Beixi Zhou


I am a Visiting Assistant Professor of Economics at the University of Pittsburgh. 

My research field is game theory, with a focus on dynamic games.


Email: beixi.zhou@pitt.edu

CV: [PDF]

Research

Optimal Disclosure Windows (Online Appendix)

I study a dynamic disclosure game in which an agent controls the time window over which information flows to the decision maker, but does not control the content of that information. In equilibrium, the agent has incentives to delay the start of disclosure to continue to learn privately for some time. This delay exacerbates the information asymmetry between the agent and the decision maker as the agent is learning while the decision maker is not. This information asymmetry is then (partially) resolved during the disclosure window. The length of the disclosure window is determined by the degree of information asymmetry at the beginning of the window, with longer windows associated with greater information asymmetry.


Dynamic Coordination with Payoff and Informational Externalities (Online Appendix)

Games and Economic Behavior, 2024, 144, 141-166

I study a two-player continuous-time dynamic coordination game with observational learning. Each player has one opportunity to make a reversible investment with an uncertain return that is realized only when both players invest. Each player learns about the potential return by observing a private signal and the actions of the other player. In equilibrium, players' roles as leader and follower are endogenously determined. Information aggregates in a single burst initially, then gradually through delayed investment and disinvestment over time. More precise signals lead to faster coordination conditional on initial disagreement, but might also increase the probability of initial disagreement.


Causation and Incentives with Updating Courts (with Keith Hylton)

Journal of Institutional and Theoretical Economics, 2020, 176(1), 123-146

This paper examines the negligence standard in the presence of intervening causal factors. The court observes the evidence and assigns a probability to the intervening factor in the course of evaluating the injurer’s negligence. The court must, under the law, put a substantial weight on the facts in estimating the intervention probability. We allow the court to also put some weight on its own prior. Under such an adaptive approach to assessing negligence, incentives for care are affected by the court’s inference process in addition to the usual factors. Courts can generate efficient incentives for care through the choice of prior. 


Mediated Efficiency in Moral Hazard Mixing Games (with Allen Vong)

Sharing Data (with Allen Vong)

Teaching

University of Pittsburgh

Boston University