TY  - JOUR
AU  - Cary,Matthew
AU  - Das,Aparna
AU  - Edelman,Benjamin
AU  - Giotis,Ioannis
AU  - Heimerl,Kurtis
AU  - Karlin,Anna R.
AU  - Mathieu,Claire
AU  - Schwarz,Michael
TI  - On Best-Response Bidding in GSP Auctions
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 13788
PY  - 2008
Y2  - February 2008
UR  - http://www.nber.org/papers/w13788
L1  - http://www.nber.org/papers/w13788.pdf
N1  - Author contact info:
Matthew Cary
 University of Washington
Seattle, WA 98195
E-Mail: cary@cs.washington.edu

Aparna Das
Brown University
Computer Science Department
Box 1910
Providence, RI 02912
E-Mail: aparna@cs.brown.edu

Benjamin Edelman
Harvard Business School
Baker Library 445
Soldiers Field
Boston, Massachusetts 02163
E-Mail: bedelman@hbs.edu

Ioannis Giotis
University of Washington
Department of Computer Science
   and Engineering
Seattle, WA 98195
E-Mail: giotis@cs.washington.edu

Kurtis Heimerl
University of Washington
Department of Computer Science
  and Engineering
Seattle, WA 98195
E-Mail: heimerl@cs.washington.edu

Anna R. Karlin
University of Washington
Department of Computer Science
  and Engineering
Box 352350
Seattle, WA 98195
E-Mail: karlin@cs.washington.edu

Claire Mathieu
Brown University
Computer Science Department
Box 1910
Providence, RI 02912
E-Mail: claire@cs.brown.edu

Michael Schwarz
Yahoo! Research
2397 Shattuck Ave
Berkeley, CA 94704
Fax: 510/704-2401
E-Mail: mschwarz@yahoo-inc.com
AB  - 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.
ER  -