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Is Sniping A Problem For Online Auction Markets?

Author

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  • Matthew Backus
  • Tom Blake
  • Dimitriy V. Masterov
  • Steven Tadelis

Abstract

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.

Suggested Citation

  • Matthew Backus & Tom Blake & Dimitriy V. Masterov & Steven Tadelis, 2015. "Is Sniping A Problem For Online Auction Markets?," NBER Working Papers 20942, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20942
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    Cited by:

    1. März, Armin & Lachner, Michael & Heumann, Christian G. & Schumann, Jan H. & von Wangenheim, Florian, 2021. "How You Remind Me! The Influence of Mobile Push Notifications on Success Rates in Last-Minute Bidding," Journal of Interactive Marketing, Elsevier, vol. 54(C), pages 11-24.
    2. Sofia Moroni, 2016. "Sniping in Proxy Auctions with Deadlines," Working Paper 5875, Department of Economics, University of Pittsburgh.
    3. Barbaro, Salvatore & Bracht, Bernd, 2021. "Shilling, Squeezing, Sniping. A further explanation for late bidding in online second-price auctions," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    4. Jannett Highfill & Kevin M. O’Brien, 2018. "eBay Memorabilia Auctions vis-à -vis Predictions for the 2016 U.S. Presidential Election," The American Economist, Sage Publications, vol. 63(1), pages 71-78, March.
    5. Yan Chen & Peter Cramton & John A. List & Axel Ockenfels, 2021. "Market Design, Human Behavior, and Management," Management Science, INFORMS, vol. 67(9), pages 5317-5348, September.
    6. Christopher Helm & Tim A. Herberger & Marcel Tyrell, 2021. "Demand dynamics across secondary German Book markets: an information aggregation and synthetization approach," Information Systems and e-Business Management, Springer, vol. 19(2), pages 567-596, June.
    7. Backus, Matthew R. & Podwol, Joseph Uri & Schneider, Henry S., 2014. "Search costs and equilibrium price dispersion in auction markets," European Economic Review, Elsevier, vol. 71(C), pages 173-192.
    8. Maryam Saeedi & Hugo A. Hopenhayn, 2015. "Dynamic Bidding in Second Price Auction," 2015 Meeting Papers 1346, Society for Economic Dynamics.
    9. Matthew Backus & Thomas Blake & Dimitriy V. Masterov & Steven Tadelis, 2017. "Expectation, Disappointment, and Exit: Reference Point Formation in a Marketplace," NBER Working Papers 23022, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

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