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

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A Correction to this article was published on 02 March 2022

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Abstract

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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Funding

This work is supported by the pilot programs for major science, technology and innovation projects toward 2030 of China Energy Investment Corporation- Clean and efficient utilization of coal: Research on medium and long-term carbon emission reduction paths and energy structure optimization strategies of China (Grant No. GJNY2030XDXM-19–20.1), the key program of National Social Science Fund of China (Grant No. 21AZD067), National Research Foundation of Republic of Korea (No. 2019K2A9A2A0602441012), National Statistical Science Research Project (2021LY055) and Social Science Foundation of Jiangsu, China (Grant No. 19GLC015).

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Authors and Affiliations

  1. School of Business, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Ellen Thio, MeiXuen Tan, Liang Li & Bangzhu Zhu

  2. Research Institute for Environment and Health, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Liang Li

  3. College of Economic and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Muhammad Salman

  4. School of Management, Jiangsu University, Zhenjiang, 212013, China

    Xingle Long

  5. School of Finance and Economics, Jiangsu University, Zhenjiang, 212013, China

    Huaping Sun

Authors
  1. Ellen Thio
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  2. MeiXuen Tan
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  3. Liang Li
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  4. Muhammad Salman
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  5. Xingle Long
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  6. Huaping Sun
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  7. Bangzhu Zhu
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Contributions

ET contributed to original draft preparation, data collection, formal analysis, review and editing; MT contributed to formal analysis, writing—review and editing; LL contributed to rewriting, conceptualization, methodology, writing—review and editing and supervision; MS contributed to validation, writing—review and editing; XL and HS and BZ contributed to writing—review and editing.

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Correspondence to Liang Li.

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Thio, E., Tan, M., Li, L. et al. The estimation of influencing factors for carbon emissions based on EKC hypothesis and STIRPAT model: Evidence from top 10 countries. Environ Dev Sustain 24, 11226–11259 (2022). https://doi.org/10.1007/s10668-021-01905-z

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