Detection of the Industrial Business Cycle using SETAR models

Dominique Guegan () and Laurent Ferrara
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Dominique Guegan: IDHE - Institutions et Dynamiques Historiques de l'Economie - ENS Cachan - École normale supérieure - Cachan - UP1 - Université Paris 1 Panthéon-Sorbonne - UP8 - Université Paris 8 Vincennes-Saint-Denis - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique

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Abstract: We consider a threshold time series model in order to take into account some stylized facts of the industrial business cycle such as asymmetries in the phase 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. Specifically, 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 area industrial production index to detect, through a dynamic simulation approach, the dates of peaks and thoughs in business cycle.

Keywords: Economic cycle; Turning point detection Threshold model; Euro area IPI (search for similar items in EconPapers)
Date: 2005
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00201309
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Citations: View citations in EconPapers (4)

Published in Journal of Business Cycle Measurement and Analysis, 2005, 2, pp.353-371

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Related works:
Journal Article: Detection of the Industrial Business Cycle using SETAR Models (2006)
Working Paper: Detection of the industrial business cycle using SETAR models (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-00201309

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