IDEAS home Printed from https://ideas.repec.org/a/nos/voprec/y2016id264.html
   My bibliography  Save this article

DSGE-based forecasting: What should our perspective be?

Author

Listed:
  • O. Malakhovskaya

Abstract

The article compares the accuracy of point forecasts made with a structural dynamic stochastic general equilibrium model (DSGE) to those made with vector autoregressions estimated by OLS (VAR) and by Bayesian methods (BVAR). The main question addressed in the article is whether DSGE-based forecasts are as accurate as non-structural model ones. The comparison is made on the ground of mean squared forecast errors. The results show that the forecasting ability of the DSGE model is in general inferior to that of the BVAR. However, the difference is not critical. Moreover, for some variables and forecasting horizons, the DSGE model produces the forecast with the lowest error among all three models in question.

Suggested Citation

  • O. Malakhovskaya, 2016. "DSGE-based forecasting: What should our perspective be?," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 12.
    • Handle: RePEc:nos:voprec:y:2016:id:264
    DOI: 10.32609/0042-8736-2016-12-129-146
    as

    Download full text from publisher

    File URL: https://www.vopreco.ru/jour/article/viewFile/264/264
    Download Restriction: no
    File URL: https://libkey.io/10.32609/0042-8736-2016-12-129-146?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:nos:voprec:y:2016:id:264. 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: NEICON (email available below). General contact details of provider: https://www.vopreco.ru .

    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.