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Detection of the industrial business cycle using SETAR models

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  • Ferrara, Laurent
  • Guégan, Dominique

Abstract

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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Bibliographic Info

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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Keywords: Economic cycle; turning point detection; Threshold model; Euro-zone IPI;

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  1. Hans-Martin Krolzig & Juan Toro, 2004. "Classical and modern business cycle measurement: The European case," Spanish Economic Review, Springer, Springer, vol. 7(1), pages 1-21, January.
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  6. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, Econometric Society, vol. 57(2), pages 357-84, March.
  7. Maria-Teresa Perez & Ana-Maria Fuertes & Jerry Coakley, 2001. "Numerical Issues in Threshold Autoregressive Modelling of Time Series," Working Papers, Warwick Business School, Finance Group wp01-09, Warwick Business School, Finance Group.
  8. van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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  17. Mike Artis & Hans-Martin Krolzig & Juan Toro, 2004. "The European business cycle," Oxford Economic Papers, Oxford University Press, vol. 56(1), pages 1-44, January.
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  21. Gilles Dufrénot & Dominique Guegan & Anne Peguin-Feissolle, 2005. "Long-memory dynamics in a SETAR model - Applications to stock markets," Post-Print halshs-00179339, HAL.
  22. 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,CIRET, OECD Publishing,CIRET, vol. 2004(2), pages 193-225.
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  26. Kajal Lahiri & Wenxiong Yao & Peg Young, 2003. "Cycles in the Transportation Sector and the Aggregate Economy," Discussion Papers, University at Albany, SUNY, Department of Economics 03-14, University at Albany, SUNY, Department of Economics.
  27. Dufrenot, Gilles & Guegan, Dominique & Peguin-Feissolle, Anne, 2005. "Modelling squared returns using a SETAR model with long-memory dynamics," Economics Letters, Elsevier, Elsevier, vol. 86(2), pages 237-243, February.
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Cited by:
  1. Roque Montero, 2011. "Does linearity in the dynamics of inflation gap and unemployment rate matter?," Working Papers Central Bank of Chile, Central Bank of Chile 614, Central Bank of Chile.
  2. repec:hal:journl:halshs-00368358 is not listed on IDEAS
  3. Singh, Tarlok, 2014. "On the regime-switching and asymmetric dynamics of economic growth in the OECD countries," Research in Economics, Elsevier, Elsevier, vol. 68(2), pages 169-192.
  4. repec:hal:journl:halshs-00423890 is not listed on IDEAS

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