IDEAS home Printed from https://ideas.repec.org/p/kud/kuiedp/8924.html
   My bibliography  Save this paper

Bayesian Analysis - Applications to Danish Data

Author

Listed:
  • Y. P. Gupta

    (Institute of Economics, University of Copenhagen)

Abstract

The principal distinction between classical inference and Bayesian inference lies in terms of the definitions of probability. The classical inference is based on the notion of 'objective' probability, i.e. probability with reference to repetitive phenomena or relative frequencies in repeated situations. On the other hand the Bayesian inference involves the notion of 'subjective' probability, i.e. individualistic assessment of 'rational' behaviour. Bayes' principle provides a convenient way of combining pre-sample (prior) information with observed sample information leading to post sample probabilities. The object of the paper is to illustrate the use of Bayes' principle in econometric modelling of an economy. Two different empirical examples are considered, and comparative advantages of Bayes' analysis in relation to classical approach are discussed.

Suggested Citation

  • Y. P. Gupta, 1989. "Bayesian Analysis - Applications to Danish Data," Discussion Papers 89-24, University of Copenhagen. Department of Economics.
  • Handle: RePEc:kud:kuiedp:8924
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:kud:kuiedp:8924. 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: Thomas Hoffmann (email available below). General contact details of provider: https://edirc.repec.org/data/okokudk.html .

    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.