Do Factor Market Distortions and Carbon Dioxide Emissions Distort Energy Industry Chain Technical Efficiency? A Heterogeneous Stochastic Frontier Analysis

被引:19
作者
Lu, Hengfan [1 ]
Peng, Jiachao [2 ,3 ]
Lu, Xiangyi [4 ]
机构
[1] China Univ Geosci Wuhan, Sch Publ Adm, Wuhan 430074, Peoples R China
[2] Wuhan Inst Technol Law & Business Sch, Wuhan 430205, Peoples R China
[3] Wuhan Inst Technol, Ctr High Qual Collaborat Dev Resources Environm &, Wuhan 430205, Peoples R China
[4] China Univ Geosci Wuhan, Sch Econ & Management, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
factor market distortion; energy industry chain; technological effect; carbon dioxide emission; stochastic frontier analysis of heterogeneity; counterfactual method; PANEL-DATA;
D O I
10.3390/en15176154
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
China's high-quality economic development is hampered by market distortions, and promises to achieve peak carbon emissions by 2030, meaning that its economic growth faces serious environmental constraints. We use a heterogeneous stochastic frontier model to analyze the impact of factor market distortions and carbon dioxide emissions on economic growth, and to evaluate the Chinese energy industry's chain technical efficiency under the influence of factor distortions and carbon dioxide emissions. Finally, the counterfactual measurement method is used to calculate the factor market distortions and loss of the energy industry chain technology efficiency as a result of carbon dioxide emissions. The main research results show that China's energy technology efficiency is 0.959, and the average energy industry chain technical efficiency for each region from the highest to the lowest is east (0.961), center (0.957), northeast (0.955), and west (0.950). The space for efficiency improvement is 3.6377%, 4.5151%, 4.7669%, and 5.2521%, respectively. Factor market distortion and carbon dioxide emissions are the main sources of losses of energy industry chain technical efficiency. Although the energy industry chain technical efficiency is subject to market factors, the structural factors caused by sustainable efficiency are more obvious. In the case of factor market distortions and carbon dioxide emissions, China's energy industry chain technical efficiency slowly increased from 0.952 in 2000 to 0.964 in 2016. By reducing the degree of factor market distortion, China's average energy industry chain technical efficiency will rise to 0.9651 from 0.9649, representing an improvement of 3.6162%.
引用
收藏
页数:22
相关论文
共 46 条
[1]   The transient and persistent efficiency of Italian and German universities: a stochastic frontier analysis [J].
Agasisti, Tommaso ;
Gralka, Sabine .
APPLIED ECONOMICS, 2019, 51 (46) :5012-5030
[2]  
Aminpour S., 2020, IND MANAG J, V12, P319, DOI [10.22059/IMJ.2020.304115.1007743, DOI 10.22059/IMJ.2020.304115.1007743]
[3]   Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions [J].
Banyai, Tamas .
ENERGIES, 2018, 11 (07)
[4]  
Battese G.E., 1992, J. Prod. Anal., V3, P153, DOI [10.1007/BF00158774, DOI 10.1007/BF00158774]
[5]   SMALL-SCALE ETHANOL-PRODUCTION FROM CORN - TECHNOLOGY, ENERGY EFFICIENCY AND ECONOMICS [J].
BENGTSON, HH .
ENERGY IN AGRICULTURE, 1983, 2 (03) :197-217
[6]   Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model [J].
Bi, Gong-Bing ;
Song, Wen ;
Zhou, P. ;
Liang, Liang .
ENERGY POLICY, 2014, 66 :537-546
[7]  
Chen X, 2018, SE ACAD RES, P151, DOI [10.13658/j.cnki.sar.2018.01.017, DOI 10.13658/J.CNKI.SAR.2018.01.017]
[8]  
[陈星星 Chen Xingxing], 2019, [中国管理科学, Chinese Journal of Management Science], V27, P191
[9]   INFERENCE ON COUNTERFACTUAL DISTRIBUTIONS [J].
Chernozhukov, Victor ;
Fernandez-Val, Ivan ;
Melly, Blaise .
ECONOMETRICA, 2013, 81 (06) :2205-2268
[10]   Analysis of the innovation strategies for green supply chain management in the energy industry using the QFD-based hybrid interval valued intuitionistic fuzzy decision approach [J].
Cui Haiyun ;
Huang Zhixiong ;
Yuksel, Serhat ;
Dincer, Hasan .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2021, 143 (143)