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

Askar H. Choudhury; Simon Power; Robert St Louis

doi:10.1080/03610919708813382

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

Askar H. Choudhury, Simon Power, Robert St Louis

Business, W. P. Carey School of (WPC)

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

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-à-vis existing OLS and GLS linear estimators.

Original language	English (US)
Pages (from-to)	315-332
Number of pages	18
Journal	Communications in Statistics Part B: Simulation and Computation
Volume	26
Issue number	1
DOIs	https://doi.org/10.1080/03610919708813382
State	Published - Jan 1 1997

Keywords

Approximate GLS estimator
Autocorrelation
Regression

ASJC Scopus subject areas

Statistics and Probability
Modeling and Simulation

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10.1080/03610919708813382

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abstract = "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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AU - St Louis, Robert

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AB - 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-à-vis existing OLS and GLS linear estimators.

KW - Approximate GLS estimator

KW - Autocorrelation

KW - Regression

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

Abstract

Keywords

ASJC Scopus subject areas

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