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Business Cycles and Turning Points: A Survey of Statistical Techniques

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  • 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.

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Bibliographic Info

Article provided by National Institute of Economic and Social Research in its journal National Institute Economic Review.

Volume (Year): 183 (2003)
Issue (Month): 1 (January)
Pages: 90-106

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Handle: RePEc:sae:niesru:v:183:y:2003:i:1:p:90-106

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Cited by:
  1. Timo Terasvirta & Andrés González, . "Modelling autoregressive processes with a shifting mean," Borradores de Economia 420, Banco de la Republica de Colombia.
  2. 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.
  3. Mark 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.
  4. Sèna Kimm Gnangnon, 2012. "An analysis of duration dependence of government revenue expansions and contractions in Developing Countries," Working Papers halshs-00722083, HAL.

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