IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i19p14042-d1245179.html
   My bibliography  Save this article

The Impact and Mechanism of the Digital Economy on Carbon Emission Efficiency: A Perspective Based on Provincial Panel Data in China

Author

Listed:
  • Lu Liu

    (School of Economics and Management, Xinjiang University, Urumqi 830047, China)

  • Yuxin Meng

    (School of Economics and Management, Xinjiang University, Urumqi 830047, China)

  • Qiying Ran

    (School of Business and Economics, Shanghai Business School, Shanghai 200235, China)

Abstract

The regional carbon emission efficiency (RCEE) of 30 provinces in mainland China from 2011 to 2019 was calculated using a super-slack-based measure (Super-SBM) model. Then, using the system generalized method of moments (system GMM) model, spatial Durbin model (SDM), and mediating effect model, we examined the direct effect, spatial effect, and influence mechanism of the digital economy (DE) on RCEE. It was found that DE significantly promoted regional RCEE, but had a negative effect on RCEE in provinces with a high economic correlation. The mechanism studies showed that DE improved RCEE by reducing the energy intensity and promoting industrial upgrading and green technology innovation. Regional heterogeneity analysis found that DE significantly improved RCEE in eastern provinces, but not in central and western provinces. While RCEE in economically developed areas was improved by DE, it was decreased in economically underdeveloped provinces. This paper provides some empirical and theoretical references for the development of DE to improve RCEE.

