4.6 Article

The estimation of influencing factors for carbon emissions based on EKC hypothesis and STIRPAT model: Evidence from top 10 countries

Journal

ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
Volume 24, Issue 9, Pages 11226-11259

Publisher

SPRINGER
DOI: 10.1007/s10668-021-01905-z

Keywords

Environmental Kuznets curve; STIRPAT model; Environmental pollution

Funding

  1. pilot program for major science, technology and innovation projects toward 2030 of China Energy Investment Corporation-Clean [GJNY2030XDXM-19-20.1]
  2. pilot program for efficient utilization of coal: Research on medium and long-term carbon emission reduction paths and energy structure optimization strategies of China [GJNY2030XDXM-19-20.1]
  3. key program of National Social Science Fund of China [21AZD067]
  4. National Research Foundation of Republic of Korea [2019K2A9A2A0602441012]
  5. National Statistical Science Research Project [2021LY055]
  6. Social Science Foundation of Jiangsu, China [19GLC015]

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The study found that an increase in per capita income significantly increases environmental pollution in the top 10 carbon emissions countries, while technology innovation contributes to carbon emissions reduction. Population, energy use, exports, and imports of information communication technology are identified as key factors of higher level of carbon emissions.
Global climate change due to greenhouse gas emissions has observable impacts on environment. Among the GHG emissions, carbon dioxide is the primary source of global climate change. In order to provide appropriate measures to control carbon emissions, it appears that there is an urgent need to address how such factors such as economic growth, exports, imports, and technology innovation affect carbon emissions in world's top carbon emitter countries. We thus employed an extended Environmental Kuznets Curve, Population, Affluence and Technology (STIRPAT) model combined with panel quantile regression to analyze the driving factors of carbon emissions across top 10 countries from 2000 to 2014. We also conducted the panel quantile regression to ascertain the relationship between variables and examine the EKC. The results obtained show that firstly, the main results are that income per capita significantly increases environmental pollution across top 10 carbon emissions countries; this study also supported the EKC hypothesis in the top 10 countries in China, USA, India, Russia, Japan, Germany, South Korea, Canada, Mexico, and South Africain China, USA, India, Russia, Japan, Germany, South Korea, Canada, Mexico, and South Africa. Second, with the top 10 countries, the STIRPAT model is verified using the panel quantile regression approach, and population, energy use, exports, and imports of information communication technology are found to be the key impact factors of higher level of carbon emissions. However, technology innovation is conducive to the carbon emissions reduction. The results obtained show that the EKC hypothesis holds across top 10 carbon emissions countries. The governments of these countries should institute policies for promoting environmental technology innovation and energy efficiency in order to achieve sustainable development of population, resources, and the environment.

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