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Data factor agglomeration and urban green finance: A quasi-natural experiment based on the National Big Data Comprehensive Pilot Zone

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  • Wang, Huizong
  • Hao, Yulong
  • Fu, Qiang

Abstract

Using panel data from 246 cities in China from 2008 to 2021, we investigate the impact of data factor agglomeration on the development of urban green finance through a quasi-natural experiment based on the National Big Data Comprehensive Pilot Zone. Findings reveal that the effect of data agglomeration, characterized by the construction of big data comprehensive pilot zone, has significantly improved urban green finance development in the pilot zones. Further research shows that data factor agglomeration can expand the development scale of urban green finance by promoting industrial structure upgrading and improve the development efficiency of urban green finance by driving innovation in digital technology, both of which can promote urban green finance development. Furthermore, the impact of data factor agglomeration on urban green finance development is influenced by geographic location and urban administrative level, with greater significance for cities in the eastern region and those with high administrative levels. Meanwhile, the human capital level and environmental regulation strength positively moderate the efficacy of the data factors' agglomeration. Our study explores the effective and realistic approaches to promote the development of urban green finance from the perspective of data factor agglomeration, providing a reference for countries to accelerate the construction of good data factor ecosystems and promote green finance reform in depth.

Suggested Citation

  • Wang, Huizong & Hao, Yulong & Fu, Qiang, 2024. "Data factor agglomeration and urban green finance: A quasi-natural experiment based on the National Big Data Comprehensive Pilot Zone," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    • Handle: RePEc:eee:finana:v:96:y:2024:i:pb:s1057521924006641
    DOI: 10.1016/j.irfa.2024.103732
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    1. Lv, Jingyao & Zhao, Zhongxiu & Ji, Yongsheng, 2025. "Can big data aggregation help businesses save energy and reduce emissions? Quasi-natural experiment in big data comprehensive test," Structural Change and Economic Dynamics, Elsevier, vol. 72(C), pages 89-102.

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