Analysis reveals increasing economic inequality due to digital transformation in China, suggesting regional innovation capacity moderates effects.
The digital economy serves as a new engine for China's economic growth and plays a key role in addressing the principal contradiction of unbalanced and inadequate development. In-depth exploration of the impact of digital transformation on regional coordinated development is of great significance for resolving China's principal contradiction. This study is based on balanced panel data from 284 prefecture-level and above cities in China from 2011 to 2022. Using a double fixed-effects model, it empirically finds that digital transformation has overall exacerbated regional economic inequality during the sample period. Further mechanism analysis reveals the key forces behind this phenomenon: regional innovation capacity and the agglomeration of production factors play moderating roles in opposite directions. Specifically, a higher regional innovation capacity significantly amplifies the effect of digital transformation on widening regional gaps, while the agglomeration of production factors effectively mitigates this expansion. This inherent contradiction explains the complexity of the impact of digital transformation. The impact of digital transformation is not static but exhibits significant spatial and temporal heterogeneity. In the eastern and central regions, it actually promotes coordinated regional development. Moreover, its effectiveness shows distinct stage-specific dynamic characteristics with the advancement of major regional coordination policies (such as the series of deployments after the 19th National Congress of the Communist Party of China). After a series of robustness and endogeneity tests, the above core conclusions remain reliable. These research findings provide important theoretical basis and policy insights for understanding the new patterns of regional development in the digital economy era and formulating precise and effective regional coordination policies.
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Qi Luo (2025) studied this question.