This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require...

This paper investigates the global macroeconomic consequences of falling oil prices due to the oil revolution in the United States, using a Global VAR model estimated for 38 countries/regions over the period 1979Q2 to 2011Q2. Set-identification of the U.S. oil supply shock is achieved through...

We nowcast and forecast Austrian economic activity, namely real gross domestic product (GDP), consumption and investment, which are available at a quarterly frequency. While nowcasting uses data up to (and including) the quarter to be predicted, forecasting uses only data up to the previous...

This paper provides new indices of global macroeconomic uncertainty and investigates the cross-country transmission of uncertainty using a global vector autoregressive (GVAR) model. The indices measure the dispersion of forecasts that results from parameter uncertainty in the GVAR. Relying on...

We propose an approach for jointly measuring global macroeconomic uncertainty and bilateral spillovers of uncertainty between countries using a global vector autoregressive (GVAR) model. Over the period 2000Q1-2020Q4, our global index is able to summarize a variety of uncertainty measures, such...

We identify variables that help explain the persistent weakness of the Norwegian krone since 2016 within a fully simultaneous model of the underlying process driving the krone-euro exchange rate. In addition to a set of fundamental variables we consider non-traditional explanatory variables...