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Digital Economy, Factor Allocation Efficiency of Dual-Economy and Urban-Rural Income Gap

Author

Listed:
  • Bochao Zhang

    (Institute of Economics, Shanghai Academy of Social Sciences, Shanghai 200020, China)

  • Wanhao Dong

    (School of Public Finance and Administration, Shanghai Lixin University of Accounting and Finance, Shanghai 201620, China)

  • Jin Yao

    (Institute of Economics, Shanghai Academy of Social Sciences, Shanghai 200020, China)

  • Xiaolong Cheng

    (Institute of Economics, Shanghai Academy of Social Sciences, Shanghai 200020, China)

Abstract

The digital economy has significant economic structural transformation effects and income distribution effects. This article analyzed the impacts and mechanisms of digital economy development on the efficiency of dual-economic factor allocation and the urban–rural income gap from a theoretical perspective, empirically tested by using China’s provincial panel data from 2008 to 2017 and a bidirectional fixed effects model. It was found that the development of the digital economy has significantly improved the efficiency of factor allocation in the dual-economy, which has a significant improvement effect on the allocation efficiency of capital and labor. The development of the digital economy alleviates the problem of surplus labor factors and insufficient capital input in the agricultural sector by promoting nonagricultural employment and the flow of capital factors to the agricultural sector. The development of the digital economy can significantly reduce the urban–rural income gap by improving the efficiency of factor allocation in the dual-economy. The main contribution of this article is verifying that the flow of production factors triggered by the digital economy has a configuration efficiency improvement effect and further extending the economic structure effect of the digital economy to the field of distribution, examining the feasible path of optimizing the income distribution pattern of the digital economy.

Suggested Citation

  • Bochao Zhang & Wanhao Dong & Jin Yao & Xiaolong Cheng, 2023. "Digital Economy, Factor Allocation Efficiency of Dual-Economy and Urban-Rural Income Gap," Sustainability, MDPI, vol. 15(18), pages 1-30, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13514-:d:1236477
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    1. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    2. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    3. Wanhao Dong & Jin Yao & Bochao Zhang, 2022. "Quantitative Evaluation and Characteristic Analysis of Resource Allocation Efficiency of the Energy Industry in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    4. Chang-Tai Hsieh & Peter J. Klenow, 2009. "Misallocation and Manufacturing TFP in China and India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1403-1448.
    5. Aoki, Shuhei, 2012. "A simple accounting framework for the effect of resource misallocation on aggregate productivity," Journal of the Japanese and International Economies, Elsevier, vol. 26(4), pages 473-494.
    6. Brandt, Loren & Van Biesebroeck, Johannes & Zhang, Yifan, 2012. "Creative accounting or creative destruction? Firm-level productivity growth in Chinese manufacturing," Journal of Development Economics, Elsevier, vol. 97(2), pages 339-351.
    7. Agnieszka Malkowska & Maria Urbaniec & Malgorzata Kosala, 2021. "The impact of digital transformation on European countries: insights from a comparative analysis," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 16(2), pages 325-355, June.
    8. Changling Sun & Zixi Zhang & Marek Vochozka & Iveta Vozòáková, 2022. "Enterprise digital transformation and debt financing cost in China’s A-share listed companies," Oeconomia Copernicana, Institute of Economic Research, vol. 13(3), pages 783-829, September.
    9. Ercan Yasar & Güray Akalin & Sinan Erdogan & Samuel Asumadu Sarkodie, 2022. "Trading Kuznets curve: empirical analysis for China," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 49(3), pages 741-768, August.
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    Cited by:

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    2. Luo, Haotian & Hu, Qing, 2024. "A re-examination of the influence of human capital on urban-rural income gap in China: College enrollment expansion, digital economy and spatial spillover," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 494-519.
    3. Shuguang Liu & Xiaowen Tang & Yubin Zhao, 2024. "Global Value Chain Participation, Employment Structure, and Urban–Rural Income Gap in the Context of Sustainable Development," Sustainability, MDPI, vol. 16(5), pages 1-19, February.
    4. Chun Yang & Wangping Liu & Jiahao Zhou, 2024. "The Role of Digital Finance in Shaping Agricultural Economic Resilience: Evidence from Machine Learning," Agriculture, MDPI, vol. 14(10), pages 1-15, October.

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