with Yingkai Li (Last update: November 2023) 

We characterize when a principal, seeking to induce an agent to acquire information over time and able to condition rewards on outcomes, should simply elicit a single report after acquiring information.

Yingkai is on the job market this year and your department should hire him.

with Zihao Li (Last update: October 2023)

In a dynamic principal-agent project selection problem where transfers cannot be used and quality can be verified at a (sufficiently low) cost, optimal verification dynamics are characterized by "increasing trust."

with Ruozi Song (Last update: September 2023)

An Electric Vehicle (EV)-based ridesharing program in Los Angeles led to an increase in EV purchases, despite being a direct substitute to car ownership. We argue information externalities are responsible.

with Kevin He (Last update: September 2023) Presented @ EC '21

We introduce a selection criterion on behavioral biases in environments with learning, and show that it need not select for a bias-free worldview in some common applications.

with Beatrice Michaeli and Elyashiv Wiedman (Last update: August 2023)

We study dynamic disclosure when an exogenous public signal may or may not reflect noise. This uncertainty creates an asymmetry in the market's interpretation of news; if equilibrium involves pre-emptive disclosure, prices may drop discontinuously as news improves

with In-Koo Cho (Last Update: July 2023) R&R @ Journal of Economic Theory

We present an algorithm which, by positing linear demand, allows the monopolist to learn the optimal price even if demand is non-linear.

with Eliot Abrams and John A. List (Last update: July 2023)

We empirically study registries, focusing mostly (but not exclusively) on the AEA RCT Registry, and theoretically discuss issues related to incentives behind registration.

The Mathematica notebook which we used in our calibration exercise can be found here, while the Mathematica notebook that checks our monotonicity condition can be found here.

with Duarte Gonçalves and Jack Willis (Last update: February 2023) R&R @ Review of Economic Studies

We conduct an experiment on belief updating and document that subjects under-react to information when it is in the form of a retraction.

(Last update: January 2023)

I demonstrate how to recover a decisionmaker's information structure from posterior beliefs over states, together with posterior beliefs that each signal could be observed. In the process, I make new observations on the geometric structure of information.