Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-27T18:50:53.690Z Has data issue: false hasContentIssue false
  • English
  • Français

Power of Tests for Nonlinear Transformation in Regression Analysis

Published online by Cambridge University Press:  11 February 2009

Masahito Kobayashi
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper compares the local power of tests for a nonlinear transformation of the dependent variable in a regression model against the alternative hypothesis of a linear transformation. It is shown that the local power of the Cox test is higher than those of the extended projection test of MacKinnon, White, and Davidson, and Bera and McAleer's test. The theoretical result is supported by a Monte-Carlo experiment in testing for a regression model with a logarithmically transformed dependent variable against a linear regression model.

Type
Research Article
Information
Econometric Theory , Volume 10 , Issue 2 , June 1994 , pp. 357 - 371
Copyright
Copyright © Cambridge University Press 1994

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Aneuryn-Evans, G. & Deaton, A.S.. Testing linear versus logarithmic regression models. Review of Economic Studies 47 (1980): 275–291.Google Scholar
2. Bera, A.K. & McAleer, M.. Nested and nonnested procedures for testing linear and log linear regression models. Sankha B 51 (1989): 212–224.Google Scholar
3. Bickel, P.J. & Doksum, K.A.. An analysis of transformations revisited. Journal of the American Statistical Association 76 (1981): 296–310.10.1080/01621459.1981.10477649Google Scholar
4. Cox, D.R. Tests of separate families of hypotheses. Proceedings of the 4th Berkeley Symposium 1 (1961): 105–123.Google Scholar
5. Cox, D.R. Further results on tests of separate families of hypotheses. Journal of the Royal Statistical Society B 24 (1962): 406–424.Google Scholar
6. Godfrey, L.G., McAleer, M. & McKenzie, C.R.. Variable addition and Lagrange multiplier tests for linear and logarithmic regression models. Review of Economics and Statistics 70 (1988): 492–503.10.2307/1926788Google Scholar
7. Loh, W.-Y. A new method for testing separate families of hypothesis. Journal of the American Statistical Association 80 (1985): 362–368.10.1080/01621459.1985.10478124Google Scholar
8. MacKinnon, J.G., White, H. & Davidson, R.. Tests for model specification in the presence of alternative hypotheses. Journal of Econometrics 21 (1983): 53–70.10.1016/0304-4076(83)90119-7Google Scholar
9. Ramsey, J.B. Tests for specification errors in classical linear least squares regression analysis. Journal of the Royal Statistical Society B 31 (1969): 350–371.Google Scholar