The unbalanced nested error component regression model

被引:15
作者
Baltagi, BH [1 ]
Song, SW
Jung, BC
机构
[1] Texas A&M Univ, Dept Econ, College Stn, TX 77843 USA
[2] Korea Univ, Dept Stat, Sungbuk Ku, Seoul 136701, South Korea
关键词
panel data; nested error component; unbalanced ANOVA; MINQUE; MLE; variance components;
D O I
10.1016/S0304-4076(00)00089-0
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper considers a nested error component model with unbalanced data and proposes simple analysis of variance (ANOVA). maximum likelihood (MLE) and minimum norm quadratic unbiased estimators (MINQUE)-type estimators of the variance components. These are natural extensions from the biometrics, statistics and econometrics literature. The performance of these estimators is investigated by means of Monte Carlo experiments. While the MLE and MINQUE methods perform the best in estimating the variance components and the standard errors of the regression coefficients, the simple ANOVA methods perform just as well in estimating the regression coefficients. These estimation methods are also used to investigate the productivity of public capital in private production. (C) 2001 Published by Elsevier science S.A.
引用
收藏
页码:357 / 381
页数:25
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