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Tempered Best Response Dynamics

Author

Listed:
  • Dai Zusai

    () (Department of Economics, Temple University)

Abstract

We propose a new deterministic evolutionary dynamic—the tempered best response dynamic (tBRD)---to capture two features of economic decision making: optimization and continuous sensitivity to incentives. That is, in the tBRD, an agent is more likely to revise his action when his current payoff is further from the optimal payoff, and he always switches to an optimal action when revising. The tBRD is a payoff monotone selection like the replicator dynamic, which makes medium and long-run outcomes more consistent with predictions from equilibrium refinement than the BRD in some situations. The technical contribution of the tBRD is continuous sensitivity, which allows us to apply results of a system of piecewise differential equations in order to obtain conditions for uniqueness and stability of solutions.

Suggested Citation

  • Dai Zusai, 2013. "Tempered Best Response Dynamics," DETU Working Papers 1301, Department of Economics, Temple University.
  • Handle: RePEc:tem:wpaper:1301
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    File URL: http://www.cla.temple.edu/RePEc/documents/DETU_13_01.pdf
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    References listed on IDEAS

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    Cited by:

    1. Sawa, Ryoji & Zusai, Dai, 2014. "Evolutionary imitative dynamics with population-varying aspiration levels," Journal of Economic Theory, Elsevier, vol. 154(C), pages 562-577.

    More about this item

    Keywords

    best response dynamic; payoff monotonicity; status-quo bias; switching costs; proper equilibrium; piecewise differential equations;

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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