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The empirical (ir)relevance of the interest rate assumption for central bank forecasts

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  • Knüppel, Malte
  • Schultefrankenfeld, Guido

Abstract

The interest rate assumptions for macroeconomic forecasts differ considerably among central banks. Common approaches are given by the assumption of constant interest rates, interest rates expected by market participants, or the central bank's own interest rate expectations. From a theoretical point of view, the latter should yield the highest forecast accuracy. The lowest accuracy can be expected from forecasts conditioned on constant interest rates. However, when investigating the predictive accuracy of the forecasts for interest rates, inflation and output growth made by the Bank of England and the Banco do Brasil, we hardly find any significant differences between the forecasts based on different interest assumptions. We conclude that the choice of the interest rate assumption, while being a major concern from a theoretical point of view, appears to be at best of minor relevance empirically.

Suggested Citation

  • Knüppel, Malte & Schultefrankenfeld, Guido, 2013. "The empirical (ir)relevance of the interest rate assumption for central bank forecasts," Discussion Papers 11/2013, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdps:112013
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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. Glas, Alexander & Heinisch, Katja, 2021. "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers 7/2021, Halle Institute for Economic Research (IWH).
    3. 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.
    4. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    5. 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.
    6. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Jan 2024.
    7. Otmar Issing, 2013. "A New Paradigm for Monetary Policy?," International Finance, Wiley Blackwell, vol. 16(2), pages 273-288, June.
    8. Guido Schultefrankenfeld, 2020. "Appropriate monetary policy and forecast disagreement at the FOMC," Empirical Economics, Springer, vol. 58(1), pages 223-255, January.
    9. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
    10. Issing, Otmar, 2013. "A new paradigm for monetary policy?," CFS Working Paper Series 2013/02, Center for Financial Studies (CFS).
    11. 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.

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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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