The Wisdom of a (Confused) Crowd: Model-Based Inference
“Crowds” are often regarded as ``wiser’‘ than individuals, and prediction markets are often regarded as effective methods for harnessing this wisdom. If the agents in prediction markets are Bayesians who share a common model and prior belief, then the no-trade theorem implies that we should see no trade in the market. But if the agents in the market are not Bayesians who share a common model and prior belief, then it is no longer obvious that the market outcome aggregates or conveys information. In this paper, we examine a stylized prediction market comprised of Bayesian agents whose inferences are based on different models of the underlying environment. We explore a basic tension—-the differences in models that give rise to the possibility of trade generally preclude the possibility of perfect information aggregation.

Please sign up for meetings below:
Date: 15 February 2019, 14:15 (Friday, 5th week, Hilary 2019)
Venue: Manor Road Building, Manor Road OX1 3UQ
Venue Details: Seminar Room A
Speaker: Larry Samuelson (Yale University)
Organising department: Department of Economics
Part of: Nuffield Economic Theory Seminar
Booking required?: Not required
Audience: Members of the University only
Editor: Melis Boya