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The power of public data: How does public data shape the spatial distribution of China's AI Firms?

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  • Ji, Qiang
  • Nie, Song

Abstract

We consider the "establishment of public data open platforms" as a quasi-experiment and adopt the staggered DID method to examine the effect of public data openness on spatial distribution of AI firms. We find that public data openness significantly increases AI firm agglomeration, especially in inland, northern, and resource-based cities. This positive effect acts through improving capital allocation and increasing talent concentration. Our findings highlight the critical role of data governance reforms in shaping digital industrial geography and provide empirical evidence on the benefits of public data openness for fostering inclusive and innovative spatial development.

Suggested Citation

  • Ji, Qiang & Nie, Song, 2025. "The power of public data: How does public data shape the spatial distribution of China's AI Firms?," Economics Letters, Elsevier, vol. 255(C).
    • Handle: RePEc:eee:ecolet:v:255:y:2025:i:c:s0165176525004008
    DOI: 10.1016/j.econlet.2025.112563
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    References listed on IDEAS

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    5. Zhong, Yuan & Lai, Huisu & Zhang, Liang & Guo, Lixiang & Lai, Xiaobing, 2025. "Does public data openness accelerate new quality productive forces? Evidence from China," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 1409-1427.
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    Cited by:

    1. Fang Tang & Longpeng Zhang, 2025. "Impact of data element development on the application of artificial intelligence in enterprises," Empirical Economics, Springer, vol. 69(6), pages 3589-3634, December.

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