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European Commission's Forecasts Accuracy Revisited: Statistical Properties and Possible Causes of Forecast Errors

Author

Listed:
  • Marco Fioramanti, ISTAT
  • Laura González Cabanillas
  • Bjorn Roelstraete
  • Salvador Adrian Ferrandis Vallterra

Abstract

This paper updates a previous assessment of the European Commission's track record for forecasting key economic variables (González Cabanillas and Terzi 2012) by extending the observation period to 2014. It also examines the accuracy of the Commission's forecasts over a shorter and more recent period (2000-2014) so that a comparison can be made between the performance of forecasts made before and after the Great Recession of 2008-2009. Going beyond the 2012 approach, this paper also examines the extent to which forecast errors can be explained by external or technical assumptions that prove incorrect ex post. It also updates the comparison of the Commission’s performance vis à vis the OECD, the IMF, a consensus forecast of market economists, and the ECB. Inclusion of the 2012-2014 period lowers the forecasting error for some key variables or leads to no change in others. Focussing on the years since the turn of the century, current-year and year-ahead forecasting errors for the three main variables examined (GDP growth, inflation and general government balances) have been larger in the crisis and post-crisis period (2008-2014) than in the precrisis period (2000-2007) for a large majority of Member States. This appears mainly to be the result of an anomalously large error in 2009, a year which confounded many forecasters. The country-bycountry analysis confirms the finding of earlier studies which show that the Commission's forecasts are largely unbiased. The newly-introduced panel data approach also confirms the absence of bias in current-year GDP forecasts across EU Member States but shows that year-ahead forecasts for GDP growth tend to be slightly over optimistic across the whole sample. The analysis also shows that autocorrelation of forecast errors is not a major issue in the Commission's forecasts. Other advanced tests shed more light on the performance of the Commission’s forecasts, demonstrating that they are directionally accurate and generally beat a naïve forecast but that they are not always efficient in terms of their use of all available data. The decomposition of forecast errors shows that unexpected changes in external assumptions seem to have only a limited impact on current-year GDP growth forecasts. However, more than half of the variance in year-ahead forecast errors appears to come from external assumptions that prove to be incorrect ex post. Finally, the Commission’s economic forecasts come out as being more accurate than those of the market and comparable to those of the other international institutions considered.

Suggested Citation

  • Marco Fioramanti, ISTAT & Laura González Cabanillas & Bjorn Roelstraete & Salvador Adrian Ferrandis Vallterra, 2016. "European Commission's Forecasts Accuracy Revisited: Statistical Properties and Possible Causes of Forecast Errors," European Economy - Discussion Papers 027, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
  • Handle: RePEc:euf:dispap:027
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    Citations

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    Cited by:

    1. Glas, Alexander & Heinisch, Katja, 2021. "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers 7/2021, Halle Institute for Economic Research (IWH).
    2. Glas, Alexander & Heinisch, Katja, 2023. "Conditional macroeconomic survey forecasts: Revisions and errors," Journal of International Money and Finance, Elsevier, vol. 138(C).
    3. Agnes Benassy-Quere, 2016. "Euro-Area Fiscal Stance: From Theory to Practical Implementation," CESifo Working Paper Series 6040, CESifo.
    4. Fioramanti, Marco & Waldmann, Robert J., 2017. "The Econometrics of the EU Fiscal Governance: is the European Commission methodology still adequate?," MPRA Paper 81858, University Library of Munich, Germany.
    5. Ludovic Dobbelaere & Igor Lebrun, 2017. "Working Paper 12-17 - Évaluation de la précision des prévisions à court terme du BFP - Une mise à jour [Working Paper 12-17 - Evaluatie van de nauwkeurigheid van de kortetermijnvooruitzichten van h," Working Papers 1712, Federal Planning Bureau, Belgium.
    6. Cardi, Olivier & Restout, Romain, 2023. "Sectoral fiscal multipliers and technology in open economy," Journal of International Economics, Elsevier, vol. 144(C).
    7. Larch, Martin & Cugnasca, Alessandro & Kumps, Diederik & Orseau, Eloïse, 2019. "Fiscal policy and the assessment of output gaps in real time: An exercise in risk management," ZEW Discussion Papers 19-013, ZEW - Leibniz Centre for European Economic Research.
    8. Larch, Martin & Kumps, Diederik & Cugnasca, Alessandro, 2021. "Fiscal stabilisation in real time: An exercise in risk management," Economic Modelling, Elsevier, vol. 99(C).
    9. Nicolas Reigl, 2023. "Noise shocks and business cycle fluctuations in three major European Economies," Empirical Economics, Springer, vol. 64(2), pages 603-657, February.
    10. Igor Lebrun, 2017. "Working Paper 13-17 - Évaluation de la précision des perspectives à moyen terme du BFP - Une mise à jour [Working Paper 13-17 - Evaluatie van de nauwkeurigheid van de middellangetermijnvooruitzicht," Working Papers 1713, Federal Planning Bureau, Belgium.
    11. 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).
    12. Andras Chabin & Sébastien Lamproye & Milan Výškrabka, 2020. "Are We More Accurate? Revisiting the European Commission’s Macroeconomic Forecasts," European Economy - Discussion Papers 128, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    13. Cronin, David & McInerney, Niall, 2023. "Official fiscal forecasts in EU member states under the European Semester and Fiscal Compact – An empirical assessment," European Journal of Political Economy, Elsevier, vol. 76(C).
    14. Sabaj, Ernil & Kahveci, Mustafa, 2018. "Forecasting tax revenues in an emerging economy: The case of Albania," MPRA Paper 84404, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions

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