01 /27 Regional Poverty and Inequality Update Latin America and the Caribbean October 2024 1 Poverty and Equity Global Practice Latin America and the Caribbean Key In 2023, poverty in Latin America and the Caribbean (LAC) dropped to FINDINGS its lowest point thus far this century, with one in four people living below the upper-middle-income-country poverty line of US$6.85/per person per day (2017 PPP). This corresponds to a reduction of 4.7 percentage points (p.p.) in the regional poverty rate between 2021 and 2023. 1 This brief summarizes the main trends related to poverty and inequality in Latin America and the Caribbean (LAC) using the latest round of harmonized household surveys from the Socio-Economic Database for Latin America and the Caribbean (SEDLAC) created by the World Bank and the Centro de Estudios Distributivos, Laborales y Social (CEDLAS). This brief was produced by the Poverty and Equity Global Practice in the Latin America and Caribbean Region of the World Bank. The core team included Karen Barreto Herrera, Luis Eduardo Castellanos Rodriguez, Catalina García García, Camila Monzon, and Diana Sanchez Castro, under the leadership of Hernan Winkler and the guidance of Carlos Rodriguez Castelan. Ana Carolina Leguizamo provided administrative assistance. Contact: lac_stats@worldbank.org. Most of the data featured in this brief can be found at the LAC Equity Lab. 02 /27 Poverty and Equity Global Practice Latin America and the Caribbean Despite this achievement, the pace of poverty reduction, economic growth, and the creation of better jobs has been sluggish since 2016. Positive labor market outcomes drove the reduction in poverty levels in most LAC countries from 2021 to 2023, accounting for almost two thirds of the decline. Public transfers continue to be an important driver of poverty reduction, but their gradual phasing out is affecting the incomes of poorer households in several LAC economies. Modest growth across the region is expected to support a minor decline in poverty reduction in 2024. 03 /27 1. Macroeconomic Trends Gross domestic product (GDP) in LAC grew by 2.1 percent in 2023, 0.6 percentage points (p.p.) below the global level for that year.2 The LAC region is experiencing a period of moderate economic growth, with most countries projecting GDP expansion in the range of 1.5 to 4 percent for 2024.3 However, regional growth (1.9 p.p. for 2024) is expected to be 0.7 p.p. below the world average, although with important differences across countries. Brazil and Mexico are expecting modest growth rates of around 1.7 to 2.8 percent, while smaller economies such as Uruguay and Costa Rica are expected to perform better. The primary drivers of growth include a recovery in tourism, strong remittance flows, and in some cases increased public investment. Inflation is generally moderating across the region, with most countries seeing rates within or approaching their central banks’ target ranges. This has allowed for monetary policy easing in several countries, potentially supporting consumption and investment. Argentina remains an exception, with inflation still high. The current levels of commodity prices are expected to benefit LAC exporters, with stable metal prices and moderate declines in agricultural and energy prices. Despite these positive trends, the region faces substantial challenges. Fiscal pressures remain a concern for many countries. External risks, including potential slowdowns in major trading partners such as the United States and China, volatile commodity prices, and tightening global financial conditions, pose threats to the region’s economic stability. These challenges raise concerns about the evolution of poverty reduction 2 World Bank, 2024. 3 Economic growth figures for LAC come from Fall 2024 Macro and Poverty Outlook (MPO). 04 /27 Poverty and Equity Global Practice Latin America and the Caribbean efforts in LAC, because they are highly dependent on macroeconomic conditions. In fact, the slow pace of poverty reduction in LAC since 2016 has reflected the low levels of economic growth during this period (figure 1). The LAC region has had the world's lowest annualized growth since 2009, at 1.9 percent, significantly below the global figure of 2.7 percent and the rate of other upper-middle-income regions such as East Asia and Pacific (EAP), where growth reached 5.9 percent. Figure 1 Poverty Reduction and GDP Growth in LAC, 2016-24 14.0 12.4 9.0 Percentage change 3.7 4.0 1.9 4.0 2.1 1.2 -1.0 -6.0 -11.0 2016 2017 2018 2019 2020 2021 2022 2023e 2024f GDP - Latin America & Caribbean Poverty reduction - Latin America & Caribbean Sources: Data for the calculation of LAC regional poverty reduction come from 18 countries (LAC-18): Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, and Uruguay. In cases where data were unavailable, values have been estimated using microsimulations and then pooled to create regional estimates. Data for LAC GDP growth come from World Bank Macro-Poverty Outlook (Fall Meetings 2024 edition). e = estimate; f = forecast. Note: “Poverty reduction” is the percentage change in poverty rates multiplied by -1. A positive value indicates a reduction in poverty. 