Advanced Search
MyIDEAS: Login

Nonparametric Forecasting of the Manufacturing Output Growth with Firm-level Survey Data

Contents:

Author Info

  • Gérard Biau

    ()

  • Olivier Biau

    ()

  • Laurent Rouvière

    ()

Registered author(s):

    Abstract

    A large majority of summary indicators derived from the individual responses to qualitative Business Tendency Surveys (which are mostly three-modality questions) result from standard aggregation and quantification methods. This is typically the case for the indicators called balances of opinion, which are currently used in short term analysis and considered by forecasters as explanatory variables in many models. In the present paper, we discuss a new statistical approach to forecast the manufacturing growth from firm-survey responses. We base our predictions on a forecasting algorithm inspired by the random forest regression method, which is known to enjoy good prediction properties. Our algorithm exploits the heterogeneity of the survey responses, works fast, is robust to noise and allows for the treatment of missing values. Starting from a real application on a French dataset related to the manufacturing sector, this procedure appears as a competitive method compared with traditional algorithms.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://dx.doi.org/10.1787/jbcma-v2007-art15-en
    Download Restriction: Full text available to READ online. PDF download available to OECD iLibrary subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by OECD Publishing,CIRET in its journal Journal of Business Cycle Measurement and Analysis.

    Volume (Year): 2007 (2007)
    Issue (Month): 3 ()
    Pages: 317-331

    as in new window
    Handle: RePEc:oec:stdkaa:5kzdnhzpzq8w

    Contact details of provider:
    Postal: 2 rue Andre Pascal, 75775 Paris Cedex 16
    Phone: 33-(0)-1-45 24 82 00
    Fax: 33-(0)-1-45 24 85 00
    Email:
    Web page: http://www.oecd.org
    More information through EDIRC

    Related research

    Keywords: Business Tendency Surveys; balance of opinion; short-term forecasting; manufactured production; k-nearest neighbor regression; random forecasts;

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:oec:stdkaa:5kzdnhzpzq8w. 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: ().

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 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.