Experimental Economics, Labor Economics, Market Design


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.

In fall 2021, I will join the Department of Economics in the Krannert School of Management at Purdue University.

View my CV here.

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Job Market Paper

Optimal allocation of scarce, life-saving medical treatment depends on society's preferences over survival distributions, governed by notions of equality and efficiency. In a novel experiment, I elicit preferences over survival distributions in incentivized, life-or-death decisions. Subjects allocate an organ transplant among real cats with kidney failure. In each choice, subjects allocate a single organ based on the expected survival of each patient. The survival rates imply a price ratio, allowing me to infer the shape of indifference curves over survival bundles. I find that the vast majority (80%) of subjects respond to increases in total expected survival time, while a small minority display Leontief preferences, providing the transplant to the shortest-lived patient at all price ratios. Hypothetical decisions may not be reliable in this context: a large share (46%) of subjects allocate a hypothetical transplant differently than a real transplant, though estimates of aggregate preferences are the same across incentivized and unincentivized conditions. Finally, I show that aversion to wealth inequality is a good predictor of aversion to survival inequality. 

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.


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.




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


Harvard University

May 2014


The University of Chicago

June 2009


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