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Identification of Auction Models Using Order Statistics

Author

Listed:
  • Yao Luo
  • Ruli Xiao
Abstract
Auction data often contain information on only the most competitive bids as opposed to all bids. The usual measurement error approaches to unobserved heterogeneity are inapplicable due to dependence among order statistics. We bridge this gap by providing a set of positive identification results. First, we show that symmetric auctions with discrete unobserved heterogeneity are identifiable using two consecutive order statistics and an instrument. Second, we extend the results to ascending auctions with unknown competition and unobserved heterogeneity.

Suggested Citation

  • Yao Luo & Ruli Xiao, 2022. "Identification of Auction Models Using Order Statistics," Papers 2205.12917, arXiv.org, revised Apr 2023.
    • Handle: RePEc:arx:papers:2205.12917
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    References listed on IDEAS

    as
    1. Emmanuel Guerre & Isabelle Perrigne & Quang Vuong, 2000. "Optimal Nonparametric Estimation of First-Price Auctions," Econometrica, Econometric Society, vol. 68(3), pages 525-574, May.
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    12. 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.
    13. JoonHwan Cho & Yao Luo & Ruli Xiao, 2022. "Deconvolution from Two Order Statistics," Working Papers tecipa-739, University of Toronto, Department of Economics.
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    20. Jason Allen & Robert Clark & Brent Hickman & Eric Richert, 2019. "Resolving Failed Banks: Uncertainty, Multiple Bidding & Auction Design," Staff Working Papers 19-30, Bank of Canada.
    21. Luo, Yao, 2020. "Unobserved heterogeneity in auctions under restricted stochastic dominance," Journal of Econometrics, Elsevier, vol. 216(2), pages 354-374.
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    23. Philip A. Haile & Elie Tamer, 2003. "Inference with an Incomplete Model of English Auctions," Journal of Political Economy, University of Chicago Press, vol. 111(1), pages 1-51, February.
    24. Joachim Freyberger & Bradley J. Larsen, 2022. "Identification in ascending auctions, with an application to digital rights management," Quantitative Economics, Econometric Society, vol. 13(2), pages 505-543, May.
    25. Matt Shum & Phil Haile & Han Hong, 2003. "Nonparametric Tests for Common Values in First-Price Auctions," Economics Working Paper Archive 501, The Johns Hopkins University,Department of Economics.
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    27. Andrés Aradillas‐López & Amit Gandhi & Daniel Quint, 2013. "Identification and Inference in Ascending Auctions With Correlated Private Values," Econometrica, Econometric Society, vol. 81(2), pages 489-534, March.
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    Full references (including those not matched with items on IDEAS)

    Citations

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    as


    Cited by:

    1. JoonHwan Cho & Yao Luo & Ruli Xiao, 2024. "Deconvolution from two order statistics," Papers 2403.17777, arXiv.org.
    2. Yao Luo & Peijun Sang & Ruli Xiao, 2024. "Order Statistics Approaches to Unobserved Heterogeneity in Auctions," Working Papers tecipa-776, University of Toronto, Department of Economics.
    3. Cristián Hernández & Daniel Quint & Christopher Turansick, 2020. "Estimation in English auctions with unobserved heterogeneity," RAND Journal of Economics, RAND Corporation, vol. 51(3), pages 868-904, September.
    4. Joachim Freyberger & Bradley J. Larsen, 2022. "Identification in ascending auctions, with an application to digital rights management," Quantitative Economics, Econometric Society, vol. 13(2), pages 505-543, May.

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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

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