IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i20p11542-d659762.html
   My bibliography  Save this article

The Relationship between Artificial Intelligence and China’s Sustainable Economic Growth: Focused on the Mediating Effects of Industrial Structural Change

Author

Listed:
  • Decheng Fan

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China)

  • Kairan Liu

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China)

Abstract

In recent years, the application of artificial intelligence (AI) has had a significant impact on economic development. This study examined the relationship between the level of AI development and economic growth in 28 Chinese provinces from 2005 to 2018, and we focused on the mediating role of the industrial structure. We found that the unreasonable state of the structure is an important reason behind the slowdown of China’s economic growth. The development of AI not only has a direct effect on economic growth, but can also improve economic slowdown by inhibiting industrial structure upgrading. Taking into account regional heterogeneity, we also conducted sub-regional regressions, and the results show that this mediating effect is particularly significant in the eastern, central, and western areas of China; the regression results also show that the development of AI technologies did not boost the economy before the 2008 financial crisis, but during the economic recovery period, the R&D and application of AI helped China’s economy to rebound. Thus, AI has gradually become an important power engine for high-quality and sustainable growth in China’s economy.

Suggested Citation

  • Decheng Fan & Kairan Liu, 2021. "The Relationship between Artificial Intelligence and China’s Sustainable Economic Growth: Focused on the Mediating Effects of Industrial Structural Change," Sustainability, MDPI, vol. 13(20), pages 1-15, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11542-:d:659762
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/20/11542/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/20/11542/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    2. Kaplan, Andreas & Haenlein, Michael, 2020. "Rulers of the world, unite! The challenges and opportunities of artificial intelligence," Business Horizons, Elsevier, vol. 63(1), pages 37-50.
    3. Jarrahi, Mohammad Hossein, 2018. "Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making," Business Horizons, Elsevier, vol. 61(4), pages 577-586.
    4. Hongwei Liao & Liangping Yang & Henan Ma & JiaoJiao Zheng, 2020. "Technology import, secondary innovation, and industrial structure optimization: A potential innovation strategy for China," Pacific Economic Review, Wiley Blackwell, vol. 25(2), pages 145-160, May.
    5. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    6. Symeou, Pavlos C., 2011. "Economy size and performance: An efficiency analysis in the telecommunications sector," Telecommunications Policy, Elsevier, vol. 35(5), pages 426-440, June.
    7. Zhou, Xiaoxiao & Pan, Zixuan & Shahbaz, Muhammad & Song, Malin, 2020. "Directed technological progress driven by diversified industrial structural change," Structural Change and Economic Dynamics, Elsevier, vol. 54(C), pages 112-129.
    8. Fang Wei & Dai Sheng & Wang Lili, 2018. "Evolutionary Model and Simulation Research of Collaborative Innovation Network: A Case Study of Artificial Intelligence Industry," Discrete Dynamics in Nature and Society, Hindawi, vol. 2018, pages 1-13, November.
    9. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    10. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 237-282, National Bureau of Economic Research, Inc.
    11. Andreoni, Antonio & Tregenna, Fiona, 2020. "Escaping the middle-income technology trap: A comparative analysis of industrial policies in China, Brazil and South Africa," Structural Change and Economic Dynamics, Elsevier, vol. 54(C), pages 324-340.
    12. Sertsios, Giorgo, 2020. "Corporate finance, industrial organization, and organizational economics," Journal of Corporate Finance, Elsevier, vol. 64(C).
    13. Dirk Nicolas Wagner, 2020. "Economic patterns in a world with artificial intelligence," Evolutionary and Institutional Economics Review, Springer, vol. 17(1), pages 111-131, January.
    14. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    15. Ali Gazni & Zahra Ghaseminik, 2019. "The increasing dominance of science in the economy: Which nations are successful?," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1411-1426, September.
    16. Teece, David J., 2018. "Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world," Research Policy, Elsevier, vol. 47(8), pages 1367-1387.
    17. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    18. Lu, Ren & Ruan, Min & Reve, Torger, 2016. "Cluster and co-located cluster effects: An empirical study of six Chinese city regions," Research Policy, Elsevier, vol. 45(10), pages 1984-1995.
    19. Xubin Lei & Shusheng Wu, 2019. "Improvement of Different Types of Environmental Regulations on Total Factor Productivity: A Threshold Effect Analysis," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-12, December.
    20. Nancey Green Leigh & Benjamin Kraft & Heonyeong Lee, 2020. "Robots, skill demand and manufacturing in US regional labour markets," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 77-97.
    21. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    22. Tsai, Diana H.A., 2018. "The effects of dynamic industrial transition on sustainable development," Structural Change and Economic Dynamics, Elsevier, vol. 44(C), pages 46-54.
    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. Xianpu Xu & Yuchen Song, 2023. "Is There a Conflict between Automation and Environment? Implications of Artificial Intelligence for Carbon Emissions in China," Sustainability, MDPI, vol. 15(16), pages 1-22, August.
    2. Xin Du & Hengming Zhang & Yawen Han, 2022. "How Does New Infrastructure Investment Affect Economic Growth Quality? Empirical Evidence from China," Sustainability, MDPI, vol. 14(6), pages 1-30, March.
    3. Julius Tan Gonzales, 2023. "Implications of AI innovation on economic growth: a panel data study," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-37, December.
    4. Shengli Dai & Yingying Wang & Weimin Zhang, 2022. "The Impact Relationships between Scientific and Technological Innovation, Industrial Structure Advancement and Carbon Footprints in China Based on the PVAR Model," IJERPH, MDPI, vol. 19(15), pages 1-21, August.

