A working paper published Tuesday by Norway's central bank seeks to go beyond traditional point-forecast focus to introduce representations of uncertainty when combining models.

Using a Bayesian framework, the authors, Monica Billio, Roberto Casarin, Francesco Ravazzolo and Herman K. van Dijk provide a multivariate combination approach to prediction based on a distributional state space representation of predictive densities from alternative models.

The method is assessed looking at figures for