IDEAS home Printed from https://ideas.repec.org/a/pal/buseco/v41y2006i1p37-44.html
   My bibliography  Save this article

Using Neural Nets to Forecast the Unemployment Rate

Author

Listed:
  • Rolando F Peláez

Abstract

The paper identifies leading indicators of the unemployment rate. Forecasts of the unemployment rate are obtained with an econometric model, and with an artificial neural network. Both model-based forecasts outperform forecasts from the Survey of Professional Forecasters. This is important because the unemployment rate forecast from the Survey of Professional Forecasters has outperformed other forecasts based on time-series models to the point that some observers view it as a proxy for a full-information forecast.Business Economics (2006) 41, 37–44; doi:10.2145/20060105

Suggested Citation

  • Rolando F Peláez, 2006. "Using Neural Nets to Forecast the Unemployment Rate," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 41(1), pages 37-44, January.
  • Handle: RePEc:pal:buseco:v:41:y:2006:i:1:p:37-44
    as

    Download full text from publisher

    File URL: http://www.palgrave-journals.com/be/journal/v41/n1/pdf/be20065a.pdf
    File Function: Link to full text PDF
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: http://www.palgrave-journals.com/be/journal/v41/n1/full/be20065a.html
    File Function: Link to full text HTML
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:pal:buseco:v:41:y:2006:i:1:p:37-44. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    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.