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Binary Mechanisms under Privacy-Preserving Noise

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  • Farzad Pourbabaee
  • Federico Echenique

Abstract

We study mechanism design for public-good provision under a noisy privacy-preserving transformation of individual agents' reported preferences. The setting is a standard binary model with transfers and quasi-linear utility. Agents report their preferences for the public good, which are randomly ``flipped,'' so that any individual report may be explained away as the outcome of noise. We study the tradeoffs between preserving the public decisions made in the presence of noise (noise sensitivity), pursuing efficiency, and mitigating the effect of noise on revenue.

Suggested Citation

  • Farzad Pourbabaee & Federico Echenique, 2023. "Binary Mechanisms under Privacy-Preserving Noise," Papers 2301.06967, arXiv.org, revised May 2024.
    • Handle: RePEc:arx:papers:2301.06967
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    References listed on IDEAS

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    1. Alex Rees-Jones & Samuel Skowronek, 2018. "An experimental investigation of preference misrepresentation in the residency match," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(45), pages 11471-11476, November.
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    3. Daniel McFadden, 2009. "The human side of mechanism design: a tribute to Leo Hurwicz and Jean-Jacque Laffont," Review of Economic Design, Springer;Society for Economic Design, vol. 13(1), pages 77-100, April.
    4. Rees-Jones, Alex, 2018. "Suboptimal behavior in strategy-proof mechanisms: Evidence from the residency match," Games and Economic Behavior, Elsevier, vol. 108(C), pages 317-330.
    5. Daniel McFadden, 2009. "The human side of mechanism design: a tribute to Leo Hurwicz and Jean-Jacques Laffont (Publisher’s Erratum)," Review of Economic Design, Springer;Society for Economic Design, vol. 13(4), pages 377-377, December.
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