中国电力行业绿色全要素生产率分析
Analysis of Green Total Factor Productivity in China′s Power Industry
邹宇桢1
作者信息
- 1. 国家电投集团山东电力有限公司,山东 济南 250000
- 折叠
摘要
为促进中国电力行业可持续发展,采用DEA方法对2016-2020年全国30个省区市(除西藏外)的电力行业绿色全要素生产率进行测算并对其时间和空间变动特征进行分析.结果表明,2016-2020年在中国30个省区市(除西藏外)电力行业绿色全要素生产率为1.000 7,绿色技术进步平均值为1.000 2,绿色技术效率平均值1.005 1.相比于经济发展因素,环境治理和科技投入等绿色发展因素对绿色全要素生产率、绿色技术效率和绿色技术进步的影响更显著.从时间特征来看绿色全要素生产率呈现波动的趋势,空间特征来看呈现地区性不平衡的特征.为此,进一步提出要着重关注技术进步,通过减碳技术和减碳设备的运用等,优化电力行业投入产出比,提升电力行业运行的稳定性,减少绿色全要素生产率波动性等建议.
Abstract
To promote the sustainable development of the electricity industry in China,the Data Envelopment Analysis(DEA)method was used to measure the green total factor productivity(GTFP)of the electricity industry in 30 provinces,municipalities,and autonomous regions in China from 2016 to 2020 and its practical and spatial varia-tion characteristics were analyzed.The results indicate that from 2016 to 2020,the GTFP in the electricity industry of 30 provinces,municipalities and autonomous regions(except Tibet)in China is 1.000 7,the average green techno-logical progress is 1.000 2,and the average green technical efficiency is 1.005 1.Compared with economic develop-ment factors,green development factors such as environmental governance and scientific and technological invest-ment have a more significant impact on green total factor productivity,green technological efficiency,and green technological progress.From the perspective of time characteristics,GTFP shows a fluctuating trend,and from the perspective of space characteristics,it shows the characteristics of regional imbalances.Therefore,it is further pro-posed to focus on technological progress,optimize the input-output ratio of the electricity industry through the appli-cation of carbon reduction technologies and equipment,enhance the stability of the electricity industry′s operations,and reduce the volatility of GTFP and other suggestions.
关键词
电力/绿色全要素生产率/绿色技术效率/绿色技术进步/时间特征/空间特征Key words
electricity/green total factor productivity/green technical efficiency/green technological prog-ress/temporal characteristics/spatial characteristics引用本文复制引用
出版年
2024
NETL
NSTL
万方数据