Global money supply and energy and non-energy commodity prices: A MS-TV-VAR approach

Stefano Grassi (), Francesco Ravazzolo (), Joaquin Vespignani and Giorgio Vocalelli ()
Additional contact information
Stefano Grassi: Department of Economics and Finance, University of Rome Tor Vergata, Italy
Francesco Ravazzolo: @ Department of Data Science and Analytics, BI Norwegian Business School, Norway; Faculty of Economics, Free University of Bozen-Bolzano, Italy
Giorgio Vocalelli: Department of Economics, University of Verona, Italy

No BEMPS100, BEMPS - Bozen Economics & Management Paper Series from Faculty of Economics and Management at the Free University of Bozen

Abstract: This paper shows that the impact of the global money supply is disproportionally high for energy than for non-energy commodities prices. An increase in the global money supply for energy commodity prices results mainly in demand-pull inflation. However, for non-energy commodity prices, an increase in global money supply leads to demand-pull and cost-push inflation, as energy is a key input for non-energy commodities. To quantify this effect, we use a Markov switching model with time-varying transition probabilities. This model considers periods of slow, moderate, and fast global money supply growth. We find that the response to global money supply shocks is almost double for energy than for non-energy commodity prices. We also find heterogeneous responses for energy and non-energy commodities under different regimes.

Keywords: Global money supply; Energy and non-energy prices; Markov-Switching VAR. (search for similar items in EconPapers)
JEL-codes: C54 E31 F01 Q43 (search for similar items in EconPapers)
Pages: [38 pages]
Date: 2023-08
New Economics Papers: this item is included in nep-ene and nep-mon
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https://repec.unibz.it/bemps100.pdf (application/pdf)

Related works:
Working Paper: Global Money Supply and Energy and Non-Energy Commodity Prices: A MS-TV-VAR Approach (2023)
Working Paper: Global money supply and energy and non-energy commodity prices: A MS-TV-VAR approach (2023)
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