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Econometrica Vol. 75 No. 5 2007

Estimating Dynamic Models of Imperfect Competition

Patrick Bajari1; C. Lanier Benkard2; Jonathan Levin2

1 University of Minnesota · 2 Stanford University

Abstract

We describe a two-step algorithm for estimating dynamic games under the assumption that behavior is consistent with Markov perfect equilibrium. In the first step, the policy functions and the law of motion for the state variables are estimated. In the second step, the remaining structural parameters are estimated using the optimality conditions for equilibrium. The second step estimator is a simple simulated minimum distance estimator. The algorithm applies to a broad class of models, including industry competition models with both discrete and continuous controls such as the Ericson and Pakes (1995) model. We test the algorithm on a class of dynamic discrete choice models with normally distributed errors and a class of dynamic oligopoly models similar to that of Pakes and McGuire (1994).

DOI
10.1111/j.1468-0262.2007.00796.x
Volume
75
Issue
5
Pages
1331-1370
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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