The network energy and environment efficiency analysis of 27 OECD countries: A multiplicative network DEA model

Ouyang, Wendi; Yang, Jian-Bo

doi:10.1016/j.energy.2020.117161

Cited by 63 publications

(23 citation statements)

References 39 publications

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“…The findings show that there exist regional disparities in environmental efficiency scores. Ouyang and Yang (2020) use 27 OECD countries to carry out a case study and the findings demonstrate that the multiplicative model is more effective in calculating energy and environmental quality than the conventional DEA model. Also, Xie et al (2014) assessed the environmental efficiency of electric power industries in organization of Economic Cooperation for Development (OECD) and Brazil, Russia, India, and China (BRIC) by using the Malmquist index method based on DEA.…”

Section: Environmental Efficiency Using Dea Methodsmentioning

confidence: 99%

The influence of technological innovation and human capital on environmental efficiency among different regions in Asia-Pacific

Twum

Long

Salman

et al. 2021

Environ Sci Pollut Res

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This study employs super-efficiency DEA model with desirable inputs and an undesirable output in calculating environmental efficiency values in different regions in Asia-Pacific from 1990 to 2018. The study compares environmental efficiency index in South East Asia, South Asia and East Asia. The study also evaluates the determinants of environmental efficiency using truncated regression. The mean environmental efficiency score demonstrates that East Asia region is highly efficient whereas South East Asia is the least efficient. Results from the truncated regression established an inverted U-shape relationship between environmental efficiency and Technological Innovation (TI) in the main panel, and the three regions. Also, economic growth shows an inverted "U" shape link with environmental efficiency in the panels except in South East Asia. Human capital promotes environmental efficiency in the main panel and the rest of the regions. Moreover, while FDI promotes environmental efficiency in the main panel and East Asia, it reduces environmental efficiency in both South East and South Asia regions within the Asia-Pacific. In addition, an interaction effect between technological innovation and renewable energy use, advances environmental efficiency within the entire study countries. Based on the findings the study proposes several policy recommendations.

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Section: Environmental Efficiency Using Dea Methodsmentioning

confidence: 99%

The influence of technological innovation and human capital on environmental efficiency among different regions in Asia-Pacific

Twum

Long

Salman

et al. 2021

Environ Sci Pollut Res

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“…[ 30 ] used traditional CCR-DEA model to analyze the energy efficiency of Turkey. Ouyang and Yang [ 8 ] analyzed the network energy and environment efficiency of 27 OECD countries by a multiplicative network DEA model. As for studies about China’s energy efficiency, many different DEA models were adopted, such as game cross-efficiency DEA [ 17 ], meta-frontier super-SBM [ 31 ], three-stage data envelopment [ 13 ], etc.…”

Section: Literature Reviewmentioning

confidence: 99%

“…As for research on regional difference of energy efficiency, its research object is mainly from three aspects. The first one is Economies, mainly including European regions [ 3 ], Mediterranean countries [ 5 ], OPEC [ 6 ] and OECD countries [ 8 ]. The second is countries, involving the United States [ 4 ], Switzerland [ 4 , 43 ], New Zealand [ 11 ], Spain [ 9 ], Korea [ 7 ] and Finland [ 10 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…The low energy efficiency not only wastes limited energy, but also causes serious environmental pollution. Therefore, the issue of energy efficiency has attracted more and more attention from academia that can put forward modern, reliable and environment-friendly energy policy suggestions for different Economies and countries [ [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] ].…”

Section: Introductionmentioning

confidence: 99%

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Revisiting China’s provincial energy efficiency and its influencing factors

Liu

Zhang

Tao

et al. 2020

Energy

106

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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.

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“…In recent decades, researchers have frequently addressed the environmental efficiency analysis. We highlight the investigations of [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. In these researches, efficiency models are applied to analyze specific industries and territories.…”

Section: Analysis Of Environmental Efficiencymentioning

confidence: 99%

Analysis of the Regional Efficiency of European Funds in Spain from the Perspective of Renewable Energy Production: The Regional Dimension

Mugambi

Blanco

Ogachi

et al. 2021

IJERPH

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During the 2010–2020 period, the European Union (EU) launched a growth strategy based on three fundamental pillars: smart growth, sustainable growth, and inclusive growth. Aiming to finance the projects related to these growth pillars, the EU used mainly the Rural Development Funds, the Structural Funds, those derived from the R&D Framework Program, the Trans-European Networks, and the European Investment Bank. This research aimed to determine whether the Spanish regions maintain homogeneous efficiency levels by using these resources to improve the levels of environmental quality related to renewable energies. A methodology that is frequently used by researchers in efficiency analyses was chosen, the Data Envelopment Analysis (DEA). The main findings revealed that the efficiency in the use of renewable energies is very uneven among the Spanish regions and these differences are maintained throughout the period analyzed. These results highlighted the need of changes regarding the proposed criteria for allocating European resources to finance the projects presented by each Spanish region.

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The network energy and environment efficiency analysis of 27 OECD countries: A multiplicative network DEA model

Cited by 63 publications

References 39 publications

The influence of technological innovation and human capital on environmental efficiency among different regions in Asia-Pacific

The influence of technological innovation and human capital on environmental efficiency among different regions in Asia-Pacific

Revisiting China’s provincial energy efficiency and its influencing factors

Analysis of the Regional Efficiency of European Funds in Spain from the Perspective of Renewable Energy Production: The Regional Dimension

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