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May 7, 2026Resources0 citationsOpen Access

Dynamic Interlinkages Between Energy, Food and Metal Prices Under the Geopolitical Tension

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LSLinda Karlina SariMBMuchamad BachtiarNANoer Azam Achsani

Key Points

  • The paper investigates the relationships among energy, food, and metal prices in the context of geopolitical tensions.
  • Daily data from January 2022 to July 2025 was used.
  • Correlation analysis and Granger causality tests were performed.
  • A Vector Error Correction Model was employed to analyze short- and long-run dynamics.
  • Impulse response functions assessed robustness across various geopolitical event windows.
  • Geopolitical risk significantly influences key commodity prices, including food prices and metal prices.
  • Copper and wheat demonstrate specific transmission patterns under geopolitical stress.
  • Gold mainly acts as a net receiver of macroeconomic uncertainty rather than a systemic transmitter.

Abstract

This study examines the dynamic interlinkages among energy, food, and metal commodity markets under geopolitical tensions using daily data from January 2022 to July 2025. The empirical framework integrates correlation analysis, Granger causality tests, and a Vector Error Correction Model (VECM) to capture both short- and long-run transmission mechanisms, with robustness assessed through impulse response functions, forecast error variance decomposition, and a Diebold–Yilmaz connectedness analysis across three structurally distinct geopolitical event windows. The results reveal asymmetric and sector-specific transmission patterns in which geopolitical risk significantly influences key commodity prices—particularly WTI crude oil, wheat, copper, and aluminium—confirming its role as a primary external shock driver. WTI emerges as the dominant transmitter of shocks, while industrial metals exhibit strong internal connectedness. Critically, gold’s role proves to be conditional and context-dependent: within an integrated energy–food–metal network under geopolitical stress, it functions primarily as a net receiver and passive absorber of macroeconomic uncertainty rather than as a systemic transmitter, a finding that complements, rather than contradicts, its established safe-haven role in financial asset pricing frameworks. These findings are subject to limitations, including reliance on futures price data and a linear VECM framework that may not fully capture nonlinear or regime-dependent dynamics.

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Cite This Study

Sari et al. (2026) studied this question.

synapsesocial.com/papers/69fbefef164b5133a91a4215https://doi.org/10.3390/resources15050061
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