Forecasting Inflation Using Dynamic Model Averaging
We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coeÃ‚Â¢ cients to change over time, but also allow for the entire forecasting model to change over time. We find that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coefficient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.
(This abstract was borrowed from another version of this item.)
Volume (Year): 53 (2012)
Issue (Month): 3 (08)
|Contact details of provider:|| Postal: |
Phone: (215) 898-8487
Fax: (215) 573-2057
Web page: http://www.econ.upenn.edu/ier
More information through EDIRC
|Order Information:|| Web: http://www.blackwellpublishing.com/subs.asp?ref=0020-6598 Email: |
When requesting a correction, please mention this item's handle: RePEc:wly:iecrev:v:53:y:2012:i:3:p:867-886. 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: (Wiley-Blackwell Digital Licensing)or ()
If references are entirely missing, you can add them using this form.