Annie Liang

Assistant Professor, Northwestern University

Department of Economics (primary) and Department of Computer Science

My research is in economic theory (in particular, learning and information), and the application of machine learning methods for model building and evaluation. Prior to joining Northwestern, I was an Assistant Professor of Economics at the University of Pennsylvania.

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Kellogg Global Hub, Office 3361

2211 Campus Drive

Evanston, Illinois 60208

Email: annie.liang at


Refereed Articles

1. Measuring the Completeness of Economic Models, joint with Drew Fudenberg, Jon Kleinberg and Sendhil Mullainathan, Forthcoming at Journal of Political Economy,  presented at EC'17

2. Dynamically Aggregating Diverse Information, with Xiaosheng Mu and Vasilis Syrgkanis, Forthcoming at Econometrica, (to be) presented at EC'21 [slides] [talk]

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

4. Predicting and Understanding Initial Play, American Economic Review, Vol. 109 (12), Pages 4112-4141, December 2019 (with Drew Fudenberg), presented at EC'19 (plenary) [slides] [talk]

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

6. Optimal and Myopic Information Acquisition, with Xiaosheng Mu and Vasilis Syrgkanis, Proceedings of the 2018 ACM Conference on Economics and Computation, 2018. [talk]

Invited Surveys

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

Working Papers

8. How Flexible is that Functional Form? Quantifying the Restrictiveness of Theories, with Drew Fudenberg and Wayne Gao (latest draft: February, 2021), (to be) presented at EC'21

9. Data and Incentives, joint with Erik Madsen (latest draft: June, 2021), presented at EC'20