This paper shows that the payoff functions in a class of dynamic games of incomplete information are nonparametrically identified under standard assumptions currently used in applied work. Models of this kind are prevalent in empirical industrial organization where, for example, firms in...

In this article, we consider two recently proposed semiparametric estimators for distribution-free binary response models under a conditional median restriction. We show that these estimators can be implemented in Stata by using the nl command through simple modifications to the nonlinear...

When a continuous time model is sampled only at equally spaced intervals, a priori restrictions on the parameters can provide natural identifying restrictions which serve to rule out otherwise observationally equivalent parameter values. Specifically, we consider identification of the parameter...

This paper develops methods for estimating dynamic structural microeconomic models with serially correlated latent state variables. The proposed estimators are based on sequential Monte Carlo methods, or particle filters, and simultaneously estimate both the structural parameters and the...

This paper revisits the question of parameter identification when a linear continuous time model is sampled only at equispaced points in time. Following the framework and assumptions of Phillips (1973), we consider models characterized by first-order, linear systems of stochastic differential...