This paper analyzes a large-scale and long-running distance education program in Mexico. We estimate marginal treatment effects (MTEs) for learning in math and Spanish in telescundarias relative to traditional Mexican secondary schools using an empirical framework that allows for unobserved sorting on gains. The estimated MTEs reveal that school choice is not random and that the average student experiences significant improvements in both math and Spanish after just one year of attendance in telesecundarias. We find that the existing policy reduces educational inequality, and our policy-relevant treatment effects show that expanding telesecundarias would yield significant improvements in academic performance.

When school-age children work, their education competes for their time and effort, which may lead to lower educational attainment and academic achievement. This paper develops and estimates a model of student achievement in Mexico, in which students make decisions on school enrollment, study effort and labor supply, taking into account locally available schooling options and wages. All of these decisions can affect their academic achievement in math and Spanish, which is modeled using a value-added framework. The model is a random utility model over discrete school-work alternatives, where study effort is determined as the outcome of an optimization problem under each of these alternatives. The model is estimated using a large administrative test score database on Mexican 6th grade students combined with survey data on students, parents and schools, geocode data on school locations, and wage data from the Mexican census. The empirical results show that if students were prohibited from working while in school, the national dropout rate would increase by approximately 20%, while achievement would increase in both math and Spanish. Expanding the conditional cash transfer, either in terms of the magnitude of the cash benefits or the coverage, in conjunction with prohibiting working while in school is an operational policy that would greatly reduce dropout while maintaining the gains in achievement.

In many countries, conditional cash transfers offered by the government have been shown to increase school enrollment for the beneficiaries. However, these policies’ potential to increase overall human capital depends on the schools’ capacity to expand enrollment with sufficiently high-quality instruction, ensuring that larger classes do not negatively affect peers. We develop a structural model in which students first face an enrolment decision, and then an effort decision which will impact their achievement and the effort of their teacher. Class composition and effort choices are determined endogenously via a strategic game, which takes into consideration peer effects within the classroom. To estimate the model, we combine administrative data on test performance and cash transfers, socioeconomic surveys, and spatial data on child wages. Our model allows for heterogeneous endowments and teacher ability, and with it we can evaluate the impact of a conditional cash transfer on not only beneficiary enrollment choices and achievement, but also on their classmates.