Efficient and Convergent Sequential Pseudo-Likelihood Estimation of Dynamic Discrete Games
动态离散博弈中高效且收敛的序贯伪似然估计
Abstract We propose a new sequential Efficient Pseudo-Likelihood (k-EPL) estimator for dynamic discrete choice games of incomplete information. k-EPL considers the joint behaviour of multiple players simultaneously, as opposed to individual responses to other agents’ equilibrium play. This, in addition to reframing the problem from conditional choice probability (CCP) space to value function space, yields a computationally tractable, stable, and efficient estimator. We show…