    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. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    2. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    3. Ping Chen & Jiawei Gao & Zheng Ji & Han Liang & Yu Peng, 2022. "Do Artificial Intelligence Applications Affect Carbon Emission Performance?—Evidence from Panel Data Analysis of Chinese Cities," Energies, MDPI, vol. 15(15), pages 1-16, August.
    4. Xie, Mengmeng & Ding, Lin & Xia, Yan & Guo, Jianfeng & Pan, Jiaofeng & Wang, Huijuan, 2021. "Does artificial intelligence affect the pattern of skill demand? Evidence from Chinese manufacturing firms," Economic Modelling, Elsevier, vol. 96(C), pages 295-309.
    5. Nazareno, Luísa & Schiff, Daniel S., 2021. "The impact of automation and artificial intelligence on worker well-being," Technology in Society, Elsevier, vol. 67(C).
    6. Li, Chao & Zhang, Yuhan & Li, Xiang & Hao, Yanwei, 2024. "Artificial intelligence, household financial fragility and energy resources consumption: Impacts of digital disruption from a demand-based perspective," Resources Policy, Elsevier, vol. 88(C).
    7. Lin, Boqiang & Xu, Chongchong, 2024. "Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities," Applied Energy, Elsevier, vol. 365(C).
    8. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).
    9. Liu, Jun & Liu, Liang & Qian, Yu & Song, Shunfeng, 2022. "The effect of artificial intelligence on carbon intensity: Evidence from China's industrial sector," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    10. Siliang Tong & Nan Jia & Xueming Luo & Zheng Fang, 2021. "The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1600-1631, September.
    11. Wang, Jiaxin & Zhao, Mu & Huang, Xiang & Song, Zilong & Sun, Di, 2024. "Supply chain diffusion mechanisms for AI applications: A perspective on audit pricing," International Review of Financial Analysis, Elsevier, vol. 93(C).
    12. Zhao, Qian & Wang, Lu & Stan, Sebastian-Emanuel & Mirza, Nawazish, 2024. "Can artificial intelligence help accelerate the transition to renewable energy?," Energy Economics, Elsevier, vol. 134(C).
    13. Wang, Bo & Wang, Jianda & Dong, Kangyin & Nepal, Rabindra, 2024. "How does artificial intelligence affect high-quality energy development? Achieving a clean energy transition society," Energy Policy, Elsevier, vol. 186(C).
    14. Chu, Yihe & Li, Yujia & Che, Ming, 2024. "Population aging and the dynamics of the skill income gap: An analysis of a multiple mediation effect," Finance Research Letters, Elsevier, vol. 62(PB).
    15. Usabiaga, Carlos & Núñez, Fernando & Arendt, Lukasz & Gałecka-Burdziak, Ewa & Pater, Robert, 2022. "Skill requirements and labour polarisation: An association analysis based on Polish online job offers," Economic Modelling, Elsevier, vol. 115(C).
    16. Cebreros Alfonso & Heffner-Rodríguez Aldo & Livas René & Puggioni Daniela, 2020. "Automation Technologies and Employment at Risk: The Case of Mexico," Working Papers 2020-04, Banco de México.
    17. repec:hal:spmain:info:hdl:2441/7n49nkmngd8448a5ts5gt5ade0 is not listed on IDEAS
    18. Marcel Steffen Eckardt, 2022. "Minimum wages in an automating economy," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(1), pages 58-91, February.
    19. Cheng, Can & Luo, Jiayu & Zhu, Chun & Zhang, Shangfeng, 2024. "Artificial intelligence and the skill premium: A numerical analysis of theoretical models," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    20. Naude, Wim, 2019. "The race against the robots and the fallacy of the giant cheesecake: Immediate and imagined impacts of artificial intelligence," MERIT Working Papers 2019-005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    21. Steve J. Bickley & Alison Macintyre & Benno Torgler, 2021. "Artificial Intelligence and Big Data in Sustainable Entrepreneurship," CREMA Working Paper Series 2021-11, Center for Research in Economics, Management and the Arts (CREMA).

    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:13:y:2021:i:20:p:11542-:d:659762. 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.