Externalities in Keyword Auctions: An Empirical and Theoretical Assessment

The value of acquiring a slot in a sponsored search list (that comes along with the organic links in a search engine's result page) might depend on who else is shown in the other sponsored positions. To empirically evaluate this claim, we develop a model of ordered search applied to keyword advertising, in which users browse slots from the top to the bottom of the sponsored list and make their clicking decisions slot by slot. Our contribution is twofold: first, we use impression and click data from Microsoft Live to estimate the ordered search model. With these estimates in hand, we are able to assess how the click-through rate of an ad is affected by the user's click history and by the other competing links. Our dataset suggests that externality effects are indeed economically and statistically significant. Second, we study Nash equilibria of the Generalized Second Price Auction (GSP) and characterize the scoring rule that produces greatest profits in a complete information setting.

[1]  Anna R. Karlin,et al.  On the Equilibria and Efficiency of the GSP Mechanism in Keyword Auctions with Externalities , 2008, WINE.

[2]  Q. Vuong Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses , 1989 .

[3]  Nick Craswell,et al.  An experimental comparison of click position-bias models , 2008, WSDM '08.

[4]  Thorsten Joachims,et al.  Accurately Interpreting Clickthrough Data as Implicit Feedback , 2017 .

[5]  E. Stacchetti,et al.  How (not) to sell nuclear weapons , 1996 .

[6]  R. Vohra,et al.  Algorithmic Game Theory: Sponsored Search Auctions , 2007 .

[7]  Mohammad Mahdian,et al.  A Cascade Model for Externalities in Sponsored Search , 2008, WINE.

[8]  Mohammad Mahdian,et al.  Externalities in online advertising , 2008, WWW.

[9]  Fan Chung Graham,et al.  Internet and Network Economics, Third International Workshop, WINE 2007, San Diego, CA, USA, December 12-14, 2007, Proceedings , 2007, WINE.

[10]  Thorsten Joachims,et al.  Accurately interpreting clickthrough data as implicit feedback , 2005, SIGIR '05.

[11]  David M. Pennock,et al.  Revenue analysis of a family of ranking rules for keyword auctions , 2007, EC '07.

[12]  Dale T. Mortensen,et al.  Chapter 15 Job search and labor market analysis , 1986 .

[13]  Ashish Goel,et al.  Truthful auctions for pricing search keywords , 2006, EC '06.

[14]  Michael R. Baye,et al.  Information, Search, and Price Dispersion , 2006 .

[15]  Glenn Ellison,et al.  Position Auctions with Consumer Search , 2007 .

[16]  Sébastien Lahaie,et al.  An analysis of alternative slot auction designs for sponsored search , 2006, EC '06.

[17]  Jon Feldman,et al.  Sponsored Search Auctions with Markovian Users , 2008, WINE.