## Abstract

We consider a linear trend regression model when the disturbances follow a serially correlated one-way error component model. In this model, we investigate the performance of the Ordinary Least Squares Esitmator (OLSE), First Difference Estimator (FDE), Generalized Least Squares Estimator (GLSE) and the Cochrane-Orcutt-Transformation Estimator (COTE) of slope coefficient in terms of efficiency. The main findings are as follows: (1) when the autocorrelation is close to unity, then the FDE is approximately the GLSE; (2) the OLSE is better than the COTE; and (3) when the value of the autocorrelation is kept constant and T → ∞, the OLSE, COTE and GLSE arc asymptotically equivalent whereas the FDE is worse than the other estimators in terms of efficiency.

Original language | English |
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Pages (from-to) | 1385-1398 |

Number of pages | 14 |

Journal | Communications in Statistics - Theory and Methods |

Volume | 31 |

Issue number | 8 |

DOIs | |

State | Published - Aug 2002 |

## Keywords

- Autocorrelation
- COTE
- FDE
- GLSE
- OLSE
- Panel data regression