Optimizing in the class of Fuller modified limited information maximum likelihood estimators

AbstractA general class of Fuller modified maximum likelihood estimators are considered. It is shown that this class possesses finite moments. Asymptotic bias and asymptotic mean squared error are derived using small-σ expansions. A simulation study is carried out to compare different estimators in this class with standard estimators

METHODS OF ESTIMATION IN TEMPORAL CROSS-SECTIONAL STUDIES

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Optimizing in the class of Fuller modified limited information maximum likelihood estimators

A general class of Fuller modified maximum likelihood estimators are considered. It is shown that this class possesses finite moments. Asymptotic bias and asymptotic mean squared error are derived using small-[sigma] expansions. A simulation study is carried out to compare different estimators in this class with standard estimators.simultaneous equations small-[sigma] expansions limited information maximum likelihood k-class estimators