The Wisdom of a Confused Crowd: Model-Based Inference

George Mailath and Larry Samuelson ()
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Larry Samuelson: Cowles Foundation, Yale University, https://economics.yale.edu/people/faculty/larry-samuelson

No 2161, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: "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.

Keywords: Wisdom of the Crowd; Information aggregation; Common prior; NonBayesian updating (search for similar items in EconPapers)
JEL-codes: D8 (search for similar items in EconPapers)
Pages: 58 pages
Date: 2019-01
New Economics Papers: this item is included in nep-ore
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Citations: View citations in EconPapers (5)

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