Adventures at the Zero Lower Bound: A Bayesian Time-Varying Parameter Vector Autoregressive Analysis of Monetary Policy Uncertainty Shocks

Using survey-based measures of future interest rate expectations from the Blue Chip Economic Indicators and the Survey of Professional Forecasters, we examine the relationship between monetary policy uncertainty, captured as the dispersion of interest rate forecasts, and fluctuations in real economic activity and core inflation. We use a flexible time-varying parameter vector autoregression (TVP-VAR) model to clearly isolate the dynamic effects of shocks to monetary policy uncertainty. To further study possible a possible nonlinear relationship between monetary policy uncertainty and the macroeconomic aggregates, we extract the impulse-response functions (IRF’s) estimated at each quarter in the time series, and use a multi-variate regression with various measures of the shape of the IRF’s and the level of monetary policy uncertainty at that quarter in the TVP-VAR model to gauge the relationship between the effectiveness of traditional monetary policy (shocks to the Federal Funds rate), forward guidance (shocks to expected interest rates) and uncertainty. The results show that monetary policy uncertainty can have a quantitatively significant impact on output, with a one standard deviation shock to uncertainty associated with a 0.6% rise in unemployment. The indirect effects are more substantial, with a one standard deviation increase in monetary policy uncertainty associated with a 23% decrease in the maximum response of unemployment to a forward guidance episode (interest rate expectations shock). This evidence points to the importance of managing monetary policy uncertainty (clear and direct forward guidance) as a key policy tool in both stimulating economic activity as well as propagating other monetary policy through the macroeconomy