(untitled) (Lex localis - Journal of Local Self-Government, 2025)
This study theoretically explores the underlying mechanisms through which China’s AI-specific policies influence the allocation of labor resources and empirically examines this relationship using panel data from 224 prefecture-level cities in China from 2010 to 2020. The results indicate that AI policies have significantly improved labor resource allocation efficiency in these cities, a conclusion that remains robust across various sensitivity tests. Moreover, the policy effects exhibit notable heterogeneity across regions. Due to differences in economic foundations and resource endowments, the effectiveness of policy implementation varies significantly across different areas. Additionally, the role of policy tools, particularly in the areas of policy goals, research and development (R&D) support, and development environments, has proven crucial in enhancing labor resource allocation efficiency. Finally, the study also finds that AI policies have had a profound indirect impact on labor resource allocation by promoting the synchronous upgrading of industrial structures and optimizing the innovation element structure. The findings affirm the positive role of government intervention in improving labor resource allocation, enriching the research on labor economics and the use of policy tools, and providing important empirical evidence for optimizing AI policy delivery and enhancing its implementation effectiveness in developing countries. This study offers valuable insights for policy practice in labor markets.