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Are macroeconomic forecasters optimists or pessimists? A reassessment of survey based forecasts

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  • Huang, Rong
  • Pilbeam, Keith
  • Pouliot, William

Abstract

We examine the issue of macroeconomic uncertainty in the Eurozone Area using forecasts from the European Central Bank’s Survey of Professional Forecasters from the inception of the Euro in 1999Q1 to 2020Q2. We provide new insights concerning the optimism or pessimism of the distribution of forecasts by examining the 25th and 75th quartiles of the forecast distribution for each three key macro economic variables, GDP growth, inflation and unemployment. In addition, we examine the over- or under-confidence of forecasters in the survey by deriving the term structure of ex-ante uncertainty for up to 2 years ahead and compare it to ex-post uncertainty, enabling us to make some comparisons with existing US studies. Our results suggest that GDP growth forecasts tend towards optimism, while those for inflation and unemployment tend towards pessimism. In addition, ex-ante uncertainty in forecasts for the Eurozone Area is less than ex-post uncertainty at both the short and longer-term forecasting horizons, for all three variables. This suggests a tendency towards over-confidence on the part of Eurozone forecasters.

Suggested Citation

  • Huang, Rong & Pilbeam, Keith & Pouliot, William, 2022. "Are macroeconomic forecasters optimists or pessimists? A reassessment of survey based forecasts," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 706-724.
  • Handle: RePEc:eee:jeborg:v:197:y:2022:i:c:p:706-724
    DOI: 10.1016/j.jebo.2022.03.012
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    References listed on IDEAS

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    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. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    3. Graham Elliott & Allan Timmermann & Ivana Komunjer, 2005. "Estimation and Testing of Forecast Rationality under Flexible Loss," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(4), pages 1107-1125.
    4. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    5. 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.
    6. Barbara Rossi & Tatevik Sekhposyan, 2015. "Macroeconomic Uncertainty Indices Based on Nowcast and Forecast Error Distributions," American Economic Review, American Economic Association, vol. 105(5), pages 650-655, May.
    7. Beckmann, Joscha, 2021. "Measurement and effects of euro/dollar exchange rate uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 773-790.
    8. Clements, Michael P. & Galvão, Ana Beatriz, 2017. "Model and survey estimates of the term structure of US macroeconomic uncertainty," International Journal of Forecasting, Elsevier, vol. 33(3), pages 591-604.
    9. 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.
    10. Giordani, Paolo & Soderlind, Paul, 2003. "Inflation forecast uncertainty," European Economic Review, Elsevier, vol. 47(6), pages 1037-1059, December.
    11. Kajal Lahiri & Xuguang Sheng, 2010. "Measuring forecast uncertainty by disagreement: The missing link," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 514-538.
    12. Engelberg, Joseph & Manski, Charles F. & Williams, Jared, 2009. "Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 30-41.
    13. Coibion, Olivier & Gorodnichenko, Yuriy & Kumar, Saten & Pedemonte, Mathieu, 2020. "Inflation expectations as a policy tool?," Journal of International Economics, Elsevier, vol. 124(C).
    14. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    15. Michael P. Clements, 2014. "Forecast Uncertainty- Ex Ante and Ex Post : U.S. Inflation and Output Growth," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 206-216, April.
    16. 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.
    17. Dale J. Poirier, 1995. "Intermediate Statistics and Econometrics: A Comparative Approach," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161494, December.
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    More about this item

    Keywords

    Macroeconomic uncertainty; ECB survey of professional forecasters; Subjective probability distribution; Ex-ante uncertainty; Ex-post uncertainty; Bayesian decision theory;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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