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

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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 mostly in demand-pull inflation. However, for non-energy commodity prices, an increase in global money supply results in demand-pull inflation and cost-push inflation, as energy is a critical input for non-energy commodities. We introduce a Markov Switching framework with timevarying transition probabilities to quantify this effect. This macro-econometric model accounts for periods when the global money supply growth is slow, moderate, and fast. We find that the response to global money supply shocks is higher for energy than for non-energy commodity prices. We also find heterogeneous responses for both energy and non-energy commodities across regimes.

Suggested Citation

  • Grassi, Stefano & Ravazzolo, Francesco & Vespignani, Joaquin & Vocalelli, Giorgio, 2023. "Global money supply and energy and non-energy commodity prices: A MS-TV-VAR approach," Working Papers 2023-01, University of Tasmania, Tasmanian School of Business and Economics.
    • Handle: RePEc:tas:wpaper:47658
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    1. Jeffrey A. Frankel, 1984. "Commodity Prices and Money: Lessons from International Finance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(5), pages 560-566.
    2. Kaufmann, Sylvia, 2015. "K-state switching models with time-varying transition distributions—Does loan growth signal stronger effects of variables on inflation?," Journal of Econometrics, Elsevier, vol. 187(1), pages 82-94.
    3. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. Van Dijk, 2016. "Interconnections Between Eurozone and us Booms and Busts Using a Bayesian Panel Markov‐Switching VAR Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1352-1370, November.
    4. Lutz Kilian, 2008. "The Economic Effects of Energy Price Shocks," Journal of Economic Literature, American Economic Association, vol. 46(4), pages 871-909, December.
    5. Hamilton, James D., 2011. "Nonlinearities And The Macroeconomic Effects Of Oil Prices," Macroeconomic Dynamics, Cambridge University Press, vol. 15(S3), pages 364-378, November.
    6. Meller, Barbara & Metiu, Norbert, 2017. "The synchronization of credit cycles," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 98-111.
    7. M. Ayhan Kose & Eswar S. Prasad & Marco E. Terrones, 2003. "How Does Globalization Affect the Synchronization of Business Cycles?," American Economic Review, American Economic Association, vol. 93(2), pages 57-62, May.
    8. Ratti, Ronald A & Vespignani, Joaquin L., 2012. "Why are crude oil prices high when global activity is weak?," MPRA Paper 43777, University Library of Munich, Germany.
    9. Sylvia Kaufmann & Sylvia Frühwirth‐Schnatter, 2002. "Bayesian analysis of switching ARCH models," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(4), pages 425-458, July.
    10. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    11. Mr. Reginald Darius, 2010. "Can Global Liquidity Forecast Asset Prices?," IMF Working Papers 2010/196, International Monetary Fund.
    12. Silvia Miranda-Agrippino & Hélène Rey, 2020. "U.S. Monetary Policy and the Global Financial Cycle," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(6), pages 2754-2776.
    13. Sousa, Joao Miguel & Zaghini, Andrea, 2007. "Global monetary policy shocks in the G5: A SVAR approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(5), pages 403-419, December.
    14. Ratti, Ronald A. & Vespignani, Joaquin L., 2015. "Commodity prices and BRIC and G3 liquidity: A SFAVEC approach," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 18-33.
    15. Moritz Schularick & Alan M. Taylor, 2012. "Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008," American Economic Review, American Economic Association, vol. 102(2), pages 1029-1061, April.
    16. John Taylor, 2013. "International Monetary Policy Coordination: Past, Present and Future," Discussion Papers 12-034, Stanford Institute for Economic Policy Research.
    17. Hamilton, James D, 1983. "Oil and the Macroeconomy since World War II," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 228-248, April.
    18. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
    19. Nalan Baştürk & Cem Çakmakli & S. Pinar Ceyhan & Herman K. Van Dijk, 2014. "Posterior‐Predictive Evidence On Us Inflation Using Extended New Keynesian Phillips Curve Models With Non‐Filtered Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1164-1182, November.
    20. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    21. Matteo Ciccarelli & Alessandro Rebucci, 2003. "BVARs: A Survey of the Recent Literature with an Application to the European Monetary System," Rivista di Politica Economica, SIPI Spa, vol. 93(5), pages 47-112, September.
    22. Rey, Hélène, 2015. "Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence," CEPR Discussion Papers 10591, C.E.P.R. Discussion Papers.
    23. Tomohiro Ando, 2007. "Bayesian predictive information criterion for the evaluation of hierarchical Bayesian and empirical Bayes models," Biometrika, Biometrika Trust, vol. 94(2), pages 443-458.
    24. David Ardia, 2009. "Bayesian estimation of a Markov-switching threshold asymmetric GARCH model with Student-t innovations," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 105-126, March.
    25. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
    26. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 47-75.
    27. Belke, Ansgar & Orth, Walter & Setzer, Ralph, 2010. "Liquidity and the dynamic pattern of asset price adjustment: A global view," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1933-1945, August.
    28. Joao Sousa & Andrea Zaghini, 2008. "Monetary policy shocks in the euro area and global liquidity spillovers," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 13(3), pages 205-218.
    29. Mr. Matteo Ciccarelli & Mr. Alessandro Rebucci, 2003. "Bayesian Vars: A Survey of the Recent Literature with An Application to the European Monetary System," IMF Working Papers 2003/102, International Monetary Fund.
    30. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    31. Jeffrey A. Frankel & Gikas A. Hardouvelis, 1983. "Commodity Prices, Overshooting, Money Surprises, and Fed Credibility," NBER Working Papers 1121, National Bureau of Economic Research, Inc.
    32. Dimitris Politis & Halbert White, 2004. "Automatic Block-Length Selection for the Dependent Bootstrap," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 53-70.
    33. Herrera, Ana María & Karaki, Mohamad B. & Rangaraju, Sandeep Kumar, 2019. "Oil price shocks and U.S. economic activity," Energy Policy, Elsevier, vol. 129(C), pages 89-99.
    34. Beckmann, Joscha & Belke, Ansgar & Czudaj, Robert, 2014. "Does global liquidity drive commodity prices?," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 224-234.
    35. Ratti, Ronald A. & Vespignani, Joaquin L., 2013. "Why are crude oil prices high when global activity is weak?," Economics Letters, Elsevier, vol. 121(1), pages 133-136.
    36. Hans-Martin Krolzig, 2000. "Predicting Markov-Switching Vector Autoregressive Processes," Economics Series Working Papers 2000-W31, University of Oxford, Department of Economics.
    37. Jeffrey A. Frankel, 1986. "Expectations and Commodity Price Dynamics: The Overshooting Model," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(2), pages 344-348.
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    More about this item

    Keywords

    global money supply; energy and non-energy prices; Markov-Switching VAR;
    All these keywords.

    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • F01 - International Economics - - General - - - Global Outlook
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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