Examining returns to sniping on eBay

Sniping—the practice of placing the initial bid in the final seconds of an online auction—is widely observed on eBay, yet its causal impact on bidder welfare remains contested because of the endogenous and strategic nature of bidding in real markets. We address this gap by developing a theoretical model of bidder heterogeneity and empirically examining the causal impact of sniping on winner surplus using a unique dataset of Xbox 360 console auctions on eBay. We show that snipers systematically target higher-value auctions—on average 5.8% more expensive than those won by early entrants—yet secure substantially greater payoffs. Leveraging instrumental-variable (IV) regression with a value-type instrument constructed from collective valuation to mitigate endogeneity, we find that sniping increases winner surplus nearly eight-fold, corresponding to an average gain of about $40 per auction. To investigate the underlying mechanism through which sniping increases winner surplus, we conducted a complementary counterfactual analysis based on propensity-score matching (PSM). The analysis reveals that, by concealing bids until the close, sniping suppresses price escalation and reduces final auction prices by roughly $33 (≈7% of item value) relative to early entry. Subsample analysis further shows that strategic sniping behavior is especially pronounced in higher-stake auctions. These results highlight bid timing as a central strategic lever in online auctions, demonstrate that sniping enhances buyer welfare under common-value uncertainty, and provide auction platforms with a systematic framework to anticipate when and where sniping is most likely to occur.

• 저널Production and Operations Management
• 토픽Auction Theory and Applications · Management Science and Operations Research
• DOI10.1177/10591478261485795
• 저자Ravi Bapna, Zhuojun Gu, Alok Gupta