Dynamic evolution and influencing factors of industrial green total factor energy efficiency in China
This paper sets up an evaluation index system (EIS) for industrial green total factor energy efficiency (IGTFEE), which contains undesired outputs. Next, the directional distance function (DDF) model was adopted to evaluate the IGTFEEs in 2003–2017 of 30 provincial administrative regions (provinces)...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2021-02-01
|
Series: | Alexandria Engineering Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016820306220 |
id |
doaj-6d075f60fa004b1dad31bf7e2a450cfb |
---|---|
record_format |
Article |
spelling |
doaj-6d075f60fa004b1dad31bf7e2a450cfb2021-06-02T14:25:45ZengElsevierAlexandria Engineering Journal1110-01682021-02-0160119291937Dynamic evolution and influencing factors of industrial green total factor energy efficiency in ChinaQuanyi Wang0Chenyuan Zhao1Corresponding author.; School of Economics and Finance, Chongqing University of Technology, Chongqing 400054, ChinaSchool of Economics and Finance, Chongqing University of Technology, Chongqing 400054, ChinaThis paper sets up an evaluation index system (EIS) for industrial green total factor energy efficiency (IGTFEE), which contains undesired outputs. Next, the directional distance function (DDF) model was adopted to evaluate the IGTFEEs in 2003–2017 of 30 provincial administrative regions (provinces) in China. The results show that: The 30 provinces differed greatly in mean IGTFEE through the sample period. Most eastern coastal provinces had relatively high IGTFEE, while most inland provinces had undesirable IGTFEE. Eastern region had far better IGTFEE than central and western regions, while central and western regions had similar IGTFEEs. Through kernel density estimation (KDE), it is learned that the kernel density curves of IGTFEE in most years have only one peak, and moved to the left with the elapse of time, revealing the declining trend of China’s IGTFEE. The results of the Tobit model indicate that IGTFEE is greatly promoted by technological progress, opening-up, and environmental regulation, obviously suppressed by energy structure, and insignificantly promoted by human capital.http://www.sciencedirect.com/science/article/pii/S1110016820306220Industrial green total factor energy efficiency (IGTFEE)Dynamic evolutionInfluencing factorsDirectional distance function (DDF) model |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Quanyi Wang Chenyuan Zhao |
spellingShingle |
Quanyi Wang Chenyuan Zhao Dynamic evolution and influencing factors of industrial green total factor energy efficiency in China Alexandria Engineering Journal Industrial green total factor energy efficiency (IGTFEE) Dynamic evolution Influencing factors Directional distance function (DDF) model |
author_facet |
Quanyi Wang Chenyuan Zhao |
author_sort |
Quanyi Wang |
title |
Dynamic evolution and influencing factors of industrial green total factor energy efficiency in China |
title_short |
Dynamic evolution and influencing factors of industrial green total factor energy efficiency in China |
title_full |
Dynamic evolution and influencing factors of industrial green total factor energy efficiency in China |
title_fullStr |
Dynamic evolution and influencing factors of industrial green total factor energy efficiency in China |
title_full_unstemmed |
Dynamic evolution and influencing factors of industrial green total factor energy efficiency in China |
title_sort |
dynamic evolution and influencing factors of industrial green total factor energy efficiency in china |
publisher |
Elsevier |
series |
Alexandria Engineering Journal |
issn |
1110-0168 |
publishDate |
2021-02-01 |
description |
This paper sets up an evaluation index system (EIS) for industrial green total factor energy efficiency (IGTFEE), which contains undesired outputs. Next, the directional distance function (DDF) model was adopted to evaluate the IGTFEEs in 2003–2017 of 30 provincial administrative regions (provinces) in China. The results show that: The 30 provinces differed greatly in mean IGTFEE through the sample period. Most eastern coastal provinces had relatively high IGTFEE, while most inland provinces had undesirable IGTFEE. Eastern region had far better IGTFEE than central and western regions, while central and western regions had similar IGTFEEs. Through kernel density estimation (KDE), it is learned that the kernel density curves of IGTFEE in most years have only one peak, and moved to the left with the elapse of time, revealing the declining trend of China’s IGTFEE. The results of the Tobit model indicate that IGTFEE is greatly promoted by technological progress, opening-up, and environmental regulation, obviously suppressed by energy structure, and insignificantly promoted by human capital. |
topic |
Industrial green total factor energy efficiency (IGTFEE) Dynamic evolution Influencing factors Directional distance function (DDF) model |
url |
http://www.sciencedirect.com/science/article/pii/S1110016820306220 |
work_keys_str_mv |
AT quanyiwang dynamicevolutionandinfluencingfactorsofindustrialgreentotalfactorenergyefficiencyinchina AT chenyuanzhao dynamicevolutionandinfluencingfactorsofindustrialgreentotalfactorenergyefficiencyinchina |
_version_ |
1721403618151628800 |