed at guaranteeing electricity (23 countries), water (15 countries) and Internet services (11 countries).

(c) Other direct support to individuals and families

In 2020, 28 countries also announced 75 measures to directly support individuals and families by reducing their spending. Payment schemes account for 58% of these measures and have been implemented in 24 countries. They include deferral of credit and mortgage instalments, loan rescheduling and refinancing, exemption from payment or suspension of penalties and interest on arrears, and measures related to residential rent payments. In addition, 17 measures in 13 countries have provided tax relief, mainly exemption from tax fines, postponement of collection and of auctions upon default, and deferral of tax payments until after lockdowns. Lastly, a total of 14 price-setting and price-control measures have been proposed in 10 countries, including price controls on basic food basket items and, to a lesser extent, a ban on rent increases (see figure III.10).

Figure III.10

Latin America and the Caribbean (28 countries): other emergency direct support measures for individuals and families, by type of measure, 2020a

(Number of measures and percentage distribution)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official data from the countries; Economic Commission for Latin America and the Caribbean (ECLAC), COVID-19 Observatory in Latin America and the Caribbean [online database] https://www.cepal.org/es/temas/covid-19; “Social protection measures to confront COVID-19”, Social Development and COVID-19 in Latin America and the Caribbean [online database] https://dds.cepal.org/observatorio/socialcovid19/en/listamedidas.php.

a Covers measures announced between 1 March and 6 November 2020. The countries included are Argentina, Bahamas, Barbados, the Bolivarian Republic of Venezuela, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, the Plurinational State of Bolivia, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Trinidad and Tobago and Uruguay.

3. Coverage and sufficiency of cash and in-kind transfers

The cash and in-kind transfers announced in 2020 by the governments in the region in response to the COVID-19 crisis vary in terms of coverage and sufficiency (amount and duration). These measures are estimated to have reached 84 million households, comprising 326 million people, equivalent to 49.4% of the population of the countries of the region (see figure III.11). This coverage is some 30 percentage points higher than that of conditional cash transfer programmes and other permanent cash transfer programmes, which cover a simple average of 18.5% of the population in the region. The measures implemented by South American countries reach, on average, two-thirds of the population, while in the Caribbean they reach less than one-third. The countries with the highest absolute household coverage are Brazil (29.9 million), Argentina (10.7 million), Colombia (8 million) and Peru (7.5 million).

Figure III.11

Latin America and the Caribbean (28 countries): persons in households receiving emergency cash and in-kind transfers (2020) and conditional cash transfer programmes, simple average by subregion (latest available year)a b c

(Percentages of the total population)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official data from the countries; Economic Commission for Latin America and the Caribbean (ECLAC), COVID-19 Observatory in Latin America and the Caribbean [online database] https://www.cepal.org/es/temas/covid-19; “Social protection measures to confront COVID-19”, Social Development and COVID-19 in Latin America and the Caribbean [online database] https://dds.cepal.org/observatorio/socialcovid19/en/listamedidas.php. Economic Commission for Latin America and the Caribbean (ECLAC), CEPALSTAT [online database] https://estadisticas.cepal.org/cepalstat/Portada.html; Non-contributory Social Protection Programmes Database in Latin America and the Caribbean [online] https://dds.cepal.org/bpsnc/cct.

a Table III.A1.4 in the annex shows the cash and in-kind transfers included in the estimate of household coverage by country, as announced between 1 March and 6 November 2020. The estimate was made based on official government information (announced or effective coverage, depending on availability), taking into account the possible complementarity between the different measures announced by each country, to minimize duplication in the calculation of coverage. The coverage of persons in households benefitting from emergency measures in 2020 is estimated by multiplying the estimated household coverage by the average household size in the first income quintile, according to the latest data available from CEPALSTAT. For measures related to transfers made per person, if no information is available on the average or maximum number of recipients per household, it was assumed that there were two recipients per household.

b Coverage of conditional cash transfer programmes or other permanent cash transfer programmes in the last year based on information available in the Non-contributory Social Protection Programmes Database - Latin America and the Caribbean.

c South America includes Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, the Plurinational State of Bolivia, and Uruguay. Central America includes Costa Rica, the Dominican Republic, El Salvador, Guatemala, Honduras and Panama, as well as Haiti and Mexico. The Caribbean includes Antigua and Barbuda, Bahamas, Barbados, Belize, Guyana, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines and Trinidad and Tobago.

To be effective, social protection measures in response to the COVID-19 pandemic should at least cover the basic needs of all people in recipient households. To analyse the sufficiency of these measures, the amounts of emergency cash transfers can be compared —considering the programmes with the greatest coverage in the countries— with the poverty line and the extreme poverty line. Only 6 out of 16 Latin American countries provide cash transfers whose average monthly amount in the March–December 2020 period is close to or above the extreme poverty line. This suggests that the amounts of emergency cash transfers in several cases were not sufficient to cover the basic needs of affected people. The average monthly amount of non-contributory cash transfers does not equal or exceed one poverty line in any country in the region (see figure III.12).

Figure III.12

Latin America (16 countries): average monthly amount of cash transfers to address the COVID-19 pandemic in the period from March to December 2020, by countrya b

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official data from the countries; Economic Commission for Latin America and the Caribbean (ECLAC), COVID-19 Observatory in Latin America and the Caribbean [online database] https://www.cepal.org/es/temas/covid-19; “Social protection measures to confront COVID-19”, Social Development and COVID-19 in Latin America and the Caribbean [online database] https://dds.cepal.org/observatorio/socialcovid19/en/listamedidas.php. Economic Commission for Latin America and the Caribbean (ECLAC), CEPALSTAT [online database] https://estadisticas.cepal.org/cepalstat/Portada.html.

a Table III.A1.4 in the annex includes the monthly dollar amount of cash transfers, as well as their frequency, number of instalments and duration. The monthly amount for each measure for the period from March to December (10 months) is calculated as the product of the monthly dollar amount multiplied by the duration in months (between March and December 2020) divided by 10, according to the information announced by the countries through to 6 November 2020.

b By country, the following measures are included: Emergency Family Income in Argentina; Universal Grant and Anti-Hunger Grant in the Plurinational State of Bolivia; Federal Government Emergency Aid in Brazil; Emergency Family Income (IFE and IFE 2.0) in Chile; Solidarity Income in Colombia; Bono Proteger in Costa Rica; the Quédate en casa (Stay at home) programme in the Dominican Republic; the Health Emergency Family Protection grant in Ecuador; the US$ 300 grant in El Salvador; Bono Familia (family Grant) in Guatemala; Solidarity grant for transportation workers in Honduras; Pension Programme for the Well Being of Older Persons (advance payment of four months, equivalent to two two-month periods) in Mexico; Panama Solidarity Plan in Panama; the Pytyvõ and Pytyvõ 2.0 grants in Paraguay; Universal Family Allowance and Second Universal Family Allowance in Peru; and the Operativo Canasta Emergency food basket in Uruguay.

c The values of the 2018 urban poverty and extreme poverty lines in current dollars according to CEPALSTAT are used. The most recent urban poverty and extreme poverty lines for Chile are from 2017 and for Guatemala they are from 2014, so the poverty line was adjusted for 2018 prices using the consumer price index (CPI).

During 2020, 20 countries implemented 33 cash transfer programmes specifically targeting informal workers and other vulnerable workers, such as the self-employed (see box III.5). This is an important innovation, as the vast majority of these workers —among whom women are overrepresented— are not covered by targeted non-contributory social protection benefits or by social security, and they are likely to have insufficient savings to weather the crisis (ECLAC, 2020a). The new measures consist of a single payment or periodic payments (3 to 15 months) and the amount transferred to each individual or household varies considerably from one country to another (see figure III.13 and annex table III.A1.5).[28]

Figure III.13

Latin America and the Caribbean (12 countries): emergency cash transfers to informal workers, by type of recipient (individual or household) and duration, 2020

(Dollars)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official data from the countries; Economic Commission for Latin America and the Caribbean (ECLAC), COVID-19 Observatory in Latin America and the Caribbean [online database] https://www.cepal.org/es/temas/covid-19; “Social protection measures to confront COVID-19”, Social Development and COVID-19 in Latin America and the Caribbean [online database] https://dds.cepal.org/observatorio/socialcovid19/en/listamedidas.php. International Monetary Fund (IMF), “Exchange rates selected indicators: national currency per SDR, period average”, Washington, D.C., 2020 [online] https://data.imf.org/regular.aspx?key=61545862.

Note: The figure includes measures announced between 1 March and 6 November that primarily target informal workers. In the case of measures with individual recipients (or dependants such as children and adolescents), it is assumed that two amounts are received per family. The calculation of the total amount per household takes into account the total duration (in months) of the measure and the number of recipients per household. The average monthly exchange rate for March to October 2020 published by the International Monetary Fund (IMF) was used.

a The Pytyvõ and Pytyvõ 2.0 programmes are used, with a duration of two months each and amounts of US$ 81 and US$ 74 per person, respectively.

b Given that the total amount per household varies according to the members of the household and their sources of income (formal or informal), this value considers the average amount of the single payment of the Emergency Family Income (IFE) (US$ 192), the average amount of the three IFE 2.0 payments (around US$ 240) and the fifth and sixth instalments (announced on 26 September), which were 70% and 55%, respectively, of the previous instalments. In other words, this would mean a fifth payment of 70,000 pesos per person (around US$ 87), and a sixth payment of 55,000 pesos per person (US$ 68). From the fifth household member onward, the amount per person gradually decreases.

c In September it was extended for four more instalments (until December and for a total of nine months), for half the amount, which is to say 300 reais (US$ 56) per person and 600 reais (US$ 112) for mothers in single-parent families.

d The amount of the grant was US$ 80 from March to June and was increased to US$ 100 on 1 July.

Box III.5

Emergency Family Income (IFE) in Argentina

When the pandemic hit, Argentina was in a particularly vulnerable economic situation and in the middle of a macroeconomic crisis that had already caused two years of recession, with falls in formal employment and an increase in informality, as well as declines in household income, as well as annual inflation close to 50%. The pandemic exacerbated this situation and prompted a set of policies to reduce the impact on production and supply of basic inputs, to cushion the fall in employment and wages. One group of actions was aimed at increasing the income of people who were already included in the social protection system (such as retirees and recipients of transfers such as the Universal Child Allowance (AUH) or other social programmes) and at strengthening access to food and health protection for people living in the most vulnerable urban settlements.

To guarantee an income floor for middle- and low-income informal and self-employed workers, on 30 March 2020, ten days after the “social, preventive and compulsory isolation (ASPO)” was ordered throughout the country for non-essential workers in the economy, the Emergency Family Income (IFE) was formulated. The programme merits detailed analysis, given the volume of resources applied, its magnitude in terms of the population covered, and the innovation of swiftly including large groups of workers who were excluded from State records and who were mostly not users of banking services.

The Emergency Family Income consists of a cash transfer of 10,000 pesos (around US$ 150) for people who are unemployed or working in the informal economy, informal self-employed workers, formal workers in the lowest simplified single-tax scheme categories and workers in private households (whether formal or not). In addition, to be eligible, recipients must be between 18 and 65 years old and a native or naturalized citizen of Argentina and legally resident in the country for at least two years. The benefit may not be received at the same time as income registered with the social security system (registered employment, own-account work under the single-tax scheme and self-employment, unemployment benefit, retirement benefits, pensions or contributory or non-contributory retirement pensions), or benefits from social programmes such as Salario Social Complementario, Hacemos Futuro, Potenciar Trabajo or other national, provincial or municipal social programmes, whether the income is received by the applicant or by a member of his or her family group. The programme, however, is compatible with the Universal Child Allowance, the Universal Pregnancy Allowance for Social Protection and the Support for Argentine Students Programme (PROGRESAR).

More than 13.4 million people applied for the Emergency Family Income programme, representing 48% of the total population aged between 18 and 65, and 67% of the labour force (employed and unemployed). Applications were made directly through a digital platform and then checked against various administrative records, revealing a higher number of women applicants (52.9%).

After confirming there were no incompatibilities for individuals or households, the Emergency Family Income was granted to a total of 8.8 million people, representing 32% of the population between 18 and 65 years of age.a The first three payments entailed an outlay of 0.9% of GDP.

Ratio between applicants and recipients of the Emergency Family Income (IFE), by eligibility criteria or employment status and proportion of women recipients

Status

Applicants

(1)

Recipients

(2)

Ratio (2)/(1)

(percentages)

Proportion of women

(percentages)

Recipients of Universal Child Allowance

2 410 790

2 389 764

99

95

Low-category single-tax workers

1 367 811

688 556

50

45

Support for Argentine Students Programme (PROGRESAR)

128 201

128 201

100

67

Registered domestic workers

317 464

188 923

60

97

Informal or unemployed workers

5 461 617

5 461 617

100

38

Other

3 725 442

2

0

Total

13 411 325

8 857 063

66

56

Source: National Social Security Administration, Boletín IFEI-2020: Caracterización de la población beneficiaria, Buenos Aires, 2020 [online] http://observatorio.anses.gob.ar/archivos/documentos/Boletin%20IFE%20I-2020.pdf.

The design and rapid implementation of this programme has made it possible to reach, in addition to the 3.3 million people who were already registered, almost 5.5 million people who are in informal employment or unemployed and who otherwise could not have been reached by the State because they were not in their records when the pandemic hit. The programme also reveals the extent of the precariousness that characterizes the labour market and highlights gaps in the social protection system; just 9.3% of all recipients of the Emergency Family Income had been in at least one month of formal employment between February 2019 and February 2020.

Argentina: population aged 18–65 with Emergency Family Income

Source: National Social Security Administration, Boletín IFEI-2020: Caracterización de la población beneficiaria, Buenos Aires, 2020 [online] http://observatorio.anses.gob.ar/archivos/documentos/Boletin%20IFE%20I-2020.pdf.

Note: The boundaries and names shown on this map do not imply official endorsement or acceptance by the United Nations.

Analysis of the available information (National Social Security Administration, 2020; Ministry of Economy, 2020) shows that the programme has reached the vast majority of the population in vulnerable situations. Women are over-represented among recipients, as they are the main users of the Universal Child Allowance, allowances for domestic workers and the Support for Argentine Students Programme. In addition, there is a high proportion of young men and women: while 32% of the total population (aged 18–65) receives the Emergency Family Income, for young people aged 18–24 this percentage is 51%, and among those aged 24–34 it is 43%.

Geographically, in line with the country’s population distribution, most Emergency Family Income recipients are concentrated in the Province of Buenos Aires (36%), followed by Córdoba and Santa Fe (8% each), and Tucumán and the Autonomous City of Buenos Aires (4% each). In terms of the percentage of people between 18 and 65 years of age, the highest coverage is found in the northern provinces of the country (with structural problems of low activity ratios and high levels of informality and poverty), with figures of over 39%. The highest percentage is in the province of Santiago del Estero, where 49% of the population between 18 and 65 years of age receives the Emergency Family Income.

In terms of sufficiency, the Emergency Family Income is equivalent to around 60% of the country’s adjustable living minimum wage.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of National Social Security Administration, Boletín IFEI-2020: Caracterización de la población beneficiaria, Buenos Aires, 2020 [online] http://observatorio.anses.gob.ar/archivos/documentos/Boletin%20IFE%20I-2020.pdf; Ministry of Economy, “Ingreso Familiar de Emergencia: análisis y desafíos para la transferencia de ingresos a trabajadores/as precarios/as”, Buenos Aires, 2020 [online] https://www.argentina.gob.ar/sites/default/files/dneig-ingresofamiliardeemergencia-analisisydesafios.pdf.

a Equivalent to 44% of the country’s labour force, although it is likely that a significant portion of recipients of the Emergency Family Income are inactive.

C. Concluding remarks

Despite their limited sufficiency and temporary nature, the social protection measures adopted by the countries of the region to address the pandemic are noteworthy as they extend coverage, especially for informal workers. Most of the measures have aimed to meet basic needs and support consumption. Given pre-existing gaps in social protection systems, these measures have been key to responding to the socioeconomic effects of the COVID-19 pandemic.

Although these measures are important, when the COVID-19 crisis hit, the region already clearly needed to redesign its social protection systems to meet the challenge of building systems that were truly universal (Filgueira and others, 2020) and not focused solely on the poorest population. The pandemic revealed severe shortfalls in the coverage and sufficiency of existing benefits, and in their ability to effectively safeguard the well-being of the entire population in a crisis. The crisis also exposed the need for comprehensive social records that are sufficiently responsive to identify short-term changes in the socioeconomic situation of households (Berner and Van Hemelryck, 2020), and to facilitate increased use of banking services by the population. These aspects are critical to ensuring timely and efficient delivery of benefits.

The experience of Latin America and the Caribbean shows that there is a window of opportunity to build universal and comprehensive social protection systems, by expanding their real coverage, which is key in a situation of increased poverty and vulnerability. These systems must seek to better interlink their various components and enable rapid response to key risks to sustainable development, such as child poverty, rising school dropout rates and the care crisis. In addition, they must focus on expanding health systems to make them truly universal and extending the coverage of crucial social security instruments, such as unemployment insurance.

In this context, now more than ever consideration must be given to measures such as a universal basic income, universal transfers for children and the expansion of social pensions, in addition to guaranteeing the right to decent work, and access to social protection for all workers. The linking of these measures, their monitoring and evaluation, as well as overcoming fragmented and dichotomic systems in terms of access and quality of benefits, are undoubtedly major challenges that need to be addressed. Similarly, greater coordination between labour and social policies is vital to consolidate progress on the dual social and labour inclusion of people and on the right to decent work. Latin America and the Caribbean faces the challenge of building a welfare state that realizes rights and contributes to strengthening productivity, capabilities and resilience. Even at the current critical juncture, there are still opportunities to reflect on and shape social protection measures (ECLAC, 2020c and 2020d).

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Annex III.A1

Table III.A1.1

Latin America (18 countries): pension system affiliation or contribution among employed persons, around 2010, 2014 and 2019a b

(Percentages)

Country

Affiliated or contributing workers aged 15 or over as a percentage of employed persons…

Affiliated or contributing workers aged 15 or over as a percentage of total…

Total

Men

Women

Urbano

Rural

Wage earners

Non-wage earnersc

Employed persons

Labour force

Argentina

2010

69.5

71.8

66.6

…

…

69.5

…

…

…

2014

69.1

70.5

67.4

…

…

69.1

…

…

…

2019

68.5

70.1

66.7

…

…

68.5

…

…

…

Bolivia (Plurinational State of)d

2011

17.5

19.6

14.8

24.3

5.4

40.0

3.0

18.1

16.5

2013

21.2

23.1

18.7

29.3

6.4

47.2

4.7

22.5

20.0

2018

19.3

20.6

17.5

26.1

6.8

47.2

4.0

20.3

17.8

Brazil

2011

59.6

59.4

59.9

65.8

25.6

75.9

24.4

60.9

54.9

2014

62.1

61.4

63.0

67.7

31.7

77.7

29.4

63.8

57.1

2019

63.0

62.0

64.4

66.2

38.7

77.0

34.1

64.1

54.6

Chile

2011

68.4

70.2

65.6

69.8

57.0

81.8

22.3

69.6

60.9

2013

69.3

71.0

66.9

71.0

56.3

82.6

21.6

71.1

62.3

2017

68.2

69.4

66.5

69.5

57.2

82.7

22.7

70.5

60.3

Colombia

2010 c

30.4

30.2

30.6

36.0

10.5

56.5

8.0

31.6

26.6

2014

35.0

35.1

34.8

40.9

13.2

61.9

10.0

36.6

31.7

2018

37.4

37.0

37.9

43.6

14.6

65.3

11.3

39.2

33.5

Costa Rica

2010

67.4

71.3

60.8

71.3

60.3

75.8

41.0

68.6

61.8

2014

68.0

71.7

62.2

70.2

61.5

76.4

40.9

69.5

61.4

2019

69.6

71.9

66.1

72.1

62.2

77.7

42.8

71.4

62.4

Dominican Republicd

2010

67.4

72.5

61.6

69.2

59.5

67.4

…

…

…

2014

69.7

76.3

62.7

71.4

60.9

69.7

…

…

…

2019

72.8

77.1

68.3

74.1

65.2

72.8

…

Ecuadord

2010

34.8

34.3

35.7

40.1

24.4

49.7

16.5

35.2

30.8

2014

45.7

47.0

43.7

48.2

40.5

62.5

23.4

46.3

42.1

2019

39.5

39.6

39.4

43.4

31.9

58.2

22.2

39.7

35.2

El Salvador

2010 c

31.7

29.7

34.5

41.5

11.9

48.5

8.6

32.8

28.7

2014 c

34.6

33.4

36.2

44.5

15.3

50.5

10.8

35.6

31.2

2019

36.3

38.2

33.7

45.2

19.7

52.1

12.1

37.5

32.9

Guatemalab

2006

38.8

36.5

43.8

46.6

25.6

38.8

…

…

…

2014

28.7

26.1

35.0

37.6

15.8

28.7

…

…

…

Honduras

2010

17.9

15.5

22.3

31.3

6.2

40.1

0.7

18.9

17.0

2014

20.9

18.5

24.9

31.8

8.5

41.7

1.2

21.7

19.3

2019

17.6

15.8

20.6

27.5

5.2

34.5

1.4

18.4

16.1

Mexicoe

2010

32.5

32.4

32.5

37.9

11.9

43.6

1.6

33.6

30.0

2014

32.9

33.6

31.8

38.7

12.0

44.0

1.6

34.2

30.8

2018

31.9

33.4

29.8

38.0

12.7

43.0

2.0

33.5

30.6

Nicaraguab

2005

17.5

14.9

22.1

25.8

5.8

34.1

0.5

18.3

16.7

2014

22.8

20.1

27.2

32.2

8.6

41.0

1.3

23.7

21.4

Panamad f

2011

53.8

51.2

58.1

66.1

27.2

76.0

7.8

56.1

51.3

2014

52.8

50.6

56.2

64.1

27.0

75.2

7.3

55.2

49.8

2019

49.0

48.1

50.3

58.2

26.6

74.6

5.3

51.5

45.2

Paraguay

2010

17.3

17.8

16.5

25.2

5.5

33

0.1

18.0

16.2

2014

22.2

21.8

22.6

28.8

11.5

38.4

1.1

22.9

20.6

2019

23.7

23.6

23.8

30.3

12.2

41.1

0.9

24.8

22.2

Peru

2010

16.4

19.2

13.0

21.4

3.1

36.3

0.2

17.5

15.5

2014

20.0

22.6

16.8

25.4

4.3

42.1

0.3

21.4

18.9

2019

20.7

23.4

17.6

25.7

4.2

44.4

0.3

22.5

19.6

Uruguay

2010

69.5

70

68.8

69.4

70.0

81.9

38.0

71.2

63.0

2014

75.6

75.1

76.2

75.8

72.4

87.8

42.7

77.4

69.1

2019

75.5

74.3

77.0

75.7

72.9

88.8

42.0

76.9

67.2

Venezuela (Bolivarian Republic of)b g

2010

70.7

66.7

76.4

…

…

70.7

…

…

…

2014

72.6

68.7

77.9

…

…

72.6

…

…

…

Latin Americah

2010

45.9

45.9

45.9

51.9

17.9

62.3

13.2

46.1

41.1

2014

48.1

48.1

48.1

53.9

21.3

64.0

16.0

48.7

43.4

2019

47.2

47.3

47.2

52.4

21.4

62.5

17.1

47.7

41.7

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

a Unless otherwise specified, the data refer to contributions to the pension system.

b There are no data after 2014, so the 2019 round is not included.

c Includes employers, own-account workers, unpaid family workers and workers in cooperatives.

d The data refer to pension system affiliation.

e The data for Mexico for 2018 are not strictly comparable with those of previous years owing to changes in the wording of some of the questions on social security access. For more details of these changes, their effects on the estimation of social security coverage (health and pensions) and procedures to adjust said estimation, see National Council for the Evaluation of Social Development Policy (CONEVAL), “Ejercicio de adecuación histórica de la carencia por acceso a la seguridad social 2016 a la serie 2010-2014”, Mexico City, 2017 [online] https://www.coneval.org.mx/Medicion/MP/Documents/Pobreza_16/Notas_Pobreza_2016/Nota_tecnica_2_ajuste_seguridad_social.pdf.

f The worker is asked whether they are directly affiliated to the social security system. This indicator does not separate access to pensions from access to health benefits, and can thus lead to the overestimation of access to pension systems.

g The measurement indicates whether the worker receives social benefits as part of their job, particularly access to the pension system. It is understood as contributions to the pension system.

h The total average and the averages by gender refer to 15 countries. The Bolivarian Republic of Venezuela, Guatemala and Nicaragua are not included because information is not available for the entire series. The averages for urban and rural areas also exclude Argentina, and therefore refer to 14 countries. In Argentina, the Bolivarian Republic of Venezuela, the Dominican Republic and Guatemala (except for 2014), measurements include only the pension system contribution or affiliation of wage earners in the years under review, which is why the averages relating to coverage among wage earners and non-wage earners include 13 countries.

Table III.A1.2

Latin America (15 countries): health system affiliation or contribution among employed persons, around 2010, 2014 and 2019a b

(Percentages)

Total

Men

Women

Urban

Rural

Wage earners

Non-wage earnersc

Argentina (urban areas)

2010

73.3

71.0

76.7

73.3

…

78.5

55.8

2014

72.8

69.8

76.8

72.8

…

78.3

54.8

2019

72.0

69.4

75.2

72.0

…

77.7

56.7

Bolivia

(Plurinational State of)d

2011

29.7

28.1

31.7

35.0

20.3

45.7

19.4

2013

38.0

37.6

38.4

41.2

32.0

50.5

30.0

2018

35.0

32.7

37.9

37.9

29.7

53.3

25.0

Chilee

2011

72.2

72.5

71.7

74.2

56.8

80.0

45.3

2013

76.4

76.2

76.7

78.4

61.1

83.9

49.8

2017

82.3

82.1

82.6

83.7

71.8

90.4

57.1

Colombia

2010

88.8

87.1

91.3

89.3

87.1

91.8

86.2

2014

91.9

90.3

94.2

92.0

91.6

94.3

89.7

2018

92.5

91.0

94.7

92.7

91.7

94.2

90.9

Costa Rica

2010

71.7

75.5

65.1

74.1

67.2

79.2

47.7

2014

73.2

76.7

67.5

74.6

68.9

80.2

50.4

2019

74.6

76.3

72.0

75.9

70.7

81.2

52.6

Dominican Republicd

2010

55.7

51.0

63.7

58.8

46.2

76.4

33.3

2014

69.4

64.7

77.2

71.2

62.8

84.2

50.6

2019

77.9

73.0

85.2

78.9

73.3

88.3

63.5

Ecuadord

2010

39.0

37.0

42.2

44.4

28.3

52.6

22.1

2014

45.9

47.3

43.9

48.6

40.6

62.6

23.9

2019

39.8

39.9

39.8

43.9

32.0

58.3

22.7

El Salvador

2010 c

32.7

30.5

35.8

42.7

12.6

49

10.4

2014 c

34.7

33.5

36.3

44.6

15.3

50.5

10.9

2019

34.6

34.3

34.9

43.0

18.7

50.1

10.5

Guatemala

2006

26.7

27.6

25.2

37.2

14.7

44.8

7.5

2014

18.4

18.0

19.1

26.3

8.9

28.0

4.0

Honduras

2010

17.1

15.0

20.7

29.6

6.1

37.9

0.9

2014

20.1

18.2

23.2

30.6

8.1

40.1

1.2

2019

17.5

15.9

20.3

27.5

5.2

34.2

1.6

Mexicoe f

2010

45.6

42.9

50

52.3

19.9

54.5

20.8

2014

46.0

44.0

49.2

53.4

19.4

55.3

19.7

2018

46.8

45.8

48.3

54.5

22.5

56

22

Nicaragua

2005

20.4

17.5

25.4

29.7

7.2

37.1

3.2

2014

23.0

20.7

26.8

32.2

9.1

41.1

1.7

Paraguay

2010

25.9

23.1

30.6

36.8

9.7

38.6

11.9

2014

31.9

29.3

35.8

39.7

19.3

44.3

15.8

2019

31.8

30.2

34.1

40.2

17.3

45.4

14.1

Peru

2010

58.1

54.8

62.0

54.4

68.0

63.3

53.8

2014

66.3

63.1

70.2

63.5

74.4

71.6

61.7

2019

74.6

71.3

78.3

71.7

84.2

77.7

71.8

Uruguaye

2010

97.1

96.2

98.2

97.1

97.4

98.4

93.8

2014

98.3

97.6

99.2

98.3

98.1

99.2

95.9

2019

98.8

98.3

99.4

98.8

99.0

99.5

97.1

Latin Americag

2010

56.6

54.0

60.4

68.3

39.8

64.5

43.6

2014

59.8

57.6

63.0

63.4

43.3

67.1

47.2

2019

60.5

58.7

63.0

64.8

43.1

67.7

48.6

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

a Unless otherwise specified, the data refer to contributions to the health system.

b There are no data after 2014 for Guatemala and Nicaragua, so these countries are not included in the 2019 round. The Bolivarian Republic of Venezuela and Brazil do not report data for this indicator, and in Panama it is not possible to distinguish this coverage specifically, so they are not included in the table.

c Includes employers, own-account workers, unpaid family workers and workers in cooperatives.

d The data refer to health system affiliation.

e In Chile, category A of the National Health Fund is not considered. In Mexico, Seguro Popular coverage is not included. In Uruguay, persons affiliated with municipal polyclinics are excluded.

f The data for Mexico for 2018 are not strictly comparable with those of previous years owing to changes in the wording of some of the questions on social security access. For more details of these changes, their effects on the estimation of social security coverage (health and pensions) and procedures to adjust said estimation, see National Council for the Evaluation of Social Development Policy (CONEVAL), “Ejercicio de adecuación histórica de la carencia por acceso a la seguridad social 2016 a la serie 2010-2014”, Mexico City, 2017 [online] https://www.coneval.org.mx/Medicion/MP/Documents/Pobreza_16/Notas_Pobreza_2016/Nota_tecnica_2_ajuste_seguridad_social.pdf.

g The total average and the averages by gender refer to 13 countries with data available for the three rounds: Argentina, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Mexico, Paraguay, Peru, Plurinational State of Bolivia and Uruguay. The averages for urban and rural areas exclude Argentina, and therefore refer to 12 countries.

Table III.A1.3

Latin America and the Caribbean (32 countries): emergency social protection measures for the population living in poverty and vulnerability, by type of measure, as of 6 November 2020

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official data from the countries; Economic Commission for Latin America and the Caribbean (ECLAC), COVID-19 Observatory in Latin America and the Caribbean [online database] https://www.cepal.org/en/topics/covid-19; “Social protection measures to confront COVID-19”, Social Development and COVID-19 in Latin America and the Caribbean [online database] https://dds.cepal.org/observatorio/socialcovid19/en/listamedidas.php.

