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基于环境压力视角的东北老工业基地生态效率研究 被引量:4

Study on the eco-efficiency of old northeastern industrial base of China from the perspective of environmental pressure
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摘要 基于整体和4类环境压力视角,结合数据包络分析(DEA)窗口分析法,测算2012—2017年东北老工业基地23个地级市的生态效率,并考察其地区差异与动态演变特征,结合面板Tobit回归模型检验东北老工业基地生态效率的影响机制。结果表明:在考察期内,东北老工业基地整体生态效率水平偏低且呈小幅度波动下降趋势;不同省市区域差异明显且节能减排潜力巨大;经济发展水平、环境规制对东北老工业基地生态效率有显著的正效应,而产业结构和过低的科技水平则抑制了其生态效率的提升。总的来说,应优化东北老工业基地的产业结构,提升以绿色技术为主力的高新技术产业的比重,实行节能减排,以此提高东北老工业基地的生态效率。 From the perspective of the overall and 4 kinds of environmental pressure,data envelopment analysis(DEA)window analysis were utilized to measure the eco-efficiency of 23 cities in old northeastern industrial base of China over the period of 2012-2017,and their regional differences and evolution trends were analyzed.Tobit regression model was used to analyze the influencing factors of eco-efficiency.Results showed that the eco-efficiency of old northeastern industrial base was still low and displayed a fluctuating downward trend.Regional differences were remarkable and there was great potential for resource saving and pollution reduction.Economic development and environmental regulation had significant positive effects on the eco-efficiency of old northeastern industrial base,however,the industrial structure and the low level of science and technology restricted the improvement of eco-efficiency.Generally speaking,the industrial structure of old northeastern industrial base should be optimized,proportion of high-tech industry should be increased where green technology played a leading role,and energy-saving emission reduction should be implemented,so as to improve the eco-efficiency of old northeastern industrial base.
作者 尹妮妮 汪克亮 YIN Nini;WANG Keliang(School of Economics and Management,Anhui University of Science and Technology,Huainan Anhui 232001)
出处 《环境污染与防治》 CAS CSCD 北大核心 2020年第12期1542-1548,共7页 Environmental Pollution & Control
基金 国家自然科学基金资助项目(No.71973131) 教育部人文社会科学研究项目(No.13YJC790136)。
关键词 环境压力 东北老工业基地 生态效率 数据包络分析 TOBIT回归模型 environmental pressure old northeastern industrial eco-efficiency DEA Tobit regression model
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