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Is There Any Difference in the Effect of Different R and D Sources on Carbon Intensity in China?

Author

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  • Feng Feng

    (School of Management, University of Science and Technology of China, Hefei 230026, China)

  • Linlin Peng

    (School of Management, University of Science and Technology of China, Hefei 230026, China)

Abstract

In recent decades, climate change, mostly caused by CO 2 emissions, has become a critical issue of concern to people worldwide. It is necessary for countries all around the world to reduce carbon emissions. China, as the world’s largest carbon emitter, is under great pressure to implement carbon-reduction strategies. Technological progress plays a crucial role in balancing environmental and economic development. The main objective of this work is to empirically compare the effects of government and enterprise research and development (R and D) on carbon-emission reduction using the panel data of 30 Chinese provinces from 2009 to 2016. The effects of both government and enterprise R and D investment on carbon intensity are compared in detail through a linear model and a threshold-regression model. Linear-regression results shows that both government and enterprise R and D decrease carbon intensity, while enterprise investment tends to be more instant. Further threshold-regression results indicate that the effects of government and enterprise R and D on carbon intensity are different in different urbanization stages. Guiding enterprises to invest in R and D in medium-developing areas, and increasing government support and subsidies for R and D activities in underdeveloped areas should be an important goal of the government policies.

Suggested Citation

  • Feng Feng & Linlin Peng, 2019. "Is There Any Difference in the Effect of Different R and D Sources on Carbon Intensity in China?," Sustainability, MDPI, vol. 11(6), pages 1-12, March.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1701-:d:215845
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    2. Jugend, Daniel & Fiorini, Paula De Camargo & Armellini, Fabiano & Ferrari, Aline Gabriela, 2020. "Public support for innovation: A systematic review of the literature and implications for open innovation," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
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    4. Qifan Guan, 2023. "Decomposing and Decoupling the Energy-Related Carbon Emissions in the Beijing–Tianjin–Hebei Region Using the Extended LMDI and Tapio Index Model," Sustainability, MDPI, vol. 15(12), pages 1-17, June.

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