理解中国绿色经济的效率与演变:一个省级分析

IF 4 4区 环境科学与生态学 Q2 ENVIRONMENTAL STUDIES
Yanyong Hu, Xuchao Zhang, Jiaxi Wu, Zheng Meng
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引用次数: 0

摘要

明确各省区绿色经济的效率水平、演化特征和驱动因素,实现经济高质量发展,实现中国“双碳”目标。本文采用考虑非预期产出的超有效松弛模型,对2005 - 2020年中国30个省(区、市)的省级绿色经济效率(GEE)分析进行了评价。此外,通过核密度估计估计了GEE发展的分布和动态演化趋势。此外,利用本研究构建的面板向量自回归模型,对经济发展水平及其影响因素(产业结构合理化[ISR]、产业结构先进性[ISA]和城镇化水平[UL])进行了检验。研究结果表明,中国的能效水平总体呈现先下降后稳定再上升的“u”型发展趋势,而整体效率水平较低,全国能效平均值为0.6934。区域GEE水平呈显著的“阶梯”型分布,东部、中部和西部分别为最高、第二级和最低。能源效率水平各省间差异显著,大部分处于中等效率水平。值得注意的是,60%的地区在2020年达到了中等效率。ISR、ISA和UL水平对促进绿色经济增长具有重要作用。本研究为中国绿色经济增长的驱动因素提供了有价值的见解,为实现可持续低碳经济的政策决策提供了指导。随着中国努力实现其雄心勃勃的碳减排目标,本研究的结果强调了继续在省级优先考虑绿色经济发展的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding the efficiency and evolution of China's Green Economy: A province-level analysis
The efficiency level, evolution characteristics, and factors driving the green economy in all provinces and regions should be clarified to achieve high-quality economic development and meet China's “double carbon” target. This study conducted the Super-Effective Slack-Based Model considering unexpected outputs to evaluate province-level Green Economic Efficiency (GEE) analysis (including 30 provinces, autonomous regions, and municipalities directly under the Central Government) in China from 2005 to 2020. Moreover, the distribution and dynamic evolution trend of GEE development was estimated through Kernel density estimation. Besides, GEE and its factors (i.e., industrial structure rationalization [ISR], industrial structure advancement [ISA], and urbanization level [UL]) were examined using a Panel vector autoregressive model that was built in this study. As indicated by the result of this study, China's GEE level generally displayed a “U-shaped” development trend of declining, stabilizing, and then rising, whereas the overall efficiency level is low, where the national GEE average reached 0.6934. The regional GEE level exhibited a significant “ladder” distribution, with the highest level, the second level, and the lowest level in the east, the middle, and the west, respectively. The GEE level varied significantly with the province, and most of the levels were at a medium efficiency level. Notably, 60% of regions had medium efficiency in 2020. The levels of ISR, ISA, and UL play significant roles in boosting green economic growth. This study provides valuable insights into the drivers of green economic growth in China guiding policy decisions on achieving a sustainable and low-carbon economy. As China strives to fulfill its ambitious carbon reduction goals, the findings of this study highlight the significance of continuing to prioritize green economic development at the provincial level.
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来源期刊
Energy & Environment
Energy & Environment ENVIRONMENTAL STUDIES-
CiteScore
7.60
自引率
7.10%
发文量
157
期刊介绍: Energy & Environment is an interdisciplinary journal inviting energy policy analysts, natural scientists and engineers, as well as lawyers and economists to contribute to mutual understanding and learning, believing that better communication between experts will enhance the quality of policy, advance social well-being and help to reduce conflict. The journal encourages dialogue between the social sciences as energy demand and supply are observed and analysed with reference to politics of policy-making and implementation. The rapidly evolving social and environmental impacts of energy supply, transport, production and use at all levels require contribution from many disciplines if policy is to be effective. In particular E & E invite contributions from the study of policy delivery, ultimately more important than policy formation. The geopolitics of energy are also important, as are the impacts of environmental regulations and advancing technologies on national and local politics, and even global energy politics. Energy & Environment is a forum for constructive, professional information sharing, as well as debate across disciplines and professions, including the financial sector. Mathematical articles are outside the scope of Energy & Environment. The broader policy implications of submitted research should be addressed and environmental implications, not just emission quantities, be discussed with reference to scientific assumptions. This applies especially to technical papers based on arguments suggested by other disciplines, funding bodies or directly by policy-makers.
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