An Empirical Model of the Medical Match
This paper develops a framework for estimating preferences in two-sided matching markets with non-transferable utility using only data on observed matches. Unlike single-agent choices, matches depend on the preferences of other agents in the market. I use pairwise stability together with a vertical preference restriction on one side of the market to identify preference parameters for both sides of the market. Recovering the distribution of preferences is only possible in an environment with many-to-one matching. These methods allow me to investigate two issues concerning the centralized market for medical residents. First, I examine the antitrust allegation that the clearinghouse restrains competition, resulting in salaries below the marginal product of labor. Counterfactual simulations of a competitive wage equilibrium show that residents’ willingness to pay for desirable programs results in estimated salary markdowns ranging from $23,000 to $43,000 below the marginal product of labor, with larger markdowns at more desirable programs. Therefore, a limited number of positions at high quality programs, not the design of the match, is the likely cause of low salaries. Second, I analyze wage and supply policies aimed at increasing the number of residents training in rural areas while accounting for general equilibrium effects from the matching market. I find that financial incentives increase the quality, but not the number of rural residents. Quantity regulations increase the number of rural trainees, but the impact on resident quality depends on the design of the intervention.
I am grateful to my advisors Ariel Pakes, Parag Pathak, Susan Athey and Al Roth for their constant support and guidance. I thank Atila Abdulkadiroglu, Raj Chetty, David Cutler, Rebecca Diamond, William Diamond, Adam Guren, Guido Imbens, Dr. Joel Katz, Larry Katz, Greg Lewis, Jacob Leshno, Julie Mortimer, Joseph Newhouse, Mark Shepard, Dr. Debra Weinstein and workshop participants at several universities for helpful discussions, suggestions and comments. Data acquisition for this project was funded by the Lab for Economic Applications and Policy and the Kuznets Award. Financial support from the NBER Non-profit Fellowship and Yahoo! Key Scientific Challenges Program is gratefully acknowledged. Computations for this paper were run on the Odyssey cluster supported by the FAS Science Division Research Computing Group at Harvard University. Email: email@example.com. The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research.
Nikhil Agarwal, 2015. "An Empirical Model of the Medical Match," American Economic Review, American Economic Association, vol. 105(7), pages 1939-78, July. citation courtesy of