Estimating Dynamic Models of Imperfect Competition

Jonathan Levin and P. Bajari

No 579, 2004 Meeting Papers from Society for Economic Dynamics

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 I.O.\ 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)

Keywords: oligopoly; markov; estimation (search for similar items in EconPapers)
JEL-codes: D43 L0 L13 (search for similar items in EconPapers)
Date: 2004
New Economics Papers: this item is included in nep-com, nep-dcm, nep-ent and nep-mic
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Citations: View citations in EconPapers (17)

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Related works:
Journal Article: Estimating Dynamic Models of Imperfect Competition (2007)
Working Paper: Estimating Dynamic Models of Imperfect Competition (2007)
Working Paper: Estimating Dynamic Models of Imperfect Competition (2004)
Working Paper: Estimating Dynamic Models of Imperfect Competition (2004)
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