We use a novel disaggregate sectoral euro area data set with a regional breakdown to investigate price changes and suggest a new method to extract factors from over-lapping data blocks. This allows us to separately estimate aggregate, sectoral, country-specific and regional components of price...

We use a novel disaggregate sectoral euro area dataset with a regional breakdown that allows explicit estimation of the sectoral component of price changes (rather than interpreting the idiosyncratic component as sectoral as done in other papers). Employing a new method to extract factors from...

We use a novel disaggregate sectoral euro area dataset with a regional breakdown that allows explicit estimation of the sectoral component of price changes (rather than interpreting the idiosyncratic component as sectoral as done in other papers). Employing a new method to extract factors from...

Measuring and displaying uncertainty around path-forecasts, i.e. forecasts made in period T about the expected trajectory of a random variable in periods T+1 to T+H is a key ingredient for decision making under uncertainty. The probabilistic assessment about the set of possible trajectories that...

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...