Gauss-Newton, Milliken-Graybill, and Exact Misspecification Testing Using Artificial Regressions

Kenneth Stewart

No 9811, Econometrics Working Papers from Department of Economics, University of Victoria

Abstract: The Gauss-Newton regression (GNR) is widely used to compute Lagrange multiplier statistics. A regression described by Milliken and Graybill yields an exact F test in a certain class of nonlinear models which are linear under the null. This paper shows that the Milliken- Graybill regression is a GNR. Hence one interpretation of Milliken- Graybill is that they identi ed a class of nonlinear models for which the GNR yields an exact test.

Keywords: Specification testing; Milliken-Graybill Theorem; Gauss- Newton regression (search for similar items in EconPapers)
JEL-codes: C12 (search for similar items in EconPapers)
Pages: 9 pages
Date: 1998-11-30
New Economics Papers: this item is included in nep-ecm
Note: ISSN 1485-6441
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.uvic.ca/socialsciences/economics/_asse ... ometrics/ewp9811.pdf (application/pdf)

Related works:
Journal Article: GNR, MGR, and exact misspeclfication testing (2000)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vic:vicewp:9811

Access Statistics for this paper

More papers in Econometrics Working Papers from Department of Economics, University of Victoria PO Box 1700, STN CSC, Victoria, BC, Canada, V8W 2Y2. Contact information at EDIRC.
Bibliographic data for series maintained by Kali Moon ().