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Decomposing Federal Funds Rate forecast uncertainty using real-time data

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  • Martin Mandler

    (University of Giessen)

Abstract

Using real-time data I estimate out-of-sample forecast uncertainty about the Federal Funds Rate. Combining a Taylor rule with a model of economic fundamentals I disentangle economically interpretable components of forecast uncertainty: uncertainty about future economic conditions and uncertainty about future monetary policy. Uncertainty about U.S. monetary policy fell to unprecedented low levels in the 1980s and remained low while uncertainty about future output and inflation declined only temporarily. This points to an important role of increased predictability of monetary policy in explaining the decline in macroeconomic volatility in the U.S. since the mid-1980s.

Suggested Citation

  • Martin Mandler, 2009. "Decomposing Federal Funds Rate forecast uncertainty using real-time data," MAGKS Papers on Economics 200947, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  • Handle: RePEc:mar:magkse:200947
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    References listed on IDEAS

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    Cited by:

    1. Pierdzioch, Christian & Rülke, Jan-Christoph, 2014. "Central banks’ interest rate projections and forecast coordination," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 130-137.

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    More about this item

    Keywords

    monetary policy reaction function; interest rate uncertainty; state-space model;
    All these keywords.

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • 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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