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Evaluating a class of nonlinear time series models


  • Heinen, Florian


We consider a recently proposed class of nonlinear time series models and focus mainly on misspecification testing for models of such type. Following the modeling cycle for nonlinear time series models of specification, estimation and evaluation we first treat how to choose an adequate transition function and then contribute to the evaluation stage by proposing tests against serial correlation, no remaining nonlinearity and parameter constancy. We also consider evaluation by generalized impulse response functions. The finite sample properties of the proposed tests are studied via simulation. We illustrate the use of these methods by an application to real exchange rate data.

Suggested Citation

  • Heinen, Florian, 2010. "Evaluating a class of nonlinear time series models," Hannover Economic Papers (HEP) dp-445, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  • Handle: RePEc:han:dpaper:dp-445

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    References listed on IDEAS

    1. Kapetanios, George & Shin, Yongcheol & Snell, Andy, 2003. "Testing for a unit root in the nonlinear STAR framework," Journal of Econometrics, Elsevier, vol. 112(2), pages 359-379, February.
    2. Taylor, Mark P & Peel, David A & Sarno, Lucio, 2001. "Nonlinear Mean-Reversion in Real Exchange Rates: Toward a Solution to the Purchasing Power Parity Puzzles," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 1015-1042, November.
    3. Öcal Nadir, 2000. "Nonlinear Models for U.K. Macroeconomic Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(3), pages 1-15, October.
    4. Hansen, Bruce E., 1992. "Convergence to Stochastic Integrals for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 8(04), pages 489-500, December.
    5. Robinson Kruse, 2011. "A new unit root test against ESTAR based on a class of modified statistics," Statistical Papers, Springer, vol. 52(1), pages 71-85, February.
    6. Jansen, Eilev S & Terasvirta, Timo, 1996. "Testing Parameter Constancy and Super Exogeneity in Econometric Equations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 735-763, November.
    7. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, March.
    8. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    9. Dirk Te Velde, 2001. "Balance of payments prospects in EMU," National Institute of Economic and Social Research (NIESR) Discussion Papers 178, National Institute of Economic and Social Research.
    10. Delli Gatti Domenico & Gallegati Mauro & Mignacca Domenico, 1998. "Nonlinear Dynamics and European GNP Data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(1), pages 1-19, April.
    11. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
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    More about this item


    Nonlinearities; Smooth transition; Specification testing; Real exchange rates;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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