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Prospect dynamics and loss dominance

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  • Sawa, Ryoji
  • Wu, Jiabin

Abstract

This paper investigates the role of loss-aversion in affecting the long-run equilibria of stochastic evolutionary dynamics. We consider a finite population of loss-averse agents who are repeatedly and randomly matched to play a symmetric two-player normal form game. When an agent revises her strategy, she compares the payoff from each strategy to a reference point. Under the resulting dynamics, called prospect dynamics, risk-dominance is no longer sufficient to guarantee stochastic stability in 2 × 2 coordination games. We propose a stronger concept, loss-dominance: a strategy is loss-dominant if it is risk-dominant and a maximin strategy. In 2 × 2 coordination games, the state where all agents play the loss-dominant strategy is uniquely stochastically stable under prospect dynamics for any degree of loss-aversion and all types of reference points. For symmetric two-player normal form games, a generalized concept, generalized loss-dominance, gives a sufficient condition for stochastic stability under prospect dynamics.

Suggested Citation

  • Sawa, Ryoji & Wu, Jiabin, 2018. "Prospect dynamics and loss dominance," Games and Economic Behavior, Elsevier, vol. 112(C), pages 98-124.
  • Handle: RePEc:eee:gamebe:v:112:y:2018:i:c:p:98-124
    DOI: 10.1016/j.geb.2018.07.006
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    Cited by:

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    2. Ennio Bilancini & Leonardo Boncinelli, 2020. "The evolution of conventions under condition-dependent mistakes," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 69(2), pages 497-521, March.
    3. Hwang, Sung-Ha & Rey-Bellet, Luc, 2021. "Positive feedback in coordination games: Stochastic evolutionary dynamics and the logit choice rule," Games and Economic Behavior, Elsevier, vol. 126(C), pages 355-373.
    4. Eugenio Vicario, 2021. "Imitation and Local Interactions: Long Run Equilibrium Selection," Games, MDPI, vol. 12(2), pages 1-19, April.
    5. Arigapudi, Srinivas, 2020. "Exit from equilibrium in coordination games under probit choice," Games and Economic Behavior, Elsevier, vol. 122(C), pages 168-202.
    6. Sawa, Ryoji, 2021. "A stochastic stability analysis with observation errors in normal form games," Games and Economic Behavior, Elsevier, vol. 129(C), pages 570-589.
    7. Roberto Rozzi, 2021. "Competing Conventions with Costly Information Acquisition," Games, MDPI, vol. 12(3), pages 1-29, June.
    8. Sawa, Ryoji, 2021. "A prospect theory Nash bargaining solution and its stochastic stability," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 692-711.
    9. Sawa, Ryoji & Wu, Jiabin, 2018. "Reference-dependent preferences, super-dominance and stochastic stability," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 96-104.
    10. Khan, Abhimanyu, 2022. "Expected utility versus cumulative prospect theory in an evolutionary model of bargaining," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    11. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    12. Nax, Heinrich H. & Newton, Jonathan, 2019. "Risk attitudes and risk dominance in the long run," Games and Economic Behavior, Elsevier, vol. 116(C), pages 179-184.

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    More about this item

    Keywords

    Evolutionary game theory; Behavioral game theory; Equilibrium selection; Loss-aversion; Prospect dynamic; Loss-dominance; Risk-dominance; Half-dominance; Maximin;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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