Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts
AbstractWe 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 (C) 2010 John Wiley & Sons, Ltd.
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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.
Volume (Year): 30 (2011)
Issue (Month): 3 (April)
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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966
macro model ; forecast projections ; out‐of‐sample ; in‐sample ; forecast accuracy ; structural break ; Economic Monetary Union ;
Other versions of this item:
- Mestre, Ricardo & McAdam, Peter, 2008. "Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts," Working Paper Series 0950, European Central Bank.
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
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- Martin Schneider & Christian Ragacs, 2009. "Why did we fail to predict GDP during the last cycle? A breakdown of forecast errors for Austria," Working Papers 151, Oesterreichische Nationalbank (Austrian Central Bank).
- Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
- Hjelm, Göran & Jönsson, Kristian, 2010. "In Search of a Method for Measuring the Output Gap of the Swedish Economy," Working Paper 115, National Institute of Economic Research.
- Kevin Clinton & Marianne Johnson & Jaromir Benes & Douglas Laxton & Troy Matheson, 2010. "Structural Models in Real Time," IMF Working Papers 10/56, International Monetary Fund.
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