Externalities in Keyword Auctions: An Empirical and Theoretical Assessment

It is widely believed that 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) highly depends on who else is shown in the other sponsored positions. To capture such externality effects, we consider a model of keyword advertising where bidders participate in a Generalized Second Price (GSP) auction and users perform ordered search (they browse 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. Further, we compare the clicking predictions of our ordered search model to those of the most widely used model of user behavior: the separable click-through rate model. Second, we study complete information Nash equilibria of the GSP under different scoring rules. First, we characterize the efficient and revenue-maximizing complete information Nash equilibrium (under any scoring rule) and show that such an equilibrium can be implemented with any set of advertisers if and only if a particular weighting rule that combines click-through rates and continuation probabilities is used. Interestingly, this is the same ranking rule derived in [11] for solving the efficient allocation problem. On the negative side, we show that there is no scoring rule that implements an efficient equilibrium with VCG payments (VCG equilibrium) for all profiles of valuations and search parameters. This result extends [8], who argue that the rank-by-revenue GSP does not possess a VCG equilibrium.