Annie Liang
I am an Assistant Professor of Economics (primary appointment) and the Karr Family Assistant Professor of Computer Science at Northwestern University.
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, and a postdoctoral researcher at Microsoft Research-New England.
Kellogg Global Hub, Office 3361
2211 Campus Drive
Evanston, Illinois 60208
Email: annie.liang at northwestern.edu
Publications
Refereed Articles
1. Measuring the Completeness of Economic Models
with Drew Fudenberg, Jon Kleinberg and Sendhil Mullainathan
Journal of Political Economy, Vol. 130 (4), Pages 956-990, April 2022
extended abstract at EC'17
2. Dynamically Aggregating Diverse Information
with Xiaosheng Mu and Vasilis Syrgkanis
Econometrica, Vol. 90 (1), Pages 47-80, January 2022
extended abstract at EC'21
3. Complementary Information and Learning Traps
with Xiaosheng Mu
Quarterly Journal of Economics, Vol. 135 (1), Pages 389-448, February 2020
extended abstract at EC'18
4. Predicting and Understanding Initial Play
with Drew Fudenberg
American Economic Review, Vol. 109 (12), Pages 4112-4141, December 2019
plenary talk at EC'19 ("Highlights Beyond EC" session)
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
Invited Surveys
7. Machine Learning for Evaluating and Improving Theories
with Drew Fudenberg
SIGEcom Exchanges, Vol. 18 (1), Pages 4-11, 2020
Working Papers
8. Data and Incentives
with Erik Madsen
R&R at Theoretical Economics
extended abstract at EC'20
latest draft: April, 2022
9. The Transfer Performance of Economic Models
with Isaiah Andrews, Drew Fudenberg, and Chaofeng Wu
latest draft: March, 2022
10. Algorithmic Design: Fairness Versus Accuracy
with Jay Lu and Xiaosheng Mu
latest draft: February, 2022
extended abstract at EC'22
11. How Flexible is that Functional Form? Quantifying the Restrictiveness of Theories
with Drew Fudenberg and Wayne Gao
extended abstract at EC'21, selected as the "Exemplary AI and Computation Track Paper"
latest draft: August, 2021
12. Games of Incomplete Information Played by Statisticians
latest draft: June, 2021