Preliminary-Test Estimation of the Error Variance in Linear Regression

dc.contributor.author	Clarke, Judith A.	en_US
dc.contributor.author	Giles, David E. A.	en_US
dc.contributor.author	Wallace, Dudley	en_US
dc.date.accessioned	2010-06-28T18:50:29Z
dc.date.available	2010-06-28T18:50:29Z
dc.date.issued	1987-08	en_US
dc.identifier.uri	http://hdl.handle.net/10161/2568
dc.description.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.	en_US
dc.format.extent	188317 bytes
dc.format.mimetype	application/pdf
dc.language.iso	en_US
dc.publisher	Econometric Theory	en_US
dc.subject	biases	en_US
dc.subject	error	en_US
dc.subject	linear regression	en_US
dc.subject	pretest estimators	en_US
dc.title	Preliminary-Test Estimation of the Error Variance in Linear Regression	en_US
dc.type	Journal Article	en_US
dc.department	Economics