The efficiency of the sample mean in a linear regression model when errors follow a first-order moving average process

In this paper a linear regression model is considered with the sample mean to be estimated. Errors are assumed to follow a MA(1) process. We derive the efficiency function for the OLS estimator relative to the best linear unbiased estimator (Aitken) for finite sample size. In the case of positive correlation among the errors a greatest lower bound for the efficiency is established.