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Bayesian markets to elicit private information.

Aurélien Baillon1

  • 1Erasmus School of Economics, Erasmus University Rotterdam, 3000 DR Rotterdam, The Netherlands baillon@ese.eur.nl.

Proceedings of the National Academy of Sciences of the United States of America
|July 12, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces Bayesian markets, a novel mechanism for eliciting private information. These markets incentivize truthful revelation of subjective judgments and unverifiable facts through asset trading.

Keywords:
Bayesianismeconomic incentivesmechanism designprediction marketstruth telling

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Area of Science:

  • Decision Sciences
  • Behavioral Economics
  • Information Economics

Background:

  • Financial markets forecast future events.
  • Prediction markets predict election outcomes.
  • Existing markets struggle to elicit private, subjective information.

Purpose of the Study:

  • To design a market mechanism, termed Bayesian markets, for eliciting private information.
  • To enable the revelation of subjective judgments and unverifiable facts.
  • To create a system rewarding truthful information disclosure.

Main Methods:

  • Designed Bayesian markets where participants trade assets.
  • Asset value represents the proportion of affirmative answers to a question.
  • Utilized a Bayesian framework where private information (type) acts as a signal.

Main Results:

  • Trading positions in Bayesian markets reveal participants' private information.
  • The market design transforms correlated beliefs about others' types into truth-telling incentives.
  • Bayesian markets do not require prior information or elicitation of metabeliefs.

Conclusions:

  • Bayesian markets offer a novel and effective method for eliciting private information.
  • This mechanism incentivizes honest reporting of subjective judgments and unverifiable facts.
  • The design overcomes limitations of previous information-elicitation methods.