Arbeitspapier
Asymmetric information in auctions: Are resellers better appraisers?
This paper shows that in online car auctions, resellers are better at appraising the value of the cars they are bidding on than are consumers. Using a unique data set of online car auctions, I show that differences in bidding behavior between resellers and consumers can be explained by heterogeneity in the accuracy of bidders' private signals and heterogeneity in the dispersion of private value components. I use the asymmetric ascending auction model of Hong and Shum (2003) to quantify the differences between resellers and consumers, finding that the dispersion of reseller value signals is roughly half that of consumers and simulate three different counterfactual scenarios - one in which consumers are provided with more information, one in which consumers are subsidized and one in which consumers are allowed into all-reseller auctions. Finally, I argue that the asymmetry in signal precision stems not from asymmetric information regarding the technical characteristics of a car but rather from uncertainty about the car's resale value.
- Sprache
-
Englisch
- Erschienen in
-
Series: IFN Working Paper ; No. 1110
- Klassifikation
-
Wirtschaft
Model Construction and Estimation
Auctions
Asymmetric and Private Information; Mechanism Design
Automobiles; Other Transportation Equipment; Related Parts and Equipment
- Thema
-
Ascending (English) Auctions
Asymmetric Auctions
Experience
Learning
Winner's Curse
Bid Shading
Signal Precision
Resellers
- Ereignis
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Geistige Schöpfung
- (wer)
-
Koptyug, Nikita
- Ereignis
-
Veröffentlichung
- (wer)
-
Research Institute of Industrial Economics (IFN)
- (wo)
-
Stockholm
- (wann)
-
2016
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Koptyug, Nikita
- Research Institute of Industrial Economics (IFN)
Entstanden
- 2016