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Disagreement versus uncertainty: Evidence from distribution forecasts

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  • Krüger, Fabian
  • Nolte, Ingmar

Abstract

We use a cross-section of economic survey forecasts to predict the distribution of US macro variables in real time. This generalizes the existing literature, which uses disagreement (i.e., the cross-sectional variance of survey forecasts) to predict uncertainty (i.e., the conditional variance of future macroeconomic quantities). Our results show that cross-sectional information can be helpful for distribution forecasting, but this information needs to be modeled in a statistically efficient way in order to avoid overfitting. A simple one-parameter model which exploits time variation in the cross-section of survey point forecasts is found to perform well in practice.

Suggested Citation

  • Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    • Handle: RePEc:eee:jbfina:v:72:y:2016:i:s:p:s172-s186
    DOI: 10.1016/j.jbankfin.2015.05.007
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    More about this item

    Keywords

    Forecasting; Survey data; Density forecasting; Disagreement; Uncertainty;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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