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

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Author Info

  • Monica Billio

    ()
    (Università Ca' Foscari of Venice - Department of Economics)

  • Laurent Ferrara

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, DGEI-DAMEP - Banque de France)

  • Dominique Guegan

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

  • Gian Luigi Mazzi

    ()
    (Eurostat - Office Statistique des Communautés Européennes)

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.

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Bibliographic Info

Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00423890.

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Date of creation: Aug 2009
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Handle: RePEc:hal:cesptp:halshs-00423890

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Related research

Keywords: Business cycle; Euro zone; Markov switching model; SETAR model; unemployment; industrial production.;

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