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A Closer Look at the Behavior of Uncertainty and Disagreement: Micro Evidence from the Euro Area

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  • ROBERT RICH
  • JOSEPH TRACY

Abstract

This paper examines point and density forecasts of real GDP growth, inflation, and unemployment from the European Central Bank's Survey of Professional Forecasters. We analyze individual uncertainty measures as well as introduce individual point‐ and density‐based disagreement measures. The analysis indicates forecasters’ uncertainty and disagreement display substantial heterogeneity and persistence, with the latter feature challenging a key prediction of expectations models emphasizing information frictions. We also find that uncertainty is characterized by prominent respondent effects and disagreement by prominent time effects, suggesting these divergent properties underlie the well‐documented weak uncertainty–disagreement linkage. Taken together, our results provide a basis for further development of expectations models.

Suggested Citation

  • Robert Rich & Joseph Tracy, 2021. "A Closer Look at the Behavior of Uncertainty and Disagreement: Micro Evidence from the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 233-253, February.
    • Handle: RePEc:wly:jmoncb:v:53:y:2021:i:1:p:233-253
    DOI: 10.1111/jmcb.12728
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    Cited by:

    1. Nikos Apokoritis & Gabriele Galati & Richhild Moessner & Federica Teppa, 2019. "Inflation expectations anchoring: new insights from micro evidence of a survey at high-frequency and of distributions," BIS Working Papers 809, Bank for International Settlements.
    2. Gabriele Galati & Richhild Moessner & Maarten van Rooij, 2020. "The anchoring of long-term inflation expectations of consumers: insights from a new survey," Working Papers 688, DNB.
    3. Hong, T., 2021. "Revisiting the Trade Policy Uncertainty Index," Cambridge Working Papers in Economics 2174, Faculty of Economics, University of Cambridge.
    4. Petar Soric & Oscar Claveria, 2021. ""Employment uncertainty a year after the irruption of the covid-19 pandemic"," IREA Working Papers 202112, University of Barcelona, Research Institute of Applied Economics, revised May 2021.
    5. Yongchen Zhao, 2022. "Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 810-828, July.
    6. Ambrocio, Gene & Hasan, Iftekhar, 2022. "Belief polarization and Covid-19," Bank of Finland Research Discussion Papers 10/2022, Bank of Finland.
    7. Vania Esady, 2019. "Real and Nominal Effects of Monetary Shocks under Time-Varying Disagreement," CESifo Working Paper Series 7956, CESifo.
    8. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    9. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    10. Brent Meyer & Emil Mihaylov & Jose Maria Barrero & Steven J. Davis & David Altig & Nicholas Bloom, 2022. "Pandemic-Era Uncertainty," JRFM, MDPI, vol. 15(8), pages 1-14, July.
    11. Coleman, Winnie & Nautz, Dieter, 2022. "Inflation target credibility in times of high inflation," Discussion Papers 2022/5, Free University Berlin, School of Business & Economics.
    12. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    13. Gabriele Galati & Richhild Moessner & Maarten van Rooij, 2021. "Anchoring of consumers’ long-term euro area inflation expectations during the pandemic," Working Papers 715, DNB.

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    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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