Department of Business, Zhengzhou University, Zhengzhou, China.
PLoS One. 2024 Sep 6;19(9):e0307893. doi: 10.1371/journal.pone.0307893. eCollection 2024.
Based on panel data collected from 2003 to 2020 across 30 provinces in China, the paper employs the spatial vector angle method and spatial Durbin model to investigate industrial agglomeration's nonlinear and spatial spillover effects on the energy consumption structure's low-carbon transition process (Lct). The results indicate the following: First, the influence of industrial agglomeration on Lct exhibits an inverted U-shaped pattern. As the degree of industrial agglomeration expands, its effect on Lct shifts from positive to negative. Second, industrial agglomeration demonstrates spatial spillover effects. It promotes the improvement of Lct in neighboring provinces through agglomeration effects. However, the continuous expansion of industrial agglomeration inhibits the improvement of Lct in neighboring provinces through congestion effects. Third, the heterogeneity test finds that industrial agglomeration has a significant role in promoting Lct in the samples of eastern region, but this effect is not significant in the samples of western and middle regions.
基于 2003 年至 2020 年中国 30 个省份的面板数据,本文采用空间向量角方法和空间杜宾模型,考察了产业集聚对能源消费结构低碳转型过程(Lct)的非线性和空间溢出效应。结果表明:第一,产业集聚对 Lct 的影响呈倒 U 型模式。随着产业集聚程度的扩大,其对 Lct 的影响由正转负。第二,产业集聚具有空间溢出效应。通过集聚效应促进了邻近省份 Lct 的改善。然而,产业集聚的不断扩大通过拥挤效应抑制了邻近省份 Lct 的改善。第三,异质性检验发现,产业集聚在东部地区样本中对 Lct 的促进作用显著,但在西部地区和中部地区样本中不显著。