中文版 | English
Title

A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency

Author
Corresponding AuthorQin,Quande
Publication Years
2023-03-01
DOI
Source Title
ISSN
0140-9883
EISSN
1873-6181
Volume119
Abstract
Traditional three-stage data envelopment analysis (DEA) models do not consider the problem of functional form and multicollinearity. This study develops a new stochastic semi-parametric frontier-based three-stage DEA model. The frontier incorporates the effects of both external environmental factors and statistical noise on efficiency. We adopt the StoNED (stochastic non-smooth envelopment of data) approach and use the quasi-likelihood estimation method to estimate the parameters of inefficiency term and stochastic noise. We conduct Monte Carlo experiments to examine the performance of the new frontier under different circumstances. Our results show that the new frontier provides a more realistic and accuracy estimator for efficiency measures. An empirical analysis is used to evaluate green economic efficiency (GEE) in China. We empirically compare different models and the results show that external environmental factors cause significant differences. We provide each provincial average GEE evaluated by the improved QLE-StoNED model, which are outperforms compared with other recently developed estimators. And a gradient difference emerges in the GEE among the eastern, central and western areas of China. The results also offer practical implications for the harmonious development of industrial production and a green economy in China.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Others
Funding Project
National Natural Science Foundation of China["71871146","72174124"] ; Guangdong Special Support Program for Young Top-notch Talent in Science and Technology Innovation[2019TQ05L989] ; Natural Science Foundation of Guangdong Province[2021A1515011777] ; Research Platforms and Project in Ordinary Universities of Education Department of Guangdong Province[2020WTSCX079]
WOS Research Area
Business & Economics
WOS Subject
Economics
WOS Accession No
WOS:000939859200001
Publisher
ESI Research Field
ECONOMICS BUSINESS
Scopus EID
2-s2.0-85148689995
Data Source
Scopus
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/497244
DepartmentSchool of Environmental Science and Engineering
Affiliation
1.School of Management,Shenzhen Polytechnic,Shenzhen,518055,China
2.College of Management,Shenzhen University,Shenzhen,518060,China
3.School of Environmental Science & Engineering,Southern University of Science and Technology,Shenzhen,518055,China
Recommended Citation
GB/T 7714
Liu,Fangmei,Li,Li,Ye,Bin,et al. A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency[J]. ENERGY ECONOMICS,2023,119.
APA
Liu,Fangmei,Li,Li,Ye,Bin,&Qin,Quande.(2023).A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency.ENERGY ECONOMICS,119.
MLA
Liu,Fangmei,et al."A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency".ENERGY ECONOMICS 119(2023).
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