[1] The main international instruments include the Universal Declaration of Human Rights (United Nations, 1948), the Social Security (Minimum Standards) Convention, 1952 (No. 102) of the International Labour Organization (ILO) and the International Covenant on Economic, Social and Cultural Rights (United Nations, 1966). The Regional Agenda for Inclusive Social Development, approved in 2019 within the framework of the Regional Conference on Social Development in Latin America and the Caribbean, also calls for the construction of universal and comprehensive social protection systems (ECLAC, 2020a).

[2] Contributory social protection (or social security) refers to the receipt of benefits that depend on prior contributions deducted from wages (social security contributions) and participation in the formal labour market. Although non-contributory social protection (or social assistance) does not depend on such contributions, it should be recognized that the recipients of this type of benefit contribute to society and the economy in various ways, for example, through their unpaid work or by paying indirect taxes, such as value added tax (VAT). It should also be noted that contributory benefits are financed partly by government transfers from general revenues (Abramo, Cecchini and Morales, 2019), along with employer contributions.

[3] According to ILO estimates, in 2016, only 61.4% of the population in 17 countries in Latin America and the Caribbean were covered by at least one social protection benefit. See United Nations (2021).

[4] The administrative records of 17 Latin American countries show that effective pension coverage (total contributors expressed as a percentage of the labour force) increased from 34.8% to 45.3% between 2000 and 2017, albeit dropping from 48.2% to 45.3% between 2014 and 2017. The same trend can be seen in occupational coverage (contributors as a percentage of the employed population), which increased from 43.6% in 2000 to 54.2% in 2014, before slipping to 51.9% in 2017 (Arenas de Mesa, 2019).

[5] The non-wage-earning category includes employers, self-employed workers, unpaid family workers and workers in cooperatives.

[6] Although no gender inequalities are discernible in the regional aggregate, affiliation or contribution rates among individuals in the first income quintile in 2019 were 11.4% for women compared to 16.6% for men.

[7] These regimes include the individual microentrepreneur taxation system in Brazil, the “Monotributo” Single Social Tax of the Ministry of Social Development (MIDES) in Uruguay and the Ecuadorian Simplified Tax Regime (RISE) (Abramo, Cecchini and Morales, 2019).

[8] Between 2000 and 2017, contributory explained 6.8 of the 24.7 percentage-point increase in pension coverage among persons aged 65 or older, while non-contributory coverage explained the remaining 17.9 percentage points (Arenas de Mesa, 2019). In terms of amounts, around 2015, non-contributory pensions accounted for less than a quarter of the amount of contributory pensions in the Plurinational State of Bolivia, Ecuador, Mexico, Panama, Paraguay and Peru, and were less than 40% in Chile and Costa Rica (ECLAC, 2018b).

[9] Around 2015, the gap between the amounts of contributory or non-contributory benefits received by women and men reached 44% in Paraguay, 42% in Mexico and 37% in Ecuador (ECLAC, 2018b).

[10] Between 2014 and 2017, in 15 Latin American countries, the amounts of non-contributory transfers represented between 13% (Plurinational State of Bolivia) and 91% (Uruguay) of the income deficit of the population in poverty (Cecchini, Villatoro and Mancero, 2021).

[11] This section describes the non-contributory social protection measures and other direct assistance for individuals and households in situations of poverty and vulnerability, as announced by national governments between 1 March and 6 November 2020. It does not include measures by subnational governments, or measures targeting enterprises or other legal entities, which have an indirect effect on households and individuals.

[12] For example, transfer of the third instalment of Argentina’s Emergency Family Income (IFE), which was initially planned as a one-off payment, was completed on 31 August 2020. The duration of Jamaica’s Supporting Employees with Transfer of Cash (SET Cash) programme was extended from three to five months. Brazil’s Federal Government Emergency Aid programme and Saint Vincent and the Grenadines’ Interim Assistance Benefits for Vulnerable Vincentians will be in place for nine months. Colombia’s Solidarity Income programme, which was initially to last for three months (from March to May), was first extended until December 2020 and then, in July, for a total duration of 15 months (to June 2021).

[13] Initially, for example, Chile’s Emergency Family Income programme covered the most vulnerable 60% of the population. Subsequently, through Law No. 21.251 of 3 August 2020, the vulnerability requirement was eliminated and only inclusion in the country’s social register of households is now required. Thus, the first instalment reached 1.2 million households, while the fourth reached some 3 million households.

[14] Some of the new assistance targeted specific population groups. For example, in Peru, a grant for furloughed workers was announced, and in Uruguay, a grant for artists was approved.

[15] Forty-six non-contributory measures were also identified in 14 non-independent territories in the Caribbean.

[16] In Uruguay, for example, by 6 November 2020, the amounts of family allowances under the Equity Plan and the Uruguay Social Card (TUS) had been doubled three times, while in Saint Lucia the Child Disability Grant had been increased.

[17] In Mexico, for example, a payment equivalent to four months of the Pension Programme for the Well Being of Older Persons was made ahead of schedule. The first advance was in March (to cover payments for the two-month periods of March-April and May-June) and the second was in July (to cover payments for the two-month periods of July-August and September-October). In November, the regular payment for the two-month period November-December was rolled out.

[18] For example, Brazil announced an increase of 1.2 million users of the Bolsa Família programme, Belize announced increased coverage of the Building Opportunities for Our Social Transformation (BOOST) programme and Saint Lucia announced expansion of its Public Assistance Programme.

[19] In Mexico, the pension for older persons is recognized as a right in article 4 of the country’s constitution.

[20] For example, Argentina uses the database of the National Social Security Administration (ANSES), Brazil uses its Unified Register for Social Programmes of the Government of Brazil (Cadastro Único), Chile uses its Social Register of Households (RSH) and the Dominican Republic uses its Unified Beneficiaries System (SIUBEN).

[21] Examples include Belize’s Unemployment Relief Program, Costa Rica’s Bono Proteger programme and components of Jamaica’s COVID-19 Allocation of Resources for Employees (CARE) programme.

[22] For example, households that are eligible for the Bono Familia (Family Allowance) in Guatemala were identified by electricity consumption, whereby the National Electricity Commission (CNEE) and the Ministry of Energy and Mines provided a list of households whose electricity bills for February 2020 showed consumption of less than 200 kWh. This information is cross-checked with the administrative records of the National Institute of Statistics and the National Registry Office (RENAP), among other documents.

[23] In Chile, El Salvador, Jamaica and Saint Lucia, transfers have included hygiene products and contraceptives.

[24] For example, in Trinidad and Tobago, food cards were distributed, for children from vulnerable households, with a monthly value of around US$ 76.

[25] The COVID-19 Emergency Food Assistance Programme (Grace Relief) in Antigua and Barbuda, the Ayudar Nos Hace Bien network in Colombia, the “Dar una mano sin dar la mano” initiative in Ecuador, the food baskets (Health Emergency Programme) in El Salvador, the Social Relief Hampers in Guyana and the “Panamá Solidario: Por Nuestra Niñez” programme in Panama all receive private donations from companies, organizations and individuals. In addition, for some initiatives, such as the Honduras Solidaria programme, the armed forces and a network of volunteers are providing support by delivering the food.

[26] In Argentina, the ban on disconnecting services focused on retirees, patients who are dependent on electrical equipment, and recipients of the Universal Child Allowance (AUH) and the Universal Pregnancy Allowance for Social Protection (AUE).

[27] For more information on access to basic services during the pandemic, see Filgueira and others (2020).

[28] In the case of Argentina, these are changes to programmes that existed before the pandemic, namely: increasing the population coverage of the Food Card (Tarjeta alimentar), increasing the amount of the reinforcement for beneficiaries of social plans and the Family Support Allowance, and providing a grant for recipients of the Universal Child Allowance (AUH) and Universal Pregnancy Allowance for Social Protection (AUE).

Chapter IV

Recent social spending trends and commitments in terms of emergency social protection

Introduction

A. Trend of public social spending in 2000–2019

B. Estimates of emergency social protection spending in response to the pandemic

C. Costs and impacts of universal and targeted cash transfers

D. Concluding remarks

Bibliography

Annex IV.A1

Annex IV.A2

Annex IV.A3

Introduction

The COVID-19 pandemic has directly affected decision-making, on public expenditure generally and on social spending in particular. An analysis of these decisions requires a brief review of the context in which this crisis has been unfolding in the region, and of previous trends and current decisions on public funding for social policies.

As noted in COVID-19 Special Report, No. 2 (ECLAC, 2020a), Latin America and the Caribbean entered 2020 following a decade of lacklustre economic growth, compounded by stagnant public revenues that are insufficient to finance the rising level of public expenditure. All this has led to persistent global and primary deficits, growing public debt and a weak position from which to confront the current crisis in the region, notwithstanding significant differences in fiscal space from one country to another (ECLAC, 2020a and 2020b).

In keeping with the above, total government income in Latin America averaged 18.2% of GDP in the last decade and displayed lethargic growth. Tax revenues rose from 14.5% of GDP in 2010 to 15.3% in 2019. Nine countries saw increases of over 1 percentage point of GDP, and in five cases 2 percentage points or more (ECLAC, 2020b).

The Caribbean countries have also endured a complex macroeconomic situation in recent years, impacted by disasters and the use of non-recurrent external grants, along with other exceptional income. Between 2010 and 2019, however, total income rose on average from 25.9% to above 27% of GDP in the last biennium (ECLAC, 2020b).

In 2019, the gross public debt of central governments in Latin America increased, as it had done in previous years, to reach 45.2% of GDP, 3.3 percentage points higher than in the previous year. In the Caribbean subregion in contrast, the debt continued to trend down, dropping by 2.6 percentage points of GDP in the last year; but, at 68.5% of GDP, it remained significantly higher than in Latin America (ECLAC, 2020b).[1]

The cost of tax evasion and avoidance in Latin America has been estimated at US$ 325 billion in 2018, equivalent to 6.1% of GDP (ECLAC, 2020b). This situation exacerbates the challenges facing the region’s countries in keeping public social spending at levels that enable them to achieve their social-policy objectives and fulfil the commitments made in the 2030 Agenda for Sustainable Development.

Public expenditure expanded across the region between 2010 and 2019, rising from 20.1% to 21.2% of GDP in Latin America and from 27.5% to 28.7% of GDP in the Caribbean (ECLAC, 2020b).

In 2020, public spending has played a crucial role in supporting the response to the crisis, by buttressing health systems financially and channelling funds to families and businesses. In January–August 2020 and relative to the year-earlier period, primary spending (which excludes interest payments) grew significantly. Real year-on-year increases were above 10% in several countries and more than 20% in some cases (ECLAC, 2020f). Thus, it has been estimated that public spending could average 25.9% of GDP in the Latin American countries in 2020, which would be the highest level since 1950. At the same time, revenues are forecast to drop to 16.9% of GDP, their lowest level since 2004, resulting in a deficit of 9.0% of GDP (ECLAC, 2020d). The magnitude of the impacts generated by the pandemic will become clearer when fiscal statistics for the next few years are analysed. However, a preliminary estimate can be made by reviewing and quantifying the commitments entered into by the region’s countries in 2020.

This chapter analyses the volume and distribution of public resources used to finance social policies in Latin America and in five English-speaking Caribbean countries. The first section describes the trend of public social spending up to 2019, at both the regional and subregional levels, according to the Classification of the Functions of Government (COFOG). Section B estimates the resources committed by the countries in terms of non-contributory social protection to address the pandemic in 2020. Section C analyses the projected costs and impacts of various cash-transfer alternatives, whether universal or targeted to specific population groups.

A. Trend of public social spending in 2000–2019

The 2019 statistics on central government funding for social policies in the region show that the trend of the last two decades is being maintained. As a percentage of GDP, the average for Latin America has been growing relatively steadily, rising by a cumulative 36% since 2000 despite a relative stabilization in recent years. The five English-speaking Caribbean countries studied in this chapter have reported five years of stability. Nonetheless, heterogeneity remains a characteristic of the region, with eight countries allocating less than 10% of their GDP to central-government social spending, while three exceeded 17% in 2019. Absolute amounts per capita vary between less than US$ 200 and more than US$ 2,500 per year. The amounts in question are higher in the countries that report spending on institutional coverage that is higher than the coverage of the central government. Nonetheless, the challenge remains to expand the availability of these data to enhance comparability across the region.

This section presents information on social spending in the region’s countries by government function, as defined in Government Finance Statistics Manual 2001 and Government Finance Statistics Manual 2014, published by the International Monetary Fund (IMF) (IMF, 2001 and 2014). The analysis is based on a comparison of the most recent central government data spanning 2000 to 2019. In specific cases where information is available, the analysis is complemented with broader institutional coverage. Data from five English-speaking Caribbean countries are also included, along with information from the 20 Latin American ones. Thus, the series encompasses the countries considered in Social Panorama of Latin America, 2019, but with data brought up to date on the basis of official reports (see box IV.1).

Box IV.1

Statistics on public social spending

The data used to analyse public social spending in the region correspond to official information on public expenditure provided by each of the region’s countries, compiled annually by the Economic Commission for Latin America and the Caribbean (ECLAC) and available for review in CEPALSTAT and in the ECLAC database on social investment in Latin America and the Caribbean.

The following table displays the available data series for each of the countries, by level of institutional coverage. Each country’s public sector is analysed by subsector or institutional coverage: (i) central government, which encompasses ministries, secretariats and public institutions that have jurisdiction over the entire national territory (regardless of whether some departments have their own legal authority and autonomy); (ii) general government, which spans central government and subnational governments (first territorial subdivision and local governments) together with social security institutions; (iii) non-financial public sector, which comprises general government and non-financial public corporations; and (iv) public sector, which consists of the non-financial public sector plus financial public corporations. Cross-country analysis is appropriate at the central government level. However, this is more difficult for the entire public sector because the institutional coverage varies between countries, so the data are not comparable. This is particularly relevant in the case of federal countries or those with high degrees of autonomy in revenue collection and management by intermediate-level governments, where a large proportion of social spending is the responsibility of subnational authorities.

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 coverage

General government

Non-financial public sector

Public sector

Latin America

Argentina

1993–2019

1990–2017

Bolivia (Plurinational State of)

1990–2018a

1997–2008, 2010–2016

Brazil

1995–2019

2000–2019

Chile

1990–2019

Colombia

1990–2019

2009–2018

Costa Rica

1993–2019

1990–2019

Cuba

2002–2018

1996–2018

Dominican Republic

1990–2019

Ecuador

2000–2019

El Salvador

1990–2019

2002–2019

Guatemala

1995–2019

Haiti

2012–2014

Honduras

2000–2019

Mexico

1999–2019

Nicaragua

1990–1994, 1998–2019

Panama

2000–2017

Paraguay

2000–2018

2003–2018

Peru

1999–2019

Uruguay

1990–2019

Venezuela (Bolivarian Republic of)

1997–2014

Caribbean countries

Bahamas

1990–2019

Barbados

2006–2019

Guyana

2004–2019

Jamaica

1992–2019

Trinidad and Tobago

2008–2019

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of CEPALSTAT [online] http://estadisticas.cepal.org; Database of Social Investment in Latin America and the Caribbean [online] https://observatoriosocial.cepal.org/inversion/es; Social Panorama of Latin America, 2016 (LC/PUB.2017/12-P), Santiago, 2017; International Monetary Fund (IMF), Government Finance Statistics Manual 2014, Washington, D.C., 2014.

a Central administration.

1. Growth of central-government social spending in the region

In 2018, central government social spending in 17 Latin American countries represented 11.3% of GDP (simple average),[2] slightly less than in the previous year (see figure IV.1). The available data show that public social spending rose slightly in 2019 to post its highest level in the current century at 11.5% of GDP). In recent years, the share of total central government expenditure absorbed by the social functions has stabilized between 52% and 53%. Compared to the levels prevailing in the early years of the 2000 decade, the average share and volume of public social spending relative to GDP reflects the increasing importance that countries have attached to social functions over the last decade. These accounted for 72% of the increase in total central government spending in 2009–2019.

Figure IV.1

Latin America (17 countries): central-government social spending, 2000–2019a

(Percentages of GDP and of total public expenditure)

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

a The figures shown correspond to the arithmetic mean of 17 Latin American countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the 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 2019 data for the Plurinational State of Bolivia refer to 2018; the 2018 and 2019 data for Panama relate to 2017.

Among the five English-speaking Caribbean countries analysed (Bahamas, Barbados, Guyana, Jamaica, and Trinidad and Tobago), average central government social spending peaked in 2017 at 12.3% of GDP, before slipping by 0.4 percentage points to 11.9% of GDP in the most recent biennium (see figure IV.2). Thus, on average, the volume of public social spending in recent years remains at levels similar to those prevailing at the end of the previous decade.

Figure IV.2

The Caribbean (5 countries): central-government social spending, 2008–2019a

(Percentages of GDP and of total public expenditure)

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

a The figures shown correspond to the arithmetic mean of five Caribbean countries: Bahamas, Barbados, Guyana, Jamaica, and Trinidad and Tobago.

This stabilization relative to GDP in the five Caribbean countries analysed is combined with an increase in the weight of social functions in total central government social spending, and a fall in the level of public expenditure on non-social functions.

In these five Caribbean countries, the share of funding allocated to social policy relative to total government functions is significantly lower than the average for Latin American countries in 2019 (a difference of 9.3 percentage points). Nonetheless, public social spending is almost 0.4 percentage points of GDP higher than in the Latin American countries, and average total public spending is 5.5 points higher. These differences are smaller than they were in 2018.

An analysis of the relative shares of central government social spending in 2019 in the different countries and subregions of Latin America (see figure IV.3) reveals average values that are slightly higher than in 2018 in all cases. The average for the nine South American countries considered is 13.5% of GDP. This reiterates what has been reported in previous editions of Social Panorama, namely that this is the subregion with the highest level of spending, notwithstanding great heterogeneity. While Ecuador and Paraguay maintain levels of public social spending around 10% of GDP, the equivalent figures for Brazil, Chile and Uruguay are above 17%.

Figure IV.3

Latin America and the Caribbean (22 countries): central-government social spending, by country and subregion, 2019a b

(Percentages of GDP)

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

a Data for the Plurinational State of Bolivia refer to 2018, and those for Panama correspond to 2017. Coverage in the Plurinational State of Bolivia corresponds to central administration and that of Peru to general government. Data for Uruguay do not include those of the Social Security Bank.

b The 2018 levels of public social spending are shown for comparison purposes.

In the group formed by the six Central American countries plus the Dominican Republic and Mexico, central government social spending averages 9.3% of GDP. Among these countries, Costa Rica’s social spending is the highest in relative terms (12.4% of GDP), followed by Nicaragua and El Salvador (11.1% and 9.8% of GDP, respectively), while the Dominican Republic, Guatemala and Honduras are the Latin American countries with the lowest social spending, at under 8.0% of GDP.

In terms of per capita GDP in Latin America, the proportion of resources allocated to finance social policies remains smaller in the less wealthy countries and those suffering from higher levels of poverty and vulnerability, as well as greater shortcomings in various areas of social development. This situation exacerbates the vulnerability to which their populations are exposed (ECLAC, 2019a and 2019b).

For the five Caribbean countries studied, the most recent data show that central government social expenditure in 2019 averaged 12.2% of GDP, ranging from 7.6% in the Bahamas to 14.3% in Barbados.[3]

As shown in figure IV.3, although variations in terms of percentage points of GDP are generally small, the 2019 figures are higher than those of 2018 for most countries. The largest increases are reported in Ecuador and Guyana (+1 percentage point or more), followed by Chile (+0.7 points) and Mexico (+0.6 points). In contrast, six countries report a decrease: Barbados (-1.5 percentage points), Argentina (-0.6 points), Nicaragua (-0.4 points) and Trinidad and Tobago (-0.2 points), along with Colombia and Honduras (-0.1 points).

A comparison of the values presented here with the 2018 figures shows Ecuador with an increase of 1.42 GDP points, representing growth of 15.7% in a single year.[4] Next come Guyana, Mexico, Paraguay and the Bahamas, with relative increases of between 8.1% and 5.5%; while Chile, Guatemala and Peru are also among countries with growth of around 4% over the same period. In contrast, countries in which central government social spending decreased between 2018 and 2019 include Barbados (-9.7%), Argentina (-4.3%) and Nicaragua (-3.3%).

2. Increase in social spending per person

In terms of per capita amounts, in 2019 the countries of Latin America, on average, resumed the upward trend that had begun in the early years of the 2000 decade (see figure IV.4). The regional average growth rate has been 4.6% per year since 2003, with the countries of South America growing at average rates of 4.9% per year, while in the group comprising Central America, the Dominican Republic and Mexico, the rate was 4.2% per year. Thus, average expenditure per person in Latin America was US$ 956 in 2019, albeit with large variations between different subregions and countries. While the average for South America stood at US$ 1,274 per capita, the average for the group formed by the countries of Central America, the Dominican Republic and Mexico was just US$ 597.

In the case of the five English-speaking Caribbean countries included in the analysis, central government social spending averaged US$ 1,498 per capita, which is equivalent to the average for the last 11 years. The period since 2008 has been marked by high levels of volatility and a 6.4% drop in the last two years. Nevertheless, the average amount per person in these countries is still 57% higher than in Latin American ones.

Figure IV.4

Latin America and the Caribbean (22 countries): per capita central-government social spending, by subregion, 2000–2019a

(Dollars at constant 2010 prices)

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

a The Latin American figures 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, the Plurinational State of Bolivia and Uruguay) and eight from Central America (Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua and Panama), the Dominican Republic and Mexico. The Caribbean includes five countries (Bahamas, Barbados, Guyana, Jamaica and Trinidad and Tobago).

An analysis by country reveals that in the last two years Chile and Uruguay were the countries that spent the most, per capita, on social policies (US$ 2,584 and US$ 2,578, respectively), followed by Barbados (US$ 2,300), the Bahamas (US$ 2,068) and Trinidad and Tobago (US$ 2,034). A second group consists of Brazil (US$ 1,958), Argentina (US$ 1,278) and Costa Rica (US$ 1,245). These are followed by Panama, Colombia and Mexico, with per capita amounts between US$ 1,000 and US$ 955, and then Peru, the Dominican Republic, Guyana, Ecuador, Jamaica and Paraguay, between US$ 748 and US$ 501, respectively. The other Latin American countries, El Salvador, the Plurinational State of Bolivia, Guatemala, Nicaragua and Honduras, in that order, spend between US$ 351 and US$ 175 per person (see Annex IV.A1).

The data analysed here show that two characteristics that had been highlighted in previous editions of Social Panorama of Latin America persist in the Latin American countries. First, 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, are those with the lowest levels of social spending, both in absolute terms and as a proportion of their GDP. Secondly, the availability of resources for social spending in the region’s countries remains far less than in those of the Organization for Economic Cooperation and Development (OECD) and the European Union.[5]

3. Social spending by government function

The distribution of central government spending across the different social functions in 2019 is similar to that of previous years (ECLAC, 2019b). The functions with the most resources allocated in that year in Latin America were social protection, education and health, with average funding equivalent to 4.3%, 4.0% and 2.3% of GDP, respectively (see figure IV.5). Between 2000 and 2019, expenditure on these functions also grew the most in terms of percentage points of GDP: social protection increased by 1.1 percentage points of GDP; education by 0.9 points, and health by 0.8 points. The latter figure represents a relative increase of 52% over the period.

Figure IV.5

Latin America and the Caribbean (22 countries): central-government social spending, by function, 2000–2019a

(Percentages of GDP)

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

a The figures shown for Latin America (subgraph A.) represent the arithmetic mean of 17 countries, which are divided into two groups (subgraphs B and C): nine from South America (Argentina, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay) and eight from the group comprising Central America (Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua and Panama) plus the Dominican Republic and Mexico. In the case of the Caribbean (subgraph D), the following five countries are included (Bahamas, Barbados, Guyana, Jamaica and Trinidad and Tobago).

An analysis by country groupings shows that the large share of the social-protection function is influenced by the situation in the nine South American countries analysed, which in 2019 spent an average of 6.3% of GDP on this function. In contrast, in the grouping comprising Central America, the Dominican Republic and Mexico, the resources allocated to this function represent a third of the amount recorded in South American countries. In the last year, the latter allocated the equivalent of 2.1% of GDP to social protection (more than in the previous year). Thus, the previous years’ levels were recovered to some extent, although remaining below their 2013 peak.[6]

Average levels of spending on social protection in 2019 recovered relative to the previous year’s levels, by 0.24 points of GDP in South American countries and by 0.14 points in the group formed by the Central American countries along with the Dominican Republic and Mexico. However, these amounts are still unlikely to be sufficient to provide financial sustainability to poverty eradication policies, contain the vulnerability of labour incomes and provide access to services consistent with levels of well-being that guarantee rights. This situation has become clear in 2020, in the midst of the social crisis caused by the COVID-19 pandemic, as analysed in section B of this chapter.

In the case of education, average central government spending in 2019 in the subregion formed by the Central American countries, plus the Dominican Republic and Mexico, makes it the most funded function at 4.2% of GDP, almost half a percentage point higher than the South American countries’ average of 3.8%.

The health function, meanwhile, ranks third in terms of allocation of central government funds in both subregions. The average among the countries of South America was 2.7% of GDP in 2019, that is 0.9 percentage points more than among the countries of Central America, plus the Dominican Republic and Mexico (1.8% of GDP).

In the case of housing and community amenities, expenditure was down slightly in the Central America-Dominican Republic-Mexico grouping (-0.1 percentage points of GDP). On average, this group allocated twice as much central government funding as the South American countries (0.8% and 0.4% of GDP, respectively).

An analysis of data for the five English-speaking Caribbean countries in 2019 shows a functional distribution similar to the average for Central America, the Dominican Republic and Mexico. Thus, the education function received the most funding (4.4% of GDP), with a stable level being maintained since 2011. This is followed by spending on the health function, which reached a level of 3.2% of GDP in 2019, half a percentage point more than among the South American countries. Meanwhile, social protection spending edged up in 2017 and increased slightly in 2019, to 2.8% of GDP. The housing and community amenities function, meanwhile, dropped slightly lower than in the previous three years analysed, to 0.9% of GDP its lowest level since 2012.

Complementing the above, a study of the proportional distribution of central government social among the individual functions portrays each country’s priorities and commitments, as expressed in the allocation of public funds. As noted in previous editions of Social Panorama of Latin America (ECLAC, 2018 and 2019b), and as reflected in the regional and subregional averages, in most countries the largest proportions of social spending disbursed in 2019 went to the social protection, education and health functions, albeit with significant differences in the distribution between them (see figure IV.6 and annex IV.A1).

As noted above, the analysis presented here focuses on central government coverage; but the amounts in question can change significantly if broader coverage is considered, such as general government or the non-financial public sector. This is particularly relevant in the case of countries that have a federative structure or subnational governments with high degrees of autonomy, such as Argentina, Brazil, Colombia and Mexico. It is also significant in countries where at least part, if not all, of the social security resources are managed independently, as in Costa Rica, Ecuador and Uruguay, among others. Only a few countries have broader-coverage data on public social spending (see box IV.1), as discussed further in the next section.

The following paragraphs make a brief description of the situation of central-government social spending on each function, in the Latin American and Caribbean countries for which information is available.[7]

Figure IV.6

Latin America and the Caribbean (23 countries): distribution of central-government social spending, by function, 2019a

(Percentages)

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

a Data for Cuba and the Plurinational State of Bolivia refer to 2018, while those for Panama correspond to 2017. Coverage in the Plurinational State of Bolivia corresponds to central administration and in Peru, to general government.

(a) Social protection

Resources allocated to social protection policies include disbursements in respect of services and transfers to individuals and families, for sickness and disability, old age, surviving dependents, family and children, unemployment, housing and social exclusion, in both the contributory and the non-contributory social protection sectors.8 9 This function includes policies and programmes aimed at covering the risks of income loss or increased expenses that may affect part or all of the population (related to disease, old age, care, disasters, economic and social crises[10] and unemployment), as well as those aimed at facilitating inclusion and protecting against the consequences of poverty and inequality (such as cash or in-kind transfer programmes and social pensions).

In 2019, the central governments of Latin American and Caribbean countries allocated funding for social-protection policies equivalent on average to 4.1% of GDP. Thus, both the average and the distribution between countries that provide more and those that provide less funding for social protection policies are similar to those of previous years. The countries that spent the most on this function are Brazil, Argentina and Uruguay (12.9%, 10.8% and 7.9% of GDP, respectively), while Honduras, Jamaica and Nicaragua spent the least (less than 1% of GDP).[11]

In several countries, when data from social security institutes are included, the levels of social protection expenditure may be higher than indicated above. This reflects different institutional models and modes of resource administration, some with management and accounting autonomy, others with private-sector administration. An example is Uruguay where, when consolidating central government data with data on contributory pensions managed by the Social Security Bank (BPS), the level of social protection spending rises significantly to 13.3% of GDP, according to 2016 data (ECLAC, 2019b).

Comparative analysis shows that Argentina and Brazil are the countries that allocate the largest proportion of total central-government social spending to social protection; and the analysis of extended coverage, presented below, confirms that both countries prioritize this function in their distribution of expenditure. This situation is heavily influenced by spending associated with old age, which accounts for over half of all social protection spending. The third country that prioritizes this function in its central government social spending is Cuba, with 67%,[12] followed by Colombia, Mexico, Paraguay and Uruguay, with proportions of 40% or more. Other countries that allocate a large share of their total social spending to social protection are Trinidad and Tobago, El Salvador, Chile and Costa Rica, with shares of between 35% and 39%. Meanwhile, Jamaica, Honduras and Nicaragua are the countries that allocate the smallest share of their social spending to this function (7% or less).

(b) Education

The education function encompasses all expenditures made to finance education policies at the different levels of schooling, from preschool to tertiary. It also includes ancillary services and research and development. As noted above, among Latin American countries this social function absorbs the second largest share of central government resources. Costa Rica is the country that spends relatively the most on education (7% of GDP), while the Plurinational State of Bolivia, Guyana, Chile, Barbados, Jamaica, Uruguay, Honduras, Nicaragua and Ecuador all spend between 5.7% and 4.5% of their GDP on this function.

Although the amount of funding allocated to education in each of the region’s countries does not necessarily meet needs, in several cases education spending is in line with the recommendation contained in Education 2030 Framework for Action, namely allocating at least 4% to 6% of gross domestic product (GDP) or 15% to 20% of public spending (UNESCO, 2015). Thus, the regional trend noted in previous editions of Social Panorama continues, in the sense that education absorbs the largest share of central government social spending in most of the countries analysed (14 out of 23 countries) (ECLAC, 2019b).

The country that spends the most on education is Honduras, which assigns nearly two-thirds (63%) of central-government social spending to this function, followed by Costa Rica (56%) and the Dominican Republic (53%). Next come Jamaica, the Plurinational State of Bolivia and Ecuador with proportions between 49% and 43%.

