A Trend-Cycle(-Season) Filter
Matthias Mohr ()
Econometrics from University Library of Munich, Germany
This paper proposes a new univariate method to decompose a time series into a trend, a cyclical and a seasonal component: the Trend-Cycle filter (TC filter) and its extension, the Trend-Cycle-Season filter (TCS filter). They can be regarded as extensions of the Hodrick-Prescott filter (HP filter). In particular, the stochastic model of the HP filter is extended by explicit models for the cyclical and the seasonal component. The introduction of a stochastic cycle improves the filter in three respects: first, trend and cyclical components are more consistent with the underlying theoretical model of the filter. Second, the end-of- sample reliability of the trend estimates and the cyclical component is improved compared to the HP filter since the pro-cyclical bias in end- of-sample trend estimates is virtually removed. Finally, structural breaks in the original time series can be easily accounted for.
Keywords: economic cycles; time series; filtering; trend-cycle decomposition; seasonality (search for similar items in EconPapers)
JEL-codes: C13 C22 E32 (search for similar items in EconPapers)
Pages: 44 pages
New Economics Papers: this item is included in nep-dge, nep-ecm, nep-ets and nep-mac
Note: Type of Document - pdf; pages: 44
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0508004
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