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Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts
Author(s) -
Mestre Ricardo,
McAdam Peter
Publication year - 2011
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.1173
Subject(s) - residual , econometrics , benchmark (surveying) , context (archaeology) , judgement , projection (relational algebra) , computer science , model selection , sample (material) , scale (ratio) , macro , economics , artificial intelligence , programming language , paleontology , chemistry , physics , geodesy , algorithm , chromatography , quantum mechanics , political science , law , biology , geography
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 judgement. Conclusions reached are that simple mechanical residual adjustments have a significant impact on forecasting accuracy irrespective of the model in use, likely 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 of general interest. Copyright © 2010 John Wiley & Sons, Ltd.