Generalized Random Coefficient Estimators of Panel Data Models: Asymptotic and Small Sample Properties

Mohamed Reda Abonazel^1,

¹Department of Applied Statistics and Econometrics, Institute of Statistical Studies and Research, Cairo University, Egypt

Cite this paper

Mohamed Reda Abonazel. Generalized Random Coefficient Estimators of Panel Data Models: Asymptotic and Small Sample Properties. American Journal of Applied Mathematics and Statistics. 2016; 4(2):46-58. doi: 10.12691/AJAMS-4-2-4

Abstract

This paper provides a generalized model for the random-coefficients panel data model where the errors are cross-sectional heteroskedastic and contemporaneously correlated as well as with the first-order autocorrelation of the time series errors. Of course, the conventional estimators, which used in standard random-coefficients panel data model, are not suitable for the generalized model. Therefore, the suitable estimator for this model and other alternative estimators have been provided and examined in this paper. Moreover, the efficiency comparisons for these estimators have been carried out in small samples and also we examine the asymptotic distributions of them. The Monte Carlo simulation study indicates that the new estimators are more reliable (more efficient) than the conventional estimators in small samples.

Keywords

classical pooling estimation, contemporaneous covariance, first-order autocorrelation, heteroscedasticity, mean group estimation; monte carlo simulation, random coefficient regression

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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