COLIN D. SULLIVAN
Experimental Economics, Labor Economics, Market Design
I am a Postdoctoral Fellow in the Department of Economics at Stanford University. I use experiments to study labor markets, organ markets, and other matching markets, with a focus on eliciting preferences through incentive design. I received my PhD in Applied Economics from the Wharton School at the University of Pennsylvania.
Contact me at email@example.com.
American Economic Review, 2019, Vol. 109 (11): 3713-44. Online Appendix
We introduce a new experimental paradigm to evaluate employer preferences, called Incentivized Resume Rating (IRR). Employers evaluate resumes they know to be hypothetical in order to be matched with real job seekers, preserving incentives while avoiding the deception necessary in audit studies. We deploy IRR with employers recruiting college seniors from a prestigious school, randomizing human capital characteristics and demographics of hypothetical candidates. We measure both employer preferences for candidates and employer beliefs about the likelihood candidates will accept job offers, avoiding a typical confound in audit studies. We discuss the costs, benefits, and future applications of this new methodology.
LEARNING TO MANIPULATE: EXPERIMENTAL EVIDENCE ON OUT-OF-EQUILIBRIUM TRUTH-TELLING (WITH CLAYTON R. FEATHERSTONE AND ERIC MAYEFSKY)
Work in Progress
In two-sided settings, market designers tend to advocate for deferred acceptance (DA) over priority mechanisms, even though theory tells us that both types of mechanisms can yield unstable matches in incomplete information equilibrium. However, if match participants on the proposed-to side deviate from equilibrium by truth-telling, then DA yields stable outcomes. In a novel experimental setting, we find out-of-equilibrium truth-telling under DA but not under a priority mechanism, which could help to explain the success of DA in preventing unraveling in the field. We then attempt to explain the difference in behavior across mechanisms by estimating an experience-weighted learning model adapted to this complex strategic environment. We find that initial beliefs drive the difference in agents’ ability to find strategic equilibria, rather than alternative explanations such as differences in the learning process.
PATIENTLY WAITING: STRATEGIC BEHAVIOR ON THE LIVER TRANSPLANT WAITLIST
Work in Progress
Modeling the behavior of liver transplant candidates as a dynamic discrete choice problem, I find evidence that many patients refuse lower-quality livers (e.g., those from older donors or those donated after cardiac death) and remain on the waitlist, risking death in hopes of a better offer. Leveraging a 2013 policy change, I estimate the effect of increasing the future flow of organ offers on refusal rates and graft failure. I find that allocating the best waitlist positions to the sickest patients increases graft failure and reduces overall welfare. In dynamic equilibrium, this allocation system allocates the best organs to the sickest patients, and causes relatively healthy patients to become sicker over time.
PHD IN APPLIED ECONOMICS
The Wharton School at the University of Pennsylvania
Dissertation: Essays in Matching Markets
Committee Chair: Judd B. Kessler
Committee: Clayton R. Featherstone, Corinne Low
AM IN STATISTICS
AB IN ECONOMICS; POLITICAL SCIENCE
The University of Chicago