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Are carbon emissions trading and green financial instruments synergistic? -Comprehensive quantitative research based on content analysis

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  • Hongjian Yu
  • Xiufan Zhang

Abstract

Coordinating policies is an essential guarantee for carbon emission reduction and sustainable development. Based on the theoretical framework of the policy paradigm, we quantitatively analyze 266 policy documents on promoting carbon emission trading and green financial policies from 2011 to 2022 using the content analysis research method. Based on the matching network of "policy objectives-policy tools," we analyze the synergistic characteristics of carbon emission trading policies and green financial policies in promoting carbon emission reduction targets and reveal the matching mode of "objectives-tools" of green financial policies by using social network analysis. It is found that, first, from the perspective of policy objectives, the main policy objectives of carbon emissions trading are to promote green innovation of enterprises, and the main policy objectives of green finance are to promote green development, which reflects the consistency and endogenous motivation of policy objectives. Secondly, command-control and market incentive policy tools are the main policy tools in the structure of policy tools. The proportion of public participation policy tools is small, and there is a structural asymmetry. Third, carbon emissions trading tools focus on supervision, adjustment, and platform construction. The green financial policy tools have the characteristics of guidance, public welfare, and externality. The two constitute a complementary, embedded, and integrated ’ double synergy ’ carbon emission reduction policy. Based on this, this paper puts forward some suggestions to promote policy coordination and provides a reference for China to achieve the dual carbon goal.

Suggested Citation

  • Hongjian Yu & Xiufan Zhang, 2024. "Are carbon emissions trading and green financial instruments synergistic? -Comprehensive quantitative research based on content analysis," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-30, March.
    • Handle: RePEc:plo:pone00:0298601
    DOI: 10.1371/journal.pone.0298601
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