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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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    1. Giordani, Paolo & Soderlind, Paul, 2003. "Inflation forecast uncertainty," European Economic Review, Elsevier, vol. 47(6), pages 1037-1059, December.
    2. Nicholas Bloom & Max Floetotto & Nir Jaimovich & Itay Saporta†Eksten & Stephen J. Terry, 2018. "Really Uncertain Business Cycles," Econometrica, Econometric Society, vol. 86(3), pages 1031-1065, May.
    3. 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.
    4. Manuel Amador & Pierre-Olivier Weill, 2010. "Learning from Prices: Public Communication and Welfare," Journal of Political Economy, University of Chicago Press, vol. 118(5), pages 866-907.
    5. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    6. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    7. Michael P. Clements, 2018. "Do Macroforecasters Herd?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 265-292, March.
    8. 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.
    9. Juan Angel Garcia, 2003. "An introduction to the ECB’s survey of professional forecasters," Occasional Paper Series 08, European Central Bank.
    10. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    11. Kenny, Geoff & Genre, Véronique & Bowles, Carlos & Friz, Roberta & Meyler, Aidan & Rautanen, Tuomas, 2007. "The ECB survey of professional forecasters (SPF) - A review after eight years' experience," Occasional Paper Series 59, European Central Bank.
    12. 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.
    13. Wändi Bruine De Bruin & Charles F. Manski & Giorgio Topa & Wilbert van der Klaauw, 2011. "Measuring consumer uncertainty about future inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(3), pages 454-478, April.
    14. Arroyo, Javier & Maté, Carlos, 2009. "Forecasting histogram time series with k-nearest neighbours methods," International Journal of Forecasting, Elsevier, vol. 25(1), pages 192-207.
    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. 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.
    17. Gianna Boero & Jeremy Smith & Kenneth F. Wallis, 2015. "The Measurement and Characteristics of Professional Forecasters' Uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1029-1046, November.
    18. 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.
    19. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    20. 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.
    21. Kenneth F. Wallis, 2005. "Combining Density and Interval Forecasts: A Modest Proposal," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 983-994, December.
    22. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.
    23. 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.
    24. Zarnowitz, Victor & Lambros, Louis A, 1987. "Consensus and Uncertainty in Economic Prediction," Journal of Political Economy, University of Chicago Press, vol. 95(3), pages 591-621, June.
    25. Garcí­a, Juan Angel, 2003. "An introduction to the ECB's survey of professional forecasters," Occasional Paper Series 8, European Central Bank.
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    Cited by:

    1. Jonas Dovern & Alexander Glas & Geoff Kenny, 2023. "Testing for Differences in Survey-Based Density Expectations: A Compositional Data Approach," CESifo Working Paper Series 10256, CESifo.
    2. Luca Rossi, 2020. "Indicators of uncertainty: a brief user’s guide," Questioni di Economia e Finanza (Occasional Papers) 564, Bank of Italy, Economic Research and International Relations Area.
    3. 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.
    4. Gabriele Galati & Richhild Moessner & Maarten van Rooij, 2023. "The anchoring of long-term inflation expectations of consumers: insights from a new survey," Oxford Economic Papers, Oxford University Press, vol. 75(1), pages 96-116.
    5. Monique Reid & Pierre Siklos, 2024. "Firm Level Expectations and Macroeconomic Conditions: Underpinnings and Disagreement," CAMA Working Papers 2024-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Hong, T., 2021. "Revisiting the Trade Policy Uncertainty Index," Cambridge Working Papers in Economics 2174, Faculty of Economics, University of Cambridge.
    7. 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.
    8. Michael Clements & Robert W. Rich & Joseph Tracy, 2024. "An Investigation into the Uncertainty Revision Process of Professional Forecasters," Working Papers 24-19, Federal Reserve Bank of Cleveland.
    9. Zhao, Yongchen, 2024. "Uncertainty of household inflation expectations: Reconciling point and density forecasts," Economics Letters, Elsevier, vol. 234(C).
    10. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    11. 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.
    12. Glas, Alexander & Heinisch, Katja, 2023. "Conditional macroeconomic survey forecasts: Revisions and errors," Journal of International Money and Finance, Elsevier, vol. 138(C).
    13. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.
    14. Beckmann, Joscha & Davidson, Sharada Nia & Koop, Gary & Schüssler, Rainer, 2023. "Cross-country uncertainty spillovers: Evidence from international survey data," Journal of International Money and Finance, Elsevier, vol. 130(C).
    15. Meade, Nigel & Driver, Ciaran, 2023. "Differing behaviours of forecasters of UK GDP growth," International Journal of Forecasting, Elsevier, vol. 39(2), pages 772-790.
    16. Ambrocio, Gene & Hasan, Iftekhar, 2022. "Belief polarization and Covid-19," Bank of Finland Research Discussion Papers 10/2022, Bank of Finland.
    17. Vania Esady, 2019. "Real and Nominal Effects of Monetary Shocks under Time-Varying Disagreement," CESifo Working Paper Series 7956, CESifo.
    18. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    19. Coleman, Winnie & Nautz, Dieter, 2023. "Inflation target credibility in times of high inflation," Economics Letters, Elsevier, vol. 222(C).
    20. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    21. 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.
    22. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    23. 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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