Dominant Drivers of National Inflation

Jan Ditzen and Francesco Ravazzolo ()
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Francesco Ravazzolo: Free University of Bozen-Bolzano, Italy

No BEMPS97, BEMPS - Bozen Economics & Management Paper Series from Faculty of Economics and Management at the Free University of Bozen

Abstract: 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.

Keywords: Time Series; Machine Learning; LASSO; High dimensional data; Dominant Units; Inflation. (search for similar items in EconPapers)
JEL-codes: C22 C23 C55 (search for similar items in EconPapers)
Pages: [35 pages]
Date: 2022-12
New Economics Papers: this item is included in nep-big, nep-cmp, nep-ecm and nep-mon
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Related works:
Working Paper: Dominant Drivers of National Inflation (2022)
Working Paper: Dominant Drivers of National Inflation (2022)
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