Dominant Drivers of National Inflation

In the new CAMP working paper 08/2022, Ditzen and Ravazzolo propose a novel approach christened D2ML to identify drivers of national inflation. D2ML 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, they find that the US inflation rate and oil prices are dominant drivers of national inflation rates. For a more general framework, they carry out Monte Carlo simulations to show that our estimator correctly identifies dominant drivers.

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