IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-01aa0015.html
   My bibliography  Save this article

Prior Information: The Mixed Prediction Approach

Author

Listed:
  • Harry Haupt

    (Department of Econometrics, University of Regensburg, Germany)

  • Walter Oberhofer

    (Department of Econometrics, University of Regensburg, Germany)

Abstract

This paper addresses the combination of incomplete prior and sample information. In difference to the mixed estimation approach developed by H. Theil and A.S. Goldberger, dealing with prior knowledge of regression coefficients, we consider prior information on future observations of the dependent variable(s). This prior information could be given in the form of experts' expectations, or from estimations and/or projections of additional models. A framework for the incorporation of this prior knowledge in least squares estimation and prediction is developed. The approach is particularly useful when only aggregated information on the endogenous variables is available, as is often the case with regional level data.

Suggested Citation

  • Harry Haupt & Walter Oberhofer, 2001. "Prior Information: The Mixed Prediction Approach," Economics Bulletin, AccessEcon, vol. 28(12), pages 1.
  • Handle: RePEc:ebl:ecbull:eb-01aa0015
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/pubs/EB/2001/Volume28/EB-01AA0015A.pdf
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

    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:ebl:ecbull:eb-01aa0015. 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: John P. Conley (email available below). General contact details of provider: .

    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.