Markov Perfect Industry Dynamics with Many Firms

59 Pages Posted: 5 Feb 2006 Last revised: 9 Jul 2022

See all articles by Gabriel Y. Weintraub

Gabriel Y. Weintraub

Stanford Graduate School of Business, Stanford University

C. Lanier Benkard

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

Benjamin Van Roy

Stanford University - Department of Management Science & Engineering

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Date Written: December 2005

Abstract

We propose an approximation method for analyzing Ericson and Pakes (1995)-style dynamic models of imperfect competition. We develop a simple algorithm for computing an ``oblivious equilibrium,'' in which each firm is assumed to make decisions based only on its own state and knowledge of the long run average industry state, but where firms ignore current information about competitors' states. We prove that, as the market becomes large, if the equilibrium distribution of firm states obeys a certain ``light-tail'' condition, then oblivious equilibria closely approximate Markov perfect equilibria. We develop bounds that can be computed to assess the accuracy of the approximation for any given applied problem. Through computational experiments, we find that the method often generates useful approximations for industries with hundreds of firms and in some cases even tens of firms.

Suggested Citation

Weintraub, Gabriel Y. and Benkard, C. Lanier and Van Roy, Benjamin, Markov Perfect Industry Dynamics with Many Firms (December 2005). NBER Working Paper No. w11900, Available at SSRN: https://ssrn.com/abstract=872736

Gabriel Y. Weintraub

Stanford Graduate School of Business, Stanford University ( email )

Stanford, CA 94305
United States

C. Lanier Benkard (Contact Author)

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)

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Cambridge, MA 02138
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Benjamin Van Roy

Stanford University - Department of Management Science & Engineering ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States