05 /27 2. Poverty The pace of poverty reduction in LAC has been significantly slower than that of more dynamic regions such as EAP. While in 2009 the poverty rate in EAP was almost 30 p.p. higher than in LAC, poverty levels had converged in the two regions by 2023 (figure 2). These differential dynamics between EAP and LAC largely reflect the regions’ very different trajectories in terms of labor productivity growth over the past 15 years. Despite LAC’s sluggish performance, in 2023 the share of people living in poverty in the region reached its lowest point thus far this century at 25 percent.4 Extreme poverty—those living on less than US$2.15/day (2017 PPP)—also declined by 1 p.p. since 2016 in the region, reaching 3.9 p.p. in 2023. According to the Poverty Gap indicator (using the US$6.85/day 2017 PPP line), the region’s poor became less poor between 2016 and 2023.5 For 2023, this index shows that it would cost at least US$99 million (2017 PPP) daily to eradicate poverty in LAC.6 4 Using the US$6.85/day threshold (2017 PPP). 5 The Poverty Gap is the mean shortfall in income or consumption from the poverty line, expressed as a proportion of the poverty line. This measure reflects the depth of poverty as well as its incidence. It shows the minimum cost of eliminating poverty relative to the poverty line, under the very strong assumption that all transfers can be perfectly targeted. 6 The dollar amount is calculated by multiplying 9.7 percent of the US$6.85/day poverty line by the number of people living in poverty in 2023 (149.1 million people). 06 /27 Poverty and Equity Global Practice Latin America and the Caribbean Figure 2 Poverty Rates (US$6.85, 2017 PPP) by World Region, 2009–24 90 87.3 89.4 Sub - Saharan Africa 87.7 87.6 80 Percentage of population 70 67.8 60 59.4 World 50 44.9 44.3 43.6 46.9 45.5 45.2 40 Middle East & North Africa East Asia & Pacific 44.9 30 38.4 27.4 26.1 24.7 Latin America & 20 Caribbean 26.0 25.0 24.7 10 0 2024f 2023e 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Sources: Data for LAC comes from SEDLAC (CEDLAS and the World Bank), available at LAC Equity Lab, and data for the rest of the world come from the World Bank Poverty and Inequality Platform (PIP). Note: The LAC regional aggregate is based on 18 countries (LAC-18) in the region for which SEDLAC microdata were available. In cases where data were unavailable, values have been estimated using microsimulations from 2015 onward and then pooled to create regional estimates. Due to important methodological changes in Mexico’s official household survey in 2016 that created a break in the poverty series, we have created a break in the LAC-18 from 2015 onward. For more information, visit the comparability dashboard. For other regions, the 2023 and 2024 values are those estimated by the nowcasting model implemented by PIP. e = estimate; f = forecast. Vulnerable people—those living on US$6.85 to US$14/day (2017 PPP)—face a high risk of falling into poverty in the event of economic shocks, and their share of the LAC population has remained flat, being about 31.5 percent in 2023. In contrast, the middle class—those living on US$14 to US$81/day (2017 PPP)—steadily increased from 36.0 percent in 2021 to 41.1 percent in 2023, reaching the highest level thus far this century. According to our nowcasting model, poverty in LAC is projected to continue to decrease in 2024 to 24.7 percent, while the share of the middle class is projected to increase to 41.4 percent (figure 3). 07 /27 Poverty and Equity Global Practice Latin America and the Caribbean Figure 3 Poverty, Vulnerable, and Middle Class Trends in LAC-18, 2015–24 45 41.1 39.7 41.4 40 Middle Class $14 - $81 36.0 35 32.4 32.1 Percentage of population Vulnerable $6.85 - $14 31.5 31.3 30 Poverty $6.85 29.7 26.0 25 25.0 24.7 20 15 10 5 0 2023e 2024f 2015 2016 2017 2018 2019 2020 2021 2022 Source: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Available at LAC Equity Lab. Note: The LAC regional aggregate is based on 18 countries (LAC-18) in the region for which SEDLAC microdata were available. In cases where data were unavailable, values have been estimated using microsimulations and then pooled to create regional estimates. e = estimate; f = forecast. These regional figures hide important differences across countries in the region (table 1). Although most LAC countries did see a reduction in poverty between 2021 and 2023, with Brazil and Colombia for example experiencing declines exceeding 3 p.p., Argentina, Bolivia, Chile, and Peru suffered annual increases in their poverty rates in the range of 0.4 to 1.0 p.p. The size of the middle class increased in most LAC countries between 2021 and 2023. The Dominican Republic, Brazil, Colombia, and Costa Rica witnessed significant