A Trend-Cycle(-Season) Filter
AbstractThis 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.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0508004.
Length: 44 pages
Date of creation: 03 Aug 2005
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economic cycles; time series; filtering; trend-cycle decomposition; seasonality;
Other versions of this item:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-08-13 (All new papers)
- NEP-DGE-2005-08-13 (Dynamic General Equilibrium)
- NEP-ECM-2005-08-13 (Econometrics)
- NEP-ETS-2005-08-13 (Econometric Time Series)
- NEP-MAC-2005-08-13 (Macroeconomics)
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