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.

Since Jacobsen, LaLonde, Sullivan (1993), it has been well-known that workers displaced in a mass layoff event suffer large and persistent earnings declines. However, mass layoffs often occur in the context of a local labor market. How important are the spillover effects of mass layoffs on a local labor market and how do these effects propagate across workers and firms? We extend the analysis of Gathmann, Helm, Schoenberg (2020) using administrative data from Brazil to assess the heterogeneity in the local spillover effects of mass layoffs across workers, using a matching design to compare observably similar workers in suitable control regions. First, we seek to decompose what share of the baseline displaced worker effect is due to worsening conditions within a local labor market. Second, we seek to decompose how much of any spillover effect occurs within- versus across- skill groups (defined by occupation and education) and within- versus across- affected industry groups, measuring to what degree spillovers may be due to declines in workers' outside options. We are also interested in examining to what extent the informal sector may drive effects in our context. 

I study the role that tuition discounts play in U.S. higher education through the lens of an equilibrium model of college competition. While college sticker prices have been rising faster than inflation for many years, there has also been an increasing importance of institutional discounts in the final net price paid by students, which is especially relevant at selective private institutions. I develop a model of the demand and supply of college seats, where students have heterogenous preferences over differentiated colleges and colleges have preferences over heterogenous students. The model adapts the nested-fixed point approach of D’Haultfoeuille, Durrmeyer, Février (2019) to incorporate college admissions in a decentralized equilibrium where colleges maximize both profits and student quality. I stitch together various datasets on students and colleges through an indirect inference procedure. The model decomposes prices offered to students into contributions due to heterogenous marginal costs, markups, and quality discounts. Counterfactuals will assess the pass-through of increased financial aid onto prices (“The Bennet Hypothesis”), accounting for the role of college market power, indirect effects from supply expansions, and spillovers across student groups.