An integrative approach for evaluating the environmental economic efficiency

This literature presents an integrative approach using an extended Kaya identity-based LMDI decomposition analysis (Logarithmic Mean Divisia Index) with a two-stage data envelope analysis (DEA) to identify causes for changes in energy consumption and CO2 emissions and to evaluate environmental and economic efficiency. An LMDI can express the corresponding contributions between inputs and outputs by converting all variables into rates of change. These ratios can help avoid the zero and negative values in DEA. The energy consumption, CO2 emissions and economic components of the countries covered by the Belt and Road Initiative from 1992 to 2017 are used for the two-stage efficiency assessment. The outcomes lead to some policy suggestions for the BRI countries. We find that the labor market, labor productivity and energy intensity are the main drivers of energy consumption. Demographic change and carbon intensity are the main influencers of CO2 emissions. The economic situation and the field of activity have an impact on energy consumption and CO2 emissions. Higher-income countries do better in both energy and economic efficiencies, but should be given more consideration in manufacturing. Finally, this integrative approach has a better goodness of fit than the isolated DEA. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This study used an integrative approach to analyze the causes of changes in energy consumption and CO2 emissions in countries involved in the Belt and Road Initiative, identifying labor market, demographic change, and economic situation as main drivers. Higher-income countries perform better in energy and economic efficiencies, but should focus on manufacturing.