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How do financial development, energy consumption, natural resources, and globalization affect Arctic countries' economic growth and environmental quality? An advanced panel data simulation

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  • Usman, Muhammad
  • Jahanger, Atif
  • Makhdum, Muhammad Sohail Amjad
  • Balsalobre-Lorente, Daniel
  • Bashir, Adnan

Abstract

In the modern era of globalization, financial and natural resources are considered the vital indicators that intensely contribute to mitigate environmental degradation and boost economic growth. Therefore, it is necessary to realize a more significant assessment of the intricacies of determining greenhouse gas (GHG) emissions and economic growth. The current research analyzes the dynamic association between financial development, natural resources, globalization, non-renewable, and renewable energy consumption on GHG emission and economic growth for eight Arctic countries from 1990 to 2017. Additionally, the current study confirms the presence of cross-sectional dependency by employing the second-generation panel unit root, cointegration, and long-run elasticity estimation tests for robust and efficient outcomes. The findings explored that financial development and renewable energy consumption considerably condense environmental deterioration, while other potential factors like globalization, economic growth, and non-renewable energy contribute to increased environmental degradation. Moreover, financial development, natural resources, globalization, non-renewable, and renewable energy boost economic growth. Based on these empirical outcomes, several policy recommendations are formulated to overcome and control the environmental damages without hindering economic growth for the Arctic region.

Suggested Citation

  • Usman, Muhammad & Jahanger, Atif & Makhdum, Muhammad Sohail Amjad & Balsalobre-Lorente, Daniel & Bashir, Adnan, 2022. "How do financial development, energy consumption, natural resources, and globalization affect Arctic countries' economic growth and environmental quality? An advanced panel data simulation," Energy, Elsevier, vol. 241(C).
    • Handle: RePEc:eee:energy:v:241:y:2022:i:c:s036054422102764x
    DOI: 10.1016/j.energy.2021.122515
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