increases of at least 2 p.p., with the Dominican Republic experiencing the largest growth (4.7 p.p.). In contrast, the size of the middle class in Argentina and Chile fell by about 1.3 p.p. 08 /27 Poverty and Equity Global Practice Latin America and the Caribbean Table 1 Poverty, Vulnerable, and Middle Class Headcount Rates and Annualized Changes, 2021–23 Poverty Vulnerable Middle-class US$6.85 (2017 PPP) US$6.85-$14 (2017 PPP) US$14-$85 (2017 PPP) Country 2021 2023 Change 2021 2023 Change 2021 2023 Change Argentina (urban) 11.4 13.3 1.0 26.5 27.7 0.6 59.6 57.0 -1.3 Bolivia a 15.2 16.0 0.4 31.5 32.2 0.4 52.1 50.6 -0.7 Brazil 28.4 21.8 -3.3 31.0 28.7 -1.1 37.7 45.7 4.0 Chile a 3.5 4.9 0.7 24.2 24.9 0.3 68.0 65.4 -1.3 Colombia 38.8 32.4 -3.2 29.7 30.9 0.6 29.3 34.0 2.3 Costa Rica 14.5 12.7 -0.9 29.5 27.2 -1.2 51.7 55.8 2.1 Dominican Republic 23.2 17.9 -2.7 43.1 38.8 -2.2 33.3 42.7 4.7 Ecuador 31.7 29.6 -1.1 33.9 34.1 0.1 33.3 35.6 1.1 El Salvador 28.4 24.8 -1.8 39.4 39.0 -0.2 31.9 35.7 1.9 Guatemala a 57.0 55.2 -0.9 27.0 27.8 0.4 15.5 16.5 0.5 Honduras a 53.3 51.9 -0.7 27.9 26.9 -0.5 18.6 20.9 1.2 Mexico b,c 21.8 20.8 -1.0 38.6 38.3 -0.3 38.4 39.6 1.1 Nicaragua a 38.6 34.8 -1.9 36.3 36.1 -0.1 24.1 27.9 1.9 Panama 12.9 12.9 0.0 22.5 21.2 -0.6 58.2 59.9 0.9 Paraguay a 20.8 17.6 -1.6 36.3 36.2 0.0 41.6 44.3 1.3 Peru a 33.4 34.2 0.4 39.3 38.3 -0.5 26.9 27.1 0.1 Uruguay c 6.4 6.7 0.2 22.5 22.0 -0.5 67.3 67.7 0.4 Source: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Available at LAC Equity Lab. Note: Argentina has only urban coverage; the values for Argentina, Brazil, Colombia, the Dominican Republic, El Salvador, Honduras, and Uruguay for 2023 are based on preliminary data. a / Indicates that either the 2021 or 2023 data or both are projections using microsimulation methodology. The values for Bolivia, Peru, and Paraguay are for 2023; those for Chile, Guatemala, and Nicaragua gures are for 2021 and 2023; and those for Honduras gures are for 2021. b / Mexico 2023 is a projection using neutral distribution (2022) with pass-through = 0.87, based on GDP per capita in constant local currency unit. c / The 2021 values for Mexico and Uruguay are actual estimates for 2022. 09 /27 3. Poverty by Group The poor in LAC are more likely to be younger, have lower levels of educational attainment, and more likely to live in rural areas than their counterparts in the vulnerable group and the middle class (table 2). While more than half of the poor are 24 years old or younger, fewer than 1 in 3 people in the middle class are in this age group. While 31 percent of people in the middle class are college graduates, only 11 and 5 percent of vulnerable and poor people, respectively, have this level of educational attainment. The vulnerable group has the highest share of people who are high school graduates. Almost 9 out of every 10 people in the middle class live in urban areas, whereas just 63 percent of the poor do so. Finally, poverty is also associated with reduced access to the services that are often key to taking advantage of economic opportunities, such as internet connectivity (box 1). The labor market is a key determinant of the socioeconomic status of people in LAC. Middle-class people are more likely to have formal jobs, be employed in the services sector, and be salaried employees. While 80 percent of workers Figure 1 living in poverty have informal jobs, only 34 percent of their middle-class counterparts do so. The share of agricultural workers is higher among the poor, whereas service-sector workers are overrepresented in the middle class. The share of workers in the industry sector is the highest in the vulnerable group. Finally, the share of salaried workers increases as socioeconomic standing improves. 10/27 Poverty and Equity Global Practice Latin America and the Caribbean Table 2 Socioeconomic Profiles of the Poor, Vulnerable, And Middle Class in LAC, 2023 Poor Vulnerable Middle Class Age Groups 0-14 37.0 25.7 13.8 15-24 17.5 17.8 14.0 25-64 40.4 48.4 57.5 65+ 5.0 8.0 14.7 Total 100 100 100 Education Complete Primary 45.3 36.2 25.7 Complete Secondary 33.3 41.3 36.3 Complete Tertiary 4.7 11.3 31.1 Never Attended 16.7 11.3 6.8 Total 100 100 100 Area Rural 37.2 20.4 11.2 Urban 62.8 79.6 88.8 Total 100 100 100 a Informality Informal Workers b 81.2 58.0 34.0 Formal Workers 18.8 42.0 66.0 Total 100 100 100 a Sector Agriculture 28.4 11.7 5.5 Industry 20.6 24.1 20.8 Services 51.0 64.2 73.7 Total 100 100 100 Type of Employment c Employer 4.5 3.2 4.9 Not Salaried 9.5 3.6 1.7 Salaried Worker 41.3 62.2 69.9 Self-employed 31.3 23.8 20.2 Unemployed 13.4 7.2 3.4 Total 100 100 100 Source: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Note: The LAC aggregate is based on 18 countries in the region for which microdata are available. In cases where data are unavailable for a given country in a given year, values have been interpolated using World Development Indicator data to calculate regional measures and microsimulations. a / Working people are between 15 and 64 years old. b / These are workers who do not have work-related pension insurance. For Argentina, these are salaried workers who do not receive work-related pension insurance and nonsalaried workers without complete tertiary education. For Mexico, these are workers who do not receive work-related health insurance bene ts. For Honduras, these are nonsalaried workers who either have not completed tertiary education or have completed tertiary education but are employed by small private companies and salaried workers either without any education or with some education but employed by small private companies. c / This includes workers and unemployed workers (those who are actively seeking work) between 15 and 64 years old—the labor force. 11/27 Poverty and Equity Global Practice Latin America and the Caribbean Box 1 THE DIGITAL DIVIDE IN LAC Higher levels of internet access among low-income households can assist members in moving out of poverty by, for example, enabling them to take advantage of services and new job opportunities.7 While there are publicly available statistics of internet use at the economy-wide level, no systematic effort to track internet access among the poor across countries in LAC has been made. This box features a subset of harmonized variables tracking the digital economy in SEDLAC.8 There is substantial variation across and within countries in terms of households’ internet connectivity (figure 4). As expected, internet access is the highest in the higher-income countries in the region such as Chile and Costa Rica, where it is at least 90 percent even among the poor. Lower levels of internet access in the rest of the region often reflect large disparities across socioeconomic groups. The digital divide between the poor and non-poor is the highest in Colombia, Mexico, and Peru, where non-poor households are at least 30 p.p. more likely to have an internet connection than poor ones. Internet access among the poor is the lowest in the Dominican Republic and El Salvador, where fewer than 1 out of every 5 households living in poverty have internet access at home. There are multiple factors driving this digital divide across income levels, including affordability, lack of digital infrastructure, and more-general territorial disparities between cities and regions that lag. 7 Bahia et al. 2023, 2024; Barrero, Bloom, and Davis 2021; Viollaz and Winkler 2022. 8 These figures may differ from administrative records since they are self-reported by households. 12 /27 Poverty and Equity Global Practice Latin America and the Caribbean Figure 4 Households In LAC with Internet Connection, Circa 2023 100 Non-poor households Poor households Gap 40 90 35.6 Percentage of households 35 80 32.0 31.5 30 28.5 70 24.5 25 60 22.7 21.0 23.1 20 50 15 40 10.8 10 30 8,9 20 4.5 5 2.7 10 - 0.6 0 0 -5 El Salvador a Honduras a Colombia c Paraguay b Dominican Costa Rica Republic a Uruguay a Panama c b b Mexico Brazil b Bolivia b Peru b Chile Sources: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Note: Households with connection to the internet refers to households´ access to the internet either in the house or outside the house. a / For 2023 preliminary data for the Dominican Republic, El Salvador, Honduras, and Uruguay were used. b / For Chile, Brazil, Paraguay, Bolivia, Mexico, and Peru data for 2023 were unavailable, so data for 2022 were used. Bolivia 2022 are preliminary data. c / For Colombia and Panama data for 2021 were used. 13/27 4. Inequality LAC continues to be one of the most unequal regions in the world.9 Colombia and Brazil are the countries with the highest inequality levels as measured by the Gini coefficient (53.9 points and 51.5 points as of 2023, respectively),10 considerably above the LAC regional Gini of 49.8 points. At the other extreme, the Dominican Republic and El Salvador have the lowest inequality levels in the region, with a Gini coefficient below 40 points. At the regional level, the Gini coefficient declined by 0.7 points, indicating that the income distribution became more equitable between 2021 and 2023 (figure 5).11 Inequality trends have shown mixed patterns across countries, with some making strides toward equality and others facing rising disparities. Brazil and Mexico, the largest economies in the region, experienced notable reductions: in the former inequality between 2021 and 2023 fell by 1.4 points and in the latter it fell from 46.9 in 2016 to 43.5 in 2022, a 3.4-point drop as well. Several other countries in LAC have seen a decline in their Gini coefficients: Costa Rica, Colombia, Ecuador, and Panama recorded declines in Figure 1 the range of 1 to 2 Gini points between 2021 and 2023.12 9 It is important to consider some caveats when comparing inequality measures with other regions. For example, while income-based inequality measures are reported for LAC countries, most other countries report consumption-based ones (World Bank 2016, 77–80). 