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The rate of convergence to perfect competition of matching and bargaining mechanisms

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  • Shneyerov, Artyom
  • Wong, Adam Chi Leung

Abstract

We study the steady state of a market with incoming cohorts of buyers and sellers who are matched pairwise and bargain under private information. A friction parameter is [tau], the length of the time period until the next meeting. We provide a necessary and sufficient condition for the convergence of mechanism outcomes to perfect competition at the linear rate in [tau], which is shown to be the fastest possible among all bargaining mechanisms. The condition requires that buyers and sellers always retain some bargaining power. The bargaining mechanisms that satisfy this condition are called nonvanishing bargaining power (NBP) mechanisms. Simple random proposer take-it-or-leave-it protocols are NBP, while k-double auctions (k-DA) are not. We find that k-DAs have equilibria that converge to perfect competition at a linear rate, converge at a slower rate or even do not converge at all.

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  • Shneyerov, Artyom & Wong, Adam Chi Leung, 2010. "The rate of convergence to perfect competition of matching and bargaining mechanisms," Journal of Economic Theory, Elsevier, vol. 145(3), pages 1164-1187, May.
  • Handle: RePEc:eee:jetheo:v:145:y:2010:i:3:p:1164-1187
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    Cited by:

    1. Shneyerov, Artyom & Wong, Adam Chi Leung, 2010. "Bilateral matching and bargaining with private information," Games and Economic Behavior, Elsevier, vol. 68(2), pages 748-762, March.
    2. Dipjyoti Majumdar & Artyom Shneyerov & Huan Xie, 2010. "How Optimism Leads to Price Discovery and Efficiency in a Dynamic Matching Market," Working Papers 10004, Concordia University, Department of Economics.
    3. Sergey K. Aityan, 2012. "Price-Value Potential for Near-Perfectly Competitive Markets," American Journal of Economics and Business Administration, Science Publications, vol. 3(4), pages 623-635, February.
    4. Andras Niedermayer & Artyom Shneyerov, 2014. "For‐Profit Search Platforms," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 765-789, August.
    5. Stephan Lauermann, 2013. "Dynamic Matching and Bargaining Games: A General Approach," American Economic Review, American Economic Association, vol. 103(2), pages 663-689, April.
    6. Dipjyoti Majumdar & Artyom Shneyerov & Huan Xie, 2016. "An optimistic search equilibrium," Review of Economic Design, Springer;Society for Economic Design, vol. 20(2), pages 89-114, June.
    7. Satterthwaite, Mark A. & Williams, Steven R. & Zachariadis, Konstantinos E., 2014. "Optimality versus practicality in market design: A comparison of two double auctions," Games and Economic Behavior, Elsevier, vol. 86(C), pages 248-263.
    8. Shneyerov, Artyom & Wong, Adam Chi Leung, 2011. "The role of private information in dynamic matching and bargaining: Can it be good for efficiency?," Economics Letters, Elsevier, vol. 112(1), pages 128-131, July.
    9. Shneyerov, Artyom & Wong, Adam C.L., 2020. "Price discovery in a matching and bargaining market with aggregate uncertainty," Games and Economic Behavior, Elsevier, vol. 124(C), pages 183-206.
    10. Lauermann, Stephan, 2012. "Asymmetric information in bilateral trade and in markets: An inversion result," Journal of Economic Theory, Elsevier, vol. 147(5), pages 1969-1997.
    11. Niedermayer, Andras & Wang, Chengsi, 2018. "A search model of rental markets: Who should pay the commission?," International Journal of Industrial Organization, Elsevier, vol. 58(C), pages 214-235.
    12. Shneyerov, Artyom, 2014. "A Walrasian Rubinstein and Wolinsky model," Economics Letters, Elsevier, vol. 124(2), pages 314-317.
    13. Klaus Kultti, 2010. "Inefficiency caused by random matching and heterogeneity," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 9(1), pages 19-28, April.

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    More about this item

    Keywords

    Matching and bargaining Search Double auctions Foundations for perfect competition Rate of convergence;

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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