We propose an approach for Bayesian inference in \TV SVARs identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant \TV SVARs in which the prior and posterior densities of any sequence of structural parameters belonging to the class are invariant to...

Recursively identified vector autoregressive (VAR) models often lead to a counterintuitive response of prices (and output) shortly after a monetary policy shock. To overcome this problem, we propose to estimate the VAR parameters under the restriction that economic theory is not violated, while...

Recursively identified vector autoregressive (VAR) models often lead to a counterintuitive response of prices (and output) shortly after a monetary policy shock. To overcome this problem, we propose to estimate the VAR parameters under the restriction that economic theory is not violated, while...

We fit a Bayesian time-varying parameters structural VAR with stochastic volatility to the Federal Funds rate, GDP deflator inflation, real GDP growth, and the rate of growth of M2. We identify 4 shocks–monetary policy, demand non-policy, supply, and money demand–by imposing sign...

Policy counterfactuals based on estimated structural VARs routinely suggest that bringing Alan Greenspan back in the 1970s’ United States would not have prevented the Great Inflation. We show that a standard policy counterfactual suggests that the Bundesbank–which is near-universally...

We characterise the evolution of the U.S. unemployment-inflation trade-off since the late XIX century era via a Bayesian time-varying parameters structural VAR. The Great Inflation episode appears as historically unique along several dimensions. In particular, the shape of the ‘Phillips...

This paper estimates a time-varying AR-GARCH model of inflation producing measures of inflation uncertainty for the euro area, and investigates their linkages in a VAR framework, also allowing for the possible impact of the policy regime change associated with the start of EMU in 1999. The main...