Macro Modelling with Many Models

Shaun P. Vahey, Melbourne Business School
Ida Wolden Bache, Norges Bank
James Mitchell, NIESR
Francesco Ravazzolo, Norges Bank

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 a DSGE ensemble.