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Generalizing smooth transition autoregressions

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This paper introduces a variant of the smooth transition autoregression (STAR). The proposed model is able to parametrize the asymmetry in the tails of the transition equation by using a particular generalization of the logistic function. The null hypothesis of symmetric adjustment toward a new regime is tested by building two different LM-type tests. The first one maintains the original parametrization, while the second one is based on a third-order expanded auxiliary regression. Three diagnostic tests for no error autocorrelation, no additive asymmetry and parameter constancy are also discussed. The empirical size and power of the new symmetry as well as diagnostic tests are investigated by an extensive Monte Carlo experiment. An empirical application of the so generalized STAR (GSTAR) model to four economic time series reveals that the asymmetry in the transition between two regimes is a feature to be considered for economic analysis.

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Bibliographic Info

Paper provided by Tor Vergata University, CEIS in its series CEIS Research Paper with number 294.

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Length: 49 pages
Date of creation: 15 Oct 2013
Date of revision: 15 Oct 2013
Handle: RePEc:rtv:ceisrp:294

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Postal: CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma
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Web: http://www.ceistorvergata.it

Related research

Keywords: Dynamic Asymmetry; GSTAR; LM-type Tests; Business Cycle; Long-Term Interest Spread; CO2 Emissions;

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  1. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," CREATES Research Papers 2011-01, School of Economics and Management, University of Aarhus.
  2. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
  3. 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.
  4. Sichel, Daniel E, 1993. "Business Cycle Asymmetry: A Deeper Look," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 224-36, April.
  5. Timo Terasvirta, 2004. "A Time Series Model for an Exchange Rate in a Target Zone with Applications," Econometric Society 2004 Australasian Meetings 340, Econometric Society.
  6. 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.
  7. 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.
  8. 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.
  9. Michael Dueker & Martin Sola & Fabio Spagnolo, 2006. "Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting," Department of Economics Working Papers 2006-04, Universidad Torcuato Di Tella.
  10. Skalin, Joakim & Ter svirta, Timo, 2002. "Modeling Asymmetries And Moving Equilibria In Unemployment Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 6(02), pages 202-241, April.
  11. 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.
  12. 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.
  13. 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.
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