Working papers
Coarse Information Design (with Wing Suen and Yimeng Zhang), 2026
(NEW!!!) Revivse and Resubmit at Journal of Political Economy
We study an information design problem with continuous state and discrete signal space. Under convex and S-shaped value functions, the optimal information structure is interval-partitional and exhibits a dual expectations property: each induced signal is the conditional mean (taken under the prior density) of each interval; and each interval cutoff is the barycenter (taken under the value function curvature) of the interval formed by neighboring signals. This property enables an examination into which part of the state space is more finely partitioned. The analysis can be extended to general value functions and adapted to study coarse mechanism design.
(NEW!!!) Revivse and Resubmit at Journal of Political Economy
We study an information design problem with continuous state and discrete signal space. Under convex and S-shaped value functions, the optimal information structure is interval-partitional and exhibits a dual expectations property: each induced signal is the conditional mean (taken under the prior density) of each interval; and each interval cutoff is the barycenter (taken under the value function curvature) of the interval formed by neighboring signals. This property enables an examination into which part of the state space is more finely partitioned. The analysis can be extended to general value functions and adapted to study coarse mechanism design.
Complete Contracts under Incomplete Information (with Gregorio Curello and Yimeng Zhang), Draft in Progress
We study a moral hazard model in which the output is stochastically determined by an agent's hidden effort and an uncertain state. We examine how the contractibility of ex-post state observations shapes the principal's optimal information provision. The principal faces a trade-off: finer information allows for effort levels to be tailored to the realized state (information efficiency), whereas coarser information enables the principal to aggregate the agent's incentives across states to reduce agency costs (cost-saving effect).Under complete contracts where the state is ex-post contractible, the cost-saving effect locally dominates information efficiency, rendering complete information strictly suboptimal. Conversely, under incomplete contracts where the state is not ex-post contractible, this dominance can reverse and complete information may become strictly optimal.
We study a moral hazard model in which the output is stochastically determined by an agent's hidden effort and an uncertain state. We examine how the contractibility of ex-post state observations shapes the principal's optimal information provision. The principal faces a trade-off: finer information allows for effort levels to be tailored to the realized state (information efficiency), whereas coarser information enables the principal to aggregate the agent's incentives across states to reduce agency costs (cost-saving effect).Under complete contracts where the state is ex-post contractible, the cost-saving effect locally dominates information efficiency, rendering complete information strictly suboptimal. Conversely, under incomplete contracts where the state is not ex-post contractible, this dominance can reverse and complete information may become strictly optimal.
Information Design in Cheap Talk (with Wing Suen), 2025
An uninformed sender publicly commits to an informative experiment about an uncertain state, privately observes its outcome, and sends a cheap-talk message to a receiver. We provide an algorithm valid for arbitrary state-dependent preferences that will determine the sender's optimal experiment and his equilibrium payoff under binary state space. We give sufficient conditions for informative information transmission. These conditions depend more on marginal incentives---how payoffs vary with the state---than on the alignment of sender's and receiver's rankings over actions within a state. The algorithm can be easily modified to study the canonical cheap talk game with a perfectly informed sender.
An uninformed sender publicly commits to an informative experiment about an uncertain state, privately observes its outcome, and sends a cheap-talk message to a receiver. We provide an algorithm valid for arbitrary state-dependent preferences that will determine the sender's optimal experiment and his equilibrium payoff under binary state space. We give sufficient conditions for informative information transmission. These conditions depend more on marginal incentives---how payoffs vary with the state---than on the alignment of sender's and receiver's rankings over actions within a state. The algorithm can be easily modified to study the canonical cheap talk game with a perfectly informed sender.
Publications
Optimal Refund Mechanism with Consumer Learning (Working paper version)
RAND Journal of Economics, Feb, 2026
RAND Journal of Economics, Feb, 2026
Archived
Optimal Experiment with Private Repetition (with Zheng Gong)