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Assessing the uncertainty in central banks' inflation outlooks

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  • Knüppel, Malte
  • Schultefrankenfeld, Guido

Abstract

Recent research has found that macroeconomic survey forecasts of uncertainty exhibit several deficiencies, such as horizon-dependent biases and lower accuracy than simple unconditional uncertainty forecasts. We examine the inflation uncertainty forecasts from the Bank of England, the Banco Central do Brasil, the Magyar Nemzeti Bank and the Sveriges Riksbank to assess whether central banks' uncertainty forecasts might be subject to similar problems. We find that, while most central banks' uncertainty forecasts also tend to be underconfident at short horizons and overconfident at longer horizons, they are mostly not significantly biased. Moreover, they tend to be at least as precise as unconditional uncertainty forecasts from two different approaches.

Suggested Citation

  • Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdps:562018
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    Cited by:

    1. Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.

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    More about this item

    Keywords

    Density Forecasts; Fan Charts; Forecast Optimality; Forecast Accuracy;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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