This paper investigates the role of regional specialization in ICT in fostering AI patenting performance and inter-regional spatial spillovers across China's provincial-level regions. Using panel fixed effects estimators, a Spatial Autoregressive Regression model and by adapting the technological frontier IV strategy on a comprehensive database covering 2006–2021, we find that positively selecting areas where regional ICT specialization is leveraged – the “picking the fittest” approach – can increase AI patenting performance while exacerbating regional disparities. Furthermore, we find that geographical proximity to developed AI regions impedes AI patenting progress in neighboring areas. The findings highlight the need for collaborative regional strategies and urge policy-makers to achieve a balance between strengthening regional specialization and promoting cooperation.
The 'picking the fittest' approach and spatial dynamics in China’s artificial intelligence regional development
Saverio Barabuffi;Jacopo Cricchio;Alberto Di Minin
2025-01-01
Abstract
This paper investigates the role of regional specialization in ICT in fostering AI patenting performance and inter-regional spatial spillovers across China's provincial-level regions. Using panel fixed effects estimators, a Spatial Autoregressive Regression model and by adapting the technological frontier IV strategy on a comprehensive database covering 2006–2021, we find that positively selecting areas where regional ICT specialization is leveraged – the “picking the fittest” approach – can increase AI patenting performance while exacerbating regional disparities. Furthermore, we find that geographical proximity to developed AI regions impedes AI patenting progress in neighboring areas. The findings highlight the need for collaborative regional strategies and urge policy-makers to achieve a balance between strengthening regional specialization and promoting cooperation.| File | Dimensione | Formato | |
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