Estimating Sequential-Move Games by a Recursive Conditioning Simulator

Sequential decision making among agents is a noticeable feature in strategic interactions in many subjects. The full estimation of sequential games, however, has been problematic due to the computational burden, especially when the game is large and asymmetric. In this paper, I propose an estimation method for discrete choice sequential games that is computationally feasible, easy-to-implement, and efficient, by modifying the Geweke-Hajivassiliou-Keane (GHK) simulator, the most widely used probit simulator. I show that the recursive nature of the GHK simulator is easily dovetailed with the sequential structure of strategic interactions