We document substantial variation in the effects of a highly-effective literacy program in northern Uganda. The program increases test scores by 1.40 SDs on average, but standard statistical bounds show that the impact standard deviation exceeds 1.0 SD. This implies that the variation in effects across our students is wider than the spread of mean effects across all randomized evaluations of developing country education interventions in the literature. This very effective program does indeed leave some students behind. At the same time, we do not learn much from our analyses that attempt to determine which students benefit more or less from the program. We reject rank preservation, and the weaker assumption of stochastic increasingness leaves wide bounds on quantile-specific average treatment effects. Neither conventional nor machine-learning approaches to estimating systematic heterogeneity capture more than a small fraction of the variation in impacts given our available candidate moderators

We examine how residential property values are impacted by school shootings, which are crimes that have a very low probability of being repeated in the same location. We exploit the exogenous timing of eleven mass shootings that took place between 1998 and 2014,  and use a difference-in-differences framework to estimate the causal effect of these school shootings on property values in the affected school attendance area. We find that house prices decline by an average of around 2.4 percent in a four-year period after a mass school shooting. We also find that enrollment falls in the affected school district, suggesting that families subsequently avoid schools in areas that have experienced such events.

The literature that has previously shown that boys outperform girls in math tests has failed to explain the underlying causes of the phenomenon. This math gender gap has been documented to vary across countries, and shown to grow as students advance through school. In this paper I suggest that these patterns may be explained by sample selection caused by gender differences in schooling's opportunity costs, which lead lower-achieving males to drop out. I present and test the implications of a labor supply model that examines the opportunity cost of school attendance and, thereby, the observed math gender gap. Using an exogenous policy change, the launch of a conditional cash transfer program in Colombia, I estimate that sample selection explains between 50 percent and 60 percent of the gap. Estimates of non-parametric bounds show that selection in the lower quantiles of the male distribution explains a significant portion of the gap.

We use 292 household surveys from eighteen Latin American countries to document patterns in secondary school graduation rates over the period 1990–2010. We find that enrollment and graduation rates increased during that period, while dropout rates decreased. We provide two types of explanations for these patterns. Countries implemented changes on the supply side to improve access, by increasing the resources allocated to education and designing policies to help students stay in school. Despite this progress, graduation rates are still generally low, and there are remarkable gaps in educational outcomes in terms of gender, income quintiles, and regions within countries. The quality of education is also generally low. 

Teacher quality is a key factor in improving student academic achievement. As such, educational policymakers strive to design systems to hire the most effective teachers. This paper examines the effects of a national policy reform in Colombia that established a merit-based teacher-hiring  system intended to enhance teacher quality and improve student learning. Implemented in 2005 for all public schools, the policy ties teacher-hiring decisions to candidates' performance on an exam evaluating subject-specific knowledge and teaching aptitude. We find that though the policy sharply increased pre-college test scores of teachers, it also decreased the overall stock of teacher experience and led to sharp decreases in students' exam performance and educational attainment. Using a difference-in-differences strategy to compare the outcomes of students from public and private schools over two decades, we show that the hiring reform  decreased students' performance on high school exit exams by 8 percent of a standard deviation, and reduced the likelihood that students enroll in and graduate from college by more than 10 percent. The results underscore that relying exclusively on specific ex ante measures of teacher quality to screen candidates may unintentionally reduce students' learning gains.

Significant disparities in the accumulation of human capital exist between urban and rural areas in developing countries. Selective migration seems to explain part of this gap, but it is not its only determinant. In this paper, I provide evidence that natural disasters also explain why students in rural areas obtain lower academic achievement compared to those in urban areas. I use data on the census of Colombian schools, and employ a difference-in-differences strategy that leverages variation from an unusual rainfall shock that affected more than two million people in urban and rural Colombia. The results suggest that unusual rainfall disruptions increase school dropout and failure rates, and decrease learning of remaining students at least during a decade. The effects are focused on students enrolled in rural schools, leaving those in urban schools mostly unaffected. I explore several mechanisms and rule out that the effects are driven by selective migration or a loss on educational resources. I find evidence that the rainfall shock increased poverty and production, suggesting that rural students are more likely to drop out due to smaller returns to education on the agricultural sector.

This paper shows that returns to education are not enough to capture returns to human capital. Using longitudinal data of all college graduates in Colombia, we estimate labor market returns to postsecondary degrees and to various skills --including literacy, numeracy, foreign language, field-specific, and non-cognitive skills. Graduates of longer programs, of private institutions, and of schools with higher reputation obtain higher earnings. After controlling for degree's characteristics, a one standard deviation increase in each skill predicts average earnings increases of two percent. Returns to skills vary along the earnings distribution, with tenure, and with the degree of job specialization. 

