Data Mining: A Reconsideration
Before condemning data mining one should distinguish between objective and biased data mining. The former is commendable. Even biased data mining is appropriate when used to illustrate and not to test hypotheses. In the context of testing, the problem with biased data mining arises not from the fitting of many regression, but from inadequate reporting of results. The trend towards reporting the results of more alternative specifications, and thus addressing the fragility problem, should be encouraged. To do that the incentives that economists face should be changed.
|Date of creation:||09 Jan 2003|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (530) 752-0741
Fax: (530) 752-9382
Web page: http://www.econ.ucdavis.edu
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:cda:wpaper:97-15. 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: (Scott Dyer)
If references are entirely missing, you can add them using this form.