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A Low-Dimension Portmanteau Test for Non-linearity

  • Jennifer Castle
  • David Hendry

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.

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Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 471.

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Date of creation: 01 Jan 2010
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Handle: RePEc:oxf:wpaper:471
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  1. 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.
  2. 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.
  3. Karim Abadir, 1999. "An introduction to hypergeometric functions for economists," Econometric Reviews, Taylor & Francis Journals, vol. 18(3), pages 287-330.
  4. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  5. 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.
  6. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, July.
  7. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124.
  8. Kevin Hoover & Stephen J. Perez, 2003. "Data Mining Reconsidered: Encompassing And The General-To-Specific Approach To Specification Search," Working Papers 9727, University of California, Davis, Department of Economics.
  9. Bierens, H.J., 1989. "A consistent conditional moment test of functional form," Serie Research Memoranda 0064, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  10. Phillips, Peter C.B., 2007. "Regression With Slowly Varying Regressors And Nonlinear Trends," Econometric Theory, Cambridge University Press, vol. 23(04), pages 557-614, August.
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