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Year: 2015 Publisher: Cambridge, Mass. National Bureau of Economic Research
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A common complaint about online auctions for consumer goods is the presence of "snipers," who place bids in the final seconds of sequential ascending auctions with predetermined ending times. The literature conjectures that snipers are best-responding to the existence of "incremental" bidders that bid up to their valuation only as they are outbid. Snipers aim to catch these incremental bidders at a price below their reserve, with no time to respond. As a consequence, these incremental bidders may experience regret when they are outbid at the last moment at a price below their reservation value. We measure the effect of this experience on a new buyer's propensity to participate in future auctions. We show the effect to be causal using a carefully selected subset of auctions from eBay.com and instrumental variables estimation strategy. Bidders respond to sniping quite strongly and are between 4 and 18 percent less likely to return to the platform.
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Year: 2017 Publisher: Cambridge, Mass. National Bureau of Economic Research
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We study expectation-based reference point formation using data from an online auction marketplace. We hypothesize that exit from the marketplace is affected by disappointment from abruptly losing an auction after being the leading bidder. Expectation-based reference points that evolve over time imply that a bidder who spends more time in the lead prior to an abrupt loss will suffer a higher degree of disappointment. We find that for every additional day in the lead, bidders who lose abruptly are 6 percentage points more likely to exit. In contrast, losing bidders whose expectations are informed by early, competing bids, show no effect at all. Also, consistent with our theoretical model, more experienced bidders are less sensitive to time spent in the lead.
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Year: 2003 Publisher: Cambridge, Mass. NBER
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ISBN: 9781400835614 9780691122564 Year: 2005 Publisher: Princeton, N.J. Princeton University Press
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