Estimating dynamic games of oligopolistic competition: an experimental investigation.

We evaluate standard assumptions in the estimation of dynamic oligopoly models with laboratory data. Using an entry/exit game, we estimate structural parameters under the assumption that the data are generated by a Markov‐perfect equilibrium and subsequently predict counterfactual behavior. If behav...

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Publicado en:RAND Journal of Economics (Wiley-Blackwell) Vol. 51; no. 2; pp. 447 - 470
Autores principales: Salz, Tobias, Vespa, Emanuel
Formato: Artículo
Publicado: Wiley-Blackwell Jun2020
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1111/1756-2171.12321
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        atl: Estimating dynamic games of oligopolistic competition: an experimental investigation.
      aug:
        au:
          Salz, Tobias
          Vespa, Emanuel
        affil:
          Massachusetts Institute of Technology
          UC Santa Barbara
      su:
        Forecasting
        Games
        Escape rooms
        Dynamic models
        Collusion
      sug:
        subj:
          Forecasting
          Games
          Toy and Hobby Goods and Supplies Merchant Wholesalers
          Doll, Toy, and Game Manufacturing
          Hobby, Toy, and Game Stores
          Escape rooms
          Dynamic models
          Collusion
      ab: We evaluate standard assumptions in the estimation of dynamic oligopoly models with laboratory data. Using an entry/exit game, we estimate structural parameters under the assumption that the data are generated by a Markov‐perfect equilibrium and subsequently predict counterfactual behavior. If behavior was collusive, however, the assumption would be violated and one would mispredict counterfactuals. The laboratory allows us to compare predicted behavior to true counterfactuals implemented as treatments. Our main finding is that prediction errors due to collusion are modest in size. We also document a different deviation from equilibrium behavior (inertia) that can lead to large prediction errors.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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