Although Brazil and Argentina are the countries with the smallest proportion of central-government social spending going to education, the analysis of expanded coverage, which is discussed below, shows that both countries report a larger volume of resources allocated to this function —5.2% and 5.7% of GDP, respectively.[13]

(c) Health

The health function includes disbursements made to finance services provided to individuals and groups at different levels of care, in both preventive and curative programmes. To this end, target 4.1 of the Sustainable Health Agenda for the Americas 2018–2030 states that, in order to advance towards universal health, a necessary condition is to “achieve a level of public expenditure on health of at least 6% of GDP” (PAHO/WHO, 2017, p. 35).[14] This figure contrasts with the average of 2.4% of GDP achieved by central government funding in the 23 countries analysed, and it evidences the wide gap that remains to be bridged. The COVID-19 pandemic has also posed new health-policy challenges that imply additional funding needs, both for the present and for the years to come.

None of the region’s countries attains the proposed central government public expenditure target. Relative to GDP, Chile spends the most on health (5.1%), followed by Guyana, Uruguay, Jamaica, Nicaragua, Colombia and Barbados (between 4.1% and 3%). However, in the analysis of broader institutional coverage, Argentina (7% of GDP)[15] and Costa Rica (also 7%) exceed the 6% of GDP target for public social spending on this function.

In terms of social functions as a whole, the Bahamas allocates the largest proportion of central-government social spending to health (35%), while four other countries (Jamaica, Nicaragua, Chile and Guyana) spend between 30% and 34% on this function. At the opposite extreme, the countries whose central governments spend the least on health policies out of their overall social spending are Argentina and Costa Rica, both with 6%, followed by Cuba (8%) and Mexico and Brazil (both with less than 13%).

It is worth recalling the weight of spending on social protection in some of these countries and how this interacts with the health function. As noted in the 2018 and 2019 editions of Social Panorama, in many cases the institutions associated with contributory social protection co-participate in the provision and insurance of some health services, so more disaggregated data would be required for a deeper analysis. This is compounded by the effect of resource management at the subnational level, particularly in countries with autonomous state and subnational governments. For example, all countries for which broader-coverage data are available spend heavily on this function. In addition to the countries mentioned above, Brazil, Colombia and the Plurinational State of Bolivia are very close to attaining the 6% target proposed in Sustainable Health Agenda for the Americas 2018–2030, reporting expenditures of 5.5%, 5.2% and 5.1% of GDP, respectively.

(d) Housing and community amenities

Public spending on housing and community amenities includes State funding for urbanization (including both the administration of urbanization matters and slum clearance related to residential development, construction and remodelling of homes, as well as the acquisition of land for housebuilding), community development, water supply and street lighting.

As reported last year, the most recent data again show that the countries of the region spent an average of 0.7% of GDP on this function, led by Trinidad and Tobago (1.8% of GDP) and Panama (1.7%), followed by Guatemala and Nicaragua (1.5% each).

Panama allocates the largest share of central-government social spending to this function (20%), followed by Guatemala (19%). In contrast, housing and community amenities account for less than 5% of total central government social spending in 14 of the 23 countries analysed.

(e) Recreation, culture and religion

Funding for recreation, culture and religion encompasses entertainment (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, the ministers and senior authorities of cultural affairs proposed progressively allocating a minimum of 1% of each State’s general budget to the promotion of culture (ECLAC/OEI, 2014, p. 311). However, this goal has yet to be met: in 2019, the region’s countries spent an average of just 0.18% of their GDP on recreation, culture and religion, making it the least funded of all social functions.

Cuba and Peru, with spending equivalent to 0.5% of GDP, along with Barbados (0.4%), are the countries that spend most on this function (2.3%, 2.2% and 1.7% of total central government expenditure, respectively), thus exceeding the proposed target. Three other countries assigned 1% or more of total central government spending to this function: the Bahamas and Guatemala (1.3% each), and the Dominican Republic and Panama (both 1%).

Relative to total public social spending, Cuba is again the country that allocates the largest share to recreation, culture and religion (5.3%), along with Peru (4.1%) and the Bahamas (3.5%). They are followed by Guatemala, the Dominican Republic, Guyana and Jamaica, where between 2.3% and 2.0% of their central-government social spending goes on this function. Meanwhile, in four countries (Argentina, Honduras, Paraguay and the Plurinational State of Bolivia) data on central government public expenditure make no mention of funding for recreation, culture and religion.

(f) Environmental protection

As part of the social functions, environmental protection includes spending on waste and wastewater management, pollution abatement, protection of biodiversity and landscapes, and research related to environmental protection.

In 2019, central government spending on this function averaged 0.22% of GDP among the 23 countries considered. Peru is the leader in this area also, spending the equivalent of 1.2% of GDP, followed by the Bahamas (0.8% of GDP), Barbados (0.6%) and Panama (0.4%). In contrast, Guatemala, Guyana, Jamaica, Nicaragua and Paraguay allocated just 0.2% of GDP to this function.

These amounts vary significantly when the institutional coverage is widened to encompass subnational levels of government (given the role they play in waste management) and publicly-owned wastewater treatment companies. Accordingly, to conduct a more detailed analysis, it would be advisable to analyse the data consolidation work contained in the satellite accounts for this area. In addition to providing a fuller picture of the resources allocated, these accounts include the actions carried out by different actors in the context of the countries’ environmental protection policies.[16]

4. Public social spending with broader institutional coverage than central government: selected countries

The foregoing data and comments refer to central government, which is the only level of institutional coverage that is comparable between all countries across the region. However, some countries’ institutional structures locate resource management in subsectors outside central government (IMF, 2014) that have significant impacts on the execution of public social policies. For this reason, this section complements the analysis with information available in seven new country reports with broader institutional coverage: Argentina, Brazil, Colombia, Costa Rica, El Salvador, Paraguay and Peru (see Annex IV.A1).17 18 19

In the seven countries analysed, public social spending as a percentage of GDP increases considerably when the coverage considered extends beyond central government. The most significant change occurs in Argentina, where social spending increases from 14.6% of GDP with central government coverage in 2017 to 30.3% of GDP when all levels of public expenditure are considered, and amounts to US$ 3,190 per person annually. Next come Brazil and Costa Rica, which spend the equivalent of 27% and 24.5% of GDP, respectively. These percentages are close to the average of public spending on social functions by general government in non-Latin American OECD countries, which was 29.7% of GDP in 2018.[20]

When considering broader institutional coverage, the distribution of the countries’ public social spending by function changes significantly compared to that of central government. Data for Argentina in 2017 show that the social protection share of social spending decreases from 80.1% at the central government level to 49.8% across the public sector as a whole, despite continuing to be the function that absorbs the largest volume of resources. In contrast, the other functional shares increase significantly, with health and education representing 6.1% and 10.6% of central government social spending, respectively, but accounting for 21.9% and 18.9% at the overall public-sector level. The share of spending on housing and community amenities in the broader public sector is 5.7 percentage points higher than at the central government level.

The case of Brazil in 2019 is unchanged from the previous year and similar to that of Argentina. Social protection absorbs 59% of general government social spending, compared to 73% in the case of central government. Expenditures on health and education absorb around 19% in both cases, compared to 12% and 13%, respectively, in central government coverage.

In Colombia, 2018 data show that social protection absorbs 44% of social spending at both the central and general government levels. In the other functions, education drops from 26% in the former to 21% in the broader institutional coverage. Conversely, the share of the health function increases from 24% to 26%.

In Costa Rica, an analysis of consolidated public sector expenditure in 2019 shows that the education function gained the second largest share (30%) of overall public-sector social spending, but this was down from its 56% share of central government spending. Social protection also absorbs a smaller share in the broader institutional coverage, dropping from 35% to 32%; but it is the function with the highest share of social spending in the consolidated public sector. The reverse occurs with the health function, which rises from 6% of central-government social spending to 27% in the public sector at large. In the case of housing and community amenities, the share increases from 0.4% to 10% when coverage is expanded.

In El Salvador, housing and community amenities absorbed 3% of GDP in 2019 —the largest regional share. In relation to total social spending, this function accounted for 20% at the overall public-sector level, compared to 0.7% in central-government social spending, ranking it third, ahead of health (17.5%). Social protection accounts for a similar share at both levels of institutional coverage (around 35%). In contrast, education and health have relatively less weight in the overall public sector, dropping from 37% and 24% of central-government social spending, respectively, to 26% and 17.5% at the broader institutional coverage.

Lastly, Paraguay maintains a similar structure at both the central and the general government levels, in line with the previous year’s trend (ECLAC, 2019b). In terms of the proportions of public social spending, the social protection function remains the priority, followed by education and health; but the concentration of resources is slightly different in two functions. Spending by general government on social protection and health is 3 percentage points higher than at the central government level. The opposite occurs with education, which absorbs 6 percentage points less of general government social spending than at the central government level.

B. Estimates of emergency social protection spending in response to the pandemic[21]

In 2020, non-contributory social protection spending in Latin American and Caribbean countries increased in response to the social crisis caused by the COVID-19 pandemic. Of committed resources, 73% were executed between March and August, owing to the urgent need to protect the income and consumption of the affected families. Cash and in-kind transfers head the wide variety of non-contributory measures adopted to protect the income of households hit by the crisis. The effort made by Latin American and Caribbean countries to channel additional resources and make budgetary adjustments to finance these measures is estimated at roughly US$ 86.214 billion during 2020. In simple-average terms, this expenditure is equivalent to US$ 78 per capita and represents 1.25% of 2019 GDP —1.9 times the average share of GDP executed through conditional cash transfer and social pension programmes in 2018. The amounts committed reveal the countries’ capacity to respond to the impact of the crisis.

As discussed in Chapter III, since March 2020, the countries of Latin America and the Caribbean have announced and implemented non-contributory social protection measures targeting the population affected by the economic and social crisis caused by COVID-19. The measures implemented include various emergency mechanisms consisting of cash and in-kind transfers, targeted both on the population at large and on specific target groups. These mechanisms have generated funding needs, both through additional resources and through budgetary adjustments across various government functions.

This section provides estimates of the public-expenditure commitments made by the countries of Latin America and the Caribbean on cash and in-kind transfer measures to address the crisis. The data announced for each measure are considered in terms of coverage and the number or frequency of deliveries, as well as the duration and amounts or equivalent values of the goods delivered.[22] For 144 of the 263 non-contributory cash and in-kind transfer measures that had been announced by 32 countries in the region as of 6 November 2020, there is sufficient information to estimate the amount spent on each measure in 28 countries.[23]

The information supplied by the governments of the region shows that spending commitments associated with non-contributory cash and in-kind transfer measures in the countries of Latin America and the Caribbean are likely to amount to almost US$ 86.214 billion in 2020,[24] while South American countries are forecast to spend close to US$ 76.237 billion. Among the countries of Central America, the Dominican Republic, Haiti and Mexico, expenditure on non-contributory cash and in-kind transfer measures is estimated at around US$ 9.744 billion in 2020.[25] In contrast, the Caribbean countries are expected to have spent US$ 233 million by the end of 2020, with Belize and Jamaica accounting for more than 64%.

Figure IV.7 shows that an average of between 30% and 36% of estimated spending on emergency cash and in-kind transfers is estimated to have been executed between March and May in the countries of Latin America and those of the Caribbean, respectively. In both subregions, 44% of spending was executed between June and August, and between 27% of spending in Latin America and 20% in the Caribbean is expected to be executed between September and December 2020. The grouping comprising Central America, the Dominican Republic, Haiti and Mexico is the only subregion with higher estimated spending during the months of March to May (about 44%), compared to 42% from June to August and around 14% between September and December 2020. This mainly reflects the effort that El Salvador and Honduras made in the initial months of the pandemic, executing more than 60% of their estimated expenditure.

Figure IV.7

Latin America and the Caribbean (28 countries): time distribution of spending on emergency cash and in-kind transfers, March–December 2020a

(Percentage distribution, total in millions of current dollars)b

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries; COVID-19 Observatory in Latin America and the Caribbean [online] https://www.cepal.org/es/temas/covid-19 and Observatory on Social Development in Latin America and the Caribbean, “Social Development and COVID-19 in Latin America and the Caribbean” [online] https://dds.cepal.org/observatorio/socialcovid19/listamedidas.php.

a The 28 countries of Latin America and the Caribbean are divided into two groups: 18 Latin American countries and 10 Caribbean ones (Antigua and Barbuda, Bahamas, Barbados, Belize, Guyana, Jamaica, Saint Kitts and Nevis, Saint Vincent and the Grenadines, Saint Lucia, and Trinidad and Tobago). The Latin American countries are divided into two subgroups: 10 countries from South America (Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay; and eight from the group comprising Central America (Costa Rica, El Salvador, Guatemala, Honduras and Panama), plus the Dominican Republic, Haiti and Mexico.

b The average monthly exchange rate from March to October 2020 published by the International Monetary Fund (IMF) [online] https://data.imf.org/regular.aspx?key=61545862 was used, except in the case of the Bolivarian Republic of Venezuela, where the average daily exchange rate published by the Central Bank of Venezuela [online] http://www.bcv.org.ve/estadisticas/tipo-cambio-de-referencia-smc was used.

Estimated spending on cash and in-kind transfers in response to the COVID-19 crisis averaged US$ 78.3 per capita in Latin America and the Caribbean between March and December 2020. Given the high levels of spending announced mainly by Brazil and Argentina, this figure represents per capita averages of US$ 105.2 in the South American countries and US$ 86.9 in the subregion comprising Central America, Dominican Republic, Haiti and Mexico. The overall average per capita for Latin America is US$ 97.1. In the case of the Caribbean, estimated spending on non-contributory measures in cash and in-kind transfers in response to the COVID-19 crisis averaged US$ 44.6 per capita in 2020 (see figure IV.8).

In view of the estimated coverage of emergency cash and in-kind transfers envisaged in chapter III, the per capita spending committed in transfer-recipient households is close to US$ 270 per year in Latin American and Caribbean countries, averaging US$ 220 in Latin American countries and US$ 100 in Caribbean ones.

Figure IV.8

Latin America and the Caribbean (28 countries): estimated average per capita expenditure on emergency cash and in-kind transfers, March–December 2020a

(Dollars at current prices)b

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries; COVID-19 Observatory in Latin America and the Caribbean [online] https://www.cepal.org/es/temas/covid-19 and Observatory on Social Development in Latin America and the Caribbean, “Social Development and COVID-19 in Latin America and the Caribbean” [online] https://dds.cepal.org/observatorio/socialcovid19/listamedidas.php.

a The 28 countries of Latin America and the Caribbean are divided into two groups: 18 Latin American countries and 10 Caribbean ones (Antigua and Barbuda, Bahamas, Barbados, Belize, Guyana, Jamaica, Saint Kitts and Nevis, Saint Vincent and the Grenadines, Saint Lucia, and Trinidad and Tobago). The Latin American countries are divided into two subgroups: 10 countries from South America (Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay; and eight from the group comprising Central America (Costa Rica, El Salvador, Guatemala, Honduras and Panama), plus the Dominican Republic, Haiti and Mexico. Each country’s total population in 2020 was obtained from CEPALSTAT [online] https://estadisticas.cepal.org/cepalstat/Portada.html.

b The average monthly exchange rate from March to October 2020 published by the International Monetary Fund (IMF) [online] https://data.imf.org/regular.aspx?key=61545862 was used, except in the case of the Bolivarian Republic of Venezuela, where the average daily exchange rate published by the Central Bank of Venezuela [online] http://www.bcv.org.ve/estadisticas/tipo-cambio-de-referencia-smc was used.

The pattern of subregional differences in estimated spending on emergency cash and in-kind transfers is repeated when the expenditure is expressed as a percentage of GDP. In this case, the simple average of estimated spending on this type of measure is 1.25% of GDP in the countries of Latin America and the Caribbean, and 1.55% of 2019 GDP in Latin America, while the average for the Caribbean countries is just 0.67%. The South American subregion displays the highest expenditure relative to GDP, with an average of 1.76%, Brazil leading with an estimated expenditure of over 4% of GDP, followed by Argentina, Peru and the Plurinational State of Bolivia, all with amounts above 2% of GDP. On the other hand, the resources associated with the measures announced by the countries of the subregion comprising Central America, the Dominican Republic, Haiti and Mexico average about 1.32% of 2019 GDP, with El Salvador, Guatemala and the Dominican Republic reporting amounts exceeding 1.7% of GDP (see table A2.1). Among the Caribbean countries, although the amounts committed are smaller and represent an average of 0.67% of GDP, Belize reports a level equivalent to 4.46% of GDP.

Estimated spending on emergency cash and in-kind transfers as a percentage of GDP in 2019 exceeds the average amount spent on conditional cash transfer programmes and social pensions as a percentage of GDP in 2018 (see figure IV.9). In South America, this difference is 0.75 percentage points, while in the subregion of Central America, the Dominican Republic, Haiti and Mexico, it is more than 1 percentage point. This reflects the efforts made by the region’s governments to support the most vulnerable populations in the midst of the crisis, as well as their capacity to make budgetary adjustments and raise funds for this purpose.[26]

Figure IV.9

Latin America and the Caribbean (26 countries): estimated spending on emergency cash and in-kind transfers (2020) and on conditional cash transfer (CCT) programmes and social pensions, 2018a

(Percentages of GDP)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries; COVID-19 Observatory in Latin America and the Caribbean [online] https://www.cepal.org/es/temas/covid-19 and Observatory on Social Development in Latin America and the Caribbean, “Social Development and COVID-19 in Latin America and the Caribbean” [online] https://dds.cepal.org/observatorio/socialcovid19/listamedidas.php.

a The figures shown are simple averages. The 26 countries of Latin America and the Caribbean are divided into two groups: 17 Latin American countries and nine Caribbean ones (Antigua and Barbuda, Bahamas, Barbados, Belize, Guyana, Jamaica, Saint Kitts and Nevis, Saint Vincent and the Grenadines, and Trinidad and Tobago). The Latin American countries are divided into two subgroups: nine countries from South America (Argentina, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay) and eight from the group comprising Central America (Costa Rica, El Salvador, Guatemala, Honduras and Panama), plus the Dominican Republic, Haiti and Mexico.

A comparison of average central government spending on emergency cash and in-kind transfers in the region’s countries in 2019 shows that subregional differences do not follow the pattern described above (see figure IV.10). In particular, estimated spending on measures of this type, as a percentage of social protection spending by central government, is higher in the subregion comprising Central America, the Dominican Republic, Haiti and Mexico than in South America. This is because the central governments of that country grouping spend less on social protection than those of South America. In some Central American countries, the share of central-government social spending allocated to social protection is even smaller than estimated spending on non-contributory cash and in-kind transfer measures. Examples include Guatemala, Honduras and the Dominican Republic, where estimated expenditures on measures of this type represent 128%, 337% and 123% of social spending allocated to social protection, respectively, while in El Salvador and Panama it exceeds 50%. This explains why the simple average of estimated spending on non-contributory cash and in-kind transfer measures represents 110% of social spending assigned to social protection in the countries of Central America, the Dominican Republic, Haiti and Mexico (see figure IV.10). The equivalent share is 33% in the countries of South America and 66.7% as an average for Latin America as a whole. Estimated spending on non-contributory measures in response to the pandemic accounts for 17.6% of social spending on social protection in the Caribbean, with Jamaica reporting the highest percentage in the subregion, at 56%.

Considering both total and social spending by central government, there is no major difference between the average for the countries of South America and those of Central America, the Dominican Republic, Haiti and Mexico. Spending committed to non-contributory measures in response to the COVID-19 crisis accounted for an estimated 7.1% and 7.7% of total expenditure by central government in the two subregions, respectively. Relative to central-government social spending, the corresponding shares are 13.1% and 15.9%. The Caribbean countries reported central government expenditure on these measures representing 0.8% of total expenditure and 2% of social spending.

Figure IV.10

Latin America and the Caribbean (21 countries): average spending on emergency cash and in-kind transfers between March and December 2020 relative to total central government, social and social protection spending in 2019a

(Percentages of the 2019 levels)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries; COVID-19 Observatory in Latin America and the Caribbean [online] https://www.cepal.org/es/temas/covid-19 and Observatory on Social Development in Latin America and the Caribbean, “Social Development and COVID-19 in Latin America and the Caribbean” [online] https://dds.cepal.org/observatorio/socialcovid19/listamedidas.php.

a The 21 countries of Latin America and the Caribbean are divided into two groups: 16 Latin American countries and five Caribbean ones (Bahamas, Barbados, Guyana, Jamaica and Trinidad and Tobago). The Latin American countries are divided into two subgroups: nine countries from South America (Argentina, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay) and seven from the group comprising Central America (Costa Rica, El Salvador, Guatemala, Honduras and Panama) plus the Dominican Republic and Mexico.

The results reported in this section demonstrate the scale of the effort made by the countries of the region to protect the income and consumption of households affected by the COVID-19 pandemic crisis in 2020. They also reveal the degree of vulnerability of the population, as well as the diversity of capacities and the implementation and financial challenges that exist in non-contributory social protection, both in dealing with this type of situation and in moving towards universal and comprehensive systems. Decisions made in this area will also affect the level of social spending required in the next few years.

C. Costs and impacts of universal and targeted cash transfers

ECLAC has proposed guaranteeing temporary cash transfers to meet basic needs during the pandemic. Their total cost, as well as their impact on poverty and inequality reduction, varies according to the amount of the transfers, their duration and the target population in question. The additional cost of an annual transfer equivalent to the poverty line for all people living in poverty is estimated at 4.8% of the region’s GDP.

To address the socioeconomic impacts of the crisis, in May 2020 ECLAC (2020e) proposed that governments should guarantee temporary cash transfers to enable households to meet basic needs and sustain their consumption. At that time, the transfers were intended to last for six months. However, given the persistence of the COVID-19 crisis, in July 2020, a call was made to consider alternatives lasting one year (ECLAC, 2020c), which would pave the way for actions to be implemented once the pandemic was overcome.

This section estimates the costs and impacts of implementing cash transfers to sustain basic levels of personal well-being in the face of the pandemic crisis, considering both six-month and one-year durations. The amounts of the transfers are equivalent to the extreme-poverty line, which represents the per capita cost of acquiring a basic food basket, and to the poverty line, which also covers other basic needs. The cost of the transfers is calculated for five target groups: (i) all persons (universal); (ii) all people living in poverty; (iii) all informal workers aged 18 to 64 years; (iv) all children and adolescents aged 0 to 17; and (v) all persons over 65. The combinations of target population, transfer amount and duration are alternatives to be considered according to the reality prevailing in each country.

Regionwide, a policy of universal transfer equivalent to the poverty line (on average, US$ 143 at 2010 prices) for a six-month period would cost about 9.5% of regional GDP (of 2019), rising to 19% of GDP if the transfer is maintained for a full year.[27] The costs of a universal transfer policy are significantly lower in the case of a cash transfer equivalent to a basic food basket or the extreme-poverty line income (US$ 67 on average at 2010 prices), which for one year would amount to around 8.9% of GDP (see figure IV.11).[28]

Figure IV.11

Latin America (18 countries): estimated cost and coverage of cash transfers equivalent to one poverty line and one extreme poverty line, by target population and duration, 2019a b

(Percentages of GDP and total population)

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

a The 18 countries are: Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

b Estimate based on a population of 230 million living in poverty in 2020. The administrative costs of making the transfers are not taken into account.

c The informal worker category encompasses workers in low-productivity sectors, including: domestic service, unskilled self-employed workers, unskilled workers in microenterprises and microentrepreneurs.

On the other hand, if the annual cash transfers equivalent to a poverty line income are paid exclusively to the population living in poverty, the cost would be 7% of GDP. A 12-month transfer of an extreme poverty line income to the same population would absorb about 3.3% of GDP.

Targeting these resources on other population groups would not necessarily have a direct impact on eradicating poverty and extreme poverty, but it would help to improve the well-being of poor and non-poor groups. A transfer equivalent to the poverty line to all children and adolescents for a period of one year would cost the equivalent of 5.5% of GDP (2.6% of GDP in the transfer amount was equivalent to the extreme poverty line). As families with children and adolescents are more likely to be in poverty than the rest of the population, the impact on poverty reduction would also be significant. If the transfers targeted workers in low-productivity sectors, the cost would be equivalent to 3.8% of GDP in the case of poverty line income for a whole year, and 1.8% of GDP if the transfer were equivalent to the extreme poverty line. If targeted on the elderly, the resource transfers would be equivalent to 1.7% and 0.8% of GDP, respectively.

By considering regional spending on ongoing non-contributory social protection programmes, such as conditional cash transfer programmes and social pensions, together with the emergency expenditures made by the countries of the region in 2020 to address the pandemic, it is possible to estimate the additional cost of implementing these transfers. This is done by deducting transfers that had been programmed previously from the total cost, considering the target population to be persons living in poverty.

According to information current as of 2019, conditional cash transfer programmes for poverty reduction and other social pensions cost 0.7% of GDP per year; and emergency programmes during the pandemic have cost about 1.6% of 2019 GDP. Taking this into account, a transfer equivalent to the poverty line for six months would entail additional expenditure of 2.0% of GDP to cover all persons in poverty in 2020. Extending the transfers over a one-year period would cost an additional 4.8% of GDP. If the transfer were equivalent to the extreme poverty line, the additional cost would be just 0.2% of GDP over a six-month period and 1.1% of GDP for a full year (see figure IV.12).

Figure IV.12

Latin America (18 countries):a estimated additional spending on transfers equivalent to a poverty line or an extreme poverty line complementary to permanent and emergency measures, targeting the entire population living in poverty, for 6 or 12 monthsb

(Percentages of 2019 GDP)

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

a The 18 countries are: Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

b The same amount of funding is considered for both six and 12 months.

Beyond financing, there are operational problems in implementing such transfers. From the health standpoint, the ideal is to promote physical distancing and make transfers online. However, as much of the population is unbanked, other solutions need to be found, such as payments by cell phone in physical cash, but avoiding crowds. Moreover, implementing very short-term transfers requires extensive and up-to-date social records. In this connection, one of the key challenges is the registry of informal workers, which suffers from a lack of records in contributory and even non-contributory social protection systems.

The various modalities of cash transfers have different impacts on reducing poverty and inequality. A transfer equivalent to the universal poverty line for all persons living in poverty would temporarily eradicate poverty. Other transfer scenarios have effects of different magnitude, depending on the population being targeted. Thus, a universal transfer equivalent to the extreme poverty line could eradicate extreme poverty, while reducing total poverty to around 15%.

Another significant effect can be obtained by allocating resources equivalent to the poverty line to all children and adolescents (up to 17 years of age). If annual, such a transfer would cut overall poverty from 37.2% to 20.1% and lower extreme poverty to 5.2%. Clearly if the transfer were equivalent to the extreme poverty line or a basic food basket, it would have a smaller effect on poverty reduction (see figure IV.13). Transfers targeted on older adults would also have less of an impact on reducing poverty and extreme poverty. Nonetheless, they would undoubtedly make a significant improvement to the welfare of a large proportion of older adults, given the low level of pensions in Latin America, in terms of both coverage and amount. A relatively significant impact could also be obtained by targeting transfers on workers in low-productivity sectors.

Figure IV.13

Latin America (18 countries):a impact on the reduction of poverty and extreme poverty of universal transfers and transfers targeted on specific population groups, equivalent to one poverty line and one extreme poverty line per month, for one year

(Percentages)

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

a The 18 countries are: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay.

Another significant effect of this type of transfer over a one-year period is the reduction in inequality, as measured by the Gini coefficient. The sharpest reductions in income inequality appear to come precisely from transfers equivalent to the universal poverty line (the Gini coefficient drops from 0.488 to 0.333), followed by transfers targeted only on people in poverty, and then those targeting the child population.

D. Concluding remarks

As described in the first part of this chapter, statistics on the magnitude of central government funding for social policies in 2019 in the different countries show that the trends of the last two decades are being maintained, both in the pace of growth and in the heterogeneity of situations between different countries and the priority assigned to the various social functions.

The available information shows that, between 2000 and 2019, Latin American countries maintained relatively steady growth in central government social spending on average as a percentage of GDP, generating a cumulative increase of 36%. In recent years, central government social spending has stabilized around 11.4% of GDP, with amounts representing close to US$ 950 per person per year. The five English-speaking Caribbean countries studied here have recorded five years of relative stability, with average amounts equivalent to 11.9% of GDP and US$ 1,500 per person.

As noted above, heterogeneity in social spending levels continues to be a characteristic of the region, with eight countries allocating less than 10% of their GDP to central-government social spending and three exceeding 17% (Brazil, Chile and Uruguay). In South America and the Caribbean only one country remains in the lowest central government spending group, while just two countries exceed this threshold in Central America.

In the region, the amount of funding per person also reflects that heterogeneity. Chile and Uruguay spend more than US$ 2,500 per person per year, and Barbados, the Bahamas and Trinidad and Tobago also spend more than US$ 2,000. In contrast, the Plurinational State of Bolivia, El Salvador, Guatemala, Nicaragua and Honduras allocate per capita amounts ranging from US$ 351 to US$ 175 per year. As highlighted in previous editions of Social Panorama of Latin America (ECLAC, 2018 and 2019b), the Latin American countries that face the greatest social challenges in meeting the goals of the 2030 Agenda for Sustainable Development are those that spend the least on funding social functions.

In terms of social functions, social protection, education and health are the main priorities in terms of funding levels. This is true of all three subregions analysed, although the social-protection share varies. While in the South American countries this is the main function, with average funding accounting for almost half (46%) of total central government social spending, among the English-speaking Caribbean countries and in Central America, Mexico and the Dominican Republic, this function ranks second or third (23%).

The amount that countries spend on social policy is greater when considering an institutional coverage broader than central government, encompassing autonomous institutions, particularly those related to contributory pensions. In many cases, this significantly alters the distribution of funding among the different social functions. However, it is currently only possible to analyse data from nine Latin American countries in some years, so the challenge remains to continue expanding the availability of these data and improve the comparability of public social spending throughout the region. This is particularly important in countries with subnational collection and expenditure systems that are autonomous from the central government.

Section B highlights the volume of resources committed by Latin American and Caribbean countries to respond to the economic and social crisis resulting from the pandemic, with non-contributory social protection measures involving cash and in-kind transfers. The simple average of these commitments in the region’s countries is estimated to be about 0.6 percentage points of GDP higher than spending on conditional cash transfer programmes and social pensions, which, in 2018, represented an average of 0.65% of GDP (0.68% in Latin America and 0.58% in the Caribbean). In the case of Latin America, the amounts committed, equivalent on average to 1.55% of GDP in 2019, are more than double the expenditure on such programmes in 2018.

Spending commitments under the measures analysed here involve mobilizing extraordinary resources, reallocating budgetary funding between expenditure items, or bringing forward payments already budgeted for in longer-term measures. Much of the funding also comes from allocations for the same social functions, so they do not necessarily imply higher social spending in total. Regardless of the source of the funding, the size of the amounts committed reveals the importance that countries have placed on addressing the social crisis resulting from the pandemic.

