Cargando…

Revisiting China’s provincial energy efficiency and its influencing factors

Improving the energy efficiency is a fundamental way to ensure energy security and sustainable development, and is also the requirement of supply-side structural reform of China’s energy. This paper uses the DEA-BCC model to estimate China’s energy efficiency at the provincial level, analyzes its re...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Haomin, Zhang, Zaixu, Zhang, Tao, Wang, Liyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382643/
https://www.ncbi.nlm.nih.gov/pubmed/32834422
http://dx.doi.org/10.1016/j.energy.2020.118361
_version_ 1783563285677735936
author Liu, Haomin
Zhang, Zaixu
Zhang, Tao
Wang, Liyang
author_facet Liu, Haomin
Zhang, Zaixu
Zhang, Tao
Wang, Liyang
author_sort Liu, Haomin
collection PubMed
description Improving the energy efficiency is a fundamental way to ensure energy security and sustainable development, and is also the requirement of supply-side structural reform of China’s energy. This paper uses the DEA-BCC model to estimate China’s energy efficiency at the provincial level, analyzes its regional differences from 2006 to 2016, and applies a panel data model to analyze the influencing factors of energy efficiency. It selects labor, capital stock and total energy consumption as inputs and takes real GDP and comprehensive index of environmental pollution as desirable and undesirable outputs, respectively. The results show that (1) energy efficiency when undesirable output is included is generally lower than when undesirable output is excluded; (2) There is a considerable difference in energy efficiency among provinces, and China’s energy efficiency, by and large, shows a trend of declining. The energy efficiency of four major regions demonstrates obvious regional differences: coastal region>northeastern region> middle region >western region; (3) The economic development level, technological progress, energy price and urbanization level are positively associated with energy efficiency, while the proportion of secondary industry and the energy consumption structure dominated by coal and oil are negatively correlated with energy efficiency.
format Online
Article
Text
id pubmed-7382643
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-73826432020-07-28 Revisiting China’s provincial energy efficiency and its influencing factors Liu, Haomin Zhang, Zaixu Zhang, Tao Wang, Liyang Energy (Oxf) Article Improving the energy efficiency is a fundamental way to ensure energy security and sustainable development, and is also the requirement of supply-side structural reform of China’s energy. This paper uses the DEA-BCC model to estimate China’s energy efficiency at the provincial level, analyzes its regional differences from 2006 to 2016, and applies a panel data model to analyze the influencing factors of energy efficiency. It selects labor, capital stock and total energy consumption as inputs and takes real GDP and comprehensive index of environmental pollution as desirable and undesirable outputs, respectively. The results show that (1) energy efficiency when undesirable output is included is generally lower than when undesirable output is excluded; (2) There is a considerable difference in energy efficiency among provinces, and China’s energy efficiency, by and large, shows a trend of declining. The energy efficiency of four major regions demonstrates obvious regional differences: coastal region>northeastern region> middle region >western region; (3) The economic development level, technological progress, energy price and urbanization level are positively associated with energy efficiency, while the proportion of secondary industry and the energy consumption structure dominated by coal and oil are negatively correlated with energy efficiency. Elsevier Ltd. 2020-10-01 2020-07-26 /pmc/articles/PMC7382643/ /pubmed/32834422 http://dx.doi.org/10.1016/j.energy.2020.118361 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Liu, Haomin
Zhang, Zaixu
Zhang, Tao
Wang, Liyang
Revisiting China’s provincial energy efficiency and its influencing factors
title Revisiting China’s provincial energy efficiency and its influencing factors
title_full Revisiting China’s provincial energy efficiency and its influencing factors
title_fullStr Revisiting China’s provincial energy efficiency and its influencing factors
title_full_unstemmed Revisiting China’s provincial energy efficiency and its influencing factors
title_short Revisiting China’s provincial energy efficiency and its influencing factors
title_sort revisiting china’s provincial energy efficiency and its influencing factors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382643/
https://www.ncbi.nlm.nih.gov/pubmed/32834422
http://dx.doi.org/10.1016/j.energy.2020.118361
work_keys_str_mv AT liuhaomin revisitingchinasprovincialenergyefficiencyanditsinfluencingfactors
AT zhangzaixu revisitingchinasprovincialenergyefficiencyanditsinfluencingfactors
AT zhangtao revisitingchinasprovincialenergyefficiencyanditsinfluencingfactors
AT wangliyang revisitingchinasprovincialenergyefficiencyanditsinfluencingfactors