Dominant Drivers of National Inflation

For western economies a long-forgotten phenomenon is on the horizon: rising inflation rates. We propose a novel approach christened D^{2}ML to identify drivers of national inflation. D^{2}ML combines machine learning for model selection with time dependent data and graphical models to estimate the inverse of the covariance matrix, which is then used to identify dominant drivers. Using a dataset of 33 countries, we find that the US inflation rate and oil prices are dominant drivers of national in ation rates. For a more general framework, we carry out Monte Carlo simulations to show that our estimator correctly identifies dominant drivers.