Testing for heteroskedasticity and spatial correlation in a random effects panel data model

被引：19

作者：

Baltagi, Badi H. ^{[1
,2
]}

Song, Seuck Heun ^{[3
]}

Kwon, Jae Hyeok ^{[3
]}

机构：

[1] Syracuse Univ, Dept Econ, Syracuse, NY 13244 USA

[2] Syracuse Univ, Ctr Policy Res, Syracuse, NY 13244 USA

[3] Korea Univ, Dept Stat, Seoul 136701, South Korea

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2009年 / 53卷 / 08期

关键词：

ERROR COMPONENT MODEL;

D O I：

10.1016/j.csda.2008.06.009

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A panel data regression model with heteroskedastic as well as spatially correlated disturbances is considered, and a joint LM test for homoskedasticity and no spatial correlation is derived. In addition, a conditional LM test for no spatial correlation given heteroskedasticity, as well as a conditional LM test for homoskedasticity given spatial correlation, are also derived. These LM tests are compared with marginal LM tests that ignore heteroskedasticity in testing for spatial correlation, or spatial correlation in testing for homoskedasticity. Monte Carlo results show that these LM tests, as well as their LR counterparts, perform well, even for small N and T. However, misleading inferences can occur when using marginal, rather than joint or conditional LM tests when spatial correlation or heteroskedasticity is present. (c) 2008 Elsevier B.V. All rights reserved.

引用

页码：2897 / 2922

页数：26

共 26 条

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