The Returns to College(s): Relative Value-Added and Match Effects in Higher Education
Students who attend different colleges in the U.S. end up with vastly different economic outcomes. We study the role of relative value-added across colleges within student choice sets in producing these outcome disparities. Linking high school, college, and earnings registries spanning the state of Texas, we identify relative college value-added by comparing the outcomes of students who apply to and are admitted by the same set of institutions, as this approach strikingly balances observable student potential across college treatments and renders our extensive set of covariates irrelevant as controls. Methodologically, we develop a framework for identifying and interpreting value-added under varying assumptions about match effects and sorting gains. Empirically, we estimate a relatively tight, though non-degenerate, distribution of relative value-added across the wide diversity of Texas public universities. Selectivity poorly predicts value-added within student choice sets, with only a fleeting selectivity earnings premium fading to zero after a few years in the labor market. Non-peer college inputs like instructional spending more strongly predict value-added, especially conditional on selectivity. Colleges that boost BA completion, especially in STEM majors, also tend to boost earnings. Finally, we probe the potential for (mis)match effects by allowing value-added schedules to vary by student characteristics.
For helpful comments, we are grateful to Josh Angrist, Raj Chetty, and John Friedman, along with Dan Black, Zach Bleemer, Kirill Borusyak, David Deming, Michael Dinerstein, Peter Ganong, Nathan Hendren, Peter Hull, Adam Kapor, Ezra Karger, Larry Katz, David Lee, Thomas Lemieux, Alex Mas, Jordan Matsudaira, Arnaud Maurel, Casey Mulligan, Derek Neal, Chris Neilson, Matt Notowidigdo, Jordan Richmond, Jonah Rockoff, Raffaele Saggio, Constantine Yannelis, Owen Zidar, Seth Zimmerman, and seminar participants at Princeton, the Federal Reserve Banks of New York and Chicago, the University of Oslo, Statistics Norway, Duke, Chicago Booth, Chicago Economics, NBER Labor Studies, Washington University in St. Louis, Harvard Opportunity Insights, Columbia Teachers College, NBER Summer Institute, LSE, Penn State, UCL, LMU Munich, and FGV EPGE. We also thank Rodney Andrews, Janie Jury, Mark Lu, Greg Phelan, John Thompson, and especially Greg Branch at the UT-Dallas Education Research Center for expert guidance on the administrative data. Nidhaanjit Jain provided excellent research assistance. We are grateful for financial support from the Industrial Relations Section at Princeton University and the Robert H. Topel Faculty Research Fund at the University of Chicago Booth School of Business. The conclusions of this research do not necessarily reflect the opinions or official positions of the Texas Education Research Center, the Texas Education Agency, the Texas Higher Education Coordinating Board, the Texas Workforce Commission, or the State of Texas. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.