IDEAS home Printed from https://ideas.repec.org/a/gam/jgames/v9y2018i4p79-d174303.html
   My bibliography  Save this article

Learning to Set the Reserve Price Optimally in Laboratory First Price Auctions

Author

Listed:
  • Priyodorshi Banerjee

    (Economic Research Unit, Indian Statistical Institute, Baranagar, Kolkata, West Bengal 700108, India)

  • Shashwat Khare

    (School of Business and Economics, Maastricht University, 6211 LK Maastricht, The Netherlands)

  • P. Srikant

    (Madras School of Economics, Chennai, Tamil Nadu 600025, India)

Abstract

We analyze choices of sellers, each setting a reserve price in a laboratory first price auction with automated equilibrium bidding. Subjects are allowed to gain experience for a fixed period of time prior to making a single payoff-relevant choice. Behavior of more experienced sellers was consistent with benchmark theory: average reserve price for these sellers was independent of the number of bidders and equaled the predicted level. Less experienced sellers however deviated from the theoretical benchmark: on average, they tended to shade reserve price below the predicted level and positively relate it to the number of bidders.

Suggested Citation

  • Priyodorshi Banerjee & Shashwat Khare & P. Srikant, 2018. "Learning to Set the Reserve Price Optimally in Laboratory First Price Auctions," Games, MDPI, vol. 9(4), pages 1-16, October.
    • Handle: RePEc:gam:jgames:v:9:y:2018:i:4:p:79-:d:174303
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-4336/9/4/79/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-4336/9/4/79/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Canice Prendergast, 1999. "The Provision of Incentives in Firms," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 7-63, March.
    2. Audrey Hu & Steven A. Matthews & Liang Zou, 2009. "Risk Aversion and Optimal Reserve Prices in First and Second-Price Auctions, Second Version," PIER Working Paper Archive 10-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 03 Jan 2010.
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. Andrew M. Davis & Elena Katok & Anthony M. Kwasnica, 2011. "Do Auctioneers Pick Optimal Reserve Prices?," Management Science, INFORMS, vol. 57(1), pages 177-192, January.
    5. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    6. Safra, Zvi & Segal, Uzi, 1998. "Constant Risk Aversion," Journal of Economic Theory, Elsevier, vol. 83(1), pages 19-42, November.
    7. George Wu & Richard Gonzalez, 1996. "Curvature of the Probability Weighting Function," Management Science, INFORMS, vol. 42(12), pages 1676-1690, December.
    8. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    9. Hu, Audrey, 2011. "How bidder's number affects optimal reserve price in first-price auctions under risk aversion," Economics Letters, Elsevier, vol. 113(1), pages 29-31, October.
    10. Hu, Audrey & Matthews, Steven A. & Zou, Liang, 2010. "Risk aversion and optimal reserve prices in first- and second-price auctions," Journal of Economic Theory, Elsevier, vol. 145(3), pages 1188-1202, May.
    11. Jonathan Ingersoll, 2008. "Non‐Monotonicity of the Tversky‐Kahneman Probability‐Weighting Function: A Cautionary Note," European Financial Management, European Financial Management Association, vol. 14(3), pages 385-390, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mihail Busu & Cristian Busu, 2021. "Detecting Bid-Rigging in Public Procurement. A Cluster Analysis Approach," Administrative Sciences, MDPI, vol. 11(1), pages 1-14, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martina Nardon & Paolo Pianca, 2015. "Probability weighting functions," Working Papers 2015:29, Department of Economics, University of Venice "Ca' Foscari".
    2. Salvatore Greco & Fabio Rindone, 2014. "The bipolar Choquet integral representation," Theory and Decision, Springer, vol. 77(1), pages 1-29, June.
    3. Özalp Özer & Yanchong Zheng, 2016. "Markdown or Everyday Low Price? The Role of Behavioral Motives," Management Science, INFORMS, vol. 62(2), pages 326-346, February.
    4. Daniel Cavagnaro & Mark Pitt & Richard Gonzalez & Jay Myung, 2013. "Discriminating among probability weighting functions using adaptive design optimization," Journal of Risk and Uncertainty, Springer, vol. 47(3), pages 255-289, December.
    5. Azevedo, Eduardo M. & Gottlieb, Daniel, 2012. "Risk-neutral firms can extract unbounded profits from consumers with prospect theory preferences," Journal of Economic Theory, Elsevier, vol. 147(3), pages 1291-1299.
    6. Martina Nardon & Paolo Pianca, 2019. "Behavioral premium principles," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 229-257, June.
    7. Foster, Joshua & Deck, Cary & Farmer, Amy, 2019. "Behavioral demand effects when buyers anticipate inventory shortages," European Journal of Operational Research, Elsevier, vol. 276(1), pages 217-234.
    8. Martina Nardon & Paolo Pianca, 2019. "European option pricing under cumulative prospect theory with constant relative sensitivity probability weighting functions," Computational Management Science, Springer, vol. 16(1), pages 249-274, February.
    9. Martina Nardon & Paolo Pianca, 2014. "European option pricing with constant relative sensitivity probability weighting function," Working Papers 2014:25, Department of Economics, University of Venice "Ca' Foscari".
    10. Mohammed Abdellaoui & Olivier L’Haridon & Horst Zank, 2010. "Separating curvature and elevation: A parametric probability weighting function," Journal of Risk and Uncertainty, Springer, vol. 41(1), pages 39-65, August.
    11. Foster, Gigi & Frijters, Paul & Schaffner, Markus & Torgler, Benno, 2018. "Expectation formation in an evolving game of uncertainty: New experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 379-405.
    12. Che-Yuan Liang, 2017. "Optimal inequality behind the veil of ignorance," Theory and Decision, Springer, vol. 83(3), pages 431-455, October.
    13. Kerim Keskin, 2016. "Inverse S-shaped probability weighting functions in first-price sealed-bid auctions," Review of Economic Design, Springer;Society for Economic Design, vol. 20(1), pages 57-67, March.
    14. Ariane Charpin, 2018. "Tests des modèles de décision en situation de risque. Le cas des parieurs hippiques en France," Revue économique, Presses de Sciences-Po, vol. 69(5), pages 779-803.
    15. Mohammed Abdellaoui & Horst Zank, 2023. "Source and rank-dependent utility," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 75(4), pages 949-981, May.
    16. Basieva, Irina & Khrennikova, Polina & Pothos, Emmanuel M. & Asano, Masanari & Khrennikov, Andrei, 2018. "Quantum-like model of subjective expected utility," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 150-162.
    17. Gul, Faruk & Pesendorfer, Wolfgang, 2015. "Hurwicz expected utility and subjective sources," Journal of Economic Theory, Elsevier, vol. 159(PA), pages 465-488.
    18. Galarza, Francisco, 2009. "Choices under Risk in Rural Peru," MPRA Paper 17708, University Library of Munich, Germany.
    19. Santos-Pinto, Luís & Astebro, Thomas & Mata, José, 2009. "Preference for Skew in Lotteries: Evidence from the Laboratory," MPRA Paper 17165, University Library of Munich, Germany.
    20. M. Pelé & M. Broihanne & B. Thierry & J. Call & V. Dufour, 2014. "To bet or not to bet? Decision-making under risk in non-human primates," Journal of Risk and Uncertainty, Springer, vol. 49(2), pages 141-166, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jgames:v:9:y:2018:i:4:p:79-:d:174303. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.