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Convergence Rates in Resource Allocation Games

Author

Listed:
  • Daniel Graydon Stephenson

    (Department of Economics, VCU School of Business)

Abstract
If Nash equilibrium corresponds to the long run outcome of a dy- namic process, its usefulness as a predictive tool may depend on the rate of convergence to equilibrium. This paper experimentally tests theoretical predictions about the rate of convergence to equilibrium in settings where agents simultaneously allocate resources between contests with complementary prizes. More responsive contest suc- cess functions give agents a stronger incentive to best respond, but learning models predict slower convergence to equilibrium under more responsive success functions because of the incentives agents face out of equilibrium. Consistent with learning model predictions, we observe slower convergence under more responsive success functions, suggest- ing that disequilibrium incentives contain useful information about the rate of convergence to equilibrium in empirical settings.

Suggested Citation

  • Daniel Graydon Stephenson, 2023. "Convergence Rates in Resource Allocation Games," Working Papers 2304, VCU School of Business, Department of Economics.
    • Handle: RePEc:vcu:wpaper:2304
    as

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    File URL: https://danielgstephenson.com/items/AllocationGames.pdf
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    References listed on IDEAS

    as
    1. Yan Chen & Robert Gazzale, 2004. "When Does Learning in Games Generate Convergence to Nash Equilibria? The Role of Supermodularity in an Experimental Setting," American Economic Review, American Economic Association, vol. 94(5), pages 1505-1535, December.
    2. Teck H. Ho & Xin Wang & Colin F. Camerer, 2008. "Individual Differences in EWA Learning with Partial Payoff Information," Economic Journal, Royal Economic Society, vol. 118(525), pages 37-59, January.
    3. Daniel Stephenson, 2022. "Assignment feedback in school choice mechanisms," Experimental Economics, Springer;Economic Science Association, vol. 25(5), pages 1467-1491, November.
    4. Nagel, Rosemarie, 1995. "Unraveling in Guessing Games: An Experimental Study," American Economic Review, American Economic Association, vol. 85(5), pages 1313-1326, December.
    5. Daniel Graydon Stephenson, 2023. "Multi-battle contests over complementary battlefields," Working Papers 2303, VCU School of Business, Department of Economics.
    6. Colin F. Camerer & Teck-Hua Ho & Juin-Kuan Chong, 2004. "A Cognitive Hierarchy Model of Games," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(3), pages 861-898.
    7. TeckH. Ho & Xin Wang & ColinF. Camerer, 2008. "Individual Differences in EWA Learning with Partial Payoff Information," Economic Journal, Royal Economic Society, vol. 118(525), pages 37-59, January.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    convergence; equilibrium; allocation; contest; learning;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D74 - Microeconomics - - Analysis of Collective Decision-Making - - - Conflict; Conflict Resolution; Alliances; Revolutions
    • Q34 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Natural Resources and Domestic and International Conflicts

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