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Interest rate assumptions and predictive accuracy of central bank forecasts

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  • Malte Knüppel

    (Deutsche Bundesbank)

  • Guido Schultefrankenfeld

    (Deutsche Bundesbank)

Abstract

The interest rate assumptions for macroeconomic forecasts differ among central banks. Common approaches are given by the assumptions that interest rates remain constant over the forecast horizon, follow a path as expected by market participants or follow a path as expected by the central bank itself. Theoretical papers such as Svensson (The instrument-rate projection under inflation targeting: the Norwegian example. Centre for European Policy Studies Working Paper (127), 2006) and Galí (J Monet Econ 58:537–550, 2011) suggest an accuracy ranking for these forecasts, from employing central bank expectations yielding the highest forecast accuracy to conditioning on constant interest rates yielding the lowest. Yet, when investigating the predictive accuracy of the Bank of England’s and the Banco Central do Brasil’s forecasts for interest rates, inflation and output growth, we hardly find any significant differences between forecasts based on the different interest rate paths. Our results suggest that the choice of the interest rate assumption appears to be of minor relevance empirically.

Suggested Citation

  • Malte Knüppel & Guido Schultefrankenfeld, 2017. "Interest rate assumptions and predictive accuracy of central bank forecasts," Empirical Economics, Springer, vol. 53(1), pages 195-215, August.
  • Handle: RePEc:spr:empeco:v:53:y:2017:i:1:d:10.1007_s00181-016-1182-5
    DOI: 10.1007/s00181-016-1182-5
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    2. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    3. Glas, Alexander & Heinisch, Katja, 2021. "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers 7/2021, Halle Institute for Economic Research (IWH).
    4. Malte Knüppel & Guido Schultefrankenfeld, 2017. "Interest rate assumptions and predictive accuracy of central bank forecasts," Empirical Economics, Springer, vol. 53(1), pages 195-215, August.
    5. Guido Schultefrankenfeld, 2020. "Appropriate monetary policy and forecast disagreement at the FOMC," Empirical Economics, Springer, vol. 58(1), pages 223-255, January.
    6. Issing, Otmar, 2013. "A new paradigm for monetary policy?," CFS Working Paper Series 2013/02, Center for Financial Studies (CFS).
    7. Monica Jain & Christopher S. Sutherland, 2020. "How Do Central Bank Projections and Forward Guidance Influence Private-Sector Forecasts?," International Journal of Central Banking, International Journal of Central Banking, vol. 16(5), pages 179-218, October.
    8. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
    9. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Jan 2024.
    10. Otmar Issing, 2013. "A New Paradigm for Monetary Policy?," International Finance, Wiley Blackwell, vol. 16(2), pages 273-288, June.
    11. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.

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    More about this item

    Keywords

    Forecast accuracy; Density forecasts; Projections;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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