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Disagreement, Uncertainty and the True Predictive Density

Author

Listed:
  • Fabian Krüger

    () (Department of Economics, University of Konstanz, Germany)

  • Ingmar Nolte

    () (Warwick Business School, Financial Econometrics Research Centre (FERC), University of Warwick)

Abstract

This paper generalizes the discussion about disagreement versus uncertainty in macroeconomic survey data by emphasizing the importance of the (unknown) true predictive density. Using a forecast combination approach, we ask whether cross sections of survey point forecasts help to approximate the true predictive density. We find that although these cross-sections perform poorly individually, their inclusion into combined predictive densities can significantly improve upon densities relying solely on time series information.

Suggested Citation

  • Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
  • Handle: RePEc:knz:dpteco:1143
    as

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    File URL: http://www.uni-konstanz.de/FuF/wiwi/workingpaperseries/WP_43-Krueger-Nolte-11.pdf
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    References listed on IDEAS

    as
    1. Giordani, Paolo & Soderlind, Paul, 2003. "Inflation forecast uncertainty," European Economic Review, Elsevier, vol. 47(6), pages 1037-1059, December.
    2. Komunjer, Ivana, 2005. "Quasi-maximum likelihood estimation for conditional quantiles," Journal of Econometrics, Elsevier, vol. 128(1), pages 137-164, September.
    3. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, Elsevier.
    4. Anne Sofie Jore & James Mitchell & Shaun P. Vahey, 2010. "Combining forecast densities from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 621-634.
    5. 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, July.
    6. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223, April.
    7. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
    8. Laura Coroneo & David Veredas, 2012. "A simple two-component model for the distribution of intraday returns," The European Journal of Finance, Taylor & Francis Journals, vol. 18(9), pages 775-797, October.
    9. Christian Kascha & Francesco Ravazzolo, 2010. "Combining inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 231-250.
    10. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, March.
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    14. 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.
    15. Nolte, Ingmar & Pohlmeier, Winfried, 2007. "Using forecasts of forecasters to forecast," International Journal of Forecasting, Elsevier, vol. 23(1), pages 15-28.
    16. Jeremy Smith & Kenneth F. Wallis, 2009. "A Simple Explanation of the Forecast Combination Puzzle," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 331-355, June.
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    More about this item

    Keywords

    Disagreement; Uncertainty; Predictive Density; Forecast Combination;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • E - Macroeconomics and Monetary Economics
    • F - International Economics

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