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Dating the Italian BUsiness Cycle: A Comparison of Procedures

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  • Bruno Giancarlo

    (ISAE - Institute for Studies and Economic Analyses)

  • Edoardo Otranto

    (ISTAT - Istituto Nazionale di Statistica)

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.

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File URL: http://lipari.istat.it/digibib/Working_Papers/Brunootranto41wp2004.pdf
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Bibliographic Info

Paper provided by ISTAT - Italian National Institute of Statistics - (Rome, ITALY) in its series ISAE Working Papers with number 41.

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Length: 28 pages
Date of creation: Jan 2004
Date of revision:
Handle: RePEc:isa:wpaper:41

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Keywords: business cycle; turning points; parametric methods; nonparametric methods.;

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References

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  1. Bruno, Giancarlo & Lupi, Claudio, 2003. "Forecasting Industrial Production and the Early Detection of Turning Points," Economics & Statistics Discussion Papers esdp03004, University of Molise, Dept. EGSeI.
  2. 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.
  3. 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 357-84, March.
  4. Francis X. Diebold & Glenn D. Rudebusch, 1994. "Measuring Business Cycles: A Modern Perspective," NBER Working Papers 4643, National Bureau of Economic Research, Inc.
  5. 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 231-47, July-Sept.
  6. 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.
  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 R, 1997. "Business Cycles for G7 and European Countries," The Journal of Business, University of Chicago Press, vol. 70(2), pages 249-79, April.
  9. 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, December.
  10. 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 969-96, November.
  11. Zacharias Psaradakis & Nicola Spagnolo, 2002. "On the Determination of the Number of Regimes in Markov-Switching Autoregressive Models," Computing in Economics and Finance 2002 83, Society for Computational Economics.
  12. Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
  13. 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.
  14. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
  15. 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.
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Cited by:
  1. F. Daveri & C. Jona-Lasinio, 2006. "Italy’s decline: getting the facts right," Economics Department Working Papers 2006-EP01, Department of Economics, Parma University (Italy).
  2. Edoardo Otranto, 2005. "Extraction of Common Signal from Series with Different Frequency," Econometrics 0502011, EconWPA.
  3. 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.
  4. 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.
  5. Märten Kress, 2004. "Lending cycles in Estonia," Bank of Estonia Working Papers 2004-3, Bank of Estonia, revised 10 Oct 2004.
  6. Craigwell, Roland & Maurin, Alain, 2007. "A sectoral analysis of Barbados’ GDP business cycle," MPRA Paper 33428, University Library of Munich, Germany.
  7. Mario Quagliariello, . "Banks' Performance over the Business Cycle: A Panel Analysis on Italian Intermediaries," Discussion Papers 04/17, Department of Economics, University of York.
  8. 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, November.

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