Testing panel data regression models with spatial error correlation
Testing panel data regression models with spatial error correlation
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DOI：
10.1016/s0304-4076(03)00120-9
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发表时间：
2003-11-01
影响因子：
6.3
通讯作者：
Koh, W
中科院分区：
文献类型：
--
作者：
Baltagi, BH;Song, SH;Koh, W
本文对具有空间误差相关性的面板数据回归模型进行了拉格朗日乘数(LM)检验。这些测试借鉴了早期工作的两个方面。第一个是在Anselin(空间计量经济学：方法和模型)中讨论的空间误差相关模型的LM测试；Kluwer学术出版社，Dordrecht；Rao‘s Score Testing in Space Econometrics，J.Statist。普拉姆。推理97(2001)113)和Anselin等人。(地区性科学。城市经济学人。26(1996)77)，第二个是对Breusch和Pagan(Rev.Econom)中讨论的误差分量面板数据模型的LM检验。种马。47(1980)239)和巴尔塔吉等人。(《经济计量学》54(1992)95)。其想法是在面板数据回归模型中同时考虑空间误差相关性和随机区域效应，并检验它们的联合意义。此外，本文还推导了条件LM检验，该检验在空间误差相关性存在的情况下检验随机区域效应。此外，在随机区域效应存在的情况下，空间误差相关性。这些条件LM测试是单向LM测试的替代，单向LM测试忽略空间误差相关性的存在而测试随机区域效应，或者单向LM测试忽略随机区域效应的存在。我们认为，这些联合的和有条件的LM测试防止了可能的误指定。进行了大量的蒙特卡罗实验来研究这些LM检验以及相应的似然比检验的性能。(C)2003爱思唯尔B.V.保留所有权利。
This paper derives several lagrange multiplier (LM) tests for the panel data regression model with spatial error correlation. These tests draw upon two strands of earlier work. The first is the LM tests for the spatial error correlation model discussed in Anselin (Spatial Econometrics: Methods and Models, Kluwer Academic Publishers, Dordrecht; Rao's score test in spatial econometrics, J. Statist. Plarm. Inference 97 (2001) 113) and Anselin et al. (Regional Sci. Urban Econom. 26 (1996) 77), and the second is the LM tests for the error component panel data model discussed in Breusch and Pagan (Rev. Econom. Stud. 47(1980) 239) and Baltagi et al. (J. Econometrics 54 (1992) 95). The idea is to allow for both spatial error correlation as well as random region effects in the panel data regression model and to test for their joint significance. Additionally, this paper derives conditional LM tests, which test for random regional effects given the presence of spatial error correlation. Also, spatial error correlation given the presence of random regional effects. These conditional LM tests are an alternative to the one-directional LM tests that test for random regional effects ignoring the presence of spatial error correlation or the one-directional LM tests for spatial error correlation ignoring the presence of random regional effects. We argue that these joint and conditional LM tests guard against possible misspecification. Extensive Monte Carlo experiments are conducted to study the performance of these LM tests as well as the corresponding likelihood ratio tests. (C) 2003 Elsevier B.V. All rights reserved.