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Detection of the industrial business cycle using SETAR models

  • Ferrara, Laurent
  • Guégan, Dominique

In this paper, we consider a threshold time series model in order to take into account certain stylized facts of the industrial business cycle, such as asymmetries in the phases of the cycle. Our aim is to point out some thresholds under (over) which a signal of turning point could be given. First, we introduce the various threshold models and we discuss both their statistical theoretical and empirical properties. Especially, we review the classical techniques to estimate the number of regimes, the threshold, the delay and the parameters of the model. Then, we apply these models to the Euro-zone industrial production index to detect, through a dynamic simulation approach, the dates of peaks and troughs in the business cycle.

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File URL: https://mpra.ub.uni-muenchen.de/4389/1/MPRA_paper_4389.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 4389.

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Date of creation: Sep 2005
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Publication status: Published in Journal of Business Cycle Measurement and Analysis 3.2(2005): pp. 353-372
Handle: RePEc:pra:mprapa:4389
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  1. Bruce E. Hansen, 1996. "Sample Splitting and Threshold Estimation," Boston College Working Papers in Economics 319., Boston College Department of Economics, revised 12 May 1998.
  2. Dufrenot, Gilles & Guegan, Dominique & Peguin-Feissolle, Anne, 2005. "Long-memory dynamics in a SETAR model - applications to stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(5), pages 391-406, December.
  3. Hans-Martin Krolzig & Michael Clements, 2000. "Business Cycle Asymmetries: Characterisation and Testing based on Markov-Switching Autoregressions," Economics Series Working Papers 2000-W32, University of Oxford, Department of Economics.
  4. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
  5. Jacques Anas & Laurent Ferrara, 2004. "Detecting Cyclical Turning Points: The ABCD Approach and Two Probabilistic Indicators," Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2004(2), pages 193-225.
  6. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-25, April-Jun.
  7. Potter, Simon M, 1999. " Nonlinear Time Series Modelling: An Introduction," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 505-28, December.
  8. Marcelle Chauvet & Jeremy M. Piger, 2003. "Identifying business cycle turning points in real time," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 47-61.
  9. Mike Artis & Hans-Martin Krolzig & Juan Toro, 2002. "The European Business Cycle," Economic Working Papers at Centro de Estudios Andaluces E2002/19, Centro de Estudios Andaluces.
  10. Arturo Estrella & Frederic S. Mishkin, 1996. "Predicting U.S. recessions: financial variables as leading indicators," Research Paper 9609, Federal Reserve Bank of New York.
  11. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
  12. Krolzig, H.-M. & Toro, J., 2001. "Classical And Modern Business Cycle Measurement: The European Case," Economics Series Working Papers 9960, University of Oxford, Department of Economics.
  13. Gonzalo, Jesus & Pitarakis, Jean-Yves, 2002. "Estimation and model selection based inference in single and multiple threshold models," Journal of Econometrics, Elsevier, vol. 110(2), pages 319-352, October.
  14. Hans-Martin Krolzig, 2001. "Markov-Switching Procedures for Dating the Euro-Zone Business Cycle," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 70(3), pages 339-351.
  15. 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.
  16. Gilles DUFRENOT & Dominique GUEGAN & Anne PEGUIN-FEISSOLLE, 2003. "A SETAR model with long-memory dynamics," Econometrics 0309002, EconWPA.
  17. Maravall, Agustin & Planas, Christophe, 1999. "Estimation error and the specification of unobserved component models," Journal of Econometrics, Elsevier, vol. 92(2), pages 325-353, October.
  18. Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Modelling squared returns using a SETAR model with long-memory dynamics," Post-Print halshs-00179285, HAL.
  19. Michael Artis, 2003. "Is there a European Business Cycle?," CESifo Working Paper Series 1053, CESifo Group Munich.
  20. Kajal Lahiri & Wenxiong Yao & Peg Young, 2003. "Cycles in the Transportation Sector and the Aggregate Economy," Discussion Papers 03-14, University at Albany, SUNY, Department of Economics.
  21. Coakley, Jerry & Fuertes, Ana-Maria & Perez, Maria-Teresa, 2003. "Numerical issues in threshold autoregressive modeling of time series," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2219-2242, September.
  22. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, June.
  23. G. Pfann & P. Schotman & R. Tschernig, 1994. "Nonlinear Interest Rate Dynamics and Implications for the Term Structure," SFB 373 Discussion Papers 1994,43, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  24. 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.
  25. 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 357-84, March.
  26. Cathy W. S. Chen & Mike K. P. So, 2003. "Subset threshold autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 49-66.
  27. 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.
  28. Sichel, Daniel E, 1994. "Inventories and the Three Phases of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 269-77, July.
  29. Clements, Michael P. & Smith, Jeremy, 2001. "Evaluating forecasts from SETAR models of exchange rates," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 133-148, February.
  30. Harding, Don & Pagan, Adrian, 2003. "A comparison of two business cycle dating methods," Journal of Economic Dynamics and Control, Elsevier, vol. 27(9), pages 1681-1690, July.
  31. Ferrara, Laurent, 2003. "A three-regime real-time indicator for the US economy," Economics Letters, Elsevier, vol. 81(3), pages 373-378, December.
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