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Patterns in IMF Growth Forecast Revisions: A Panel Study at Multiple Horizons

Author

Listed:
  • Metodij Hadzi-Vaskov
  • Mr. Luca A Ricci
  • Alejandro Mariano Werner
  • Rene Zamarripa

Abstract

This paper investigates the performance of the IMF WEO growth forecast revisions across different horizons and country groups. We find that: (i) growth revisions in horizons closer to the actual are generally larger, more volatile, and more negative; (ii) on average, growth revisions are in the right direction, becoming progressively more responsive to the forecast error gap as horizons get closer to the actual year; (iii) growth revisions in systemic economies are relevant for growth revisions in all country groups; (iv) WEO and Consensus Forecast growth revisions are highly correlated; (v) fall-to-spring WEO revisions are more correlated with Consensus Forecasts revisions compared to spring-to-fall revisions; and (vi) across vintages, revisions for a given time horizon are not autocorrelated; within vintages, revisions tend to be positively correlated, suggesting perception of persistent short-term shocks.

Suggested Citation

  • Metodij Hadzi-Vaskov & Mr. Luca A Ricci & Alejandro Mariano Werner & Rene Zamarripa, 2021. "Patterns in IMF Growth Forecast Revisions: A Panel Study at Multiple Horizons," IMF Working Papers 2021/136, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2021/136
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    References listed on IDEAS

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    1. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2018. "Diagnostic Expectations and Credit Cycles," Journal of Finance, American Finance Association, vol. 73(1), pages 199-227, February.
    2. Mr. Allan Timmermann, 2006. "An Evaluation of the World Economic Outlook Forecasts," IMF Working Papers 2006/059, International Monetary Fund.
    3. Allan Timmermann, 2007. "An Evaluation of the World Economic Outlook Forecasts," IMF Staff Papers, Palgrave Macmillan, vol. 54(1), pages 1-33, May.
    4. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    5. Branch, William A., 2007. "Sticky information and model uncertainty in survey data on inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 245-276, January.
    6. Mr. John C Bluedorn & Mr. Daniel Leigh, 2018. "Is the Cycle the Trend? Evidence From the Views of International Forecasters," IMF Working Papers 2018/163, International Monetary Fund.
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    Cited by:

    1. Dr. Christian Hepenstrick & Jason Blunier, 2022. "What were they thinking? Estimating the quarterly forecasts underlying annual growth projections," Working Papers 2022-05, Swiss National Bank.
    2. Frank, Luis, 2021. "¿Son sesgadas las proyecciones de WEO? El caso de la proyección de crecimiento de Argentina [Are the WEO forecasts biased? The case of Argentina's growth forecast]," MPRA Paper 114333, University Library of Munich, Germany.

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    More about this item

    Keywords

    growth revision; consensus forecast growth revision; WEO growth forecast; consensus forecasts revision; fall-to-spring WEO revision; Technology transfer; Terms of trade; Time series analysis; Vector autoregression; Europe; Caribbean;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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