IDEAS home Printed from https://ideas.repec.org/p/hit/hitcei/2010-8.html
   My bibliography  Save this paper

On the Asymptotic Distribution of the Transaction Price in a Clock Model of a Multi-Unit, Oral, Ascending-Price Auction within the Common-Value Paradigm

Author

Listed:
  • Hong, Han
  • Paarsch, Harry J.
  • Xu, Pai

Abstract

Using a clock model of a multi-unit, oral, ascending-price auction, within the commonvalue paradigm, we analyse the asymptotic behaviour of the transaction price as the number of bidders gets large. We find that even though the transaction price is determined by a (potentially small) fraction of losing drop-out bids, that price converges in probability to the ex ante unknown, true value. Subsequently, we derive the asymptotic distribution of the transaction price. Finally, we apply our methods to data from an auction of taxi license plates held in Shenzhen, China.

Suggested Citation

  • Hong, Han & Paarsch, Harry J. & Xu, Pai, 2010. "On the Asymptotic Distribution of the Transaction Price in a Clock Model of a Multi-Unit, Oral, Ascending-Price Auction within the Common-Value Paradigm," CEI Working Paper Series 2010-8, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    • Handle: RePEc:hit:hitcei:2010-8
    as

    Download full text from publisher

    File URL: https://hermes-ir.lib.hit-u.ac.jp/hermes/ir/re/29195/wp2010-8.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Mezzetti, Claudio & Tsetlin, Ilia, 2008. "On the lowest-winning-bid and the highest-losing-bid auctions," Journal of Mathematical Economics, Elsevier, vol. 44(9-10), pages 1040-1048, September.
    2. Milgrom, Paul R, 1981. "Rational Expectations, Information Acquisition, and Competitive Bidding," Econometrica, Econometric Society, vol. 49(4), pages 921-943, June.
    3. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    4. Jackson, Matthew O. & Kremer, Ilan, 2004. "The relationship between the allocation of goods and a seller's revenue," Journal of Mathematical Economics, Elsevier, vol. 40(3-4), pages 371-392, June.
    5. Milgrom, Paul R, 1979. "A Convergence Theorem for Competitive Bidding with Differential Information," Econometrica, Econometric Society, vol. 47(3), pages 679-688, May.
    6. Ilan Kremer, 2002. "Information Aggregation in Common Value Auctions," Econometrica, Econometric Society, vol. 70(4), pages 1675-1682, July.
    7. Robert Wilson, 1977. "A Bidding Model of Perfect Competition," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 44(3), pages 511-518.
    8. Milgrom,Paul, 2004. "Putting Auction Theory to Work," Cambridge Books, Cambridge University Press, number 9780521536721, September.
    9. Matthew O. Jackson & Ilan Kremer, 2006. "The Relevance of a Choice of Auction Format in a Competitive Environment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(4), pages 961-981.
    10. Wolfgang Pesendorfer & Jeroen M. Swinkels, 1997. "The Loser's Curse and Information Aggregation in Common Value Auctions," Econometrica, Econometric Society, vol. 65(6), pages 1247-1282, November.
    11. Hong, Han & Shum, Matthew, 2004. "Rates of information aggregation in common value auctions," Journal of Economic Theory, Elsevier, vol. 116(1), pages 1-40, May.
    12. Milgrom, Paul R & Weber, Robert J, 1982. "A Theory of Auctions and Competitive Bidding," Econometrica, Econometric Society, vol. 50(5), pages 1089-1122, September.
    13. Bikhchandani, Sushil & Haile, Philip A. & Riley, John G., 2002. "Symmetric Separating Equilibria in English Auctions," Games and Economic Behavior, Elsevier, vol. 38(1), pages 19-27, January.
    14. 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.
    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. Paulo Fagandini & Ingemar Dierickx, 2023. "Computing Profit-Maximizing Bid Shading Factors in First-Price Sealed-Bid Auctions," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1009-1035, March.

