We thank the co-editor and three anonymous referees for detailed and constructive suggestions. The paper has benefited from our conversations with Jeremy Fox, Phil Haile, Igal Hendel, Guido Imbens, Phillip Leslie, Ariel Pakes, Peter Reiss, Azeem Shaikh, Elie Tamer, and Ed Vytlacil. Matthew Osborne provided exemplary research assistance. We thank the Bureau of Economic Analysis and the National Science Foundation for financial support.
Estimating Dynamic Models of Imperfect Competition
Article first published online: 3 AUG 2007
Volume 75, Issue 5, pages 1331–1370, September 2007
How to Cite
Bajari, P., Benkard, C. L. and Levin, J. (2007), Estimating Dynamic Models of Imperfect Competition. Econometrica, 75: 1331–1370. doi: 10.1111/j.1468-0262.2007.00796.x
- Issue published online: 3 AUG 2007
- Article first published online: 3 AUG 2007
- Manuscript received July, 2005; final revision received November, 2006.
- Markov perfect equilibrium;
- dynamic games;
- incomplete models;
- bounds estimation
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).