We propose a straightforward algorithm to estimate large Bayesian time-varying parameter vector autoregressions with mixture innovation components for each coefficient in the system. The computational burden becomes manageable by approximating the mixture indicators driving the time-variation in...

This paper develops a global vector autoregressive (GVAR) model with time-varying parameters and stochastic volatility to analyze whether international spillovers of US monetary policy have changed over time. The proposed model allows assessing whether coefficients evolve gradually over time or...

In this paper, we use a Bayesian global vector autoregressive model to analyze the macroeconomic effects of a flattening of euro area yield curves. Our findings indicate positive effects on real activity and prices, both within the euro area as well as in neighboring economies. Spillovers...