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.

Additional Metadata
Keywords Approximate GLS estimator, Autocorrelation, Regression
Journal Communications in Statistics Part B: Simulation and Computation
Citation
Choudhury, A.H. (Askar H.), Power, S, & St. Louis, R.D. (Robert D.). (1997). Linear estimation of the regression model with arma disturbances: A simulation study. Communications in Statistics Part B: Simulation and Computation, 26(1), 315–332.