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

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  • Miura, Taiki
  • Tamaki, Tetsuya
  • Kii, Masanobu
  • Kajitani, Yoshio

Abstract

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.

Suggested Citation

  • Miura, Taiki & Tamaki, Tetsuya & Kii, Masanobu & Kajitani, Yoshio, 2021. "Efficiency by sectors in areas considering CO2 emissions: The case of Japan," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 514-528.
  • Handle: RePEc:eee:ecanpo:v:70:y:2021:i:c:p:514-528
    DOI: 10.1016/j.eap.2021.04.004
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    1. Zhou, P. & Ang, B.W., 2008. "Linear programming models for measuring economy-wide energy efficiency performance," Energy Policy, Elsevier, vol. 36(8), pages 2901-2906, August.
    2. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    3. Tamaki, Tetsuya & Nakamura, Hiroki & Fujii, Hidemichi & Managi, Shunsuke, 2019. "Efficiency and emissions from urban transport: Application to world city-level public transportation," Economic Analysis and Policy, Elsevier, vol. 61(C), pages 55-63.
    4. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. Fukuyama, Hirofumi & Matousek, Roman, 2017. "Modelling bank performance: A network DEA approach," European Journal of Operational Research, Elsevier, vol. 259(2), pages 721-732.
    7. Graham, Daniel J. & Couto, Antonio & Adeney, William E. & Glaister, Stephen, 2003. "Economies of scale and density in urban rail transport: effects on productivity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(6), pages 443-458, November.
    8. Liu, Xiaochen & Sweeney, John, 2012. "Modelling the impact of urban form on household energy demand and related CO2 emissions in the Greater Dublin Region," Energy Policy, Elsevier, vol. 46(C), pages 359-369.
    9. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    10. Graham, Daniel J., 2008. "Productivity and efficiency in urban railways: Parametric and non-parametric estimates," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(1), pages 84-99, January.
    11. Lozano, Sebastián & Gutiérrez, Ester, 2008. "Non-parametric frontier approach to modelling the relationships among population, GDP, energy consumption and CO2 emissions," Ecological Economics, Elsevier, vol. 66(4), pages 687-699, July.
    12. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    13. Wei, Yi-Ming & Liao, Hua & Fan, Ying, 2007. "An empirical analysis of energy efficiency in China's iron and steel sector," Energy, Elsevier, vol. 32(12), pages 2262-2270.
    14. Boame, Attah K., 2004. "The technical efficiency of Canadian urban transit systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 40(5), pages 401-416, September.
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