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Auctions for Online Display Advertising Exchanges: Approximations and Design

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Author Info

  • Santiago R. Balseiro

    ()
    (Graduate School of Business, Columbia University)

  • Omar Besbes

    ()
    (Graduate School of Business, Columbia University)

  • Gabriel Y. Weintraub

    ()
    (Graduate School of Business, Columbia University)

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    Abstract

    Ad Exchanges are emerging Internet markets where advertisers may purchase display ad placements, in real-time and based on specific viewer information, directly from publishers via a simple auction mechanism. Advertisers join these markets with a pre-specified budget and participate in multiple second-price auctions over the length of a campaign. This paper studies the competitive landscape that arises in Ad Exchanges and the implications for publishers' decisions. Our first main contribution is to introduce the novel notion of a Fluid Mean Field Equilibrium (FMFE) that is behaviorally appealing, computationally tractable, and in some important cases yields a closed-form characterization. Moreover, we show that a FMFE approximates well the rational behavior of advertisers in large markets. Our second main contribution is to use this framework to provide sharp prescriptions for key auction design decisions that publishers face in these markets, such as the reserve price, the allocation of impressions to the exchange versus an alternative channel, and the disclosure of viewers' information. Notably, we show that proper adjustment of the reserve price is key in (1) making profitable for the publisher to try selling all impressions in the exchange before utilizing the alternative channel; and (2) compensating for the thinner markets created by greater disclosure of viewers' information.

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    File URL: http://www.NETinst.org/Balseiro_12-11.pdf
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    Bibliographic Info

    Paper provided by NET Institute in its series Working Papers with number 12-11.

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    Length: 47 pages
    Date of creation: Sep 2012
    Date of revision:
    Handle: RePEc:net:wpaper:1211

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    Web page: http://www.NETinst.org/

    Related research

    Keywords: auction design; revenue management; ad exchange; display advertising; internet; budget constraints; dynamic games; mean field; fl uid approximation;

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    References

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    1. Simon Board, 2009. "Revealing information in auctions: the allocation effect," Economic Theory, Springer, vol. 38(1), pages 125-135, January.
    2. Dudey, Marc, 1992. "Dynamic Edgeworth-Bertrand Competition," The Quarterly Journal of Economics, MIT Press, vol. 107(4), pages 1461-77, November.
    3. Jonathan Levin & Paul Milgrom, 2010. "Online Advertising: Heterogeneity and Conflation in Market Design," American Economic Review, American Economic Association, vol. 100(2), pages 603-07, May.
    4. Mas-Colell, Andreu & Whinston, Michael D. & Green, Jerry R., 1995. "Microeconomic Theory," OUP Catalogue, Oxford University Press, number 9780195102680, September.
    5. Mireia Jofre-Bonet & Martin Pesendorfer, 2001. "Estimation of a Dynamic Auction Game," NBER Working Papers 8626, National Bureau of Economic Research, Inc.
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    Cited by:
    1. L. Elisa Celis & Gregory Lewis & Markus M. Mobius & Hamid Nazerzadeh, 2012. "Buy-it-now or Take-a-chance: Price Discrimination through Randomized Auctions," NBER Working Papers 18590, National Bureau of Economic Research, Inc.
    2. Henk Kox & Bas Straathof & Gijsbert Zwart, 2014. "Targeted advertising, platform competition and privacy," CPB Discussion Paper 280, CPB Netherlands Bureau for Economic Policy Analysis.

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