Estimating Dynamic Games of Complete Information with an Application to the Generic Pharmaceutical Industry * A. Ronald Gallant Duke University Fuqua School of Business Durham NC 27708-0120 USA Han Hong Stanford University Department of Economics Stanford CA 94305-6072 USA Ahmed Khwaja Duke University Fuqua School of Business Durham NC 27708-0120 USA First draft: January 2008 Abstract We estimate a dynamic oligopolistic entry model for the generic pharmaceutical industry that allows for dynamic spillovers from experience due to entry on future costs. Our paper contributes to both the estimation of oligopolistic dynamic games and the understanding of entry decisions in the pharmaceutical industry. Our dynamic model features unobserved firm production costs that are serially correlated over time. This introduces difficulty in the estimation of the dynamic game theoretic model which we overcome using sequential importance sampling methods. Our empirical findings show that the dynamic evolution of the production cost plays an important role in the equilibrium path of the pharmaceutical industry structure. Keywords: Dynamic Games, Dynamic Spillovers, Generic Pharmaceuticals, Se- quential Importance Sampling. JEL Classification: E00, G12, C51, C52 * Supported by the National Science Foundation. 1