Abstract
This study utilizes the dynamic data envelopment analysis (DEA) model by considering time to measure the energy environmental efficiency of 28 countries in the European Union (EU) during the period 2006–2013. There are three kinds of variables: input, output, and carry-over. The inputs are labor, capital, and energy consumption (EC). The undesirable outputs are greenhouse gas emissions (GHE) and sulfur oxide (SOx) emissions, and the desirable output variable is gross domestic product (GDP). The carry-over variable is gross capital formation (GCF). The empirical results show that first the dynamic DEA model can measure environment efficiency and provide optimum improvement for inefficient countries, as more than half of the EU countries should improve their environmental efficiency. Second, the average overall scores of the EU countries point out that the better period of performance is from 2009 to 2012. Third, the output variables of GHE, SOx, and GDP exhibit a significant impact on environmental efficiency. Finally, the average value of others is significantly better than high renewable energy utilization (HRE) with the Wilcoxon test. Thus, the EU’s strategy for environmental energy improvement should be to pay attention to the benefits of renewable energy (RE) utilization, reducing greenhouse gas emissions (GHE), and enhancing the development of RE utilization to help achieve the goal of lower GHE.
Highlights
The International Energy Agency (IEA) [1] reported that the amount of global energy consumption continues to grow
IEA forecasted that global gross domestic product (GDP) will more than double, global economic growth will rise by 88%, and carbon dioxide emissions will increase by 8% from 2013 to 2030 within the business policy as usual
The results revealed that China and Russia appeared at the top of energy efficiency rankings, France and the European Union (EU) are inefficient in four of the five periods, and the United States (US) appeared inefficient for recent electricity production
Summary
The International Energy Agency (IEA) [1] reported that the amount of global energy consumption continues to grow. The proportion of petrochemical energy usage has increased by over. When petrochemical energy reserves drop, the technology to find new reserves and mining locations becomes harder and production costs rise. IEA estimated, that under the current population and capital income growth, energy demand will continue to rise over the 20–25 years. IEA forecasted that global gross domestic product (GDP) will more than double, global economic growth will rise by 88%, and carbon dioxide emissions will increase by 8% from 2013 to 2030 (reaching 34.8 billion tons) within the business policy as usual. In a low oil price scenario analysis by IEA, the energy consumption of the global transportation industry will push
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Topics from this Paper
Dynamic Data Envelopment Analysis Model
Environmental Efficiency
Gross Capital Formation
Dynamic Data Envelopment Analysis
Greenhouse Gas Emissions
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