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Is forecasting with large models informative? Assessing the role of judgement in macro-economic forecasts

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Author Info
Ricardo Mestre () (Corresponding author: European Central Bank, DG Research, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.)
Peter McAdam () (European Central Bank, DG Research, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.)

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Abstract

We evaluate residual projection strategies in the context of a large-scale macro model of the euro area and smaller benchmark time-series models. The exercises attempt to measure the accuracy of model-based forecasts simulated both out-of-sample and in-sample. Both exercises incorporate alternative residual-projection methods, to assess the importance of unaccounted-for breaks in forecast accuracy and off-model judgment. Conclusions reached are that simple mechanical residual adjustments have a significant impact of forecasting accuracy irrespective of the model in use, ostensibly due to the presence of breaks in trends in the data. The testing procedure and conclusions are applicable to a wide class of models and thus of general interest. JEL Classification: C52, E30, E32, E37.

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Publisher Info
Paper provided by European Central Bank in its series Working Paper Series with number 950.

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Length: 61 pages
Date of creation: Oct 2008
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Handle: RePEc:ecb:ecbwps:20080950

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Keywords: Macro-model; Forecast Projections; Out-of-Sample; In-Sample; Forecast Accuracy; Structural Break.;

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This page was last updated on 2009-12-1.


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