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How forecast accuracy depends on conditioning assumptions

Author

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  • Engelke, Carola
  • Heinisch, Katja
  • Schult, Christoph

Abstract

This paper examines the extent to which errors in economic forecasts are driven by initial assumptions that prove to be incorrect ex post. Therefore, we construct a new data set comprising an unbalanced panel of annual forecasts from different institutions forecasting German GDP and the underlying assumptions. We explicitly control for different forecast horizons to proxy the information available at the release date. Over 75% of squared errors of the GDP forecast comove with the squared errors in their underlying assumptions. The root mean squared forecast error for GDP in our regression sample of 1.52% could be reduced to 1.13% by setting all assumption errors to zero. This implies that the accuracy of the assumptions is of great importance and that forecasters should reveal the framework of their assumptions in order to obtain useful policy recommendations based on economic forecasts.

Suggested Citation

  • Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
  • Handle: RePEc:zbw:iwhdps:182019
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    File URL: https://www.econstor.eu/bitstream/10419/201837/1/167161237X.pdf
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    References listed on IDEAS

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    1. Fred Joutz & Michael P. Clements & Herman O. Stekler, 2007. "An evaluation of the forecasts of the federal reserve: a pooled approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 121-136.
    2. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
    3. Heilemann, Ullrich & Stekler, H. O., 2003. "Has the accuracy of German macroeconomic forecasts improved?," Technical Reports 2003,31, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    4. repec:eee:enepol:v:118:y:2018:i:c:p:58-68 is not listed on IDEAS
    5. Cohen, Gail & Jalles, Joao Tovar & Loungani, Prakash & Marto, Ricardo, 2018. "The long-run decoupling of emissions and output: Evidence from the largest emitters," Energy Policy, Elsevier, vol. 118(C), pages 58-68.
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    More about this item

    Keywords

    forecasts; accuracy; forecast errors; external assumptions; forecast efficiency; forecast horizon;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E02 - Macroeconomics and Monetary Economics - - General - - - Institutions and the Macroeconomy
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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