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

被引：29

作者：

Bai, Yuping ^{[1
,2
,3
]}

Deng, Xiangzheng ^{[1
,2
,3
]}

Zhang, Qian ^{[1
,2
]}

Wang, Zhan ^{[1
,2
,4
]}

机构：

[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China

[2] Chinese Acad Sci, Ctr Chinese Agr Policy, Beijing 100101, Peoples R China

[3] Univ Chinese Acad Sci, Beijing 100149, Peoples R China

[4] Beijing Forestry Univ, Sch Econ & Management, Beijing 100083, Peoples R China

来源：

PHYSICS AND CHEMISTRY OF THE EARTH | 2017年 / 101卷

基金：

中国国家自然科学基金;

关键词：

Environmental performance; Metafrontier; SFA; China's industry; EFFICIENCY ANALYSIS; TECHNOLOGY; DEA; INTENSITY; EMISSIONS; COUNTRIES; MODEL;

D O I：

10.1016/j.pce.2016.12.007

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

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.

引用

页码：3 / 12

页数：10

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