Community Colleges and Student Outcomes: Causality, Counterfactuals, and Linked Administrative Data

Jack Mountjoy

Two-year community colleges enroll nearly half of all first-time college students in the U.S., yet causal estimates of their effects on student outcomes are relatively scarce. Beyond the typical challenge of selection bias driven by systematic student sorting, causal inference in this setting also requires careful attention to the multiple counterfactuals to treatment: some students induced into 2-year colleges would not have otherwise attended college, but others may be diverted from 4-year entry. Modern instrumental variables methods in this multiple-counterfactual setting cannot separately identify treatment effects along these distinct choice margins, rendering 2-year colleges a black box in how they impact students coming from different alternatives. In this paper, I develop nonparametric identification results and construct estimators that overcome these limitations, recovering counterfactual-specific causal effects along each choice margin and thus opening the black box of community college impacts. I apply the method to linked administrative data spanning the state of Texas, using continuous instrumental variation in distances to nearby 2-year and 4-year colleges (conditional on a rich set of student, school, and neighborhood characteristics) to identify the effects of initial enrollment choices on ultimate degree attainment and adult earnings. The method also permits a test of whether student decisions are consistent with sorting on comparative advantage, and informs how treatment effects might change as 2-year colleges draw deeper into the population of potential entrants. Finally, I combine the gross effect estimates with cost data to assess benefit-cost ratios of 2-year attendance and public policies that encourage it.

About Jack Mountjoy

Jack Mountjoy is a Ph.D. candidate in Economics at the University of Chicago, conducting research on the economics and econometrics of education, labor markets, and social mobility. Focusing on key transitions in the path from the classroom to the workforce, his research applies theory and modern econometric methods to large, linked administrative datasets to quantify long-run impacts of individual educational choices and large-scale public policies. Prior to his doctoral studies, he worked as an Economic Research Analyst at the U.S. Federal Trade Commission after graduating summa cum laude and Phi Beta Kappa from Whitman College.