Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro

Monica Billio, Laurent Ferrara, Dominique Guegan () and Gian Luigi Mazzi ()
Additional contact information
Dominique Guegan: Paris School of Economics - Centre d'Economie de la Sorbonne, https://cv.archives-ouvertes.fr/dominique-guegan
Gian Luigi Mazzi: Eurostat

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: In this paper, we aim at assessing Markov-switching and threshold models in their ability to identify turning points of economic cycles. By using vintage data that are updated on a monthly basis, we compare their ability to detect ex-post the occurrence of turning points of the classical business cycle, we evaluate the stability over time of the signal emitted by the models and assess their ability to detect in real-time recession signals. In this respect, we have built an historical vintage database for the Euro area going back to 1970 for two monthly macroeconomic variables of major importance for short-term economic outlook, namely the Industrial Production Index and the Unemployment Rate

Keywords: Business cycle; Euro zone; Markov switching model; SETAR mpdel; unemployment; industrial production (search for similar items in EconPapers)
JEL-codes: C22 C52 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2009-08
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-eec, nep-ets and nep-mac
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Citations: View citations in EconPapers (2)

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ftp://mse.univ-paris1.fr/pub/mse/CES2009/09053.pdf (application/pdf)

Related works:
Working Paper: Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro area (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:09053

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