    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. Harstad, Ronald M. & Pekec, Aleksandar Sasa & Tsetlin, Ilia, 2008. "Information aggregation in auctions with an unknown number of bidders," Games and Economic Behavior, Elsevier, vol. 62(2), pages 476-508, March.
    2. García, Diego & Urošević, Branko, 2013. "Noise and aggregation of information in large markets," Journal of Financial Markets, Elsevier, vol. 16(3), pages 526-549.
    3. Mezzetti, Claudio & Tsetlin, Ilia, 2008. "On the lowest-winning-bid and the highest-losing-bid auctions," Journal of Mathematical Economics, Elsevier, vol. 44(9-10), pages 1040-1048, September.
    4. Alp E. Atakan & Mehmet Ekmekci, 2014. "Auctions, Actions, and the Failure of Information Aggregation," American Economic Review, American Economic Association, vol. 104(7), pages 2014-2048, July.
    5. Axelson, Ulf & Makarov, Igor, 2023. "Informational black holes in financial markets," LSE Research Online Documents on Economics 105042, London School of Economics and Political Science, LSE Library.
    6. Hernando-Veciana, Ángel & Tröge, Michael, 2011. "The insider's curse," Games and Economic Behavior, Elsevier, vol. 71(2), pages 339-350, March.
    7. Hong, Han & Shum, Matthew, 2004. "Rates of information aggregation in common value auctions," Journal of Economic Theory, Elsevier, vol. 116(1), pages 1-40, May.
    8. Diego García & Branko Urosevic, 2004. "Noise and aggregation of information in large markets," Economics Working Papers 785, Department of Economics and Business, Universitat Pompeu Fabra.
    9. Yin, Pai-Ling, 2007. "Empirical tests of information aggregation," International Journal of Industrial Organization, Elsevier, vol. 25(6), pages 1179-1189, December.
    10. Jackson, Matthew O. & Kremer, Ilan, 2007. "On the informational inefficiency of discriminatory price auctions," Journal of Economic Theory, Elsevier, vol. 132(1), pages 507-517, January.
    11. Murto, Pauli & Välimäki, Juuso, 2015. "Large common value auctions with risk averse bidders," Games and Economic Behavior, Elsevier, vol. 91(C), pages 60-74.
    12. Gadi Fibich & Arieh Gavious, 2010. "Large auctions with risk-averse bidders," International Journal of Game Theory, Springer;Game Theory Society, vol. 39(3), pages 359-390, July.
    13. Asriyan, Vladimir & Fuchs, William & Green, Brett, 2021. "Aggregation and design of information in asset markets with adverse selection," Journal of Economic Theory, Elsevier, vol. 191(C).
    14. Theo Offerman & Giorgia Romagnoli & Andreas Ziegler, 2022. "Why are open ascending auctions popular? The role of information aggregation and behavioral biases," Quantitative Economics, Econometric Society, vol. 13(2), pages 787-823, May.
    15. Committee, Nobel Prize, 2020. "Improvements to auction theory and inventions of new auction formats," Nobel Prize in Economics documents 2020-2, Nobel Prize Committee.
    16. Neeman, Zvika & Orosel, Gerhard O., 1999. "Herding and the Winner's Curse in Markets with Sequential Bids," Journal of Economic Theory, Elsevier, vol. 85(1), pages 91-121, March.
    17. Alp E. Atakan & Mehmet Ekmekci, 2021. "Market Selection and the Information Content of Prices," Econometrica, Econometric Society, vol. 89(5), pages 2049-2079, September.
    18. Tunca, Tunay I., 2008. "Information precision and asymptotic efficiency of industrial markets," Journal of Mathematical Economics, Elsevier, vol. 44(9-10), pages 964-996, September.
    19. 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.
    20. In-Koo Cho, 2004. "Monotonicity and Rationalizability in Large Uniform Price and Double Auctions," Theory workshop papers 658612000000000076, UCLA Department of Economics.

    More about this item

    Keywords

    common value; information aggregation; multi-unit auctions; taxis;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

    Statistics

    Access and download statistics

    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:hit:hitcei:2010-8. 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: Reiko Suzuki (email available below). General contact details of provider: https://edirc.repec.org/data/cehitjp.html .

    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.