The increase in social protection spending in the countries of the region, particularly through non-contributory measures involving cash and in-kind transfers, was targeted mainly on households and individuals whose incomes were affected by the crisis. This increased the magnitude of support for those who were users of non-contributory programmes before the pandemic, mainly households living in poverty or extreme poverty (see chapter III); but it also meant an increase in coverage for the non-poor population and middle-income groups, given the vulnerability of many households in the region that are not normally covered by non-contributory social protection. Accordingly, and in view of the gaps in social protection coverage that have existed since before the COVID-19 crisis, as described in chapter III, the level of spending on non-contributory programmes should be expanded once the pandemic is over. In line with the agreements established in the Regional Agenda for Inclusive Social Development, approved at the third meeting of the Regional Conference on Social Development in Latin America and the Caribbean in 2019, it will be necessary to review models of financing and resource allocation to expand the development of universal and comprehensive social protection systems, with sufficient amounts and quality services. The impacts on poverty, extreme poverty and income inequality of annual cash transfers discussed in section C highlight the importance of gradually incorporating certain universal income guarantees into the countries’ social protection systems, for example, in the form of a universal transfer for children and a citizen’s basic income.

The region’s countries face the challenge of adapting their income and expenditures on social functions to finance recovery measures, in addition to continuing to develop their longer-term policies to advance towards the Sustainable Development Goals of the 2030 Agenda. The impact of the pandemic can thus become an opportunity to reinforce these priorities of the region’s governments and align their fiscal efforts to rebuild better and with equality, leaving no one behind.

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Annex IV.A1

Table IV.A1.1

Latin America and the Caribbean (24 countries): central-government social spending by function, 2019

(Percentages of GDP, dollars at 2010 prices and percentages)

Country

Social spending

Distribution of social spending by function, 2018

(percentages)

As a percentage of GDP

Per capita in dollars at constant 2010 prices

2018

2019

2018

2019

Social protection

Education

Health

Housing and community amenities

Recreation, culture and religion

Environmental protectiona

Total

Argentina

13.6

13.0

1 376

1 278

82.9

8.6

6.1

1.9

0.0

0.5

100

Bahamas

7.2

7.6

1 962

2 068

15.8

34.9

34.7

0.4

3.5

10.8

100

Barbados

15.8

14.3

2 551

2 300

27.3

37.1

20.9

7.4

2.9

4.4

100

Bolivia (Plurinational State of)

12.0

…

308

…

29.5

47.1

17.0

6.4

0.0

0.0

100

Brazil

17.4

17.6

1 932

1 958

73.4

13.0

12.0

0.7

0.3

0.5

100

Chile

16.4

17.1

2 485

2 584

35.3

31.3

29.8

1.9

1.1

0.6

100

Colombia

12.5

2.4

965

976

43.9

26.4

24.0

4.1

1.2

0.5

100

Costa Rica

12.1

12.4

1 197

1 245

34.6

56.4

6.5

0.4

1.0

1.0

100

Cuba

9.3

…

634

…

66.7

18.2

8.1

1.8

5.2

0.0

100

Dominican Republic

7.6

7.7

585

614

18.0

52.6

21.7

4.4

2.1

1.3

100

Ecuador

9.1

10.5

469

534

27.0

43.2

25.7

2.0

1.4

0.7

100

El Salvador

9.6

9.8

335

351

35.8

37.2

24.4

0.7

1.4

0.6

100

Guatemala

7.6

7.9

235

250

17.7

41.5

16.5

19.2

2.3

2.8

100

Guyana

12.7

13.7

515

580

18.9

40.9

29.7

7.1

2.0

1.4

100

Haitib

5.2

…

38

…

11.0

56.8

16.1

0.9

8.7

6.4

100

Honduras

7.9

7.8

176

175

5.6

62.6

29.2

0.9

0.0

1.6

100

Jamaica

10.3

10.5

502

511

7.3

48.8

34.2

5.7

2.0

2.0

100

Mexico

8.8

9.3

909

955

42.4

34.0

10.8

11.0

1.0

0.8

100

Nicaragua

11.1

10.8

207

190

6.4

43.3

33.3

13.9

1.4

1.6

100

Panamac

8.7

…

1 000

…

15.4

38.3

19.8

20.1

1.9

4.5

100

Paraguay

8.9

9.5

479

501

39.6

35.4

20.9

2.5

0.0

1.7

100

Perud

11.1

11.5

716

748

26.3

33.6

22.0

3.7

4.1

10.3

100

Trinidad and Tobago

13.7

13.5

2 078

2 034

39.3

25.4

20.6

13.0

1.7

0.0

100

Uruguaye

17.4

17.7

2 538

2 578

44.8

28.5

21.9

3.3

1.3

0.2

100

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

a Data on environmental protection may differ from estimates based on environmental satellite accounts.

b Data for Haiti correspond to 2014.

c Data for Panama correspond to 2017.

d Coverage in the case of Peru is general government.

e Data for Uruguay do not include expenditures incurred by the Social Security Bank (BPS).

Table IV.A1.2

Latin America (9 countries): social spending by institutional coverage and function, 2019

(Percentages of GDP, dollars at 2010 prices and percentages)

Country

Coverage

Social spending

Distribution of social spending by function, 2019

(percentages)

As a percentage of GDP

In dollars per capita at constant 2010 prices

Social protection

Education

Health

Housing and community amenities

Recreation, culture and religion

Environmental protectiona

Total

Argentinab

Public sector

30.3

3 190

49.8

18.9

21.9

8.5

0.8

0.0

100

Bolivia (Plurinational State of)c

General government

22.2

539

21.0

38.9

24.8

8.0

3.2

4.1

100

Brazil

General government

27.0

3 006

59.2

19.1

19.1

0.2

0.8

1.7

100

Colombiad

General government

19.7

1 517

44.1

21.3

25.9

2.6

3.5

2.6

100

Costa Rica

Public sector

24.5

2 461

31.8

29.8

27.1

10.0

0.7

0.5

100

Cubad

General government

27.6

1 884

22.4

29.0

38.1

3.9

6.5

0.0

100

El Salvador

Public sector

14.8

529

35.0

26.1

17.5

20.0

1.1

0.4

100

Paraguayd

General government

13.1

702

43.2

29.1

24.0

2.9

0.6

0.0

100

Peru

General government

11.5

748

24.0

33.6

22.2

3.9

5.3

0.0

100

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

a Data on environmental protection may differ from estimates based on environmental satellite accounts.

b Data for Argentina refer to 2017.

c Data for the Plurinational State of Bolivia refer to 2016.

d Data for Colombia, Cuba and Paraguay refer to 2018.

Annex IV.A2

Table IV.A2.1

Latin America and the Caribbean (28 countries): non-contributory measures of cash and in-kind transfers in response to the COVID-19 crisis considered for expenditure estimation, as of 6 November 2020

Country

Measure

Type of measure (priority)

Innovation (priority)

Estimated expenditure (percentage of GDP)

Antigua and Barbuda

National School Meals Programme

In-kind transfer

New action or service in existing measure or programme

0.03

COVID-19 Emergency Food Assistance Programme

In-kind transfer

New measure or programme

Argentina

Bonus for users of Universal Child Allowance (AUH) and Universal Pregnancy Allowance (AUE)

Cash transfer

Increase in amounts, goods or services of existing programme

2.23

Bonus for users of non-contributory pensions

Cash transfer

Increase in amounts, goods or services of existing programme

Food card (Tarjeta alimentar) —access acceleration and change in delivery mode

Cash transfer

Increased coverage of existing programme

Emergency Family Income (IFE)

Cash transfer

New measure or programme

Reinforcement for beneficiaries of social plans

Cash transfer

Increase in amounts, goods or services of existing programme

Adjustment to school feeding delivery mode

In-kind transfer

New action or service in existing measure or programme

Extraordinary payment for retirees

Cash transfer

New action or service in existing measure or programme

MANTA, scholarship for artisanal production development

Cash transfer

New measure or programme

Strengthen Culture Programme

Cash transfer

New measure or programme

Bahamas

Government Funded Unemployment Assistance for COVID-19

Cash transfer

New measure or programme

0.19

Meal vouchers for students

Cash transfer

New action or service in existing measure or programme

Emergency food assistance

Cash transfer

New measure or programme

Barbados

Vulnerable Family Survival Programme

Cash transfer

New measure or programmee

0.03

Belize

Unemployment Relief Programme

Cash transfer

New measure or programme

4.46

School Nutrition programme

In-kind transfer

New action or service in existing measure or programme

Food Assistance Programme

In-kind transfer

New measure or programme

Expansion of the BOOST (BOOST 2.0 or Belize COVID-19

Cash Transfer Program - BCCAT)

Cash transfer

Increased coverage of existing programme

Bolivia (Plurinational State of)

Universal Bonus

Cash transfer

New measure or programme

2.83

Bono Familia (Family allowance)

Cash transfer

New measure or programme

Canasta familiar (Family basket)

Cash transfer

New measure or programme

Anti-hunger allowance

Cash transfer

New measure or programme

Renta Dignidad (Dignity Income) annual bonus

Cash transfer

Advance delivery of amounts, goods or services of existing programme

Brazil

Emergency assistance to indigenous families under the Bolsa Família family allowance programme

Cash transfer

Increase in amounts, goods or services of existing programme

4.02

Increased coverage of Bolsa Família programme

Cash transfer

Increased coverage of existing programme

Advance payment of the continuous benefit programme

(Benefício de Prestação Contínua – BPC)

Cash transfer

Advance delivery of amounts, goods or services of existing programme

Federal Government Emergency Aid

Cash transfer

New measure or programme

School meals distribution

In-kind transfer

New action or service in existing measure or programme

Delivery of food baskets to indigenous families

In-kind transfer

New measure or programme

Food purchases from family farmers

In-kind transfer

New action or service in existing measure or programme

Chile

COVID-19 Emergency bonus

Cash transfer

New measure or programme

1.83

Emergency Family Income for COVID-19 (Ingreso Familiar de Emergencia – IFE)

Cash transfer

New measure or programme

Emergency Family Income 2.0 for COVID-19 (IFE 2.0)

Cash transfer

New measure or programme

Middle Class Protection Plan 2: Rent subsidy for the middle class

Cash transfer

New measure or programme

Middle Class Protection Plan: non-refundable bonus for the middle class

Cash transfer

New measure or programme

Colombia

Families in Action (payment of additional cash transfers)

Cash transfer

Increase in amounts, goods or services of existing programme

1.16

Youth in Action (payment of additional cash transfers)

Cash transfer

Increase in amounts, goods or services of existing programme

Colombia Mayor Senior Citizen Programme (payment of additional cash transfers)

Cash transfer

Increase in amounts, goods or services of existing programme

Colombia está Contigo (Colombia is with you) support for the elderly

In-kind transfer

New measure or programme

School Feeding Programme

In-kind transfer

New action or service in existing measure or programme

Solidarity Income

Cash transfer

New measure or programme

Early Childhood Food Baskets

In-kind transfer

Increased coverage of existing programme

Colombia está Contigo (Colombia is with you), One Million Families Programme

In-kind transfer

New measure or programme

Social welfare – value-added tax (VAT) relief

Cash transfer

New measure or programme

Humanitarian assistance for victims of the conflict

Cash transfer

Advance delivery of amounts, goods or services of existing programme

Administrative reparations for victims of the conflict

Cash transfer

Advance delivery of amounts, goods or services of existing programme

Economic incentive for farm workers and producers over 70 years of age

Cash transfer

New measure or programme

Special economic support for the population in the process of reintegration (demobilized combatants)

Cash transfer

New measure or programme

Rural water supply subsidy

In-kind transfer

New measure or programme

Support programme for workers with suspended contracts

Cash transfer

New measure or programme

Colombia está Contigo (Colombia is with you) vulnerable migrant programme

In-kind transfer

New measure or programme

Colombia está Contigo (Colombia is with you) vulnerable population programme

In-kind transfer

New measure or programme

College tuition subsidy

Cash transfer

New measure or programme

Manos que Alimentan (Hands that feed)

In-kind transfer

New measure or programme

Tiendas para la Gente (Shops for the People)

Cash transfer

New measure or programme

Costa Rica

School meal food packages

In-kind transfer

New action or service in existing measure or programme

1.27

CEN-CINAI en Casa (At home) programme

In-kind transfer

New action or service in existing measure or programme

Temporary subsidy for lottery ticket vendors

Cash transfer

New measure or programme

Proteger bonus

Cash transfer

New measure or programme

Emergency subsidy of the Mixed Social Assistance Institute (IMAS)

Cash transfer

New measure or programme

Advance payment of the Non-Contributory Regime pensions

Cash transfer

Advance delivery of amounts, goods or services of existing programme

Close season subsidy for fisherfolk

Cash transfer

New measure or programme

Dominican Republic

Quédate en casa (Stay at home) programme

Cash transfer

New measure or programme

1.70

Pa’ Ti Self-Employment Assistance Programme

Cash transfer

New measure or programme

Ecuador

Health Emergency Family Protection Bonus

Cash transfer

New measure or programme

0.13

Food kits

In-kind transfer

New measure or programme

Financial compensation for families whose income has been affected by the crisis

Cash transfer

New measure or programme

Nutritional Support Grant

Cash transfer

New measure or programme

El Salvador

Grant of US$ 300

Cash transfer

New measure or programme

1.85

Food baskets (Health Emergency Programme)

In-kind transfer

New measure or programme

Guatemala

School feeding

In-kind transfer

New action or service in existing measure or programme

1.78

Cash transfers

Cash transfer

New measure or programme

Food grant, COVID-19 Food Support and Prevention Programme.

In-kind transfer

New measure or programme

Bono Familia (family allowance)

Cash transfer

New measure or programme

Support for Popular Trade

Cash transfer

New measure or programme

Saldremos Adelante (We’ll get through this) kit

In-kind transfer

New measure or programme

Economic Contribution to the Elderly Programme, expansion of coverage

Cash transfer

Increased coverage of existing programme

COVID-19 assistance fund in the event of death abroad

Cash transfer

New measure or programme

Guyana

Social Relief Hampers

In-kind transfer

New measure or programme

0.34

Haiti

Social assistance transfer

Cash transfer

New measure or programme

0.84

Delivery of food packages

In-kind transfer

New measure or programme

Honduras

Honduras Solidaria (Honduras shows solidarity) programme

In-kind transfer

New measure or programme

1.49

Solidarity bonus for transportation workers

Cash transfer

New measure or programme

Jamaica

Programme of Advancement Through Health and Education (PATH), increased transfer and special payment

Cash transfer

Increase in amounts, goods or services of existing programme

0.43

COVID-19 Compassionate Grant - CARE Programme

Cash transfer

New measure or programme

Dignity kit packages

In-kind transfer

New measure or programme

Supporting Employees with Transfer of Cash (SETCASH) programme - CARE Programme

Cash transfer

New measure or programme

COVID-19 General Grants - CARE Programme

Cash transfer

New measure or programme

Back-to-school Grant

Cash transfer

Increase in amounts, goods or services of existing programme

Mexico

Pension Programme for the Well Being of the Elderly (advance payment equivalent to four months)

Cash transfer

Advance delivery of amounts, goods or services of existing programme

0.42

Pension Programme for the Well-being of Persons with Permanent Disabilities (advance payment equivalent to four months)

Cash transfer

Advance delivery of amounts, goods or services of existing programme

Sembrando Vida (Sowing life) programme (increased coverage)

Cash transfer

Increased coverage of existing programme

Assistance component for the well-being of fisherfolk and fish farmers (Bienpesca)

Cash transfer

Increased coverage of existing programme

Panama

Panama Solidarity Plan

Cash transfer

New measure or programme

1.18

Vale Panamá voucher programme

Cash transfer

New measure or programme

Paraguay

Tekoporã social programme (additional payment)

Cash transfer

Increase in amounts, goods or services

of existing programme

1.14

Food pensions for the elderly in a situation of poverty (advance pension payment)

Cash transfer

Advance delivery of amounts, goods or services of existing programme

Ñangareko food security programme

Cash transfer

New measure or programme

Pytyvõ subsidy programme

Cash transfer

New measure or programme

Pytyvõ 2.0 subsidy programme

Cash transfer

New measure or programme

Abrazo child protection programme - expansion of coverage

In-kind transfer

Increased coverage of existing programme

Peru

Yo me quedo en casa (I’m staying at home) bonus (also known as Bono 760 soles or Bono Urbano)

Cash transfer

New measure or programme

2.36

Universal Family Allowance

Cash transfer

New measure or programme

Rural Bonus

Cash transfer

New measure or programme

Non-contributory pensions; Pensión 65 and CONTIGO

(double payment in advance)

Cash transfer

Advance delivery of amounts, goods or services of existing programme

Additional discount voucher for the purchase of gas cylinders

In-kind transfer

Increase in amounts, goods or services of existing programme

Qali Warma food distribution programme

In-kind transfer

New action or service in existing measure or programme

Food basket

In-kind transfer

New measure or programme

Bonus for independent workers

Cash transfer

New measure or programme

Bonus for workers with suspended contracts

Cash transfer

New measure or programme

Electricity Grant

In-kind transfer

New measure or programme

Subsidy for independent cultural workers

Cash transfer

New measure or programme

Advanced transfer to users of the JUNTOS National Programme of Direct Support to the Poorest

Cash transfer

Advance delivery of amounts, goods or services of existing programme

Second Universal Family Bonus

Cash transfer

New measure or programme

Bono 200 soles (Subsidy of 200 soles) for children

Cash transfer

New measure or programme

CONTIGO programme - increased coverage

Cash transfer

Increased coverage of existing programme

Saint Kitts and Nevis

Delivery of food vouchers

In-kind transfer

New measure or programme

0.01

Saint Vincent and the Grenadines

Unemployment Benefit

Cash transfer

New measure or programme

0.40

Displacement Supplementary Income - Stimulus package

Cash transfer

New measure or programme

Love Box

In-kind transfer

New measure or programme

Interim Assistance Benefits for workers in the informal sector

Cash transfer

New measure or programme

Interim Assistance Benefit for vulnerable Vincentians

Cash transfer

New action or service in existing measure or programme

Economic support for cultural and creative professionals

Cash transfer

New measure or programme

Saint Lucia

Self Employed Subsistence Allowance

Cash transfer

New measure or programme

0.63

Temporary Income Support Programme for Non-NIC Contributors

Cash transfer

New measure or programme

Expansion of the Public Assistance Programme, Cash Transfer

Cash transfer

Increased coverage of existing programme

Increase in Child Disability Grant

Cash transfer

Increase in amounts, goods or services

of existing programme

Increased Grant for Persons Living with HIV

Cash transfer

Increase in amounts, goods or services

of existing programme

Increase in the grant for children in foster care

Cash transfer

Increase in amounts, goods or services

of existing programme

Electricity Assistance Programme (EAP)

In-kind transfer

New measure or programme

Trinidad and Tobago

Food Card

Cash transfer

Increase in amounts, goods or services

of existing programme

0.12

Public Assistance and Disability Grant

Cash transfer

Increase in amounts, goods or services

of existing programme

Rental Assistance

Cash transfer

New measure or programme

School Feeding Programme

Cash transfer

Increase in amounts, goods or services

of existing programme

Emergency Food Support to New Beneficiaries - Food Vouchers

In-kind transfer

New action or service in existing measure or programme

Uruguay

Uruguay Social Card (TUS) (doubling of transfer amounts)

Cash transfer

Increase in amounts, goods or services

of existing programme

0.14

Family Allowance - Equity Plan (doubling of transfer amounts)

Cash transfer

Increase in amounts, goods or services

of existing programme

Operativo Canasta emergency food basket

Cash transfer

New measure or programme

School feeding

Cash transfer

New action or service in existing measure or programme

Venezuela (Bolivarian Republic of)

Local supply and production committees (CLAP) food box

In-kind transfer

New action or service in existing measure or programme

-

“Disciplina y Solidaridad” (Discipline and Solidarity) grant

Cash transfer

New measure or programme

“Quédate en casa” (Stay at Home) grant

Cash transfer

New measure or programme

Easter Bonus

Cash transfer

New action or service in existing measure or programme

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official information from the countries; Observatory on Social Development in Latin America and the Caribbean, “Social Development and COVID-19 in Latin America and the Caribbean” [online] https://dds.cepal.org/observatorio/socialcovid19/listamedidas.php.

Annex IV.A3

Methodology used to estimate spending on non-contributory cash and in-kind transfer measures announced in response to the COVID-19 crisis in Latin American and Caribbean countries

Spending commitments in respect of non-contributory social protection measures announced by the region’s countries in the context of the COVID-19 pandemic are estimated on the basis of measures publicly announced by the region’s governments between March and 6 November 2020. This information has been systemized by ECLAC in the COVID-19 Observatory in Latin America and the Caribbean and in the Observatory of Social Development in Latin America and the Caribbean —Social Development and COVID-19 in Latin America and the Caribbean.[29]

The following criteria were considered for the analysis presented in this chapter:

i)Only measures representing cash or in-kind transfers are included.

ii)For each country, the estimate is made in current national currency and then expressed in current dollars and as a percentage of 2019 GDP.

iii)The estimation of expenditures by measure prioritizes expenditures actually executed, as reported by the entities in charge of the programmes.

iv)In the absence of data on executed expenditure, expenditure is estimated from information available on the amounts of the transfers (or the equivalent amount in the case of in-kind transfers), the announced or executed coverage, the number of deliveries or the duration of the measure and its starting date. The monthly expenditure per measure is estimated by multiplying the announced coverage, in terms of either individuals or households, by the monthly amount payable to each individual or household unit, as the case may be.

v)The monthly amount in current national currency is obtained from information on the amount of the benefit or service. In cases where the amount payable depends on the characteristics of the users (income, household size, age or sex, among other criteria), the available information is used to obtain the closest approximation to the average monthly amount in national currency. In the absence of direct information on the average amount, the calculation is based on the characteristics of each measure.

vi)To convert the monthly amount of transfers in local currency into current dollars, the average monthly exchange rate from March to October 2020 published by the International Monetary Fund was used (accessed on 11 November 2020 [online] https://data.imf.org/regular.aspx?key=61545862). In the case of the Bolivarian Republic of Venezuela, the average daily exchange rate published by the Central Bank of Venezuela was used (accessed on 13 November 2020 [online] http://www.bcv.org.ve/estadisticas/tipo-cambio-de-referencia-smc).

vii)If a measure does not include information on transfer coverage or amounts, but does provide data on budget, delivery frequency and duration, this is used to estimate the missing data. For example, if a measure is delivered once per person and data on coverage and budget are available, the amount per person can be calculated by dividing the budget by the coverage. A similar process is followed if the missing information is the amount of the transfer.

viii)Once the monthly expenditure per measure has been estimated in current dollars, then the total expenditure per measure is calculated between March and May, between March and August, and between March and December 2020, depending on the duration in question. For example, if a measure lasts for three months starting in March 2020, then the monthly spending is multiplied by three to obtain the estimated spending for the measure between March and May, by six to obtain the estimated spending between March and August, and by ten to obtain the estimated spending between March and December. If a measure is to last six months and implementation began in April 2020, then the monthly spending per measure in dollars is multiplied by two to obtain the estimated spending for the measure from March to May, by five for the spending from March to August, and by six for the spending over the year.

ix)Once the monthly expenditure in current dollars has been estimated for March–May, March–August and March–December, the total expenditure by country for the same periods is estimated as the sum of the estimated expenditure for all measures considered over the period in question.

x)Estimated spending on non-contributory cash and in-kind transfer measures in the subregions is calculated as the sum of the estimated spending of the respective countries for which information is available: 10 Caribbean countries (Antigua and Barbuda, Bahamas, Barbados, Belize, Guyana, Jamaica, Saint Kitts and Nevis, Saint Vincent and the Grenadines, Saint Lucia, and Trinidad and Tobago) and 18 Latin American ones. The latter are divided into two subgroups: ten countries from South America (Argentina, the Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay) and eight from the group comprising Central America (Costa Rica, El Salvador, Guatemala, Honduras and Panama), together with the Dominican Republic, Haiti and Mexico.

xi)For comparison purposes, estimates of expenditure committed on non-contributory cash and in-kind transfer measures to address the COVID-19 crisis in 2020 are expressed as percentages of 2019 GDP for each country. These amounts are then contrasted with the latest available data on total central government public spending (2019), central government spending on social protection (2019), and spending on conditional cash transfers and social pensions (2018).

[1] In line with the higher levels of public debt, interest payments in Latin America rose from 1.7% to 2.6% of GDP between 2010 and 2019. In contrast, among Caribbean countries they fell from 3.6% of GDP in 2010 to 2.7% in 2019 (ECLAC, 2020b).

[2] Information for the Bolivarian Republic of Venezuela, Cuba and Haiti are not included, since up-to-date figures are not available for the entire series considered.

[3] Data for some Caribbean countries indicate higher figures than those reported in Social Panorama of Latin America, 2018, owing to adjustments made in the countries’ official information (ECLAC, 2018).

[4] The rise reflects an increase in transfers to the Ecuadorian Social Security Institute (IESS). In March 2018, Ecuador’s Constitutional Court ordered the central government to resume its contribution to finance 40% of the pension fund, which had been suspended in 2015 as part of the Organic Law for Labour Justice and Recognition of Household Work, which replaced this central government contribution with a guarantee.

[5] For further information, see Organization for Economic Cooperation and Development (OECD), OECD.Stat [online database] https://stats.oecd.org/.

[6] The way in which Latin American and Caribbean countries manage their pension systems may affect these comparisons, since several countries do not record the corresponding expenditures in central government statistics, but separately in social security entities, whether publicly or privately managed.

[7] Data for the Plurinational State of Bolivia correspond to 2018; data for Panama refer to 2017; and both Haiti and the Bolivarian Republic of Venezuela are excluded owing to a lack of information.

[8] Expenditure associated with surviving dependents consists of social protection in the form of cash transfers and in-kind benefits for the survivors of a deceased person (such as spouse, former spouse, children, grandchildren, parents and other relatives).

[9] Refers to support to facilitate access to housing and includes: “Provision of social protection in the form of benefits in kind to help households meet the cost of housing (recipients of these benefits are means-tested) · Administration, operation, or support of such social protection schemes · Benefits 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 (i.e., to help with paying mortgages or interest), and provision of low-cost or social housing.” (IMF, 2014, p. 188).

[10] Such as that resulting from the COVID-19 pandemic during 2020, which is discussed in the next section.

[11] Information for 2018.

[12] Ibid.

[13] Data corresponding to 2017.

[14] See Goal 4 of the Sustainable Health Agenda for the Americas 2018–2030 (PAHO/WHO, 2017).

[15] Data for 2017.

[16] For further details on this topic, see ECLAC’s regional network of environmental statistics [online] https://comunidades.cepal.org/estadisticas-ambientales/es.

[17] Although two other countries publish information of broader institutional coverage (Cuba and the Plurinational State of Bolivia), the latest reports analysed were already considered in Social Panorama of Latin America, 2019, and no new information is available for this edition.

[18] Obtaining data series with a broader coverage than central government requires a major effort to consolidate public finances between the different levels of government. For this reason, information is not available for all countries, and in some cases the year of analysis differs.

[19] In the case of Peru, the series is the same as that referred to in the previous sections, since only data on general government coverage is available.

[20] Includes 31 countries. For comparison purposes, countries from the region are not considered. Data for Luxembourg, the Republic of Korea and the United States refer to 2017. For further details, see expenditure data by function in Organization for Economic Co-operation and Development (OECD) OECD Statistics [online] https://stats.oecd.org/.

[21] The information used in this section corresponds to official announcements made by the authorities of each of the region’s countries, which are systemized in the subsite on Social Development and COVID-19 in Latin America and the Caribbean of the Observatory COVID-19 in Latin America and the Caribbean [online] https://www. https://www.cepal.org/en/topics/covid-19 and of ECLAC’s Observatory of Social Development in Latin America and the Caribbean [online] https://dds.cepal.org/observatorio/socialcovid19/.

[22] Annex IV.A3 describes the methodology used to estimate spending on non-contributory cash and in-kind transfer measures in response to the social crisis of the COVID-19 pandemic.

[23] Table A2.1 lists the 144 measures used to estimate expenditure by country. All the measures considered are publicly financed, except four that have a mixture of public and private funding. In these cases there is insufficient information to estimate specific government spending. The four measures in question are: the COVID-19 Emergency Food Assistance Programme in Antigua and Barbuda; the Food Kits programme in Ecuador; the Food Baskets (Health Emergency Programme) in El Salvador; and the Social Relief Hampers programme in Guyana. For detailed information on non-contributory social protection measures announced by countries in the region in the context of the COVID-19 pandemic, see ECLAC’s Observatory of Social Development in Latin America and the Caribbean – Social Development and COVID-19 in Latin America and the Caribbean [online] https://dds.cepal.org/observatorio/socialcovid19/listamedidas.php and COVID-19 Observatory in Latin America and the Caribbean [online] https://www.cepal.org/en/topics/covid-19.

[24] This estimated spending includes measures to bring forward payments for existing programmes; measures to increase the coverage of existing programmes; measures to increase the amounts, goods or services of existing programmes; measures involving new actions or services in existing programmes; and measures involving the creation of new programmes specifically to counter the effects of the COVID-19 crisis. Most governments have provided data to estimate spending used specifically to mitigate the effects of the COVID-19 crisis. However, some measures to advance payments for existing programmes, while requiring governments to make an effort to cover expenditures in periods outside the budget, have estimated expenditure that was already considered in the annual budget of the countries concerned. These measures in question are: the Renta Dignidad annual bonus, in the Plurinational State of Bolivia (US$ 43.4 million); Humanitarian assistance for victims of the conflict, and Administrative reparations for victims of the conflict in Colombia (US$ 134.4 million); Advance payment of the non-contributory regime pensions in Costa Rica (US$ 4,353.1 million); Advance payment of the Pension programme for the well-being of the elderly, and Advance payment of the Pension programme for the well-being of persons with disabilities, in Mexico (US$ 434,126.7 million); Advance payment of the food pension for the elderly in a situation of poverty, in Paraguay (US$ 16.7 million), and Advance payment of the non-contributory pensions –Pension 65 and CONTIGO, and Advance transfer to users of the JUNTOS national programme of direct support to the poorest in Peru (US$ 520.9 million). There are also 17 measures within existing programmes that make use of the programmed budget, but redirected to new actions. Examples include the school feeding programmes, which used the school feeding budget to prepare and deliver food baskets to the families of children and adolescents who stopped attending school.

[25] Among South American countries, Brazil and Argentina jointly account for about 71% of all announced spending. These countries also accounted for 70% of the GDP and 60% of the population of South America in 2019. Of the spending reported among the countries of Central America, the Dominican Republic, Haiti and Mexico, 46% corresponds to the latter country. Mexico also accounts for 80% of GDP and 64% of the population of this subregion. In 2019, it implemented a restructuring and expansion of cash transfers, which has prioritized protecting income and consumption among the most vulnerable families during the crisis.

