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An Investigation of the Cycle Extraction Properties of Several Bandpass Filters Used to Identify Business Cycles

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Abstract

The purpose of this article is to investigate the ability of bandpass filters commonly used in economics to extract a known periodicity. The specific bandpass filters investigated include a Discrete Fourier Transform (DFT) filter, together with those proposed by Hodrick and Prescott (1997) and Baxter and King (1999). Our focus on the cycle extraction properties of these filters reflects the lack of attention that has been given to this issue in the literature, when compared, for example, to studies of the trend removal properties of some of these filters. The artificial data series we use are designed so that one periodicity deliberately falls within the passband while another falls outside. The objective of a filter is to admit the ‘bandpass’ periodicity while excluding the periodicity that falls outside the passband range. We find that the DFT filter has the best extraction properties. The filtered data series produced by both the Hodrick-Prescott and Baxter-King filters are found to admit low frequency components that should have been excluded.

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  • Melvin J. Hinich & John Foster & Philip Wild, 2008. "An Investigation of the Cycle Extraction Properties of Several Bandpass Filters Used to Identify Business Cycles," Discussion Papers Series 358, School of Economics, University of Queensland, Australia.
  • Handle: RePEc:qld:uq2004:358
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    File URL: http://www.uq.edu.au/economics/abstract/358.pdf
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    1. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    2. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    3. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
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    1. Melvin J. Hinich & John Foster & Philip Wild, 2008. "Discrete Fourier Transform Filters as Business Cycle Extraction Tools: An Investigation of Cycle Extraction Properties and Applicability of ‘Gibbs’ Effect," Discussion Papers Series 357, School of Economics, University of Queensland, Australia.

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