Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generation

Due to the imbalance of regional development and the different energy efficiency of different regions in China, it is necessary to measure the total factor energy efficiency of various economic zones and get the actual situation of each region. The paper uses SBM-DEA Model considering undesired gene...

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Main Authors: Yu Shang, Haibin Liu, Yue Lv
Format: Article
Language:English
Published: Elsevier 2020-04-01
Series:Journal of King Saud University: Science
Online Access:http://www.sciencedirect.com/science/article/pii/S1018364720300355
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spelling doaj-65c800e406494e7d9de81ee852efb2572020-11-25T02:26:17ZengElsevierJournal of King Saud University: Science1018-36472020-04-0132319251931Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generationYu Shang0Haibin Liu1Yue Lv2Management School, China University of Mining & Technology (beijing), Beijing 100083, ChinaManagement School, China University of Mining & Technology (beijing), Beijing 100083, ChinaManagement School, China University of Mining & Technology (beijing), Beijing 100083, ChinaDue to the imbalance of regional development and the different energy efficiency of different regions in China, it is necessary to measure the total factor energy efficiency of various economic zones and get the actual situation of each region. The paper uses SBM-DEA Model considering undesired generations to measure the total factor energy efficiency in different regions of China. When analyzing the situation of multiple inputs and multiple outputs, the paper will adopt a decision making-unit that measures multiple inputs and outputs. Thirty provinces and municipalities are divided into eight economic zones by using the State Council’s division method. The average annual total factor energy measurement value in China from 2005 to 2016 is 0.4559 under the consideration of environmental constraints. With the existing technology and the constant investment scale, there is still a 50% increase in this value. This provides a theoretical upside for the further transformation and upgrading of China’s energy production capacity and the reform of the supply side. Then it uses Moran index to get the spatial correlation of TFEE separately. It shows that there is a significant spatial positive correlation of China’s total factor energy efficiency. The conclusion is that China’s total factor energy efficiency has not increased with economic growth, and the regional gap is large, and there is room for improvement of 50%. It also shows that there is a positive spatial correlation among regional TFEE values. That is, high TFEE value in certain area could promote the value of surrounding provinces, indicating that China’s current economic growth is still dominated by energy consumption, and China is also in the middle and late stages of industrialization. Keywords: SBM-DEA Model, Total factor energy efficiency, Moran index, Spatial correlation testhttp://www.sciencedirect.com/science/article/pii/S1018364720300355
collection DOAJ
language English
format Article
sources DOAJ
author Yu Shang
Haibin Liu
Yue Lv
spellingShingle Yu Shang
Haibin Liu
Yue Lv
Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generation
Journal of King Saud University: Science
author_facet Yu Shang
Haibin Liu
Yue Lv
author_sort Yu Shang
title Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generation
title_short Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generation
title_full Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generation
title_fullStr Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generation
title_full_unstemmed Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generation
title_sort total factor energy efficiency in regions of china: an empirical analysis on sbm-dea model with undesired generation
publisher Elsevier
series Journal of King Saud University: Science
issn 1018-3647
publishDate 2020-04-01
description Due to the imbalance of regional development and the different energy efficiency of different regions in China, it is necessary to measure the total factor energy efficiency of various economic zones and get the actual situation of each region. The paper uses SBM-DEA Model considering undesired generations to measure the total factor energy efficiency in different regions of China. When analyzing the situation of multiple inputs and multiple outputs, the paper will adopt a decision making-unit that measures multiple inputs and outputs. Thirty provinces and municipalities are divided into eight economic zones by using the State Council’s division method. The average annual total factor energy measurement value in China from 2005 to 2016 is 0.4559 under the consideration of environmental constraints. With the existing technology and the constant investment scale, there is still a 50% increase in this value. This provides a theoretical upside for the further transformation and upgrading of China’s energy production capacity and the reform of the supply side. Then it uses Moran index to get the spatial correlation of TFEE separately. It shows that there is a significant spatial positive correlation of China’s total factor energy efficiency. The conclusion is that China’s total factor energy efficiency has not increased with economic growth, and the regional gap is large, and there is room for improvement of 50%. It also shows that there is a positive spatial correlation among regional TFEE values. That is, high TFEE value in certain area could promote the value of surrounding provinces, indicating that China’s current economic growth is still dominated by energy consumption, and China is also in the middle and late stages of industrialization. Keywords: SBM-DEA Model, Total factor energy efficiency, Moran index, Spatial correlation test
url http://www.sciencedirect.com/science/article/pii/S1018364720300355
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