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Equitable Auction Design: With and Without Distributions

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  • Ruiqin Wang
  • Cagil Kocyigit
  • Napat Rujeerapaiboon

Abstract

We study a mechanism design problem where a seller aims to allocate a good to multiple bidders, each with a private value. The seller supports or favors a specific group, referred to as the minority group. Specifically, the seller requires that allocations to the minority group are at least a predetermined fraction (equity level) of those made to the rest of the bidders. Such constraints arise in various settings, including government procurement and corporate supply chain policies that prioritize small businesses, environmentally responsible suppliers, or enterprises owned by historically disadvantaged individuals. We analyze two variants of this problem: stochastic mechanism design, which assumes bidders' values follow a known distribution and seeks to maximize expected revenue, and regret-based mechanism design, which makes no distributional assumptions and aims to minimize the worst-case regret. We characterize a closed-form optimal stochastic mechanism and propose a closed-form regret-based mechanism, and establish that the ex-post regret under the latter is at most a constant multiple (dependent on the equity level) of the optimal worst-case regret. We further quantify that this approximation constant is at most 1.31 across different equity levels. Both mechanisms can be interpreted as set-asides, a common policy tool that reserves a fraction of goods for minority groups. Furthermore, numerical results demonstrate that the stochastic mechanism performs well when the bidders' value distribution is accurately estimated, while the regret-based mechanism exhibits greater robustness under estimation errors.

Suggested Citation

  • Ruiqin Wang & Cagil Kocyigit & Napat Rujeerapaiboon, 2025. "Equitable Auction Design: With and Without Distributions," Papers 2502.08369, arXiv.org.
  • Handle: RePEc:arx:papers:2502.08369
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    References listed on IDEAS

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    1. Çağıl Koçyiğit & Daniel Kuhn & Napat Rujeerapaiboon, 2024. "Regret Minimization and Separation in Multi-Bidder, Multi-Item Auctions," INFORMS Journal on Computing, INFORMS, vol. 36(6), pages 1543-1561, December.
    2. Susan Athey & Dominic Coey & Jonathan Levin, 2013. "Set-Asides and Subsidies in Auctions," American Economic Journal: Microeconomics, American Economic Association, vol. 5(1), pages 1-27, February.
    3. Kirk Bansak & Elisabeth Paulson, 2024. "Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing," Operations Research, INFORMS, vol. 72(6), pages 2375-2390, November.
    4. Dirk Bergemann & Karl H. Schlag, 2012. "Pricing Without Priors," World Scientific Book Chapters, in: Robust Mechanism Design The Role of Private Information and Higher Order Beliefs, chapter 12, pages 405-415, World Scientific Publishing Co. Pte. Ltd..
    5. Alireza Fallah & Michael I. Jordan & Annie Ulichney, 2024. "Fair Allocation in Dynamic Mechanism Design," Papers 2406.00147, arXiv.org, revised Oct 2024.
    6. Christian Ewerhart, 2013. "Regular type distributions in mechanism design and $$\rho $$ -concavity," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 53(3), pages 591-603, August.
    7. Mallesh Pai & Rakesh Vohra, 2012. "Auction Design with Fairness Concerns: Subsidies vs. Set-Asides," Discussion Papers 1548, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    8. Zhi Chen & Zhenyu Hu & Ruiqin Wang, 2024. "Screening with Limited Information: A Dual Perspective," Operations Research, INFORMS, vol. 72(4), pages 1487-1504, July.
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