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On Best-Response Bidding in GSP Auctions

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  • Matthew Cary
  • Aparna Das
  • Benjamin Edelman
  • Ioannis Giotis
  • Kurtis Heimerl
  • Anna R. Karlin
  • Claire Mathieu
  • Michael Schwarz
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    Abstract

    How should players bid in keyword auctions such as those used by Google, Yahoo! and MSN? We model ad auctions as a dynamic game of incomplete information, so we can study the convergence and robustness properties of various strategies. In particular, we consider best-response bidding strategies for a repeated auction on a single keyword, where in each round, each player chooses some optimal bid for the next round, assuming that the other players merely repeat their previous bids. We focus on a strategy we call Balanced Bidding (bb). If all players use the bb strategy, we show that bids converge to a bid vector that obtains in a complete information static model proposed by Edelman, Ostrovsky and Schwarz (2007). We prove that convergence occurs with probability 1, and we compute the expected time until convergence.

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    Bibliographic Info

    Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 13788.

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    Date of creation: Feb 2008
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    Handle: RePEc:nbr:nberwo:13788

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    1. Groves, Theodore, 1973. "Incentives in Teams," Econometrica, Econometric Society, Econometric Society, vol. 41(4), pages 617-31, July.
    2. Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007. "Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords," American Economic Review, American Economic Association, American Economic Association, vol. 97(1), pages 242-259, March.
    3. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, Econometric Society, vol. 61(1), pages 57-84, January.
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