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Turning-point indicators from business surveys: real-time detection for the euro area and its major member countries

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  • Alberto Baffigi

    ()
    (Banca d'Italia)

  • Antonio Bassanetti

    ()
    (Banca d'Italia)

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    Abstract

    We present tools for real-time detection of turning points in the industrial production growth-cycle of the euro area and its four largest economies. In particular, we apply a multivariate hidden Markov model to national survey results – i.e. to the earliest information about current economic developments - in order to estimate the probability of expansionary and recessionary phases. The balances of opinions used as inputs of the model are selected by ranking them according to their degree of commonality with respect to the cyclical fluctuations of the industrial sector, as estimated with the Generalized Dynamic Factor Model. The indicators appear reliable and stable.

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    File URL: http://www.bancaditalia.it/pubblicazioni/econo/temidi/td04/td500_04/td500/tema_500.pdf
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    Bibliographic Info

    Paper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 500.

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    Date of creation: Jun 2004
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    Handle: RePEc:bdi:wptemi:td_500_04

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    Web page: http://www.bancaditalia.it
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    Related research

    Keywords: business cycle; hidden Markov model; business surveys;

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    1. Paolo Finaldi Russo & Luigi Leva, 2004. "Il debito commerciale in Italia: quanto contano le motivazioni finanziarie?," Temi di discussione (Economic working papers) 496, Bank of Italy, Economic Research and International Relations Area.
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    Cited by:
    1. Raffaello Bronzini, 2004. "Foreign Direct Investment and Agglomeration: Evidence from Italy," ERSA conference papers ersa04p321, European Regional Science Association.
    2. Sangalli, Ilaria, 2013. "Inventory investment and financial constraints in the Italian manufacturing industry: A panel data GMM approach," Research in Economics, Elsevier, vol. 67(2), pages 157-178.

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