I'm an assistant professor of finance at the UChicago Booth School of Business. I work on market design, and my research covers topics such as financial derivatives, housing markets, bilateral bargaining, and the allocation of natural resource use rights. My CV is here, and you can reach me at email@example.com.
This paper develops methods and metrics for quantifying manipulation risk in cash-settled derivative contract markets. I show how to estimate market participants' manipulation incentives, and predict manipulation-induced market distortions, using commonly observed market data. I develop a simple manipulation index, which can be used as a diagnostic metric to detect potentially manipulable contract markets, similar to the Herfindahl-Hirschman index (HHI) in antitrust settings. I apply my results to estimate manipulation risk in a number of contract markets.
(This is a revised version of the first half of my job market paper. The JMP version and online appendix, from December 2018, is longer and contains material which will be incorporated into my work-in-progress paper "A Bayesian Volatility Index".)
Media: Chicago Booth Review
A Mechanism Design Approach to Identification and Estimation, with Brad Larsen, July 2018.
In many trading games, agents take actions which affect the probability that they receive a good and monetary transfer payments they make or receive. In this paper, we show that agents' choices on a menu of probabilities and transfers available in equilibrium can be used to identify agents' values in many such trading games. This "empirical menu" approach can accomodate various extensions, such as certain kinds of unobserved heterogeneity and partially observed actions. We apply these results to study bargaining efficiency, competition and surplus division in used car bargaining.
Search Frictions and Idiosyncratic Price Dispersion in the US Housing Market, with Nadia Kotova, May 2019.
This paper studies the sources of idiosyncratic house price dispersion. We construct a search-and-bargaining model of the housing market, which predicts that idiosyncratic price dispersion should be positively correlated with time-on-market and negatively correlated with house prices and sales volume. Using a methodology which combines repeat-sales and hedonic approaches, we measure idiosyncratic price dispersion across locations and over time. We show that idiosyncratic price dispersion is countercyclical and seasonal, and that it is associated with prices, sales volume, and time-on-market in the directions predicted by our model, cross-sectionally as well as in panel regressions.
Perpetual licenses incent owners to invest in the common value of public resources, but impede efficient reallocation of resources to higher-valued entrants. Short-term licenses improve allocative efficiency but discourage investment. We propose a depreciating license that improves on this tradeoff. Licensees periodically announce valuations at which they commit to sell their licenses, and pay a percent of these valuations as license fees. Depreciating licenses produce time-stationary investment incentives while encouraging truthful value revelation that improves allocative efficiency. The only tuning parameter, the depreciation rate, can be chosen appropriately by targeting the observed equilibrium frequency of license turnover.
Implementability, Walrasian Equilibria, and Efficient Matchings, with Piotr Dworczak, Economics Letters, 2017, 153 pp. 57–60.
A Bayesian Volatility Index
Subsidies and Taxes in Double Auctions, with Daniel Chen
A Machine Learning Approach to Bargaining Game Estimation, with Brad Larsen