Literature DB >> 28696293

Bayesian markets to elicit private information.

Aurélien Baillon1.   

Abstract

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.

Entities:  

Keywords:  Bayesianism; economic incentives; mechanism design; prediction markets; truth telling

Year:  2017        PMID: 28696293      PMCID: PMC5544302          DOI: 10.1073/pnas.1703486114

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  8 in total

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Authors:  Leslie K John; George Loewenstein; Drazen Prelec
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Journal:  Proc Natl Acad Sci U S A       Date:  2015-11-09       Impact factor: 11.205

3.  A Bayesian truth serum for subjective data.

Authors:  Drazen Prelec
Journal:  Science       Date:  2004-10-15       Impact factor: 47.728

4.  Price dynamics in political prediction markets.

Authors:  Saikat Ray Majumder; Daniel Diermeier; Thomas A Rietz; Luís A Nunes Amaral
Journal:  Proc Natl Acad Sci U S A       Date:  2009-01-20       Impact factor: 11.205

5.  Economics. The promise of prediction markets.

Authors:  Kenneth J Arrow; Robert Forsythe; Michael Gorham; Robert Hahn; Robin Hanson; John O Ledyard; Saul Levmore; Robert Litan; Paul Milgrom; Forrest D Nelson; George R Neumann; Marco Ottaviani; Thomas C Schelling; Robert J Shiller; Vernon L Smith; Erik Snowberg; Cass R Sunstein; Paul C Tetlock; Philip E Tetlock; Hal R Varian; Justin Wolfers; Eric Zitzewitz
Journal:  Science       Date:  2008-05-16       Impact factor: 47.728

Review 6.  Maximization, learning, and economic behavior.

Authors:  Ido Erev; Alvin E Roth
Journal:  Proc Natl Acad Sci U S A       Date:  2014-07-14       Impact factor: 11.205

7.  Evaluating replicability of laboratory experiments in economics.

Authors:  Colin F Camerer; Anna Dreber; Eskil Forsell; Teck-Hua Ho; Jürgen Huber; Magnus Johannesson; Michael Kirchler; Johan Almenberg; Adam Altmejd; Taizan Chan; Emma Heikensten; Felix Holzmeister; Taisuke Imai; Siri Isaksson; Gideon Nave; Thomas Pfeiffer; Michael Razen; Hang Wu
Journal:  Science       Date:  2016-03-03       Impact factor: 47.728

8.  Measuring utility by a single-response sequential method.

Authors:  G M Becker; M H DeGroot; J Marschak
Journal:  Behav Sci       Date:  1964-07
  8 in total
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Review 1.  Human social sensing is an untapped resource for computational social science.

Authors:  Mirta Galesic; Wändi Bruine de Bruin; Jonas Dalege; Scott L Feld; Frauke Kreuter; Henrik Olsson; Drazen Prelec; Daniel L Stein; Tamara van der Does
Journal:  Nature       Date:  2021-06-30       Impact factor: 49.962

  1 in total

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