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The connectedness of Energy Transition Metals

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  • Bastianin, Andrea
  • Casoli, Chiara
  • Galeotti, Marzio

Abstract

We assess the degree of connectedness among 16 metals that are critical for the production of clean energy technologies. These commodities are the constituents of the Energy Transition Metals (ETMs) price index maintained by the International Monetary Fund and comprise base, precious, and minor metals. We rely on Vector Autoregressive models and generalized forecast error variance decomposition to quantify spillovers among ETMs returns and volatilities. By calculating both static and dynamic measures of connectedness, we gain insight into the patterns of shock transmission between ETMs. Our static analysis reveals that base and precious metals are net shock transmitters, while minor and most battery metals are net receivers. By splitting the analysis into three groups, we find that almost half of the connectedness originates within each group, whereas the other half is due to cross-group spillovers. Moreover, we find that the system-wide connectedness of returns is positively correlated with proxies of economic activity, whereas volatility connectedness seems to be more related to global economic policy uncertainty.

Suggested Citation

  • Bastianin, Andrea & Casoli, Chiara & Galeotti, Marzio, 2023. "The connectedness of Energy Transition Metals," FEEM Working Papers 336984, Fondazione Eni Enrico Mattei (FEEM).
  • Handle: RePEc:ags:feemwp:336984
    DOI: 10.22004/ag.econ.336984
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    Cited by:

    1. Zhang, Hongwei & Li, Zongzhen & Song, Huiling & Gao, Wang, 2024. "Insight into clean energy market’s role in the connectedness between joint-consumption metals," Energy, Elsevier, vol. 302(C).
    2. Jamel Saadaoui & Russell Smyth & Joaquin Vespignani, 2024. "Ensuring the Security of the Clean Energy Transition: Examining the Impact of Geopolitical Risk on the Price of Critical Minerals," CAMA Working Papers 2024-69, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

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    More about this item

    Keywords

    Research Methods/ Statistical Methods; Resource /Energy Economics and Policy;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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