• Medientyp: E-Book
  • Titel: To Score or Not to Score? Estimates of a Sponsored Search Auction Model
  • Beteiligte: Hsieh, Yu-Wei [VerfasserIn]; Shum, Matthew [Sonstige Person, Familie und Körperschaft]; Yang, Sha [Sonstige Person, Familie und Körperschaft]
  • Erschienen: [S.l.]: SSRN, [2018]
  • Erschienen in: USC-INET Research Paper ; No. 15-09
  • Umfang: 1 Online-Ressource (27 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.2564735
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 1, 2015 erstellt
  • Beschreibung: Using data from "WebsiteX", one of the largest online marketplaces in the world, we estimate a structural model of sponsored search auctions where bidders have heterogeneous click-through curves. Unlike earlier studies, our model accommodates two stylized empirical facts: the advertiser prominence eff ect and the position paradox. Using our estimates, we simulate the e ffects of introducing bid-scoring to the auctions. We fi nd that scoring reduces equilibrium per-click prices, but boosts the number of clicks by sorting prestigious merchants to the top positions. Overall there is only a very modest reduction in total revenues from introducing bid-scoring, despite the intent to reward high-quality merchants with price discounts. Methodologically, this paper also illustrates an application of a novel "approximate Bayesian" estimation method to a structural multi-item auction model
  • Zugangsstatus: Freier Zugang