Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China

The mining industry is one of the pillar industries of Guangxi’s economic and social development. The output value of mining and related industries accounts for 27% of the whole district’s total industrial output value. Therefore, the mining eco-efficiency measurement in Guangxi can be of great sign...

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Main Authors: Yonglin Li, Zhili Zuo, Deyi Xu, Yi Wei
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:https://www.mdpi.com/1660-4601/18/10/5397
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spelling doaj-7e26d384f77146ca8d5910743f0d89612021-06-01T00:24:22ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012021-05-01185397539710.3390/ijerph18105397Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, ChinaYonglin Li0Zhili Zuo1Deyi Xu2Yi Wei3School of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaSchool of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaSchool of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaSchool of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaThe mining industry is one of the pillar industries of Guangxi’s economic and social development. The output value of mining and related industries accounts for 27% of the whole district’s total industrial output value. Therefore, the mining eco-efficiency measurement in Guangxi can be of great significance for the sustainable development of Guangxi’s mining industry. This study adopted Meta-US-SBM to measure the mining eco-efficiency in Guangxi from 2008 to 2018, including economic efficiency, resource efficiency, and environmental efficiency. It used the standard deviation ellipse model to simulate the migration trend of four efficiencies in Guangxi and used GeoDetector and Tobit models to explore the internal and external factors that affect the mining eco-efficiency. The four efficiencies in Guangxi show large temporal and spatial heterogeneity, and the internal and external factors that affect the mining eco-efficiency are different. The following conclusions can be drawn. (1) Environmental efficiency and mining eco-efficiency are improving, while economic efficiency and resource efficiency are deteriorating. Cities bordering other provinces have a significantly better mining eco-efficiency than non-bordering cities. (2) The development center in Guangxi has migrated to the Beibu Gulf Economic Zone. (3) Natural resources index and mining economic scale have a great impact on the mining eco-efficiency, and with the increase of the mining economic scale, the mining eco-efficiency showed a typical “U-shaped” curve. Finally, this study put forward corresponding policy recommendations to improve the mining eco-efficiency in Guangxi from four aspects: opening-up, technological progress, regional coordination, and government control.https://www.mdpi.com/1660-4601/18/10/5397mining eco-efficiencyMeta-US-SBMstandard deviation ellipse modelGeoDetectorTobit ModelGuangxi
collection DOAJ
language English
format Article
sources DOAJ
author Yonglin Li
Zhili Zuo
Deyi Xu
Yi Wei
spellingShingle Yonglin Li
Zhili Zuo
Deyi Xu
Yi Wei
Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China
International Journal of Environmental Research and Public Health
mining eco-efficiency
Meta-US-SBM
standard deviation ellipse model
GeoDetector
Tobit Model
Guangxi
author_facet Yonglin Li
Zhili Zuo
Deyi Xu
Yi Wei
author_sort Yonglin Li
title Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China
title_short Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China
title_full Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China
title_fullStr Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China
title_full_unstemmed Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China
title_sort mining eco-efficiency measurement and driving factors identification based on meta-us-sbm in guangxi province, china
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1661-7827
1660-4601
publishDate 2021-05-01
description The mining industry is one of the pillar industries of Guangxi’s economic and social development. The output value of mining and related industries accounts for 27% of the whole district’s total industrial output value. Therefore, the mining eco-efficiency measurement in Guangxi can be of great significance for the sustainable development of Guangxi’s mining industry. This study adopted Meta-US-SBM to measure the mining eco-efficiency in Guangxi from 2008 to 2018, including economic efficiency, resource efficiency, and environmental efficiency. It used the standard deviation ellipse model to simulate the migration trend of four efficiencies in Guangxi and used GeoDetector and Tobit models to explore the internal and external factors that affect the mining eco-efficiency. The four efficiencies in Guangxi show large temporal and spatial heterogeneity, and the internal and external factors that affect the mining eco-efficiency are different. The following conclusions can be drawn. (1) Environmental efficiency and mining eco-efficiency are improving, while economic efficiency and resource efficiency are deteriorating. Cities bordering other provinces have a significantly better mining eco-efficiency than non-bordering cities. (2) The development center in Guangxi has migrated to the Beibu Gulf Economic Zone. (3) Natural resources index and mining economic scale have a great impact on the mining eco-efficiency, and with the increase of the mining economic scale, the mining eco-efficiency showed a typical “U-shaped” curve. Finally, this study put forward corresponding policy recommendations to improve the mining eco-efficiency in Guangxi from four aspects: opening-up, technological progress, regional coordination, and government control.
topic mining eco-efficiency
Meta-US-SBM
standard deviation ellipse model
GeoDetector
Tobit Model
Guangxi
url https://www.mdpi.com/1660-4601/18/10/5397
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