Abstract
In this paper, the asymptotic distribution of corrected maximum likelihood estimators is formally derived when the misspecification present is local, or small, but unknown. Although these corrections are designed to remove the asymptotic bias from maximum likelihood estimators, they can have much larger sampling variances. In order to gain some insight into this trade-off, an asymptotic mean square error criterion is considered. On the basis of this criterion, a testable condition is established that ensures that the usual maximum likelihood estimators remain superior to the corrections. Copyright 1989 by Blackwell Publishing Ltd and the Board of Trustees of the Bulletin of Economic Research
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