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Outperforming IMF Forecasts by the Use of Leading Indicators

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  • Drechsel, Katja
  • Giesen, Sebastian
  • Lindner, Axel

Abstract

This study analyzes the performance of the IMF World Economic Outlook forecasts for world output and the aggregates of both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current and the next year, we examine whether IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time dataset for GDP and for the indicators we nd that some simple single-indicator forecasts on the basis of data that are available at higher frequency can signi cantly outperform the IMF forecasts if the publication of the Outlook is only a few months old.

Suggested Citation

  • Drechsel, Katja & Giesen, Sebastian & Lindner, Axel, 2014. "Outperforming IMF Forecasts by the Use of Leading Indicators," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100393, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc14:100393
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    1. Katja Drechsel & Laurent Maurin, 2011. "Flow of conjunctural information and forecast of euro area economic activity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 336-354, April.
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    5. Audrone Jakaitiene & Stephane Dees, 2012. "Forecasting the World Economy in the Short Term," The World Economy, Wiley Blackwell, vol. 35(3), pages 331-350, March.
    6. Allan Timmermann, 2007. "An Evaluation of the World Economic Outlook Forecasts," IMF Staff Papers, Palgrave Macmillan, vol. 54(1), pages 1-33, May.
    7. Roy Batchelor, 2001. "How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 225-235.
    8. Laura Gonzalez Cabanillas & Alessio Terzi, 2012. "The accuracy of the European Commission's forecasts re-examined," European Economy - Economic Papers 2008 - 2015 476, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    9. Golinelli, Roberto & Parigi, Giuseppe, 2014. "Tracking world trade and GDP in real time," International Journal of Forecasting, Elsevier, vol. 30(4), pages 847-862.
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    11. Arora, Harjit K. & Smyth, David J., 1990. "Forecasting the developing world : An accuracy analysis of the IMF's forecasts," International Journal of Forecasting, Elsevier, vol. 6(3), pages 393-400, October.
    12. Gerard van Welzenis & Wim Suyker, 2005. "Explanatory note on the CPB world trade series," CPB Memorandum 116, CPB Netherlands Bureau for Economic Policy Analysis.
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    14. repec:zbw:iwhdps:5-11 is not listed on IDEAS
    15. Katja Drechsel & Rolf Scheufele, 2012. "The Financial Crisis from a Forecaster’s Perspective," Credit and Capital Markets, Credit and Capital Markets, vol. 45(1), pages 1-26.
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    Cited by:

    1. Camacho, Maximo & Martinez-Martin, Jaime, 2015. "Monitoring the world business cycle," Economic Modelling, Elsevier, vol. 51(C), pages 617-625.
    2. Klaus Abberger & Michael Graff & Oliver Müller & Jan-Egbert Sturm, 2022. "Composite global indicators from survey data: the Global Economic Barometers," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 158(3), pages 917-945, August.
    3. Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.

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    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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