Addressing Collinearity Among Competing Econometric Forecasts: Regression Based Forecast Combination Using Model Selection
Based on Monte Carlo simulations using both stationary and nonstationary data, a model selection approach which uses the SIC to select a "best" group of forecasts in the context of forecast combination regressions dominates a number of other techniques, including the standard t-statistic approach which is commonly used in practical applications.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" 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.
|Date of creation:||1996|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://econ.la.psu.edu/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:fth:pensta:4-96-5. 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: (Thomas Krichel)
If references are entirely missing, you can add them using this form.