This paper formalizes the process of updating the nowcast and forecast on output and inflation as new releases of data become available. The marginal contribution of a particular release for the value of the signal and its precision is evaluated by computing "news" on the basis of an evolving...

This paper formalizes the process of updating the nowcast and forecast on output and inʿation as new releases of data become available. The marginal contribution of a particular release for the value of the signal and its precision is evaluated by computing "news" on the basis of an evolving...

This paper formalizes the process of updating the nowcast and forecast on out-put and inflation as new releases of data become available. The marginal contribution of a particular release for the value of the signal and its precision is evaluated by computing news on the basis of an evolving...

Not so much and we should not, at least not yet. JEL Classification: E32, C33, C53, F2, F43

This paper shows how large-dimensional dynamic factor models are suitable for structural analysis. We establish sufficient conditions for identification of the structural shocks and the associated impulse response functions. In particular, we argue that, if the data follow an approximate factor...

This paper shows that Vector Autoregression with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results by De Mol, Giannone, and Reichlin (2008) and show that, when the degree of shrinkage is set in relation to the cross-sectional dimension, the forecasting...

Global financial integration unlocks a huge potential for international risk sharing. We examine the degree to which international equity holdings act as a risk sharing device in industrial and emerging economies. We split equity returns into investment income (dividend distribution) and capital...