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Do Forecasters Inform or Reassure?: Evaluation of the German Real-Time Data


  • Konstantin A. Kholodilin
  • Boriss Siliverstovs


The paper evaluates the quality of the German national accounting data (GDP and its use-side components) as measured by the magnitude and dispersion of the forecast/ revision errors. It is demonstrated that government consumption series are the least reliable, whereas real GDP and real private consumption data are the most reliable. In addition, early forecasts of GDP, private consumption, and investment growth rates are shown to be systematically upward biased. Finally, early forecasts of all the variables seem to be no more accurate than naïve forecasts based on the historical mean of the final data.

Suggested Citation

  • Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do Forecasters Inform or Reassure?: Evaluation of the German Real-Time Data," Discussion Papers of DIW Berlin 858, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp858

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    References listed on IDEAS

    1. Enrico Santarelli & Marco Vivarelli, 2007. "Entrepreneurship and the process of firms’ entry, survival and growth," Industrial and Corporate Change, Oxford University Press, vol. 16(3), pages 455-488, June.
    2. Eichhorst, Werner & Zimmermann, Klaus F., 2007. "Dann waren's nur noch vier… Wie viele (und welche) Maßnahmen der aktiven Arbeitsmarktpolitik brauchen wir noch? Eine Bilanz nach der Evaluation der Hartz-Reformen," IZA Discussion Papers 2605, Institute for the Study of Labor (IZA).
    3. Werner Eichhorst & Klaus F. Zimmermann, 2007. "And Then There Were Four...How Many (and Which) Measures of Active Labor Market Policy Do We Still Need?," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 53(3), pages 243-272.
    4. Marco Caliendo & Viktor Steiner, 2007. "Ich-AG und Überbrückungsgeld: neue Ergebnisse bestätigen Erfolg," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 74(3), pages 25-32.
    5. Hans J. Baumgartner & Marco Caliendo & Viktor Steiner, 2006. "Existenzgründungsförderung für Arbeitslose: erste Evaluationsergebnisse für Deutschland," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 75(3), pages 32-48.
    6. Pfeiffer, Friedhelm & Reize, Frank, 2000. "Business start-ups by the unemployed -- an econometric analysis based on firm data," Labour Economics, Elsevier, vol. 7(5), pages 629-663, September.
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    Cited by:

    1. Fátima Cardoso & António Rua, 2011. "The Quarterly National Accounts in real-time: an analysis of the revisions over the last decade," Economic Bulletin and Financial Stability Report Articles, Banco de Portugal, Economics and Research Department.
    2. Helmut Herwartz & Konstantin A. Kholodilin, 2014. "In‐Sample and Out‐of‐Sample Prediction of stock Market Bubbles: Cross‐Sectional Evidence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 15-31, January.
    3. Jacopo Cimadomo, 2016. "Real-Time Data And Fiscal Policy Analysis: A Survey Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 30(2), pages 302-326, April.
    4. Katharina Glass & Ulrich Fritsche, 2015. "Real-time Macroeconomic Data and Uncertainty," Macroeconomics and Finance Series 201406, Hamburg University, Department Wirtschaft und Politik.
    5. Ullrich Heilemann & Herman O. Stekler, 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, Verein für Socialpolitik, vol. 14(2), pages 235-253, May.

    More about this item


    Quality of statistical data; real-time data; signal-to-noise ratio; forecasts; revisions;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other

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