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Real-time detection of the business cycle using SETAR models

Author

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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)

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.

Suggested Citation

  • Laurent Ferrara & Dominique Guegan, 2006. "Real-time detection of the business cycle using SETAR models," Post-Print halshs-00185372, HAL.
    • Handle: RePEc:hal:journl:halshs-00185372
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00185372
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    References listed on IDEAS

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    Cited by:

    1. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2009. "Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro," Documents de travail du Centre d'Economie de la Sorbonne 09053, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

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