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Learning to Forecast with a DGE Model ∗

By Juha Kilponen, Bank Of Finland and Antti Ripatti

Abstract

The Bank of Finland has used a newly built D(S)GE model (Aino model) as its main forecasting tool since August 2004. A common forecasters’ prejudice is that DSGE models are difficult to use and their data coherence is very low. In this paper we provide contradicting view. We describe the Aino model, its forecasting related modifications, and collect experiences in the use of the model. A succesfull forecasting tool need to digest expert information while retaining its theoretical consistency, i.e. it has to incorporate judgement without relaxing story telling features. Aino’s design is based on this prerequisite. It makes use of Harrod neutral technical change within CES aggregators and allow many preference and technology parameters to be time-varying. These choices are key to fullfill practical needs of forecasting with a D(S)GE model. JEL: E60, C68 Aino model is a result of the joint project by Juha Kilponen, Mika Kuismanen (ECB)

Year: 2006
OAI identifier: oai:CiteSeerX.psu:10.1.1.307.7997
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