Dynamically Aggregating Diverse Information
- Dr. Annie Liang, Northwestern University
- Time: 2021-03-05 23:00
- Host: Dr. Yuqing Kong
- Venue: Online Talk
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.
Joint work with Xiaosheng Mu and Vasilis Syrgkanis.
Annie Liang is an Assistant Professor of Economics and the Karr Family Assistant Professor of Computer Science at Northwestern University. Her work focuses on economic theory and the application of machine learning techniques in the social sciences. She has studied the dynamics of strategic information acquisition, as well as the use of machine learning to evaluate and improve economic models.