趋同(经济学)
索引(排版)
集聚经济
构造(python库)
生态效率
计量经济模型
经济
环境经济学
绿色发展
空间计量经济学
计量经济学
产业组织
计算机科学
可持续发展
微观经济学
经济增长
生态学
万维网
程序设计语言
生物
作者
Nan Zhao,Xiaojie Liu,Pan Chang-feng,Chenyang Wang
标识
DOI:10.1016/j.seps.2021.101062
摘要
In this new stage of global economic development, we hope to achieve both economic development and environmental improvements via innovation. Green innovation aims to meet the dual goals of economic development and ecological protection. The scientific evaluation of the performance of China's green innovation appears to be quite meaningful. Some studies have evaluated the performance of green innovation, but are limited by the use of a single efficiency measurement method. To fill this research gap, this article uses a combination of two methods to evaluate green innovation efficiency, which provides a more precise evaluation of efficiency. Specifically, this article uses the vertical-and-horizontal scatter degree method to construct a pollutant index and then sets that index as the undesirable output in a slacks-based measure (SBM) model to evaluate efficiency. To further study the regional differences in green innovation efficiency, this article uses a convergence model. Most existing convergence analyses ignore spatial elements. Focusing on the influence of spatial factors, this article introduces a spatial econometric model into the convergence analyses. This article draws the following main conclusions. (i) The efficiency of green innovation in the country as a whole has been increasing each year, and green innovation efficiency in the central and western regions has increased significantly. (ii) Regional differences have narrowed each year. (iii) Green innovation efficiency is significantly positively spatially correlated, which is reflected in the spatial agglomeration of regions with the same efficiency level. (iv) Green innovation efficiency exhibits σ-convergence and spatial conditional β-convergence. (iv) Spatial factors accelerate the convergence of green innovation efficiency.
科研通智能强力驱动
Strongly Powered by AbleSci AI