Generalized Random Coefficient Estimators of Panel Data Models: Asymptotic and Small Sample Properties
Mohamed Abonazel ()
MPRA Paper from University Library of Munich, Germany
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; Heteroskedasticity; Mean group estimation; Monte Carlo simulation; Random coefficient regression. (search for similar items in EconPapers)
JEL-codes: B23 C1 C23 C4 C5 (search for similar items in EconPapers)
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Published in American Journal of Applied Mathematics and Statistics 2.4(2016): pp. 46-58
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:72586
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