10 Estimated using preliminary data from SEDLAC (CEDLAS and the World Bank). 11 Based on a “pooled” Gini coefficient (see note to figure 5). Alternative ways of calculating a regional Gini include a finding a simple average or population-weighted average of country-level coefficients. Rodríguez-Castelán et al. (2022) find that these alternative methods generally show consistent patterns during the 1993–2013 period. In addition, all three methods consistently show a decline in inequality during the 2000–2013 period. 12 Other indicators of income inequality, such as the 90th to 10th percentile average income ratios and the Kuznets ratio (ratio of the top 10 to bottom 40 income shares) show similar patterns. For example, the former registered a decline from 10.5 to 9.8 in LAC from 2021 to 2023 and the latter fell from 3.3 to 3.2 during the same period. 14 /27 Poverty and Equity Global Practice Latin America and the Caribbean Figure 5 Gini Coefficients for LAC and Subregions, 2021, 2019, and 2023 54 2023e 52 2019 2021 51.5 50 49.8 49.9 Gini points 48 48.8 46 44 42 43.5 43.3 40 Southern Mexico a Andean Latin America Central Brazil Cone Region and The America Caribbean Source: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Note: The LAC regional aggregate is based on 18 countries (LAC-18) in the region for which SEDLAC microdata were available. This is a “pooled” Gini coefficient, in the sense that it is calculated using the pooled microdata for all countries (at the regional or subregional levels). In cases where data were unavailable, values have been estimated using a combination of methods, including microsimulations, and then pooled to create regional estimates. The Andean region is the aggregate of Bolivia, Colombia, Ecuador, and Peru; the Central America region is the aggregate of Costa Rica, Guatemala, Honduras, Nicaragua, Panama, El Salvador, and the Dominican Republic; and the Southern Cone region is the aggregate of Argentina, Chile, Paraguay, and Uruguay; e = estimate. a/ For Mexico the values are those of the previous adjacent year (2022, 2020, and 2018). The decline in income inequality in LAC from 2021 on was primarily due to faster income growth among lower-income households (figure 6). While average household income per capita growth in the poorest decile was 9.5 percent from 2021 to 2023, income growth for the richest decile was roughly half of that. While income growth between 2021 and 2022 was more pro-poor, this pattern moderated significantly between 2022 and 2023 with the growth incidence curve (GIC) flattening considerably, indicating relatively uniform and lower income growth of around 3 p.p. across all income groups. 15/27 Poverty and Equity Global Practice Latin America and the Caribbean Figure 6 Growth Incidence Curves, LAC 2021–22, 2021–23, 2022–23 16 14 2022-21 2023-21 2023-22 Growth rate (annualized) 12 10 8 6 4 2 0 1 2 3 4 5 6 7 8 9 10 Deciles of per capita household income Sources: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Note: The LAC regional aggregate is based on 18 countries (LAC-18) in the region for which SEDLAC microdata were available. In cases where data were unavailable, values have been estimated using microsimulations and then pooled to create regional estimates. 16 /27 5. Sources of Income 5.1. Changes in Income Sources Labor income was the primary driver of poverty and inequality reduction in LAC from 2021 to 2023 ( gure 7), with growth rates signi cantly higher for the poorest (15.7 and 9.0 percent for the rst and the second deciles, respectively), compared to an annualized growth rate of 4.7 percent for the richest decile. In contrast, nonlabor income exhibited negative growth across most income deciles—likely re ecting the rolling back of transfers linked to the COVID-19 pandemic—but without a clear distributional incidence at the regional level. While in some countries public transfers continued to support poverty reduction (as in Brazil and Colombia), their decline in others tended to push poverty upward (as in Ecuador and El Salvador). Figure 7 Annualized Per Capita Income Growth by Decile and Source, LAC-9, 2021–23 25 Percentage change from 2021 to 2023 Labor income Nonlabor income Total 20 15.7 15 10 9.0 7.9 7.2 7.3 7.4 6.3 5.3 5.2 4.7 5 0 -5 1 2 3 4 5 6 7 8 9 10 Deciles Source: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Note: The LAC aggregate is based on nine countries (LAC-9) in the region for which microdata are available for 2021 and 2023 (Argentina, Brazil, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Panama, and Uruguay). Uruguay 2021 refers to the second semester and is not strictly comparable with 2023. 