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

Liangen Zeng, Haiyan Lu, Yenping Liu, Yang Zhou and Haoyu Hu
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Liangen Zeng: College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Haiyan Lu: College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Yenping Liu: College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Yang Zhou: Shenzhen Environmental Science and New Energy Technology Engineering Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518055, China
Haoyu Hu: College of Urban and Environmental Sciences, Peking University, Beijing 100871, China

Energies, 2019, vol. 12, issue 16, 1-21

Abstract: 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.

Keywords: carbon emission efficiency; regional differences; influencing factors; the Modified undesirable EBM DEA model; Tobit model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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