IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v150y2025ics0264999325001270.html
   My bibliography  Save this article

A Hodrick–Prescott filter with automatically selected breaks

Author

Listed:
  • Maranzano, Paolo
  • Pelagatti, Matteo

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 breaks. We propose a modification of the Hodrick–Prescott filter that contemplates breaks and automatically selects the time points in which the breaks occur. We provide efficient implementation of the new filter in an R package. We use our new filter to assess what Italian labour market reforms impacted employment in different age groups.

Suggested Citation

  • Maranzano, Paolo & Pelagatti, Matteo, 2025. "A Hodrick–Prescott filter with automatically selected breaks," Economic Modelling, Elsevier, vol. 150(C).
  • Handle: RePEc:eee:ecmode:v:150:y:2025:i:c:s0264999325001270
    DOI: 10.1016/j.econmod.2025.107132
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999325001270
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2025.107132?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Trend; State–space form; Unobserved component model; Structural change; LASSO; Business cycle; Employment;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:150:y:2025:i:c:s0264999325001270. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.