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Analysis of forecast errors in micro-level survey data

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  • Paloviita, Maritta
  • Virén, Matti

Abstract

This paper studies forecasts errors at the micro level using two alternative survey data sets. The main focus is on inflation and real GDP growth forecasts in the ECB Survey of Professional Forecasters. For comparison, inflation forecasts in the US Survey of Professional Forecasters are also examined. Our analysis indicates that forecast errors are positively related to the subjective uncertainties based on probability distributions, but not to disagreement (standard deviation of point forecasts). We also show that forecast errors, which are rather persistent, are related to forecast revisions. Revisions of expectations generally lead to larger forecast errors. Subjective uncertainty measures, which are available at the time of forecasting, are useful in assessing future forecast errors.

Suggested Citation

  • Paloviita, Maritta & Virén, Matti, 2014. "Analysis of forecast errors in micro-level survey data," Bank of Finland Research Discussion Papers 8/2014, Bank of Finland.
    • Handle: RePEc:zbw:bofrdp:rdp2014_008
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    References listed on IDEAS

    as
    1. Clements, Michael P., 2010. "Explanations of the inconsistencies in survey respondents' forecasts," European Economic Review, Elsevier, vol. 54(4), pages 536-549, May.
    2. Keith Sill, 2012. "Measuring economic uncertainty using the Survey of Professional Forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Q4, pages 16-27.
    3. Geoff Kenny & Thomas Kostka & Federico Masera, 2014. "How Informative are the Subjective Density Forecasts of Macroeconomists?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(3), pages 163-185, April.
    4. Joshua Abel & Robert Rich & Joseph Song & Joseph Tracy, 2016. "The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 533-550, April.
    5. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
    6. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    7. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    8. Gianna Boero & Jeremy Smith & Kenneth F. Wallis, 2008. "Uncertainty and Disagreement in Economic Prediction: The Bank of England Survey of External Forecasters," Economic Journal, Royal Economic Society, vol. 118(530), pages 1107-1127, July.
    9. Carlos Bowles & Roberta Friz & Veronique Genre & Geoff Kenny & Aidan Meyler & Tuomas Rautanen, 2010. "An Evaluation of the Growth and Unemployment Forecasts in the ECB Survey of Professional Forecasters," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(2), pages 1-28.
    10. Robert Rich & Joseph Tracy, 2010. "The Relationships among Expected Inflation, Disagreement, and Uncertainty: Evidence from Matched Point and Density Forecasts," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 200-207, February.
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    More about this item

    Keywords

    Forecasting; Survey data; Expectations;
    All these keywords.

    JEL classification:

    • 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
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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