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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. 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.
    2. Evans, Georgina & King, Gary, 2023. "Statistically Valid Inferences from Differentially Private Data Releases, with Application to the Facebook URLs Dataset," Political Analysis, Cambridge University Press, vol. 31(1), pages 1-21, January.
    3. Avinatan Hassidim & Assaf Romm & Ran I. Shorrer, 2021. "The Limits of Incentives in Economic Matching Procedures," Management Science, INFORMS, vol. 67(2), pages 951-963, February.
    4. Graeme Blair & Kosuke Imai & Yang-Yang Zhou, 2015. "Design and Analysis of the Randomized Response Technique," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1304-1319, September.
    5. Eric Budish & Judd B. Kessler, 2022. "Can Market Participants Report Their Preferences Accurately (Enough)?," Management Science, INFORMS, vol. 68(2), pages 1107-1130, February.
    6. Daniel Krähmer & Roland Strausz, 2023. "Optimal Nonlinear Pricing with Data-Sensitive Consumers," American Economic Journal: Microeconomics, American Economic Association, vol. 15(2), pages 80-108, May.
    7. repec:nas:journl:v:115:y:2018:p:11471-11476 is not listed on IDEAS
    8. Avinatan Hassidim & Déborah Marciano & Assaf Romm & Ran I. Shorrer, 2017. "The Mechanism Is Truthful, Why Aren't You?," American Economic Review, American Economic Association, vol. 107(5), pages 220-224, May.
    9. Alex Rees-Jones & Samuel Skowronek, 2018. "An Experimental Investigation of Preference Misrepresentation in the Residency Match," Papers 1802.01990, arXiv.org, revised Aug 2018.
    10. 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.
    11. 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.
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