This paper identifies U.S. monetary and fiscal dominance regimes using machine learning techniques. The algorithms are trained and verified by employing simulated data from Markov-switching DSGE models, before they classify regimes from 1968-2017 using actual U.S. data. All machine learning...

This paper identifies U.S. monetary and fiscal dominance regimes using machine learning techniques. The algorithms are trained and verified by employing simulated data from Markov-switching DSGE models, before they classify regimes from 1968-2017 using actual U.S. data. All machine learning...

In a dynamic, three-region environmental multi-sector general equilibrium model (called EMuSe), we find that carbon pricing generates a recession initially as production costs rise. Benefits from lower emissions damage materialize only in the medium to long run. A border adjustment mechanism...

In a dynamic, three-region environmental multi-sector general equilibrium model, we find that carbon pricing generates a recession initially as production costs rise. Benefits from lower emissions damage materialize only in the medium to long run. A border adjustment mechanism mitigates but does...

In this paper, we introduce a dynamic environmental multi-sector general equilibrium model to analyze the effects of financing a labor tax reduction through higher consumption, energy or emissions taxation. We find that, for sufficiently high environmental damage, using energy and emission taxes...

This paper introduces a reinforcement learning based approach to compute optimal interest rate reaction functions in terms of fulfilling inflation and output gap targets. The method is generally flexible enough to incorporate restrictions like the zero lower bound, nonlinear economy structures...

In this paper, we introduce a closed-economy version of the dynamicenvironmental multi-sector general equilibrium modelEMuSeto analyze the effects of financing a labor tax reduction through higher consumption, energy or emissions taxation.We find that, for sufficiently high environmental damage,...