Decomposing Federal Funds Rate Forecast Uncertainty Using Real-time Data
Source: Munich Personal Repec Archive
This paper uses real-time data for the U.S. to estimate out-of-sample forecast uncertainty about the Federal Funds Rate. By combining a Taylor rule with an unobserved components model of economic fundamentals the author separates forecast uncertainty into economically interpretable components that represent uncertainty about future economic conditions and uncertainty about future monetary policy. The estimation results indicate important time variation in uncertainty about the future Federal Funds Rate. The aim of this paper is to study forecast uncertainty in the U.S. money market by estimating changes in uncertainty about forecasts of the Federal Funds Rate in the U.S. Estimates of interest rate uncertainty are important for a wide range of financial market applications such as portfolio allocation, derivative pricing, risk management etc.