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A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model

机译:用于固定效应面板数据模型中横截面依赖性的拉格朗日乘数检验

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摘要

It is well known that the standard Breusch and Pagan (1980) LM test for cross-equation correlation in a SUR model is not appropriate for testing cross-sectional dependence in panel data models when the number of cross-sectional units (n) is large and the number of time periods (T) is small. In fact, a scaled version of this LM test was proposed by Pesaran (2004) and its finite sample bias was corrected by Pesaran et al. (2008). This was done in the context of a heterogeneous panel data model. This paper derives the asymptotic bias of this scaled version of the LM test in the context of a fixed effects homogeneous panel data model. This asymptotic bias is found to be a constant related to n and T, which suggests a simple bias corrected LM test for the null hypothesis. Additionally, the paper carries out some Monte Carlo experiments to compare the finite sample properties of this proposed test with existing tests for cross-sectional dependence. (C) 2012 Elsevier B.V. All rights reserved.
机译:众所周知,当横截面单位数(n)大时,用于SUR模型中交叉方程相关性的标准Breusch和Pagan(1980)LM测试不适用于测试面板数据模型中的横截面依赖性。并且时间段(T)的数量很少。实际上,Pesaran(2004)提出了这种LM测试的缩放版本,而Pesaran等人则对其有限的样本偏差进行了校正。 (2008)。这是在异构面板数据模型的背景下完成的。本文在固定效应均质面板数据模型的背景下,推导了这种缩放版本的LM测试的渐近偏差。发现该渐近偏差是与n和T相关的常数,这表明针对零假设的简单偏差校正LM检验。此外,本文还进行了一些蒙特卡洛实验,以比较该拟议测试的有限样本属性与现有的横截面相关性测试。 (C)2012 Elsevier B.V.保留所有权利。

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