We explore whether modelling parameter time variation improves the point, interval and density forecasts of nine major exchange rates vis-a-vis the US dollar over the period 1976-2015. We find that modelling parameter time variation is needed for an accurate calibration of forecast confidence...

We document that expansionary monetary policy shocks are less effective at stimulating output and investment in periods of high volatility compared to periods of low volatility, using a regime-switching vector autoregression. The lower effectiveness of monetary policy can be linked to weaker...

We investigate whether frictions in US financial markets amplify the international propagation of US financial shocks. The dynamics of the US economy is modeled jointly with global macroeconomic and financial variables using a threshold vector autoregression that allows us to capture...

The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...

Temporal aggregation in general introduces a moving average (MA) component in the aggregated model. A similar feature emerges when not all but only a few variables are aggregated, which generates a mixed frequency model. The MA component is generally neglected, likely to preserve the possibility...