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Ita-coin: a new coincident indicator for the Italian economy

Author

Listed:
  • Valentina Aprigliano

    (Bank of Italy)

  • Lorenzo Bencivelli

    (Bank of Italy)

Abstract

In this paper we present a coincident indicator for the Italian economy, Ita-coin. We construct a multivariate filter based on a broad information set, whose dimension is reduced by the Generalized Dynamic Factor Model (GDFM) approach proposed by Forni et al. (2002). A regression based on the least absolute shrinkage and selection operator (LASSO) is used to estimate Ita-coin. Most Italian macroeconomic indicators are characterized by high short-term volatility and the 2008-2009 crisis has affected the volatility of both the high- and low-frequency components and the relationships between the variables have become more unstable. LASSO regression allows us to select recursively the relevant information about the comovement of the variables over time. Our indicator displays a satisfactory performance in the pseudo real-time validation as a timely cyclical indicator.

Suggested Citation

  • Valentina Aprigliano & Lorenzo Bencivelli, 2013. "Ita-coin: a new coincident indicator for the Italian economy," Temi di discussione (Economic working papers) 935, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_935_13
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    References listed on IDEAS

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    6. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2010. "New Eurocoin: Tracking Economic Growth in Real Time," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1024-1034, November.
    7. Lippi, Marco & Reichlin, Lucrezia & Hallin, Marc & Forni, Mario & Altissimo, Filippo & Cristadoro, Riccardo & Veronese, Giovanni & Bassanetti, Antonio, 2001. "EuroCOIN: A Real Time Coincident Indicator of the Euro Area Business Cycle," CEPR Discussion Papers 3108, C.E.P.R. Discussion Papers.
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    Cited by:

    1. Piergiorgio Alessandri & Leonardo Del Vecchio & Arianna Miglietta, 2019. "Financial Conditions and 'Growth at Risk' in Italy," Temi di discussione (Economic working papers) 1242, Bank of Italy, Economic Research and International Relations Area.
    2. Ellul, Reuben, 2016. "A real-time measure of business conditions in Malta," MPRA Paper 75057, University Library of Munich, Germany.
    3. Giuseppe Ferrero & Andrea Nobili & Gabriele Sene, 2019. "Credit risk-taking and maturity mismatch: the role of the yield curve," Temi di discussione (Economic working papers) 1220, Bank of Italy, Economic Research and International Relations Area.
    4. Corona Francisco & González-Farías Graciela & López-Pérez Jesús, 2022. "Timely Estimates of the Monthly Mexican Economic Activity," Journal of Official Statistics, Sciendo, vol. 38(3), pages 733-765, September.
    5. Francisco Corona & Graciela Gonz'alez-Far'ias & Jes'us L'opez-P'erez, 2021. "A nowcasting approach to generate timely estimates of Mexican economic activity: An application to the period of COVID-19," Papers 2101.10383, arXiv.org.

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    More about this item

    Keywords

    factor analysis; frequency-domain; LASSO regression; business cycle.;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models

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