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Business Cycles and Turning Points: A Survey of Statistical Techniques

Author

Listed:
  • Michael Massmann

    (National Institute of Economic and Social Research)

  • James Mitchell

    (National Institute of Economic and Social Research, j.mitchell@niesr.ac.uk)

  • Martin Weale

    (National Institute of Economic and Social Research, mweale@niesr.ac.uk)

Abstract

The business cycle has an importance in the popular debate which can tend to run ahead of the problems in measuring it. This paper provides a survey of the main statistical techniques that are used to measure the cycle. An application to the UK illustrates that the choice of what measure, or measures, to use is more than a dry academic issue. Inference about the business cycle is potentially sensitive to measurement. Fortunately, however, there is an element of consensus.

Suggested Citation

  • Michael Massmann & James Mitchell & Martin Weale, 2003. "Business Cycles and Turning Points: A Survey of Statistical Techniques," National Institute Economic Review, National Institute of Economic and Social Research, vol. 183(1), pages 90-106, January.
  • Handle: RePEc:sae:niesru:v:183:y:2003:i:1:p:90-106
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    Citations

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    Cited by:

    1. Mark J. Holmes & Brian Silverstone, 2010. "Business confidence and cyclical turning points: a Markov-switching approach," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 229-233, February.
    2. Maurizio Bovi, 2003. "Nonparametric Analysis Of The International Business Cycles," ISAE Working Papers 37, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    3. Klaus Wohlrabe, 2011. "Konstruktion von Indikatoren zur Analyse der wirtschaftlichen Aktivität in den Dienstleistungsbereichen," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 55, June.
    4. Massmann, Michael & Mitchell, James, 2003. "Reconsidering the evidence: Are Eurozone business cycles converging," ZEI Working Papers B 05-2003, University of Bonn, ZEI - Center for European Integration Studies.
    5. González Andrés & Teräsvirta Timo, 2008. "Modelling Autoregressive Processes with a Shifting Mean," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-28, March.
    6. Francis W. Ahking, 2015. "Measuring U.S. Business Cycles: A Comparison of Two Methods and Two Indicators of Economic Activities (With Appendix A)," Working papers 2015-06, University of Connecticut, Department of Economics.
    7. Kovačić, Zlatko & Vilotić, Miloš, 2017. "Assessing European business cycles synchronization," MPRA Paper 79990, University Library of Munich, Germany.
    8. Francis W. Ahking, 2013. "Measuring U.S. Business Cycles: A Comparison of Two Methods and Two Indicators of Economic Activities," Working papers 2013-10, University of Connecticut, Department of Economics.
    9. Lourdes Montoya & Jakob Haan, 2008. "Regional business cycle synchronization in Europe?," International Economics and Economic Policy, Springer, vol. 5(1), pages 123-137, July.
    10. Sèna Kimm Gnangnon, 2012. "An analysis of duration dependence of government revenue expansions and contractions in Developing Countries," Working Papers halshs-00722083, HAL.
    11. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil II: Die Zyklendatierung," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(14), pages 24-31, July.

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