Zhou Mengling, Ye Yaojun, Huang Yaru
School of Sciences, Zhejiang University of Science and Technology, Hangzhou, 310023, China.
Environ Sci Pollut Res Int. 2023 Jan;30(3):7087-7105. doi: 10.1007/s11356-022-22650-4. Epub 2022 Aug 27.
The problem of environmental pollution is becoming more and more prominent. Making ecological governance take an effective and sustainable development path has become a complex problem for countries to think about. The proposal of green governance provides new ideas for governments to manage enterprises and local environmental governance. The DEA method is commonly used to measure the effectiveness of environmental governance, but the traditional DEA method ignores environmental factors and management factors, and the measurement error is significant. Therefore, this paper introduces the total waste discharge and PM2.5 average concentration and other unexpected outputs, using the three-stage DEA model and three-stage DEA Malmquist index model, creatively constructing the green governance measurement index system, which measures and evaluates the green governance efficiency of 30 provinces in China from 2004 to 2019 from static and dynamic perspectives. The research results show that the efficiency value obtained by the three-stage DEA model is higher than the first stage, which confirms that the external environmental factors have a specific impact on the GGE. At the same time, the comprehensive technical efficiency value presents a "U"-shaped trend with time. From the perspective of sub-regions, there is heterogeneity in the efficiency values between regions, showing a decreasing trend of "east, west, and middle." From the efficiency decomposition results, the main reason for the negative growth rate of GGE is the low efficiency of technological progress, which provides targeted suggestions for governance in various regions of China. This study will help provinces prepare to strengthen investment in technological innovation, maximize the benefits of input and output, and promote green and sustainable development.
环境污染问题日益突出。使生态治理走上有效且可持续的发展道路已成为各国需要思考的复杂问题。绿色治理的提出为政府管理企业和地方环境治理提供了新思路。数据包络分析(DEA)方法常用于衡量环境治理的有效性,但传统DEA方法忽视了环境因素和管理因素,测量误差较大。因此,本文引入总废弃物排放量和PM2.5平均浓度等非期望产出,运用三阶段DEA模型和三阶段DEA-Malmquist指数模型,创新性地构建绿色治理测量指标体系,从静态和动态两个视角对2004—2019年中国30个省份的绿色治理效率进行测度与评价。研究结果表明,三阶段DEA模型得出的效率值高于第一阶段,证实了外部环境因素对绿色治理效率有显著影响。同时,综合技术效率值随时间呈“U”形趋势。从子区域角度看,各区域间效率值存在异质性,呈现出“东部、西部、中部”递减的趋势。从效率分解结果来看,绿色治理效率负增长的主要原因是技术进步效率低下,这为中国各地区的治理提供了针对性建议。本研究将有助于各省准备加强技术创新投入,最大化投入产出效益,促进绿色可持续发展。