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Generalizing smooth transition autoregressions

  • Emilio Zanetti Chini

    ()

    (University of Rome "Tor Vergata")

We introduce a variant of the smooth transition autoregression - the GSTAR model - capable to parametrize the asymmetry in the tails of the transition equation by using a particular generalization of the logistic function. A General-to-Specific modelling strategy is discussed in detail, with particular emphasis on two different LM-type tests for the null of symmetric adjustment towards a new regime and three diagnostic tests, whose power properties are explored via Monte Carlo experiments. Four classical real datasets illustrate the empirical properties of the GSTAR, jointly to a rolling forecasting experiment to evaluate its point and density forecasting performances. In all the cases, the dynamic asymmetry in the cycle is efficiently captured by the new model. The GSTAR beats AR and STAR competitors in point forecasting, while this superiority becomes less evident in density forecasting, specially if robust measures are considered.

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Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2013-32.

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Length: 53
Date of creation: 26 Sep 2013
Date of revision:
Handle: RePEc:aah:create:2013-32
Contact details of provider: Web page: http://www.econ.au.dk/afn/

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  1. Daniel E. Sichel, 1989. "Business cycle asymmetry: a deeper look," Working Paper Series / Economic Activity Section 93, Board of Governors of the Federal Reserve System (U.S.).
  2. Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
  3. Lundbergh, Stefan & Teräsvirta, Timo, 2003. "A time series model for an exchange rate in a target zone with applications," SSE/EFI Working Paper Series in Economics and Finance 533, Stockholm School of Economics.
  4. Michael Dueker & Martin Sola & Fabio Spagnolo, 2007. "Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting," Discussion Papers 5_2007, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
  5. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
  6. Amado, Cristina & Teräsvirta, Timo, 2013. "Modelling volatility by variance decomposition," Journal of Econometrics, Elsevier, vol. 175(2), pages 142-153.
  7. Rothman, Philip, 1991. "Further evidence on the asymmetric behavior of unemployment rates over the business cycle," Journal of Macroeconomics, Elsevier, vol. 13(2), pages 291-298.
  8. Seo, Byeongseon, 2003. "Nonlinear mean reversion in the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11), pages 2243-2265.
  9. Skalin, Joakim & Teräsvirta, Timo, 1998. "Modelling asymmetries and moving equilibria in unemployment rates," SSE/EFI Working Paper Series in Economics and Finance 262, Stockholm School of Economics, revised 05 Oct 1998.
  10. 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 104-21, January.
  11. 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.
  12. Seo, Byeongseon, 2003. "Nonlinear mean reversion in the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2243-2265, September.
  13. 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 S119-36, Suppl. De.
  14. Proietti Tommaso, 1998. "Characterizing Asymmetries in Business Cycles Using Smooth-Transition Structural Time-Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(3), pages 1-18, October.
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