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Identification and Estimation of Risk Aversion in First-Price Auctions with Unobserved Auction Heterogeneity

Author

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  • Serafin Grundl
  • Yu Zhu
Abstract
This paper shows point identification in first-price auction models with risk aversion and unobserved auction heterogeneity by exploiting multiple bids from each auction and variation in the number of bidders. The required exclusion restriction is shown to be consistent with a large class of entry models. If the exclusion restriction is violated, but weaker restrictions hold instead, the same identification strategy still yields valid bounds for the primitives. We propose a sieve maximum likelihood estimator. A series of Monte Carlo experiments illustrate that the estimator performs well in finite samples and that ignoring unobserved auction heterogeneity can lead to a significant bias in risk-aversion estimates. In an application to U.S. Forest Service timber auctions we find that the bidders are risk neutral, but we would reject risk neutrality without accounting for unobserved auction heterogeneity.

Suggested Citation

  • Serafin Grundl & Yu Zhu, 2016. "Identification and Estimation of Risk Aversion in First-Price Auctions with Unobserved Auction Heterogeneity," Staff Working Papers 16-23, Bank of Canada.
    • Handle: RePEc:bca:bocawp:16-23
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    References listed on IDEAS

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    Cited by:

    1. Vasserman, Shoshana & Watt, Mitchell, 2021. "Risk aversion and auction design: Theoretical and empirical evidence," International Journal of Industrial Organization, Elsevier, vol. 79(C).
    2. JoonHwan Cho & Yao Luo & Ruli Xiao, 2022. "Deconvolution from Two Order Statistics," Working Papers tecipa-739, University of Toronto, Department of Economics.
    3. Jun, Sung Jae & Zincenko, Federico, 2022. "Testing for risk aversion in first-price sealed-bid auctions," Journal of Econometrics, Elsevier, vol. 226(2), pages 295-320.
    4. Kim, Dong-Hyuk & Ratan, Anmol, 2022. "Disentangling risk aversion and loss aversion in first-price auctions: An empirical approach," European Economic Review, Elsevier, vol. 150(C).
    5. JoonHwan Cho & Yao Luo & Ruli Xiao, 2024. "Deconvolution from two order statistics," Papers 2403.17777, arXiv.org.
    6. Emmanuel Guerre & Yao Luo, 2019. "Nonparametric Identification of First-Price Auction with Unobserved Competition: A Density Discontinuity Framework," Papers 1908.05476, arXiv.org, revised Jan 2022.
    7. Grundl, Serafin & Zhu, Yu, 2024. "Two results on auctions with endogenous entry," Economics Letters, Elsevier, vol. 234(C).

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    More about this item

    Keywords

    Econometric and statistical methods;

    JEL classification:

    • C57 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Econometrics of Games and Auctions
    • 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
    • L00 - Industrial Organization - - General - - - General

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