Next Article in Journal
A Si-FET-Based High Switching Frequency Three-Level LLC Resonant Converter
Next Article in Special Issue
Energy Performance Certificates—The Role of the Energy Price
Previous Article in Journal
Adaptive Frequency-Based Reference Compensation Current Control Strategy of Shunt Active Power Filter for Unbalanced Nonlinear Loads
Previous Article in Special Issue
The Symptoms of Illness: Does Israel Suffer from “Dutch Disease”?
Open AccessArticle

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

1
College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
2
Freie Universität Berlin, Department of History and Cultural Studies, Institute of Sinology, Fabeckstraße 23-25, 14195 Berlin, Germany
3
Shenzhen Environmental Science and New Energy Technology Engineering Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518055, China
*
Author to whom correspondence should be addressed.
Energies 2019, 12(16), 3081; https://doi.org/10.3390/en12163081
Received: 4 June 2019 / Revised: 21 July 2019 / Accepted: 23 July 2019 / Published: 9 August 2019
(This article belongs to the Special Issue Energy Economics and Policy in Developed Countries)
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. View Full-Text
Keywords: carbon emission efficiency; regional differences; influencing factors; the Modified undesirable EBM DEA model; Tobit model carbon emission efficiency; regional differences; influencing factors; the Modified undesirable EBM DEA model; Tobit model
Show Figures

Figure 1

MDPI and ACS Style

Zeng, L.; Lu, H.; Liu, Y.; Zhou, Y.; Hu, H. Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015. Energies 2019, 12, 3081.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

1
Back to TopTop