To Score or Not to Score? Estimates of a Sponsored Search Auction Model

Abstract

We estimate a structural model of a sponsored search auction model. To accommodate the "position paradox", we relax the assumption of decreasing click volumes with position ranks, which is often assumed in the literature. Using data from "Website X", one of the largest online marketplaces in China, we find that merchants of different qualities adopt different bidding strategies: high quality merchants bid more aggressively for informative keywords, while low quality merchants are more likely to be sorted to the top positions for vague keywords. Counterfactual evaluations show that the price trend becomes steeper after moving to a score-weighted generalized second price auction, with much higher prices obtained for the top position but lower prices for the other positions. Overall there is only a very modest change in total revenue from introducing popularity scoring, despite the intent in bid scoring to reward popular merchants with price discounts. JEL classification numbers: D44; D47; C11; C15

Bid Coordination in Sponsored Search Auctions: Detection Methodology and Empirical Analysis*

“…7 In fact, despite the stunning economic importance of the sponsored search auction, the confidential nature of the data has hindered their empirical analysis. Important exceptions are those in Varian [2007], Ghose and Yang [2009], Athey and Nekipelov [2014], Borgers et al [2013], Lewis and Rao [2015], Goldman and Rao [2015], and Hsieh et al [2018], as well as those based on the of the proprietary data, about which we are not allowed to disclose further information, we describe some stylized features of the market through publicly available data on Google sponsored search. Thanks to the availability of these new data, this study presents a rare opportunity to analyze a phenomenon-bid coordination via intermediaries-that so far has only been possible to study in the theoretical literature.…”

Marketing Agencies and Collusive Bidding in Online Ad Auctions

“…26 While an in depth discussion of potential applications to data is beyond the scope of this paper, we refer to Ghose and Yang (2009) for an empirical model of the Google or Microsoft-Bing type of search auctions and to Hsieh, Shum and Yang (2018) for the case of Taobao auctions. Neither these two papers nor others we are aware of in the literature develop methods for estimating an empirical model of the search auctions in the presence of collusive bidding.…”