Computational Methods for Oblivious Equilibrium

Gabriel Y. Weintraub (), C. Lanier Benkard () and Benjamin Van Roy ()
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Gabriel Y. Weintraub: Business School, Columbia University, New York, New York 10027
C. Lanier Benkard: Department of Economics, Yale University, New Haven, Connecticut 06511
Benjamin Van Roy: Stanford University, Stanford, California 94305

Operations Research, 2010, vol. 58, issue 4-part-2, 1247-1265

Abstract: Oblivious equilibrium is a new solution concept for approximating Markov-perfect equilibrium in dynamic models of imperfect competition among heterogeneous firms. In this paper, we present algorithms for computing oblivious equilibrium and for bounding approximation error. We report results from computational case studies that serve to assess both efficiency of the algorithms and accuracy of oblivious equilibrium as an approximation to Markov-perfect equilibrium. We also extend the definition of oblivious equilibrium, originally proposed for models with only firm-specific idiosyncratic random shocks, and our algorithms to accommodate models with industry-wide aggregate shocks. Our results suggest that, by using oblivious equilibrium to approximate Markov-perfect equilibrium, it is possible to greatly increase the set of dynamic models of imperfect competition that can be analyzed computationally.

Keywords: games/group decisions; stochastic; dynamic programming/optimal control; Markov (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (12)

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