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Different Estimators for Stochastic Parameter Panel Data Models with Serially Correlated Errors |
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PP: 423-434 |
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doi:10.18576/jsap/070303
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Author(s) |
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Mohamed Reda Abonazel,
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Abstract |
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| This paper considers stochastic parameter panel data models when the errors are first-order serially correlated. The feasible
generalized least squares (FGLS) and simple mean group (SMG) estimators for these models have been reviewed and examined. The
efficiency comparisons for these estimators have been carried when the regression parameters are stochastic, non-stochastic, and mixedstochastic.
Monte Carlo simulation study and a real data application are given to evaluate the performance of FGLS and SMG estimators.
The results indicate that, in small samples, SMG estimator is more reliable in most situations than FGLS estimators, especially when
the model includes one or more non-stochastic parameter. |
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