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Can R&D Intensity Reduce Carbon Emissions Intensity? Evidence from China

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  • Yan Zhao

    (School of Economics and Management, Xinjiang University, Urumqi 830046, China
    Center for Innovation Management Research of Xinjiang, Xinjiang University, Urumqi 830046, China)

  • Hui Sun

    (School of Economics and Management, Xinjiang University, Urumqi 830046, China
    Center for Innovation Management Research of Xinjiang, Xinjiang University, Urumqi 830046, China)

  • Xuechao Xia

    (School of Economics and Management, Xinjiang University, Urumqi 830046, China
    Center for Innovation Management Research of Xinjiang, Xinjiang University, Urumqi 830046, China)

  • Dianyuan Ma

    (School of Economics and Management, Xinjiang University, Urumqi 830046, China
    Center for Innovation Management Research of Xinjiang, Xinjiang University, Urumqi 830046, China)

Abstract

Among the ways to reduce carbon emission intensity (CEI), increasing the intensity of research and development intensity (RDI) plays an important role in the process. In China, how RDI reduces CEI has attracted widespread attention. Most scholars have not considered spatial effects in the study of the correlation between RDI and CEI; therefore, this paper uses panel data of 30 Chinese provinces from 2007–2019 as a research sample to explore the spatial effects of RDI on CEI using spatial measures, analyzes the regulatory effects of the market and government in the process using the interaction effect model, and explores the role and mediating effects in the process of industrial upgrading, technological innovation and human capital effects using the mediating effect model. The empirical results illustrate that: (1) RDI and CEI have significant positive spatial autocorrelation. The spatial clustering characteristics of CEI have obvious regional differences. (2) RDI reduces the CEI of the local area while it has the same reducing effect on the CEI of the surrounding areas. The conclusion is robust. (3) The market and government play a facilitating role in RDI that affects CEI, but there are regional differences. (4) RDI can indirectly reduce CEI by promoting industrial upgrading, improving technological innovation, and increasing human capital. Finally, according to the research conclusions, the paper put forward policy suggestions: strengthen regional cooperation, guide funds into the research and development field, improve the business environment, promote technological innovation and train relevant talents. The research content and findings of this paper enrich the theories related to the influence of RDI on CEI, and have certain implications for future research on CEI based on spatial perspective.

Suggested Citation

  • Yan Zhao & Hui Sun & Xuechao Xia & Dianyuan Ma, 2023. "Can R&D Intensity Reduce Carbon Emissions Intensity? Evidence from China," Sustainability, MDPI, vol. 15(2), pages 1-24, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1619-:d:1035473
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    as
    1. Inglesi-Lotz, Roula, 2017. "Social rate of return to R&D on various energy technologies: Where should we invest more? A study of G7 countries," Energy Policy, Elsevier, vol. 101(C), pages 521-525.
    2. Wei, Hao & Yuan, Ran & Zhao, Laixun, 2020. "International talent inflow and R&D investment: Firm-level evidence from China," Economic Modelling, Elsevier, vol. 89(C), pages 32-42.
    3. Zvi Griliches, 1998. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 17-45, National Bureau of Economic Research, Inc.
    4. Sergio Scicchitano, 2010. "Complementarity between heterogeneous human capital and R&D: can job-training avoid low development traps?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 37(4), pages 361-380, November.
    5. Die Hu & Yuandi Wang & Yu Li, 2017. "How Does Open Innovation Modify the Relationship between Environmental Regulations and Productivity?," Business Strategy and the Environment, Wiley Blackwell, vol. 26(8), pages 1132-1143, December.
    6. Gene M. Grossman & Alan B. Krueger, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 353-377.
    7. Kato, Atsushi, 2005. "Market structure and the allocation of R&D expenditures," Economics Letters, Elsevier, vol. 87(1), pages 55-59, April.
    8. Ge, Tao & Cai, Xuesen & Song, Xiaowei, 2022. "How does renewable energy technology innovation affect the upgrading of industrial structure? The moderating effect of green finance," Renewable Energy, Elsevier, vol. 197(C), pages 1106-1114.
    9. Tan, Sieting & Yang, Jin & Yan, Jinyue & Lee, Chewtin & Hashim, Haslenda & Chen, Bin, 2017. "A holistic low carbon city indicator framework for sustainable development," Applied Energy, Elsevier, vol. 185(P2), pages 1919-1930.
    10. Hashai, Niron & Almor, Tamar, 2008. "R&D intensity, value appropriation and integration patterns within organizational boundaries," Research Policy, Elsevier, vol. 37(6-7), pages 1022-1034, July.
    11. David C. Mowery, 2009. "Plus ca change," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 18(1), pages 1-50, February.
    12. Wang, Bin & Yu, Minxiu & Zhu, Yucheng & Bao, Pinjuan, 2021. "Unveiling the driving factors of carbon emissions from industrial resource allocation in China: A spatial econometric perspective," Energy Policy, Elsevier, vol. 158(C).
    13. Yang, Zhenbing & Shao, Shuai & Li, Chengyu & Yang, Lili, 2020. "Alleviating the misallocation of R&D inputs in China's manufacturing sector: From the perspectives of factor-biased technological innovation and substitution elasticity," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    14. Wu, Haitao & Hao, Yu & Ren, Siyu & Yang, Xiaodong & Xie, Guo, 2021. "Does internet development improve green total factor energy efficiency? Evidence from China," Energy Policy, Elsevier, vol. 153(C).
    15. Adomako, Samuel & Amankwah-Amoah, Joseph & Danso, Albert & Danquah, Joseph Kwadwo & Hussain, Zahid & Khan, Zaheer, 2021. "R&D intensity, knowledge creation process and new product performance: The mediating role of international R&D teams," Journal of Business Research, Elsevier, vol. 128(C), pages 719-727.
    16. Yu, Feifei & Guo, Yue & Le-Nguyen, Khuong & Barnes, Stuart J. & Zhang, Weiting, 2016. "The impact of government subsidies and enterprises’ R&D investment: A panel data study from renewable energy in China," Energy Policy, Elsevier, vol. 89(C), pages 106-113.
    17. Huang, Caihong & Zhang, Xiaoqing & Liu, Kai, 2021. "Effects of human capital structural evolution on carbon emissions intensity in China: A dual perspective of spatial heterogeneity and nonlinear linkages," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    18. Yang, Yuan & Cai, Wenjia & Wang, Can, 2014. "Industrial CO2 intensity, indigenous innovation and R&D spillovers in China’s provinces," Applied Energy, Elsevier, vol. 131(C), pages 117-127.
    19. Huang, Junbing & Chen, Xiang, 2020. "Domestic R&D activities, technology absorption ability, and energy intensity in China," Energy Policy, Elsevier, vol. 138(C).
    20. Alonso-Borrego, César & Forcadell, Francisco Javier, 2010. "Related diversification and R&D intensity dynamics," Research Policy, Elsevier, vol. 39(4), pages 537-548, May.
    21. Zhao Chen & Sang-Ho Lee & Wei Xu, 2017. "R&D Performance in High-Tech Firms in China," Asian Economic Papers, MIT Press, vol. 16(3), pages 193-208, Fall.
    22. Yan, Bin & Wang, Feng & Dong, Mingru & Ren, Jing & Liu, Juan & Shan, Jing, 2022. "How do financial spatial structure and economic agglomeration affect carbon emission intensity? Theory extension and evidence from China," Economic Modelling, Elsevier, vol. 108(C).
    23. Xuan Chang & Jinye Li, 2022. "Effects of the Digital Economy on Carbon Emissions in China: A Spatial Durbin Econometric Analysis," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
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