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This study provides new evidence on the local labor market impacts of trade, differentiating between the employment, income, migration, and informality channels. It uses a unique dataset matching information on exports and imports from customs with indicators on employment and labor incomes for around 2,000 Mexican municipalities over 2004-14. The analysis uses an instrumental variable approach that combines the initial structure of trade across municipalities with global trends in trade between low- and middle-income countries (excluding Mexico) and the United States by sector. First, the study finds that expanding exports per worker in Mexico's municipalities increased labor force participation but not employment rates. Exports also raised total labor incomes but not average labor incomes, implying a growing labor supply. The results also find that export and import expansion increased immigration and lowered the rate of informal workers. Second, the analysis examines differences by geography and sectors. It finds that trade affected labor markets in the North through the income and migration channels and in the South through the employment and informality channels. Exports benefitted the total incomes of workers in both the manufacturing and service sectors but reduced informality only in manufacturing. Third, the study suggests a more favorable role of intermediate relative to final imports, driven by manufacturing imports. It also finds evidence for positive spillovers from global value chain participation through the employment and income channels. Finally, it examines how local policy mediates the labor market effects from trade, focusing on connectivity, labor market flexibility, and education spending.

International trade.

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Understanding the selection of workers into informality is a policy priority to design programs to increase formalization across Sub-Saharan Africa, where nine out of ten workers are informal. This paper estimates a model of self-selection with entry barriers into the formal sector to identify the extent of involuntary informality in Senegal, a representative country in terms of levels of informality in West Africa and with one of the most rigid labor markets in the world. The results show that the desire of being formal is greater for workers with formal education, married, and a lower proportion of children younger than age five living in the household. The individual's preference for the formal sector also grows with age at a decreasing rate. The results also show that labor informality is mainly a voluntary phenomenon, with 30 percent of informal workers being involuntarily displaced into the informal sector. The results are robust to different model specifications, definitions of labor informality, and heterogeneous groups of workers.

Equity.

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This paper studies the effects of differential exposure to COVID-19 on educational outcomes in Guatemala. The government adopted a warning index (ranging from 0 to 10) to classify municipalities by infection rates in 2020, which was then used by the Ministry of Education in 2021 to establish a "stoplight" system for in-person instruction. Using administrative panel data for all students in Guatemala, the study employs 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. The 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. These effects were more pronounced during the first year of the pandemic. The findings show differential effects by the level of instruction, with greater losses for younger children in initial and primary education. The results are robust to specification choice, multiple hypothesis adjustments, and placebo experiments, suggesting that the pandemic has had heterogeneous consequences.

Educational planning.

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Across Latin America, school dropout is a growing concern, because of its negative social and economic consequences. Although a wide range of interventions hold potential to reduce dropout rates, policy makers in many countries must first address the basic question of how to target limited resources effectively for such interventions. Identifying who is most likely to drop out and, therefore, who should be prioritized for targeting, is a prediction problem that has been addressed in a rich set of research in countries with strong education system data. This paper makes use of newly established administrative data systems in Guatemala and Honduras, to estimate some of the first dropout prediction models for lower-middle-income countries. These models can correctly identify 80 percent of sixth grade students who will drop out in the transition to lower secondary school, performing as well as models used in the United States and providing more accurate results than other commonly used targeting approaches.

Dropout --- Early Warning --- Prediction