In a linear regression model with arbitrary disturbance covariance structure, least squares estimators subject to correct linear restrictions dominate unrestricted least squares for all estimable functions of the parameters if and only if the covariance matrix obeys conditions closely related to those of the Gauss-Markov theorem.
MLA
Taylor, William E.. “Prior Information on the Coefficients when the Disturbance Covariance Matrix is Unknown.” Econometrica, vol. 44, .no 4, Econometric Society, 1976, pp. 725-739, https://www.jstor.org/stable/1913439
Chicago
Taylor, William E.. “Prior Information on the Coefficients when the Disturbance Covariance Matrix is Unknown.” Econometrica, 44, .no 4, (Econometric Society: 1976), 725-739. https://www.jstor.org/stable/1913439
APA
Taylor, W. E. (1976). Prior Information on the Coefficients when the Disturbance Covariance Matrix is Unknown. Econometrica, 44(4), 725-739. https://www.jstor.org/stable/1913439
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