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Energy transition minerals: Systemic interdependence, market-specific dynamics, and the role of global risk factors in an evolving policy landscape

Author

Listed:
  • Gideon Ndubuisi
  • Christian Urom

    (PSB - Paris School of Business - HESAM - HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université)

  • Ramzi Benkraiem

    (Audencia Business School)

Abstract

This paper investigates the dynamic interdependence among six energy transition minerals (Aluminum, Cobalt, Copper, Lithium, Nickel, and Manganese). It also examines how global risk factors (climate risk, geopolitical tensions, equity market volatility, supply chain disruptions, and trade policy uncertainty) shape this interdependence and development in individual energy transition mineral (ETM) markets. Using a frequency-based dynamic connectedness framework, we find that ETMs are highly interdependent, with return connectedness (46%) exceeding volatility connectedness (40.12%). However, both are stronger in the long-term than in the short-term. Applying a quantile-based Granger causality framework, we uncover strong evidence of state-dependent and heterogeneous transmission mechanisms across both system-wide connectedness and individual mineral markets. The results show that climate risk and geopolitical risk are the primary drivers of return connectedness, albeit with distinct temporal profiles. Equity market volatility has negligible effects on connectedness, while supply chain bottlenecks and trade policy uncertainty emerge as dominant drivers of volatility connectedness. At the individual mineral level, the findings also reveal significant heterogeneity, with lithium, cobalt, and manganese showing greater sensitivity to geopolitical and supply-side shocks, while copper remains relatively insulated.

Suggested Citation

  • Gideon Ndubuisi & Christian Urom & Ramzi Benkraiem, 2026. "Energy transition minerals: Systemic interdependence, market-specific dynamics, and the role of global risk factors in an evolving policy landscape," Post-Print hal-05739122, HAL.
  • Handle: RePEc:hal:journl:hal-05739122
    DOI: 10.1016/j.enpol.2026.115450
    Note: View the original document on HAL open archive server: https://hal.science/hal-05739122v1
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    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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