 General Model-based Filters for Extracting Cycles and Trends in Economic Time SeriesAndrew Harvey and Thomas Trimbur Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge Abstract: A new class of model-based filters for extracting trends and cycles in economic time series is presented. These low pass and band pass filters are derived in a mutually consistent manner as the joint solution to a signal extraction problem in an unobserved components model. The resulting trends and cycles are computed in finite samples using a Kalman filter and associated smoother. The filters form a class which is a generalisation of the class of Butterworth filters, widely used in engineering. They are very flexible and have the important property of allowing relatively smooth cycles to be extracted from economic time series. Perfectly sharp, or ideal, band pass filters emerge as a special case. Applying the method to a quarterly series on US investment shows a clearly defined cycle currently at the peak of a boom. Keywords: band pass filter; Butterworth filter; ideal filter; Kalman filter; signal extraction; unobserved components (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:0113 Access Statistics for this paper More papers in Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge |
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