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Evolutionary equilibrium in contests with stochastic participation: Entry, effort and overdissipation

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  • Gu, Yiquan
  • Hehenkamp, Burkhard
  • Leininger, Wolfgang

Abstract

This paper examines the evolutionary stability of behaviour in contests where players’ participation can be stochastic. We find, for exogenously given participation probabilities, players exert more effort under the concept of a finite-population evolutionarily stable strategy (FPESS) than under Nash equilibrium (NE). We show that there is ex-ante overdissipation under FPESS for sufficiently large participation probabilities, if, and only if, the impact function is convex. With costly endogenous entry, players enter the contest with a higher probability and exert more effort under FPESS than under NE. Importantly, under endogenous entry, overdissipation can occur for all (Tullock) contest success functions, in particular those with concave impact functions.

Suggested Citation

  • Gu, Yiquan & Hehenkamp, Burkhard & Leininger, Wolfgang, 2019. "Evolutionary equilibrium in contests with stochastic participation: Entry, effort and overdissipation," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 469-485.
  • Handle: RePEc:eee:jeborg:v:164:y:2019:i:c:p:469-485
    DOI: 10.1016/j.jebo.2019.06.011
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    Keywords

    Contests with stochastic participation; Overdissipation; Evolutionarily stable strategy; Finite population; Endogenous entry;

    JEL classification:

    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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