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Measuring environmental performance of industrial sub-sectors in China: A stochastic metafrontier approach

机译:衡量中国工业子行业的环境性能:随机地区方法

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In this paper, we quantitatively measure the environmental performance and potential capacities of carbon emission mitigation of 39 industrial sectors in China during 2005-2011 by adopting a stochastic metafrontier approach. We also analyze the differences of environmental performance and technology gap ratios (TGRs) across three categorized industrial groups. Cluster analysis of carbon intensity provides the categorized groups. The results show that due to neglect of technology gaps among the categorized groups, the environmental performance measured by a stochastic frontier approach (SFA) is underestimated. Comparison analysis infers that, relative to the metafrontier, the industrial sectors in Group 1 achieve the highest environmental performance and TGRs, while environmental performance and TGRs of industrial sectors in Group 3 is still at a low level for lack of advanced production technology. Industrial sectors also perform significant differences on potential capacities of carbon emission mitigation. We suggest that policies and regulations on industrial technology innovation and control of carbon emissions should be strengthened for eco-efficient and sustainable development. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在本文中,我们通过采用随机式联合方法,定量衡量2005 - 2011年中国39个工业部门碳排放的环境绩效和潜在能力。我们还分析了三个分类的工业集团环境绩效和技术差距比率(TGRS)的差异。碳强度的集群分析提供了分类组。结果表明,由于忽视了分类组之间的技术差距,低估了通过随机前沿方法(SFA)测量的环境性能。比较分析infers认为,相对于Metafr之间,第1组的工业部门实现了最高的环境性能和TGR,而第3组的工业部门的环境表现和TGR仍处于缺乏先进生产技术的低水平。工业部门还对碳排放减缓潜在能力进行了显着差异。我们建议生态效率和可持续发展,应加强对工业技术创新和碳排放控制的政策和规定。 (c)2016 Elsevier Ltd.保留所有权利。

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