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Procurement auctions with avoidable fixed costs: an experimental approach

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  • Larson, Nathan
  • Elmaghraby, Wedad

Abstract

Bidders in procurement auctions often face avoidable fixed costs. This can make bidding decisions complex and risky, and market outcomes volatile. If bidders deviate from risk neutral best responses, either due to faulty optimization or risk attitudes, then equilibrium predictions can perform poorly. In this paper, we confront laboratory bidders with three auction formats that make bidding difficult and risky in different ways. We find that measures of `difficulty' provide a consistent explanation of deviations from best response bidding across the three formats. In contrast, risk and loss preferences cannot explain behavior across all three formats.

Suggested Citation

  • Larson, Nathan & Elmaghraby, Wedad, 2008. "Procurement auctions with avoidable fixed costs: an experimental approach," MPRA Paper 32163, University Library of Munich, Germany, revised 2011.
  • Handle: RePEc:pra:mprapa:32163
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    References listed on IDEAS

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    1. Anthony M. Kwasnica & John O. Ledyard & Dave Porter & Christine DeMartini, 2005. "A New and Improved Design for Multiobject Iterative Auctions," Management Science, INFORMS, vol. 51(3), pages 419-434, March.
    2. Paul Klemperer, 2002. "What Really Matters in Auction Design," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 169-189, Winter.
    3. Peter Cramton & John McMillan & Paul Milgrom & Bradley Miller & Bridger Mitchell & Daniel Vincent & Robert Wilson, 1998. "Simultaneous Ascending Auctions with Package Bidding," Papers of Peter Cramton 98cra2, University of Maryland, Department of Economics - Peter Cramton.
    4. Cramton, Peter & Stoft, Steven, 2007. "Why We Need to Stick with Uniform-Price Auctions in Electricity Markets," The Electricity Journal, Elsevier, vol. 20(1), pages 26-37.
    5. John O. Ledyard & Mark Olson & David Porter & Joseph A. Swanson & David P. Torma, 2002. "The First Use of a Combined-Value Auction for Transportation Services," Interfaces, INFORMS, vol. 32(5), pages 4-12, October.
    6. Ausubel Lawrence M & Milgrom Paul R, 2002. "Ascending Auctions with Package Bidding," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 1(1), pages 1-44, August.
    7. Yechiam, Eldad & Busemeyer, Jerome R., 2008. "Evaluating generalizability and parameter consistency in learning models," Games and Economic Behavior, Elsevier, vol. 63(1), pages 370-394, May.
    8. Charles R. Plott, 1997. "Laboratory Experimental Testbeds: Application to the PCS Auction," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 6(3), pages 605-638, September.
    9. Kenneth E. Train & Daniel L. McFadden & Moshe Ben-Akiva, 1987. "The Demand for Local Telephone Service: A Fully Discrete Model of Residential Calling Patterns and Service Choices," RAND Journal of Economics, The RAND Corporation, vol. 18(1), pages 109-123, Spring.
    10. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    11. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    12. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    13. Michael H. Rothkopf, 2007. "Thirteen Reasons Why the Vickrey-Clarke-Groves Process Is Not Practical," Operations Research, INFORMS, vol. 55(2), pages 191-197, April.
    14. Daniel Kahneman & Jack L. Knetsch & Richard H. Thaler, 1991. "Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias," Journal of Economic Perspectives, American Economic Association, vol. 5(1), pages 193-206, Winter.
    15. Terry Jones & Stephanie Forrest, 1995. "Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms," Working Papers 95-02-022, Santa Fe Institute.
    16. Page, Scott E, 1996. "Two Measures of Difficulty," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 8(2), pages 321-346, August.
    17. Cramton, Peter, 1998. "Ascending auctions," European Economic Review, Elsevier, vol. 42(3-5), pages 745-756, May.
    18. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    19. Scott E. Page, 1996. "Two measures of difficulty (*)," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 8(2), pages 321-346.
    20. Van Boening, Mark V & Wilcox, Nathaniel T, 1996. "Avoidable Cost: Ride a Double Auction Roller Coaster," American Economic Review, American Economic Association, vol. 86(3), pages 461-477, June.
    21. Michael H. Rothkopf & Aleksandar Pekev{c} & Ronald M. Harstad, 1998. "Computationally Manageable Combinational Auctions," Management Science, INFORMS, vol. 44(8), pages 1131-1147, August.
    22. Elena Katok & Alvin E. Roth, 2004. "Auctions of Homogeneous Goods with Increasing Returns: Experimental Comparison of Alternative "Dutch" Auctions," Management Science, INFORMS, vol. 50(8), pages 1044-1063, August.
    23. Goeree, Jacob K. & Holt, Charles A., 2010. "Hierarchical package bidding: A paper & pencil combinatorial auction," Games and Economic Behavior, Elsevier, vol. 70(1), pages 146-169, September.
    24. Hobbs, Benjamin F. & Rothkopf, Michael H. & Hyde, Laurel C. & O'Neill, Richard P., 2000. "Evaluation of a Truthful Revelation Auction in the Context of Energy Markets with Nonconcave Benefits," Journal of Regulatory Economics, Springer, vol. 18(1), pages 5-32, July.
    25. Groves, Theodore, 1973. "Incentives in Teams," Econometrica, Econometric Society, vol. 41(4), pages 617-631, July.
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    More about this item

    Keywords

    Auctions; Experimental; Procurement; Synergies; Asymmetric Bidders; Learning; Optimization errors;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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