Variable Addition and Lagrange Multiplier Tests for Linear and Logarithmic Regression Models

Abstract

The purpose of this paper is to examine the properties of various tests of linear and logarithmic (or log-linear) regression models. The test procedures may be categorized as follows: (1) tests that exploit the fact that the two models are intrinsically non-nested; (2) tests based on the Box-Cox data transformation; and (3) diagnostic tests of functional form misspecification against an unspecified alternative. The small-sample properties of several tests are investigated through a Monte Carlo experiment, as is their robustness to non-normality of the errors. Copyright 1988 by MIT Press.