Thanks to the increasing availability of granular, yet high-dimensional, firm level data, machine learning (ML) algorithms have been successfully applied to address multiple research questions related to firm dynamics. Especially supervised learning (SL), the branch of ML dealing with the...

This paper introduces the term structure of interest rates into a medium-scale DSGE model. This extension results in a multi-period forecasting model that is estimated under both adaptive learning and rational expectations. Term structure information enables us to characterize agents'...

This chapter has described tools to improve forecasting of trends and of the effects of interventions. Among these methods, role playing and rule-based forecasting have seldom been used lot environmental forecasting. Role playing is appropriate when forecasting the outcome of a situation...