Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE System
We use data generated by a macroeconomic DSGE model to study the relative benefits of forecast combinations based on forecast-encompassing tests relative to simple uniformly weighted forecast averages across rival models. Assumed rival models are four linear autoregressive specifications, one of them a more sophisticated factor-augmented vector autoregression (FAVAR). The forecaster is assumed not to know the true data-generating DSGE model. The results critically depend on the prediction horizon. While one-step prediction hardly supports test-based combinations, the test-based procedure attains a clear lead at prediction horizons greater than two.
|Date of creation:||May 2010|
|Date of revision:|
|Contact details of provider:|| Postal: Josefstädterstr. 39, A-1080 Vienna, Austria|
Phone: ++43 - (0)1 - 599 91 - 0
Fax: ++43 - (0)1 - 599 91 - 555
Web page: http://www.ihs.ac.at
More information through EDIRC
|Order Information:|| Postal: Institute for Advanced Studies - Library, Josefstädterstr. 39, A-1080 Vienna, Austria|
When requesting a correction, please mention this item's handle: RePEc:ihs:ihsesp:251. 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: (Doris Szoncsitz)
If references are entirely missing, you can add them using this form.