Necessary and sufficient conditions for the equality of ordinary least squares and generalized least squares estimators in the linear regression model with firstorder spatial error processes are given.

Bounds for the efficiency of ordinary least squares relative to generalized least squares estimator in the linear regression model with first order spatial error process are given.

Conditions for the consistency of the estimator s2 of the variance of the disturbance a2u under first-order spatial error processes are given.

The best linear unbiased estimator BLUE (CXb) of a linear transform CX b in the general Gauss-Markov model (y, E (y) = X b Cov (y) =a2v) is the linear transform C BLUE (Xb) of the best linear unbiased estimator BLUE (Xb) of Xb. Similarly, for the ordinary least squares estimator OLSE (CXb) = C...