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Dating the Italian Business Cycle: A Comparison of Procedures

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  • Giancarlo Bruno

    (ISAE-Roma)

  • Edoardo Otranto

    (DEIR-Università di Sassari)

Abstract

The problem of dating the business cycle has recently received many contributions, with a lot of proposed statistical methodologies, parametric and non parametric. Despite of this, only a few countries produce an official dating of the business cycle. In this work we try to apply some procedures for an automatic dating of the Italian business cycle in the last thirty years, checking differences among various methodologies and with the ISAE chronology. To this end parametric as well as non parametric methods are employed. The analysis is carried out both aggregating results from single time series and directly in a multivariate framework. The different methods are also evaluated with respect to their ability to timely track turning points. KEYWORDS: signal extraction, turning points, parametric methods, nonparametric methods

Suggested Citation

  • Giancarlo Bruno & Edoardo Otranto, 2003. "Dating the Italian Business Cycle: A Comparison of Procedures," Econometrics 0312003, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpem:0312003
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    Cited by:

    1. Sergey V. Smirnov & Nikolay V. Kondrashov & Anna V. Petronevich, 2017. "Dating Cyclical Turning Points for Russia: Formal Methods and Informal Choices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 13(1), pages 53-73, May.
    2. Marianna Brunetti & Costanza Torricelli, 2009. "Economic activity and recession probabilities: information content and predictive power of the term spread in Italy," Applied Economics, Taylor & Francis Journals, vol. 41(18), pages 2309-2322.
    3. Bartoletto, Silvana & Chiarini, Bruno & Marzano, Elisabetta & Piselli, Paolo, 2019. "Business cycles, credit cycles, and asymmetric effects of credit fluctuations: Evidence from Italy for the period of 1861–2013," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    4. Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
    5. Mario Quagliariello, "undated". "Banks' Performance over the Business Cycle: A Panel Analysis on Italian Intermediaries," Discussion Papers 04/17, Department of Economics, University of York.
    6. Mario Quagliariello, 2006. "Banks� Riskiness Over the Business Cicle: a Panel Analysis on Italian Intermediaries," Temi di discussione (Economic working papers) 599, Bank of Italy, Economic Research and International Relations Area.
    7. Francesco Daveri & Cecilia Jona-Lasinio, 2005. "Italy's Decline: Getting the Facts Right," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 64(4), pages 365-410, December.
    8. Silvana Bartoletto & Bruno Chiarini & Elisabetta Marzano & Paolo Piselli, 2015. "Business Cycles, Credit Cycles and Bank Holdings of Sovereign Bonds: Historical Evidence for Italy 1861-2013," CESifo Working Paper Series 5318, CESifo.
    9. Nada Kulendran & Kevin K.F. Wong, 2009. "Predicting Quarterly Hong Kong Tourism Demand Growth Rates, Directional Changes and Turning Points with Composite Leading Indicators," Tourism Economics, , vol. 15(2), pages 307-322, June.
    10. Silvia Palasca & Elisabeta Jaba, 2014. "Leading and Lagging Indicators Of the Economic Crisis," Romanian Statistical Review, Romanian Statistical Review, vol. 62(3), pages 31-47, September.
    11. Fachin, Stefano & Gavosto, Andrea, 2007. "The decline in Italian productivity: a study in estimation of long-Run trends in Total Factor Productivity with panel cointegration methods," MPRA Paper 3112, University Library of Munich, Germany.
    12. Mario Quagliariello, 2007. "Banks' riskiness over the business cycle: a panel analysis on Italian intermediaries," Applied Financial Economics, Taylor & Francis Journals, vol. 17(2), pages 119-138.
    13. Craigwell, Roland & Maurin, Alain, 2007. "A sectoral analysis of Barbados’ GDP business cycle," MPRA Paper 33428, University Library of Munich, Germany.
    14. Stefano Fachin & Andrea Gavosto, 2010. "Trends of labour productivity in Italy: a study with panel co‐integration methods," International Journal of Manpower, Emerald Group Publishing Limited, vol. 31(7), pages 755-769, October.
    15. Märten Kress, 2004. "Lending cycles in Estonia," Bank of Estonia Working Papers 2004-3, Bank of Estonia, revised 10 Oct 2004.
    16. Edoardo Otranto, 2005. "Extraction of Common Signal from Series with Different Frequency," Econometrics 0502011, University Library of Munich, Germany.
    17. Cabrer-Borrás, Bernanrdi & Serrano, Guadalupe & Pavía, José M., 2017. "Evaluación del sesgo en las estimaciones de Contabilidad Nacional Trimestral: Estudio de las añadas en España /Assessing Quarterly Spanish National Accounts Estimates. A Study of the vintages," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 271-298, Mayo.

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    More about this item

    Keywords

    signal extraction; turning points; parametric methods; nonparametric methods;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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