Econometrica: Jul 1973, Volume 41, Issue 4
Generalized Least Squares with an Estimated Autocovariance Matrix
Takeshi AmemiyaThe paper proves the asymptotic normality of a generalized least squares estimator utilizing estimated autocovariances of the residual in a regression equation having a residual following a mixed autoregressive, moving-average process. It also proves the asymptotic normality of the best linear unbiased estimator and shows that the two asymptotic distributions are the same.
Log In To View Full Content