On the Performance of the Ordinary Least Squares Method under an Error Component Model
نویسنده
چکیده
Starting from the one{dimensional results by Wang et al (1994) we consider the performance of the ordinary least squares estimator in comparison to the best linear unbiased estimator under an error component model with random eeects in units and time. Upper bounds are derived for the rst{ order approximation to the diierence between both estimators and for the spectral norm of the diierence between their dispersion matrices.
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