IDEAS home Printed from https://ideas.repec.org/p/ags/canzdp/262937.html
   My bibliography  Save this paper

Estimation of the Error Variance after a Preliminary-Test of Homogeneity in a Regression Model with Spherically Symmetric Disturbances

Author

Listed:
  • Giles, Judith A.

Abstract

In this paper we consider the risk (under quadratic loss) of an estimator cf the error variance after a pre-test for homogeneity of the variances in the two-sample linear regression model. We investigate the effects on risk of assuming normal disturbances when in fact the error distribution is spherically symmetric. We also broaden the standard assumption that the never-pool variance estimators are based on the least squares principle. Using the special case of multivariate Student-t regression disturbances as an illustration, our results show that in some situations we should always pre-test, even if the error variances are equal, and we provide the optimal test critical value. The evaluations also show that using the least squares technique to form the never-pool estimators may not always be the preferred strategy.

Suggested Citation

Handle: RePEc:ags:canzdp:262937
DOI: 10.22004/ag.econ.262937
as

Download full text from publisher

File URL: https://ageconsearch.umn.edu/record/262937/files/canterbury-nz-023.pdf
Download Restriction: no
File URL: https://ageconsearch.umn.edu/record/262937/files/canterbury-nz-023.pdf?subformat=pdfa
Download Restriction: no
File URL: https://libkey.io/10.22004/ag.econ.262937?utm_source=ideas
LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
---><---

More about this item

Keywords

;
;

Statistics

Access and download statistics

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:canzdp:262937. See general information about how to correct material in RePEc.

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

We have no bibliographic references for this item. You can help adding them by using this form .

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: .

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.