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ANALYTICAL POWER COMPARISONS OF NESTED AND NONNESTED TESTS FOR LINEAR AND LOGLINEAR REGRESSION MODELS

Published online by Cambridge University Press:  01 February 1999

Masahito Kobayashi
Affiliation:
Yokohama National University
Michael McAleer
Affiliation:
University of Western Australia

Abstract

This paper compares several tests for linear and loglinear regression models where both the dependent and independent variables are transformed. It is shown that the Lagrange multiplier test proposed by Godfrey and Wickens (1981, Review of Economic Studies 48, 487–496) in the framework of the Box–Cox regression model has the highest asymptotic power of the compared tests. The extended projection test of MacKinnon, White, and Davidson (1983, Journal of Econometrics 11, 53–70), the test of Bera and McAleer (1983, paper presented to the SSRC Econometric Study Group Conference on Model Specification and Testing, Warwick; 1989, Sankhya B 51, 212–224), and the test of Andrews (1971, Biometrika 58, 249–254) are shown to have asymptotically equivalent powers and to have lower powers than the nonnested test of Cox (1961, Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1, 105–123, Berkeley: University of California Press; 1962, Journal of the Royal Statistical Society B 24, 406–424).

Type
Research Article
Copyright
© 1999 Cambridge University Press

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ANALYTICAL POWER COMPARISONS OF NESTED AND NONNESTED TESTS FOR LINEAR AND LOGLINEAR REGRESSION MODELS
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