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Statistical surveillance of cyclical processes with application to turns in business cycles

Author

Listed:
  • David Bock

    (Göteborg University, Sweden)

  • Eva Andersson

    (Göteborg University, Sweden)

  • Marianne Frisén

    (Göteborg University, Sweden)

Abstract

On-line monitoring of cyclical processes is studied. An important application is early prediction of the next turn in business cycles by an alarm for a turn in a leading index. Three likelihood-based methods for detection of a turn are compared in detail. One of the methods is based on a hidden Markov model. The two others are based on the theory of statistical surveillance. One of these is free from parametric assumptions of the curve. Evaluations are made of the effect of different specifications of the curve and the transitions. The methods are made comparable by alarm limits, which give the same median time to the first false alarm, but also other approaches for comparability are discussed. Results are given on the expected delay time to a correct alarm, the probability of detection of a turning point within a specified time, and the predictive value of an alarm. Copyright © 2005 John Wiley & Sons, Ltd.

Suggested Citation

  • David Bock & Eva Andersson & Marianne Frisén, 2005. "Statistical surveillance of cyclical processes with application to turns in business cycles," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(7), pages 465-490.
    • Handle: RePEc:jof:jforec:v:24:y:2005:i:7:p:465-490
    DOI: 10.1002/for.966
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    References listed on IDEAS

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    Cited by:

    1. Li, Yushu, 2013. "Wavelet based outlier correction for power controlled turning point detection in surveillance systems," Economic Modelling, Elsevier, vol. 30(C), pages 317-321.
    2. Vasyl Golosnoy & Jens Hogrefe, 2013. "Signaling NBER turning points: a sequential approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 438-448, February.
    3. Pettersson, Kjell, 2008. "On curve estimation under order restrictions," Research Reports 2007:15, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    4. Schiöler, Linus & Frisén, Marianne, 2008. "On statistical surveillance of the performance of fund managers," Research Reports 2008:4, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    5. Frisén, Marianne, 2011. "Methods and evaluations for surveillance in industry, business, finance, and public health," Research Reports 2011:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    6. Zhou, Qin & Luo, Yunzhao & Wang, Zhaojun, 2010. "A control chart based on likelihood ratio test for detecting patterned mean and variance shifts," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1634-1645, June.
    7. Golosnoy, Vasyl & Hogrefe, Jens, 2009. "Sequential methodology for signaling business cycle turning points," Kiel Working Papers 1528, Kiel Institute for the World Economy (IfW Kiel).
    8. Bock, David & Andersson, Eva & Frisén, Marianne, 2007. "Similarities and differences between statistical surveillance and certain decision rules in finance," Research Reports 2007:8, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.

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