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Dynamically Aggregating Diverse Information

Speaker: Annie Liang (Assistant Professor, Northwestern University)

Host: National School of Development, Peking University

TimeApril 29 Thusday, 10:30-12:00

Zoom:ID963 7895 5301, PW:941315

An agent has access to multiple information sources, each of which provides information about a different attribute of an unknown state. Information is acquired continuously---where the agent chooses both which sources to sample from, and also how to allocate attention across them---until an endogenously chosen time, at which point a decision is taken. We provide an exact characterization of the optimal information acquisition strategy under weak conditions on the agent's prior belief about the different attributes. We then apply this characterization to derive new results regarding: (1) endogenous information acquisition for binary choice, (2) strategic information provision by biased news sources, and (3) the dynamic consequences of attention manipulation.

Annie Liang is an Assistant Professor of Economics and the Karr Family Assistant Professor of Computer Science at Northwestern University.  She is an economic theorist whose work focuses on information economics, and the application of machine learning techniques for model building and evaluation. Annie received her Ph.D. in Economics from Harvard in 2016. Prior to joining Northwestern, she previously held positions as a postdoctoral researcher at Microsoft Research-New England and as an Assistant Professor of Economics at the University of Pennsylvania. She has published in leading economics journals, including American Economic Review, Quarterly Journal of Economics and Journal of Economic Theory.