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The competitive market paradox

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  • Gjerstad, Steven

Abstract

The competitive market model is a paradoxical. In perfect competition, agents cannot influence price: they only select an output quantity. Such passive behavior doesn t conform to the intuitive notion of competition. This paper describes an experiment which demonstrates that near or even at a competitive equilibrium price, competition is undiminished. A substantial difference between the performance of sellers and buyers frequently results from this vigorous competition, even with low price variability and approximate efficiency. In double auction experiment sessions conducted with both automated and human agents, exogenous variation of the pace of asks and bids of automated agents demonstrates that the performance difference between sellers and buyers results primarily from a difference between the pace of asks and bids. If the buyers pace is slower than sellers pace, buyers make price concessions less frequently than sellers so that prices move below the equilibrium price. Then more buyers become active and fewer sellers remain active. Prices stabilize when changes to the numbers of active buyers and sellers offset the superior bargaining capability of one side or the other. In competitive equilibrium, to a first approximation agents are price takers, but that doesn t preclude vigorous competition: competitive behavior moves to the dimension of bargaining pace.
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  • Gjerstad, Steven, 2007. "The competitive market paradox," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1753-1780, May.
  • Handle: RePEc:eee:dyncon:v:31:y:2007:i:5:p:1753-1780
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    References listed on IDEAS

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    1. Rubinstein, Ariel, 1982. "Perfect Equilibrium in a Bargaining Model," Econometrica, Econometric Society, vol. 50(1), pages 97-109, January.
    2. Cason, Timothy N. & Friedman, Daniel, 1996. "Price formation in double auction markets," Journal of Economic Dynamics and Control, Elsevier, vol. 20(8), pages 1307-1337, August.
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    Cited by:

    1. Corgnet, Brice & DeSantis, Mark & Siemroth, Christoph, 2023. "Algorithmic Trading, Price Efficiency and Welfare: An Experimental Approach," Economics Discussion Papers 36273, University of Essex, Department of Economics.
    2. Steven Gjerstad, 2013. "Price dynamics in an exchange economy," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(2), pages 461-500, March.
    3. Marta Posada & Cesáreo Hernández & Adolfo López-Paredes, 2008. "Testing Marshallian And Walrasian Instability With An Agent-Based Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 249-260.
    4. Xintong Wang & Christopher Hoang & Yevgeniy Vorobeychik & Michael P. Wellman, 2021. "Spoofing the Limit Order Book: A Strategic Agent-Based Analysis," Games, MDPI, vol. 12(2), pages 1-43, May.
    5. Angerer, Martin & Neugebauer, Tibor & Shachat, Jason, 2023. "Arbitrage bots in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 206(C), pages 262-278.
    6. Steven Gjerstad & Jason M. Shachat, 2007. "Individual Rationality and Market Efficiency," Purdue University Economics Working Papers 1204, Purdue University, Department of Economics.
    7. Yan Peng & Jason Shachat & Lijia Wei & S. Sarah Zhang, 2024. "Speed traps: algorithmic trader performance under alternative market balances and structures," Experimental Economics, Springer;Economic Science Association, vol. 27(2), pages 325-350, April.
    8. David Byrd, 2019. "Explaining Agent-Based Financial Market Simulation," Papers 1909.11650, arXiv.org.
    9. March, Christoph, 2021. "Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer players," Journal of Economic Psychology, Elsevier, vol. 87(C).
    10. Caginalp, Carey & Caginalp, Gunduz, 2020. "Derivation of non-classical stochastic price dynamics equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    11. Carey Caginalp & Gunduz Caginalp, 2019. "Derivation of non-classical stochastic price dynamics equations," Papers 1908.01103, arXiv.org, revised Aug 2020.
    12. Svitlana Vyetrenko & David Byrd & Nick Petosa & Mahmoud Mahfouz & Danial Dervovic & Manuela Veloso & Tucker Hybinette Balch, 2019. "Get Real: Realism Metrics for Robust Limit Order Book Market Simulations," Papers 1912.04941, arXiv.org.
    13. Te Bao & Elizaveta Nekrasova & Tibor Neugebauer & Yohanes E. Riyanto, 2022. "Algorithmic trading in experimental markets with human traders: A literature survey," Chapters, in: Sascha Füllbrunn & Ernan Haruvy (ed.), Handbook of Experimental Finance, chapter 23, pages 302-322, Edward Elgar Publishing.
    14. Gunduz Caginalp, 2020. "Fat tails arise endogenously in asset prices from supply/demand, with or without jump processes," Papers 2011.08275, arXiv.org, revised Mar 2021.

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    More about this item

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D41 - Microeconomics - - Market Structure, Pricing, and Design - - - Perfect Competition
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

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