Real-time detection of the business cycle using SETAR models

Laurent Ferrara () and Dominique Guegan ()
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Laurent Ferrara: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique
Dominique Guegan: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - 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 business cycle such as asymmetries in the phases. 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: 2006
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00185372
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Published in G.L. Mazzi and G. Savio. Growth and Cycle in the Euro-zone, Palgrave MacMillan, New York, pp.221-232, 2006

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