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Identifying the multiple nexus between geopolitical risk, energy resilience, and carbon emissions: Evidence from global data

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  • Feng, Yanchao
  • Pan, Yuxi
  • Lu, Shan
  • Shi, Jiaxin

Abstract

Under the frequent occurrence of extreme weather events and the increasingly complex geopolitical situation in recent years, how to balance the nexus between energy security, economic stability, and the achievement of sustainable development goals has gradually become the forefront of international attention. In light of this context, this paper examines the multiple nexus between geopolitical risks (GR), energy resilience (ER), and carbon emissions (PCO2) using annual panel data from 31 countries between 2000 and 2019. The second-generation unit root, cointegration tests, wavelet quantile correlation analysis, and other advanced statistical techniques are adopted to address methodological challenges effectively and avoid spurious regression. The findings consistently indicate the inhibitory effects of geopolitical risks and energy resilience on PCO2 across all quantiles and periods. And the restraining effect exhibits significant heterogeneity and asymmetry, particularly in non-emerging economies. Besides, the bidirectional causality among the three variables has been confirmed. Further, we confirm that the combined effects of energy resilience and geopolitical risks are particularly noteworthy for future carbon reduction efforts, especially in scenarios with low-ER and high-GR. In a short, the findings provide novel insights for global emissions reduction and offer specific policy recommendation to attain sustainable development goals.

Suggested Citation

  • Feng, Yanchao & Pan, Yuxi & Lu, Shan & Shi, Jiaxin, 2024. "Identifying the multiple nexus between geopolitical risk, energy resilience, and carbon emissions: Evidence from global data," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
  • Handle: RePEc:eee:tefoso:v:208:y:2024:i:c:s0040162524004591
    DOI: 10.1016/j.techfore.2024.123661
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    Cited by:

    1. Xichun Luo & Chaoming Cai & Honghao Zhao, 2024. "Study on the Evolutionary Characteristics of Spatial and Temporal Patterns and Decoupling Effect of Urban Carbon Emissions in the Yangtze River Delta Region Based on Neural Network Optimized by Aquila," Land, MDPI, vol. 14(1), pages 1-23, December.

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