BERK-NASH EQUILIBRIUM: A FRAMEWORK FOR MODELING AGENTS WITH MISSPECIFIED MODELS.

We develop an equilibrium framework that relaxes the standard assumption that people have a correctly specified view of their environment. Each player is characterized by a (possibly misspecified) subjective model, which describes the set of feasible beliefs over payoff-relevant consequences as a fu...

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Detalles Bibliográficos
Publicado en:Econometrica Vol. 84; no. 3; pp. 1093 - 1131
Autores principales: ESPONDA, IGNACIO, POUZO, DEMIAN
Formato: Artículo
Publicado: Wiley-Blackwell May2016
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2016
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        10.3982/ECTA12609
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        atl: BERK-NASH EQUILIBRIUM: A FRAMEWORK FOR MODELING AGENTS WITH MISSPECIFIED MODELS.
      aug:
        au:
          ESPONDA, IGNACIO
          POUZO, DEMIAN
        affil:
          Olin Business School, Washington University in St. Louis, 1 Brookings Drive, Campus Box 1133, St. Louis, MO 63130, U.S.A.
          Dept. of Economics, UC Berkeley, 530-1 Evans Hall #3880, Berkeley, CA 94720, U.S.A.
      su:
        Structural frames
        Modeling agencies
        Equilibrium
        Economics literature
        Statistics
      sug:
        subj:
          Employment placement agencies and executive search services
          Agents and Managers for Artists, Athletes, Entertainers, and Other Public Figures
          Framing Contractors
          Finish Carpentry Contractors
          Structural frames
          Modeling agencies
          Equilibrium
          Economics literature
          Statistics
      keyword:
        MisspecifiedBayesian learningequilibrium
        MisspecifiedBayesian learningequilibrium
      ab: We develop an equilibrium framework that relaxes the standard assumption that people have a correctly specified view of their environment. Each player is characterized by a (possibly misspecified) subjective model, which describes the set of feasible beliefs over payoff-relevant consequences as a function of actions. We introduce the notion of a Berk-Nash equilibrium: Each player follows a strategy that is optimal given her belief, and her belief is restricted to be the best fit among the set of beliefs she considers possible. The notion of best fit is formalized in terms of minimizing the Kullback- Leibler divergence, which is endogenous and depends on the equilibrium strategy profile. Standard solution concepts such as Nash equilibrium and self-confirming equilibrium constitute special cases where players have correctly specified models. We provide a learning foundation for Berk-Nash equilibrium by extending and combining results from the statistics literature on misspecified learning and the economics literature on learning in games.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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