Analytical Power Comparisons Of Nested And Nonnested Tests For Linear And Loglinear Regression Models
AbstractThis 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).
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 15 (1999)
Issue (Month): 01 (February)
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- Godfrey, L.G. & Santos Silva, J.M.C., 2007. "A note on variable addition tests for linear and log-linear models," Economics Letters, Elsevier, vol. 95(3), pages 422-427, June.
- Corradi, Valentina & Swanson, Norman R., 2006.
"The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test,"
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Elsevier, vol. 132(1), pages 195-229, May.
- Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
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