Mixed Linear Regression with equi-cross-correlated errors

This paper investigates an one-step procedure for the General Least Squares Estimation (GLSE) in the Linear Regression Model with stochastic linear restrictions on the regression coefficients. The covariance matrix of the errors is assumed to be known up to the correlations between the errors of the observations and the errors of the restrictions. It is assumed that all of these correlations are equal. After transforming the model into its canonical form we show, that the GLSE coincides with the Ordinary Least Squares Estimation (OLS) of the complete model or with OLS after deleting one appropriate observation. Additionally, a new test is proposed for the independence of the disturbances. (orig.)Available from TIB Hannover: RR 2036(126) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman