Winner's Curse, Reserve Prices and Endogenous Entry: Empirical Insights from eBay Auctions

Bajari, Patrick; Hortaçsu, Ali

doi:10.2139/ssrn.224950

Cited by 355 publications

(516 citation statements)

References 15 publications

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“…They observe that in 240 antique auctions on eBay, 89 had bids in the last minute and 29 in the last 10 seconds. 4 Similar findings have been reported by Bajari and Hortaçsu (2003), Shmueli, Russo and Jank (2004) and Schindler (2003). Explanations for late bidding range from tacit collusion against sellers to the presence of naïve bidders who don't understand proxy bidding, to common value components in the items being auctioned.…”

Section: A Field Experiments To Determine Highest Winning Bid On Ebaysupporting

confidence: 84%

Consumer Surplus in Online Auctions

2005

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Despite the growing research interest in Internet auctions, particularly those on eBay, little is known about quantifiable consumer surplus levels in such mechanisms. Using an ongoing novel field experiment that involves real bidders participating in real auctions, and voting with real dollars, we collect and examine a unique dataset to empirically quantify and understand determinants of consumer surplus in eBay auctions. The estimation procedure for private value auctions relies mainly on knowing the highest bid, which is not disclosed by eBay, but is available to us from our experiment. For common value auctions, where bidders bid strategically to avoid winner's curse, we develop an estimation procedure that infers the bidders' signals from their bids, and subsequently infers the item's common value and resulting surplus, from the signals. Our analysis, based on a sample of 4514 eBay auctions, indicates that the median surplus level per eBay auction is $3.61, which roughly translates to $1.5 billion in accrued consumer surplus for the year 2003 alone. On a percentage basis, consumers are capturing at least 18.3% of the total surplus generated in eBay auctions. We find that consumer surplus is significantly different across currencies and item categories, negatively influenced by seller experience, auction duration and competition, and positively influenced by bidder experience, bidder aggressiveness and item price.

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Section: A Field Experiments To Determine Highest Winning Bid On Ebaysupporting

confidence: 84%

Consumer Surplus in Online Auctions

2005

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“…Bajari and Hortaçsu (2003) used data on collectible coin auctions in which the CV assumption is motivated by informational asymmetries between buyers and sellers, along with the existence of a highly liquid resale market and the presence of speculative collectors. Due to the presence of speculative bidders who presumably have expertise in appraising coins, the authors also modeled bidders' private signals as being distributed asymmetrically.…”

Section: Common Values and Pure Common Valuesmentioning

confidence: 99%

“…This is consistent with a model in which sellers' optimal policy isto report only information that reflects positively on the condition of the sale item. Lewis rendered his model dynamics more tractable by employing the same abstraction as described above in Bajari and Hortaçsu (2003). In his model, this implied that the game essentially unravels to a static Vickrey auction in which bids are based on private signals, the number of competitors, and the number of signals received from the seller.…”

Section: Common Values and Pure Common Valuesmentioning

confidence: 99%

“…He argued that the advantage of his method over Hong and Shum (2002), which we discuss below, or Bajari and Hortaçsu (2003) is that it deals with the curse of dimensionality remarkably well, allowing him to include over thirty covariates in the model. He found that sellers can significantly affect the sale price by providing large amounts of information to buyers.…”

Section: Common Values and Pure Common Valuesmentioning

confidence: 99%

“…Thus, an appealing characteristic of their model is that it has a built-in method of testing between the polar extremes of PCV and IPV, while allowing for elements of both to be present simultaneously. Bajari and Hortaçsu (2003) studied eBay auctions, which they argued correspond to the English auction format. They were motivated by features of the sale objects in their data-rare collectible coins with unknown future resale value-to assume a CV information structure.…”

Section: Testing Common Versus Private Valuesmentioning

confidence: 99%

See 2 more Smart Citations

Structural Econometric Methods in Auctions: A Guide to the Literature

Hickman¹,

Hubbard²,

Saglam³

2012

Journal of Econometric Methods

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Auction models have proved to be attractive to structural econometricians who, since the late 1980s, have made substantial progress in identifying and estimating these rich game-theoretic models of bidder behavior. We provide a guide to the literature in which we contrast the various informational structures (paradigms) commonly assumed by researchers and uncover the evolution of the field. We highlight major contributions within each paradigm and benchmark modifications and extensions to these core models. Lastly, we discuss special topics that have received substantial attention among auction researchers in recent years, including auctions for multiple objects, auctions with risk averse bidders, testing between common and private value paradigms, unobserved auction-specific heterogeneity, and accounting for an unobserved number of bidders as well as endogenous entry.Keywords: auctions, structural econometrics. JEL Classification Numbers: C01, D44. * We were all students of Harry J. Paarsch and would like to express our sincere gratitude and appreciation to him. Harry was not only a pioneer of this literature, but he introduced each of us to the field and continues to inspire us today. We would also like to thank two anonymous referees for helpful suggestions. Any errors are our own.

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A Family of Growth Models for Representing the Price Process in Online Auctions

Hyde¹,

Shmueli²,

Jank³

2008

Statistical Methods in E‐Commerce Research

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Bids during an online auction arrive at unequally-spaced discrete time points. Our goal is to capture the entire continuous price-evolution function by representing it as a functional object. Various nonparametric smoothing methods exist to recover the functional object from the observed discrete bid data. Previous studies use penalized polynomial and monotone smoothing splines; however, these require the determination of a large number of coefficients and often lengthy computational time. We present a family of parametric growth curves that describe the price-evolution during online auctions. Our approach is parsimonious and has an appealing interpretation in the online auction context. We also provide an automated fitting algorithm that is computationally fast. Our method is illustrated on several eBay datasets.

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Winner's Curse, Reserve Prices and Endogenous Entry: Empirical Insights from eBay Auctions

Cited by 355 publications

References 15 publications

Consumer Surplus in Online Auctions

Consumer Surplus in Online Auctions

Structural Econometric Methods in Auctions: A Guide to the Literature

A Family of Growth Models for Representing the Price Process in Online Auctions

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