Suggested Citation

  • Lu Liu & Yuxin Meng & Qiying Ran, 2023. "The Impact and Mechanism of the Digital Economy on Carbon Emission Efficiency: A Perspective Based on Provincial Panel Data in China," Sustainability, MDPI, vol. 15(19), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14042-:d:1245179
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/19/14042/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/19/14042/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bhattacharya, Mita & Rafiq, Shuddhasattwa & Bhattacharya, Sankar, 2015. "The role of technology on the dynamics of coal consumption–economic growth: New evidence from China," Applied Energy, Elsevier, vol. 154(C), pages 686-695.
    2. Wang, Jianda & Dong, Kangyin & Dong, Xiucheng & Taghizadeh-Hesary, Farhad, 2022. "Assessing the digital economy and its carbon-mitigation effects: The case of China," Energy Economics, Elsevier, vol. 113(C).
    3. Huaping Guan & Binhua Guo & Jianwu Zhang, 2022. "Study on the Impact of the Digital Economy on the Upgrading of Industrial Structures—Empirical Analysis Based on Cities in China," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    4. Xian Zhao & Yiting Dong & Xinshu Gong, 2022. "The Digital Economy and Carbon Productivity: Evidence at China’s City Level," Sustainability, MDPI, vol. 14(17), pages 1-20, August.
    5. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    6. Aydin, Erdal & Brounen, Dirk & Kok, Nils, 2018. "Information provision and energy consumption: Evidence from a field experiment," Energy Economics, Elsevier, vol. 71(C), pages 403-410.
    7. Ran, Qiying & Yang, Xiaodong & Yan, Hongchuan & Xu, Yang & Cao, Jianhong, 2023. "Natural resource consumption and industrial green transformation: Does the digital economy matter?," Resources Policy, Elsevier, vol. 81(C).
    8. Zihanxin Li & Nuoyan Li & Huwei Wen, 2021. "Digital Economy and Environmental Quality: Evidence from 217 Cities in China," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    9. Ghasemaghaei, Maryam & Calic, Goran, 2019. "Does big data enhance firm innovation competency? The mediating role of data-driven insights," Journal of Business Research, Elsevier, vol. 104(C), pages 69-84.
    10. Alam, Md. Mahmudul & Murad, Md. Wahid, 2020. "The impacts of economic growth, trade openness and technological progress on renewable energy use in organization for economic co-operation and development countries," Renewable Energy, Elsevier, vol. 145(C), pages 382-390.
    11. Díaz, Antonia & Marrero, Gustavo A. & Puch, Luis A. & Rodríguez, Jesús, 2019. "Economic growth, energy intensity and the energy mix," Energy Economics, Elsevier, vol. 81(C), pages 1056-1077.
    12. Yu, Yantuan & Zhang, Ning, 2021. "Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 96(C).
    13. Ang, B. W., 1999. "Is the energy intensity a less useful indicator than the carbon factor in the study of climate change?," Energy Policy, Elsevier, vol. 27(15), pages 943-946, December.
    14. Jie Zhou & Hanlin Lan & Cheng Zhao & Jianping Zhou, 2021. "Haze Pollution Levels, Spatial Spillover Influence, and Impacts of the Digital Economy: Empirical Evidence from China," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    15. Börje Johansson & Charlie Karlsson & Roger Stough (ed.), 2006. "The Emerging Digital Economy," Advances in Spatial Science, Springer, number 978-3-540-34488-9.
    16. Ning-Yu Xie & Yang Zhang & Chao Huang, 2022. "The Impact of Digital Economy on Industrial Carbon Emission Efficiency: Evidence from Chinese Provincial Data," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, September.
    17. Songqin Zhao & Diyun Peng & Huwei Wen & Huilin Song, 2022. "Does the Digital Economy Promote Upgrading the Industrial Structure of Chinese Cities?," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    18. Shuhong Wang & Xiaoli Sun & Malin Song, 2021. "Environmental Regulation, Resource Misallocation, and Ecological Efficiency," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(3), pages 410-429, February.
    19. Ziyu Meng & Wen-Bo Li & Chaofan Chen & Chenghua Guan, 2023. "Carbon Emission Reduction Effects of the Digital Economy: Mechanisms and Evidence from 282 Cities in China," Land, MDPI, vol. 12(4), pages 1-21, March.
    20. Liang Liu & Yuhan Zhang & Xiujuan Gong & Mengyue Li & Xue Li & Donglin Ren & Pan Jiang, 2022. "Impact of Digital Economy Development on Carbon Emission Efficiency: A Spatial Econometric Analysis Based on Chinese Provinces and Cities," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
    21. Börje Johansson & Charlie Karlsson & Roger R. Stough, 2006. "Entrepreneurship, Clusters and Policy in the Emerging Digital Economy," Advances in Spatial Science, in: Börje Johansson & Charlie Karlsson & Roger Stough (ed.), The Emerging Digital Economy, chapter 1, pages 1-19, Springer.
    22. Zhao, Jun & Jiang, Qingzhe & Dong, Xiucheng & Dong, Kangyin & Jiang, Hongdian, 2022. "How does industrial structure adjustment reduce CO2 emissions? Spatial and mediation effects analysis for China," Energy Economics, Elsevier, vol. 105(C).
    23. Shushu Li & Yong Ma, 2014. "Urbanization, Economic Development and Environmental Change," Sustainability, MDPI, vol. 6(8), pages 1-19, August.
    24. Sa Xu & Cunyi Yang & Zhehao Huang & Pierre Failler, 2022. "Interaction between Digital Economy and Environmental Pollution: New Evidence from a Spatial Perspective," IJERPH, MDPI, vol. 19(9), pages 1-23, April.
    25. Zhuoxi Yu & Shan Liu & Zhichuan Zhu, 2022. "Has the Digital Economy Reduced Carbon Emissions?: Analysis Based on Panel Data of 278 Cities in China," IJERPH, MDPI, vol. 19(18), pages 1-18, September.
    26. Wu, Jie & Zhu, Qingyuan & Liang, Liang, 2016. "CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China," Applied Energy, Elsevier, vol. 166(C), pages 282-291.
    27. Ma, Qiang & Tariq, Muhammad & Mahmood, Haider & Khan, Zeeshan, 2022. "The nexus between digital economy and carbon dioxide emissions in China: The moderating role of investments in research and development," Technology in Society, Elsevier, vol. 68(C).
    28. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    Full references (including those not matched with items on IDEAS)