17/27 Poverty and Equity Global Practice Latin America and the Caribbean Between 2021 and 2023, labor income grew in most countries across LAC in real terms ( gure 8). Notably, Colombia, Chile, and Mexico saw signi cant increases, with growth rates of about 9 percent. Brazil, the Dominican Republic, and El Salvador also experienced substantial growth. In contrast, Argentina su ered a decline of 2.9 percent. The overall growth in labor income in LAC was very similar across genders and across geographic areas (urban vs. rural). However, there were more di erences across educational attainment groups, with both college graduates and those who had never attended school experiencing the smallest gains. Figure 8 Annualized Change in Total Labor Income Per Capita by Country, 2017 PPP, 2021–23 Colombia 9.1 Chile a 9.0 Mexico b 8.6 Brazil 8.3 Dominican Republic 8.1 El Salvador 4.9 Paraguay a 4.6 Costa Rica 2.9 a Honduras 2.9 Panama 1.9 Peru b 1.7 Guatemala a 1.3 b Uruguay 1.2 Ecuador 1.0 Nicaragua a 0.5 Bolivia a - 0.1 Argentina - 2.9 -4 -2 0 2 4 6 8 10 Source: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Note: Argentina has only urban coverage; the 2023 data for Argentina, Brazil, Colombia, the Dominican Republic, El Salvador, Honduras, and Uruguay are preliminary. a / Indicates that either the 2021 or 2023 or both data are projections using microsimulation methodology. The values for Bolivia, Peru, and Paraguay are for 2023; those for Chile, Guatemala, and Nicaragua are for 2021 and 2023; and those for Honduras figures are for 2021. b / The Mexico change is 2022 vs. 2020 and that of Uruguay is 2022 vs. 2023. 18 /27 Poverty and Equity Global Practice Latin America and the Caribbean 5.2. Which Factors Drove Poverty Changes? Three factors have largely driven poverty reduction in LAC since 2021 ( gure 9), the rst two of which re ect stronger labor markets in the region. These were increases in the employment rate and labor earnings, which accounted for reductions in poverty of 1.8 p.p. and 1.5 p.p., respectively. The last factor was public transfers, which were responsible for a 1.1. p.p. decline in poverty. Additional factors, such as remittances and other nonlabor income sources, accounted for smaller fractions of poverty changes (about 0.3 p.p. each). The type and magnitude of poverty reduction drivers were very similar to these regional patterns in Brazil and Colombia, as well as in Mexico (during the 2020–22 period). In the remaining countries that saw a signi cant reduction in poverty—Costa Rica, the Dominican Republic, Ecuador, and El Salvador—a stronger labor market was the main driver, while a decline in public transfers tended to push poverty upward (by 0.1–0.6 p.p.). Even though the recent improvements in labor market dynamics are encouraging, the long-term indicators of job quality show a very static picture (see section 5.3). Moreover, the decline in public transfers added stress to poverty levels in 9 out of 18 countries, which raises concerns about the strength of this particular poverty-reducing mechanism in the near future, especially considering the scal space for most countries across the region.13 13 The decline in public transfers tended to push poverty upward in Argentina, Bolivia, Chile, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Panama, and Peru. 19/27 Poverty and Equity Global Practice Latin America and the Caribbean Figure 9 Contribution to Changes in Poverty Rate (Shapley Decomposition), LAC-9, 2023–21 0 -0.3 -0.3 -0.3 -0.1 -1 -1.1 -1.5 -2 -1.8 -3 -4 -5 -5.3 -6 Labor Other non- Public Remittances Retirement Share of Share who Total change earnings labor income transfers and pensions individuals are employed (15-64 years old) Source: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Available at LAC Equity Lab. Note: The LAC aggregate is based on nine countries in the region for which microdata from 2021 and 2023 were available (Argentina, Brazil, Colombia, Costa Rica, the Dominican Republic, Ecuador, El Salvador, Panama, and Uruguay). The -5.3 p.p. poverty decline is di erent from the -4.7 p.p. decline shown in gure 3, because the latter includes 18 countries. Uruguay 2021 refers to the second semester and is not strictly comparable with 2023. The most notable exception to the recent regional patterns is Argentina, which experienced an increase in poverty between 2021 and 2023. The increase in the employment rate partially o set the overall increase in poverty (by 0.8 p.p.). However, the decline in labor earnings pushed poverty upward by 1.5 p.p. 20/27 Poverty and Equity Global Practice Latin America and the Caribbean 5.3. The Quality of Jobs The quantity and quality of jobs are key drivers of poverty and inequality reduction. While measuring the number of jobs is relatively straightforward, measuring their quality is more challenging. This section introduces a new indicator for LAC: the Job Quality Index (JQI). This indicator assesses the quality of employment by evaluating four key dimensions: benefits, income, satisfaction, and security.14 The JQI aggregates these dimensions to provide a summary measure, with higher values indicating better job quality. In 2023, the countries with the highest JQI in the LAC region were Costa Rica (0.84), Chile (0.85—in 2022), and Brazil (0.76). Although