The covariance matrix for the residuals of a regression process is written as the identity matrix plus a matrix V. The matrix V is bounded from above, and the corresponding set of generalized least squares estimates is identified. The extreme estimates in this set are functions of the usual t statistics; in particular the number ((T - k)/8)1/2/|t| measures the influence of reweighting extreme observations, where T - k gives the degrees of freedom, t is the t statistic, and the weights on observations are allowed to vary by a factor of at most 2.
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Edward E. Leamer (1984) studied this question.
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