Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/284129 
Year of Publication: 
2023
Series/Report no.: 
cemmap working paper No. CWP05/23
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
This paper presents an empirical model of sponsored search auctions in which advertisers are ranked by bid and ad quality. We introduce a new nonparametric estimator for the advertiser's ad value and its distribution under the 'incomplete information' assumption. The ad value is characterized by a tractable analytical solution given observed auction parameters. Using Yahoo! search auction data, we estimate value distributions and study the bidding behavior across product categories. We find that advertisers shade their bids more when facing less competition. We also conduct counterfactual analysis to evaluate the impact of score squashing (ad quality raised to power &#x03b8; < 1) on the auctioneer's revenue. Our results show that product-specific score squashing can enhance auctioneer revenue at the expense of advertiser profit and consumer welfare.
Subjects: 
Sponsored search links
generalized second price auction
incomplete information
nonparametric estimation
bid shading
score squashing
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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