IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i20p15125-d1264554.html
   My bibliography  Save this article

The Impact of the Digital Economy on Transformation and Upgrading of Industrial Structure: A Perspective Based on the “Poverty Trap”

Author

Listed:
  • Jianing Pang

    (School of Economics and Business Administration, Heilongjiang University, Harbin 150080, China)

  • Yimeng Zhang

    (School of Economics and Management, Harbin University of Science and Technology, Harbin 150080, China)

  • Fangyi Jiao

    (School of Economics and Business Administration, Heilongjiang University, Harbin 150080, China)

Abstract

Breaking the “poverty trap” has gradually become the core topic of economic research. The transformation and upgrading of industrial structure is considered an essential means to break the “poverty trap”. How to use the digital economy effect to change the allocation of capital and labor factors and realize the transformation and upgrading of industrial structure is a significant issue in this paper. The study focuses on examining the development of China’s digital economy between 2013 and 2021, uses the entropy method to measure it, and conducts an empirical study through a fixed-effects model and an intermediary-effect model to investigate the influence and mechanism of the digital economy on industrial structure transformation and upgrading. The results indicate the following: Firstly, the digital economy plays a crucial role in facilitating the transformation and upgrading of industrial structure, and this conclusion was still robust even after controlling for a series of factors affecting the transformation and upgrading of industrial structure and correcting the endogenous estimation deviation by using instrumental variables. Secondly, through the heterogeneity analysis of regions with different economic development levels, it was found that compared with economically developed regions, economically backward regions need to pay more attention to the development of the digital economy. Thirdly, the examination of the mechanism revealed that the digital economy has realized the transformation and upgrading of industrial structure by optimizing the allocation of capital and labor. In this paper, Schumpeter’s innovation theory is regarded as a new perspective to break the “poverty trap” and realize the transformation and upgrading of industrial structure, filling the gap in related research in this field. This study provides a suggestion for economically backward areas to break the “poverty trap” and provides theoretical support and practical guidance for the sustained economic growth of the whole country.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:20:p:15125-:d:1264554
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/20/15125/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/20/15125/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Nathan Nunn & Nancy Qian, 2014. "US Food Aid and Civil Conflict," American Economic Review, American Economic Association, vol. 104(6), pages 1630-1666, June.
    3. Sascha Kraus & Paul Jones & Norbert Kailer & Alexandra Weinmann & Nuria Chaparro-Banegas & Norat Roig-Tierno, 2021. "Digital Transformation: An Overview of the Current State of the Art of Research," SAGE Open, , vol. 11(3), pages 21582440211, September.
    4. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    5. 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.
    6. Gary S. Becker, 1964. "Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, First Edition," NBER Books, National Bureau of Economic Research, Inc, number beck-5, February.
    7. Jinqi Su & Ke Su & Shubin Wang, 2021. "Does the Digital Economy Promote Industrial Structural Upgrading?—A Test of Mediating Effects Based on Heterogeneous Technological Innovation," Sustainability, MDPI, vol. 13(18), pages 1-24, September.
    8. Jingwei Sun & Jingzhu Chen, 2023. "Digital Economy, Energy Structure Transformation, and Regional Carbon Dioxide Emissions," Sustainability, MDPI, vol. 15(11), pages 1-16, May.
    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. Dorel Mihai Paraschiv & Muhammad Atif & Ioan-Radu Petrariu & Maria Gheorghe & Ramona Iulia Dieaconescu & Mihai Istudor, 2024. "Shaping Europe s Digital and Sustainable Future: Analysis of the Digital Economy and Society Index in the Pre- and Post-Pandemic Period," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(Special 1), pages 1012-1012, November.
