Social Learning Equilibria
Abstract
We consider a large class of social learning models in which a group of agents face uncertainty regarding a state of the world, share the same utility function, observe private signals, and interact in a general dynamic setting. We introduce social learning equilibria, a static equilibrium concept that abstracts away from the details of the given extensive form, but nevertheless captures the corresponding asymptotic equilibrium behavior. We establish general conditions for agreement, herding, and information aggregation in equilibrium, highlighting a connection between agreement and information aggregation.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2020
- Source ID
- 10.3982/ecta16465
Entities
People
- Allan Sly
- Elchanan Mossel
- Manuel Mueller-frank
- Omer Tamuz
Organizations
- California Institute of Technology
- IESE Business School
- Massachusetts Institute of Technology
- Ministry of Economy, Industry and Competitiveness
- National Science Foundation
- Office of Naval Research
- Princeton University
- Simons Foundation