[26] Total spending on conditional cash transfer (CCT) programmes and social pensions in Latin America and the Caribbean represents about 1.2% of regional GDP in 2018. This figure differs from the simple average of spending on these programmes as a percentage of GDP shown in figure IV.9, owing to the greater weight of spending on CCTs and social pensions in some countries relative to regional GDP.

[27] These costs differ significantly from one country to another. For example, the annual cost varies from around 10% to more than 40% of GDP, depending on the country in question.

[28] The poverty line values represent a regional weighted average. In the simple average, the poverty line is equivalent to US$ 118 and the extreme poverty line is equivalent to US$ 57, both at 2010 prices.

[29] See [online] https://www.cepal.org/en/topics/covid-19 and https://dds.cepal.org/observatorio/socialcovid19/en/.

Chapter V

The care economy: a sector of strategic importance for reactivation with equality

Introduction

A. The care crisis and care in crises

B. Care work in times of COVID-19

C. The benefits of investing in care

Bibliography

Introduction

The current sexual division of labour and the social organization of care continue to be one of the structural challenges of inequality in Latin America and the Caribbean (ECLAC, 2018a). They not only interfere with women’s full enjoyment of their rights and their autonomy but also generate a series of economic and social inefficiencies that have negative spillovers for society as a whole. They deepen existing inequalities because they impinge on the rights of those who give or provide care and those who receive it. Now, in the midst of the COVID-19 pandemic, the inequalities that are already a characteristic trait of the region are likely to deepen further.

The availability and quality of care are directly related to employment levels and working conditions in the paid care sector, where most of the employees are women (ILO, 2018). The supply of public and private affordable, quality services also influences the redistribution of responsibilities from the home to the State and the private sector, which frees up women’s time and contributes to their economic autonomy (ECLAC, 2019b).

The concept of “care economy” thus includes all unpaid work that is performed in households, as well as domestic and care work performed for pay in the labour market (see diagram V.1). Noteworthy in the latter category is the provision of goods and services for households by paid domestic workers, whose employment conditions continue to reflect the undervaluation of care work in the commercial sphere. This term also encompasses care at the most micro level, i.e. the basic work performed in the home that is necessary for the reproduction of the labour force, as well as the market dynamics of care (employment and service delivery), the provision of infrastructure and the formulation of public policy.

Diagram V.1

The care economy

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Women’s autonomy in changing economic scenarios, (LC/CRM/14.3), Santiago, 2019.

Care is thus a social function involving recipients and providers that should be regarded as a right: the right to take care of someone, to be taken care of, to not take care of someone and to take care of oneself. A person who provides care takes on certain responsibilities for that other person and expends various types of physical, mental and emotional effort. The fulfilment of those responsibilities creates an emotional bond between the provider and recipient of care (ECLAC, 2019b).

The term “social organization of care” refers to the way in which society organizes the reproduction of the population or, in other words, the way in which families, the State, the market and community organizations all work to produce and distribute care (Rodríguez, 2015).

This chapter will look at the lessons learned from previous crises and the benefits afforded by approaches that incorporate a gender perspective and place importance on the care economy. It will also show how, even before the COVID-19 pandemic, the rigid sexual division of labour in the region and the lack of comprehensive care policies had major implications in terms of the gaps existing between men and women, between women in different socioeconomic groups and between women living in one area or country and another. This will be followed by a discussion of the effects that the current pandemic is having on the people who perform paid or unpaid care work. The chapter concludes with an exposition on the reasons why the cost of investing in the care economy is lower than the cost of inaction for various groups within society. The pandemic has revealed the enormous cost for the region of its lack of an integrated, high-quality, broad-coverage, defeminized system of care. There is an urgent need to invest in this sector so that the region can cope with the crisis, guarantee the right to care and reactivate its economy in a way that will uphold gender equality and that will further a sustainable development process. In order for the region to accomplish this, it must rethink the current distribution of labour, the use of time by men and women, and the extent to which it is possible for people to generate their own incomes within the framework of the existing social organization of care and the crisis generated by the pandemic, which imposes an excessive burden of care work, especially for women (ECLAC, 2020c).

In terms of the 2030 Agenda for Sustainable Development, investment in the care economy contributes to efforts to put an end to poverty and to implement appropriate social protection systems and measures for all (Sustainable Development Goal 1), ensure healthy lives for all (Sustainable Development Goal 3), achieve gender equality (Sustainable Development Goal 5), promote inclusive and sustainable economic growth (Sustainable Development Goal 8) and reduce inequalities (Sustainable Development Goal 10).

A. The care crisis and care in crises

Recent global crises have demonstrated that that the consequences of economic recessions and of the reorganization of the labour market are different for men than they are for women (ECLAC/ILO, 2010). The impacts of crises are not confined to their direct effects; they are also channelled through the repercussions of the policies that are designed to respond to those crises and to reactivate the economy: policies that, in most cases, are blind to gender inequalities.

1. The care crisis

The term “care crisis” refers to the challenge of working out a way to make social security systems financially sustainable, strengthening public health services and providing care to dependent persons at a time when demographic shifts are altering the distribution of the population in a way that leaves fewer people in a position to provide care. In a number of countries of the region, the exhaustion of the demographic dividend and the ageing of the population are being reflected in an increased demand for care coupled with a reduced supply. As a result of this shortage of potential caregivers, women may be obliged to take on an excessive burden of unpaid work, since women are the ones who have historically been given the responsibility of providing care. This can be seen by tracking the number of hours in the day that women devote to unpaid domestic tasks and caregiving (see figure V.1). The current family-based model of the social organization of care, which has been maintained by women’s performance of unpaid work, is no longer sustainable and yet State and market mechanisms for the assumption of that social responsibility of care are insufficient (ECLAC, 2019b).

Figure V.1

Latin America (7 countries): potential caregivers and the proportion of time spent on unpaid domestic and care work (Sustainable Development Goal indicator 5.4.1), by sex, 2020–2060a b c

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Women’s autonomy in changing economic scenarios, (LC/CRM/14.3), Santiago, 2019.

a Potential caregivers are defined as people between 15 and 64 years of age. The size of this group is calculated as a percentage of the total male or female population, as appropriate.

b Sustainable Development Goal indicator 5.4.1 counts domestic and care work performed in the home, in other houses and in the community and volunteer work, except in the cases of Cuba and Guatemala. The data are national totals for the population aged 15 years and over.

c The Sustainable Development Goal indicator 5.4.1 was calculated for the following years: Chile, 2015; Colombia, 2017; Cuba, 2016; Dominican Republic, 2016; El Salvador, 2017; Guatemala, 2017; and Uruguay, 2016.

Before the COVID-19 pandemic, women in the region spent more than three times as many hours performing unpaid work as men did. The presence of children in the home, especially in poor households, is associated with an excessive burden of caregiving for women that limits their participation in the labour market. As is shown by the data for 10 countries of the region, the main barrier to women’s full participation in the labour market has to do with family responsibilities involving domestic and care work. Approximately 60% of the women in households where children under the age of 15 are present say that they are not participating in the labour market because of their family responsibilities, whereas, in homes where there are no children in this age group, only some 18% of women say the same thing (see figure V.2). As a consequence of the region’s socioeconomic stratification and the scarcity of quality public services, this is a much greater problem in lower-income households. They have a much harder time deciding how to organize caregiving tasks because they cannot afford to purchase goods and services that would lighten their burden of unpaid work (ECLAC, 2019b). One out of every three women between the ages of 20 and 59 in households in the first income quintile is not participating in the labour market because of family responsibilities. In the fifth income quintile, on average, only 5% of the women are in this situation.

Figure V.2

Latin America (10 countries): women between 20 and 59 years of age who are not participating in the labour market for family-related reasons, around 2019

(Percentages)

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

The data suggest that extended absences from the labour market may be associated with a deterioration in a person’s career path or job opportunities and a lower level of present and future earnings. This can be a particularly serious problem for women when they become mothers and when their children are young (known as the “mommy tax”) (Waldfogel, 1997; Sigle-Rushton and Waldfogel, 2007; Crittenden, 2002). The data for Latin America (see figure V.3) show that the presence of children in the home translates into a widening of the gender pay gap. In some countries, this gap is even wider in the presence of children between 0 and 5 years of age.

Figure V.3

Latin America (8 countries): incomes of female and male urban wage earners between 20 and 59 years of age who work 35 hours or more per week, by presence of children in different age groups, latest available year

(Percentages)

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

Note: The age categories are mutually exclusive. If there are children in both age groups (0–5 years and 6–14 years) in a household, it is classified as falling into the category of “At least one child between 0 and 5 years of age”.

Nancy Folbre (1994) has argued that the costs of caregiving have been privatized and shifted onto women while the benefits (earnings) have been socialized, since the whole of society, albeit in a differentiated manner, enjoys the benefits generated by unpaid caregiving. A number of studies have shown that, if the costs of caregiving were to be incorporated into the wage bill, it would increase substantially. Thus, within the region, a link has been established between unpaid work and poorly paid work, and that link is one of the elements that gives rise to, reproduces and deepens gender inequalities in Latin America.

The harmful effects of the crisis in the care sector are not confined to caregivers as such. In addition to women’s loss of capacities that they possess and have acquired, these impacts also extend to the people who are in need of care. In the absence of a response from the public sector that would allow this type of work to be redistributed, the unjust social organization of care combines with and recreates not only inequalities between men and women but also socioeconomic, ethnic, racial, territorial and inter-country inequalities. This occurs because care work is not only distributed unequally but is also a vector of inequality in its own right.

Women in the lowest income quintile devote about 39% more hours per week on unpaid care work than those in the highest income quintile. (ECLAC, 2019a). Because of this socioeconomic stratification of time use, the rights of people to give care and receive care will be at risk unless flexible strategies for the delivery of quality care services are designed.

Care solutions are linked to the availability of time and income. The COVID-19 pandemic has had a strong impact on the delivery of care services and on household incomes and, as a result, families have had to work out new caregiving arrangements. Children who are not going to school because of the virus are exposed to a series of new hazards. They may, for example, be at risk if they accompany their parents to their jobs if those worksites are not child-proof. Older women, particularly grandmothers, are also subject to hazards associated with the need to care for children so that their mothers can continue to work. Before the crisis, mothers had time while their children were in daycare or school. In the space of less than five years, the proportion of older adults who provide care for their spouse or for other family members or friends without pay has increased (Huenchuan, 2018). Older adults play a particularly prominent role in caring for other older persons. In Cuba, for example, caregivers for adults over the age of 85 are usually 60 years or older themselves (64.2%) (Selman-Houssein and others, 2012). In Colombia, the results of the 2015 Health, Well-being and Ageing Survey (SABE) indicate that 83.9% of caregivers for older adults are women and 16.7% of them are aged 60 or over (MINSALUD/Colciencias, 2015). In addition to serving as caregivers, the older adult population is a high-risk group for COVID-19. Having these people provide care to other older adults or children may thus, in turn, increase the demand for care services, thereby placing a greater burden on health-care systems which, as in the case of most of the countries of the region, are already on the verge of collapse.

In designing measures for reopening the economy while taking into consideration gender-related effects and how they intersect with factors relating to different stages in the life cycle, policymakers must make sure to avoid infringing on the rights of caregivers and care recipients. A good example of this approach is provided by Costa Rica, which has decided to keep its care facilities open during the pandemic in order to uphold the right to provide care and the right to receive care of people who have no choice but to seek care services outside the home.

Care-related mobility is another aspect of the social organization of care services where inequality between men and women is a factor. Even before the crisis, the amount of time that men and women had to travel or commute in connection with care services differed (ECLAC, 2017; Rico and Segovia, 2017). During the pandemic, although people have been moving around less than before, the needs of children whose parents do not live together have not, with few exceptions, been taken into consideration in the region. One exception is Argentina, where special travel permits have been issued during the lockdown to mothers, fathers and their children in order to avoid having one or the other parent take on the sole responsibility of caring for their children.[1]

2. Gender biases in reactivation measures

Stimulus packages aimed at mitigating the effects of the crisis by promoting job creation, protecting jobs, providing subsidies to the poorest households and increasing social spending in general do not always have a positive effect in terms of women’s autonomy. A failure to incorporate a gender perspective into response measures can deepen pre-existing gender inequalities. Basing the design of such measures on an analysis of the care economy can help to improve job quality in that sector, promote production in other sectors and support aspirations for a sustainable form of development with equality.

Feminist economics paves the way for the changes needed to forge a new approach to the crisis. This will entail a systematic rethinking of the androcentrically biased assumptions of orthodox neoclassical economic theory (Elson, 1995; Folbre, 1994). Folbre (1994) contends that orthodox economic thought has interfered with the formulation of a persuasive economic analysis of economic development and social reproduction. Gender biases in approaches to dealing with the crisis strongly influence the design of responses and their effects in either reversing or deepening existing inequalities. One way of categorizing these biases is as follows:

(a) Biases about gender roles in the labour market

One of the types of gender biases that influence the design of public policies for coping with economic crises has to do with the idea that women’s paid employment is a secondary contribution to household income. An associated “man as the breadwinner” bias incorporates the assumption that there is a female caregiver. This is manifested in the following ways:

•Priority in job creation policies on traditionally male sectors (construction energy, etc.)

•Conditions attached to cash transfer programmes that implicitly require women to spend time on fulfilling them (ECLAC, 2013)

•Absence of policies for an effective redistribution of care work.

The prevalence of this social imaginary has persisted despite recent sociodemographic changes, the increasing entry of women into the labour market and the importance of women’s contribution to their families’ livelihoods.

Prior to the crisis, women earned less than men, and larger percentages of women than men worked in the informal sector and engaged in care work. Despite the increase in women’s average number of years of schooling and an upswing of 8 percentage points in their participation in the labour market just in the period 1990–2010 (ILO, 2019), the female labour force participation rate was still not even slightly more than two thirds of the male participation rate in 2019. In addition, more women than men engage in part-time, temporary (only certain months out of the year) and own-account work (ILO, 2019).

(b) Gender bias in fiscal adjustments

One of the ways in which States react to a crisis is by making fiscal spending adjustments. These kinds of adjustments are usually conducted in ways that overlook the differences between men and women in terms of their positions as economic agents. For example, fiscal austerity measures may involve funding cuts based on the assumption that the supply of certain goods and services by the public sector can be taken over by the family, and this includes health-related and education services. This has a direct impact on women’s available time (Elson, 2010) and reinforces a rigid sexual division of labour instead of transforming it.

These fiscal adjustment policies may appear to have an overall positive effect but, because they tend to cut back on benefits or services that are more closely related to women’s lives than those of men, they entail inefficiencies and have negative impacts on women’s well-being and autonomy that often go unnoticed.

(c) Gender bias in resource allocation

Reactivation policies have historically prioritized sectors such as mining, construction and natural resource exploitation, which employ a large number of men. The current crisis has some particular features that need to be taken into account in the design of resource allocation policies. Women workers are concentrated in a number of sectors that are being hit hard by the crisis, such as retail trade (21.6%), manufacturing (11.0%), tourism (9.2%) and domestic service (11.1%) (see figure V.4). In all, 56.9% of all employed women are working in sectors where employees run a high risk of losing their jobs.

Figure V.4

Latin America (weighted average for 17 countries): distribution of employed men and women, by sector of economic activity and economic risk, around 2019a b c

(Percentages)

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

a Sectors of economic activity are defined on the basis of the International Standard Industrial Classification of All Economic Activities (ISIC), Rev. 4.

b Economic sectors are categorized by how much risk there is of a reduction in production volumes and in the number and quality of jobs as a result of the measures adopted to curb the spread of the COVID-19 virus. In this classification, the high-risk sectors are wholesale and retail trade; motor vehicle (including motorcycles) repairs; manufacturing; accommodation and meal service; households as employers; real estate; and business and support services. The intermediate-risk category includes transport and storage; information and communications; the arts, entertainment and recreation; mining and quarrying; finance and insurance; other services; construction; and agriculture, forestry and fisheries. The low-risk sectors are health and social services; teaching; professional, scientific and technical activities; public administration and defence; sanitation; and offshore organizations and bodies.

c The data are from 2019 for Argentina, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Panama, Peru and Uruguay; 2018 for Mexico and the Plurinational State of Bolivia; 2017 for Chile; and 2014 for the Bolivarian Republic of Venezuela, Guatemala and Nicaragua.

The COVID-19 pandemic is exacerbating gender inequalities in the labour market. Projections prepared by the Economic Commission for Latin America and the Caribbean (ECLAC) indicate that, as a consequence of the pandemic, the regional female unemployment rate may have risen to around 15.2% and the male rate to 12.3% at the close of 2020, compared to the 2019 rates of 9.6% and 7.1%, respectively (ECLAC, 2020a). The Commission also projects that the number of women living in poverty will have climbed to 118 million by end-2020.[2]

Another factor that influences resource allocation has to do with the way in which the care economy is analysed and how it is incorporated into national budgets. When budgets are being drawn up, care services are usually included under social spending. Recent studies (Braunstein, van Staveren and Tavani, cited in ECLAC, 2019b; ILO, 2018) have found, however, that the resources allocated to the care economy are more accurately described as an investment and that they have positive spillovers for the rest of the economy. It has been determined that resources invested in the implementation of care-related policies boost job creation in sectors where women workers have traditionally been concentrated. This, in turn, leads to improvements in the number and quality of jobs and in pay levels for the persons employed in these sectors. The resulting increase in income augments households’ consumption capacity, thereby spurring economic activity and allowing part of that investment to return to the government in the form of tax payments (see diagram V.2).

Diagram V.2

Virtuous circle of investment in the care economy

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

(d) Gender bias in the financial sector

Expanded access for households and businesses to the financial sector is a powerful tool for reactivating the economy. It is important, however, to take account of the existing gender gaps in the area of finance in order to ensure that these kinds of initiatives will benefit both men and women. Access for women, both as private individuals and as entrepreneurs, is essential. Measures taken should be free of stereotypes concerning credit risk ratings, credit history and co-signer and collateral requirements.

Various studies have found that women have less access to financial products and services, are granted smaller amounts when the apply for loans and other financial products and pay higher interest rates even though they are more reliable in repaying their loans than men are (ECLAC, 2019b; Hess, 2020). The most recent data compilations[3] point to a gender gap in both the number of loans and the total amount of credit that are granted. In Chile, for example, data gathered in December 2018 indicate that the female debtor base is just two percentage points smaller than the male debtor base, but, also in 2018, the differential in this metric was 22 percentage points in Costa Rica and 28 percentage points in Guatemala. Yet the total amount of credit outstanding for women borrowers was 40 percentage points less for women than for men in Chile, 32.9 points lower in Costa Rica and 44 percentage points lower in Guatemala. Not only is the total amount of credit granted to women less than it is for men, but women also have a significantly smaller amount of debt, on average, than men. Data for Guatemala also reveal differences in lending terms and conditions for men and women. The average interest rate for credit operations signed by women was 20.8% whereas it was 19.2% for men (SIB, 2018), and these figures are comparable to the findings for Chile and Costa Rica.

B. Care work in times of COVID-19

The current health crisis is providing further evidence of the unjust nature of the social organization of care in Latin America and the Caribbean. There is a pressing need to search for approaches for providing care that incorporate a gender perspective. As ECLAC has demonstrated on numerous occasions, women are the ones who shoulder most of the burden in providing paid and unpaid care (ECLAC, 2019b).

1. The impacts of the pandemic on care in the home

Lockdowns and social distancing measures have had a particularly marked impact on gender dynamics by sharply increasing the workload for caregivers in the home. Inequalities between men and women have thus been exacerbated. New inequalities have been created and existing ones have been recreated within the framework of the social organization of care. The home has borne the brunt of the demand for education and recreation, the need to provide health care to persons who are ill and the need for people to hold on to their jobs at a time when unemployment levels are climbing and huge contingents of the labour force are being thrown out of work.

The time that adults must spend on supervision in the home is a clear-cut example of the excessive workload borne by caregivers. For the most part, women are the ones who take on the responsibility of meeting their children’s educational needs. Not only do they need to ensure that their children do their schoolwork; they also are called upon to help them learn how to use the relevant digital platforms. Inequality in the amount of time spent helping children with their schoolwork has been heightened during the pandemic. In Uruguay, for example, the bulk of the demand associated with schoolwork in the home has been met by children’s mothers. In an opinion poll conducted in that country in April 2020, 73% of the respondents thought that mothers are the ones who usually help children with their schoolwork, while only 10% said that fathers play the leading role in that regard (UN-Women/UNICEF, 2020). In Chile, information gathered in July and August 2020 indicates that, on average, women have been devoting 5.4 hours per week to helping their children with their schoolwork during the pandemic, while men have been spending 2.4 hours per week on this task, and 71% of the men in households with children under 18 years of age (versus 48% of the women respondents) stated that they had not spent any time helping their children with schoolwork during the reference week (Centro UC Encuestas y Estudios Longitudinales, 2020).

Just obtaining the devices or making the arrangements needed to ensure the availability of an Internet connection —an essential requirement for remote school attendance— can present a formidable challenge. In general, women have been more involved in education and other related tasks. Conditions during the pandemic have been such that more infrastructure is needed in the home and a greater demand is placed on women’s time to ensure that their children and adolescents can continue to pursue their education remotely. Since households in the lower income quintiles are the ones which have less access to such resources and in which women spend more time performing unpaid work, this situation has sharpened existing socioeconomic and gender inequalities (see figure V.5). Only two thirds of the population has an Internet connection in the region, and in urban areas alone, nearly half (46%) of the children between 5 and 12 years of age live in households that do not have Internet access (ECLAC, 2020b). According to information collected by the National Administrative Department of Statistics (DANE) of Colombia in August 2020, children in 4.5% of the country’s households have been unable to continue their education since the schools have been closed because of budget constraints to pay for school (41%), lack of Internet access (23%) or they lack of a device on which to connect up to virtual classes (17%) (DANE, 2020).

Figure V.5

Latin America (5 countries): children in households that lack Internet access, and the amount of time devoted to unpaid work by women aged 15 and over in households with children between the ages of 5 and 12 years, by income quintile, based on information for the most recent year available a

(Percentages and hours per week)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of Household Survey Data Bank (BADEHOG) and Gender Equality Observatory for Latin America and the Caribbean, Repository of information on time use in Latin America and the Caribbean [online] https://oig.cepal.org/en/infographics/repository-information-time-use-latin-america-and-caribbean.

Note: National data except for Argentina, where the information corresponds to 31 urban centres.

a The BADEHOG databases refer to 2018, except in the cases of Chile and Ecuador, where they refer to 2017. The time-use surveys refer to 2017 for Colombia, Costa Rica and El Salvador, to 2014 for Mexico and to 2013 for Argentina.

Box V.1

Data collection on care during the pandemic

Efforts have been made in a number of countries to gather information on how the distribution of caregiving in the household may have shifted as a result of lockdowns and changes in employment status during the pandemic. Argentina, Colombia, Chile, Mexico and Uruguay have all launched major campaigns to collect survey data on pandemic-driven household dynamics relating to caregiving and time use.

In some countries, these types of data have been compiled by the national statistical offices. In Colombia, for example, by the end of 2020, the National Administrative Department of Statistics (DANE), with technical support from the United Nations Children’s Fund (UNICEF), had published the results of six rounds of the Encuesta Pulso Social (“Social Pulse Survey”), which is being conducted to obtain information on the pandemic’s impact on society. DANE also uses its large-scale integrated household survey to track the increase in the number of women working in the home during the pandemic. In addition, in September 2020 it started to utilize its time-use surveys to provide the country with detailed information on how the population is using and distributing its time during the health emergency. In Mexico, the National Institute of Statistics and Geography (INEGI) conducted the COVID-19 and Labour Market Telephone Survey (ECOVID-ML) from April to July 2020 to supplement the information obtained from the Employment Telephone Survey (ETOE) that it carried out at the height of the pandemic. The 2020 ETOE also gathered information on gender-differentiated time use in April, May and June of that year. In Chile, a COVID-19 social survey has been carried out as part of an initiative undertaken by the United Nations Development Programme (UNDP) in conjunction with the National Institute of Statistics (INE) and the Ministry for Social Development and the Family. The results of that survey provide information on how caregiving tasks have been distributed since the outbreak of this health crisis. Finally, the Catholic University Longitudinal Studies and Surveys Centre has conducted a longitudinal study on employment and COVID-19 to collect real-time employment data that include information on participation in domestic and caregiving tasks and on the number of hours per week devoted to such tasks.

In other countries, United Nations funds and programmes have compiled a great deal of information on care and caregiving. In Argentina, UNICEF undertook a rapid assessment of the changes that COVID-19 has brought about in household activities, access to social transfers, household income, domestic violence and other areas. In Uruguay, UN-Women and UNICEF have published the findings of a survey on children, gender and time use which shed light on changes in the country’s households brought about by the social distancing measures put in place by the government, particularly with regard to gender relations and the situation of children and adolescents.

These data point to an increased awareness of the overload of unpaid work that households have been saddled with during the pandemic. In Colombia, the second round of the Encuesta Pulso Social, which was conducted in August and September 2020, showed that 39.6% of the female respondents and 23.5% of the male respondents felt overworked. By December 2020, this feeling had diminished, but the gender gap remained, with 29.6% of the women and 13.8% of the men reporting that they were overworked. According to the information gathered in Argentina between 8 and 15 April 2020, 51% of the female respondents over the age of 18 said that they were more overloaded with domestic tasks than before, with the principal components of that workload being housecleaning (32%), caregiving (28%), food preparation (20%) and helping with schoolwork (22%). In Uruguay, 20% of the female respondents said that they felt “very” or “quite” overworked during the pandemic, whereas only 4% of the male respondents did. In Chile, the COVID-19 social survey conducted in July 2020 indicates that, since the start of the health crisis, domestic and caregiving tasks have been performed mainly by women in the household in 48.2% of the cases, mainly by men in the household in 2.5% of the cases and by both men and women in 49.3% of the cases. It also indicates that the distribution of these tasks is the same as it was before the pandemic in 80.8% of the cases, while it has become less unequal in 13.4% of the cases and more unequal in 5.8%.

The information collected in the countries of the region thus indicates that the number of hours devoted to unpaid work has increased and that housework and caregiving tasks are unequally distributed between men and women, regardless of whether these activities are measured in terms of shares of the work or the number of hours spent on it. In Mexico, data compiled in April 2020 show that women spent 31.9 hours per week and men 11.6 hours per week performing unpaid work, on average, while the figures for the second quarter of 2019 were 30.8 and 9.2 hours per week, respectively. In terms of how unpaid work is shared, the findings for Mexico indicate that 91.9% of the women engaged in housework and caregiving tasks while 78% of the men did. The data compiled on Argentina make it possible to compare the situation before and after the beginning of the pandemic. Those findings show that, before the pandemic, housework was usually performed by women in 68% of the cases and that, during the pandemic, that figure has climbed to 71%.

The survey conducted in Uruguay in April 2020 makes it possible to compare the number of hours per day spent on paid and unpaid work before and after the start of the COVID-19 pandemic and to disaggregate the figures by sex. The number of hours devoted to unpaid work by women rose from 6.9 to 8.1 hours per day (a 16% increase), while the corresponding figures for men climbed from 3.9 to 4.6 hours per day (a 15% increase). Overall workloads fell by 12% for women and by 21% for men, mainly as a result of reductions in paid work hours. In Chile, according to the data supplied by the longitudinal study on employment and COVID-19 carried out in that country, 38% of the male respondents and 14% of the female respondents said that they had not engaged in domestic tasks during the reference week. On average, men spent 8.2 hours per week performing such tasks while women spent 17.8 hours on domestic work during the pandemic, compared to 6.5 and 16.4 hours per week, respectively, prior to the outbreak of the pandemic. In households with children under 14 years of age, 57% of the men reported that they had not spent any time on caregiving tasks during the reference week, compared to 27.6% of the women. Among those who did take care of children under the age of 14 years, women spent an average of 18.9 hours per week while men spent an average of 8.2 (compared to 16.6 and 5.8 hours per week, respectively, prior to the pandemic).

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of National Administrative Department of Statistics (DANE), “Encuesta Pulso Social 2020: resultado segunda ronda (agosto 2020)”, Bogota, September 2020; United Nations Entity for Gender Equality and the Empowerment of Women/United Nations Children’s Fund (UN-Women), Principales resultados de la Encuesta sobre niñez, género y uso del tiempo en el marco de la emergencia sanitaria. Uruguay, Montevideo, 2020; UNICEF, Encuesta de Percepción y Actitudes de la Población. Impacto de la pandemia COVID-19 y las medidas adoptadas por el gobierno sobre la vida cotidiana, May 2020, Buenos Aires; United Nations Development Programme/National Institute of Statistics of Chile/Ministry of Social Development and Family (UNDP/INE/MDSF), “Encuesta Social COVID-19”, 2020 [online] http://observatorio.ministeriodesarrollosocial.gob.cl/encuesta-social-covid19; Centro UC de Encuestas y Estudios Longitudinales, “Estudio Longitudinal Empleo-COVID19: datos de empleo en tiempo real”, 2020 [online] https://www.uc.cl/site/efs/files/11854/presentacion-estudio-longitudinal-empleo-covid19-noviembre2020.pdf; National Institute of Statistics and Geography (INEGI), “Encuesta Telefónica sobre COVID-19 y Mercado Laboral (ECOVID-ML)”, Mexico City, 23 July 2020; “Indicadores estratégicos de ocupación de las mujeres en etapa de COVID-19, e impacto en el trabajo no remunerado”, paper presented in the Twenty-First International Meeting on Gender Statistics, 10 September 2020.

2. Women on the frontlines in the fight against the pandemic

As of 2019, 27.9% of employed women in the region were working in the areas of education, social services and health or in the households as employers sector, all of which are occupations associated with the care economy. These sectors also all have a high percentage of female workers and exhibit marked gender gaps in terms of occupational and wage segmentation (see table V.1). For example, only 2.8% of the women employed in the care economy occupy management positions, versus 4.3% of the men in those occupational categories (ECLAC, 2019b). These sectors include a quite varied mix of occupations, and wage levels within each sector are correspondingly diverse, even when occupations requiring equivalent levels of qualifications and skills are compared with one another. Even bearing this in mind, however, gender pay gaps still exist.[4] This demonstrates how, even when equally qualified, men and women do not have equal opportunities to secure wages that are commensurate with their occupational profiles (ECLAC, 2019b).

Table V.1

Latin America (17 countries): characteristics of the workforce in sectors of the care economy, weighted averages, around 2019 a

(Percentages)

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

a The data are from 2019 for Argentina, Brazil, Costa Rica, Dominican Republic, El Salvador, Ecuador, Honduras, Panama, Peru and Uruguay; from 2018 for Colombia, Mexico and the Plurinational State of Bolivia; from 2017 for Chile; and from 2014 for the Bolivarian Republic of Venezuela, Guatemala and Nicaragua.

b National household surveys provide information on workers’ pension system coverage. The countries that provide data on such coverage are the Dominican Republic, Ecuador, Panama and the Plurinational State of Bolivia.

