Working Papers:

Goals, Constraints, and Public Assignment: A Field Study of the UEFA Champions League

(with Marta Boczon)

Paper (Febuary 2020), revise & resubmit at Management Science

We analyze a matching mechanism developed to solve a complex constrained-assignment problem, where the entire randomization needs to be transparent to an outside observer. The application (the UEFA Champions League tournament draw) is high stakes; participants' expected outcomes can shift by millions of euro depending on the draw's realization. Moreover, for a centralized assignment with nontrivial constraints, the draw brings in a huge audience, with at least a million following along from around the world. After quantifying the constraint effects, we turn to a normative assessment: Are there better, fairer procedures? Relying upon a combination of theory, structural estimation, and simulation, we outline a quantitative methodology aimed at assessing the transparent assignment procedure developed by UEFA. Our analysis indicates that the mechanism comes quantitatively close to a constrained-best in fairness terms. Moreover, we demonstrate that while substantially better mechanisms do not exist given the current constraint structure, it is possible to substantially reduce matching distortions by only marginally slacking the constraints.

Additional details:

Online Appendix

Top of the Batch: Interviews and the Match

(with Federico Echenique, Ruy Gonzalez and Leeat Yariv)

Paper (February 2020)

Most doctors in the NRMP are matched to one of their most-preferred internship programs. This suggests a puzzle: high match ranks are difficult to reconcile with any commonality in doctors' preferences, as documented in various surveys. We provide one possible explanation for the puzzle. We show that the patterns observed in the NRMP data may be an artifact of the interview process that precedes the match. Our analysis highlights the importance of interactions occurring outside of a matching clearinghouses for resulting outcomes, and casts doubts on analysis of clearinghouses that take reported preferences at face value.

Belief Elicitation: Limiting Truth Telling with Information on Incentives

(with David Danz and Lise Vesterlund)

Paper (January 2020)

Belief elicitation is central to inference on economic decision making. The recently introduced Binarized Scoring Rule (BSR) is heralded for its robustness to individuals holding risk averse preferences and for its superior performance when eliciting beliefs. Consequently, the BSR has become the state-of-the-art mechanism. We study truth telling under the BSR and examine whether information on the offered incentives improves reports about a known objective prior. We find that transparent information on incentives gives rise to error rates in excess of 40 percent, and that only 15 percent of participants consistently report the truth. False reports are conservative and appear to result from a biased perception of the BSR incentives. While attempts to debias are somewhat successful, the highest degree of truth telling occurs when information on quantitative incentives is withheld. Consistent with incentives driving false reports, we find that slow release of information decreases truth telling. Perversely, our results suggest that information on the BSR incentives substantially distorts reported beliefs.

Additional details:


Costly Communication in Groups: Theory and an Experiment

Paper (February 2014), reject & resubmit at Games and Economic Behavior

I develop a novel model of group-based communication in which group members communicate with one another. Communication is costly in the sense that group members who choose to send or listen to messages incur costs. Equilibrium strategies have an intuitive characterization - those with the best information send, those with the worst information receive. Free-riding leads to less information exchange than is optimal, but a simple system of transfers and subsidies can correct this. Examining the model's predictions with an experiment I find that subjects over-communicate when costs are high, but fail to benefit from this as much as they should. Additionally, I find that listening costs are more harmful to welfare, in contrast with the theory which indicates sending costs.

Preference Reversals between One-Shot and Repeated Decisions: The Case of Regret

(with Alex Imas and Diego Lamé).

Paper (February, 2017), revise and resubmit at The Economic Journal

Under regret theory, decision-makers derive utility both from the outcome of their chosen action and the counterfactual. Evidence for anticipatory regret aversion has been found in one-shot settings, with "regret lotteries" that provide counterfactual information being valued higher than more-standard lotteries. These one-shot findings have motivated a literature that advocates the use of regret as a policy tool to boost incentives for behaviors such as exercise and drug adherence, often as recurrent decisions. However, differences in learning opportunities and the interaction between anticipated and realized regret make the consequences of regret in repeated settings far from clear. Through a series of controlled experiments, we replicate the one-shot result that regret lotteries have higher valuations than standard lotteries. In contrast, for sequential repeated decisions, the pattern reverses. For repeated decisions, regret lotteries are valued significantly less than standard lotteries, from the very first decision and onwards. Our results serve to highlight the issues that can arise when extrapolating behavioral effects from one-shot to repeated settings.

Additional details:


Paired-Uniform Scoring: Implementing a binarized scoring rule with non-mathematical language

(with Emanuel Vespa).

Paper (October, 2017)

We outline a mechanism for eliciting probabilities using two uniform random numbers that is equivalent to the binarized scoring rule (BSR). Though our implementation is simple to describe and has a non-mathematical explanation, it retains the desirable theoretical features of the BSR. Moreover, we show that a discretized version with evenly-spaced reporting intervals can be implemented in the field with no more equipment than a pair of dice.

The Times They are a-Changing: Dynamic Adverse Selection in the Laboratory

(with Felipe Araujo and Stephanie Wang).

Paper (April, 2018), revise and resubmit at AEJ:Micro

Across a variety of contexts decision-makers exhibit a robust failure to understand the interaction of private information and strategy, with one prominent example being the winner's curse. Such failures have generally been observed in static settings, where participants fail to think through a future hypothetical. We use a laboratory experiment to examine a common-value matching environment where strategic thinking is entirely backward looking, and adverse selection is a dynamic, non-stationary process. Our results indicate the majority of subjects in our environment use a sub-optimal stationary response -- even after extended experience and feedback. In terms of learning, even stationary subjects learn to adjust their behavior in response to the adverse selection, though adjusting their unconditional response. In contrast the minority using non-stationary responses do so very quickly, reflecting an introspective rather than learned solution to the problem.

Work in Progress:

Laws of Large Numbers and Risk Preferences

(with Felipe Araujo and Alex Imas)

Dynamic Games and Teams

(with John Kagel and Emanuel Vespa)

Strategic Uncertainty in Dynamic Games

(with Emanuel Vespa)

Competition and Communication: An Experiment

(with Emanuel Vespa)

An Elicitation Horse Race (Where the Blinkered Horse Win by a Nose)

(with David Danz, Lise Vesterlund and my experimental class)

Paying it forward: An experiment on an experimental college financing

(with David Danz, David Huffman, Lise Vesterlund and Stephanie Wang)