IDEAS home Printed from https://ideas.repec.org/a/kea/keappr/ker-20060630-22-1-05.html
   My bibliography  Save this article

Fi-break Model of US Inflation Rate: Long-memory, Level Shifts, or Both?

Author

Listed:
  • Namwon Hyung

    (University of Seoul)

  • Philip Hans Franses

    (Econometric Institute Erasmus University Rotterdam)

Abstract

This paper presents a new time series model, called the FI-BREAK model, which is used to describe US inflation, and incorporates long moemory and occasional level shifts at a priori unknown locations. It is demonstrated that, even in the presence of such level shifts, the long memory parameter of the FI-BREAK model can be estimated reasonably accurately. For US inflaction, it is found that the proposed mode's in-sample fit and out-of-sample forecasts are superior over those of single-feature models with long memory or level shifts.

Suggested Citation

  • Namwon Hyung & Philip Hans Franses, 2006. "Fi-break Model of US Inflation Rate: Long-memory, Level Shifts, or Both?," Korean Economic Review, Korean Economic Association, vol. 22, pages 83-97.
  • Handle: RePEc:kea:keappr:ker-20060630-22-1-05
    as

    Download full text from publisher

    File URL: http://keapaper.kea.ne.kr/RePEc/kea/keappr/KER-20060630-22-1-05.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    FI-BREAK; long memory; level shifts; inflation;
    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

    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:kea:keappr:ker-20060630-22-1-05. 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: KEA (email available below). General contact details of provider: https://edirc.repec.org/data/keaaaea.html .

    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.