Preliminary-Test Estimation of the Error Variance in Linear Regression

Judith A. Clarke, David Giles () and T. Dudley Wallace

Econometric Theory, 1987, vol. 3, issue 02, pages 299-304

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.

Date: 1987

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Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:3:y:1987:i:02:p:299-304_01

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