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Energy Consumption, Economic Growth, and Environmental Degradation in OECD Countries

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  • Dong Kyun Kim

Abstract

The world is governed by the issues of environmental degradation, climate control, pollutant emissions and other such phenomena due to the increasing dilapidation of environmental resources. For a while now, the focus has been on the production of green technologies, clean energy solutions and the development of a sustainable module that will aid in the restoration and protection of the environment. In this scenario, the dependence on consumption patterns of energy, economic growth (EG), and environmental degradation (ED) have become the focus of many researchers and policymakers. The Organization for Economic Co-operation and Development (OECD) countries are understandably characterized as the fastest developing nations of the world. However, literature evaluating the influence of energy consumption (EC) and economic growth (EG) on environmental degradation has presented conflicting results. This study aims to solve this conflict by presenting a panel dataset comprised of 35 OECD between 2000–2014. The Generalized Method of Moments Panel Vector Autoregression (GMM-PVAR) has been used to estimate the impact and causal relationship between the variables. The results of the study indicate that EG and consumption patterns of energy are vital for the improvement of the environmental performance of the firms. In contrast to other empirical literature, this study finds that the economic development of the country or countries and the patterns of consumption have started to coagulate with set environmental performance parameters. Environmental policies, consumption patterns and plans for EG are all being aligned in OECD countries. The results of this study are robust, as different methods for the evaluation have been used.

Suggested Citation

  • Dong Kyun Kim, 2020. "Energy Consumption, Economic Growth, and Environmental Degradation in OECD Countries," Asian Journal of Economics and Empirical Research, Asian Online Journal Publishing Group, vol. 7(2), pages 242-250.
  • Handle: RePEc:aoj:ajeaer:v:7:y:2020:i:2:p:242-250:id:2193
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    Cited by:

    1. Kahia, Montassar & Moulahi, Tarek & Mahfoudhi, Sami & Boubaker, Sabri & Omri, Anis, 2022. "A machine learning process for examining the linkage among disaggregated energy consumption, economic growth, and environmental degradation," Resources Policy, Elsevier, vol. 79(C).

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