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Monitoring cyclical processes. A non-parametric approach

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  • E. Andersson

Abstract

Forecasting the turning points in business cycles is important to economic and political decisions. Time series of business indicators often exhibit cycles that cannot easily be modelled with a parametric function. This article presents a method for monitoring time-series with cycles in order to detect the turning points. A non-parametric estimation procedure that uses only monotonicity restrictions is used. The methodology of statistical surveillance is used for developing a system for early warnings of cycle turning points in monthly data. In monitoring, the inference situation is one of repeated decisions. Measurements of the performance of a method of surveillance are, for example, average run length and expected delay to a correct alarm. The properties of the proposed monitoring system are evaluated by means of a simulation study. The false alarms are controlled by a fixed median run length to the first false alarm. Results are given on the median delay time to a correct alarm for two situations: a peak after two and three years respectively .

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  • E. Andersson, 2002. "Monitoring cyclical processes. A non-parametric approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(7), pages 973-990.
    • Handle: RePEc:taf:japsta:v:29:y:2002:i:7:p:973-990
    DOI: 10.1080/0266476022000006685
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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. Marianne Frisén, 2014. "Spatial outbreak detection based on inference principles for multivariate surveillance," IISE Transactions, Taylor & Francis Journals, vol. 46(8), pages 759-769, August.
    3. Christian Sonesson, 2003. "Evaluations of some Exponentially Weighted Moving Average methods," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1115-1133.
    4. Michael Berlemann & Julia Freese & Sven Knoth, 2012. "Eyes Wide Shut? The U.S. House Market Bubble through the Lense of Statistical Process Control," CESifo Working Paper Series 3962, CESifo.
    5. 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.
    6. Marianne Frisen & Eva Andersson & Linus Schioler, 2010. "Evaluation of multivariate surveillance," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(12), pages 2089-2100.
    7. 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.
    8. Marianne Frisén, 2003. "Statistical Surveillance. Optimality and Methods," International Statistical Review, International Statistical Institute, vol. 71(2), pages 403-434, August.
    9. Frisén, Marianne, 2008. "Introduction to financial surveillance," Research Reports 2008:1, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    10. Bock, David, 2007. "Consequences of using the probability of a false alarm as the false alarm measure," Research Reports 2007:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    11. Frisén, Marianne & Andersson, Eva, 2008. "Semiparametric surveillance of outbreaks," Research Reports 2007:11, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    12. Andersson, E., 2005. "On-line detection of turning points using non-parametric surveillance: The effect of the growth after the turn," Statistics & Probability Letters, Elsevier, vol. 73(4), pages 433-439, July.
    13. Frisén, Marianne & Andersson, Eva & Pettersson, Kjell, 2008. "Semiparametric estimation of outbreak regression," Research Reports 2007:13, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    14. David Bock, 2008. "Aspects on the control of false alarms in statistical surveillance and the impact on the return of financial decision systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(2), pages 213-227.
    15. Bock, David & Andersson, Eva & Frisén, Marianne, 2007. "Statistical Surveillance of Epidemics: Peak Detection of Influenza in Sweden," Research Reports 2007:6, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    16. 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.
    17. 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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