统计与信息论坛

结合马歇尔外部性理论和新经济地理学理论，论述数字产业集聚所产生的正、负外部性效应对地区绿色全要素生产率的影响，并进一步探讨地方政府干预在这一过程中发挥的调节作用。基于2010—2021年省级面板数据，在刻画特征现状的基础上，对其影响效果、调节机制进行实证检验。研究发现：数字产业集聚规模逐年提高、分化程度逐步改善，但整体的分化格局仍未扭转；数字产业集聚规模、地区绿色全要素生产率的空间分布情况均呈现东高西低的特征。数字产业集聚所产生的正、负外部性对地区绿色全要素生产率的影响呈现先促进再抑制的倒U型曲线特征；异质性分析表明，数字产品制造业集聚对地区绿色全要素生产率的影响呈倒U型，数字技术应用业集聚的影响不具有统计显著性；中西部地区处于倒U型曲线的左端、正外部性占主导地位，东部地区部分省份过度集聚、负外部性涌现。数字产业集聚对地区绿色全要素生产率的影响更多地体现在对绿色技术进步的作用上，地方政府干预在这一过程中发挥了负向调节作用。

Rationally promoting digital industry agglomeration to enhance regional green total factor productivity serves as an effective approach to building a modern industrial system and achieving green development.Grounded in Marshall's externality theory and the agglomeration theory of new economic geography, digital industry agglomeration, regional GTFP,and local government intervention are integrated into a unified framework.The positive and negative externalities of the digital industry due to the four agglomeration mechanisms of sharing, matching, learning and competition, which have an impact on the regional green total factor productivity.Furthermore, the regulatory role of local government intervention in the process is analyzed.Using data from 30 provinces in China(2010-2021),digital industry agglomeration and regional GTFP are measured.A dynamic panel model and a nonlinear moderating effect model are employed to empirically test the influence mechanisms, impact channels, and the moderating role of local government intervention.Industial and regional heterogeneity are also explored.The findings indicate three key conclusions.First, the scale of digital industry agglomeration has steadily increased, with regional differentiation slightly improving, however, the overall trend still reflects multipolar development dynamics.Provincially, Beijing, Guangdong, Shanghai, Jiangsu, Tianjin, Fujian, and Zhejiang demonstrate comparative advantages as leading regions in digital industry development.Regionally, central and western regions exhibit lower levels of digital industry agglomeration compared to the eastern region, which remains dominant.The spatial distribution of digital industry agglomeration and regional GTFP aligns with economic development levels, both displaying an east-high, west-low pattern.Second, the relationship between digital industry agglomeration and regional GTFP follows an inverted U-shaped trajectory.During early stages, positive externalities dominate, enhancing GTFP.However, beyond the optimal scale, negative externalities, such as congestion and resource depletion, suppress further improvements.During the study period, the average agglomeration levels in Beijing, Guangdong, Shanghai, and Jiangsu exceeded the inverted U-curve's inflection point, highlighting pronounced negative externalities.The effects of agglomeration also vary by industries and regions.For digital product manufacturing, an inverted U-shaped relationship with GTFP is observed, while digital technology application industries show no significant impact.Regionally, central and western regions benefit from positive externalities, while some eastern provinces face over-agglomeration and rising negative effects.Last, the impact of digital industry agglomeration on regional green total factor productivity is primarily reflected in its role in driving green technological progress.Local government intervention, however, plays a negative moderating role in this process.These findings emphasize the need for policy adjustments that enhance positive externalities, mitigate negative impacts, and align with the dynamics of digital industry agglomeration.