The error components regression model: conditional relative efficiency comparisons

This paper considers a simple linear regression with two-way error component disturbances and derives the conditional relative efficiency of any feasible GLS estimator with respect to OLS, true GLS, or any other feasible GLS estimator, conditional on the estimated variance components. This is done at two crucial choices of the x variable. The first choice is where OLS is least efficient with respect to GLS and the second choice is where an arbitrary feasible GLS estimator is least efficient with respect to GLS. Our findings indicate that a better guess of a certain 'variance components ratio' leads to better estimates of the regression coefficients.