A trend-cycle(-season) filter

Matthias Mohr

No 499, Working Paper Series from European Central Bank

Abstract: 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. JEL Classification: C13, C22, E32

Keywords: economic cycles; filtering; seasonality; time series; trend-cycle decomposition (search for similar items in EconPapers)
Date: 2005-07
Note: 79802
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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