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General truthfulness characterizations via convex analysis

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  • Frongillo, Rafael M.
  • Kash, Ian A.

Abstract

We present a model of truthful elicitation which generalizes and extends mechanisms, scoring rules, and a number of related settings that do not qualify as one or the other. Our main result is a characterization theorem, yielding characterizations for all of these settings. This includes a new characterization of scoring rules for non-convex sets of distributions. We combine the characterization theorem with duality to give a simple construction to convert between scoring rules and randomized mechanisms. We also show how a generalization of this characterization gives a new proof of a mechanism design result due to Saks and Yu.

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  • Frongillo, Rafael M. & Kash, Ian A., 2021. "General truthfulness characterizations via convex analysis," Games and Economic Behavior, Elsevier, vol. 130(C), pages 636-662.
    • Handle: RePEc:eee:gamebe:v:130:y:2021:i:c:p:636-662
    DOI: 10.1016/j.geb.2021.09.010
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    Cited by:

    1. Rafael Frongillo, 2022. "Quantum Information Elicitation," Papers 2203.07469, arXiv.org.

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    More about this item

    Keywords

    Information elicitation; Mechanism design; Proper scoring rules; Implementability characterizations; Property elicitation; Convex analysis;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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