Computational Methods for Oblivious Equilibrium

Operations Research, Vol. 58, No. 4, pp. 1247-1265, July-August 2010

19 Pages Posted: 20 Oct 2011

See all articles by Gabriel Y. Weintraub

Gabriel Y. Weintraub

Stanford Graduate School of Business, Stanford University; Columbia University - Columbia Business School - Decision Risk and Operations

C. Lanier Benkard

Stanford Graduate School of Business; National Bureau of Economic Research (NBER)

Benjamin Van Roy

Stanford University - Management Science & Engineering

Multiple version iconThere are 2 versions of this paper

Date Written: 2010

Abstract

Oblivious equilibrium is a new solution concept for approximating Markov perfect equilibrium in dynamic models of imperfect competition among heterogeneous firms and has recently been used in multiple economic studies. 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.

Suggested Citation

Weintraub, Gabriel Y. and Benkard, C. Lanier and Van Roy, Benjamin, Computational Methods for Oblivious Equilibrium (2010). Operations Research, Vol. 58, No. 4, pp. 1247-1265, July-August 2010 . Available at SSRN: https://ssrn.com/abstract=1946494

Gabriel Y. Weintraub (Contact Author)

Stanford Graduate School of Business, Stanford University ( email )

Stanford, CA 94305
United States

Columbia University - Columbia Business School - Decision Risk and Operations ( email )

New York, NY
United States

C. Lanier Benkard

Stanford Graduate School of Business ( email )

Stanford, CA 94305-5015
United States
650-723-4124 (Phone)
650-725-0468 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Benjamin Van Roy

Stanford University - Management Science & Engineering ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

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