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Extracting business cycle fluctuations: what do time series filters really do?

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  • Arturo Estrella

Abstract

Various methods are available to extract the "business cycle component" of a given time series variable. These methods may be derived as solutions to frequency extraction or signal extraction problems and differ in both their handling of trends and noise and their assumptions about the ideal time-series properties of a business cycle component. The filters are frequently illustrated by application to white noise, but applications to other processes may have very different and possibly unintended effects. This paper examines several frequently used filters as they apply to a range of dynamic process specifications and derives some guidelines for the use of such techniques.

Suggested Citation

  • Arturo Estrella, 2007. "Extracting business cycle fluctuations: what do time series filters really do?," Staff Reports 289, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednsr:289
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    References listed on IDEAS

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    Cited by:

    1. Pu Chen & Willi Semmler, 2018. "Short and Long Effects of Productivity on Unemployment," Open Economies Review, Springer, vol. 29(4), pages 853-878, September.
    2. Ladislava Issever Grochová & Petr Rozmahel, 2015. "On the Ideality of Filtering Techniques in the Business Cycle Analysis Under Conditions of European Economy," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(3), pages 915-926.
    3. He, Dong & Liao, Wei & Wu, Tommy, 2015. "Hong Kong's growth synchronization with China and the US: A trend and cycle analysis," Journal of Asian Economics, Elsevier, vol. 40(C), pages 10-28.
    4. Hangyong Lee and Jin Lee, 2019. "Inflation Co-Movement in the ASEAN Countries," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 44(4), pages 135-152, December.

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    Keywords

    Business cycles; time series analysis;

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