SIMULATION-BASED INFERENCE - A SURVEY WITH SPECIAL REFERENCE TO PANEL-DATA MODELS

In this article we study the recent developments of inference methods based on simulations. In particular, we discuss the Simulated Generali zed Method of Moments. the Simulated Maximum Likelihood Method. and th e Simulated Pseudo Maximum Likelihood Methods. The asymptotic properti es of the estimators are described when the number of observations n g oes to infinity, and we distinguish the case where the number H of sim ulations per observation is fixed from the case where this number also goes to infinity. In the former case, the possible asymptotic bias is evaluated and. in the latter case, we carefully examine the consequen ces of the assumptions on the relative divergence rates of n and H. We also show how these methods apply to various contexts, in particular to the case of panel data models.