Macro Modelling with Many Models

James Mitchell () and Bache, I.W., Ravazzolo, F., Vahey, S.P.
Authors registered in the RePEc Author Service: Francesco Ravazzolo () and Shaun P. Vahey

NIESR Discussion Papers from National Institute of Economic and Social Research

Abstract: 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.

New Economics Papers: this item is included in nep-cba, nep-dge, nep-for, nep-mac and nep-mon
Date: 2009-08
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Working Paper: Macro modelling with many models (2009)
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Persistent link: http://EconPapers.repec.org/RePEc:nsr:niesrd:337

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