COLIN D. SULLIVAN

Experimental Economics, Labor Economics, Market Design

ABOUT ME

I am a Postdoctoral Fellow in the Department of Economics at Stanford University, invited by Alvin Roth and Muriel Niederle. 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.

I will be available for interviews on the 2021 job market.

View my CV here. 

Contact me at cdsulliv@stanford.edu.

 

RESEARCH

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.

Working Paper

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

I modeling the behavior of liver transplant candidates as a dynamic discrete choice problem and 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 in the future. In dynamic equilibrium, this strategic behavior leads to the sickest patients receiving the best transplants, and causes relatively healthy patients to become sicker over time, reducing overall welfare. Improvements in overall welfare come at a tradeoff: offering transplants to healthier patients increases total survival time and prevents some patients from becoming sicker, but harms the sickest patients. The value of this tradeoff depends on society's preferences toward different bundles of survival times. In a novel incentivized survey, I elicit these preferences by having subjects choose how to allocate a real organ transplant among sick cats with different life expectancies. I then measure how preferences toward survival distributions relate to preferences toward fairness, risk, and temporal discounting.

OTHER-REGARDING PREFERENCES AND PATERNALISTIC DISCRIMINATION IN HIRING (WITH NINA BUCHMANN AND SUHANI JALOTA)

Work in Progress

Do norms aimed at protecting women actually increase gender discrimination in hiring? We develop a model that generates testable predictions to detect other-regarding preferences in hiring. We define paternalistic discrimination as a form of other-regarding preference in which employers hire men to protect female candidates from jobs perceived as harmful or difficult. We then document other-regarding preferences and paternalistic discrimination in a series of hiring experiments where jobs are designed to vary systematically in their perceived harm to women. Finally, we estimate the share of gender discrimination resulting from other-regarding preferences, and use survey data to benchmark the magnitude of paternalistic discrimination in a variety of industries.

 

EDUCATION

PHD IN APPLIED ECONOMICS

May 2019

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

Harvard University

May 2014

AB IN ECONOMICS; POLITICAL SCIENCE

The University of Chicago

June 2009

 

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