In the health sector, women are on the frontlines in the fight to prevent the spread of COVID-19 and to care for its victims, as 73.2% of the persons employed in the region’s health sector are women (see table V.1). During this crisis, the workdays of health-care staff have grown longer, and some health workers lack sufficient protective gear, rendering them more likely to catch the virus themselves and causing stress levels to soar. It is difficult for them to reconcile the excessive workload that they face on the job with their need to care for family members, especially given the current restrictions on movement and other measures designed to prevent the virus from spreading. The combination of all these different factors poses a major challenge for workers in this sector, many of whom do not earn enough to be able to outsource the care of family members in need of such services.

As a consequence of the health emergency, in-person classes have been suspended in most schools in an effort to prevent the virus from spreading and mitigate its impact. According to information collected by the United Nations Educational, Scientific and Cultural Organization (UNESCO), as of mid-May 2020, more than 160 million students at all levels of education in Latin America and the Caribbean were not attending school in person. Most of the countries (29 out of 33) have set up various forms of remote learning systems (ECLAC/UNESCO, 2020).

A majority (70.4%) of the jobs in the region’s education sector are held by women (see table V.1). Teachers –a large majority of whom are women– have had to adjust to these new forms of instruction without, in many cases, having received any specialized training beforehand, and many of them lack the skills or resources needed to adapt their teaching routines to the demands of distance learning and the use of online platforms. In addition to their customary tasks, persons employed in the education sector have had to work together to ensure the material safety of their students and the students’ families by distributing food, sanitation products, school supplies and other materials. It is not yet known how much longer the effort to combat the virus will require schools and other educational centres to remain closed. And once it does become possible to resume in-person classes, teachers and other school personnel will have to take on new responsibilities for the care of their students and the prevention of contagion, in addition to hygiene and social distancing protocols, as well as taking the necessary measures to ensure platform complementarity. Strategies therefore need to be devised for supporting the education sector, which has been playing a key role in the response to the COVID-19 pandemic, without overburdening the women employed in this sector or worsening their working conditions.

In the households as employers sector, domestic workers provide a crucial service by caring for children, persons who are ill and other dependents as well as by helping to run the household on a daily basis and contributing to efforts to contain the virus. In Latin America and the Caribbean, around 13 million people were performing paid work in the household sector as of 2019. Of that total, 91.5% are women (many of whom are Afrodescendent, are from indigenous populations or are migrants) and 76% of those women have no social security coverage; in some countries, more than 90% lack such coverage (see table V.1).

The International Labour Organization (ILO) estimates that 70.4% of female domestic workers have been affected by lockdowns, the reduction in economic activity, unemployment, cuts in working hours or the loss of wages (ILO, 2020). Unions of female workers employed in private households in the region have published information that paints a similar picture (UN-Women/ILO/ECLAC, 2020). They contend that contracts have been rescinded without reasonable cause, working conditions have been unilaterally altered, working hours and wages have been cut and some workers have been obliged to remain at their places of work, far from their families and without being allowed to take sufficient time off to rest.

Because of all these factors, many women working in this sector, especially those who do not have a formal employment contract, cannot be certain of how much they will earn. Those who have continued to work have had to take on added responsibilities in connection, for example, with activities related to school closures in homes where children are present. They have also had to intensify their housecleaning tasks to help to prevent contagion and even to provide health care to members of the household where they work, which exposes them to the risk of contagion and requires them to engage in activities for which they have not necessarily been trained (ECLAC, 2020c). Many of these workers have also been dismissed from their jobs. A number of national statistical offices in the region have published data that illustrate the magnitude of this problem. In Brazil, the year-on-year reduction in the number of people employed in the domestic service sector for the April–June quarter of 2020 came to -24.7%. In Chile, the year-on-year decrease in women’s employment in the household sector for May–July was -46.3%, meaning that around 150,000 women lost their jobs. In Colombia, the year-on-year reduction in female employees in the domestic service sector was -44.4% for that same quarter. In Costa Rica, the year-on-year reduction for female workers in this sector in April–June was -45.5%. In Mexico, female employment in the domestic service sector fell by 33.2% in July 2020. Finally, Paraguay reported a 15.5% drop in domestic service employment for the second quarter of 2020 (ECLAC, 2021).

Map V.1

Latin America (6 countries): variation in paid employment in the domestic service sector, latest available period, 2020-2019

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of official sources: Brazilian Institute of Geography and Statistics (IBGE), Pesquisa Nacional por Amostra de Domicílios Contínua, Trimestre Móvel abr-jun 2020/2019, Brasilia; National Institute of Statistics of Chile (INE), “Encuesta Nacional de Empleo Principales resultados trimestre mayo-julio de 2020”, Santiago; National Administrative Department of Statistics (DANE), “Gran Encuesta Integrada de Hogares (GEIH): mercado laboral mayo-julio 2020/ 2019”, Bogota; National Institute of Statistics and Censuses (INEC), “Encuesta Continua de Empleo al segundo trimestre de 2020/2019”, San Jose; National Institute of Statistics and Geography (INEGI), “Encuesta Nacional de Ocupación y Empleo Nueva Edición (ENOEN)”, Mexico City, July 2020; “Encuesta Nacional de Ocupación y Empleo (ENOE)”, Mexico City, July 2019; Paraguayan Department of Statistics, Surveys and Censuses (DGEEC), “Encuesta Permanente de Hogares Continua segundo trimestre 2020/2019”, Asuncion.

Note: For Brazil, Chile and Costa Rica, the data correspond to the variation in employment in the sector of activity identified as the households as employers or domestic service sector. In the cases of Colombia and Paraguay, the information refers to variations in employment in the occupational category for paid domestic work. The statistics for Mexico refer to the distribution of employment per economic unit and cover employment in the household sector, which corresponds to paid domestic service work. The variations in employment shown for Paraguay and Brazil include employment of both men and women.

The boundaries and names shown on this map do not imply official endorsement or acceptance by the United Nations.

Another impact of the COVID-19 pandemic that is reflected in the care economy has to do with the migration status of many women who are employed in domestic service (see box V.2). According to ILO, 51.6% of migrants in Latin America are women, and over one third (35.3%) of the women migrants who engage in paid work are employed in the domestic service sector (ILO, 2016). As a consequence of border closures and the pandemic’s enormous impact on employment in this sector, many migrant women who were working in this sector have lost their source of income (and, in some cases, housing) and are having a great deal of difficulty in returning to their home countries. This is also reducing the income of the households that rely on remittances, notably in the Central American countries, where care services are often paid for with the money sent by migrant women, since these women must delegate the caregiving tasks that they would normally perform in their own homes to other women. This gives rise to what are known as “global care chains”, which are a global and regional phenomenon that reflects the movement of people from poorer areas to cities or countries where income levels are higher. These chains stretch along migration routes within individual countries in the region (from rural to urban areas), between countries of the region (when, for example, Peruvian women migrate to Argentina or Chile, Paraguayan women move to Argentina and Nicaraguan women relocate to Costa Rica) and between the region and other countries such as the United States, Italy and Spain. These workers are generally subject to greater job insecurity and poorer working conditions and are more vulnerable than local workers. Since, in addition to the often unfavourable conditions associated with domestic service work, their status as migrants adds to their vulnerability, they are at greater risk of discrimination and violence (UN-Women/ILO/ECLAC, 2020).

Box V.2

Paid domestic work: the convergence of socioeconomic, ethnic/racial and gender inequalities in the care economy

Paid domestic work continues to be an area in which gender inequalities are perpetuated and intersect with other structural pillars of the social inequality matrix, such as ethnic-racial status, age and area of residence (ECLAC, 2017). The hierarchical system established during the colonial era when the slave trade was at its height has left its mark on the region and continues to be reflected today in the racial and gender-based distribution of paid domestic work and the relationships of domination and inequality associated with it.

It is precisely in this sector where many indigenous women and Afrodescendent women find employment in Latin America and the Caribbean. In Brazil, one out of every five indigenous women is employed as a paid domestic worker, and in Chile, Mexico and Uruguay, nearly 10% of the women in these groups work in the households as employers sector, while over 16% of Afrodescendent women in Brazil and Uruguay are employed as domestic service workers.

Data from household surveys that provide for ethnic/racial self-identification shed light on the overrepresentation of Afrodescendent and indigenous women in paid domestic service –a low-ranking occupational category in social and economic terms that is typically associated with a high level of informality and a lack of social protection. When measured in terms of the percentages of their respective population groups, more Afrodescendent women are employed as domestic workers than non-Afrodescendent and non-indigenous women are in four countries of the region: Brazil and Uruguay, where, in percentage terms, the former group is almost twice as large as the latter group, and Costa Rica and Ecuador. In Panama and Peru, the latter group outnumbers the former group (see figure 1).

In Brazil, Chile, Mexico and Uruguay, the percentage of indigenous women who work in the domestic service sector is larger than the percentage of non-Afrodescendent, non-indigenous women employed in that sector. In Colombia, no significant difference between the two groups is observed, while in Ecuador, Peru and the Plurinational State of Bolivia, the proportion of indigenous women employed in domestic service is smaller than the proportion of non-indigenous, non-Afrodescendent women. Generally speaking, however, even in those cases where indigenous women and Afrodescendent women are not in the majority, domestic service work is nonetheless an occupational category in which a significant percentage of them are employed (see figure 1).

Because so few domestic service employees have social security coverage, they are unlikely to have access to a pension or, consequently, to have a great deal of economic autonomy in their old age. This situation is being exacerbated by the job and wage cuts in the sector being brought about by the COVID-19 pandemic. Because so many of Afrodescendent and indigenous women who work in domestic service do not have unemployment insurance, they are at risk of finding themselves without any income at all or with too small an income to meet their basic needs and those of their families and thus of slipping below the poverty line.

Figure 1

Latin America (9 countries): women aged 15 years and over employed in the paid domestic service sector, by ethno-racial status, around 2018

(Percentages)

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

The COVID-19 pandemic poses a serious threat of increased socioeconomic, ethnic-racial and gender-based inequalities and is having a direct impact on employment in the domestic service sector. This situation underscores the need to develop ways of improving job quality in this sector and ensuring the observance of decent work standards.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of “Situación de las personas afrodescendientes en América Latina y desafíos de políticas para la garantía de sus derechos”, Project Documents (LC/TS.2017/121), Santiago, 2017 and “Afrodescendent women in Latin America and the Caribbean: Debts of equality”, Project Documents (LC/TS.2018/33), Santiago, 2018.

C. The benefits of investing in care

The COVID-19 pandemic has made it glaringly clear to the world just how important care services are for sustaining life and maintaining the economy as a whole. In social terms, the pandemic has also made it clear how caregiving tasks reproduce existing inequalities and has made people aware of what a significant role they play in responding to the crisis and in reviving economic and other forms of activity. The potential benefits of recognizing and appreciating the value of care work and of redistributing that workload may well outweigh the costs of failing to incorporate it into crisis response measures.

One of the various arguments for making sure that public policy decisions place priority on care work has to do with its monetary benefits for the economy. A number of different studies have gauged the economic contribution that households make to GDP and have highlighted the macroeconomic benefits of investing in the care economy. Such investments boost job creation and tax revenues, drive the economy and help to reduce inequality. Examples of some of the research findings in this connection are discussed below.

1. The contribution of unpaid domestic work to GDP

Historically, unpaid caregiving has not been considered to be work in the sense that it has not been categorized as an economic activity. Thanks to the work done in the field of feminist economics, however, in recent years a number of national accounting and statistical tools have been developed that can be used to update these systems. It has become possible to include unpaid care work in accounting systems, thereby broadening the concept of work, and to rethink the concept of the production frontier, which cannot be properly understood without including the dimension of the reproduction of the workforce (Commission of the European Communities and others, 1993).5 6

Recent changes in this area have made it possible to reach agreements such as those reflected in the Regional Gender Agenda and the 2030 Agenda for Sustainable Development. These agreements establish the importance of recognizing and valuing unpaid work and of developing instruments for measuring time use by men and women. Progress has been made in the past few decades in devising accounting methodologies for recording the value added by care work, and these instruments have been used to calculate the value contributed to GDP by this type of work. However, these conceptual and methodological advances notwithstanding, in many cases people who work in these areas are still being classified as economically inactive. Feminist economic thought has played a fundamental role in reframing the very concept of the economy and in questioning the underlying concept on which the measurement of GDP is based, i.e. the idea that anything that does not have a monetary manifestation in the form of a price does not generate value. It has thus established that work (which in this case is not remunerated and is performed primarily by women) does indeed create value even though no price is assigned to it and it is not accorded social or statistical recognition.

The economic value of unpaid work performed in the households of the countries of the region has been calculated at between 15.9% and 25.3% of GDP (see table V.2). Women generate nearly 75% of that amount.

Table V.2

Latin America (10 countries): economic value of unpaid work performed in the home, 2010–2018

(Percentages of GDP)

Country

Year

Total

Argentinaa

2013

15.9

Chileb

2015

21.8

Colombia

2017

20.0

Costa Rica

2017

25.3

Ecuador

2017

19.1

El Salvador

2010

21.3

Guatemala

2014

18.8

Mexico

2018

23.5

Peru

2010

20.4

Uruguayc

2013

22.9

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of valuation of unpaid work calculated by the lead agencies for the preparation of annual accounts in each country.

a National Office of Economy, Equality and Gender of the Ministry of Economic Affairs, Los cuidados, un sector económico estratégico. Medición del aporte del trabajo doméstico y de cuidados no remunerado al producto interno bruto, Buenos Aires, 2020.

b Unofficial estimate cited in “ComunidadMujer, ¿Cuánto aportamos al PIB? Primer Estudio Nacional de Valoración Económica del Trabajo Doméstico y de Cuidado No Remunerado en Chile”, Santiago, 2019.

c Unofficial estimate computed by S. Salvador, “La valoración económica del trabajo no remunerado”, Los tiempos del bienestar social: género, trabajo no remunerado y cuidados en Uruguay, K. Batthyány, Montevideo, Instituto Nacional de las Mujeres (INMUJERES)/Ministry of Social Development/ Doble clic Editoras, 2015.

2. Job creation and the revitalization of the economy

The creation of jobs to meet the demand for childcare and early education can be seen as another powerful tool for rolling back the crisis through investment in the care economy. Job creation also boosts aggregate demand, which in turn drives the economy.

De Henau, Himmelweit and Perrons (2017) calculate that, if emerging economies were to invest at least 2% of GDP in the health and care sector, overall employment would rise by between 1.2% and 3.2%. An investment of that size would, for example, translate into 4.2 million jobs in Brazil and 63,000 jobs in Costa Rica. In addition, investment in job creation in urban areas will, in the medium term, pay for itself, since a portion of investment in the care economy will be recaptured in the form of tax revenues.

A study carried out by UN-Women and ECLAC in 2020 has posited that the establishment of a universal, free, high-quality childcare system for boys and girls under 6 years of age in Mexico would have an annual cost, on average, of 1.16% of GDP as of 2019 over a five-year period. An additional expenditure equivalent to 1.16% of GDP on the childcare system would translate into an average annual increase of 1.77% in the total gross value of output and a 3.9% jump in total employment relative to the size of the working population as of 2019. Given current investment levels in Mexico and the tax revenues that would be generated by the expansion of coverage, the shortfall would amount to 0.58% of GDP (UN-Women/ECLAC, 2020).

Gender-based employment gaps introduce inefficiencies that interfere with the economy’s growth potential. As discussed previously, the excessive burden of unpaid work shouldered by many women hinders them from becoming full-fledged participants in the labour market. Freeing up women’s time and ensuring their economic autonomy will generate positive externalities in the rest of the economy. In 2015, the McKinsey Global Institute (2015) estimated that the region’s GDP could increase by nearly 34% if, by 2025, men and women had the same labour force participation rates, worked the same number of hours and had the same level of productivity. Evidence leading to a similar conclusion has been offered in an econometric study on Chile. Berlien and others (2016) estimate that closing gender gaps in labour force participation rates would boost GDP by between 6% and 9%. For its part, ECLAC has estimated (2018b) that, if the female labour force participation rate were to climb by 1% per year from now until 2030, its contribution to growth could amount to as much as 2.14 percentage points of GDP in that year.

3. A reduction in inequality and poverty

Gender gaps produce and reproduce poverty and inequality. Braunstein, Bouhia and Seguino (2020) argue that closing the gaps between the male and female labour force participation rates could help to reduce poverty and inequality significantly. If women had the same participation rates as men, poverty in 18 Latin American countries could be lowered by between 1 and 12 percentage points and inequality (as measured by the Gini coefficient) could be reduced by between 1 and 4 percentage points. Meanwhile, closing the gender-based income gap would result in a reduction of poverty of between 1 and 14 percentage points and a reduction in the Gini coefficient of between 2 and 8 percentage points (ECLAC, 2014).

These lines of reasoning and estimates show how inefficient it would be for public policymakers to overlook rights-based aspects relating to care and the care economy. It thus seems evident that, in order to overcome existing inequalities and reduce poverty, a new social and gender compact is needed.

4. The care economy as an agent of reactivation

The inclusion of the care economy in crisis mitigation and reactivation plans will contribute to the growth of the economy and help to prevent the ground that has been gained in terms of women’s rights and gender equality from being lost.

In the public policy domain, mechanisms must be deployed to establish the right to provide and receive care while taking into account the higher interest of children, older adults’ right to a life of dignity and the right of persons with disabilities to live independently. This entails the following challenges:

•The defeminization of care: gender roles needed to be deconstructed, making caregiving a choice, and social protection systems need to include unpaid caregivers.

•Democratization: steps need to be taken to foster co-responsibility, with the provision of care being shared by the State, the market, the community and the family, and to promote a balance between men and women in the home.

•Decommercialization: the care experience needs to be decommercialized by moving away from the idea that access is restricted to those who have the ability to pay for it. Providing access to quality care offers a way of reducing social inequalities by upholding the rights of those who require care and those who provide it.

A public policy response that addresses all of these challenges will serve as an effective tool for consolidating the autonomy of women in the region, protecting the rights of children, older adults and persons with disabilities and bringing about a transformative recovery with equality.

Today there is a more favourable climate than ever for the development of policies for distributing care work more fairly in the countries of the region. In fact, in January 2020 —before anyone knew what was to happen a few months later— the Santiago Commitment was adopted at the fourteenth session of the Regional Conference on Women in Latin America and the Caribbean.[7] The Commitment makes explicit reference to the care economy and economic crises when it calls upon the member States to:

“Implement gender-sensitive countercyclical policies in order to mitigate the impact of economic crises and recessions on women’s lives and promote regulatory frameworks and policies to galvanize the economy in key sectors, including the care economy” (ECLAC, 2020c, para. 24).

The member States also agreed to:

“Design comprehensive care systems from a gender, intersectional, intercultural and human rights perspective that foster co-responsibility between men and women, the State, the market, families and the community and include joined-up policies on time, resources, benefits and universal, good-quality public services to meet the different care needs of the population, as part of social protection systems” (ECLAC, 2020c, para. 26).

The Santiago Commitment thus serves as a guide for the countries’ policy efforts to spur a sustainable reactivation in which the concept of care plays a pivotal role. On the basis of the guidelines set out in the Commitment, the countries would do well to bear the following areas of effort in mind as they strive to meet these challenges:

•Drawing attention to the multiplier effects of the care economy in terms of women’s participation in the labour market, the well-being of the population, the redistribution of time and income, economic growth and an increase in tax revenues

•Working to reverse the deterioration in job quality in this sector, to improve working conditions and to promote the formalization of caregiving

•Promoting the introduction of new technologies, training and the certification of qualifications in the care sector

•Upholding the right to care of persons who are in need of it throughout the life cycle and the rights of people who provide that care, whether it is paid for or not

•Achieving universal coverage of care services and implementing integrated systems for providing care based on a coordinated policy package covering time considerations, resources, benefits and services relating to the population’s various needs for care

•Incorporating the gender perspective into the design of anti-poverty programmes in order to avoid the use of conditionalities that are excessively time-consuming for women

•Promoting co-responsibility between men and women and among the State, the market and the family and improving the supply of quality care services so that they are accessible to the poorest sectors of the population without requiring reliance on unpaid work by women

•Expanding social protection coverage to include women in jobs where working conditions are substandard, women working in the informal sector, women working in domestic service, women without incomes of their own, women living in poverty and women who have dependents.

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UN-Women/ILO/ECLAC (United Nations Entity for Gender Equality and the Empowerment of Women/International Labour Organization/Economic Commission for Latin America and the Caribbean) (2020), Trabajadoras remuneradas del hogar en América Latina y el Caribe frente a la crisis del COVID-19, Santiago, 12 June.

UN-Women/UNICEF (United Nations Entity for Gender Equality and the Empowerment of Women /United Nations Children’s Fund) (2020), Principales resultados de la Encuesta sobre niñez, género y uso del tiempo en el marco de la emergencia sanitaria. Uruguay, Montevideo.

Waldfogel, J. (1997), “The effect of children on women’s wages”, American Sociological Review, vol. 62, No. 2, Sage Publications.

[1] Resolution 132/2020: In the case of children whose parents do not reside in the same dwelling, an exception is made to the restriction of movement. Priority shall be given to the child’s or children’s presence in the household that constitutes his, her or their principal home. Such children may therefore be relocated, for one time only, to the residence of the other parent, relative or principal caregiver if those persons are not with the child or children at the time that the quarantine order is issued. (see [online]: https://cepalstat-prod.cepal.org/forms/covid-countrysheet/index.html?country=ARG).

[2] This projection does not take into account the effect of emergency cash transfer programmes designed to soften the economic impact of the pandemic.

[3] The data presented in this section are taken from the following sources: the 18th edition of the report Género en el Sistema Financiero, of the Financial Market Commission of Chile, December 2018 (CMF, 2019); the Boletín Trimestral de Inclusión Financiera, No. 20, of the Superintendency of Banks of Guatemala, 30 September 2018 (SIB, 2018); and the Informe de brechas entre hombres y mujeres en el acceso y uso del sistema financiero en Costa Rica, prepared by the National Women’s Institute, the General Superintendency of Financial Institutions and the Development Banking System of Costa Rica, December 2018 (INAMU/SUGEF/SBD, 2019).

[4] For example, certain occupations in the health professions for which licences and specific degrees are required or which have strong unions can restrict the job supply and keep wage levels at a higher level than they might otherwise be (ILO, 2018).

[5] The 1993 revised version of the System of National Accounts (SNA) opened up the possibility of constructing satellite accounts in order to provide a fuller picture of specific areas of economic activity. This expanded the analytical capacity of national accounts without overburdening or disrupting the central system. These satellite accounts make it possible to apply complementary or alternative concepts that help to clarify or more fully describe aspects that are not apparent or that are only partially represented in that central system.

[6] The definition of “work” was broadened in a resolution adopted at the nineteenth International Conference of Labour Statisticians in 2013: “Work comprises any activity performed by persons of any sex and age to produce goods or to provide services for use by others or for own use” (ILO, 2013).

[7] See [online] https://conferenciamujer.cepal.org/14/es/documentos/compromiso-santiago.

Chapter VI

Social unrest: keys for a new social compact

Introduction

A. Social unrest and its dimensions

B. Different expressions of social unrest in societies with high levels of inequality

C. Perceptions of the pandemic’s impact

D. The risks of ignoring citizen unrest

Bibliography

Introduction

Social unrest is a subjective experience that takes multiple forms and is inseparable from the objective and material conditions that characterize people’s daily lives (UNDP, 2012). In the different shapes it can assume, unrest can be a factor for transformation and social progress and can give rise to social movements and demands for change shared by broad sectors of society. However, it can also generate apathy or political disaffection when the underlying discontent is not expressed in a structured way through specific demands. Similarly, the failure of governments and institutions to respond to unrest, or their failure to provide sustainable responses, can generate major tensions, conflict and instability. Addressing the factors that fuel unrest is therefore essential to avoid increasing levels of conflict, outbreaks of violence and crises of representation and democratic legitimacy, all of which hinder economic performance

(ECLAC, 2018).

Because of its structural social and economic problems and as a result of the COVID-19 coronavirus pandemic, the region is experiencing a major decline in its living standards, which can be seen in objective indicators such as increased unemployment, poverty and inequality. These objective indicators have their correlations in subjective expressions of both individual and collective unrest.

Prior to the pandemic, there was already considerable dissatisfaction with the persistent inequality in the distribution of resources and the perception of defencelessness against multiple threats, especially labour and economic risks, oftentimes in contexts of high levels of household indebtedness. There was also dissatisfaction with how politics and politicians function and a growing distrust of institutions and, in extreme cases, of democracy as the best form of government. This translated into demands for greater equality and non-discrimination and, in some cases, into social mobilizations and protests demanding substantive transformations to build fairer and more inclusive societies (see box VI.1). The expansion of middle-income sectors and the consolidation of a more demanding citizenry that is less tolerant of inequalities and corruption and more eager to participate undoubtedly contributed to those processes. The region’s citizens are increasingly questioning the patterns of discrimination and inequality that permeate institutions and social relations and that underpin the culture of privilege of colonial origin that normalizes deep socioeconomic, gender, ethnic, racial and other inequalities (ECLAC, 2018).

Section A of this chapter presents a brief description of the phenomenon of social unrest and the main dimensions through which it can be analysed. Section B examines the expressions of discontent found in the region’s countries in accordance with three dimensions: the socioeconomic structure, the political and institutional dimension, and social relations. Section C deals with perceptions of the impact of the pandemic, with a particular focus on young people and persons with disabilities. Lastly, section D contains a series of conclusions regarding the broad challenges facing the region in promoting a culture of equality, strengthening democratic institutions and the role of a new social State.

Box VI.1

Chile and Ecuador: two major protest movements in 2019 and 2020

During 2019 and 2020, major protest movements took place in several Latin American countries, including Chile and Ecuador. Despite their differences, these protests shared common elements within a context of social unrest and underlying social conflicts. The citizens were expressing discontent arising from the perception that the institutions had failed to channel their demands for greater equality or had failed in representing them properly. Those demands led the governments to design short-term responses to address public unrest, eliminating certain measures or seeking agreements to bring about changes of a more structural nature.

Although the immediate trigger for Chile’s October 2019 protests was an increase in public transport costs, a number of mobilizations seeking to improve the population’s quality of life had taken place since 2006 (Rozas Bugeño and Somma, 2019; Jara, 2019; Red Digital, 2018). The 2019 demonstrations were thus framed by the accumulation of demands with respect to different areas of social life that had been ignored by successive governments (including education, health and pensions) and by negative perceptions of how the institutions had dealt with those demands (Güell, 2019; Luna and Murillo, 2020). According to the results of the 2016–2019 Social Longitudinal Study of Chile (COES, 2020), 2019 saw a marked increase in individual levels of participation in social movements, which rose from 21% in 2017–2018 to 39% in 2018–2019. Those participation rates were associated with feelings of anger at the country’s levels of inequality and living costs. In late 2019, the protests expanded to encompass a series of social demands and culminated in the demand for a new constitution (Yasunaga Kumano, 2020) in the belief that the current one poses an obstacle to the proposed reforms (Heiss, 2020; Castiglioni, 2020). Against that backdrop, the main political forces struck a political agreement to organize a plebiscite on a new constitution, which partially calmed the demonstrations.

In Ecuador, the demonstrations were triggered by discontent arising from the elimination of fuel subsidies, a step taken as part of government measures to reduce the fiscal deficit in order to secure a loan from the International Monetary Fund (IMF) and pay off the country’s external debt (Barría, 2019; Ospina Peralta, 2019). With austerity policies already prompting high levels of public dissatisfaction (El Universo, 2018), the protests were framed by discontent arising from the perception that the government was backtracking on the delivery of social and economic guarantees. After a political agreement was reached to overturn the elimination of the fuel subsidies and to establish mechanisms that would target resources at the neediest sectors, the protests calmed down (Deutsche Welle, 2019). They began anew, however, following the adoption of the Organic Law on Humanitarian Support to Combat the Health Crisis arising from COVID-19, which contained a string of new austerity policies, and following the announcement that eight public companies were to be closed (Quiroz and Alvarado, 2020).

Source: C. Barría, “Crisis en Ecuador: 4 razones que explican la crisis que llevó a Lenín Moreno a decretar el ‘paquetazo’ que desató las protestas”, BBC News Mundo, 9 October 2019 [online] https://www.bbc.com/mundo/noticias-49978717; R. Castiglioni, “La política chilena en tiempos de pandemia”, Nueva Sociedad, No. 287, May–June 2020; Deutsche Welle, “Ecuador: indígenas cesan protestas tras acuerdo con Moreno”, 14 October 2019; Centro de Estudios de Confllicto y Cohesión Social (COES), Radiografía del cambio social: análisis de resultados longitudinales. Estudio Longitudinal Social de Chile, ELSOC 2016-2019, 2020; El Universo, “Ajustes y varios pedidos en política económica de Ecuador provoca manifestaciones”, 30 August 2018 [online] https://www.eluniverso.com/noticias/2018/08/30/nota/6929603/ajuste-varios-pedidos-provocan-manifestaciones; “Gasolina súper se incrementa a $ 2,98, entre nuevas medidas del Gobierno ecuatoriano”, 21 August 2018 [online]

https://www.eluniverso.com/noticias/2018/08/21/nota/6916997/nuevas-medidas-economicas-ecuador; P. Güell, “El estallido social de Chile: piezas para un rompecabezas”, Mensaje, vol. 68, No. 685, December 2019; C. Heiss, ¿Por qué necesitamos una nueva Constitución?, Santiago, Aguilar, 2020; A. Jara, “Cronología: los hitos que han marcado la crisis del Instituto Nacional”, La Tercera, Santiago, 15 October 2019 [online] https://www.latercera.com/nacional/noticia/los-hitos-marcado-la-crisis-del-instituto-nacional/861697/; J. P. Luna and M. V. Murillo, “Chile en perspectiva: descontento social, representación política y COVID-19”, Columbia Global Centers, 24 June 2020 [online] https://ilas.columbia.edu/content/chile-en-perspectiva-descontento-social-representacion-politica-y-covid-19; G. Quiroz and P. Alvarado, “8 empresas públicas tienen las horas contadas, ¿cuáles son y cuánto dejan en pérdidas?”, El Comercio, 19 May 2020; P. Ospina Peralta, “Ecuador contra Lenín Moreno”, Nueva Sociedad, October 2019 [online] https://nuso.org/articulo/ecuador-lenin-moreno/; Red Digital, “Importante movilización nacional: el pueblo volvió a gritar ¡No más AFP!”, 25 October 2018 [online] https://reddigital.cl/2018/10/25/movilizacion-no-mas-afp/; J. Rozas Bugeño and N. Somma, “Determinantes de la protesta juvenil en Chile”, Revista Mexicana de Sociología, vol. 82, No. 3, June 2020; M. Yasunaga Kumano, “La desigualdad y la inestabilidad política en América Latina: las protestas en Ecuador, Chile y Colombia”, Documento de Opinión, No. 22, Spanish Institute for Strategic Studies, March 2020.

