IDEAS home Printed from
   My bibliography  Save this paper

Trend-Cycle Decomposition: Implications from an Exact Structural Identification


  • Mardi Dungey
  • Jan P. A. M. Jacobs
  • Jing Jian
  • Simon van Norden


A well-documented property of the Beveridge-Nelson trend-cycle decomposition is the perfect negative correlation between trend and cycle innovations. We show how this may be consistent with a structural model where trend shocks enter the cycle, or cycle shocks enter the trend and that identification restrictions are necessary to make this structural distinction. A reduced form unrestricted version such as Morley, Nelson and Zivot (2003) is compatible with either option, but cannot distinguish which is relevant. We discuss economic interpretations and implications using US real GDP data. Une caractéristique bien connue de la décomposition Beveridge-Nelson est la corrélation négative parfaite entre les innovations aux cycles et aux tendances. Nous montrons comment cette corrélation est compatible avec des modèles structurels où les chocs aux tendances entrent par les cycles, ou les chocs aux cycles entrent par les tendances et que des restrictions d'identification sont nécessaires pour faire cette distinction structurelle. Une forme réduite sans restriction comme celle de Morley, Nelson et Zivot (2003) est compatible avec les deux options, mais ne peut pas les distinguer. Nous discutons des interprétations économiques et les implications en utilisant des données réelles du PIB américain.

Suggested Citation

  • Mardi Dungey & Jan P. A. M. Jacobs & Jing Jian & Simon van Norden, 2013. "Trend-Cycle Decomposition: Implications from an Exact Structural Identification," CIRANO Working Papers 2013s-23, CIRANO.
  • Handle: RePEc:cir:cirwor:2013s-23

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. Perron, Pierre & Wada, Tatsuma, 2009. "Let's take a break: Trends and cycles in US real GDP," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
    2. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    3. Anderson, Heather M. & Low, Chin Nam & Snyder, Ralph, 2006. "Single source of error state space approach to the Beveridge Nelson decomposition," Economics Letters, Elsevier, vol. 91(1), pages 104-109, April.
    4. Morley, James C., 2002. "A state-space approach to calculating the Beveridge-Nelson decomposition," Economics Letters, Elsevier, vol. 75(1), pages 123-127, March.
    5. Morley, James C., 2011. "The Two Interpretations Of The Beveridge–Nelson Decomposition," Macroeconomic Dynamics, Cambridge University Press, vol. 15(03), pages 419-439, June.
    6. Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
    7. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
    8. Tommaso Proietti, 2006. "Trend-Cycle Decompositions with Correlated Components," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 61-84.
    9. Tara M. Sinclair, 2009. "The Relationships between Permanent and Transitory Movements in U.S. Output and the Unemployment Rate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 529-542, March.
    10. Enzo Weber, 2011. "Analyzing U.S. Output and the Great Moderation by Simultaneous Unobserved Components," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(8), pages 1579-1597, December.
    Full references (including those not matched with items on IDEAS)

    More about this item


    trend-cycle decomposition; data revision; state-space form;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:cir:cirwor:2013s-23. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Webmaster). General contact details of provider: .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.