IDEAS home Printed from https://ideas.repec.org/a/cup/macdyn/v26y2022i2p394-418_4.html
   My bibliography  Save this article

Trend-Cycle Decompositions Of Real Gdp Revisited: Classical And Bayesian Perspectives On An Unsolved Puzzle

Author

Listed:
  • Kim, Chang-Jin
  • Kim, Jaeho

Abstract

While Perron and Wada (2009) maximum likelihood estimation approach suggests that postwar US real GDP follows a trend stationary process (TSP), our Bayesian approach based on the same model and the same sample suggests that it follows a difference stationary process (DSP). We first show that the results based on the approach should be interpreted with caution, as they are relatively more subject to the ‘pile-up problem’ than those based on the Bayesian approach. We then directly estimate and compare the two competing TSP and DSP models of real GDP within the Bayesian framework. Our empirical results suggest that a DSP model is preferred to a TSP model both in terms of in-sample fits and out-of-sample forecasts.

Suggested Citation

  • Kim, Chang-Jin & Kim, Jaeho, 2022. "Trend-Cycle Decompositions Of Real Gdp Revisited: Classical And Bayesian Perspectives On An Unsolved Puzzle," Macroeconomic Dynamics, Cambridge University Press, vol. 26(2), pages 394-418, March.
    • Handle: RePEc:cup:macdyn:v:26:y:2022:i:2:p:394-418_4
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1365100520000218/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    More about this item

    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:cup:macdyn:v:26:y:2022:i:2:p:394-418_4. 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/mdy .

    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.