IDEAS home Printed from https://ideas.repec.org/a/fep/journl/v20y2007i2p166-176.html
   My bibliography  Save this article

Using All Observations when Forecasting under Structural Breaks

Author

Listed:
  • Stanislav Anatolyev

    () (New Economic School, Moscow)

  • Victor Kitov

    () (Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow)

Abstract

We extend the idea of the trade-off window approach by Pesaran and Timmermann (2007) of using observations preceding the last structural break to estimate model parameters for the purpose of forecasting. Our weighted least squares method utilizes information in all observations but with weights varying from one to another interval between breaks. This leads to a smaller mean squared prediction error which is illustrated by simulations. The proposed procedure is computationally simple having a convenient associated optimization program. We also describe and evaluate a cross-validation analog of the proposed method.

Suggested Citation

  • Stanislav Anatolyev & Victor Kitov, 2007. "Using All Observations when Forecasting under Structural Breaks," Finnish Economic Papers, Finnish Economic Association, vol. 20(2), pages 166-176, Autumn.
  • Handle: RePEc:fep:journl:v:20:y:2007:i:2:p:166-176
    as

    Download full text from publisher

    File URL: http://www.taloustieteellinenyhdistys.fi/images/stories/fep/fep22007_anatolyev_kitov.pdf
    Download Restriction: no

    Citations

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


    Cited by:

    1. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:fep:journl:v:20:y:2007:i:2:p:166-176. 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: (Editorial Secretary). General contact details of provider: http://edirc.repec.org/data/talouea.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.