Econometrica: Sep 1971, Volume 39, Issue 5

Comparison of k-Class Estimators When the Disturbances Are Small

https://doi.org/0012-9682(197109)39:5<723:COKEWT>2.0.CO;2-1
p. 723-737

Joseph B. Kadane

A new approach to the choice of econometric 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 overidentification 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.

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