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Optimal Auctions With Signaling Bidders


  • Oliver Bos
  • Martin Pollrich


We study optimal auctions in a symmetric private values setting, where bidders’ care about winning the object and a receiver’s inference about their type. We reestablish revenue equivalence when bidders’ signaling concerns are linear, and the auction makes participation observable via an entry fee. With convex signaling concerns, optimal auctions are fully transparent: every standard auction, which reveals all bids yields maximal revenue. With concave signaling concerns there is no general revenue ranking. We highlight a trade-off between maximizing revenue derived from signaling, and extracting information from bidders. Our methodology combines tools from mechanism design with tools from Bayesian persuasion.

Suggested Citation

  • Oliver Bos & Martin Pollrich, 2020. "Optimal Auctions With Signaling Bidders," CRC TR 224 Discussion Paper Series crctr224_2020_158, University of Bonn and University of Mannheim, Germany.
  • Handle: RePEc:bon:boncrc:crctr224_2020_158

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    References listed on IDEAS

    1. Piotr Dworczak & Giorgio Martini, 2019. "The Simple Economics of Optimal Persuasion," Journal of Political Economy, University of Chicago Press, vol. 127(5), pages 1993-2048.
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    3. Friedrichsen, Jana, 2018. "Signals Sell: Product Lines when Consumers Differ Both in Taste for Quality and Image Concern," Rationality and Competition Discussion Paper Series 70, CRC TRR 190 Rationality and Competition.
    4. Philippe Jehiel & Benny Moldovanu, 2000. "Auctions with Downstream Interaction Among Buyers," RAND Journal of Economics, The RAND Corporation, vol. 31(4), pages 768-791, Winter.
    5. Piotr Dworczak, 2020. "Mechanism Design With Aftermarkets: Cutoff Mechanisms," Econometrica, Econometric Society, vol. 88(6), pages 2629-2661, November.
    6. Scarpatetti, Benedikt von & Wasser, Cédric, 2010. "Signaling in Auctions among Competitors," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 293, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    7. Milgrom, Paul R & Weber, Robert J, 1982. "A Theory of Auctions and Competitive Bidding," Econometrica, Econometric Society, vol. 50(5), pages 1089-1122, September.
    8. Benjamin R. Mandel, 2009. "Art as an Investment and Conspicuous Consumption Good," American Economic Review, American Economic Association, vol. 99(4), pages 1653-1663, September.
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    Cited by:

    1. Roland Bénabou & Armin Falk & Luca Henkel & Jean Tirole, 2020. "Eliciting Moral Preferences: Theory and Experiment," Working Papers 2020-17, Princeton University. Economics Department..
    2. Olivier Bos & Tom Truyts, 2021. "Auctions with signaling concerns," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 30(2), pages 420-448, May.
    3. Fugger, Nicolas & Gretschko, Vitali & Pollrich, Martin, 2022. "Information design in sequential procurement," Games and Economic Behavior, Elsevier, vol. 135(C), pages 79-85.
    4. Jibang Wu & Ashwinkumar Badanidiyuru & Haifeng Xu, 2021. "Auctioning with Strategically Reticent Bidders," Papers 2109.04888,

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    More about this item


    optimal auctions; revenue equivalence; Bayesian persuasion; information design;
    All these keywords.

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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