Filtering permanent cycles with complex unit roots
Donald S. Allen
No 1997-001, Working Papers from Federal Reserve Bank of St. Louis
Abstract:
Separating cyclical movement from trend growth at seasonal and business cycle frequencies is important to macroeconomic research. At business cycle frequencies, time trends, first differences and the more recent Hodrick-Prescott (HP) filter are used to separate trends from cycles. At seasonal frequencies, ad-hoc methods like the Census Bureau's X-11 seasonal filter are applied. This paper reviews the criteria for permanent cycles in systems characterized by difference equations and looks at the effect of filtering data which exhibit permanent cyclicality. Second order moving averages with complex unit roots at appropriate frequencies are used to filter data at seasonal and business cycle frequencies; and spectral analysis of the filtered data is used to illustrate the effect. The X-11 seasonal filter and the HP filter are also discussed in this framework. As with any filter that is applied to data where the data generating process is unknown, filtering for specific frequencies can induce cycles at harmonics of the fundamental frequency.
Keywords: Business cycles; Seasonal variations (Economics) (search for similar items in EconPapers)
Date: 1997
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://research.stlouisfed.org/wp/more/1997-001 (application/pdf)
http://research.stlouisfed.org/wp/1997/97-001.pdf
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:fip:fedlwp:1997-001
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in Working Papers from Federal Reserve Bank of St. Louis Contact information at EDIRC.
Bibliographic data for series maintained by Anna Oates ().