    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. Shunbin Zhong & Huafu Shen & Ziheng Niu & Yang Yu & Lin Pan & Yaojun Fan & Atif Jahanger, 2022. "Moving towards Environmental Sustainability: Can Digital Economy Reduce Environmental Degradation in China?," IJERPH, MDPI, vol. 19(23), pages 1-23, November.
    2. Abdulqadir, Idris A. & Asongu, Simplice A., 2022. "The asymmetric effect of internet access on economic growth in sub-Saharan Africa," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 44-61.
    3. Fengge Yao & Ying Song & Xiaomei Wang, 2023. "How the Digital Economy Empowers the Structural Upgrading of Cultural Industries—An Analysis Based on the Spatial Durbin Model," Sustainability, MDPI, vol. 15(19), pages 1-17, October.
    4. Abdulqadir, Idris & Asongu, Simplice, 2021. "The asymmetric effect of internet access on economic growth in sub-Saharan Africa: Insight from a dynamic panel threshold regression," MPRA Paper 109904, University Library of Munich, Germany.
    5. Dong, Kangyin & Wei, Shuo & Liu, Yang & Zhao, Jun, 2023. "How does energy poverty eradication promote common prosperity in China? The role of labor productivity," Energy Policy, Elsevier, vol. 181(C).
    6. Pingguo Xu & Leyi Chen & Huajuan Dai, 2022. "Pathways to Sustainable Development: Corporate Digital Transformation and Environmental Performance in China," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
    7. Yukun Ma & Shaojian Wang & Chunshan Zhou, 2023. "Can the Development of the Digital Economy Reduce Urban Carbon Emissions? Case Study of Guangdong Province," Land, MDPI, vol. 12(4), pages 1-13, March.
    8. Zhuoqi Teng & Yugang He & Zhi Qiao, 2023. "Exploring the Synergistic Effects of Digitalization and Economic Uncertainty on Environmental Sustainability: An Investigation from China," Sustainability, MDPI, vol. 15(15), pages 1-24, August.
    9. Chen, Yu & Wang, Yuandi & Zhao, Changyi, 2024. "From riches to digitalization: The role of AMC in overcoming challenges of digital transformation in resource-rich regions," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    10. Huaxue Zhao & Yu Cheng & Ruijing Zheng, 2022. "Impact of the Digital Economy on PM 2.5 : Experience from the Middle and Lower Reaches of the Yellow River Basin," IJERPH, MDPI, vol. 19(24), pages 1-20, December.
    11. Zhongxin Ma & Fenglan Wu, 2022. "Smart City, Digitalization and CO 2 Emissions: Evidence from 353 Cities in China," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
    12. Ting Zhu & Xiaqing Chen & Wenwen Zhang & Basil Sharp, 2023. "Analysis of the Spatial–Temporal Evolution of the Digital Economy and Its Impact on the Employment Structure in China from 2001 to 2020," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
    13. Karlilar, Selin & Balcilar, Mehmet & Emir, Firat, 2023. "Environmental sustainability in the OECD: The power of digitalization, green innovation, renewable energy and financial development," Telecommunications Policy, Elsevier, vol. 47(6).
    14. Senhua Huang & Feng Han & Lingming Chen, 2023. "Can the Digital Economy Promote the Upgrading of Urban Environmental Quality?," IJERPH, MDPI, vol. 20(3), pages 1-21, January.
    15. Congqi Wang & Rui Zhang & Haslindar Ibrahim & Pengzhen Liu, 2023. "Can the Digital Economy Enable Carbon Emission Reduction: Analysis of Mechanisms and China’s Experience," Sustainability, MDPI, vol. 15(13), pages 1-20, June.
    16. Dong, Kangyin & Ni, Guohua & Taghizadeh-Hesary, Farhad & Zhao, Congyu, 2023. "Does smart transportation matter in inhibiting carbon inequality?," Energy Economics, Elsevier, vol. 126(C).
    17. Lingzhang Kong & Jinye Li, 2022. "Digital Economy Development and Green Economic Efficiency: Evidence from Province-Level Empirical Data in China," Sustainability, MDPI, vol. 15(1), pages 1-26, December.
    18. Baglan, Deniz & Yoldas, Emre, 2014. "Non-linearity in the inflation–growth relationship in developing economies: Evidence from a semiparametric panel model," Economics Letters, Elsevier, vol. 125(1), pages 93-96.
    19. Simplice Asongu & Nicholas M. Odhiambo, 2020. "Financial access, governance and insurance sector development in sub-Saharan Africa," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(4), pages 849-875, February.
    20. Zhenxiang Cao & Liqing Peng, 2023. "The Impact of Digital Economics on Environmental Quality: A System Dynamics Approach," SAGE Open, , vol. 13(4), pages 21582440231, December.

    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:19:p:14042-:d:1245179. 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.