Directed graphs, information structure and forecast combinations: an empirical examination of US unemployment rates

Previous studies show that it is not always optimal to combine forecasts of alternative models. In this paper, we propose to use the recent advances in modeling directed acyclic graphs to study the issue of forecast combinations. In forecasting US unemployment rates, we demonstrate that the proposed procedure can be a useful tool for comparing information in rival forecasts and guiding the combination of individual forecasts.