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Uncertainty and disagreement in economic forecasting

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  • Stefania D'Amico
  • Athanasios Orphanides

Abstract

Using the probabilistic responses from the Survey of Professional Forecasters, we study the evolution of uncertainty and disagreement associated with inflation forecasts in the United States since 1968. We compare and contrast alternative measures summarizing the distributions of mean forecasts and forecast uncertainty across individuals at an approximate one-year-ahead horizon. In light of the heterogeneity in individual uncertainty reflected in the survey responses, we provide quarterly estimates for both average uncertainty and disagreement regarding uncertainty. We propose direct estimation of parametric distributions characterizing the uncertainty across individuals in a manner that mitigates errors associated with rounding and approximation of responses when individual uncertainty is small. Our results indicate that higher average expected inflation is associated with both higher average inflation uncertainty and greater disagreement about the inflation outlook. Disagreement about the mean forecast, however, may be a weak proxy for forecast uncertainty. We also examine the relationship of these measures with the term premia embedded in the term-structure of interest rates.

Suggested Citation

  • Stefania D'Amico & Athanasios Orphanides, 2008. "Uncertainty and disagreement in economic forecasting," Finance and Economics Discussion Series 2008-56, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2008-56
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    References listed on IDEAS

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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. 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.
    3. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    4. Robert W. Rich & Joseph Tracy, 2003. "Modeling uncertainty: predictive accuracy as a proxy for predictive confidence," Staff Reports 161, Federal Reserve Bank of New York.
    5. Fushang Liu & Kajal Lahiri, 2006. "Modelling multi-period inflation uncertainty using a panel of density forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1199-1219.
    6. Robert W. Rich & Joseph Tracy, 2006. "The relationship between expected inflation, disagreement, and uncertainty: evidence from matched point and density forecasts," Staff Reports 253, Federal Reserve Bank of New York.
    7. Victor Zarnowitz & Louis A. Lambros, 1983. "Consensus and Uncertainty in Economic Prediction," NBER Working Papers 1171, National Bureau of Economic Research, Inc.
    8. Dean Croushore, 1993. "Introducing: the survey of professional forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 3-15.
    9. 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.
    10. Víctor Gómez & Agustín Maravall, 1998. "Automatic Modeling Methods for Univariate Series," Working Papers 9808, Banco de España;Working Papers Homepage.
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    Citations

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    Cited by:

    1. Caldara, Dario & Fuentes-Albero, Cristina & Gilchrist, Simon & Zakrajšek, Egon, 2016. "The macroeconomic impact of financial and uncertainty shocks," European Economic Review, Elsevier, vol. 88(C), pages 185-207.
    2. repec:eee:dyncon:v:78:y:2017:i:c:p:1-25 is not listed on IDEAS
    3. Artur Tarassow, 2017. "Forecasting growth of U.S. aggregate and household-sector M2 after 2000 using economic uncertainty measures," Macroeconomics and Finance Series 201702, Hamburg University, Department Wirtschaft und Politik.
    4. Hartmann, Matthias & Herwartz, Helmut & Ulm, Maren, 2017. "A comparative assessment of alternative ex ante measures of inflation uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 76-89.
    5. Michael Ehrmann & Sylvester Eijffinger & Marcel Fratzscher, 2012. "The Role of Central Bank Transparency for Guiding Private Sector Forecasts," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(3), pages 1018-1052, September.
    6. Rich, Robert W. & Tracy, Joseph, 2017. "The behavior of uncertainty and disagreement and their roles in economic prediction: a panel analysis," Staff Reports 808, Federal Reserve Bank of New York.
    7. Pacheco, Luis, 2010. "ECB Projections: should leave it to the pros?," Working Papers 11/2010, Universidade Portucalense, Centro de Investigação em Gestão e Economia (CIGE).
    8. Berger, Helge & Ehrmann, Michael & Fratzscher, Marcel, 2011. "Geography, skills or both: What explains Fed watchers' forecast accuracy of US monetary policy?," Journal of Macroeconomics, Elsevier, vol. 33(3), pages 420-437, September.
    9. Ricco, Giovanni & Callegari, Giovanni & Cimadomo, Jacopo, 2014. "Signals from the Government: Policy Uncertainty and the Transmission of Fiscal Shocks," MPRA Paper 56136, University Library of Munich, Germany.
    10. Clements, Michael P, 2012. "Subjective and Ex Post Forecast Uncertainty : US Inflation and Output Growth," The Warwick Economics Research Paper Series (TWERPS) 995, University of Warwick, Department of Economics.
    11. Levin, Andrew T., 2014. "The design and communication of systematic monetary policy strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 49(C), pages 52-69.

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    Keywords

    Inflation (Finance) ; Economic forecasting;

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