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Investigating the role of globalization, and energy consumption for environmental externalities: Empirical evidence from developed and developing economies

Abstract Achieving sustainable environmental development, while further avoiding environmental degradation is an unprecedented challenge for policymakers. This article aims to explore whether the Environmental Kuznets Curve (EKC) hypothesis holds if the relevant carbon emissions modelling approach includes both energy consumption and the Konjunkturforschungsstelle (KOF) globalization index. The analysis is performed through panel methods and for 67 developed and developing countries, spanning the period 1971–2018. The empirical results demonstrate that there is a significant and positive association between globalization and carbon emissions. At the same time, higher GDP increases carbon emissions, while higher coal energy also leads to higher emissions, with the coefficient of the squared GDP turning out to be negative, which lends amble support to the validity of the EKC hypothesis. The findings of this article might be helpful in policy making regarding overall energy structure, carbon emissions, and globalization trends in developing and developed countries.
- Scottish Church College India
- Central South University China (People's Republic of)
- University of Piraeus Greece
- Süleyman Şah University Turkey
- Süleyman Şah University Turkey
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citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).182 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 0.1%
