IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpem/0312003.html
   My bibliography  Save this paper

Dating the Italian Business Cycle: A Comparison of Procedures

Author

Listed:
  • 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
    Note: Type of Document - pdf; prepared on Win98; to print on A4 paper; pages: 20. pdf document submitted via ftp
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0312/0312003.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
    2. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    3. Artis, Michael J & Kontolemis, Zenon G & Osborn, Denise R, 1997. "Business Cycles for G7 and European Countries," The Journal of Business, University of Chicago Press, vol. 70(2), pages 249-279, April.
    4. Giancarlo Bruno & Claudio Lupi, 2004. "Forecasting industrial production and the early detection of turning points," Empirical Economics, Springer, vol. 29(3), pages 647-671, September.
    5. Garcia-Ferrer, Antonio & Bujosa-Brun, Marcos, 2000. "Forecasting OECD industrial turning points using unobserved components models with business survey data," International Journal of Forecasting, Elsevier, vol. 16(2), pages 207-227.
    6. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    7. Edoardo Otranto & Giampiero Gallo, 2002. "A Nonparametric Bayesian Approach To Detect The Number Of Regimes In Markov Switching Models," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 477-496.
    8. Artis, Michael J & Kontolemis, Zenon G & Osborn, Denise, 1995. "Classical Business Cycles for G7 and European Countries," CEPR Discussion Papers 1137, C.E.P.R. Discussion Papers.
    9. Zacharias Psaradakis & Nicola Spagnolo, 2003. "On The Determination Of The Number Of Regimes In Markov‐Switching Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 237-252, March.
    10. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    11. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, June.
    12. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
    13. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    14. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
    15. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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, vol. 31(7), pages 755-769, October.
    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. Märten Kress, 2004. "Lending cycles in Estonia," Bank of Estonia Working Papers 2004-3, Bank of Estonia, revised 10 Oct 2004.
    9. Edoardo Otranto, 2005. "Extraction of Common Signal from Series with Different Frequency," Econometrics 0502011, University Library of Munich, Germany.
    10. Craigwell, Roland & Maurin, Alain, 2007. "A sectoral analysis of Barbados’ GDP business cycle," MPRA Paper 33428, University Library of Munich, Germany.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Eric Hillebrand & Siem Jan Koopman (ed.),Dynamic Factor Models, volume 35, pages 481-538, Emerald Publishing Ltd.
    16. 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.
    17. 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.

    More about this item

    Keywords

    signal extraction; turning points; parametric methods; nonparametric methods;

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpem:0312003. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.