Model Specification Tests Based on Artificial Linear Regressions

Russell Davidson and James MacKinnon

Working Paper from Economics Department, Queen's University

Abstract: This paper develops a general procedure for performing a wide variety of model specification tests by running artificial linear regressions and then using conventional significance tests. In particular, this procedure allows us to develop non-nested hypothesis tests for any set of models which attempt to explain the same dependent variable(s), even when the error specifications of the models differ. For example, it is straightforward to test linear regression models against loglinear ones. These procedures are illustrated with an application to estimate competing models of personal savings in Canada.

Pages: 32
Date: 1980
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Related works:
Journal Article: Model Specification Tests Based on Artificial Linear Regressions (1984)
Working Paper: Model Specification Tests Based on Artificial Linear Regressions (1981)
Working Paper: Model Specification Tests Based on Artificial Linear Regressions (1980)
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