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Application of Threshold Regression Analysis to Study the Impact of Clean Energy Development on China’s Carbon Productivity

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  • Dongri Han

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China)

  • Tuochen Li

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China)

  • Shaosong Feng

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China)

  • Ziyi Shi

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China)

Abstract

Facing the pressures of international carbon emission reduction, the transformation into a low-carbon economy has become a common issue of all countries. The core of developing a low-carbon economy is to increase carbon productivity, which can be measured as the economic benefits of unit carbon emissions. Therefore, using province-level panel data in China from 2009 to 2017, we analyze the carbon productivity level of each region, and empirically investigate the threshold effect of clean energy development on carbon productivity under different technological innovation levels. The results show that the carbon productivity is rising, and China’s economic development pattern has been shifting towards low-carbon and sustainable development. Furthermore, the driving force of clean energy development on carbon productivity is not monotonously increasing (decreasing) but is a “double threshold effect” of technological innovation capability. Finally, based on the research conclusions and realistic requirements of China’s low-carbon economic transformation, this paper proposes improving carbon productivity from the aspects of innovation capability improvement and institutional guarantee.

Suggested Citation

  • Dongri Han & Tuochen Li & Shaosong Feng & Ziyi Shi, 2020. "Application of Threshold Regression Analysis to Study the Impact of Clean Energy Development on China’s Carbon Productivity," IJERPH, MDPI, vol. 17(3), pages 1-16, February.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:3:p:1060-:d:317906
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    Cited by:

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