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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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  1. James H. Stock & Mark W. Watson, 2010. "Modeling Inflation After the Crisis," NBER Working Papers 16488, National Bureau of Economic Research, Inc.
  2. Giordani, Paolo & Soderlind, Paul, 2000. "Inflation Forecast Uncertainty," SSE/EFI Working Paper Series in Economics and Finance 384, Stockholm School of Economics, revised 09 Oct 2000.
  3. 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.
  4. Tom Stark & Dean Croushore, 2001. "Forecasting with a real-time data set for macroeconomists," Working Papers 01-10, Federal Reserve Bank of Philadelphia.
  5. García, Juan Angel & Manzanares, Andrés, 2007. "Reporting biases and survey results: evidence from European professional forecasters," Working Paper Series 0836, European Central Bank.
  6. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
  7. Joseph Engelberg & Charles F. Manski & Jared Williams, 2006. "Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters," NBER Working Papers 11978, National Bureau of Economic Research, Inc.
  8. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
  9. Gianna Boero & Jeremy Smith & KennethF. 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, 07.
  10. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
  11. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, 02.
  12. Lahiri, Kajal & Sheng, Xuguang, 2009. "Learning and heterogeneity in GDP and inflation forecasts," MPRA Paper 21448, University Library of Munich, Germany.
  13. Clements, Michael P., 2010. "Explanations of the inconsistencies in survey respondents' forecasts," European Economic Review, Elsevier, vol. 54(4), pages 536-549, May.
  14. Xuguang Sheng & Jingyun Yang, 2013. "Truncated Product Methods for Panel Unit Root Tests," Working Papers 2013-004, The George Washington University, Department of Economics, Research Program on Forecasting.
  15. Dean Croushore, 1993. "Introducing: the survey of professional forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 3-15.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. Batchelor, Roy & Dua, Pami, 1991. "Blue Chip Rationality Tests," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 23(4), pages 692-705, November.
  23. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
  24. J. Steven Landefeld & Eugene P. Seskin & Barbara M. Fraumeni, 2008. "Taking the Pulse of the Economy: Measuring GDP," Journal of Economic Perspectives, American Economic Association, vol. 22(2), pages 193-216, Spring.
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