On the identification of models with conditional characteristic functions

Abstract

In this paper, we revisit a potential identification failure of estimation of models based on conditional characteristic functions. An arbitrary choice of moment conditions does not guarantee the parameter identifiability. We show that moment conditions based on the conditional characteristic functions and an exponential instrument satisfy the identification condition. We also provide a consistent GMM estimator that is computationally tractable and its asymptotic properties. This paper could provide useful guidelines to empirical researchers estimating this class of models.