In the existence of autocorrelation problem, the Ordinary Least Squares
(OLS) estimates become incompetent. The Cochrane - Orcutt Prais -
Winsten iterative method (COPW) is the most widely used remedial
measure to rectify this problem. However, this iterative procedure is
based on the OLS estimates, which is not resistant and easily in�uenced
by high leverage points (outliers in the x-direction) and outliers in the
y-direction. The COPW based on MM estimator is developed to remedy
both problems of autocorrelation and high leverage points. Nevertheless, MM estimator does not perform well in the presence of bad leverage points. In this paper, we propose to improvise the Cochrane-Orcutt