Energy efficiency evaluation for regions in China: an application of DEA and Malmquist indices

Wu, Ai Hua; Yanying, Cao; Liu, Bo

doi:10.1007/s12053-013-9232-8

Cited by 81 publications

(34 citation statements)

References 33 publications

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“…As China's society continues to develop, economic development is shifting from pursuing quantity to pursuing quality, with a gradually greater focus on resource utilization efficiency and environmental impacts (Tang [1]). Zhou et al [2], Lv et al [3], Song et al [4], Wang et al [5], Wu et al [6], Wu et al [7], and Guo et al [8] used different methods and indicators to evaluate energy efficiency. The main input indicators were labor, energy use, and capital, and the output variables were mostly GDP.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In terms of research samples in the literature, Apergis [31] selected OECD member countries, Chang [32] employed 27 EU members, Song et al [4] researched energy efficiency and carbon emissions in BRICS, Cui [33] selected nine countries, Zhang et al [22] looked at 23 developing countries, Choi et al [20] utilized panel data from 30 provinces in China, and Honma and Hu [34] used data on 47 regions in Japan. For research on China's resource utilization efficiency and environmental efficiency, most scholars use provincial panel data, such as Wei et al [35], Jia and Liu [15], Wang et al [21], Wu et al [6], Shen et al [36], Li and Lin [37], Zou et al [38], and Guo et al [12]. For research on regions, Tang [1] divided China into eastern, central, and western regions to study the input-output efficiency of resources from 2000 to 2015.…”

Section: Literature Reviewmentioning

confidence: 99%

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Energy, CO2, and AQI Efficiency and Improvement of the Yangtze River Economic Belt

et al. 2019

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With the rapid development of its economy, environmental governance is becoming more important in China. The Yangtze River Economic Belt (YREB), as the world’s largest inland shipping channel, can lead the country’s regional green economy development. As most research on China’s environmental efficiency focuses on provinces or the east and west regions, this paper examines its energy input and output and environmental effects from the aspects of YREB and non-YREB, breaking through the limitations of previous studies that only used cross-section or panel data for environmental assessment. This paper employs the meta-frontier dynamic SBM model, selects fixed assets as carry-over indicators, and considers the interrelationships between the dynamics variables during 2014–2016. The results are as follows: The overall energy efficiency and CO2 emission efficiency of YREB are higher than those of non-YREB. The difference in energy consumption, CO2, and AQI efficiency is large, but the performance of YREB is generally better than that of non-YREB. After setting the meta-frontier, non-YREB is better than YREB, for the main reason that the technology gap values of YREB are smaller than those of non-YREB. Our findings thus suggest that YREB should strengthen technical exchanges and promotion within its region, thereby decreasing regional technology differences, while non-YREB should address environment protection and CO2 emissions and advocate a low-carbon production mode.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Energy, CO2, and AQI Efficiency and Improvement of the Yangtze River Economic Belt

et al. 2019

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“…For example, in countries like Italy [34], Canada [20], Sweden [29], Nigeria [44], United States [2], Germany and Colombia [22], China [47], Japan [42], Thailand [38] and Poland [46]. This reinforces the importance of the subject in the global energy context.…”

Section: Framework and Mathematical Model Formulationmentioning

confidence: 73%

Enterprise-wide optimization in a petrochemical plant: a MILP approach to energy efficiency improvement

2017

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Public policy, dollar rate, market prices, contracts values and equipment efficiency influence the costs of the energy sources at an ethylene plant. The aim of this research is to identify energy efficiency opportunities at the energy management resources in a petrochemical industry. It was proved that using MILP makes it possible to achieve energy efficiency gains. MILP proved to be effective, accurate and robust. It confirmed the importance of modeling and simulation with quick response and its implementation in a higher possible rate, since the potential gains running the model once per day were 81% higher than performing it once a month. The optimal resources choice had an average annual potential saving of US$ 556.000/year.

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“…Shen and Wang (2013 exclude the influence of environmental variables and random errors on energy efficiency and utilize the three-stage DEA model to calculate the energy efficiency in China. Wu et al (2014) use Malmquist indices to investigate energy utilization efficiency of 30 provinces in China. The industrial energy overall technical efficiency, industrial energy pure technical efficiency, industrial energy scale efficiency, etc., in different regions of China are examined, by the comparative analysis of energy efficiency, the results show that the eastern regions are better than the central and western regions according to energy efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

The technology gap of Chinese regions' energy efficiency and spatial convergence—Based on the hybrid meta-frontier data envelopment analysis

Zou

Cai

Shen

et al. 2015

Journal of Renewable and Sustainable Energy

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This paper applies the hybrid meta-frontier data envelopment analysis model to estimate the energy efficiency of the eastern, central, western, and northeastern regions in China as well as all Chinese provinces during 2003-2012. We further compare the energy efficiency under the regional frontier and the meta-frontier for different provinces and then examine the convergence situation among these four regions in China as well as the national energy efficiency. The results show the evidence of big gaps in the energy efficiency between the provinces under both the regional frontier and the national meta-frontier. In general, the highest energy efficiency lies in eastern China, followed by western China and then northeastern China, with the lowest in central China. Using the technology gap ratio, the findings present that eastern China achieves the national potential optimized production technology, whereas the central, western, and northeastern regions are still some distance away from their own national potential optimized production technology with considerable room for improvement. As for the variation trends of energy efficiency, those of the central and northeastern regions have a convergence tendency, whereas the energy efficiencies of eastern and western China show the characteristics of slight divergence. Moreover, the convergence tendency of energy efficiency for the whole country has not yet been formed. Based on the above research conclusions, we propose a number of energy policy recommendations for China's government in order to improve energy efficiency. V C 2015 AIP Publishing LLC.

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Energy efficiency evaluation for regions in China: an application of DEA and Malmquist indices

Cited by 81 publications

References 33 publications

Energy, CO2, and AQI Efficiency and Improvement of the Yangtze River Economic Belt

Energy, CO2, and AQI Efficiency and Improvement of the Yangtze River Economic Belt

Enterprise-wide optimization in a petrochemical plant: a MILP approach to energy efficiency improvement

The technology gap of Chinese regions' energy efficiency and spatial convergence—Based on the hybrid meta-frontier data envelopment analysis

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