IDEAS home Printed from https://ideas.repec.org/p/ctl/louvir/2002027.html
   My bibliography  Save this paper

Two Alternative Approaches to Modelling the Nonlinear Dynamics of the Composite Economic Indicator

Author

Listed:
  • Konstantin, KHOLODILIN

    (UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES))

Abstract

The analysis and prediction of the short-run economic dynamics, or the evolution of the business cycle, often require a construction of the composite economic indicator (CEI). This indicator may be endowed with nonlinear dynamics to take care of the possible asymmetries between different phases of the business cycle. This paper suggests using the smooth transition autoregression to model the CEI. The performance of this model is compared to the already classical CEI with regime switching. Both models turn out to produce statistically equally good results in terms of forecasting the business cycle turning points.

Suggested Citation

  • Konstantin, KHOLODILIN, 2002. "Two Alternative Approaches to Modelling the Nonlinear Dynamics of the Composite Economic Indicator," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2002027, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  • Handle: RePEc:ctl:louvir:2002027
    as

    Download full text from publisher

    File URL: http://sites.uclouvain.be/econ/DP/IRES/2002-27.pdf
    Download Restriction: no

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kholodilin Konstantin A., 2005. "Forecasting the German Cyclical Turning Points: Dynamic Bi-Factor Model with Markov Switching," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(6), pages 653-674, December.
    2. Konstantin A. Kholodilin, 2006. "Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies," Discussion Papers of DIW Berlin 554, DIW Berlin, German Institute for Economic Research.
    3. Konstantin A. Kholodilin, 2005. "Forecasting the Turns of German Business Cycle: Dynamic Bi-factor Model with Markov Switching," Discussion Papers of DIW Berlin 494, DIW Berlin, German Institute for Economic Research.
    4. Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
    5. Konstantin A., Kholodilin, 2003. "Identifying and Forecasting the Turns of the Japanese Business Cycle," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2003008, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    6. Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Post-Print hal-01159200, HAL.

    More about this item

    Keywords

    composite economic indicator; Markov switching; smooth transition autoregression; turning points; NBER dating; forecasting;

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    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:ctl:louvir:2002027. 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: (Virginie LEBLANC). General contact details of provider: http://edirc.repec.org/data/iruclbe.html .

    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 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.

    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.