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Selling Impressions: Efficiency vs. Competition

Author

Listed:
  • Dirk Bergemann

    (Cowles Foundation, Yale University)

  • Tibor Heumann

    (Pontificia Universidad Católica de Chile)

  • Stephen Morris

    (Dept. of Economics, MIT)

  • Constantine Sorokin

    (Glasgow University and Higher School of Economics)

  • Eyal Winter

    (The Hebrew University of Jerusalem)

Abstract

In digital advertising, a publisher selling impressions faces a trade-off in deciding how precisely to match advertisers with viewers. A more precise match generates efficiency gains that the publisher can hope to exploit. A coarser match will generate a thicker market and thus more competition. The publisher can control the precision of the match by controlling the amount of information that advertisers have about viewers. We characterize the optimal trade-off when impressions are sold by auction. The publisher pools premium matches for advertisers (when there will be less competition on average) but gives advertisers full information about lower quality matches.

Suggested Citation

  • Dirk Bergemann & Tibor Heumann & Stephen Morris & Constantine Sorokin & Eyal Winter, 2021. "Selling Impressions: Efficiency vs. Competition," Cowles Foundation Discussion Papers 2300, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:2300
    as

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    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d23/d2300.pdf
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    References listed on IDEAS

    as
    1. Palfrey, Thomas R, 1983. "Bundling Decisions by a Multiproduct Monopolist with Incomplete Information," Econometrica, Econometric Society, vol. 51(2), pages 463-483, March.
    2. Bergemann, Dirk & Pesendorfer, Martin, 2007. "Information structures in optimal auctions," Journal of Economic Theory, Elsevier, vol. 137(1), pages 580-609, November.
    3. Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2017. "First‐Price Auctions With General Information Structures: Implications for Bidding and Revenue," Econometrica, Econometric Society, vol. 85, pages 107-143, January.
    4. Nick Arnosti & Marissa Beck & Paul Milgrom, 2016. "Adverse Selection and Auction Design for Internet Display Advertising," American Economic Review, American Economic Association, vol. 106(10), pages 2852-2866, October.
    5. Andreas Kleiner & Benny Moldovanu & Philipp Strack, 2021. "Extreme Points and Majorization: Economic Applications," Econometrica, Econometric Society, vol. 89(4), pages 1557-1593, July.
    6. Simon Board, 2009. "Revealing information in auctions: the allocation effect," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 38(1), pages 125-135, January.
    7. Juan-José Ganuza, 2004. "Ignorance Promotes Competition: An Auction Model of Endogenous Private Valuations," RAND Journal of Economics, The RAND Corporation, vol. 35(3), pages 583-598, Autumn.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2021. "Optimal Information Disclosure in Auctions," Cowles Foundation Discussion Papers 2318, Cowles Foundation for Research in Economics, Yale University.

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    More about this item

    Keywords

    Second Price Auction; Conflation; Targeted Advertising; Impressions; Two-Sided Private Information; Bayesian Persuasion; Information Design;
    All these keywords.

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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