Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/284129 
Erscheinungsjahr: 
2023
Schriftenreihe/Nr.: 
cemmap working paper No. CWP05/23
Verlag: 
Centre for Microdata Methods and Practice (cemmap), London
Zusammenfassung: 
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.
Schlagwörter: 
Sponsored search links
generalized second price auction
incomplete information
nonparametric estimation
bid shading
score squashing
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