Abstract
In this paper we obtain a small-disturbance approximation to the moment matrix of the limiting distribution of an operational generalized least squares (OGLS) estimator of the mean response vector in a random coefficient model.It is shown that for small samples the moment matrix of the limiting distribution underestimates the small-disturbance approximate moment matrix of the limiting distribution of the OGLS estimator. This suggests that for small samples the ‘standard errors’ of the OGLS estimates should be obtained from the small-disturbance approximate moment matrix of the limiting distribution rather than from the conventional asymptotic moment matrix.
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