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

Abonazel, Mohamed R. (2016): Generalized Random Coefficient Estimators of Panel Data Models: Asymptotic and Small Sample Properties. Published in: American Journal of Applied Mathematics and Statistics , Vol. 4, No. 2 (June 2016): pp. 46-58.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Classical pooling estimation; Contemporaneous covariance; First-order autocorrelation; Heteroskedasticity; Mean group estimation; Monte Carlo simulation; Random coefficient regression.
• Subjects: B - History of Economic Thought, Methodology, and Heterodox Approaches > B2 - History of Economic Thought since 1925 > B23 - Econometrics ; Quantitative and Mathematical Studies; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C23 - Panel Data Models ; Spatio-temporal Models; C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling

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