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Bayesian implementation with verifiable information

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  • Peralta, Esteban

Abstract

This note studies the class of allocations that are fully Bayesian implementable in the presence of verifiable information. I identify a condition, termed evidence distinguishability, that together with incentive compatibility is both necessary and sufficient for full Bayesian implementation in direct mechanisms that elicit verifiable information. I show, however, that every evidence distinguishable allocation that is incentive compatible when verifiable information is not elicited is Bayesian monotonic at every verifiable deception; namely, at every verifiable joint report of information at which the direct mechanism delivers an undesirable outcome. To the extent that requiring Bayesian monotonicity to hold at every verifiable deception is a demanding condition, only indirect mechanisms can exploit the presence of verifiable information to fully implement incentive compatible allocations.

Suggested Citation

  • Peralta, Esteban, 2019. "Bayesian implementation with verifiable information," Games and Economic Behavior, Elsevier, vol. 116(C), pages 65-72.
    • Handle: RePEc:eee:gamebe:v:116:y:2019:i:c:p:65-72
    DOI: 10.1016/j.geb.2019.04.003
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    Cited by:

    1. Soumen Banerjee & Yi-Chun Chen, 2022. "Implementation with Uncertain Evidence," Papers 2209.10741, arXiv.org.

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    More about this item

    Keywords

    Mechanism design; Bayesian implementation; Verifiable information;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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