This paper provides tools for partial identification inference and sensistivity analysis in a general class of semiparametric models. The main working assumption is that the finite-dimensional parameter of interest and the possibility infinite-dimensional nuisance parameter are identified...

This paper puts forward a Bayesian version of the global vector autoregressive model (B-GVAR) that accommodates international linkages across countries in a system of vec-tor autoregressions. We compare the predictive performance of B-GVAR models for the one- and four-quarter ahead forecast...