New Estimators of Disturbances in Regression Analysis

Abstract

In this article, an alternative v for the vector û of least-squares residuals in the linear model is derived. It is best in the class of all linear unbiased estimators' of u having a certain fixed covariance matrix chosen a priori. Under the normality assumption, the distribution of the Von Neumann Ratio based on v is independent of the regression vectors, so that v is particularly useful for testing on serial correlation of the disturbances. It is pointed out that the existing tests for serial correlation in economic time-series models might be improved by using v based on an appropriate covariance matrix; the Durbin-Watson upper-bound tables can be used for this purpose.