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Identifying the Cycle of a Macroeconomic Time-Series Using Fuzzy Filtering

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Author Info
David E. Giles () (Department of Economics, University of Victoria)
Chad N. Stroomer () (Department of Economics, University of Victoria)

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Abstract

This paper presents a new method for extracting the cycle from an economic time series. This method uses the fuzzy c-means clustering algorithm, drawn from the pattern recognition literature, to identify groups of observations. The time series is modeled over each of these sub-samples, and the results are combined using the “degrees of membership” for each data-point with each cluster. The result is a totally flexible model that readily captures complex non-linearities in the data. This type of “fuzzy regression” analysis has been shown by Giles and Draeseke (2003) to be highly effective in a broad range of situations with economic data. The fuzzy filter that we develop here is compared with the well-known Hodrick-Prescott (HP) filter in a Monte Carlo experiment, and the new filter is found to perform as well as, or better than, the HP filter. The advantage of the fuzzy filter is especially pronounced when the data have a deterministic, rather than stochastic, trend. Applications with real time-series illustrate the different conclusions that can emerge when the fuzzy regression filter and the HP filter are each applied to extract the cycle.

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Publisher Info
Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0406.

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Length: 24 pages
Date of creation: 29 Dec 2004
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Handle: RePEc:vic:vicewp:0406

Note: ISSN 1485-6441
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Postal: PO Box 1700, STN CSC, Victoria, BC, Canada, V8W 2Y2
Phone: (250)721-8540
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Web page: http://web.uvic.ca/econ
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Related research
Keywords: Fuzzy filter fuzzy clustering business cycle trend extraction HP filter

Other versions of this item:

Find related papers by JEL classification:
C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Other
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    Other versions:
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    Other versions:
  6. Robert J. Hodrick & Edward Prescott, 1981. "Post-War U.S. Business Cycles: An Empirical Investigation," Discussion Papers 451, Northwestern University, Center for Mathematical Studies in Economics and Management Science. [Downloadable!]
    Other versions:
  7. David K. Backus & Patrick J. Kehoe, 1992. "International Evidence on the Historical Properties of Business Cycles," Working Papers 92-5, New York University, Leonard N. Stern School of Business, Department of Economics.
    Other versions:
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  12. Schlicht, Ekkehart, 2004. "Estimating the Smoothing Parameter in the So-Called Hodrick-Prescott Filter," IZA Discussion Papers 1054, Institute for the Study of Labor (IZA). [Downloadable!]
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  14. David E. A. Giles & Robert Draeseke, 2001. "Econometric Modelling based on Pattern recognition via the Fuzzy c-Means Clustering Algorithm," Econometrics Working Papers 0101, Department of Economics, University of Victoria. [Downloadable!]
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  22. Giles, David E A, 1997. "Testing for Asymmetry in the Measured and Underground Business Cycles in New Zealand," The Economic Record, The Economic Society of Australia, vol. 73(222), pages 225-32, September.
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Hui Feng & David E. Giles, 2007. "Bayesian Fuzzy Regression Analysis and Model Selection: Theory and Evidence," Econometrics Working Papers 0710, Department of Economics, University of Victoria. [Downloadable!]
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