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Power to Ignore: Locally Ordinal Bayesian Incentive Compatibility

Author

Listed:
  • Miho Hong

    (Yale Univ)

  • Semin Kim

    (Yonsei Univ)

Abstract

We investigate the locally ordinal notion of Bayesian incentive compatibility (LOBIC) of deterministic voting mechanisms. We consider a standard Bayesian environment where agents have private and strict preference orderings on a finite set of alternatives. Our main domains of preferences over alternatives are even larger than a broad class of domains — a few of its constituents being the unrestricted domain, the single-peaked domain, and the single-dipped domain. With independent and generic priors, we show that LOBIC of a mechanism combined with unanimity implies the tops-only property. Furthermore, we find a subclass of the domains where a mechanism with LOBIC and unanimity is dictatorial. We study the sufficiency of local incentive constraints for full incentive constraints and the relationship between LOBIC and dominant strategy incentive compatibility.

Suggested Citation

  • Miho Hong & Semin Kim, 2020. "Power to Ignore: Locally Ordinal Bayesian Incentive Compatibility," Working papers 2020rwp-170, Yonsei University, Yonsei Economics Research Institute.
    • Handle: RePEc:yon:wpaper:2020rwp-170
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    More about this item

    Keywords

    Incentive compatibility; Local incentive compatibility; Tops-only property; Dictatorship; Connected domains; Unanimity;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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