THE ASYMPTOTIC PROPERTIES OF THE SYSTEM GMM ESTIMATOR IN DYNAMIC PANEL DATA MODELS WHEN BOTHNANDTARE LARGE
推导了在截面维N和时间维T都很大时，动态面板数据模型中系统GMM估计量的渐近性质，证明使用次优加权矩阵时两步系统GMM估计量仍一致，支持其在N和T都大的场景下使用。
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.