Abstract

We consider dynamic oligopoly models in the spirit of Ericson and Pakes (1995). We introduce a new computationally tractable model for industries with a few dominant firms and many fringe firms, in which firms keep track of the detailed state of dominant firms and of few moments of the distribution that describes the states of fringe firms. Based on this idea we introduce a new equilibrium concept that we call moment-based Markov equilibrium (MME). MME is behaviorally appealing and computationally tractable. However, because moments may not summarize all payoff relevant information, MME strategies may not be optimal. We propose different approaches to overcome this difficulty with varying degrees of restrictions on the model primitives and strategies. We illustrate our methods with computational experiments and show that they work well in empirically relevant models, and significantly extend the class of dynamic oligopoly models that can be studied computationally. In addition, our methods can also be used to improve approximations in other settings such as dynamic industry models with a continuum of firms and an aggregate shock and stochastic growth models.

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