IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i9p7422-d1137008.html
   My bibliography  Save this article

Spatial Imbalance, Dynamic Evolution and Convergence of the Digital Economy: Analysis Based on Panel Data of 278 Cities in China

Author

Listed:
  • Zhuoxi Yu

    (School of Mathematics and Statistics, Liaoning University, Shenyang 110031, China)

  • Shan Liu

    (School of Economics, Liaoning University, Shenyang 110136, China)

  • Zhichuan Zhu

    (School of Mathematics and Statistics, Liaoning University, Shenyang 110031, China)

  • Lianyan Fu

    (School of Mathematics and Statistics, Liaoning University, Shenyang 110031, China)

Abstract

Accelerating the development of the digital economy is the way to build a modern industrial system and promote sustainable development. In order to accurately analyze the development status of China’s digital economy, this study introduced a text analysis method to construct an index of the digital economy and surveyed the digital economy based on the panel data of 278 Chinese cities from 2011 to 2019. Moran’s I index, the Dagum Gini coefficient, the kernel density and a Markov chain were used to reveal the space-time difference and dynamic change characteristics. Considering the impact of the spatial correlation and regional division on convergence, we compared the σ values and spatial σ values to study the convergence characteristics after grouping with the decision tree method. The research showed that the digital economy had greatly improved, but it showed a significant imbalance. The research on the regional division of cities according to their geographical distribution and grade showed that the development status of the digital economy was increasingly different, and there was no convergence feature. We chose continuous classification variables and used the decision tree method to divide cities into 10 groups to investigate the convergence. The results showed that the σ values and spatial σ values decreased significantly and showed convergence characteristics. The development of the digital economy showed convergence, indicating that the convergence was greatly affected by the geographical location and grouping basis. Overall, this study contributes to our understanding of the development status of the digital economy, and targeted policy recommendations were proposed to improve the level of digital economy development.

Suggested Citation

  • Zhuoxi Yu & Shan Liu & Zhichuan Zhu & Lianyan Fu, 2023. "Spatial Imbalance, Dynamic Evolution and Convergence of the Digital Economy: Analysis Based on Panel Data of 278 Cities in China," Sustainability, MDPI, vol. 15(9), pages 1-26, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7422-:d:1137008
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/9/7422/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/9/7422/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shuming Ren & Lianqing Li & Yueqi Han & Yu Hao & Haitao Wu, 2022. "The emerging driving force of inclusive green growth: Does digital economy agglomeration work?," Business Strategy and the Environment, Wiley Blackwell, vol. 31(4), pages 1656-1678, May.
    2. Rongwu Zhang & Wenqiang Fu & Yingxu Kuang, 2022. "Can Digital Economy Promote Energy Conservation and Emission Reduction in Heavily Polluting Enterprises? Empirical Evidence from China," IJERPH, MDPI, vol. 19(16), pages 1-21, August.
    3. Bera, Subhasis, 2019. "Club convergence and drivers of digitalization across Indian states," Telecommunications Policy, Elsevier, vol. 43(8), pages 1-1.
    4. Yubo Zhao & Gui Zhang & Hongwei Zhao & Anirban Chakraborti, 2021. "Spatial Network Structures of Urban Agglomeration Based on the Improved Gravity Model: A Case Study in China’s Two Urban Agglomerations," Complexity, Hindawi, vol. 2021, pages 1-17, February.
    5. Xue, Dan & Yue, Li & Ahmad, Fayyaz & Draz, Muhammad Umar & Chandio, Abbas Ali & Ahmad, Munir & Amin, Waqas, 2022. "Empirical investigation of urban land use efficiency and influencing factors of the Yellow River basin Chinese cities," Land Use Policy, Elsevier, vol. 117(C).
    6. Frederico Cruz-Jesus & Tiago Oliveira & Fernando Bacao, 2018. "The Global Digital Divide: Evidence and Drivers," Journal of Global Information Management (JGIM), IGI Global, vol. 26(2), pages 1-26, April.
    7. Xiaolan Chen & Qinggang Meng & Jianing Shi & Yufei Liu & Jing Sun & Wanfang Shen, 2022. "Regional Differences and Convergence of Carbon Emissions Intensity in Cities along the Yellow River Basin in China," Land, MDPI, vol. 11(7), pages 1-19, July.
    8. Wen Chen & Ying Wu, 2022. "Does intellectual property protection stimulate digital economy development?," Journal of Applied Economics, Taylor & Francis Journals, vol. 25(1), pages 723-730, December.
    9. Horoshko, Olena-Ivanna & Horoshko, Andrii & Bilyuga, Stanislav & Horoshko, Viktoriia, 2021. "Theoretical and Methodological Bases of the Study of the Impact of Digital Economy on World Policy in 21 Century," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    10. Qianqian Wan & Daqian Shi, 2022. "Smarter and Cleaner: The Digital Economy and Environmental Pollution," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 30(6), pages 59-85, November.
    11. Li Liu & Tingting Gu & Hao Wang, 2022. "The Coupling Coordination between Digital Economy and Industrial Green High-Quality Development: Spatio-Temporal Characteristics, Differences and Convergence," Sustainability, MDPI, vol. 14(23), pages 1-14, December.
    12. Liang, Xiaoying & Min Fan, & Xiao, Yuting & Yao, Jing, 2022. "Temporal-spatial characteristics of energy-based carbon dioxide emissions and driving factors during 2004–2019, China," Energy, Elsevier, vol. 261(PA).
    13. 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).
    14. Rui Li & Jing Rao & Liangyong Wan, 2022. "The digital economy, enterprise digital transformation, and enterprise innovation," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2875-2886, October.
    15. Dagum, Camilo, 1997. "A New Approach to the Decomposition of the Gini Income Inequality Ratio," Empirical Economics, Springer, vol. 22(4), pages 515-531.
    16. 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).
    17. Chen, Xiaohui & Teng, Lei & Chen, Wen, 2022. "How does FinTech affect the development of the digital economy? Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    18. Jinlin Li & Litai Chen & Ying Chen & Jiawen He, 2022. "Digital economy, technological innovation, and green economic efficiency—Empirical evidence from 277 cities in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(3), pages 616-629, April.
    19. Xue, Yan & Tang, Chang & Wu, Haitao & Liu, Jianmin & Hao, Yu, 2022. "The emerging driving force of energy consumption in China: Does digital economy development matter?," Energy Policy, Elsevier, vol. 165(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. Jianing Pang & Yimeng Zhang & Fangyi Jiao, 2023. "The Impact of the Digital Economy on Transformation and Upgrading of Industrial Structure: A Perspective Based on the “Poverty Trap”," Sustainability, MDPI, vol. 15(20), pages 1-20, October.