A. Social unrest and its dimensions

Social unrest is linked to a negative perception of different dimensions of social life. It can arise from disapproval of various elements of the socioeconomic structure, the political and institutional framework or social relations, and it takes the form of dissatisfaction with the exercise of public power, political representation and the distribution of well-being, distrust towards institutions and individuals, and feelings of insecurity.

Social unrest is a powerful warning signal about the deterioration of the basic conditions that allow life in society and the construction of a common project. It indicates a subjective state shaped by a negative perception or assessment of various dimensions that structure social life. Although the phenomenon is a cause for concern, it also has the potential to bring about transformations, in that the questions it poses can translate into opportunities to implement the changes needed to build a more just, inclusive and cohesive society.

Discussions on social unrest have focused mainly on expressions of distrust in institutions, disapproval of government actions, exasperation with corruption, and political disaffection or apathy (Cantillana Peña and others, 2017; Di Palma, 1970). Other notable manifestations of discontent are the perception that society is not progressing positively, that economic performance is inadequate and that the future is not promising, as well as a lack of trust and increased conflicts within people’s social relations (Elchardus and De Keere, 2013). In our region, one key task is to investigate perceptions of objective gaps and inequalities specific to a society.

In analytical terms, social unrest can be examined through citizens’ negative assessments of their objective conditions in opinion polls with respect to at least three dimensions: (i) the socioeconomic structure, defined as access to and the distribution of resources and assets for sustaining an adequate standard of living and protecting against risks, (ii) the political and institutional dimension, which refers to the way in which political power is distributed and exercised, a society’s capacity for representation and perceptions of how its institutions function, and (iii) interpersonal social relations, defined by the characteristics of interactions between people (see diagram VI.1). The boundaries between the three dimensions of analysis are not absolute and overlapping is possible (e.g. when dissatisfaction with the distribution of well-being feeds into negative assessments of governance).

Diagram VI.1

Analytical dimensions of social unrest

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

One of the most significant aspects of the socioeconomic structure that can generate unrest is injustice and arbitrariness in the different dimensions of inequality (Oxhorn, 2003; Wilkinson and Pickett, 2009; Cantillana Peña and others, 2017; Orchard and Jiménez, 2016). This is expressed not only in widespread dissatisfaction and frustration with the distribution of well-being, access to health, education and social protection, but also —and more profoundly— in the questioning of the patterns of discrimination and inequality that have historically permeated institutions and social relations in the region through the culture of privilege (ECLAC, 2018).

Social unrest may also be related to the political and institutional dimension (Orchard and Jiménez, 2016), arising from dissatisfaction with the exercise of public power and political representation, and frustration with the practical experience of not being represented (Joignant, Morales and Fuentes, 2017). This is expressed through mistrust towards institutions (Tilly, 2008), authority, politics and democratic rule (Torcal and Montero, 2006; Gherghina, 2017), and through disapproval of the public administration or the low levels of credibility afforded it (Cantillana Peña and others, 2017). In particular, disaffection towards the democratic regime and its actors is a potential source of ungovernability and instability, as it delegitimizes the processes of participatory deliberation and decision-making, thus complicating consensus-building around policy alternatives for addressing common challenges.

Finally, social unrest can arise from people’s negative assessments of their interpersonal social relationships, in both the private and public spheres, if they perceive exclusionary and discriminatory attitudes and a lack of equal treatment by individuals or institutions. This discontent can be expressed through an absence —or low levels— of interpersonal trust, through fear of others and through an exaggerated individualism and lack of solidarity that can negatively affect people’s willingness to collaborate and reciprocate, to use and share public spaces and resources (UNDP, 1998) and to express solidarity.

B. Different expressions of social unrest in societies with high levels of inequality

There is a growing discomfort in Latin America with respect to the main dimensions that structure social life. Before the pandemic, the population already felt very vulnerable and dissatisfied with the distribution of resources. Moreover, in 2018, 48.3% of people said that their incomes were insufficient to cover their needs, and household over-indebtedness was on the rise. The population was also expressing increasing dissatisfaction with the functioning of democracy, with 78.8% of people believing that their countries were governed by a few powerful groups for their own benefit. And the backdrop to all this is a context of social relations marked by mistrust and discrimination, where in 2018 barely 14.1% of people reported trusting others.

This section analyses the various ways in which social unrest has manifested itself in recent years in the region’s countries in accordance with the three proposed analytical dimensions: socioeconomic structure, the political and institutional dimension, and social relations.

1. Feelings of vulnerability and concern about well-being

Insufficient incomes, precarious employment conditions, high levels of indebtedness and welfare state shortcomings mean that a significant part of the population is highly vulnerable to critical events, such as the COVID-19 crisis. At the subjective level, these problems fuel not only feelings of helplessness in the face of threats, but also pronounced dissatisfaction with how well-being is distributed. It is therefore essential to analyse perceptions of the current socioeconomic structure and how they relate to growing unrest.

The evolution in the proportion of people who believe their incomes are insufficient to ensure an adequate standard of living broadly follows the region’s poverty trends: that percentage fell during the period of growth, improving labour markets and poverty reduction (from 62% in 2003 to 45% in 2011) and, after a few years of stagnation, it rose again from 2016 onwards (see figure VI.1). The result varies from one country to the next (see figure VI.2) and is subject to abrupt changes in the event of a crisis such as the COVID-19 pandemic[1] Results also vary by population group: in 2018, the percentage of people indicating that their incomes did not allow them to satisfactorily cover their needs was higher among women (50.8%) than among men (45.6%) and among people with incomplete primary education (64.5%), although notably almost a third of those with complete university educations also reported being in that situation (32.1%). At the same time, income insufficiency was reported by more than half of all indigenous and Afrodescendent people (52% and 51.3%, respectively), with slightly lower results among the non-indigenous and non-Afrodescendent population (45.6%).

Figure VI.1

Latin America (17 countries): people stating that their incomes fail to cover their needs satisfactorily, 1996–2018a b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a People aged 18 and over (16 and over in Brazil) who stated that their incomes were not enough and that they experienced difficulties and great difficulties in response to the question: “Does the salary or wage that you receive and your total family income allow you to satisfactorily cover your needs? In which of these situations do you find yourself?” “Don’t know/No response” answers have been excluded.

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

Figure VI.2

Latin America (18 countries): people stating that their incomes fail to cover their needs satisfactorily, 2013 and 2018a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a People aged 18 and over (16 and over in Brazil) who stated that their incomes were not enough and that they experienced difficulties and great difficulties in response to the question: “Does the salary or wage that you receive and your total family income allow you to satisfactorily cover your needs? In which of these situations do you find yourself?” “Don’t know/No response” answers have been excluded.

b Simple average.

With regard to social protection, 34.3% of people aged 16 and over surveyed in seven Latin American countries in 2018 said that were they to require public benefits, receiving them would not be easy[2] With regard to health, around 2018–2019, 30.1% of people surveyed in ten countries indicated that during the past 12 months they or their families had been in a situation in which they had been unable to access needed medicines or medical treatment.[3] The COVID-19 pandemic can be expected to have exacerbated those experiences, resulting in even greater perceptions of defencelessness.

Similarly, the percentage who think that income distribution is unfair or very unfair has increased steadily since 2013: it rose from 73% that year to 83% in 2018, with which it returned to the levels reported at the beginning of the century (see figure VI.3). This increase coincides with the slowdown in the reduction of income inequality described in chapter I. Perceptions of unfairness in income distribution rose in the vast majority of the countries between 2013 and 2018, reaching over 90% in Argentina, the Bolivarian Republic of Venezuela, Brazil and Chile (see figure VI.4).

Figure VI.3

Latin America (17 countries): people stating that income distribution in their country is unfair or very unfair, 1997–2018a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a Simple average of the following countries: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay. The survey question was: “How fair do you think income distribution is in (country)?” “Don’t know/No response” answers have been excluded. Interviews of people aged 18 and over (16 and over in Brazil).

Figure VI.4

Latin America (18 countries): people stating that income distribution in their country is unfair or very unfair, 2013 and 2018

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a Simple average. The survey question was: “How fair do you think income distribution is in (country)?” “Don’t know/No response” answers have been excluded. Interviews of people aged 18 and over (16 and over in Brazil).

Another relevant topic for exploration is the extent to which the region’s people believe the effort they put into their work is rewarded, in conjunction with present and future expectations of better opportunities. According to data collected between 2018 and 2019, 44% of the people surveyed think hard work correlates more to a better life and success than good luck or connections (20.5%) (see figure VI.5). However, there are only two countries (Ecuador and Peru) where more than half the people think this way. Furthermore, in 2018–2019, 52.2% of the respondents indicated that their standard of living was the same or worse than that of their parents when they were their age, suggesting a rather pessimistic view of their present.[4]

Figure VI.5

Latin America (10 countries): people stating that hard work or good luck and connections are the most important factors behind a better life and success, 2018–2019

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of the World Values Survey (WVS).

a Simple average.

b Includes those responding between 1 and 3 on a scale of 1 to 10, where 1 means total agreement with the option “In the long run, hard work usually brings a better life” and 10 means total agreement with the option “Hard work doesn’t generally bring success —it’s more a matter of luck and connections”. “Don’t know/No response” answers have been excluded. Interviews of people aged 18 and over.

c Includes those responding between 8 and 10 on a scale of 1 to 10, where 1 means total agreement with the option “In the long run, hard work usually brings a better life” and 10 means total agreement with the option “Hard work doesn’t generally bring success —it’s more a matter of luck and connections”. “Don’t know/No response” answers have been excluded. Interviews of people aged 18 and over.

2. Household indebtedness as a factor in uncertainty, vulnerability and discontent

Household indebtedness is a reality where the objective and subjective dimensions of unrest converge. Although according to the theories of intertemporal consumption (Friedman, 1957; Modigliani, 1986; Hall, 1978), it is rational, expected and beneficial for people to smooth out their levels of consumption by taking on debt at the beginning of their active lives, saving later and divesting themselves of those savings at the end of their lives, new theories and empirical evidence indicate that household debt decisions are complex and not so rational (Blundel, Browning and Meghir, 1994). Regardless of the different reasons for which households may take on debt (increased consumption, acquisition of durable goods or property, financing a business venture or paying for education or health services), the burden of debt repayment —especially in times of economic crisis— can become unsustainable, lead to over-indebtedness and generate a greater sense of insecurity that has a negative impact on the quality of life (Stiglitz, Sen and Fitoussi, 2009).

The available macro-level data for Latin America show a sustained increase in the level of household indebtedness over the past 15 years (see figure VI.6).[5] Brazil, Chile and Colombia report notable increases in indebtedness as a percentage of disposable household income, while in Mexico the trend is also increasing, but less pronounced. By way of comparison, figure VI.6 also shows that household debt levels in Germany and the eurozone countries are higher but have remained more stable over time.

The aggregate levels of household debt indicated by analyses of national accounts conceal the disparities that exist between different population segments. An analysis of household financial surveys in Chile and Colombia reveals those differences.[6] In Chile, 68% of households had some level of debt in 2017, while the corresponding figure for Colombia in 2018 was 39%[7] In both cases, indebtedness can be seen to increase according to income quintile (see figure VI.7), while the financial burden is inverted, to weigh most heavily on the lowest income quintiles (see figure VI.8). The type of debt contracted is mainly consumer debt: 56% of Chilean households have some type of consumer debt and 22% owe money on mortgages, while the corresponding figures for Colombian households are 37% and 6% (see figure VI.7).[8] Likewise, it is estimated that 11.9% of households in Chile and 12.2% in Colombia are over-indebted, which means that their current and expected incomes are insufficient to meet their financial obligations without compromising their standards of living.[9] In Chile, 8% of households take on debt to cover other debts (Madeira, 2015), which represents an additional source of vulnerability, especially at a time of falling employment and incomes.

Figure VI.7

Chile and Colombia: debt holdings by quintile and debt type

(Percentage of households)

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

Figure VI.8

Chile and Colombia: financial burden of debt by quintile, 2017 and 2018

(Percentage of household income)

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

Households’ perceptions of their level of indebtedness must also be taken into account, as they provide information on the degree of stress and discomfort caused by high levels of debt (European Commission, 2008). In Chile, 35% of households perceive their indebtedness to be high or excessive. This perception is higher in the first quintile, where 44% of households see their level of indebtedness as excessive or high, while in households in quintiles 4 and 5 such feelings drop to 31% and 33%, respectively (see figure VI.9).

Figure VI.9

Chile: perception of indebtedness by quintile, 2017a

(Percentage of households)

Source: conomic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of the Household Financial Survey (EFH) of Chile.

a Indicating answers to question G1: “Taking all of your household’s debts into account, how would you assess your household’s level of debt?”

3. Manifestations of discontent with institutions and democracy

Another source of social unrest is dissatisfaction with the public sphere: in other words, with the exercise of public power (how governance is carried out), political representation (how citizens’ demands and expectations are processed) and, in general, institutional functioning (how the State fulfils its responsibilities). Discontent in the political and institutional dimension has numerous interconnections with the socioeconomic sphere and social relations, and there is, for example, a correspondence between distrust in institutions and the perception of injustice in income distribution (ECLAC, 2013). Likewise, appreciations of democracy are shaped by formal values and principles, but also by people’s material situation within the social order and by present and future expectations regarding their situation.

In a region where the State has limited capacities to discharge such fundamental tasks as ensuring the legitimate monopoly of violence in the national territory and making institutions function effectively in accordance with the formal norms of the rule of law, the possibility for discontent is enormous. This is compounded by dissatisfaction with the functioning and results of democracy, whose main actors —especially political parties— are perceived as focusing on their own interests and not effectively representing the citizenry’s will. The proportion of those stating that government is run for a few powerful groups rose from 60.9% in 2009 to 78.8% in 2018, indicating an increase in the perceived lack of representation and the failure to protect citizens’ interests (see figure VI.10).

Figure VI.10

Latin America (18 countries):a people aged 18 and over who believe that the country is run by a few powerful groups for their own benefit or for the good of all the people, 2009, 2013 and 2018b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a The countries included are 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 The question analysed is: “Generally speaking, would you say that (country) is governed for a few powerful groups in their own interest? Or is it governed for the good of all?”

These critical perceptions do not necessarily imply a delegitimization of democracy per se; rather, they highlight a great deal of dissatisfaction with how it functions, in a context in which the majority of the region’s population still considers democracy to be the best form of government. The evolution of that preference is worrying, however, as it fell in all the countries between 2013 and 2018, with the regional average dropping from 79% to 64% (see figure VI.11). In 2018, in only six countries (Argentina, Bolivarian Republic of Venezuela, Chile, Costa Rica, Paraguay and Uruguay) did 70% or more of people consider democracy to be the best form of government. The decline in this indicator is a generalized phenomenon in the countries, regardless of gender, age, ethnicity, race or academic achievement. Noteworthy, however, is the fact that among respondents with incomplete primary education, support for democracy is 18 percentage points lower than among those who have completed university or further studies (see figure VI.12).

Figure VI.11

Latin America (18 countries):a people who agree or strongly agree that democracy has problems but is the best system of government, 2009, 2013 and 2018b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a The question analysed is: “Democracy may have problems, but it is the best system of government.”

b Simple average.

Figure VI.12

Latin America (18 countries):a people who strongly agree or agree that democracy has problems but is the best system of government, by gender, age, ethnicity, race and education, 2009, 2013 and 2018b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a The countries included are 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 The question analysed is: “Democracy may have problems, but it is the best system of government.”

At the same time, an examination of attitudes towards corruption reveals signs of widespread discontent. In all the countries, most people think that corruption among public officials is somewhat widespread or very widespread. During the most recent elections, 35% of people said they saw candidates or party personnel distributing gifts or favours, and 43% believe that corruption has increased in the past 12 months. At least some degree of tolerance for corruption exists, however, since 40% of respondents agreed or strongly agreed with the claim that a certain degree of corruption is a price that can be paid as long as the country’s problems are solved. Figure VI.13 also shows that the perception of corruption varies little by age, sex, ethnic or racial origin and level of schooling.

Figure VI.13

Latin America (18 countries): perceptions related to corruption in the country, 2018a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a The questions analysed are: “During the last electoral campaign, did you see candidates or people from the parties giving gifts or doing favours in your neighbourhood?” “In your opinion, over the past year, has the level of corruption in [country] increased a lot (1), increased some (2), stayed the same (3), decreased some (4) or decreased a lot (5)?” “A certain degree of corruption is a price that can be paid as long as the country’s problems are solved.”

Another cause for concern is the high and growing level of distrust that people feel towards various institutions, particularly those more linked to the political sphere such as political parties, legislatures and governments, but also towards the judiciary. Religious institutions are the only institutions that maintain the trust of a majority of citizens, although this has also been decreasing over time (see figure VI.14). To summarize, the indicators analysed show that even though citizens value the importance of democracy as the best form of government, there are strong and growing signs of dissatisfaction with the political and institutional dimension, as well as with the functioning of the State, which could hinder governance and the legitimacy of politics in general.

Figure VI.14

Latin America (18 countries):a trust of persons aged 18 and over in selected institutions, 2009, 2013 and 2018b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a The countries included are 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 The question analysed is: “Please look at this card and tell me how much trust you have in each of the following groups/institutions. Would you say you have a lot (1), some (2), a little (3) or no trust (4) in ... “.

4. Social relations: fear of the other and the experience of discrimination

Social unrest can also arise from negative or unsatisfactory perceptions of interpersonal relationships, a phenomenon that is closely linked to the culture of privilege and its expression in interactions that are often discriminatory. When “the other” —that is, a person who is considered different or alien to one’s own community— is seen as a source of threat, interpersonal trust and a sense of belonging are weakened. This can, first, increase the sense of vulnerability and fear among people, and, second, fuel aggressive, racist, xenophobic or homophobic behaviour, which further deepens the gaps that exist between different population groups. It can also undermine reciprocity and solidarity and lead to the emergence or heightening of unrest and feelings of injustice. The following paragraphs explore a series of indicators that highlight experiences of situations of discrimination and the permanent presence of different manifestations of discontent in the social relations that shape people’s daily lives, in terms of both distrust of others and feelings of insecurity.

One way of examining the satisfaction or dissatisfaction that people experience in their social relationships is through the level of trust they claim to have in others. Interpersonal trust is a fundamental component of building inclusive and cohesive societies, in that it reflects the belief that others —whether familiar or strangers— will behave cooperatively rather than with aggression (UNDP, 1998). Accordingly, the region’s low levels of interpersonal trust are a cause for concern. Over the past two decades, the proportion of people in Latin America who say that most people can be trusted has ranged from 13.8% to 23.1% of the population (see figure VI.15). This widespread distrust indicates a weakness of social unity and of the sense of community belonging, which not only translates into lower levels of cooperation and reciprocity but also means weak or deficient social cohesion. All this results in feelings of discontent.

Figure VI.15

Latin America (18 countries): interpersonal trust, 1996–2018a b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

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

b Averages for the period 1996–2003 (inclusive) do not include the Dominican Republic. The survey question was: “Generally speaking, would you say that you can trust most people, or that you can never be too careful in dealing with others? Most people can be trusted / One can never be too careful when dealing with others.”

This is exacerbated by a high feelings of insecurity, both in the neighbourhoods where people live and in general, which further deepens interpersonal distrust. According to the survey conducted by the Latinobarómetro Corporation in 2018, people identify crime and public safety as the most important problem in the communities and municipalities where they live, outstripping even negative perceptions about the basic services available (Corporación Latinobarómetro, 2018). Similarly, in 2018, nearly 40% of the population said they worried “every day” or “almost every day” about falling victim to violent crime (see figure VI.16). The highest results were reported in Brazil (66.4%), the Bolivarian Republic of Venezuela (52.9%) and Ecuador (48.8%). A lack of trust in others and feelings of insecurity can have a negative impact on the use of public spaces, locations that are considered essential for forging bonds of belonging and community (Kaz´mierczak, 2013). If interactions in those places are not satisfactory or positive in kind or quality, this can deepen a lack of trust in others, increase discontent and weaken social cohesion.

In addition to mistrust and fears about security, another source of discontent in social relations is the perception of unequal treatment, often expressed as experiences of discrimination or exclusion, together with the persistence of negative stereotypes about certain population groups.

Figure VI.16

Latin America (18 countries): frequency of concerns about being a victim of violent crime, 2009, 2013 and 2018a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of surveys conducted by Corporación Latinobarómetro.

a Simple average of the following countries: Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay. The survey question was: “How often are you concerned that you could be a victim of a violent crime? All or almost all the time / Sometimes / Occasionally / Never.”

First, gender stereotypes associated with discriminatory and exclusionary behaviour and attitudes still persist in the region. For example, almost 20% of people agree or strongly agree that men make better business executives than women, a result that breaks down to 24.6% among men and 15.3% among women.[10] Likewise, in 2017, 23.6% of the population stated that they disagreed or strongly disagreed that half of the members of the national legislature had to be women, and 24.5% disagreed with requiring half of judges to be women (Corporación Latinobarómetro, 2017).[11]

In recent years, however, awareness has been growing about the different forms of discrimination that women suffer, whether through workplace discrimination, lack of political participation or persistent sexual harassment and violence against women and girls, including femicide as its most extreme manifestation (see box VI.2). One of the main expressions of that awareness is massive attendance at marches and demonstrations, notably International Women’s Day (8 March) and various specific movements, such as #NiUnaMenos (“Not One Less”). Women’s movements in the region have played a crucial role in giving expression to demands for greater substantive equality through new forms of collective action that seek to influence the public agenda in order to assert women’s rights and bring about a change in power relations (see box VI.3).

Box VI.2

Gender-based violence against women in the time of COVID-19

Gender-based violence against women is a historical problem that has direct consequences for the exercise of women’s rights and their psychosocial and physical development. More than a merely individual phenomenon, it is a social and cultural problem because of its effects on families and communities.

In Latin American and Caribbean countries such as Chile, the Dominican Republic, Ecuador and Mexico, one out of every three women experience physical, psychological, financial or sexual violence from their partners at some point in their lives, a proportion that rises to two thirds if workplace sexual harassment, street harassment, and other forms of violence are also included (INEC, 2019; INEGI, n/d; National Statistics Office, 2019; Undersecretariat for Crime Prevention, 2020). This is further compounded by an estimated 4,000 femicide cases reported to the ECLAC Gender Equality Observatory for Latin America and the Caribbean in 2019. Against that backdrop, violence against women in the current pandemic has become a concern not only for governments, but also for other institutional and social actors, and it has received broad coverage in the media.

Since the onset of the pandemic, the obstacles imposed by infection mitigation measures —such as travel restrictions— have affected the use of face-to-face services for dealing with gender-based violence against women. This was one of the main driving forces behind the use of remote hotlines: already a resource in high demand, emergency hotlines recorded high numbers of calls at a time when the incidence of other crimes was trending downwards in most countries (UNDP/USAID, 2020). The public response to the increased number of complaints was to strengthen the hotlines and adopt various protocols and campaigns —such as the Mascarilla19 (“Facemask19”) initiative in Chile and the Barbijo rojo (“Red Facemask”) campaign in Argentina— to enable cases of violence against women to be detected by public services and pharmacies, two areas that were not previously assigned a specialized role on the issue. Government responses to the increased visibility of violence against women in the media and on social networks were mixed. In Argentina, Colombia, the Dominican Republic, Honduras, Mexico and Honduras, for example, services for women facing violence were declared either wholly or partially essential. Although most countries did not rule gender-based violence against women and girls as grounds for an exception to travel restrictions, some did allow exceptions to the suspension of court hearings so they could continue to respond to urgent complaints involving protective or precautionary measures, especially when children and adolescents were involved.

Some of the region’s countries have released figures from their hotlines (some including calls to police hotlines, prosecutors’ offices and mechanisms for the advancement of women). While calls increased in year-on-year terms in Mexico, Paraguay and Peru, the number of calls fell in other countries, such as Ecuador and the Dominican Republic. Those changes in the figures do not, however, necessarily reflect increases or decreases in the phenomenon: a lower number of calls compared to 2019 should not be interpreted as indicating lower rates of violence, as limitations on the use of hotline resources may increase during periods of confinement.

With regard to femicides, information published by ten of the region’s countries for the period March–June 2020 shows that in eight countries (Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, Honduras, Paraguay and Peru) there was a decrease in the number of reported cases. This correlates to a lower total number of murders of women. The figures for Panama remained stable, while Mexico reported an increase between March and June 2020 compared to the corresponding period in 2019. It should be borne in mind that the 2019 femicide rate rose only in Brazil, Chile, Ecuador and Mexico, while the official records for 11 other countries in the region reported reductions (ECLAC, 2020).

There are factors specific to this pandemic and its negative impacts that could exacerbate violence against women: for example, the economic crisis and loss of employment, confinement (in many cases in small spaces and without the facilities necessary to undertake activities in the same way as prior to the pandemic) and the overload of unpaid care work.

Information on budget resources allocated to measures for addressing gender-based violence against women and girls during this time of crisis is scarce. One aspect that could be analysed is spending on services such as shelters and safe houses, since they offer places of refuge from threats of extreme violence, such as femicide. An analysis is still needed of how confinement, physical distancing and its impact on travel, and the use of public spaces —now less frequented— increase the risks of physical, psychological and sexual violence; in the short and medium terms, in-depth studies of information on sexual violence in public spaces, rapes and disappearances of women will be essential.

Latin America (5 countries): hotline calls involving domestic violence and gender-based violence against women, 2019 and during 2020 confinement, equivalent periods

(Absolute numbers)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), Gender Equality Observatory for Latin America and the Caribbean, on the basis of Executive Secretariat of the National Public Security System, Información sobre violencia contra las mujeres: incidencia delictiva y llamadas de emergencia 9-1-1, Mexico City, 2020; and data from the Secretariat for Human Rights of Ecuador, the Colombian Observatory of Women (OCM), the Ministry of Women of the Dominican Republic and the Ministry of Women of Paraguay

The progress made in recent years in the quality of government information on gender-based violence against women and girls greatly assisted the strategies and interventions adopted during the health emergency. However, progress still needs to be made with quality of records and with ensuring that the analysis of the data supports more efficient public policies to eradicate violence against women and girls, as required by the 2030 Agenda for Sustainable Development.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), “Gender-based violence against women”, COVID-19 Observatory in Latin America and the Caribbean, 2020 [online] https://www.cepal.org/en/topics/covid-19; ECLAC, “In light of women’s greater exposure, ECLAC calls on States to guarantee their rights in the context of the COVID-19 pandemic”, 8 April 2020 [online] https://www.cepal.org/en/pressreleases/light-womens-greater-exposure-eclac-calls-states-guarantee-their-rights-context-covid; National Statistics and Census Institute (INEC) of Ecuador, Encuesta Nacional sobre Relaciones Familiares y Violencia de Género contra las Mujeres (ENVIGMU), Quito, 2019; National Institute of Statistics and Geography (INEGI) of Mexico, “Encuesta Nacional sobre la Dinámica de las Relaciones en los Hogares (ENDIREH) 2016” [online] https://www.inegi.org.mx/programas/endireh/2016/; National Statistics Office of the Dominican Republic, Encuesta Experimental sobre la Situación de las Mujeres (ENESIM-2018), Santo Domingo, 2019; Undersecretariat for Crime Prevention of Chile, IV Encuesta de Violencia contra la Mujer en el Ámbito de Violencia Intrafamiliar y en Otros Espacios (ENVIF-VCM), Santiago, 2020; Office of the United Nations High Commissioner for Human Rights (OHCHR), “COVID-19 guidance”, 13 May 2020 [online] https://www.ohchr.org/Documents/Events/COVID-19_Guidance.pdf; United Nations Development Programme (UNDP)/United States Agency for International Development (USAID), “Analysis of citizen security and response to Covid-19: Central America and the Dominican Republic”, Infosegura, May 2020 [online] https://infosegura.org/wp-content/uploads/2020/05/PPT_Webinars_7_14_21_May-ENG-SLIDES.pdf; Centre of Excellence for Statistical Information on Governance, Victims of Crime, Public Security and Justice, “Monitoreando la violencia contra las mujeres durante el confinamiento por la pandemia del COVID-19”, 2020 [online] https://www.unodc.org/documents/mexicoandcentralamerica/2020/CdE/Monitoreando_la_violencia_contra_las_mujeres_durante_el_confinamiento_por_la_pandemia_del_COVID-19.pdf; United Nations Population Fund (UNFPA), “Impact of the COVID-19 pandemic on family planning and ending gender-based violence, female genital mutilation and child marriage”, 27 April 2020 [online] https://lac.unfpa.org/sites/default/files/pub-pdf/COVID-19_impact_brief_for_UNFPA_24_April_2020_1_0.pdf.

Box VI.3

Women’s mobilizations and gender demands for a more equal, democratic and fair society

The feminist movements of the 21st century are characterized by efforts to transform society in the direction of increased democratization and equality. In their struggle for rights not previously respected, the mobilization of these groups in the region addresses all dimensions of life. They are expressing their demands for equality between men and women through different forms of protest and collective action, bringing together a diversity of women with multiple identities who aim to mainstream the cause of women with those of other movements also struggling for the transformation of power relations. The use of digital platforms and social networks has allowed them to position themselves as a mass movement and, at the same time, to dynamize their mechanisms for internal organization. Communications strategies and political cyberactivism have been crucial tools in raising the profile of their arguments and influencing the public agenda (Accossatto and Sendra, 2018).

The movements emerged in specific places but very quickly expanded and achieved a regional scope, attaining synergies and echoes in most countries. The following paragraphs describe some of the most notable mobilizations of the past five years, which remain current not only on digital platforms, but also within the demands of women’s movements’ demands at the regional and global levels.

#NIUNAMENOS #LASTESIS

#NIUNAMENOS (“Not One Less”) was the slogan of the mass march held on 3 June 2015, when Argentina’s women gathered to demand the State adopt measures to put an end to sexist violence and femicides. The Ni una menos movement represents the crystallization of social discontent in the face of male violence. It achieved mass support and, from the onset, captured the attention of the media; it succeeded in convincing public opinion of the need for action to halt gender violence and its most extreme manifestation, femicide. As a result of the mass mobilizations and the increased public visibility of feminist women in various spheres, broader venues for debate on gender equality were opened up. Women’s organizations were able to forge alliances with other sectors and attain a greater impact, allowing the movement to expand to other countries. In Chile, the Las Tesis feminist collective composed a song decrying sexual violence against women in 2019; its lyrics and choreography quickly went viral and it was taken up by feminist groups in more than 50 countries around the world.

