This study investigates whether text messages can encourage caregivers to increase their intention to use in-person early childhood services and subsequently, increase actual attendance. We randomly assigned 719 educational centers that cover 15,100 low-income beneficiaries into one control and two treatment groups. Both treatments consisted of a set of text messages sent to caregivers’ mobile phones over three weeks with information on the safety of children returning to in-person services. The texts for the first treatment group appealed to caregivers’ risk and loss aversion by stressing the potential losses imposed on children who do not attend early childhood education. The messages in the second treatment group emphasized the social norm that children’s attendance is a civic duty of caregivers. Results show greater reported intent from caregivers who receive text messages for their children to attend but no significant differences because of the framing of the messages. However, this increased willingness to attend does not translate into greater effective attendance. These findings suggest that while text messages may be useful to communicate information, these nudges may be insufficient to change behaviors and additional efforts to turn intentions into actions are required.

We study green and carbon-intensive employment in India and discuss the implications of the ongoing green transition for the education and skill development ecosystem. Our analysis employs two definitions to identify green and carbon-intensive jobs in survey data. The first is India’s official green occupations list and the second is an international classification of carbon-intensive occupations used in previous research. We apply these definitions to data from the 2019–20 Periodic Labour Force Survey to estimate the size and composition of green and carbon-intensive employment, examine their distributions across sectors and states, and characterize green and carbon-intensive workers in attributes and wages. Our results highlight the importance of monitoring green and carbon-intensive jobs with robust labor market monitoring systems to guide decisions on the sustainability transition and suggest key aspects to consider when investing in green skills and the potential distributive consequences of sustainability policies on the population.

This paper introduces, validates, and applies a Least Absolute Shrinkage and Selection Operator with multiple imputation by Predictive Mean Matching (LASSO-PMM) method to estimate intra-generational income dynamics from cross-sectional data. We validate the method using 36 harmonized panel data sets in four Latin American countries and apply it to cross-section data from 43 countries across the world. Results show that LASSO-PMM predictions are statistically indistinguishable from actual household poverty rates, mobility indicators, and income or consumption changes. These findings suggest that estimating economic mobility using a LASSO-PMM approach may accurately approximate actual income dynamics when panel data are unavailable.

This chapter analyzes migration patterns in Colombia across four survey waves of the Encuesta Longitudinal de Colombia (ELCA), documenting the evolution, magnitude, and socioeconomic determinants of internal and international migration between 2010 and 2019.

We study the short-term effects of differential exposure to COVID-19 on educational outcomes in Guatemala. The government adopted a warning index to classify municipalities by cases and infection rates in 2020. Using administrative panel data for all students in Guatemala, we employ a difference-in-differences strategy that leverages municipal differences over time in the warning index to estimate the effects of the pandemic on dropout, promotion, and school switching in 2021 and 2022. Results show that municipalities with a higher warning index had significantly larger dropout, lower promotion rates, and a greater share of students switching from private to public schools.

This paper studies whether household surveys precisely identify the LGBT population and are suitable to measure labor market discrimination in Colombia. We first quantify the size of the LGBT population and estimate labor market inequalities from these data, highlighting potential pitfalls from using this approach. We then present findings from a list experiment in the capital city of Bogotá. Results show that household surveys underestimate the size of the LGBT population and may yield biased estimates of labor market inequalities. While survey estimates range between 1 and 4 %, we find that LGBT individuals represent around 12–22 % of the total population. We find heterogeneous reporting by sex at birth, age groups, educational attainment, and marital status. Our findings suggest that while current measurement practices are a step forward for LGBTQ+ visibility, further steps are required before household surveys may be used to consistently estimate discrimination and guide policy responses to protect their welfare.

This paper evaluates the randomized Good Drinks program in four localities of Bogotá, Colombia. The intervention encourages bartenders to adopt standardized practices that promote responsible behavior and de-escalation of violence in drinking establishments. Using a cluster-randomized controlled trial, we find that the program significantly reduced violent incidents in treated establishments, providing evidence that supply-side interventions targeting alcohol service practices can be effective tools for violence reduction in urban settings.

This paper characterizes the labor market of youth in Colombia from 2008 to 2017. We estimate labor market indicators for individuals aged between 14 and 28 years using microdata from Colombia’s household surveys over the study period. Our estimates document the main patterns and trends in employment, unemployment, informality, and earnings for young workers, compare Colombia’s situation to that of other Latin American countries, and discuss the main policy challenges and opportunities to improve youth labor market outcomes.

This chapter analyzes the social and economic impacts of the COVID-19 pandemic on Honduras and evaluates policy options available to the government to mitigate the crisis, with particular attention to social protection, labor markets, and fiscal constraints.

This paper examines whether access to Colombia’s social pension program is associated with improvements in mental health and social and health behaviors among poor older adults. Using a regression discontinuity design that exploits the program’s means-tested eligibility cutoff, we estimate the causal effect of pension receipt on depression, social engagement, and health behaviors, contributing to the evidence on the non-income effects of social protection programs in developing countries.

