Linear estimation of the regression model with ARMA disturbances: A simulation study

被引：1
|
作者：
Choudhury, AH
Power, S
StLouis, RD
机构：
[1] UNIV ALASKA,SCH BUSINESS,ANCHORAGE,AK 99508
[2] CARLETON UNIV,DEPT ECON,OTTAWA,ON K1S 5B6,CANADA
[3] ARIZONA STATE UNIV,COLL BUSINESS,TEMPE,AZ 85287
来源：
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 1997年 / 26卷 / 01期
关键词：
regression; autocorrelation; approximate GLS estimator;
D O I：
10.1080/03610919708813382
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Koreisha and Pukkila (1990a) have recently proposed a computationally convenient three-step GLS-type linear estimator for the regression model with ARMA disturbances involving three sequential applications of least squares. One potential drawback to this estimation procedure is that it entails dropping a significant number of initial observations. This paper uses Monte Carlo methods to evaluate its performance vis-a-vis existing OLS and GLS linear estimators.
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页码：315 / 332
页数：18
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