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The Role of Digital Finance in Shaping Agricultural Economic Resilience: Evidence from Machine Learning

Author

Listed:
  • Chun Yang

    (College of Management, Sichuan Agricultural University, Chengdu 611130, China)

  • Wangping Liu

    (College of Management, Sichuan Agricultural University, Chengdu 611130, China)

  • Jiahao Zhou

    (Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China)

Abstract

This study offers detailed recommendations on strengthening government support without harming digital finance benefits, especially in negatively affected areas, which is critical for enhancing the inclusiveness of the digital financial landscape and reducing social disparities. This paper uses year 2011–2022 panel data from China’s 31 provinces to empirically analyze digital finance’s effects, mechanisms, and heterogeneity on agricultural economy resilience with a two-way, fixed-effect model. It further explores each feature’s impacts using machine learning methodologies like the random forest, GBRT, SHAP value method, and ALE plot. The findings show that digital finance boosted agri-economy resilience, varying by food-producing status and marketization. Among all the features analyzed, government input, urbanization level, and planting structure emerged as the most critical factors influencing agri-economy resilience. Notably, government input negatively moderated this relationship. The ALE plot revealed non-linear effects of digital finance and planting structure on agri-economy resilience.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:10:p:1834-:d:1501836
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    References listed on IDEAS

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    1. Qifeng Yang & Pingyu Zhang & Yuxin Li & Jiachen Ning & Nanchen Chu, 2023. "Does the Policy of Decoupled Subsidies Improve the Agricultural Economic Resilience?—Evidence from China’s Main Corn Producing Regions," Sustainability, MDPI, vol. 15(13), pages 1-23, June.
    2. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1.
    3. Jie Zhou & Haipeng Chen & Qingyun Bai & Linxin Liu & Guohong Li & Qianling Shen, 2023. "Can the Integration of Rural Industries Help Strengthen China’s Agricultural Economic Resilience?," Agriculture, MDPI, vol. 13(9), pages 1-19, September.
    4. Robert Berry & Mauro Vigani & Julie Urquhart, 2022. "Economic resilience of agriculture in England and Wales: a spatial analysis," Journal of Maps, Taylor & Francis Journals, vol. 18(1), pages 70-78, January.
    5. Ibrahim Bozkurt & Rıfat Karakuş & Melek Yildiz, 2018. "Spatial Determinants of Financial Inclusion over Time," Journal of International Development, John Wiley & Sons, Ltd., vol. 30(8), pages 1474-1504, November.
    6. Hui Zhang & Jing Li & Tianshu Quan, 2023. "Strengthening or Weakening: The Impact of an Aging Rural Workforce on Agricultural Economic Resilience in China," Agriculture, MDPI, vol. 13(7), pages 1-16, July.
    7. Yunping Hao & Bing Zhang & Hongfei Yin, 2023. "Can digital finance drive urban–rural integration?," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 36(2), pages 2169736-216, July.
    8. 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.
    9. Pant, Raghav & Barker, Kash & Zobel, Christopher W., 2014. "Static and dynamic metrics of economic resilience for interdependent infrastructure and industry sectors," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 92-102.
    10. Wang, Jing, 2023. "Digital inclusive finance and rural revitalization," Finance Research Letters, Elsevier, vol. 57(C).
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