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

被引:39
|
作者
Baltagi, Badi H. [1 ,2 ]
Jung, Byoung Cheol [3 ]
Song, Seuck Heun [4 ]
机构
[1] Syracuse Univ, Dept Econ, Syracuse, NY 13244 USA
[2] Syracuse Univ, Ctr Policy Res, Syracuse, NY 13244 USA
[3] Univ Seoul, Dept Stat, Seoul 130743, South Korea
[4] Korea Univ, Dept Stat, Seoul 136701, South Korea
关键词
Panel data; Heteroskedasticity; Serial correlation; Lagrange multiplier tests; Likelihood ratio; Random effects;
D O I
10.1016/j.jeconom.2009.04.009
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper considers a panel data regression model with heteroskedastic as well as serially correlated disturbances, and derives a joint LM test for homoskedasticity and no first order serial correlation. The restricted model is the standard random individual error component model. it also derives a conditional LM test for homoskedasticity, given serial correlation, as well as, a conditional LM test for no first order serial correlation given heteroskedasticity, all in the context of a random effects panel data model. Monte Carlo results show that these tests along with their likelihood ratio alternatives have good size and power under various forms of heteroskedasticity including exponential and quadratic functional forms. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:122 / 124
页数:3
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