Diagnostic Checking in a Flexible Nonlinear Time Series Model
This paper considers a sequence of misspecification tests for a flexible nonlinear time series model. The model is a generalization of both the Smooth Transition AutoRegressive (STAR) and the AutoRegressive Artificial Artificial Neural Network (AR-ANN) models. The tests are Lagrange multiplier (LM) type tests of parameter constancy against the alternative of smoothly changing ones, of serial independence, and constant variance of the error term against the hypothesis that the variance smoothly changes between regimes. The small sample behaviour of the proposed tests is evaluated throw a Monte-Carlo study and the results show that the tests have size close to the nominal one and a good power.
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|Date of creation:||06 Jun 2000|
|Date of revision:||15 Jan 2001|
|Publication status:||Published in Journal of Time Series Analysis, 2003, pages 461-482.|
|Contact details of provider:|| Postal: The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden|
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- Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999.
"A simple variable selection technique for nonlinear models,"
SSE/EFI Working Paper Series in Economics and Finance
296, Stockholm School of Economics, revised 06 Apr 2000.
- Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999. "A simple variable selection technique for nonlinear models," SFB 373 Discussion Papers 1999,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Chung-Ming Kuan, 2006. "Artificial Neural Networks," IEAS Working Paper : academic research 06-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
- Russell Davidson & James G. MacKinnon, 1994. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," Working Papers 903, Queen's University, Department of Economics.
- Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
- Eitrheim, Øyvind & Teräsvirta, Timo, 1995. "Testing the Adequacy of Smooth Transition Autoregressive Models," SSE/EFI Working Paper Series in Economics and Finance 56, Stockholm School of Economics.
- T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 239-253.
- Breusch, T.S. & Pagan, A.R., "undated". "The Lagrange multiplier test and its applications to model specification in econometrics," CORE Discussion Papers RP 412, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
- Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
- Lundbergh, Stefan & Terasvirta, Timo & van Dijk, Dick, 2003. "Time-Varying Smooth Transition Autoregressive Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 104-121, January.
- Lundbergh, Stefan & Teräsvirta, Timo & van Dijk, Dick, 2000. "Time-Varying Smooth Transition Autoregressive Models," SSE/EFI Working Paper Series in Economics and Finance 376, Stockholm School of Economics.
- Medeiros, Marcelo & Veiga, Alvaro, 2000. "A Flexible Coefficient Smooth Transition Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 360, Stockholm School of Economics, revised 29 Apr 2004. Full references (including those not matched with items on IDEAS)