17 Pages Posted: 21 Apr 2011 Last revised: 5 May 2011
Date Written: April 19, 2011
A large literature lauds the benefits of central bank transparency and credibility, but when a central bank like the U.S. Federal Reserve has a dual mandate, is not specific to the extent it targets employment versus price stability, and is not specific to the magnitude interest rates should change in response to these targets, market participants must depend largely on past data to form expectations about monetary policy. We suppose market participants estimate a Taylor-like regression equation to understand the conduct of monetary policy, which likely guides their short-run and long-run expectations. When the Federal Reserve's actions deviate from its historical targets for macroeconomic variables, an environment of greater uncertainty may be the result. We quantify this degree of uncertainty by measuring and aggregating recent deviations of the federal funds rate from econometric forecasts predicted by constant gain learning. We incorporate this measure of uncertainty into a VAR model with ARCH shocks to measure the effect monetary policy uncertainty has on inflation, output growth, unemployment, and the volatility of these variables. We find that a higher degree of uncertainty regarding monetary policy is associated with greater volatility of output growth and unemployment.
Keywords: Uncertainty, Learning, Volatility, Taylor Rule, Vector Autoregression, ARCH
JEL Classification: E31, E32, E58
Suggested Citation: Suggested Citation
Murray, James and Herro, Nicholas, Dynamics of Monetary Policy Uncertainty and the Impact on the Macroeconomy (April 19, 2011). Available at SSRN: https://ssrn.com/abstract=1815462 or http://dx.doi.org/10.2139/ssrn.1815462