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.
Year of publication: |
2009-08
|
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Authors: | Mitchell, James ; Bache, I.W., Ravazzolo, F., Vahey, S.P. |
Institutions: | National Institute of Economic and Social Research |
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