Improved estimation of the linear regression model with autocorrelated errors

For estimating the coefficient vector of a linear regression model with first order autoregressive disturbances, a family of Stein-rule estimators based on the two-step Prais-Winsten estimating procedure is considered and an Edgeworth type asymptotic expansion for its distribution is derived. The performance of this family of estimators relative to the two-step Prais-Winsten estimator is also derived under a squared error loss function.