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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:
docs.google.com/spreadsheets/d/1ywTkCR-sjBInsVwaWA_M7D2iF7QamyiaLY0qYxR1NOM/edit#gid=0
Date:
15 February 2019, 14:15
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 Clark
