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Decomposing Federal Funds Rate forecast uncertainty using time-varying Taylor rules and real-time data

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  • Mandler, Martin

Abstract

This paper studies uncertainty about out-of-sample interest rate forecasts implied by an estimated Taylor rule. It is shown that the Taylor rule leads to a decomposition of forecast uncertainty into an element that depends on uncertainty about the future state of the economy and another element that is related to uncertainty about the monetary policy reaction function of the Federal Reserve. Uncertainty about one-quarter ahead Federal Funds Rate forecasts from 1975 to 2007 is estimated and analyzed using a real-time data set for the U.S.

Suggested Citation

  • Mandler, Martin, 2012. "Decomposing Federal Funds Rate forecast uncertainty using time-varying Taylor rules and real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 23(2), pages 228-245.
  • Handle: RePEc:eee:ecofin:v:23:y:2012:i:2:p:228-245
    DOI: 10.1016/j.najef.2012.01.003
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    5. Beckmann, Joscha, 2013. "Nonlinear adjustment, purchasing power parity and the role of nominal exchange rates and prices," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 176-190.

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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
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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