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Empirical Implementation of Nonparametric First-Price Auction Models

Author

Listed:
  • Daniel J. Henderson
  • John A. List
  • Daniel L. Millimet
  • Christopher F. Parmeter
  • Michael K. Price

Abstract

Nonparametric estimators provide a flexible means of uncovering salient features of auction data. Although these estimators are popular in the literature, many key features necessary for proper implementation have yet to be uncovered. Here we provide several suggestions for nonparamteric estimation of first-price auction models. Specifically, we show how to impose monotonicity of the equilibrium bidding strategy; a key property of structural auction models not guaranteed in standard nonparametric estimation. We further develop methods for automatic bandwidth selection. Finally, we discuss how to impose monotonicity in auctions with differering number of bidders, reserve prices, and auction-specific characteristics. Finite sample performance is examined using simulated data as well as experimental auction data.

Suggested Citation

  • Daniel J. Henderson & John A. List & Daniel L. Millimet & Christopher F. Parmeter & Michael K. Price, 2011. "Empirical Implementation of Nonparametric First-Price Auction Models," NBER Working Papers 17095, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:17095
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Sundström, David, 2016. "The Competition Effect in a Public Procurement Model: An error-in-variables approach," Umeå Economic Studies 920, Umeå University, Department of Economics, revised 17 Jun 2016.
    2. Federico Zincenko, 2016. "Nonparametric Estimation of First-Price Auctions with Risk-Averse Bidders," Working Paper 5855, Department of Economics, University of Pittsburgh.
    3. Michael Delgado & Christopher Parmeter & Valentina Hartarska & Roy Mersland, 2015. "Should all microfinance institutions mobilize microsavings? Evidence from economies of scope," Empirical Economics, Springer, vol. 48(1), pages 193-225, February.
    4. Yao Luo & Yuanyuan Wan, 2015. "Integrated-quantile-based estimation for first price auction models," Working Papers tecipa-539, University of Toronto, Department of Economics.
    5. Zhang, Yu Yvette, 2017. "A shape constrained estimator of bidding function of first-price sealed-bid auctions," Economics Letters, Elsevier, vol. 150(C), pages 67-72.
    6. Wu, Ximing & Sickles, Robin, 2014. "Semiparametric Estimation under Shape Constraints," Working Papers 15-021, Rice University, Department of Economics.
    7. Lorentziadis, Panos L., 2016. "Optimal bidding in auctions from a game theory perspective," European Journal of Operational Research, Elsevier, vol. 248(2), pages 347-371.
    8. repec:kap:enreec:v:69:y:2018:i:1:d:10.1007_s10640-016-0071-x is not listed on IDEAS
    9. Satterthwaite, Mark A. & Williams, Steven R. & Zachariadis, Konstantinos E., 2014. "Optimality versus practicality in market design: A comparison of two double auctions," Games and Economic Behavior, Elsevier, vol. 86(C), pages 248-263.
    10. Ma, Jun & Marmer, Vadim & Shneyerov, Artyom, 2016. "Inference for First-Price Auctions with Guerre, Perrigne, and Vuong's estimator," Microeconomics.ca working papers vadim_marmer-2016-4, Vancouver School of Economics, revised 17 Mar 2018.

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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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