Nonlinear hypotheses, inequality restrictions and non-nested hypotheses: Exact simultaneous tests in linear regressions
In the classical linear model, comparison of two arbitrary hypotheses on the regression coefficients is considered. Problems involving nonlinear hypotheses, inequality restrictions, or non-nested hypotheses are included. Exact bounds on the null distribution of likelihood ratio statistics are derived (based on the central Fisher distribution). As a special case, a bounds test similar to the Durbin-Watson test is proposed. Multiple testing problems are studied: the bounds obtained for a single pair of hypotheses are shown to enjoy a simultaneity property that allows combination of any number of tests. This result extends to nonlinear hypotheses a well-known result given by H. Scheffe for linear hypotheses. A method of building bounds-induced tests is suggested. Copyright 1989 by The Econometric Society.
(This abstract was borrowed from another version of this item.)
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||01 Jan 1986|
|Date of revision:|
|Contact details of provider:|| Postal: |
Fax: +32 10474304
Web page: http://www.uclouvain.be/core
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:cor:louvco:1986016. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alain GILLIS)
If references are entirely missing, you can add them using this form.