    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. Yang, Senmiao & Wang, Jianda & Dong, Kangyin & Jiang, Qingzhe, 2023. "A path towards China's energy justice: How does digital technology innovation bring about a just revolution?," Energy Economics, Elsevier, vol. 127(PA).
    2. Guo, Bingnan & Wang, Yu & Zhang, Hao & Liang, Chunyan & Feng, Yu & Hu, Feng, 2023. "Impact of the digital economy on high-quality urban economic development: Evidence from Chinese cities," Economic Modelling, Elsevier, vol. 120(C).
    3. 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.
    4. Yating Zeng & Xinyue Xu & Yuyao Zhao & Bin Li, 2023. "Impact of Digital Economy on the Upgrading of Energy Consumption Structure: Evidence from Mainland China," Sustainability, MDPI, vol. 15(7), pages 1-18, March.
    5. Taghizadeh-Hesary, Farhad & Dong, Kangyin & Zhao, Congyu & Phoumin, Han, 2023. "Can financial and economic means accelerate renewable energy growth in the climate change era? The case of China," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 730-743.
    6. Hao Su & Shuo Yang, 2022. "Spatio-Temporal Urban Land Green Use Efficiency under Carbon Emission Constraints in the Yellow River Basin, China," IJERPH, MDPI, vol. 19(19), pages 1-28, October.
    7. Razzaq, Asif & Yang, Xiaodong, 2023. "Digital finance and green growth in China: Appraising inclusive digital finance using web crawler technology and big data," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    8. Mingguang Liu & Gaoyang Li, 2023. "Research on the Impact of the Digital Economy on Carbon Pollution Based on the National Big Data Comprehensive Pilot Zone in China," Sustainability, MDPI, vol. 15(21), pages 1-20, October.
    9. Haiyang Qiu & Xin Li & Long Zhang, 2023. "Influential Effect and Mechanism of Digital Finance on Urban Land Use Efficiency in China," Sustainability, MDPI, vol. 15(20), pages 1-21, October.
    10. Guoteng Xu & Jingtong Shan & Chengjiang Li & Xia Chen & Na Zhou, 2023. "Study on the Innovation-Driven Effect of Digital Economy on Real Economy—A Theoretical and Empirical Analysis from an R&D Perspective," Sustainability, MDPI, vol. 15(21), pages 1-18, October.
    11. Lin, Boqiang & Huang, Chenchen, 2023. "How will promoting the digital economy affect electricity intensity?," Energy Policy, Elsevier, vol. 173(C).
    12. Wenjing Zhang & Bin Sun & Zaijun Li & Suleman Sarwar, 2023. "The Impact of the Digital Economy on Industrial Eco-Efficiency in the Yangtze River Delta (YRD) Urban Agglomeration," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
    13. Meili Zhang & Shi Yin, 2023. "Can China’s Digital Economy and Green Economy Achieve Coordinated Development?," Sustainability, MDPI, vol. 15(7), pages 1-25, March.
    14. 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.
    15. 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.
    16. Zhe Wang & Ziling Yu & Lili Ma & Aolei Li, 2022. "The Digital Economy and the Energy “Internal Circulation”: Evidence from China’s Interprovincial Energy Trade," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    17. Peng, Hua-Rong & Zhang, Yue-Jun & Liu, Jing-Yue, 2023. "The energy rebound effect of digital development: Evidence from 285 cities in China," Energy, Elsevier, vol. 270(C).
    18. Cao, Yuqiang & Hu, Yong & Liu, Qian & Lu, Meiting & Shan, Yaowen, 2023. "Job creation or disruption? Unraveling the effects of smart city construction on corporate employment in China," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    19. Wang, Lianghu & Shao, Jun, 2023. "Digital economy, entrepreneurship and energy efficiency," Energy, Elsevier, vol. 269(C).
    20. Yanwei Lyu & Yahui Ge & Jinning Zhang, 2023. "The impact of digital economy on capital misallocation: evidence from China," Economic Change and Restructuring, Springer, vol. 56(5), pages 3475-3499, October.

    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:9:p:7422-:d:1137008. 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.