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Probability Distributions or Point Predictions? Survey Forecasts of US Output Growth and Inflation

  • Clements, Michael P

    (University of Warwick)

We consider whether survey respondents’probability distributions, reported as histograms, provide reliable and coherent point predictions, when viewed through the lens of a Bayesian learning model, and whether they are well calibrated more generally. We argue that a role remains for eliciting directly-reported point predictions in surveys of professional forecasters. Key words: probability distribution forecasts ; point forecasts ; Bayesian learning JEL classification: C53

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File URL: http://www2.warwick.ac.uk/fac/soc/economics/research/workingpapers/2012/twerp_976.pdf
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Paper provided by University of Warwick, Department of Economics in its series The Warwick Economics Research Paper Series (TWERPS) with number 976.

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Date of creation: 2012
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Handle: RePEc:wrk:warwec:976
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Web page: http://www2.warwick.ac.uk/fac/soc/economics/

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  1. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
  2. James H. Stock & Mark W. Watson, 2010. "Modeling inflation after the crisis," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 173-220.
  3. Clements, Michael P., 2010. "Explanations of the inconsistencies in survey respondents' forecasts," European Economic Review, Elsevier, vol. 54(4), pages 536-549, May.
  4. Giordani, Paolo & Soderlind, Paul, 2003. "Inflation forecast uncertainty," European Economic Review, Elsevier, vol. 47(6), pages 1037-1059, December.
  5. Boero,Gianna & Smith,Jeremy & Wallis,Kenneth F, 2006. "Uncertainty and disagreement in economic prediction : the Bank of England Survey of External Forecasters," The Warwick Economics Research Paper Series (TWERPS) 811, University of Warwick, Department of Economics.
  6. 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.
  7. García, Juan Angel & Manzanares, Andrés, 2007. "Reporting biases and survey results: evidence from European professional forecasters," Working Paper Series 0836, European Central Bank.
  8. James H. Stock & Mark W. Watson, 2006. "Why Has U.S. Inflation Become Harder to Forecast?," NBER Working Papers 12324, National Bureau of Economic Research, Inc.
  9. Andrew Atkeson & Lee E. Ohanian., 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
  10. 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.
  11. Eugene Kandel & Ben-Zion Zilberfarb, 1999. "Differential Interpretation Of Information In Inflation Forecasts," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 217-226, May.
  12. Xuguang Sheng & Jingyun Yang, 2013. "Truncated Product Methods for Panel Unit Root Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(4), pages 624-636, 08.
  13. Victor Zarnowitz & Phillip Braun, 1992. "Twenty-two Years of the NBER-ASA Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance," NBER Working Papers 3965, National Bureau of Economic Research, Inc.
  14. Sebastiano Manzan, 2011. "Differential Interpretation in the Survey of Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 993-1017, 08.
  15. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
  16. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-74, October.
  17. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
  18. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia.
  19. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
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