this higher JQI as expected reflects better performance across the four key dimensions, it is especially driven by the benefits category (figure 10, panel b). Uruguay also ranked high with a JQI of 0.75. Conversely, the countries with the lowest JQI in 2022 were Peru (0.55), Mexico (0.61), and Bolivia (0.60). Despite the recent uptick in labor markets across LAC, the JQI has been very stagnant across most countries in LAC since around 2016 (figure 10, panel a). Only Brazil, Colombia, Costa Rica, El Salvador, and Mexico experienced modest improvements, being within the 0.02–0.05 range. In contrast, the quality of jobs during the same period declined or stagnated in six countries (Argentina, Bolivia, Ecuador, Panama, Peru, and Uruguay). 14 "Benefits" measure the availability of health insurance or retirement benefits, while "Income" evaluates whether wages exceed a minimum (US$6.85/day, 2017 PPP) welfare threshold. "Satisfaction" reflects the worker's contentment with their job, with assumptions about lower satisfaction for those juggling multiple jobs. Finally, "Security" considers the stability of the job, including contract status and duration of employment. For more details, please see The Quality of Jobs. 21/27 Poverty and Equity Global Practice Latin America and the Caribbean Figure 10 Job Quality Index in LAC by Country Circa 2016 Panel A Argentina 1.00 Circa 2023 Uruguay (b) Bolivia (a) 0.80 El Salvador Brazil 0.60 0.40 Paraguay (a) 0.20 Chile (a,b) 0.00 Peru (a) Colombia (b) Panama Costa Rica Dominican Mexico (a) Republic (b) Ecuador Bene ts Argentina Panel B 1.0 Income Uruguay 0.9 Bolivia a 0.8 Satisfaction 0.7 El Salvador Brazil Security 0.6 0.5 0.4 0.3 Paraguay a 0.2 Chile a 0.1 0.0 Peru a Colombia Panama Costa Rica Mexico a Dominican Republic Ecuador Source: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Note: The Job Quality Index (JQI) is based on Brummund, Mann, and Rodriguez-Castelan (2018) and Hovhannisyan et al (2022) and follows the Alkire and Foster (2011) framework. The JQI includes four dimensions: job income (minimum US$6.85/day, 2017 PPP), job bene ts (health insurance or retirement bene ts), job security (contract or tenure of three years), and job satisfaction (no second job). Argentina has only urban coverage. The values for Argentina, Brazil, Colombia, the Dominican Republic, El Salvador and Uruguay for 2023 are based on preliminary data. a / Indicates that either the data for 2016 or 2023 or both are based on data from either the previous or following year. Data for Bolivia, Mexico, Peru, Chile, and Paraguay in 2023 are unavailable, hence 2022 data were used. The values for Bolivia for 2022 are based on preliminary data. Panel B: Circa 2023. b / To maintain comparability the base year for Colombia is 2021 instead of 2016, and the base year for the Dominican Republic and Chile is 2017. Data for Uruguay are for 2017 and 2019. 22 /27 Poverty and Equity Global Practice Latin America and the Caribbean There is a significant gender gap in job quality in the LAC region, with women experiencing worse job conditions than men across all countries. The data reveal that on average men tend to have better job quality than women (figure 11). The largest gender gaps are observed in Peru (0.11), Ecuador (0.08), Bolivia (0.08), and Colombia (0.06). Conversely, Chile (0.03) and Panama (0.03) report the narrowest. Overall, the JQI gender gap has shown little to no reduction across LAC countries over the past decade. Figure 11 Job Quality Index by Gender, Circa 2023 0.90 0.87 0.86 Female Male 0.85 0.84 0.78 0.80 0.77 0.81 0.72 0.73 0.75 0.72 Job Quality Index 0.70 0.69 0.70 0.73 0.72 0.67 0.69 0.64 0.64 0.65 0.68 0.62 0.65 0.60 0.65 0.60 0.63 0.61 0.55 0.59 0.58 0.56 0.50 0.49 0.45 0.40 Chile a Costa Rica Brazil Uruguay Panama Dominican Argentina Ecuador Colombia Paraguay a El Salvador Mexico a Bolivia a Peru a Republic Source: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Note: The Job Quality Index (JQI) is based on Brummund, Mann, and Rodriguez-Castelan (2018) and follows the Alkire and Foster (2011) framework. The JQI includes four dimensions: job income (minimum US$6.85/day, 2017 PPP), job benefits (health insurance or retirement benefits), job security (contract or tenure of three years), and job satisfaction (no second job). Argentina has only urban coverage. The values for Argentina, Brazil, Colombia, the Dominican Republic, El Salvador, and Uruguay for 2023 are based on preliminary data. a / Indicates that 2023 data are based on data from either the previous or following year. Data for Bolivia, Mexico, Peru, Chile, and Paraguay for 2023 were unavailable, hence 2022 data were used. The data for Bolivia for 2022 are preliminary. 