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Comparison of k-Class Estimators When the Disturbances Are Small
journal contribution
posted on 1975-12-12, 00:00 authored by Joseph B. KadaneA new approach to the choice ofeconometric estimators, called small-sigma asymptotics,
is introduced and applied to the choice of k-class estimators of the parameters of a single
equation in a system of linear simultaneous stochastic equations. I find that when the degree
of over-identification is no more than six, the two stage least squares estimator uniformly
dominates the limited information maximum likelihood estimator in a certain sense. The
small sigma method can be used on many problems in statistics and econometrics.