THE ASYMPTOTIC PROPERTIES OF THE SYSTEM GMM ESTIMATOR IN DYNAMIC PANEL DATA MODELS WHEN BOTH N AND T ARE LARGE

Abstract

In this paper, we derive the asymptotic properties of the system generalized method of moments (GMM) estimator in dynamic panel data models with individual and time effects when both N and T, the dimensions of cross-section and time series, are large. Specifically, we show that the two-step system GMM estimator is consistent when a suboptimal weighting matrix where off-diagonal blocks are set to zero is used. Such consistency results theoretically support the use of the system GMM estimator in large N and T contexts even though it was originally developed for large N and small T panels. Simulation results indicate that the large N and large T asymptotic results approximate the finite sample behavior reasonably well unless persistency of data is strong and/or the variance ratio of individual effects to the disturbances is large.