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Preliminary-Test Estimation of the Error Variance in Linear Regression

Published online by Cambridge University Press:  11 February 2009

Judith A. Clarke,
David E. A. Giles and
T. Dudley Wallace
Judith A. Clarke
Affiliation:
University of Canterbury
David E. A. Giles
Affiliation:
University of Canterbury
T. Dudley Wallace
Affiliation:
Duke University
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Abstract

We derive exact finite-sample expressions for the biases and risks of several common pretest estimators of the scale parameter in the linear regression model. These estimators are associated with least squares, maximum likelihood and minimum mean squared error component estimators. Of these three criteria, the last is found to be superior (in terms of risk under quadratic loss) when pretesting in typical situations.

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Type
ET Interview
Information
Econometric Theory , Volume 3 , Issue 2 , April 1987, pp. 299 - 304
Copyright
Copyright © Cambridge University Press 1987

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References

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