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Forecasting ECB Policy Rates with Different Monetary Policy Rules

Author

Listed:
  • Ansgar Belke

    (University of Duisburg-Essen, Centre for European Policy Studies, Brussels, Belgium
    King’s College, London, UK
    Institute for the Study of Labor, Bonn, Germany)

  • Jens Klose

    (THM Business School, Giessen, Germany)

Abstract

This article compares two types of monetary policy rules – the Taylor-Rule and the Orphanides-Rule – with respect to their forecasting properties for the European Central Bank. In this respect the basic rules, results from estimates models and augmented rules are compared. Using quarterly real-time data from 1999 to the beginning of 2019, we find that an estimated Orphanides-Rule performs best in nowcasts, while it is outperformed by an augmented Taylor-Rule when it comes to forecasts. However, also a no-change rule delivers good results for forecasts, which is hard to beat for most policy rules.

Suggested Citation

  • Ansgar Belke & Jens Klose, 2019. "Forecasting ECB Policy Rates with Different Monetary Policy Rules," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(3), pages 238-252, June.
  • Handle: RePEc:fau:fauart:v:69:y:2019:i:3:p:238-252
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    Cited by:

    1. Klose, Jens, 2024. "Monetary policy rules and the ECB rotation model," The Journal of Economic Asymmetries, Elsevier, vol. 30(C).

    More about this item

    Keywords

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    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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