Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China

Industrial waste discharged by heavy pollution industry is one of the main causes of global environmental degradation. Research on the environmental efficiency of high-polluting industry is necessary to tackle the problem of global environmental pollution. Using panel data of 19 sub-industries in Ch...

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Main Authors: Jun Xu, Yuchen Jiang, Xin Guo, Li Jiang
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:International Journal of Environmental Research and Public Health
Subjects:
DEA
Online Access:https://www.mdpi.com/1660-4601/18/11/5761
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spelling doaj-1c8cba93fa7746ce84faa7a76a4b6d872021-06-01T01:20:47ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012021-05-01185761576110.3390/ijerph18115761Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from ChinaJun Xu0Yuchen Jiang1Xin Guo2Li Jiang3School of Business, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Business, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Business, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Business, Jiangsu Normal University, Xuzhou 221116, ChinaIndustrial waste discharged by heavy pollution industry is one of the main causes of global environmental degradation. Research on the environmental efficiency of high-polluting industry is necessary to tackle the problem of global environmental pollution. Using panel data of 19 sub-industries in China’s heavy pollution industry from 2001 to 2015, this article employs Data Envelopment Analysis (DEA) and Malmquist index (MI) to measure the environmental efficiency of heavy pollution industry from both the dynamic and static perspectives. The results show that the environmental efficiency of China’s heavy pollution industry maintains an upward trend but did not reach the optimal level. The general trend shows a phased trend of increasing first and then decreasing. Besides, there are inter-industry differences in the environmental efficiency across the examined sub-industries. Based on the research findings, this article proposes a set of corresponding countermeasures to solve the global pollution problem, such as reducing energy inputs and minimizing the volumes of the main categories of emissions in high-polluting industry, as well as improving the production management in the group of high environmental efficiency and strengthening technical capabilities in the group of low environmental efficiency.https://www.mdpi.com/1660-4601/18/11/5761environmental efficiencyheavy pollution industryDEAMalmquist indexenvironmental pollutionglobal problem
collection DOAJ
language English
format Article
sources DOAJ
author Jun Xu
Yuchen Jiang
Xin Guo
Li Jiang
spellingShingle Jun Xu
Yuchen Jiang
Xin Guo
Li Jiang
Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China
International Journal of Environmental Research and Public Health
environmental efficiency
heavy pollution industry
DEA
Malmquist index
environmental pollution
global problem
author_facet Jun Xu
Yuchen Jiang
Xin Guo
Li Jiang
author_sort Jun Xu
title Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China
title_short Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China
title_full Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China
title_fullStr Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China
title_full_unstemmed Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China
title_sort environmental efficiency assessment of heavy pollution industry by data envelopment analysis and malmquist index analysis: empirical evidence from china
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1661-7827
1660-4601
publishDate 2021-05-01
description Industrial waste discharged by heavy pollution industry is one of the main causes of global environmental degradation. Research on the environmental efficiency of high-polluting industry is necessary to tackle the problem of global environmental pollution. Using panel data of 19 sub-industries in China’s heavy pollution industry from 2001 to 2015, this article employs Data Envelopment Analysis (DEA) and Malmquist index (MI) to measure the environmental efficiency of heavy pollution industry from both the dynamic and static perspectives. The results show that the environmental efficiency of China’s heavy pollution industry maintains an upward trend but did not reach the optimal level. The general trend shows a phased trend of increasing first and then decreasing. Besides, there are inter-industry differences in the environmental efficiency across the examined sub-industries. Based on the research findings, this article proposes a set of corresponding countermeasures to solve the global pollution problem, such as reducing energy inputs and minimizing the volumes of the main categories of emissions in high-polluting industry, as well as improving the production management in the group of high environmental efficiency and strengthening technical capabilities in the group of low environmental efficiency.
topic environmental efficiency
heavy pollution industry
DEA
Malmquist index
environmental pollution
global problem
url https://www.mdpi.com/1660-4601/18/11/5761
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AT yuchenjiang environmentalefficiencyassessmentofheavypollutionindustrybydataenvelopmentanalysisandmalmquistindexanalysisempiricalevidencefromchina
AT xinguo environmentalefficiencyassessmentofheavypollutionindustrybydataenvelopmentanalysisandmalmquistindexanalysisempiricalevidencefromchina
AT lijiang environmentalefficiencyassessmentofheavypollutionindustrybydataenvelopmentanalysisandmalmquistindexanalysisempiricalevidencefromchina
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