One way workers can adapt to adverse shocks after entering the labor market is by returning to school later in life, a choice involving substantial opportunity costs in terms of foregone earnings and lost work experience. This paper uses administrative data on earnings and enrollment histories to estimate a dynamic model quantifying these tradeoffs. I first exploit variation from the Great Recession to show that adult workers respond to industry-level shocks by increasing community college enrollment, with heterogeneity across fields of study and industries playing a key role in driving enrollment. The model unpacks what these patterns imply for policies intended to increase worker earnings, such as targeted tuition subsidies. A key contribution of the framework is that it flexibly quantifies multidimensional skills using a data-driven approach, capturing interactions between fields of study and career pathways. A counterfactual tuition subsidy increases enrollment but results in returns that are negative on average, with substantial heterogeneity. Decomposing these returns emphasizes the importance of on-the-job work experience and aligning education with desired career transitions in the design of retraining policies.

This paper studies how the choice of college and major are related to earnings in a context where selection bias can potentially confound direct measurement. Three decades of ranked college application and assignment data for the population of college students in Chile are linked to a decade of administrative tax data on earnings which enable the study of how student choices, college, and major interact to affect earnings. Ranked order application lists, biased OLS regressions, and thousands of local RD estimates are tied together in a Roy model of college-major choice and earnings outcomes. Preliminary estimates indicate that student outcomes are quite heterogenous – match effects explain a large share of the variance in earnings, most of which are on observable dimensions. This result suggests that policy recommendations based on assuming homogenous gains may be misleading in our context.

It is well known that workers displaced by mass layoff events suffer large and persistent earnings losses. However, mass layoffs often occur in the context of local labor markets, where displaced workers can interact with and impact the outcomes of non-laid off workers. What are the equilibrium effects of mass layoffs and how do these effects vary across workers and firms? We use administrative data from Brazil to assess heterogeneity in impacts of mass layoffs across several local labor markets. Using a matched differences-in-differences research design across regions, we estimate the total and spillover effects of flagship mass layoff events, separating effects into those from directly displaced workers and those from indirectly affected workers in the same region. We find strong declines in local employment four years after a mass layoff event, about half of which is attributed to workers not directly exposed to a flagship layoff event. A worker-level analysis shows a limited role for out-migration, indicating that aggregate impacts are driven by reduced in-migration. Our results are consistent with declines in local consumer demand (with impacts on wage rates in non-tradeable industries) and agglomeration effects, but we find little evidence for impacts on workers in the same skill groups as layoff workers.