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A Low-Dimension Portmanteau Test for Non-linearity

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  • Jennifer Castle
  • David Hendry

Abstract

A new test for non-linearity in the conditional mean is proposed using functions of the principal components of regressors. The test extends the non-linearity tests based on Kolmogorov-Gavor polynomials (Thursby and Schmidt, 1977, Tsay, 1986, and Terasvirta, Lin and Granger, 1993), but circumvents problems of high dimensionality, is equivariant to collinearity, and includes exponential functions, so is a portmanteau test with power against a wide range of possible alternatives. A Monte Carlo analysis compared the performance of the test to the optimal infeasible test and to alternative tests. The relative performance of the test is encouraging: the test has the appropriate size and has high power in many situations.

Suggested Citation

  • Jennifer Castle & David Hendry, 2010. "A Low-Dimension Portmanteau Test for Non-linearity," Economics Series Working Papers 471, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:471
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    1. Kevin D. Hoover & Stephen J. Perez, 1999. "Data mining reconsidered: encompassing and the general-to-specific approach to specification search," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 167-191.
    2. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    3. Karim Abadir, 1999. "An introduction to hypergeometric functions for economists," Econometric Reviews, Taylor & Francis Journals, vol. 18(3), pages 287-330.
    4. Phillips, Peter C.B., 2007. "Regression With Slowly Varying Regressors And Nonlinear Trends," Econometric Theory, Cambridge University Press, vol. 23(4), pages 557-614, August.
    5. White, Halbert, 1983. "Corrigendum [Maximum Likelihood Estimation of Misspecified Models]," Econometrica, Econometric Society, vol. 51(2), pages 513-513, March.
    6. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, Decembrie.
    7. A. I. McLeod & W. K. Li, 1983. "Diagnostic Checking Arma Time Series Models Using Squared‐Residual Autocorrelations," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 269-273, July.
    8. 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.
    9. Bierens, Herman J, 1990. "A Consistent Conditional Moment Test of Functional Form," Econometrica, Econometric Society, vol. 58(6), pages 1443-1458, November.
    10. Phoebus J. Dhrymes & E. Philip Howrey & Saul H. Hymans & Jan Kmenta & Edward E. Leamer & Richard E. Quandt & James B. Ramsey & Harold T. Shapiro & Victor Zarnowitz, 1972. "Criteria for Evaluation of Econometric Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 3, pages 291-324, National Bureau of Economic Research, Inc.
    11. Teräsvirta Timo, 1996. "Power Properties of Linearity Tests for Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(1), pages 1-10, April.
    12. Timo Teräsvirta & Chien‐Fu Lin & Clive W. J. Granger, 1993. "Power Of The Neural Network Linearity Test," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(2), pages 209-220, March.
    13. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124, September.
    14. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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