A Hodrick-Prescott filter with automatically selected jumps

Paolo Maranzano and Matteo Pelagatti
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Paolo Maranzano: Department of Economics, Management and Statistics, University of Milano-Bicocca and Fondazione Eni Enrico Mattei

No 2024.18, Working Papers from Fondazione Eni Enrico Mattei

Abstract: The Hodrick-Prescott filter is a popular tool in macroeconomics for decomposing a time series into a smooth trend and a business cycle component. The last few years have witnessed global events, such as the Global Financial Crisis, the COVID-19 pandemic, and the war in Ukraine, that have had abrupt structural impacts on many economic time series. Moreover, new regulations and policy changes generally lead to similar behaviours. Thus, those events should be absorbed by the trend component of the trend-cycle decomposition, but the Hodrick-Prescott filter does not allow for jumps. We propose a modification of the Hodrick-Prescott filter that contemplates jumps and automatically selects the time points in which the jumps occur. We provide an efficient implementation of the new filter in an R package. We use our modified filter to assess what Italian labour market reforms impacted employment in different age groups.

Keywords: Trend; State-space form; Unobserved component model; Structural change; LASSO; Business cycle; Employment (search for similar items in EconPapers)
JEL-codes: C22 C63 E32 J21 (search for similar items in EconPapers)
Date: 2024-07
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-lma
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Working Paper: A Hodrick-Prescott filter with automatically selected jumps (2024)
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