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A Frequency Selective Filter for Short-Length Time Series

An effective and easy-to-implement frequency filter is designed by convolving a Hamming window with the ideal rectangular filter response function. Three other filters (Hodrick-Prescott, Baxter-King, and Christiano-Fitzgerald) are critically reviewed. The behavior of the Hamming-windowed filter is compared to the others through their frequency responses and by applying them both to an artificial, known-structure series and the Euro zone GDP quarterly series. As for the Hodrick-Prescott filter, a bandpass version of it is used. The Hamming-windowed filter has almost no leakage and is thus much better than the others at eliminating high frequency components, while the response in the passband is significantly flatter. Moreover, its behavior at low frequencies ensures a better removal of undesired long-term components. Those improvements are particularly evident when working with short-length time series, which are common in Macroeconomics. The proposed filter is stationary, symmetric, uses all the information contained in the raw data and stationarizes series integrated up to order two. It thus proves to be a good candidate for extracting frequency-defined business cycle components.

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Paper provided by Observatoire Francais des Conjonctures Economiques (OFCE) in its series Documents de Travail de l'OFCE with number 2004-05.

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Date of creation: 2004
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Handle: RePEc:fce:doctra:0405
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  1. King, R.G. & Rebelo, S.T., 1989. "Low Frequency Filtering And Real Business Cycles," RCER Working Papers 205, University of Rochester - Center for Economic Research (RCER).
  2. Andrew Harvey, 2004. "Trend estimation, signal-noise ratios and the frequency of observations," Econometric Society 2004 Australasian Meetings 343, Econometric Society.
  3. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, 05.
  4. Uhlig, H.F.H.V.S. & Ravn, M., 1997. "On Adjusting the H-P Filter for the Frequency of Observations," Discussion Paper 1997-50, Tilburg University, Center for Economic Research.
  5. Harvey, A.C. & Trimbur, T.M., 2001. "General Model-based Filters for Extracting Cycles and Trends in Economic Time Series," Cambridge Working Papers in Economics 0113, Faculty of Economics, University of Cambridge.
  6. Christian J. Murray, 2003. "Cyclical Properties of Baxter-King Filtered Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 472-476, May.
  7. Gomez, Victor, 2001. "The Use of Butterworth Filters for Trend and Cycle Estimation in Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 365-73, July.
  8. Luca Benati, 2001. "Band-pass filtering, cointegration, and business cycle analysis," Bank of England working papers 142, Bank of England.
  9. Haldane, Andrew & Quah, Danny, 1999. "UK Phillips curves and monetary policy," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 259-278, October.
  10. James H. Stock & Mark W. Watson, 1998. "Business Cycle Fluctuations in U.S. Macroeconomic Time Series," NBER Working Papers 6528, National Bureau of Economic Research, Inc.
  11. 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.
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