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New Insights into the Impact of Local Corruption on China’s Regional Carbon Emissions Performance Based on the Spatial Spillover Effects

Author

Listed:
  • Xianpu Xu

    (School of Business, Xiangtan University, Xiangtan 411105, China)

  • Bijiao Yi

    (School of Business, Xiangtan University, Xiangtan 411105, China)

Abstract
The increase of carbon dioxide emissions (CO 2 ) is one of the greatest challenges facing mankind today. Although some studies have examined the factors influencing carbon emissions from various angles, research on the nexus between corruption and carbon pollution has not received enough attention. In this context, using provincial panel data for China from 2003 to 2017, this paper adopts spatial econometric methods to explore the effect and mechanisms of corruption on CO 2 emissions. The results indicate that: (1) China’s carbon emissions present significant spatial agglomeration characteristics; (2) Corruption not only directly exacerbates CO 2 emissions, but also, and more importantly, has a positive and significant spatial spillover effect on pollutant emissions, implying that corruption stimulates the production of carbon dioxide on a regional level, as well as in neighboring regions. As an internal mechanism, the influence of corruption on CO 2 emissions mainly reflects the “local competition” and “innovation distortion” effects; (3) Improvements at the economic level, the increase in FDI, and upgrades to the structure of industry can promote carbon emission reductions, while R&D investment has an inhibitory effect. Finally, this paper proposes countermeasures to promote sustainable and high-quality development of China’s economy by strengthening regional collaboration and intensifying institutional supervision.

Suggested Citation

  • Xianpu Xu & Bijiao Yi, 2022. "New Insights into the Impact of Local Corruption on China’s Regional Carbon Emissions Performance Based on the Spatial Spillover Effects," Sustainability, MDPI, vol. 14(22), pages 1-26, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15310-:d:976363
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