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Nonparametric estimation of English auctions with selective entry: An application to online judicial auctions

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  • Nianqing Liu
  • Kexin Xu

Abstract

This paper proposes an estimation approach following the constructive identification strategy of Athey and Haile, and Gentry and Li with adaption in the context of ascending auctions with selective entry. Our estimators are shown to be consistent in a large sample and to perform well in a finite sample by a simulation study. We apply our estimation approach to the Alibaba online judicial auctions of used cars to recover the bounds of conditional value distribution and the entry cost. The bounds estimates of both conditional value distribution and entry cost are quite tight (resp., relatively wide) for middle‐valued (resp., low‐valued or high‐valued) signal, and the cumulative distribution functions of conditional value distribution given signal comply with the law of ordered dominance. Finally, our counterfactual analysis indicates that (i) the ascending auction yields a higher revenue than the first‐price sealed bid auction, and (ii) the revenue can be improved significantly when the entry cost is cut by half.

Suggested Citation

  • Nianqing Liu & Kexin Xu, 2024. "Nonparametric estimation of English auctions with selective entry: An application to online judicial auctions," International Studies of Economics, John Wiley & Sons, vol. 19(2), pages 247-267, June.
    • Handle: RePEc:wly:intsec:v:19:y:2024:i:2:p:247-267
    DOI: 10.1002/ise3.68
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    References listed on IDEAS

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    1. Nianqing Liu & Yao Luo, 2017. "A Nonparametric Test For Comparing Valuation Distributions In First‐Price Auctions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58, pages 857-888, August.
    2. Susan Athey & Jonathan Levin & Enrique Seira, 2011. "Comparing open and Sealed Bid Auctions: Evidence from Timber Auctions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(1), pages 207-257.
    3. Elena Krasnokutskaya & Katja Seim, 2011. "Bid Preference Programs and Participation in Highway Procurement Auctions," American Economic Review, American Economic Association, vol. 101(6), pages 2653-2686, October.
    4. Bajari, Patrick & Hortacsu, Ali, 2003. "The Winner's Curse, Reserve Prices, and Endogenous Entry: Empirical Insights from eBay Auctions," RAND Journal of Economics, The RAND Corporation, vol. 34(2), pages 329-355, Summer.
    5. An, Yonghong & Hu, Yingyao & Shum, Matthew, 2010. "Estimating first-price auctions with an unknown number of bidders: A misclassification approach," Journal of Econometrics, Elsevier, vol. 157(2), pages 328-341, August.
    6. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
    7. Jingfeng Lu & Isabelle Perrigne, 2008. "Estimating risk aversion from ascending and sealed-bid auctions: the case of timber auction data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(7), pages 871-896.
    8. Nianqing Liu & Yao Luo, 2017. "A Nonparametric Test For Comparing Valuation Distributions In First‐Price Auctions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(3), pages 857-888, August.
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