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

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 identied a class of nonlinear models for which the GNR yields an exact test.

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Year of publication:	1998-11-30
Authors:	Stewart, Kenneth G.
Institutions:	Department of Economics, University of Victoria
Subject:	Specification testing \| Milliken-Graybill Theorem \| Gauss- Newton regression

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Extent:	application/pdf
Series:	Econometrics Working Papers.
Type of publication:	Book / Working Paper
Language:	English
Notes:	ISSN 1485-6441 Number 9811 9 pages
Classification:	C12 - Hypothesis Testing
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005260591