An Approximate Dynamic Programming Approach to Solving Dynamic Oligopoly Models
Coauthor(s): Vivek Farias, Denis Saure.
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In this paper we introduce a new method to approximate Markov perfect equilibrium in large scale Ericson and Pakes (1995)-style dynamic oligopoly models that are not amenable to exact solution due to the curse of dimensionality. The method is based on an algorithm that iterates an approximate best response operator using an approximate dynamic programming approach. The method, based on linear programming, approximates the value function with a linear combination of basis functions. We provide results that lend theoretical support to our approach. We introduce a rich, yet tractable set of basis functions and test our method on important classes of models. Our results suggest that the approach we propose significantly expands the set of dynamic oligopoly models that can be analyzed computationally.
Source: Working Paper
Farias, Vivek, Denis Saure, and Gabriel Weintraub. "An Approximate Dynamic Programming Approach to Solving Dynamic Oligopoly Models." Working Paper, Columbia Business School, July 2011.