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Varying the number of bidders in the first-price sealed-bid auction: experimental evidence for the one-shot game

Author

Listed:
  • Tibor Neugebauer
  • Sascha F llbrunn

    (LSF)

Abstract

The paper reports experimental data on the behavior in the first-price sealed-bid auction for a varying number of bidders when values and bids are private information. This feedback-free design is proposed for the experimental test of the one-shot game situation. We consider both within-subject and betweensubjects variations. In line with the qualitative risk neutral Nash equilibrium prediction, the data show that bids increase in the number of bidders. However, in auctions involving a small number of bidders, average bids are above, and in auctions involving a larger number of bidders, average bids are below the risk neutral equilibrium prediction. The quartile analysis reveals that bidding behavior is not constant across the full value range for a given number of bidders. On the high value quartiles, however, the average bid-value ratio is not different from the risk neutral prediction. The behavior is different when the winning bid is revealed after each repetition.

Suggested Citation

  • Tibor Neugebauer & Sascha F llbrunn, 2013. "Varying the number of bidders in the first-price sealed-bid auction: experimental evidence for the one-shot game," DEM Discussion Paper Series 13-10, Department of Economics at the University of Luxembourg.
    • Handle: RePEc:luc:wpaper:13-10
    as

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    File URL: http://wwwen.uni.lu/content/download/65011/818493/file/Binder10_Varying%20the%20number%20of%20bidders%20in%20the%20first-price%20sealed-bid%20auction_experimental%20evidence%20for%20the%20one-shot%20game_Neugebauer_October%202013.pdf
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    References listed on IDEAS

    as
    1. Park, Sangin, 2003. "Semiparametric instrumental variables estimation," Journal of Econometrics, Elsevier, vol. 112(2), pages 381-399, February.
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    Cited by:

    1. Chen, Jiafeng & Chen, Xiaohong & Tamer, Elie, 2023. "Efficient estimation of average derivatives in NPIV models: Simulation comparisons of neural network estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1848-1875.
    2. Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021. "Efficient Estimation of Average Derivatives in NPIV Models: Simulation Comparisons of Neural Network Estimators," Cowles Foundation Discussion Papers 2319, Cowles Foundation for Research in Economics, Yale University.
    3. Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021. "Efficient Estimation in NPIV Models: A Comparison of Various Neural Networks-Based Estimators," Papers 2110.06763, arXiv.org, revised Oct 2022.
    4. Chen, Tao & Parker, Thomas, 2014. "Semiparametric efficiency for partially linear single-index regression models," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 376-386.

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