Identifying the Cycle of a Macroeconomic Time-Series Using Fuzzy Filtering
AbstractThis 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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Bibliographic InfoPaper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0406.
Length: 24 pages
Date of creation: 29 Dec 2004
Date of revision:
Note: ISSN 1485-6441
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Fuzzy filter; fuzzy clustering; business cycle; trend extraction; HP filter;
Find related papers by JEL classification:
- C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-01-02 (All new papers)
- NEP-CMP-2005-01-02 (Computational Economics)
- NEP-ECM-2005-01-02 (Econometrics)
- NEP-ETS-2005-01-02 (Econometric Time Series)
- NEP-MAC-2005-01-02 (Macroeconomics)
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