This paper studies the effects of a large-scale information policy that nudges high school students towards college information websites in Colombia. We collect panel data on 6,000 students in 115 public schools and match them to administrative records. Students in 58 randomly-chosen schools received a 35-minute presentation on the earning premiums of college, funding opportunities to cover costs, and the importance of test scores for admission. Students learn about financial aid but do not update beliefs on college earnings. Providing information has small effects on aspirations, effort, and enrollment. We conduct an in-depth analysis of the reasons why information has limited effects.

This paper evaluates the long-run effects of different incentive structures in a conditional cash transfer program in Honduras, comparing outcomes for beneficiaries who received demand-side versus supply-side transfers over a decade after the program ended. We find that the form of incentive delivery matters for long-run educational and labor market outcomes, contributing to the sparse evidence on the persistence of CCT impacts and the mechanisms through which different incentive structures shape human capital investment.

School dropout is a growing concern across Latin America because of its negative social and economic consequences. Identifying who is likely to drop out, and therefore could be targeted for interventions, is a well-studied prediction problem in countries with strong administrative data. In this paper, we use new data in Guatemala and Honduras to estimate some of the first dropout prediction models for lower-middle income countries. These models correctly identify 80% of sixth grade students who will drop out within the next year, performing better than other commonly used targeting approaches and as well as models used in the U.S.

Minimum wage policies are implemented in most developing countries, so understanding their consequences is critical to determine their effectiveness. This paper quantifies the labor market and poverty effects of Honduran minimum wages from 2005 to 2012. Using 13 household surveys as repeated cross-sections, I estimate the net effects of minimum wage hikes using variation from annual reforms to multiple minimum wages, a 60% increase, and changes in the number of minimum wage categories. Evidence shows that employers are partially complying with minimum wage laws, and respond to hikes by increasing their level of non-compliance. Higher minimum wages reduce covered (formal) employment and increase uncovered (informal) employment. Formal sector wages increase but greater labor supply in the informal sector leads to a negative net effect on wages. This last result is often empirically ambiguous, although consistent with the dual-sector minimum wage model. I find no evidence that minimum wages reduce extreme or moderate poverty.

This article studies minimum wage non-compliance in Honduras, a dual labor market with high wage floors that are weakly enforced. However, rather than just counting how many workers earn sub-minimum wages, it also estimates violation indices that measure compliance at the intensive margin. I first explore cross-sectional heterogeneity in violations using household survey data. Then, I quantify compliance adjustments to minimum wage hikes by comparing indices before and after a large unexpected increase. Results show substantial differences in non-compliance across industries, location, and coverage status. Violations worsen with rising minima, but less in in more compliant sectors.

Most conditional cash transfer evaluations have focused on estimating program effects on schooling, consumption, and labor supply. Fewer studies have addressed these outcomes using a distributive lens. This article uses data from three programs in Latin America to obtain evidence of their impact on educational inequality of opportunity, measured using primary enrollment. The main results indicate that groups considered vulnerable gain more in terms of access to education and that these interventions help level the playing field. They do not eliminate inequality of opportunity but are certainly a useful complement to equity-enhancing policies.

This paper documents the evolution and trends in Honduran migration patterns, both internal and international, and estimates their socioeconomic impacts on sending households and communities. Using nationally representative household survey data, we characterize migrants by origin, destination, and socioeconomic background, and estimate the effects of remittances on household income and expenditure.

This article carries out a validation exercise of vulnerability measures as predictors of poverty at the aggregate and micro levels based on short and long term panel data for Argentina and Chile. It then compares their performance to that of deprivation indicators. The main findings indicate that while vulnerability measures are good predictors of poverty in the aggregate, the same does not occur at household level. These results imply that while useful, vulnerability estimates require incorporating shocks to attenuate biased estimates if they are to be used for targeting purposes.

This paper provides a comprehensive descriptive analysis of trends in inequality and poverty in Honduras over the preceding two decades, documenting changes in income distribution and poverty rates across regions, demographic groups, and economic sectors. The analysis draws on the Encuesta Permanente de Hogares de Propósitos Múltiples (EPHPM) to construct comparable estimates across survey years.

This paper presents empirical evidence on the deprivation costs of the 2001-2002 Argentinean crisis. The selected approach is multidimensional and focuses on four aspects of quality of life: labor, assets, education and income. These dimensions are constructed by multivariate data reduction techniques and then aggregated using the Bourguignon and Chakravarty’s axiomatic multidimensional poverty measure. The main findings indicate that the crisis had larger costs on well-being dimensions which are tied to the economic cycle, such as income and labor. Costs were mild on structural aspects of well-being, such as assets and education. A sensitivity analysis shows that these results are robust to different deprivation lines.

This chapter presents evidence on quality of life variation across Buenos Aires neighborhoods using a dedicated survey instrument, examining how residents perceive and experience well-being at the sub-city level and the factors driving spatial differences in life satisfaction.