Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015

With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences i...

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Main Authors: Liangen Zeng, Haiyan Lu, Yenping Liu, Yang Zhou, Haoyu Hu
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/12/16/3081
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spelling doaj-b671968ad7c94679ab9239f7bfd40b692020-11-24T21:25:44ZengMDPI AGEnergies1996-10732019-08-011216308110.3390/en12163081en12163081Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015Liangen Zeng0Haiyan Lu1Yenping Liu2Yang Zhou3Haoyu Hu4College of Urban and Environmental Sciences, Peking University, Beijing 100871, ChinaCollege of Urban and Environmental Sciences, Peking University, Beijing 100871, ChinaCollege of Urban and Environmental Sciences, Peking University, Beijing 100871, ChinaShenzhen Environmental Science and New Energy Technology Engineering Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518055, ChinaCollege of Urban and Environmental Sciences, Peking University, Beijing 100871, ChinaWith the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions.https://www.mdpi.com/1996-1073/12/16/3081carbon emission efficiencyregional differencesinfluencing factorsthe Modified undesirable EBM DEA modelTobit model
collection DOAJ
language English
format Article
sources DOAJ
author Liangen Zeng
Haiyan Lu
Yenping Liu
Yang Zhou
Haoyu Hu
spellingShingle Liangen Zeng
Haiyan Lu
Yenping Liu
Yang Zhou
Haoyu Hu
Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015
Energies
carbon emission efficiency
regional differences
influencing factors
the Modified undesirable EBM DEA model
Tobit model
author_facet Liangen Zeng
Haiyan Lu
Yenping Liu
Yang Zhou
Haoyu Hu
author_sort Liangen Zeng
title Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015
title_short Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015
title_full Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015
title_fullStr Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015
title_full_unstemmed Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015
title_sort analysis of regional differences and influencing factors on china’s carbon emission efficiency in 2005–2015
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2019-08-01
description With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions.
topic carbon emission efficiency
regional differences
influencing factors
the Modified undesirable EBM DEA model
Tobit model
url https://www.mdpi.com/1996-1073/12/16/3081
work_keys_str_mv AT liangenzeng analysisofregionaldifferencesandinfluencingfactorsonchinascarbonemissionefficiencyin20052015
AT haiyanlu analysisofregionaldifferencesandinfluencingfactorsonchinascarbonemissionefficiencyin20052015
AT yenpingliu analysisofregionaldifferencesandinfluencingfactorsonchinascarbonemissionefficiencyin20052015
AT yangzhou analysisofregionaldifferencesandinfluencingfactorsonchinascarbonemissionefficiencyin20052015
AT haoyuhu analysisofregionaldifferencesandinfluencingfactorsonchinascarbonemissionefficiencyin20052015
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