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Bayesian markets to elicit private information
Journal article   Open access

Bayesian markets to elicit private information

Aurélien Baillon
Proceedings of the National Academy of Sciences, Vol.114(30), pp.7958-7962
25/07/2017

Abstract

Predictive maintenance economic incentives truth telling mechanism design Bayesianism
"Financial markets reveal what investors think about the future, and prediction markets are used to forecast election results. Could markets also encourage people to reveal private information, such as subjective judgments (e.g., “Are you satisfied with your life?”) or unverifiable facts? This paper shows how to design such markets, called Bayesian markets. People trade an asset whose value represents the proportion of affirmative answers to a question. Their trading position then reveals their own answer to the question. The results of this paper are based on a Bayesian setup in which people use their private information (their “type”) as a signal. Hence, beliefs about others’ types are correlated with one’s own type. Bayesian markets transform this correlation into a mechanism that rewards truth telling. These markets avoid two complications of alternative methods: they need no knowledge of prior information and no elicitation of metabeliefs regarding others’ signals."
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https://doi.org/10.1073/pnas.1703486114View
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Citation topics
4 Electrical Engineering, Electronics & Computer Science
4.48 Knowledge Engineering & Representation
4.48.1974 Crowdsourcing and Crowdsensing
Web of Science research areas
Economics
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