Econometrica: Jul 1973, Volume 41, Issue 4

Generalized Least Squares with an Estimated Autocovariance Matrix<723:GLSWAE>2.0.CO;2-H
p. 723-732

Takeshi Amemiya

The 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.

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