Efficiency by sectors in areas considering CO2 emissions: The case of Japan

Economic growth is an emerging issue in Japan because of the declining birthrate, aging population, and declining population of many local Japanese cities. Furthermore, the challenge of lowering the emission of greenhouse gases has become more prominent in the world, and the 2015 Paris Agreement sets reduction targets for each country. Based on these circumstances, city planning that aims for both efficient production activities and low carbon emissions must be conducted to work toward a sustainable society in Japan. In this study, we applied network data envelope analysis (NDEA) to clarify the production efficiency in 47 prefectures of Japan. The sectors are organized into primary, secondary, and tertiary industries, and the transportation industry, which are calculated in decision-making unit (DMU). Considering this classification, each sector is independently evaluated to determine which contributes the most to CO2 emissions, resulting in a detailed production efficiency analysis by transportation capital. The analysis results demonstrate the differences in the measures that should be taken by the prefectures that are deemed less efficient. In addition, comparing the estimation results of the conventional data envelopment analysis (DEA) and NDEA, we reveal the effect of each sector on the fluctuation of DMU's efficiency value and clarify the reference set for each sector that could not be judged through conventional DEA analysis. (C) 2021 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.

Automated summary

The article discusses the emerging issues facing Japan's economy and how efficient production activities with low carbon emissions can be achieved through city planning to move towards a sustainable society. Network Data Envelope Analysis (NDEA) is used to evaluate the production efficiency in 47 prefectures of Japan, providing detailed analysis on the contribution of each sector to CO2 emissions and suggesting measures for improving efficiency. Comparing the results of conventional Data Envelopment Analysis (DEA) with NDEA, the study reveals the impact of each sector on the fluctuation of efficiency values and clarifies reference sets for sectors that could not be determined through conventional DEA analysis.