IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v74y1996i1p59-75.html
   My bibliography  Save this article

Testing the adequacy of smooth transition autoregressive models

Author

Listed:
  • Eitrheim, Oyvind
  • Terasvirta, Timo

Abstract

Smooth transition autoregressive models are a flixible family of nonlinear time series models that have also been used for modelling economic data. This paper contributes to the evaluation stage of a proposed specification, estimation, and evaluation cycle of this models by introducing a Lagrange multiplier (LM) test for the hypothesis of no error autocorrelation and LM type tests for the hypothesis of remaining nonlinearity and that of parameter constancy. Small sample properies of the F versions of the tests and some alternative tests are investigated by simulation. The results indicate that the proposed tests can be applied in small samples already.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
  • Handle: RePEc:eee:econom:v:74:y:1996:i:1:p:59-75
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0304-4076(95)01751-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    2. 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.
    3. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thomas Chiang & Jiandong Li & Sheng-Yung Yang, 2015. "Dynamic stock–bond return correlations and financial market uncertainty," Review of Quantitative Finance and Accounting, Springer, vol. 45(1), pages 59-88, July.
    2. Tolga Omay & Furkan Emirmahmutoğlu, 2017. "The Comparison of Power and Optimization Algorithms on Unit Root Testing with Smooth Transition," Computational Economics, Springer;Society for Computational Economics, vol. 49(4), pages 623-651, April.
    3. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    4. Milas Costas & Legrenzi Gabriella, 2006. "Non-linear Real Exchange Rate Effects in the UK Labour Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(1), pages 1-34, March.
    5. Heather M. Anderson & Farshid Vahid, 2005. "Nonlinear Correlograms and Partial Autocorrelograms," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 957-982, December.
    6. Corradi, Valentina & Swanson, Norman R., 2002. "A consistent test for nonlinear out of sample predictive accuracy," Journal of Econometrics, Elsevier, vol. 110(2), pages 353-381, October.
    7. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    8. Kapetanios, G. & Tzavalis, E., 2010. "Modeling structural breaks in economic relationships using large shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 417-436, March.
    9. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    10. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    11. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415.
    12. Q. Farooq Akram & Øyvind Eitrheim & Lucio Sarno, 2005. "Non-linear dynamics in output, real exchange rates and real money balances: Norway, 1830-2003," Working Paper 2005/2, Norges Bank.
    13. Heather M. Anderson, 2002. "Choosing Lag Lengths in Nonlinear Dynamic Models," Monash Econometrics and Business Statistics Working Papers 21/02, Monash University, Department of Econometrics and Business Statistics.
    14. Mills, Terence C., 1995. "Business cycle asymmetries and non-linearities in U.K. macroeconomic time series," Ricerche Economiche, Elsevier, vol. 49(2), pages 97-124, June.
    15. Carlo Altavilla & Paul De Grauwe, 2005. "Non-Linearities in the Relation between the Exchange Rate and its Fundamentals," CESifo Working Paper Series 1561, CESifo.
    16. Hasanov, Mübariz & Araç, Aysen & Telatar, Funda, 2010. "Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey," Economic Modelling, Elsevier, vol. 27(5), pages 1103-1115, September.
    17. Mohamed Boutahar & Imene Mootamri & Anne Peguin-Feissolle, 2007. "An exponential FISTAR model applied to the US real effective exchange rate," Working Papers halshs-00353836, HAL.
    18. Franses, Philip Hans & Draisma, Gerrit, 1997. "Recognizing changing seasonal patterns using artificial neural networks," Journal of Econometrics, Elsevier, vol. 81(1), pages 273-280, November.
    19. Dijk, Dick van & Franses, Philip Hans, 1999. "Modeling Multiple Regimes in the Business Cycle," Macroeconomic Dynamics, Cambridge University Press, vol. 3(3), pages 311-340, September.
    20. Ubilava, David & holt, Matt, 2013. "El Ni~no southern oscillation and its effects on world vegetable oil prices: assessing asymmetries using smooth transition models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(2), pages 1-25.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:econom:v:74:y:1996:i:1:p:59-75. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nithya Sathishkumar). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.