摘要
探究碳生产率是否存在最优集聚规模,对于优化经济要素空间格局、促进低碳经济发展具有重要意义。文章基于2004—2019年省级面板数据构建动态空间面板模型,分析空间效应视角下经济集聚与碳生产率的内在联系及影响机制,结果表明:(1)经济集聚与碳生产率之间存在正“N”型曲线,且在稳健性检验后依旧成立。(2)碳生产率具有较强的时空依赖特征,在空间维度上表现出显著的正相关性,在时间维度上表现出明显的路径依赖。(3)产业结构在经济集聚对碳生产率的作用中存在显著的中介效应,经济集聚能够推动产业结构转型升级并促进碳生产率增长。基于此,本文从推进经济深度集聚,促进区域协调发展,推动产业结构升级等角度提出促进碳生产率增长的政策建议。
Exploring whether there is an optimal agglomeration scale for carbon productivity is of great significance for optimizing the spatial pattern of economic factors and promoting low-carbon economic development.The article constructs a dynamic spatial panel model based on provincial panel data from 2004 to 2019,analyzing the internal relationship and impact mechanism between economic agglomeration and carbon productivity from the perspective of spatial effects.The results show that:(1)there is a positive“N”curve between economic agglomeration and carbon productivity,and it still holds after robustness testing;(2)carbon productiv⁃ity has a strong spatiotemporal dependence,showing a significant positive correlation in the spatial dimension and a significant path dependence in the temporal dimension;(3)there is a significant mediating effect of industrial structure in the effect of econom⁃ic agglomeration on carbon productivity.Economic agglomeration can promote the transformation and upgrading of industrial struc⁃ture and promote carbon productivity growth.Based on this,this article proposes policy recommendations to promote carbon produc⁃tivity growth from the perspectives of promoting deep economic agglomeration,promoting regional coordinated development,and promoting industrial structure upgrading.
作者
杨成羽
熊晓炼
Yang Chengyu;Xiong Xiaolian(School of Economics,Guizhou University,Guiyang 550025,Guizhou,China;Development and Application Research Center of Marxist Economics,Guizhou University,Guiyang 550025,Guizhou,China)
出处
《新疆农垦经济》
2023年第9期25-34,共10页
Xinjiang State Farms Economy
基金
2023年贵州省教育厅高等学校人文社会科学研究项目(项目编号:23RWJD031)
2022年度贵州大学人文社会科学一般课题(项目编号:GDYB2022037)。
关键词
碳生产率
经济集聚
中介效应
空间计量
carbon productivity
economic agglomeration
mediation effect
spatial metrology