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A Low-Dimension Collinearity-Robust Test for Non-linearity

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  • Jennifer L. Castle
  • David F. Hendry

Abstract

A new test for non-linearity is developed using weighted combinations of regressor powers based on the eigenvectors of the variance-covariance matrix. The test extends the ingenious test for heteroskedasticity proposed by White (1980), but both circumvents problems of high dimensionality and collinearity, and allows inclusion of cubic functions to ensure power against asymmetry or skewness. A Monte Carlo analysis compares the performance of the test to the optimal infeasible test and to a variant of White`s test. The relative performance of the test is encouraging: the test has the appropriate size and has high power in many situations. Furthermore, collinearity between regressors can increase the power of the test.

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File URL: http://www.economics.ox.ac.uk/materials/working_papers/paper326.pdf
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Bibliographic Info

Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 326.

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Date of creation: 01 May 2007
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Handle: RePEc:oxf:wpaper:326

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Keywords: Functional Form Test; Non-linearity; Collinearity;

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  1. Quandt, Richard E., 1983. "Computational problems and methods," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 12, pages 699-764 Elsevier.
  2. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
  3. repec:att:wimass:9520 is not listed on IDEAS
  4. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
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