    2. Xinyu Wei & Mingwang Cheng & Kaifeng Duan & Xiangxing Kong, 2024. "Effects of Big Data on PM 2.5 : A Study Based on Double Machine Learning," Land, MDPI, vol. 13(3), pages 1-21, March.
    3. Chin, Min Yee & Qin, Yuting & Hoy, Zheng Xuan & Farooque, Aitazaz Ahsan & Wong, Keng Yinn & Mong, Guo Ren & Tan, Jian Ping & Woon, Kok Sin, 2024. "Assessing carbon budgets and reduction pathways in different income levels with neural network forecasting," Energy, Elsevier, vol. 305(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. Lu, Jing & Xiao, Qinglan & Wang, Taoxuan, 2023. "Does the digital economy generate a gender dividend for female employment? Evidence from China," Telecommunications Policy, Elsevier, vol. 47(6).
    2. Du, Juntao & Shen, Zhiyang & Song, Malin & Zhang, Linda, 2023. "Nexus between digital transformation and energy technology innovation: An empirical test of A-share listed enterprises," Energy Economics, Elsevier, vol. 120(C).
    3. Wang, Heting & Wang, Huijuan & Guan, Rong, 2024. "Digitalization of industries and labor mobility in China," China Economic Review, Elsevier, vol. 87(C).
    4. Lee, Chien-Chiang & Yan, Jingyang & Wang, Fuhao, 2024. "Impact of population aging on food security in the context of artificial intelligence: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    5. Josep Ubalde & Amado Alarcón, 2020. "Are all automation-resistant skills rewarded? Linguistic skills in the US labour market," The Economic and Labour Relations Review, , vol. 31(3), pages 403-424, September.
    6. Eggenberger, Christian & Backes-Gellner, Uschi, 2023. "IT skills, occupation specificity and job separations," Economics of Education Review, Elsevier, vol. 92(C).
    7. Mariachiara Barzotto, 2024. "Educational (mis)match in the context of new manufacturing: A qualitative comparative analysis study in five European countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2116-2138, April.
    8. Li Chen & Yuanbo Zhang, 2023. "Does the Development of the Digital Economy Promote Common Prosperity?—Analysis Based on 284 Cities in China," Sustainability, MDPI, vol. 15(5), pages 1-16, March.
    9. Zeyer-Gliozzo, Birgit, 2020. "Returns to formal, non-formal and informal training for workers at risk of automation," Ruhr Economic Papers 857, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    10. Hong Tang & Chaoyue Cai & Chunxiao Xu, 2022. "Does the Digital Economy Improve Urban Tourism Development? An Examination of the Chinese Case," Sustainability, MDPI, vol. 14(23), pages 1-23, November.
    11. Qiuqiu Guo & Xiaoyu Ma, 2023. "How Does the Digital Economy Affect Sustainable Urban Development? Empirical Evidence from Chinese Cities," Sustainability, MDPI, vol. 15(5), pages 1-21, February.
    12. Pengju Liu & Yitong Zhang & Shengqi Zhou, 2023. "Has Digital Financial Inclusion Narrowed the Urban–Rural Income Gap? A Study of the Spatial Influence Mechanism Based on Data from China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    13. 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.
    14. Žilvinas Martinaitis & Aleksandr Christenko & Jonas AntanaviÄ ius, 2021. "Upskilling, Deskilling or Polarisation? Evidence on Change in Skills in Europe," Work, Employment & Society, British Sociological Association, vol. 35(3), pages 451-469, June.
    15. 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).
    16. Satı, Zümrüt Ecevit, 2024. "Comparison of the criteria affecting the digital innovation performance of the European Union (EU) member and candidate countries with the entropy weight-TOPSIS method and investigation of its importa," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    17. 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.
    18. Yufang Shi & Tianlun Zhang & Yufeng Jiang, 2023. "Digital Economy, Technological Innovation and Urban Resilience," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    19. Changya Di & Decai Tang & Yifan Xu, 2023. "Impact of Digital Economy on the High-Quality Development of China’s Service Trade," Sustainability, MDPI, vol. 15(15), pages 1-19, August.
    20. Yaozhi Xu & Liling Xu, 2023. "The Convergence between Digital Industrialization and Industrial Digitalization and Export Technology Complexity: Evidence from China," Sustainability, MDPI, vol. 15(11), pages 1-18, June.

    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:20:p:15125-:d:1264554. 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.