Signal Extraction in Continuous Time and the Generalized Hodrick- Prescott Filter

Roberto Iannaccone and Edoardo Otranto
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Roberto Iannaccone: Istat

Econometrics from University Library of Munich, Germany

Abstract: A widely used filter to extract a signal in a time series, in particular in the business cycle analysis, is the Hodrick-Prescott filter. The model that underlies the filter considers the data series as the sum of two unobserved component (signal and non signal) and a smoothing parameter which for quarterly series is set to a specified value. This paper proposes a generalization of the Hodrick-Prescott filter to a continuous time support, using the well-established relationship between cubic splines and state-space models. The spline formulation of the filter leads to a state space model with several practical advantages: first, the smoothing parameter can be either pre-specified or estimated as the other parameters in the model; second, the unobserved components can be modelled by the addition of particular ARIMA structures; lastly the model is capable of working in the presence of missing values or for irregular surveys. Monte Carlo experiments support these considerations.

Keywords: smoothing parameter; cubic spline; state-space model; irregular surveys. (search for similar items in EconPapers)
JEL-codes: C1 C3 C5 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2003-11-07
New Economics Papers: this item is included in nep-dge, nep-ecm and nep-ets
Note: Type of Document - PDF; pages: 20. PDF document submitted via ftp
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0311002

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