We use census-like data and a regression discontinuity design to study the labor market impacts of a signal provided by a government-sponsored award to top-performing students on a nationwide college exit exam in Colombia. Students who can signal their high level of specific skills earn seven to ten percent more than identical students lacking such a signal. The signal allows workers to find jobs in more productive firms and sectors that better use their skills. The positive returns persist for up to five years. The signal favors workers from less advantaged groups who enter the market with weaker signals. 

This paper examines the impact of trade liberalization on wage inequality in developing economies. We study a new mechanism that may amplify or lessen the inequality effect of trade. In particular, we include different degrees of substitutability between labor and intermediate inputs across sectors into a dynamic quantitative trade model. We use administrative data from Colombia and exploit exogenous tariff variation to estimate the key elasticities of the model through an indirect inference approach. We find complementarities between labor and intermediate inputs in the non-tradable sector and substitutability in the manufacturing and agricultural sectors. Armed with the estimates, we compute the gains from the trade reform, finding that different substitutabilities in the production function amplify the wage inequality effects.

• • • Previously circulated as: Entering the Major Leagues: The Effect of Competition from the United States on Workers and Firms in an Emerging Economy

The allocation of resources within the household has been extensively theorized, but empirical evidence on this topic has been very scarce. Endogeneity concerns hinder this type of analysis due to the lack of identifying variation within the household. In this paper, we overcome these difficulties by exploiting a unique setting that introduced random variation in resource allocation within households. We evaluate the effects of a program that provided alternative delivery methods of conditional cash transfers in Bogotá, Colombia, and allocated resources at the student level. The individual randomization implied that some households had treated and untreated siblings, allowing us to extend the analysis to estimate spillover effects of the program on beneficiaries and their siblings. Students were randomly allocated to a standard design and a design that prioritized enrollment in tertiary education. We find that standard delivery methods increase educational outcomes for treated children but decrease the same outcomes for untreated siblings of treated students. We rationalize the results by estimating a structural model that uses the standard delivery method for estimation and the alternative delivery method for validation

We assess whether crop seasonality impacts school dropout rates in rural areas. Schooling calendars often coincide with harvesting calendars in numerous regions, posing a significant challenge for rural students in developing countries due to the substantial increase in the opportunity cost of remaining enrolled in school. To investigate this phenomenon, we leverage variation resulting from an unexpected change in school calendars among public schools in two states in Colombia, leading to an increased overlap in the number of weeks between school attendance and harvesting seasons. The findings reveal that this overlap resulted in a higher incidence of school dropouts, suggesting that a potential policy solution for addressing high dropout rates in rural schools is to adjust the school and harvesting calendars.

 Life-cycle income growth rates differ significantly across countries. In this paper, we study the relative importance of human capital accumulation, labor market frictions and labor market opportunities in shaping life-cycle age-income profiles in Brazil, Colombia and the US. Through the lens of a random search model with learning on the job, we find that labor market opportunities are the single most important driver of the life-cycle wage profile.  

We study the differential effects of migration by suggesting a novel hypothesis that reconciles pre-existing contradictory evidence of the effects of migrants on local communities. Our hypothesis relates the effects of migration to the migrants' cost of not migrating (i.e. the opportunity cost of migration), and suggests that the consequences of migration vary depending on the migrants' incentives to migrate. Most of the negative effects of migrants are usually driven by the their willingness to accept lower paid jobs, but the incentives to migrate depend on the opportunity cost (i.e. the benefit received by not migrating), which varies between several types of migrants. It is expected that migrants with low opportunity cost of relocating (or less incentives to stay in their origin) accept lower paid others (including joining illegal activities), whereas migrants with a higher opportunity cost will not.

This project received funding by LEM and is it in the process of data collection. 

I employ individual-level data from admission oral exams to investigate the impact of jury gender composition on student performance. Through random assignment, students are allocated to jury members, ensuring an exogenous gender mix within each evaluation board. Notably, a 10 percent rise in the proportion of males on the jury decreases students' scores in 0.6 percent, even when accounting for jury members fixed effects. The male composition of the jury does not predict any variations in other measurements of the student's test scores. These negative point estimates are primarily attributed to lower scores obtained by male students when assessed by jury boards composed entirely of males. This suggests a noteworthy gender-based influence on student performance during admission oral exams.