Fast convergence in evolutionary models: A Lyapunov approach

Glenn Ellison (), Drew Fudenberg and Lorens A. Imhof

Journal of Economic Theory, 2016, vol. 161, issue C, 1-36

Abstract: Evolutionary models in which N players are repeatedly matched to play a game have “fast convergence” to a set A if the models both reach A quickly and leave A slowly, where “quickly” and “slowly” refer to whether the expected hitting and exit times remain bounded when N tends to infinity. We provide simple and general Lyapunov criteria which are sufficient for reaching quickly and leaving slowly. We use these criteria to determine aspects of learning models that promote fast convergence.

Keywords: Hitting time; Learning model; Local interaction; Lyapunov function; Markov chain; Recency (search for similar items in EconPapers)
JEL-codes: C69 C73 D83 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:161:y:2016:i:c:p:1-36

DOI: 10.1016/j.jet.2015.10.008

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