Annie Liang

I am an Assistant Professor of Economics at the University of Pennsylvania. (I am on leave at Harvard for Fall, 2020.)

My research is in economic theory (in particular, learning and information), and the application of machine learning methods for model building and evaluation.

The Ronald O. Perelman Center (Office 501)

133 South 36th Street
Philadelphia, PA 19104


I've had the pleasure of working with Drew Fudenberg, Wayne Gao, Jon Kleinberg, Erik Madsen, Xiaosheng Mu, Sendhil Mullainathan, and Vasilis Syrgkanis.



1. Complementary Information and Learning Traps, Quarterly Journal of Economics, Vol. 135 (1), Pages 389-448, February 2020 (joint with Xiaosheng Mu), presented at EC'18

2. Predicting and Understanding Initial Play, American Economic Review, Vol. 109 (12), Pages 4112-4141, December 2019 (joint with Drew Fudenberg), presented at EC'19 (invited plenary session)

3. Inference of Preference Heterogeneity from Choice Data, Journal of Economic Theory, Vol. 179, Pages 275-311, January 2019

Invited Surveys

4. Machine Learning for Evaluating and Improving Theories, SIGEcom Exchanges, Vol. 18 (1), Pages 4-11, 2020 (joint with Drew Fudenberg)

Working Papers

5. How Flexible is that Functional Form? Quantifying the Restrictiveness of Theories, joint with Drew Fudenberg and Wayne Gao (latest draft: July, 2020)

6. Data and Incentives, joint with Erik Madsen (latest draft: April, 2020), accepted for presentation at EC'20

7. Dynamically Aggregating Diverse Information, joint with Xiaosheng Mu and Vasilis Syrgkanis (latest draft: April, 2020)

8. Measuring the Completeness of Theories, joint with Drew Fudenberg, Jon Kleinberg and Sendhil Mullainathan (latest draft: June, 2020), presented at EC'17

10. Optimal and Myopic Information Acquisitionjoint with Xiaosheng Mu and Vasilis Syrgkanis (latest draft: April, 2019), presented at EC'18