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The comprehensive environmental efficiency of socioeconomic sectors in China: An analysis based on a non-separable bad output SBM

The increasingly high frequency of heavy air pollution in most regions of China signals the urgent need for the transition to an environmentally friendly production performance by socioeconomic sectors for the sake of people's health and sustainable development. Focusing on CO2 and major air pollutants, this paper presents a comprehensive environmental efficiency index based on evaluating the environmental efficiency of major socioeconomic sectors, including agriculture, power, industry, residential and transportation, at the province level in China in 2010 based on a slack-based measure DEA model with non-separable bad output and weights determined by the coefficient of variation method. In terms of the environment, 5, 16, 6, 7 and 4 provinces operated along the production frontier for the agricultural, power, industrial, residential and transportation sectors, respectively, in China in 2010, whereas Shanxi, Heilongjiang, Ningxia, Hubei and Yunnan showed lowest efficiency correspondingly. The comprehensive environmental efficiency index varied from 0.3863 to 0.9261 for 30 provinces in China, with a nationwide average of 0.6383 in 2010; Shanghai ranked at the top, and Shanxi was last. Regional disparities in environmental efficiency were identified. A more detailed inefficiency decomposition and benchmarking analysis provided insight for understanding the source of comprehensive environmental inefficiency and, more specifically, the reduction potential for CO2 and air pollutants. Some specific research and policy implications were uncovered from this work.
- Tsinghua University China (People's Republic of)
- University College of London United Kingdom
- Chinese Academy of Agricultural Sciences China (People's Republic of)
- UNIVERSITY COLLEGE LONDON United Kingdom
- Beijing Institute of Technology China (People's Republic of)
690, Technology, China, AGRICULTURAL SECTOR, 330, INDUSTRIAL SECTORS, DATA ENVELOPMENT ANALYSIS, Environmental Sciences & Ecology, Environmental, Engineering, Slack-based model, Environmental efficiency, GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY, Data envelop analysis, Science & Technology, POWER INDUSTRY, ENERGY EFFICIENCY, DEA MODEL, UNDESIRABLE OUTPUTS, PERFORMANCE, CO2 EMISSIONS, Science & Technology - Other Topics, TRANSPORTATION INDUSTRY, Socioeconomic sectors, Life Sciences & Biomedicine, Environmental Sciences, Air pollutants
690, Technology, China, AGRICULTURAL SECTOR, 330, INDUSTRIAL SECTORS, DATA ENVELOPMENT ANALYSIS, Environmental Sciences & Ecology, Environmental, Engineering, Slack-based model, Environmental efficiency, GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY, Data envelop analysis, Science & Technology, POWER INDUSTRY, ENERGY EFFICIENCY, DEA MODEL, UNDESIRABLE OUTPUTS, PERFORMANCE, CO2 EMISSIONS, Science & Technology - Other Topics, TRANSPORTATION INDUSTRY, Socioeconomic sectors, Life Sciences & Biomedicine, Environmental Sciences, Air pollutants
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).55 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
