Macro modelling with many models
We argue that the next generation of macro modellers at Inflation Targeting central banks should adapt a methodology from the weather forecasting literature known as `ensemble modelling'. In this approach, uncertainty about model specifications (e.g., initial conditions, parameters, and boundary conditions) is explicitly accounted for by constructing ensemble predictive densities from a large number of component models. The components allow the modeller to explore a wide range of uncertainties; and the resulting ensemble `integrates out' these uncertainties using time-varying weights on the components. We provide two examples of this modelling strategy: (i) forecasting inflation with a disaggregate ensemble; and (ii) forecasting inflation with an ensemble DSGE.
|Date of creation:||17 Aug 2009|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +47 22 31 60 00
Fax: +47 22 41 31 05
Web page: http://www.norges-bank.no/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:bno:worpap:2009_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: ()
If references are entirely missing, you can add them using this form.