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Forecasting Euro Area Real GDP: Optimal Pooling of Information


  • Oliver Hülsewig
  • Johannes Mayr
  • Timo Wollmershäuser


This paper proposes a new method of forecasting euro area quarterly real GDP that uses area-wide indicators, which are derived by optimally pooling the information contained in national indicator series. Following the ideas of predictive modeling, we construct the area-wide indicators by utilizing weights that minimize the variance of the out-of-sample forecast errors of the area-wide target variable. In an out-of-sample forecast experiment we find that our optimal pooling of information approach outperforms alternative forecasting methods in terms of forecast accuracy.

Suggested Citation

  • Oliver Hülsewig & Johannes Mayr & Timo Wollmershäuser, 2008. "Forecasting Euro Area Real GDP: Optimal Pooling of Information," CESifo Working Paper Series 2371, CESifo Group Munich.
  • Handle: RePEc:ces:ceswps:_2371

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    References listed on IDEAS

    1. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2005. "Leading Indicators for Euro-area Inflation and GDP Growth," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 785-813, December.
    2. Brodie, Joshua & Daubechies, Ingrid & De Mol, Christine & Giannone, Domenico, 2007. "Sparse and Stable Markowitz Portfolios," CEPR Discussion Papers 6474, C.E.P.R. Discussion Papers.
    3. George Kapetanios & Massimiliano Marcellino, 2009. "A parametric estimation method for dynamic factor models of large dimensions," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(2), pages 208-238, March.
    4. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    5. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    6. Anna Stangl, 2007. "World Economic Survey," Chapters,in: Handbook of Survey-Based Business Cycle Analysis, chapter 5 Edward Elgar Publishing.
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    Cited by:

    1. Evgenia Kudymowa & Johanna Garnitz & Klaus Wohlrabe, 2013. "Ifo World Economic Survey und die realwirtschaftliche Entwicklung in ausgewählten Ländern," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(19), pages 23-30, October.
    2. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics 11140, University of Munich, Department of Economics.
    3. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2017. "Forecasting GDP all over the World: Evidence from Comprehensive Survey Data," MPRA Paper 81772, University Library of Munich, Germany.
    4. Evgenia Kudymowa & Johanna Garnitz & Klaus Wohlrabe, 2014. "Ifo World Economic Survey and the Business Cycle in Selected Countries," CESifo Forum, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 14(4), pages 51-57, January.

    More about this item


    forecasting; aggregation; model averaging; real time experiment;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications


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