Is AI a key driving force for Chinese total factor productivity growth? Mechanistic analysis of employment, supply chain, and information asymmetry

Ruifeng Xu and Frank M. Song

Economic Modelling, 2025, vol. 150, issue C

Abstract: Using artificial intelligence (AI) patent data and financial records from Chinese-listed firms, we find that AI-driven innovations enhance total factor productivity (TFP) at a rate 40 times greater than that of ordinary patents. Our findings suggest that AI serves as a crucial TFP driver in China and may help mitigate the risks associated with the country's aging population and the potential middle-income trap. This works because AI enhances workforce education, optimizes supply chains, and reduces information asymmetry and agency costs. A heterogeneity analysis reveals that computer system AI patents hold the highest value, whereas AI innovation has the most significant impact on the TFP of cultural enterprises. These insights offer valuable strategic guidance for optimizing AI development in the postpandemic era.

Keywords: Digital economy; Artificial intelligence; Total factor productivity; Innovation value; Solow paradox (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:150:y:2025:i:c:s026499932500121x

DOI: 10.1016/j.econmod.2025.107126

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