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Dating Business Cycles in Historical Perspective: Evidence for Switzerland


  • Siliverstovs Boriss

    () (KOF Swiss Economic Institute, ETH Zurich, Weinbergstrasse 35, 8092 Zurich, Switzerland)


In this study we suggest a chronology of the classical business cycle in Switzerland based on dating algorithms suggested in Artis et al. (2004) and Harding and Pagan (2002). A further contribution of our study is that we determine the sensitivity of the chronology with respect to the particular GDP vintage used. For this purpose we employ a real-time database that contains 59 vintages of GDP data starting from 1997Q4 and ending in 2012Q2. We show that major changes in identified phases of the classical business cycle in Switzerland can be well traced to several benchmark revisions to the national accounts. In the absence of benchmark revisions the vintage-to-vintage variation exerts a comparatively minor effect on identified phases of the classical business cycle.

Suggested Citation

  • Siliverstovs Boriss, 2013. "Dating Business Cycles in Historical Perspective: Evidence for Switzerland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(5-6), pages 661-679, October.
  • Handle: RePEc:jns:jbstat:v:233:y:2013:i:5-6:p:661-679

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    References listed on IDEAS

    1. Tommaso Proietti, 2009. "On the Model-Based Interpretation of Filters and the Reliability of Trend-Cycle Estimates," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 186-208.
    2. Proietti, Tommaso, 2008. "Structural Time Series Models for Business Cycle Analysis," MPRA Paper 6854, University Library of Munich, Germany.
    3. Harding, Don & Pagan, Adrian, 2001. "Extracting, Using and Analysing Cyclical Information," MPRA Paper 15, University Library of Munich, Germany.
    4. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters,in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1 National Bureau of Economic Research, Inc.
    5. Proietti, Tommaso, 2005. "New algorithms for dating the business cycle," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 477-498, April.
    6. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    7. Gomez, Victor, 2001. "The Use of Butterworth Filters for Trend and Cycle Estimation in Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 365-373, July.
    8. Nicolas Cuche-Curti & Pamela Hall & Attilio Zanetti, 2009. "Swiss GDP revisions: A monetary policy perspective," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(2), pages 183-213.
    9. Boldin, Michael D, 1994. "Dating Turning Points in the Business Cycle," The Journal of Business, University of Chicago Press, vol. 67(1), pages 97-131, January.
    10. Pollock, D. S. G., 2000. "Trend estimation and de-trending via rational square-wave filters," Journal of Econometrics, Elsevier, vol. 99(2), pages 317-334, December.
    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, January.
    12. Michael Artis & Massimiliano Marcellino & Tommaso Proietti, 2004. "Dating Business Cycles: A Methodological Contribution with an Application to the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(4), pages 537-565, September.
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