IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i2p1619-d1035473.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/2/1619/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/2/1619/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    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. 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.
    3. 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.
    4. Kato, Atsushi, 2005. "Market structure and the allocation of R&D expenditures," Economics Letters, Elsevier, vol. 87(1), pages 55-59, April.
    5. 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.
    6. 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.
    7. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LLC, vol. 9(1), pages 86-136, March.
    8. 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.
    9. 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.
    10. 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.
    11. 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).
    12. 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.
    13. 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.
    14. 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).
    15. Huang, Junbing & Chen, Xiang, 2020. "Domestic R&D activities, technology absorption ability, and energy intensity in China," Energy Policy, Elsevier, vol. 138(C).
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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).
    21. 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.
    22. 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).
    23. Alonso-Borrego, César & Forcadell, Francisco Javier, 2010. "Related diversification and R&D intensity dynamics," Research Policy, Elsevier, vol. 39(4), pages 537-548, May.
    24. 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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ul-Durar, Shajara & De Sisto, Marco & Arshed, Noman & Yasin, Naveed & Reynolds, Kae, 2025. "Natural capital productivity as a decoupler of energy and emissions in Sub-Saharan Africa," Energy Economics, Elsevier, vol. 145(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dong, Xiao-Ying & Hao, Yu, 2018. "Would income inequality affect electricity consumption? Evidence from China," Energy, Elsevier, vol. 142(C), pages 215-227.
    2. Yu Hao & Yunxia Guo & Haitao Wu, 2022. "The role of information and communication technology on green total factor energy efficiency: Does environmental regulation work?," Business Strategy and the Environment, Wiley Blackwell, vol. 31(1), pages 403-424, January.
    3. Nana Jiang & Wei Jiang & Haibo Chen, 2023. "Innovative urban design for low‐carbon sustainable development: Evidence from China's innovative city pilots," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(2), pages 698-715, April.
    4. Le Ngoc, Anh & Heshmati, Almas, 2025. "The Green Path: FDI’s Influence on Asia’s Sustainable Economic Growth," IZA Discussion Papers 17900, Institute of Labor Economics (IZA).
    5. Xu, Qiong & Zhong, Meirui & Li, Xin, 2022. "How does digitalization affect energy? International evidence," Energy Economics, Elsevier, vol. 107(C).
    6. Wang, Lianghu & Shao, Jun, 2023. "Digital economy, entrepreneurship and energy efficiency," Energy, Elsevier, vol. 269(C).
    7. Gao, Da & Li, Ge & Yu, Jiyu, 2022. "Does digitization improve green total factor energy efficiency? Evidence from Chinese 213 cities," Energy, Elsevier, vol. 247(C).
    8. Congyu Zhao & Kangyin Dong & Farhad Taghizadeh-Hesary, 2023. "Can smart transportation enhance green development efficiency?," Economic Change and Restructuring, Springer, vol. 56(2), pages 825-857, April.
    9. Senhua Huang & Lingming Chen, 2023. "The Impact of the Digital Economy on the Urban Total-Factor Energy Efficiency: Evidence from 275 Cities in China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    10. Ajanaku, B.A. & Collins, A.R., 2021. "Economic growth and deforestation in African countries: Is the environmental Kuznets curve hypothesis applicable?," Forest Policy and Economics, Elsevier, vol. 129(C).
    11. Arminen, Heli & Menegaki, Angeliki N., 2019. "Corruption, climate and the energy-environment-growth nexus," Energy Economics, Elsevier, vol. 80(C), pages 621-634.
    12. Huaide Wen & Jun Dai, 2021. "The Change of Sources of Growth and Sustainable Development in China: Based on the Extended EKC Explanation," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    13. Shao, Shuai & Yang, Lili & Yu, Mingbo & Yu, Mingliang, 2011. "Estimation, characteristics, and determinants of energy-related industrial CO2 emissions in Shanghai (China), 1994-2009," Energy Policy, Elsevier, vol. 39(10), pages 6476-6494, October.
    14. Mohamed Boly, 2018. "CO 2 mitigation in developing countries: the role of foreign aid," Working Papers halshs-01740881, HAL.
    15. Nikolaos Terzidis & Raquel Ortega‐Argilés, 2021. "Employment polarization in regional labor markets: Evidence from the Netherlands," Journal of Regional Science, Wiley Blackwell, vol. 61(5), pages 971-1001, November.
    16. Kin Sibanda & Rufaro Garidzirai & Farai Mushonga & Dorcas Gonese, 2023. "Natural Resource Rents, Institutional Quality, and Environmental Degradation in Resource-Rich Sub-Saharan African Countries," Sustainability, MDPI, vol. 15(2), pages 1-11, January.
    17. Bravo-Ortega, Claudio & García Marín, Álvaro, 2011. "R&D and Productivity: A Two Way Avenue?," World Development, Elsevier, vol. 39(7), pages 1090-1107, July.
    18. Gutiérrez-López, Cristina & Castro, Paula & Tascón, María T., 2022. "How can firms' transition to a low-carbon economy affect the distance to default?," Research in International Business and Finance, Elsevier, vol. 62(C).
    19. Fang, Wen Shwo & Miller, Stephen M. & Yeh, Chih-Chuan, 2012. "The effect of ESCOs on energy use," Energy Policy, Elsevier, vol. 51(C), pages 558-568.
    20. Nguyen, Van Bon, 2021. "The Difference in the FDI - CO2 Emissions Relationship between Developed and Developing Countries: Empirical Evidence Based on Institutional Perspective," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 62(2), pages 124-140, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1619-:d:1035473. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.