#NUNCAMASSASSINNOSOTRAS

In 2018, female university students in Chile halted classes for weeks to demand a non-sexist education and, in 2019, they launched a broad process of social mobilization that began with marches to commemorate International Women’s Day. The initiative enjoyed mass participation. Similarly, in the context of the social unrest of October 2019 and the process of drafting a new constitution, women’s movements —along with other social organizations— played a key role in critically examining the current model and denouncing State violence and women’s political exclusion. Under the slogan Nunca más sin nosotras (“Never Again Without Us”), they were successful in ensuring that the new constitution will be drafted by a Constituent Convention with gender parity (Arce-Riffo, Garrido and Suárez-Cao, 2019).

#8M #ParoNacionaldeMujeres #UndíasinMujeres

The main theme of the mass marches of the past few years has been violence. However, the demands of the feminist collectives go further than that, and many of the events organized around International Women’s Day are focused on public policies for reproductive health, care work and decent pay for women. Mexico has a long tradition of women mobilizing against violence and impunity. Women’s groups and feminist collectives are enjoying a prominent and growing public presence across the country as they denounce gender violence, the high rate of femicides and the impunity that still surrounds a large number of crimes against women. One example of this was the coordinated action around the slogan El nueve nadie se mueve (“On the Ninth Nobody Moves)” and the Un día sin nosotras (“A Day Without Us”) call for a national strike (9 March 2020), which urged women to ignore their regular activities and stay at home. In Colombia, as in several other countries in the region, mobilizations against gender violence, sexual violence and femicides have been the focus of the activities carried out by the 8M movement. At the end of 2019, the platform of demands of the National Strike (21N) incorporated issues related to women’s rights, gender equality and the fight against violence in politics, largely due to the country’s extensive feminist claims and mobilizations.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of R. Accossatto and M. Sendra, “Movimientos feministas en la era digital: las estrategias comunicacionales del movimiento Ni Una Menos”, Encuentros, No. 8, August-December 2018; J. Arce-Riffo, C. Garrido and J. Suárez-Cao, “Todo sobre el mecanismo paritario que puede transformarnos en ejemplo mundial de inclusión de las mujeres”, Centro de Investigación Periodística (CIPER), 30 December 2019 [online] https://www.ciperchile.cl/2019/12/30/todo-sobre-el-mecanismo-paritario-que-puede-transformarnos-en-ejemplo-mundial-de-inclusion-de-las-mujeres/; and information from Ni Una Menos, CNN Chile, Campaña Nacional por el Derecho al Aborto Legal, Seguro y Gratuito, and Forbes México.

Negative stereotypes can also be observed with respect to other population groups. Although such opinions have decreased over time, in six Latin American countries, more than a fifth of the population would not like to have homosexual people in their neighbourhood (see figure VI.17). At the same time, 6.8% of the population surveyed said that they would be bothered by having neighbours who were of a different race, 7.4% would be bothered if they professed a different religion and 7.2% if they spoke a different language, while 11% of people would be bothered if their neighbours were immigrants or foreign workers. This last percentage has increased significantly over time. Such statements suggest a lack of acceptance and appreciation of diversity, which can reinforce patterns of segregation and discrimination. In particular, the perception of being or having been discriminated against is higher among people of African descent (20.2%) and indigenous origin (23.5%) than among the general population (16.3%) (Corporación Latinobarómetro, 2015).[12]

Figure VI.17

Latin America (6 countries): people saying they would not like to have certain groups as neighbours, 2005–2009, 2010–2014 and 2017–2020a b

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations of the World Values Survey (WVS).

a Simple average of the following countries: Argentina, Brazil, Chile, Colombia, Mexico and Peru. The survey question was: “On this list are various groups of people. Could you please mention any that you would not like to have as neighbours?” Interviews of people aged 18 and over.

b The 2005–2009 average for the question on immigrants or foreign workers and different languages does not include Colombia.

C. Perceptions of the pandemic’s impact

People’s hardships, deprivations and vulnerabilities in all areas have been intensified by the COVID-19 pandemic. In view of this, the partial information available indicates that government responses are seen critically and through the lens of considerable prior distrust. From the worries of young people about their financial situation and their ability to continue their studies, to the desire of people with disabilities to be heard by governments, by way of mental health issues and the increased risk of violence against women, children and adolescents, the COVID-19 pandemic also amplifies the range of urgent issues that need to be addressed by public policies.

The outbreak of the COVID-19 pandemic has triggered a far-reaching crisis and enormous uncertainty. The State has been called upon to play a leading role in dealing with the crisis and, in all countries, governments have had to react urgently and, in general, step up their interventions and resources in various areas of public policy. In addition to the effectiveness of the health, social and economic measures adopted and the volume of fiscal resources mobilized to address the crisis, citizens’ perceptions of government actions also need to be examined. However, only partial data are available on perceptions of government results in the region, as they respond to specific moments in time in the context of a pandemic that has not yet ended.

One first concern has to do with the management of the health crisis itself. In this connection, figure VI.18 shows that at the beginning of the pandemic (April 2020), levels of trust in health authorities were far from uniform. Among those with the lowest levels of trust were countries such as Honduras and the Dominican Republic, which have historically had low levels of confidence in their institutions.

Figure VI.18

Latin America and the Caribbean (10 countries): stated level of confidence in national health authorities’ capacity to deal with the COVID-19 pandemic, April 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of CID Gallup, “Percepción ciudadana: coyuntura COVID-19 (estudio en línea)”, April 2020 [online] https://www.cidgallup.com/uploads/virtual_library/book_files/book_1594246829000.pdf.

a Responses to the question: “How confident are you that the your country’s health authorities will be able to deal with the COVID-19 pandemic?” Online survey of 18,612 people aged 18 and over conducted between 4 and 12 April 2020 in ten countries: Belize Colombia, Costa Rica, Dominican Republic, El Salvador, Guatemala, Honduras, Nicaragua, Panama and Peru.

Perceptions of the performance of the region’s governments during the pandemic vary widely. In terms of how the economic authorities’ handling of the crisis was assessed and how those assessments evolved over time, between April and August 2020, in all the countries —with the exception of Mexico— there was a downward trend in the approval levels reported by opinion leaders, although some countries were notable for their initially high levels of approval (see figure VI.19).

Figure VI.19

Latin America (8 countries): approval of the government’s handling of the COVID-19 crisis, April–August 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of IPSOS, “La crisis del coronavirus: encuesta a líderes de opinión de Latinoamérica”, April 2020 [online] https://www.ipsos.com/sites/default/files/ct/news/documents/2020-04/la_crisis_del_coronavirus_en_america_latina.pdf and “La crisis del coronavirus: encuesta a líderes de opinión de Latinoamérica”, August 2020 [online] https://www.ipsos.com/sites/default/files/ct/news/documents/2020-09/la_crisis_del_coronavirus-_encuesta_a_lideres_de_opinion_de_latinoamerica_0.pdf.

a Respondents who in April and August 2020 answered “I approve of it” to the question: “To what extent do you approve or disapprove of the handling of the COVID-19 health crisis by the governments of each of the following countries?” Universe: 371 opinion leaders and prominent journalists who regularly publish their views in the Latin American media.

1. Young people: concerns, uncertainty and solidarity

In recent times, the region’s young people have been leading social movements to demand greater levels of inclusion in the face of high, persistent and unjust levels of inequality and widespread distrust of public institutions. In the current context, the pandemic poses a serious threat that could lead to setbacks in the inclusion of young people in education, health and decent work.

Given the scarce information available on youth experiences in the context of the pandemic, the inter-agency youth task force for Latin America and the Caribbean of the United Nations Sustainable Development Group (UNDGLS) conducted an online consultation to explore young people’s lives during the COVID-19 crisis.[13] The results reveal that the pandemic experiences of the region’s young people between the ages of 15 and 29 have sparked a series of concerns and uncertainties related to their current and future well-being. For example, more than one out of every four young people expressed concern about their family’s financial situation or their own (see figure VI.20), with higher rates among those in the 25–29 age group and among males. Another central concern, particularly for indigenous adolescents and young people, is their situation in relation to academic continuity, delayed learning and being forced to drop out of school. In addition to concerns about their family’s health, they also feel the stress generated by distance education, lost incomes and the difficulty of finding work in the current context. Across the region, 52% of young people have experienced increased stress and 47% report having moments of anxiety and panic. Because of the stress and anxiety experienced on account of their current or pre-existing situations, 20% of young people aged 15–29 say they would like to receive psychological support from the health services. That figure rises to almost a quarter of young people with disabilities (23.5%) and of young people belonging to the lesbian, gay, bisexual, transgender, intersex and queer (LGBTIQ) population (24.3%). The COVID-19 pandemic is having a strong impact on general mental health —both among youth and in general— through both the burden of infection and the lack of access to necessary treatment (see box VI.4).

Figure VI.20

Latin America and the Caribbean (39 countries and territories): major concerns of young people regarding the future, May–June 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations, “Encuesta de las Naciones Unidas sobre Juventudes de América Latina y el Caribe dentro del Contexto de la Pandemia del COVID-19”, 2021, forthcoming.

a Responses to the question: “What are your biggest concerns for the future?” Includes the following countries and territories: Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, United States Virgin Islands and Uruguay.

Box VI.4

Mental health in times of COVID-19

The World Health Organization (WHO) defines integral health as a state of complete physical, mental and social well-being, and not merely as the absence of disease or infirmity. Before the pandemic, the mental health situation in Latin American and Caribbean countries was not very positive. In 2012, mental and neurological disorders accounted for 22% of the region’s burden of disease —i.e. diseases that impair health— compared to 14% globally. The most common mental disorders in the region are depression (5%) and anxiety disorder (3.4%), followed by recurrent depressive disorder, obsessive-compulsive disorders and so on. Despite that reality, access to mental health care is low. This lack of care is the result of a combination of factors, including a lack of adequate services, an insufficient number of mental health practitioners, low investment in mental health and the social stigma associated with mental disorders.

The main measures adopted during the pandemic to counter the spread of the virus —lockdowns, quarantines and physical distancing— have reduced mobility and increased the isolation of people; despite having positive effects in terms of flattening the contagion curve, this has also had negative consequences related to paid and unpaid work that generate feelings of uncertainty, stress, anxiety, depression and angst.

The impact of the pandemic on mental health is widespread and, in addition to young people, other population groups have also been particularly affected: children and adolescents, older persons, women, health workers, persons with disabilities, refugee and migrant populations and so on. This is in addition to the population living with pre-existing mental illnesses, whose treatments have frequently been affected or, worse, interrupted.

Children and adolescents are exposed to increased levels of stress and anxiety as their routines are disrupted by the closure of schools and childcare centres, and by the reduction or suspension of social relationships with members of their peer groups and, in many cases, families. This sector of the population is also vulnerable to abuse, especially children and adolescents with disabilities, those in overcrowded accommodation and those living and working on the street. Prior to the pandemic, there was an estimated 55% prevalence of physical aggression and a 48% prevalence of psychological aggression among children in Latin America and the Caribbean. At present, because the crisis has exacerbated risk factors and eroded protection mechanisms, the region’s children and adolescents are more exposed than ever to the dangers of serious physical or psychological violence (such as the use of physical and humiliating punishment as a parenting practice), neglect, sexual violence and online violence. Exposure to high levels of stress, social isolation and domestic violence has a negative impact on their development, with significant long-term consequences.

Likewise, since loneliness is a risk factor for physical and mental health, the mental health of older people is also particularly affected by physical distancing measures, which in many countries have been stricter for older people than for other population groups. Since they are less familiar with digital technologies, older people have limited opportunities for social contact at a time of social distancing, which deepens their isolation and has a negative impact on mental health.

Finally, women are also at greater mental health risk, in that the pandemic has placed an even greater burden of unpaid care work on them, exposing them to higher levels of stress and anxiety. A mental health survey in Chile conducted during the quarantine period revealed that women had higher rates of symptoms of health problems than men and that, for example, they had felt more overwhelmed and under stress (46.3% of men compared to 63.3% of women).

In response to that situation, the United Nations has called for guaranteed universal access to mental health by incorporating mental health care as an additional component of the COVID-19 response (e.g. by ensuring the availability of emergency mental health and psychosocial support services, through both community-based actions and interventions that can be delivered online). The organization has also expressed the need to support communities in recovering from COVID-19 by establishing mental health services for the future, which can take the shape of reforms to mental health services to adopt a more community-centred approach rather than one based on psychiatric institutions or hospitals. In addition to this, progress must be made in better monitoring and in improved indicators of the population’s mental health.

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of UC Surveys and Longitudinal Studies Center/Chilean Safety Association (ACHS), “Termómetro de la salud mental en Chile”, 25 August 2020 [online] https://www.uc.cl/site/efs/files/11421/presentacion_termometro_de_la_salud_mental_en_chile_25082020.pdf; Economic Commission for Latin America and the Caribbean (ECLAC), “Latin America and the Caribbean and the COVID-19 pandemic: economic and social effects”, COVID-19 Special Report, No. 1, Santiago, April 2020; Economic Commission for Latin America and the Caribbean (ECLAC)/United Nations Children’s Fund (UNICEF)/Office of the Special Representative of the Secretary-General on Violence against Children (OSRSG-VAC), “Violence against children and adolescents in the time of COVID-19”, ECLAC-UNICEF-Office of the Special Representative of the Secretary-General on Violence against Children COVID-19 Report, Santiago, November 2020; E. Holmes and others, “Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science”, The Lancet Psychiatry, vol. 7, No. 6, 2020; S. Huenchuan, El derecho a la vida y la salud de las personas mayores en el marco de la pandemia por COVID-19 (LC/MEX/TS.2020/9), Mexico City, Economic Commission for Latin America and the Caribbean (ECLAC), 2020; S. Möller, “Intervenciones sociosanitarias y uso de las tecnologías de la industria 4.0 para enfrentar la enfermedad por coronavirus (COVID-19) en América Latina y el Caribe”, Social Policy series, No. 234 (LC/TS.2020/87), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2020; United Nations Sustainable Development Group (UNSDG), “Jóvenes ante COVID-19 en América Latina y el Caribe”, 2020 [online] https://www.cepal.org/sites/default/files/presentations/ppt_dia_internacional_de_la_juventud_2020.pdf; United Nations, Informe de políticas: la COVID-19 y la necesidad de actuar en relación con la salud mental, May 2020 [online] https://www.un.org/sites/un2.un.org/files/policy_brief_-_covid_and_mental_health_spanish.pdf, and Policy Brief: The Impact of COVID-19 on Children, April 2020 [online] https://unsdg.un.org/resources/policy-brief-impact-covid-19-children; United Nations Entity for Gender Equality and the Empowerment of Women (UN-Women)/ Economic Commission for Latin America and the Caribbean (ECLAC), Care in Latin America and the Caribbean during the COVID-19: towards comprehensive systems to strengthen response and recovery, Santiago, August 2020; Organización Internacional del Trabajo (ILO), ILO Monitor: COVID-19 and the world of work, fourth edition, May 2020 [online] https://www.ilo.org/wcmsp5/groups/public/@dgreports/@dcomm/documents/briefingnote/wcms_745963.pdf; L. Rico-Uribe and others, ”Association of loneliness with all-cause mortality: a meta-analysis”, PLoS One, vol. 13, No. 1, January 2018; J. Weller and others, “El impacto de la crisis sanitaria del COVID-19 en los mercados laborales latinoamericanos”, Project Documents (LC/TS.2020/90), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2020.

Young people’s perceptions of their governments’ pandemic responses are mixed: they are fairly evenly divided between the three classifications considered (bad or very bad, fair, and good or very good), with a slight tendency towards positive ratings. Young people in the Caribbean, in particular, offered very positive assessments of their governments’ performance in the face of the pandemic, as did young people of African descent. LGBTIQ youth, however, reported a more negative perception than the average (see figure VI.21).

Figure VI.21Latin America and the Caribbean (39 countries and territories): assessment of the government response to the COVID-19 emergency, May–June 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations, “Encuesta de las Naciones Unidas sobre Juventudes de América Latina y el Caribe dentro del Contexto de la Pandemia del COVID-19”, 2021, forthcoming.

a Responses to the question: “How do you rate your country’s government response to the COVID-19 emergency?” Includes the following countries and territories: Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, United States Virgin Islands and Uruguay.

That notwithstanding, young people are more critical of the government response to specific problems. For example, their assessment of the government response to gender-based violence during the pandemic was negative, especially among young women and LGBTIQ youth: only 6% of young people said that the government response to cases of gender-based violence was good. Similarly, 54% of LGBTIQ youth disapproved of government efforts in this area, as did around 40% of young women, indigenous youth and young people with disabilities (see figures VI.22 and VI.23).

Figure VI.22

Latin America and the Caribbean (39 countries and territories): perceptions of increased gender-based violence during the pandemic, May–June 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations, “Encuesta de las Naciones Unidas sobre Juventudes de América Latina y el Caribe dentro del Contexto de la Pandemia del COVID-19”, 2021, forthcoming.

a Affirmative answers to the question: “Do you think that situations/cases of gender-based violence (against women, girls, LGBTIQ) have increased or decreased?” Includes the following countries and territories: Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, United States Virgin Islands and Uruguay.

Figure VI.23

Latin America and the Caribbean (39 countries and territories): assessment of government responses to cases of gender-based violence, May–June 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations, “Encuesta de las Naciones Unidas sobre Juventudes de América Latina y el Caribe dentro del Contexto de la Pandemia del COVID-19”, 2021, forthcoming.

a Responses to the question: “How has your government responded to cases of gender violence?” Includes the following countries and territories: Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, United States Virgin Islands and Uruguay.

However, young people also perceive that solidarity and empathy increased in these times of crisis, and adolescents expressed this view to a greater extent than average. Nevertheless, almost one out of every four young people with disabilities said that solidarity and empathy had weakened, indicating that they see the situation less optimistically (see figure VI.24).

Figure VI.24

Latin America and the Caribbean (39 countries and territories): perceptions on higher or lower solidarity and empathy during quarantine, May–June 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations, “Encuesta de las Naciones Unidas sobre Juventudes de América Latina y el Caribe dentro del Contexto de la Pandemia del COVID-19”, 2021, forthcoming.

a Responses to the question: “Do you think that solidarity and empathy have increased or decreased during quarantine?” Includes the following countries and territories: Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, United States Virgin Islands and Uruguay.

In keeping with their optimistic view of solidarity and empathy during the crisis, the region’s young people stated they were increasingly and proactively combating the spread of the virus and working to mitigate and address the pandemic’s social and economic impact in their communities. Those efforts mainly took the shape of online volunteering, donations or other contributions to the response actions of civil society organizations. More than a third of young people reported being involved in or leading some form of action in response to COVID-19, with greater rates of participation among young people in the 25–29 age group, young people of African descent and young people living with HIV (see figure VI.25). This showcases the opportunity available for societies to see their adolescents and young people as actors of change and drivers of a new model of sustainable development.

Figure VI.25

Latin America and the Caribbean (39 countries and territories): participation in COVID-19 response actions, May–June 2020a

(Percentages)

Source: Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of United Nations, “Encuesta de las Naciones Unidas sobre Juventudes de América Latina y el Caribe dentro del Contexto de la Pandemia del COVID-19”, 2021, forthcoming.

a Responses to the question: “Have you been involved in or led any COVID-19 response actions?” Includes the following countries and territories: Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, United States Virgin Islands and Uruguay.

2. Persons with disabilities: scant participation in government decisions[14]

The adoption in 2006 of the Convention on the Rights of Persons with Disabilities and its subsequent ratification by all the region’s countries constituted a major step forward in raising the profile of the rights of persons with disabilities. That notwithstanding, this segment of the population has been left behind by development processes, and there is a significant risk that the COVID-19 pandemic will deepen that exclusion. The population with disabilities in Latin America and the Caribbean numbers more than 70 million people, is heterogeneous and faces multiple and simultaneous forms of discrimination by reason of socioeconomic conditions, sex, age, place of residence, ethnic or racial condition, migratory status and other factors.

The scant information available in the current context prevents reliable estimates of how the pandemic has impacted the population with disabilities and the determination of how many persons with disabilities have access to the emergency measures adopted in the areas of health, education, social protection and employment. It is not known, for example, how many students with disabilities have been unable to continue their studies due to a lack of access to electronic devices, how many people with disabilities have lost their jobs during the pandemic, how many families have seen their care and rehabilitation strategies for their members with disabilities interrupted, or how many girls and women with disabilities need protection from gender-based or domestic violence.

Although data-gathering on the effects of the crisis on different populations is still embryonic and insufficient, it is clear that the economic and social impact will hit more vulnerable groups the hardest. It will therefore be difficult to prevent the crisis from having a major impact on persons with disabilities, the vast majority of whom are already in precarious situations and are often dependent on family networks to meet their most basic needs.

To cast some light on the prospects of persons with disabilities against the backdrop of the pandemic, an online survey was conducted among members of social organizations and networks serving that segment of the population between 22 May and 3 June 2020 (ELIOS Questionnaire: People with disabilities and the COVID-19 crisis) to explore their views of the main programmes, barriers to access and mutual support initiatives instituted in the COVID-19 context. The results —assembled from 125 responses returned by representatives of organizations of persons with disabilities from 16 of the region’s countries— reveal that the situation of persons with disabilities during the pandemic is characterized by negative perceptions of the areas of health, education, access to social protection and, particularly, in relation to employment (Meresman and Ullmann, 2020).

In government responses to the pandemic, people with disabilities are generally included on the lists of vulnerable groups, but it is not always possible to detect whether the necessary adaptations and reasonable accommodations have been adopted to ensure that this population can access services, programmes and benefits. At the same time, there are tensions and challenges in relation to the measures taken by governments to address the COVID-19 crisis and the perceptions that civil society and disability organizations have of those measures. For example, even when governments have made significant efforts to include the disabled population, the assessments of the measures taken are predominantly negative and the prospects for the future are perceived pessimistically.

Much of that tension can be explained by the absence of consultation and collaboration between the designers of public policies and the non-governmental organizations that work with disabilities. Thus, 76% of the survey respondents said that their governments had not consulted persons with disabilities or encouraged their participation in the decision-making process for COVID-19 response measures (see figure VI.26).

Figure VI.26

Latin America (16 countries): perceptions of the participation of persons with disabilities in COVID-19 crisis decision-making and response measures, May–June 2020a

(Percentages)

Source: S. Meresman and H. Ullmann, “COVID-19 y las personas con discapacidad en América Latina: mitigar el impacto y proteger derechos para asegurar la inclusión hoy y mañana”, Social Policy series, No. 237 (LC/TS.2020/122), Santiago, Economic Commission for Latin America and the Caribbean (ECLAC), 2020.

a Responses to the question: “Has the government consulted persons with disabilities and/or encouraged their participation in decision-making and response measures in connection with the COVID-19 crisis?” The countries included are Argentina, Brazil, Colombia, Costa Rica, Chile, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, the Plurinational State of Bolivia and Uruguay.

This mismatch between government action and the expectations of organizations and networks that work with persons with disabilities often leads to duplicated efforts and missed opportunities for complementing universal measures with adjustments and support resources that are sensitive to the different and specific needs of persons with disabilities.

The slogan of the disability rights movement —“Nothing about us without us”— expresses the vital importance of participation by persons with disabilities and their organizations in increasing the legitimacy and effectiveness of policies and programmes for promoting their rights. People with disabilities must be considered in the medium- and long-term recovery and reactivation measures to ensure that they are not left (further) behind and that the reconstruction measures are equitable and inclusive.

This crisis provides an opportunity to rethink the interconnection and integration between public policies and the social and community assets that are essential for inclusive development. One first step in this direction would be to establish local consultation and participation mechanisms to allow the knowledge, experience and resources of organizations and networks that work with persons with disabilities to feed into the general measures and strategies adopted in response to COVID-19. This would enable an understanding of this group’s needs and the identification of the support capacities that are essential in overcoming the vertical and welfarist approaches that still persist in connection with disabilities, and it would further promote the human rights approach.

D. The risks of ignoring citizen unrest

Faced with the current scenario, the imperative is to listen to the citizenry and, also, to consider unrest as a positive factor for change and social progress. In particular, progress must be made towards social policies that focus on the enjoyment of rights, equality, recognition and dignified treatment, and towards the construction of social compacts aimed at building fairer, more inclusive and cohesive societies.

The data analysed in this chapter show increased social unrest in the main dimensions examined. This is a powerful wake-up call for a region reeling from the health, social and economic impacts of COVID-19. The increase in poverty and inequality, the high percentage of the population without access to social protection and the high level of indebtedness observed in the countries for which information is available correlate with the pre-pandemic perception of widespread and growing vulnerability and dissatisfaction with the way resources are distributed. In terms of the institutional dimension and democracy, the period between 2009 and 2013 was marked by greater confidence and optimism, while over the last five years that has evolved into greater political polarization and growing disenchantment. There was growing dissatisfaction with the functioning of democracy prior to the pandemic, even though most people still view it as the best form of government. This exists alongside growing levels of expectations and demands from democracy by many citizens who are urging a response to old and new demands for greater well-being and the recognition of rights and equality.

In addition to all this, there is discontent with the way people relate to and treat each other, shaped by mistrust and fear. This suggests how the culture of privilege has permeated social relations through negative, discriminatory and, in some cases, even racist, xenophobic or homophobic interactions that weaken and deteriorate community ties while, at the same time, deepening feelings of injustice and mistrust that are replicated in the socioeconomic structure and in the political and institutional dimension. This combination of factors underscores the urgent need to build a common project and develop a genuine sense of belonging. Despite the complex scenario, there are various hopeful signs and areas of opportunity that need to be highlighted, since unrest is also a positive factor for change and social progress. As stated by Norbert Lechner (2000, p. 5), “malaise can be read as a tacit (non-verbalized) criticism of the state of affairs and, simultaneously, as a search for alternatives”.

The demand for a more egalitarian society with fully guaranteed rights is a positive phenomenon that opens up possibilities for creating new partnerships and broad compacts, with a solid role to be played by the middle classes, popular sectors and the population as a whole in the recognition of their diversity. At the same time, young people are a vital source of change and transformation. Recognizing their wealth, potential and concrete contributions is fundamental to promoting societies oriented towards a new development model and a new regime for social well-being, with social policies focused on the enjoyment of rights, equality, recognition and dignified treatment. Attention must be paid to the citizenry, so their perceptions and evaluations can be heard, as well as their demands. In particular, it is critical that attention be paid to the voice of civil society, since its organizations are often at the forefront of promoting citizen demands and of demanding greater accountability from the State and political actors in general.

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[1] For example, in the COVID-19 Social Survey conducted in Chile by the National Statistics Institute (INE), the Ministry of Social Development and Family and the United Nations Development Programme (UNDP), 49% of the surveyed households perceived that their total incomes were insufficient during the pandemic, compared to only 17% prior to the crisis (UNDP/Ministry of Social Development and Family, 2020).

[2] The survey question used in the AmericasBarometer Latin American Public Opinion Project (LAPOP) was: “I believe it would be easy to receive public benefits provided by the State, if I needed them. To what extent do you agree or disagree with that contention?” The countries surveyed were Argentina, Brazil, Chile, Colombia, Costa Rica, Mexico and Peru.

[3] The data are from wave 7 of the World Values Survey (WVS), with information from 2018 and 2019 for the following countries: Argentina, Brazil, Chile, Colombia, Ecuador, Guatemala, Mexico, Nicaragua, Peru and Plurinational State of Bolivia. For example, the question asked in Chile was: “In the last 12 months, how often have your or your family… Gone without medicine or medical treatment that you needed?” Those who responded “Often” or “Sometimes” are included.

[4] Data from wave 7 of the World Values Survey, with information for Argentina, Brazil, Chile, Colombia, Ecuador, Guatemala, Mexico, Nicaragua, Peru and the Plurinational State of Bolivia.

[5] Abeles, Pérez Caldentey and Valdecantos (2018) assert that the dynamics of growing household debt in Latin America are on account of the expansion strategies of commercial banks and the broader process of financialization of economies.

[6] The Central Bank has been in charge of conducting Chile’s Household Financial Survey (EFH), which studies the financial behaviour of households, since 2007. The survey asks a representative household member about income amounts and sources (employment, pensions, subsidies and rent), debt types and amounts, the financial burden of each debt, household assets and the means of payment used. For this chapter, the 2017 survey was examined, which covers the nation’s urban areas through a total of 4,549 observations representing 4.9 million households. In Colombia, the Household Financial Burden and Financial Education Survey (IEFIC), conducted since 2010 by the National Administrative Statistics Department (DANE), seeks to obtain data on household wealth, indebtedness and financial education. IEFIC is a subsample of the Comprehensive Survey of Households (GEIH), which asks about the financial services that households have or use and is aimed at people over 18 years of age. The IEFIC universe covers the population residing in private households in the urban areas of Bogotá, Medellín and Cali that make use of financial services. This chapter is based on the 2018 survey, which examined a sample of 26,754 households.

[7] According to Balestra and Tonkin (2018), 51% of households in 28 member countries of the Organization for Economic Cooperation and Development (OECD) had some form of debt in 2015. Chile ranked fourth among the OECD countries with the highest debt levels, after Norway (81%), the United States (77%) and Denmark (76%).

[8] As a comparison, on average, 30% of households in OECD countries have consumer debt (Balestra and Tonkin, 2018).

[9] The percentage of over-indebted households is calculated by means of a liquidity indicator: the ratio of debt burden to household income. Above the 50% threshold, households are considered to be over-indebted.

[10] World Values Survey data; simple average of 10 countries: Argentina, Brazil, Chile, Colombia, Ecuador, Guatemala, Mexico, Nicaragua, Peru and Plurinational State of Bolivia.

[11] Simple average of 15 countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Plurinational State of Bolivia and Uruguay.

[12] In connection with this, there are high perceptions of the existence of ethnic or racial conflicts: in 2017, 57.8% of non-Afrodescendent people and 64.4% of people of African descent said that racial conflict in their country was pronounced or very pronounced (ECLAC/UNFPA, 2020).

[13] The United Nations survey on youth and COVID-19 in Latin America and the Caribbean was carried out to obtain evidence on the situation of the region’s adolescents and young people aged 15 to 29 in the context of the pandemic. The survey, which does not have a probability sample design, was conducted online between 4 May and 11 June 2020. Replies were received from adolescents and young people from 39 of the region’s countries, with 7,242 respondents from Latin America and 504 from the Caribbean (United Nations, 2021).

[14] This section is based on ECLAC (2014 and 2020b) and Meresman and Ullmann (2020).

Index

Index

Table of Contents

Maintitle

Copyright

Contents

Introduction

Chapter I

Poverty and inequality: recent trends and expected impacts of the coronavirus disease (COVID-19) pandemic

Chapter II

Labour market: structural gaps during the pandemic

Chapter III

Social protection in response to COVID-19: pre-existing gaps and emerging responses

Chapter IV

Recent social spending trends and commitments in terms of emergency social protection

Chapter V

The care economy: a sector of strategic importance for reactivation with equality

Chapter VI

Social unrest: keys for a new social compact