Panel data models with spatially correlated error components
Panel data models with spatially correlated error components
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DOI：
10.1016/j.jeconom.2006.09.004
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发表时间：
2007-09-01
影响因子：
6.3
通讯作者：
Prucha, Ingmar R.
中科院分区：
文献类型：
--
作者：
Kapoor, Mudit;Kelejian, Harry H.;Prucha, Ingmar R.
在本文中，我们考虑了一个面板数据模型的误差成分，空间和时间的相关。该模型混合规格通常认为在空间文献中与那些被认为是在错误的组成部分文献。我们介绍了Kelejian和Prucha（1999）提出的广义矩估计的推广。空间模型中自回归参数的广义矩估计。International Economic Review 40，509-533），用于估计空间自回归参数和扰动过程的方差分量。然后，我们使用这些估计量来定义一个可行的广义最小二乘回归参数的程序。我们给出了正式的大样本结果所提出的估计。我们强调，我们的估计仍然是计算上可行的，即使在大样本。(C)2006 Elsevier B. V.保留所有权利。
In this paper we consider a panel data model with error components that are both spatially and time-wise correlated. The model blends specifications typically considered in the spatial literature with those considered in the error components literature. We introduce generalizations of the generalized moments estimators suggested in Kelejian and Prucha (1999. A generalized moments estimator for the autoregressive parameter in a spatial model. International Economic Review 40, 509-533) for estimating the spatial autoregressive parameter and the variance components of the disturbance process. We then use those estimators to define a feasible generalized least squares procedure for the regression parameters. We give formal large sample results for the proposed estimators. We emphasize that our estimators remain computationally feasible even in large samples. (C) 2006 Elsevier B.V. All rights reserved.