23/27 Poverty and Equity Global Practice Latin America and the Caribbean Box 2 PROSPERITY GAP The Prosperity Gap (PG) is a new indicator that quantifies the average income shortfall from a prosperity benchmark of US$25/day (2017 PPP), which is roughly equal to the average income when countries reach high-income status. It represents the average multiplier needed to elevate the income of every person in a country or region to this prosperity standard.15 In LAC, the PG in 2023 had a value of 3.6, meaning that incomes would have to increase 3.6 times to achieve the minimum prosperity standard. When compared to other regions, LAC has a moderate PG. While LAC’s PG is higher than that of Europe and Central Asia (1.7), it is significantly lower than that of Sub-Saharan Africa (12.3) and South Asia (6.2).16 As of 2023, Uruguay and Chile (2022) led the region with the smallest prosperity gaps (1.6 and 1.7, respectively). These countries are the closest to a PG of 1.0, which is the level where no additional income is needed to reach the minimum prosperity threshold. At the other extreme, the PG indicator is the largest in Colombia, Peru, and several Central American countries. In Honduras, incomes would have to increase almost eightfold to reach the prosperity threshold. 15 Kraay et al. 2023, 2024; World Bank 2024. 16 As estimated by the nowcasting model implemented by PIP. 24 /27 Poverty and Equity Global Practice Latin America and the Caribbean Figure 12 Prosperity Gap, Circa 2023 Honduras 7.7 Guatemala a 5.7 Colombia 4.4 Nicaragua a 4.1 Peru a 3.6 El Salvador 3.5 Ecuador 3.4 Brazil 3.0 Mexico a 2.8 Paraguay a 2.7 Bolivia a 2.7 Dominican Republic 2.6 Argentina 2.2 Costa Rica 2.1 Panama 2.1 Chile a 1.7 Uruguay 1.6 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 Sources: Own elaboration based on SEDLAC (CEDLAS and the World Bank). Note: Argentina has only urban coverage; the values for Argentina, Brazil, Colombia, the Dominican Republic, El Salvador, Honduras, and Uruguay for 2023 are based on preliminary data. a / Data for Bolivia, Chile, Mexico, Peru, and Paraguay for 2023 were unavailable, hence 2022 data was used. The most recent data for Nicaragua and Guatemala are from 2014. The data for Bolivia 2022 are preliminary. 25/27 Poverty and Equity Global Practice Latin America and the Caribbean References Alkire, S., and J. Foster. 2011. “Counting and Multidimensional Poverty Measurement.” Journal of Public Economics 95 (7–8): 476–87. Bahia, K., Castells, P., Cruz, G., Masaki, T., Rodríguez-Castelán, C., & Sanfelice, V. (2023). Mobile broadband, poverty, and labor outcomes in Tanzania. The World Bank Economic Review, 37(2), 235-256. Bahia, K., P. Castells, G. Cruz, T. Masaki, X. Pedrós, T. Pfutze, C. Rodríguez-Castelán, and H. Winkler. 2024. “The Welfare E ects of Mobile Broadband Internet: Evidence from Nigeria.” Journal of Development Economics 170: 103314. https://doi.org/10.1016/j.jdeveco.2024.103314 Barrero, J. M., N. Bloom, and S. Davis. 2021. “Internet Access and its Implications for Productivity, Inequality, and Resilience.” Working Paper 29102, National Bureau of Economic Research, Cambridge, MA. https://doi.org/10.3386/w29102 Brummund, P., C. Mann, and C. Rodriguez‐Castelan. 2018. “Job Quality and Poverty in Latin America.” Review Of Development Economics 22 (4): 1682–1708. https://doi.org/10.1111/rode.12512 Hovhannisyan, S., Montalva-Talledo, V., Remick, T., Rodríguez-Castelán, C., & Stamm, K. (2022). Global Job Quality: Evidence from Wage Employment across Developing Countries. IZA DP No. 15565 Kraay, A., C. Lakner, B. Özler, B. Decerf, D. Jolli e, O. Sterck, and N. Yonzan. 2023. A New Distribution Sensitive Index for Measuring Welfare, Poverty, and Inequality. Washington, DC: World Bank eBooks. https://doi.org/10.1596/1813-9450-10470 26 /27 Poverty and Equity Global Practice Latin America and the Caribbean References Kraay, A., C. Lakner, B. Özler, B. Decerf, D. M. Jolliffe, O. Sterck, and N. Yonzan2024. “The Prosperity Gap: A Proposed New Indicator to Monitor Shared Prosperity.” World Bank Blogs, July 19, 2024. https://blogs.worldbank.org/en/developmenttalk/prosperity-gap-proposed-new- indicator-monitor-shared-prosperity#:~:text=The%20prosperity%20gap%20is% 20an,understand%2C%20and%20straightforward%20to%20estimate Rodríguez‐Castelán, C., López‐Calva, L. F., Lustig, N., & Valderrama, D. (2022). Wage inequality in the developing world: Evidence from latin america. Review of Development Economics, 26(4), 1944-1970. Viollaz, M., and H. Winkler. 2021. “Does the Internet Reduce Gender Gaps? The Case of Jordan.” Journal of Development Studies 58 (3): 436–53. https://doi.org/10.1080/00220388.2021.1965127 World Bank. 2016. Poverty and Shared Prosperity 2016: Taking on Inequality. Washington, DC: World Bank eBooks. https://doi.org/10.1596/978-1-4648-0958-3 World Bank. 2024. Poverty, Prosperity, and Planet Report 2024: Pathways Out of the Polycrisis. Washington, DC: World Bank. doi:10.1596/978-1-4648-2123-3. License: Creative Commons Attribution CC BY 3.0 IGO World Bank. 2024. Global Economic Prospects, June 2024. Washington, DC: World Bank. doi:10.1596/978-1-4648-2058-8. License: Creative Commons Attribution CC BY 3.0 IGO Learn more: LAC EQUITY LAB