Econometric analysis demonstrates that cross-regional digital knowledge flows reduce regional economic disparities in China, suggesting that technological diffusion fosters balanced growth.
Regional coordinated development requires achieving sustained economic growth and balanced development in per capita terms on the basis of regional synergy. In the digital economy era, digital knowledge has become a source of technological progress and economic growth, and constitutes an important force for promoting regional coordinated development in China. Using a fine-tuned BERT (Bidirectional Encoder Representations from Transformers) model, which is a kind of language model, and patent citation information, this paper measures the cross-regional flow of digital knowledge. By further integrating nighttime light data and population grid data, it thoroughly examines the impact of digital knowledge flow on regional coordinated development, thereby endowing traditional growth theory with new connotations in the digital age. The findings indicate that digital knowledge flowing from developed regions to less developed regions can promote regional coordinated development. Mechanism analysis shows that, under the premise that industries in less developed regions are compatible with digital knowledge, improving the adaptability of the supply side to demand to alleviate factor endowment gaps is a key pathway through which digital knowledge flow facilitates regional coordinated development. Heterogeneity analysis reveals that digital knowledge flowing from developed eastern cities to less developed central and western cities, from large developed cities to small less developed cities, and among cities at similar development levels, exhibits stronger effects in promoting regional coordinated development. Further analysis finds that digital knowledge flowing from central districts/counties to peripheral districts/counties within cities can significantly alleviate the “center–periphery” pattern, and this effect is persistent over the long term.
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Ma et al. (2026) studied this question.
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