IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/2006-059.html

An Evaluation of the World Economic Outlook Forecasts

Author

Listed:
  • Mr. Allan Timmermann

Abstract

The World Economic Outlook (WEO) is a key source of forecasts of global economic conditions. It is therefore important to review the performance of these forecasts against both actual outcomes and alternative forecasts. This paper conducts a series of statistical tests to evaluate the quality of the WEO forecasts for a very large cross section of countries, with particular emphasis on the recent recession and recovery. It assesses whether forecasts were unbiased and informationally efficient, and characterizes the process whereby WEO forecasts get revised as the time to the point of the forecast draws closer. Finally, the paper assess whether forecasts can be improved by combining WEO forecasts with the Consensus forecasts. The results suggest that the performance of the WEO forecasts is similar to that of the Consensus forecasts. While WEO forecasts for many variables in many countries meet basic quality standards in some, if not all, dimensions, the paper raises a number of concerns with current forecasting performance.

Suggested Citation

  • Mr. Allan Timmermann, 2006. "An Evaluation of the World Economic Outlook Forecasts," IMF Working Papers 2006/059, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:2006/059
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=18800
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    2. Hernández, Juan R., 2025. "Covered interest parity: A forecasting approach to estimate the neutral band," Economic Modelling, Elsevier, vol. 148(C).
    3. Hayashi, Masayoshi, 2014. "Forecasting welfare caseloads: The case of the Japanese public assistance program," Socio-Economic Planning Sciences, Elsevier, vol. 48(2), pages 105-114.
    4. Julia Eichholz & Thorsten Knauer & Sandra Winkelmann, 2023. "Digital Maturity of Forecasting and its Impact in Times of Crisis," Schmalenbach Journal of Business Research, Springer, vol. 75(4), pages 443-481, December.
    5. Tobias Adrian & Domenico Giannone & Matteo Luciani & Mike West, 2026. "Risks and Uncertainty in Monetary Policy," Papers 2606.16708, arXiv.org.
    6. Alex Tagliabracci, 2020. "Asymmetry in the conditional distribution of euro-area inflation," Temi di discussione (Economic working papers) 1270, Bank of Italy, Economic Research and International Relations Area.
    7. Dennis Kant & Andreas Pick & Jasper de Winter, 2025. "Nowcasting GDP using machine learning methods," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 109(1), pages 1-24, March.
    8. Chen, Heng & Li, Xu & Pei, Guangyu & Xin, Qian, 2024. "Heterogeneous overreaction in expectation formation: Evidence and theory," Journal of Economic Theory, Elsevier, vol. 218(C).
    9. Kaya, Huseyin, 2013. "Forecasting the yield curve and the role of macroeconomic information in Turkey," Economic Modelling, Elsevier, vol. 33(C), pages 1-7.
    10. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    11. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    12. Blaskowitz, Oliver & Herwartz, Helmut, 2011. "On economic evaluation of directional forecasts," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1058-1065, October.
    13. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2012. "Is there an Optimal Forecast Combination? A Stochastic Dominance Approach to Forecast Combination Puzzle," Working Paper series 17_12, Rimini Centre for Economic Analysis.
    14. Bizer, Kilian & Meub, Lukas & Proeger, Till & Spiwoks, Markus, 2014. "Strategic coordination in forecasting: An experimental study," University of Göttingen Working Papers in Economics 195, University of Goettingen, Department of Economics.
    15. M. Stocker & W. Ma{l}gorzewicz & M. Fontana & S. Ben Taieb, 2025. "A Gentle Introduction to Conformal Time Series Forecasting," Papers 2511.13608, arXiv.org.
    16. Aysun, Uluc & Wright, Cardel, 2024. "A two-step dynamic factor modelling approach for forecasting inflation in small open economies," Emerging Markets Review, Elsevier, vol. 62(C).
    17. Adam Elbourne & Coen Teulings, 2011. "The potential of a small model," CPB Discussion Paper 193.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    18. Régis Barnichon & Geert Mesters, 2025. "Policy evaluation with Sufficient Macro Statistics -a primer," Working Papers 1474, Barcelona School of Economics.
    19. Erik Olsen & Gavin Fay & Sarah Gaichas & Robert Gamble & Sean Lucey & Jason S Link, 2016. "Ecosystem Model Skill Assessment. Yes We Can!," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-24, January.
    20. Chen, Guojin & Liu, Yanzhen & Zhang, Yu, 2021. "Systemic risk measures and distribution forecasting of macroeconomic shocks," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 178-196.

    More about this item

    Keywords

    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:imf:imfwpa:2006/059. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Akshay Modi (email available below). General contact details of provider: https://edirc.repec.org/data/imfffus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.