Xiaosheng's Site

Welcome to my website!

My name is Xiaosheng Mu, and I am an assistant professor in the Department of Economics at Princeton University. My research interests include information acquisition, mechanism design and various stochastic orders.

Prior to joining Princeton, I was an assistant professor of economics at Columbia University and a post-doctoral researcher at the Cowles Foundation at Yale University. I obtained my Ph.D. in economics from Harvard University, where I was advised by Drew Fudenberg, Eric Maskin and Tomasz Strzalecki.

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CV
Xiaosheng's CV
Working Papers
Monotone Additive Statistics, with Luciano Pomatto, Philipp Strack and Omer Tamuz (July 2021) R&R at Econometrica

Algorithmic Design: Fairness and Accruacy, with Annie Liang and Jay Lu (August 2022)

Stand Out from the Millions: Market Congestion and Information Friction on Global E-Commerce Platforms, with Jie Bai, Maggie Chen, Jin Liu and Daniel Yi Xu (April 2022)

Background Risk and Small-Stakes Risk Aversion, with Luciano Pomatto, Philipp Strack and Omer Tamuz (August 2022)

Sequential Choice with Incomplete Preferences (July 2021) R&R at Social Choice and Welfare

Paying (for) Attention: The Impact of Information Processing Costs on Bayesian Inference, with Scott D. Kominers and Alex Peysakhovich (January 2019) R&R at Games and Economic Behavior

Keeping Your Story Straight: Truthtelling and Liespotting, with Johannes Hörner and Nicolas Vieille (April 2017)
Publications
Dynamically Aggregating Diverse Information (with Annie Liang and Vasilis Syrgkanis) Econometrica, 90 (1): 47-90, 2022.

Bayesian Privacy (with Ran Eilat and Kfir Eliaz) Theoretical Economics, 16 (4): 1557-1603, 2021.

Informational Robustness in Intertemporal Pricing (with Jonathan Libgober) Review of Economic Studies, 88 (3): 1224-1252, 2021.

From Blackwell Dominance in Large Samples to Rényi Divergences and Back Again (with Luciano Pomatto, Philipp Strack and Omer Tamuz) Econometrica, 89 (1): 475-506, 2021.

Complementary Information and Learning Traps (with Annie Liang) Quarterly Journal of Economics, 135 (1): 389-448, 2020.

Optimal and Myopic Information Acquisition (with Annie Liang and Vasilis Syrgkanis) EC ’18, Proceedings of the 2018 ACM Conference on Economics and Computation, 2018.

Log-concavity of a Mixture of Beta Distributions. Statistics and Probability Letters, 99: 125-130, 2015.

Differentially Private and Incentive Compatible Recommendation System for the Adoption of Network Goods (with Kevin He) EC ’14, Proceedings of the 2014 ACM Conference on Economics and Computation, 2014.