The miracle of the Septuagint and the promise of data mining in economics
This paper argues that the sometimes-conflicting results of a modern revisionist literature on data mining in econometrics reflect different approaches to solving the central problem of model uncertainty in a science of non-experimental data. The literature has entered an exciting phase with theoretical development, methodological reflection, considerable technological strides on the computing front and interesting empirical applications providing momentum for this branch of econometrics. The organising principle for this discussion of data mining is a philosophical spectrum that sorts the various econometric traditions according to their epistemological assumptions (about the underlying data-generating-process DGP) starting with nihilism at one end and reaching claims of encompassing the DGP at the other end; call it the DGP-spectrum. In the course of exploring this spectrum the reader will encounter various Bayesian, specific-to-general (S-G) as well general-to-specific (G-S) methods. To set the stage for this exploration the paper starts with a description of data mining, its potential risks and a short section on potential institutional safeguards to these problems.
|Date of creation:||2006|
|Contact details of provider:|| Postal: Private Bag X1, 7602 Matieland|
Fax: +27 (0)21-808 2409
Web page: https://www.ekon.sun.ac.za
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:sza:wpaper:wpapers29. 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: (Melt van Schoor)
If references are entirely missing, you can add them using this form.