A Low-Dimension Portmanteau Test for Non-linearity
AbstractA 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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Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 471.
Date of creation: 01 Jan 2010
Date of revision:
Functional form; Portmanteau test; Non-linearity; Principal components; Collinearity;
Other versions of this item:
- Castle, Jennifer L. & Hendry, David F., 2010. "A low-dimension portmanteau test for non-linearity," Journal of Econometrics, Elsevier, vol. 158(2), pages 231-245, October.
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-02-05 (All new papers)
- NEP-ECM-2010-02-05 (Econometrics)
- NEP-ETS-2010-02-05 (Econometric Time Series)
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