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

Kazuhiko Hayakawa

Econometric Theory, 2015, vol. 31, issue 3, 647-667

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.

Date: 2015
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