How Does Manufacturing Agglomeration Affect Green Development? A Spatial and Nonlinear Perspective

Abstract

Developing high-quality manufacturing industries and realizing green transformation are relatively pressing issues in the 21st century. Existing studies only focus on the economic or environmental effects of agglomeration, and the combined effects of manufacturing agglomeration have been neglected. Therefore, by referring to industrial agglomeration theory and constructing a theoretical analytical framework for manufacturing agglomeration and green development, this paper adopts the spatial panel Durbin model and mediating effect model with the panel data from China’s Yangtze River Economic Belt to empirically test the influence and its mechanism of manufacturing agglomeration on green development. The results show that: (1) There are significant temporal and spatial differences in green development in the Yangtze River Economic Belt. Overall, green development has maintained a steady increase on the timeline, but each region shows a hierarchical structure of “multiple peaks-multiple centers”. (2) There is a typical inverted U-shaped relationship between manufacturing agglomeration and green development, and the linear and quadratic coefficients of manufacturing agglomeration are −0.585 and −0.167, respectively. (3) Under the constraints of temporal, spatial, and urban heterogeneity, the impacts of manufacturing agglomeration on green development show significant differences. (4) Manufacturing agglomeration affects green development through three paths: the labor force upgrading effect, industrial structure upgrading effect, and technological innovation effect. The study can provide a theoretical and empirical basis for the green development of developing countries around the world.

Identifying impacts of industrial co-agglomeration on carbon emissions: Evidence from China

“…Second, the crowding effect of IC also exerts a harmful influence on carbon emissions, which mainly comes from the regional heterogeneity of industry spatial layout. For instance, excessive labor agglomeration may distort the factor market and bring out a series of urgent issues, such as the congestion effect, high energy utilization, and more pollutant emissions, which is an obstacle to the coordinated development of the economy and environment (20,39). Hence, China is still facing severe pressure on carbon emission reduction due to the adverse effects of IC, especially the energy consumption effect and population crowding effect.…”

“…The final category of literature has made the assertion that the nexus between IC and environmental pollutant emission issues is non-linear in different development stages from the diversity perspectives (18)(19)(20). For example, a typical non-linear shaped nexus between IC and green development (21), haze pollution (22), and industrial eco-efficiency (23) have been proposed in recent research.…”

“…For example, a typical non-linear shaped nexus between IC and green development (21), haze pollution (22), and industrial eco-efficiency (23) have been proposed in recent research. In addition, the multiform nonlinear relationship between IC and carbon emissions is also gradually being proposed and proved by scholars, such as inverted N-shaped nexus (24,25), an inverse U-curve nexus (8,26), a U-curve nexus (7,20), and so on. Besides, there are a number of scholars have considered the relationship between them in depth from different perspectives.…”

“…The final category of literature has made the assertion that the nexus between IC and environmental pollutant emission issues is non-linear in different development stages from the diversity perspectives ( 18 – 20 ). For example, a typical non-linear shaped nexus between IC and green development ( 21 ), haze pollution ( 22 ), and industrial eco-efficiency ( 23 ) have been proposed in recent research. In addition, the multiform nonlinear relationship between IC and carbon emissions is also gradually being proposed and proved by scholars, such as inverted N-shaped nexus ( 24 , 25 ), an inverse U-curve nexus ( 8 , 26 ), a U-curve nexus ( 7 , 20 ), and so on.…”

Government innovation support for green development efficiency in China: A regional analysis of key factors based on the dynamic GMM model

“…Researchers have found that moderate decentralization ability (Wu and Wu, 2018) and performance appraisal system (Huang, 2017) are among the important factors promoting government innovation. The third stream, the influence mechanism of government innovation diffusion, explores the precise framework through which government innovation occurs in a certain region (e.g., Guo and Zhang, 2020;Yuan et al, 2022). The diffusion of government innovation refers to the process through which government innovation policies or projects are spread in a certain social system through certain channels.…”