The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries

Woo, Chungwon; Chung, Yanghon; Chun, Dong Won; Seo, Hye Sook; Hong, Sung Jun

doi:10.1016/j.rser.2015.03.070

Cited by 176 publications

(72 citation statements)

References 45 publications

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“…The behavior of this trend, in which Spain is included, coincides with that described in Woo et al (2015), who attribute it directly to the world economic crisis. This result is tempered in our work by differentiating between the changes which took place in productivity due to the natural approach and the managerial approach.…”

Section: Malmquist Indexsupporting

confidence: 79%

“…The first input is total employment, which is people who worked at least one hour for pay or profit during the reference week or were temporarily absent from such work (in thousands of people, Eurostat) (this input is used in Menegaki, 2013;Woo et al, 2015;Kounetas, 2015;Makridou et al, 2016). The second input is the energy consumption, which is gross inland consumption (in thousands of Toe, Eurostat) (this input is used in (Menegaki, 2013;Kounetas, 2015;Makridou et al, 2016).…”

Section: Datamentioning

confidence: 99%

“…(this input has also been used by Menegaki, 2013;Woo et al, 2015;Kounetas, 2015;Makridou et al, 2016). The outputs employed have been one desirable, the real GDP (expressed in millions of euros, the same output is used by Woo et al, 2015;Kounetas, 2015) and one undesirable, this is the GHG emissions (these emissions are an aggregate of 6 greenhouse gases: CO2, N2O, CH4, HFC, PFC, SF6, in thousands of equivalent tonnes of CO2), as in Menegaki (2013) and Makridou et al (2016)).…”

Section: Datamentioning

confidence: 99%

“…To the best of the author´s knowledge, DEA and Malmquist has not been used commonly to make a comparative analysis of the environmental efficiency in the EU, differentiating between the countries that belonged to it before 2004 (basically located in western Europe) and those which entered from this date (for the most part from eastern Europe). There are other papers which used countries in their analyses, such as Hoang and Alauddin, 2012;Krautzberger and Wetzel, 2012;Bampatsou et al, 2013;Menegaki, 2013;Chang, 2014;Woo et al, 2015). Finally, Kounetas (2015) has done a similar study but he separates the North-South clusters and he only analyzes two years (2002 and 2008).…”

mentioning

confidence: 99%

“…It must know where it stands in comparison to other countries with similar and different geographical, regulatory or other contextual environments. In our model, and following Woo et al (2015), we use employment, energy consumption and gross fixed capital formation (GFCF) as inputs, and the GDP as a desirable output and GHG emissions as an undesirable output. Via the Malmquist Index natural efficiency and managerial efficiency were calculated from a static and dynamic point of view, considering the possibility of a frontier crossover taking place between one period and another due to technological progress.…”

mentioning

confidence: 99%

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An analysis of Spain's global and environmental efficiency from a European Union perspective

et al. 2017

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Section: Malmquist Indexsupporting

confidence: 79%

Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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An analysis of Spain's global and environmental efficiency from a European Union perspective

et al. 2017

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Efficiency assessment of electricity generation from renewable and non‐renewable energy sources using Data Envelopment Analysis

Rodríguez-Lozano

Cifuentes-Yate

2021

Int J Energy Res

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Summary This study assesses the efficiency of electricity generation from renewable and non‐renewable energy sources, by evaluating 126 countries selected as decision‐making units from different continents in the period between 2000 and 2016, using the Data Envelopment Analysis methodology. The model used is Banker‐Charnes‐Cooper output‐oriented, taking into account the totality of electricity generation. Input variables correspond to capacities of electricity generation, such as coal, oil, natural gas, nuclear, hydroelectric, wind, solar, geothermal, tidal, biomass and waste. Output variables are the amounts of electricity produced by each of these sources and carbon dioxide equivalent avoided by each country due to the use of renewable energies in electricity production. Results show that units' efficiency is often set between 60.0% and 79.9%, and countries such as Saudi Arabia, Bahrain, Canada, China, South Korea, the United States, France, Paraguay, Russia and South Africa are efficient throughout the study period. It is highlighted that Oceanian countries obtained the highest average efficiency among other evaluated countries, discriminated by continents.

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The superefficiency direction distance function and total factor energy efficiency: Evidence from the comprehensive and progressive agreement for trans‐pacific partnership (CPTPP) member countries

Feng

Lee

et al. 2022

Energy Science & Engineering

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This study used the superefficiency direction distance function and total factor energy efficiency to evaluate the changes in energy efficiency and total factor energy efficiency of 11 member countries of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) from 2013 to 2017. Based on the results, we consider the policy implications for CPTPP members, and suggest approaches to improve the direction and range of the difference variable for aalyzing energy efficiency performance. In the selection of variables, input variables include labor force, energy consumption, and capital formation; undesirable output variables include the domestic production gross, life expectancy, and PM 2.5 . The results show that Canada, Japan, and Mexico have the best performance in terms of energy superefficiency and total factor energy efficiency; in contrast, Chile, Malaysia, Peru, and Vietnam would benefit from improved energy efficiency. Energy efficiency can be improved by reducing labor and final energy consumption, increasing gross domestic product, and reducing PM 2.5 . However, simultaneously improving all three factors is challenging. Countries should first focus on appropriately adjusting energy policies, actively developing new energy use, improving production technology, avoiding waste, reducing PM 2.5 , and accelerating urban development to achieve optimal energy efficiency.

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The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries

Cited by 176 publications

References 45 publications

An analysis of Spain's global and environmental efficiency from a European Union perspective

An analysis of Spain's global and environmental efficiency from a European Union perspective

Efficiency assessment of electricity generation from renewable and non‐renewable energy sources using Data Envelopment Analysis

The superefficiency direction distance function and total factor energy efficiency: Evidence from the comprehensive and progressive agreement for trans‐pacific partnership (CPTPP) member countries

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