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Information Variability Impacts in Auctions

Author

Listed:
  • Justin Jia

    (Smeal College of Business, Pennsylvania State University, University Park, Pennsylvania 16802)

  • Ronald M. Harstad

    (Department of Economics, University of Missouri, Columbia, Missouri 65211)

  • Michael H. Rothkopf

    (Formerly at the Smeal College of Business, Pennsylvania State University, University Park, Pennsylvania 16802)

Abstract

A wide variety of auction models exhibit close relationships between expected revenue and the second-highest order statistic of bidders' expected asset values. Similarly close relationships between the winner's expected profit and the expected difference between the highest and second-highest order statistics of bidders' information are also common. We use stochastic orderings to see when greater environmental variability of bidders' information enhances expected profit and expected revenue.

Suggested Citation

  • Justin Jia & Ronald M. Harstad & Michael H. Rothkopf, 2010. "Information Variability Impacts in Auctions," Decision Analysis, INFORMS, vol. 7(1), pages 137-142, March.
    • Handle: RePEc:inm:ordeca:v:7:y:2010:i:1:p:137-142
    DOI: 10.1287/deca.1090.0163
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    References listed on IDEAS

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    1. Mark Bagnoli & Ted Bergstrom, 2006. "Log-concave probability and its applications," Studies in Economic Theory, in: Charalambos D. Aliprantis & Rosa L. Matzkin & Daniel L. McFadden & James C. Moore & Nicholas C. Yann (ed.), Rationality and Equilibrium, pages 217-241, Springer.
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    3. Bergemann, Dirk & Pesendorfer, Martin, 2007. "Information structures in optimal auctions," Journal of Economic Theory, Elsevier, vol. 137(1), pages 580-609, November.
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    5. Jacob K. Goeree & Theo Offerman, 2003. "Competitive Bidding in Auctions with Private and Common Values," Economic Journal, Royal Economic Society, vol. 113(489), pages 598-613, July.
    6. Dirk Bergemann & Juuso Valimaki, 2002. "Information Acquisition and Efficient Mechanism Design," Econometrica, Econometric Society, vol. 70(3), pages 1007-1033, May.
    7. Jeroen M. Swinkels & Wolfgang Pesendorfer, 2000. "Efficiency and Information Aggregation in Auctions," American Economic Review, American Economic Association, vol. 90(3), pages 499-525, June.
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    Citations

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    Cited by:

    1. Schweizer, Nikolaus & Szech, Nora, 2017. "Revenues and welfare in auctions with information release," Journal of Economic Theory, Elsevier, vol. 170(C), pages 86-111.
    2. Joaquín Coleff & Daniel Garcia, 2017. "Information Provision in Procurement Auctions," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 19(2), pages 426-444, April.
    3. Robert F. Bordley & Elena Katok & L. Robin Keller, 2010. "Honoring Michael H. Rothkopf's Legacy of Rigor and Relevance in Auction Theory: From the Editors," Decision Analysis, INFORMS, vol. 7(1), pages 1-4, March.
    4. Joaquín Coleff & Daniel Garcia, 2017. "Information Provision in Procurement Auctions," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 19(2), pages 426-444, April.
    5. Kirkegaard, René, 2014. "Ranking asymmetric auctions: Filling the gap between a distributional shift and stretch," Games and Economic Behavior, Elsevier, vol. 85(C), pages 60-69.

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    More about this item

    Keywords

    auctions; revenue; expected profit; order statistics; stochastic orderings;
    All these keywords.

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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