Identification and Estimation of Dynamic Games∗

This paper studies the identification problem in infinite horizon Markovian games and proposes a generally applicable estimation method. Every period firms simultaneously select an action from a finite set. We characterize the set of Markov equilibria. Period profits are a linear function of equilibrium choice probabilities. The question of identification of these values is then reduced to the existence of a solution to this linear equation system. We characterize the identification conditions. We propose a simple estimation procedure which follows the steps in the identification argument. The estimator is consistent, asymptotic normally distributed, and