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      A DEA Approach for Assessing the Energy, Environmental and Economic Performance of Top 20 Industrial Countries

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      Processes
      MDPI AG

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          Abstract

          Due to growing concerns of global warming, reducing carbon emissions has become one of the major tasks for developing countries to meet the national demand for energy policies. The objective of this study is to measure the energy consumption, carbon emission and economic-environmental efficiency in terms of the environmental performance of the top 20 industrial countries by employing a data envelopment analysis (DEA) model from 2013 to 2017. This study used the trilemma of energy efficiency, CO2 emission efficiency, and environmental efficiency, and also the contribution included the quantitative analysis of 20 industrial countries The results show that the energy efficiency of Australia, China, Japan, Saudi Arabia, and Poland are the best performing countries, whereas Mexico, Indonesia, Russia, and Brazil are identified as least efficient among all 20 countries. Furthermore, Russia’s energy intensity has a maximum score while Poland has a minimum score. Additionally, in the case of CO2 emission efficiency, Brazil, France, and Saudi Arabia are considered as efficient while nine country’s scores were less than 0.5. The results show that most countries exhibit higher performance in economic efficiency than environmental efficiency. The study provides valuable information for energy policy-makers.

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          Measuring the efficiency of decision making units

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            A slacks-based measure of efficiency in data envelopment analysis

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              Multilateral Productivity Comparisons When Some Outputs are Undesirable: A Nonparametric Approach

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                Author and article information

                Contributors
                Journal
                PROCCO
                Processes
                Processes
                MDPI AG
                2227-9717
                December 2019
                December 02 2019
                : 7
                : 12
                : 902
                Article
                10.3390/pr7120902
                3e5add47-a824-45de-bfb7-cd5d3039647f
                © 2019

                https://creativecommons.org/licenses/by/4.0/

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