Technology gap and China's regional energy efficiency: A parametric metafrontier approach

2013 ◽  
Vol 40 ◽  
pp. 529-536 ◽  
Author(s):  
Boqiang Lin ◽  
Kerui Du
2013 ◽  
Vol 291-294 ◽  
pp. 1241-1244 ◽  
Author(s):  
Rui Xiang Liu ◽  
Jing Luo

It is crucial to improve China’s energy efficiency in the context of energy conversation and environmental regulation. This paper approaches the measurement of Chinese regional energy efficiency based on slack-based directional distance function from a production theoretic perspective. The results show that there exists inequality among different regions in China and the east area have the best average energy efficiency for the period 2000-2009, followed by the central area. Based on these findings, this paper correspondingly proposes some policies to improve energy efficiency in China.


2020 ◽  
Vol 12 (4) ◽  
pp. 1402 ◽  
Author(s):  
Ya Chen ◽  
Wei Xu ◽  
Qian Zhou ◽  
Zhixiang Zhou

The phenomena of “large energy consumption, high carbon emission, and serious environmental pollution” are against the goals of “low energy consumption, low emissions” in China’s industrial sector. The key to solving the problem lies in improving total factor energy efficiency (TFEE) and carbon emission efficiency (TFCE). Considering the heterogeneity of different sub-industries, this paper proposes a three-stage global meta-frontier slacks-based measure (GMSBM) method for measuring TFEE and TFCE, as well as the technology gap by combining meta-frontier technology with slacks-based measure (SBM) using data envelopment analysis (DEA). DEA can effectively avoid the situation where the technology gap ratio (TGR) is larger than unity. This paper uses the three-stage method to empirically analyze TFEE and TFCE of Anhui’s 38 industrial sub-industries in China from 2012 to 2016. The main findings are as follows: (1) Anhui’s industrial sector has low TFEE and TFCE, which has great potential for improvement. (2) TFEE and TFCE of light industry are lower than those of heavy industry under group-frontier, while they are higher than those of heavy industry under meta-frontier. There is a big gap in TFEE and TFCE among sub-industries of light industry. Narrowing the gap among different sub-industries of light industry is conducive to the overall improvement in TFEE and TFCE. (3) The TGR of light industry is significantly higher than that of heavy industry, indicating that there are sub-industries with the most advanced energy use and carbon emission technologies in light industry. And there is a bigger carbon-emitting technology gap in heavy industry, so it needs to encourage technology spillover from light industry to heavy industry. (4) The total performance loss of industrial sub-industries in Anhui mainly comes from management inefficiency, so it is necessary to improve management and operational ability. Based on the findings, some policy implications are proposed.


2019 ◽  
Vol 77 ◽  
pp. 02005
Author(s):  
Roman Muzychuk

A study of the energy efficiency of the fuel and energy complex of the regions has a great attention. For an integrated introduction of trends and patterns in the energy sector, approaches we use based on the analysis of the fuel and energy balance (FEB). The function of FEB is to show the availability and use of energy resources in a certain territory and determination of indices of energy efficiency. The article presents an approach to the formation of fuel and energy balances based on the available statistical information.


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