IDEAS home Printed from https://ideas.repec.org/a/eee/ecanpo/v70y2021icp514-528.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0313592621000539
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eap.2021.04.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Fukuyama, Hirofumi & Matousek, Roman, 2017. "Modelling bank performance: A network DEA approach," European Journal of Operational Research, Elsevier, vol. 259(2), pages 721-732.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yichen Ding & Yaping Huang & Lairong Xie & Shiwei Lu & Leizhou Zhu & Chunguang Hu & Yidan Chen, 2022. "Spatial Patterns Exploration and Impacts Modelling of Carbon Emissions: Evidence from Three Stages of Metropolitan Areas in the YREB, China," Land, MDPI, vol. 11(10), pages 1-18, October.
    2. Panda Su & Yu Wang, 2022. "Does It Help Carbon Reduction in China? A Research Paper about the Mediating Role of Production Automation Based on the Carbon Kuznets Curve," Sustainability, MDPI, vol. 14(23), pages 1-18, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ning Zhang & Jong-Dae Kim, 2014. "Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure," Sustainability, MDPI, vol. 6(3), pages 1-13, March.
    2. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    3. Tianbo Tang & Jianxin You & Hui Sun & Hao Zhang, 2019. "Transportation Efficiency Evaluation Considering the Environmental Impact for China’s Freight Sector: A Parallel Data Envelopment Analysis," Sustainability, MDPI, vol. 11(18), pages 1-24, September.
    4. Ke Wang & Xueying Yu, 2017. "Industrial Energy and Environment Efficiency of Chinese Cities: An Analysis Based on Range-Adjusted Measure," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1023-1042, July.
    5. Song, Malin & Zhang, Jie & Wang, Shuhong, 2015. "Review of the network environmental efficiencies of listed petroleum enterprises in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 65-71.
    6. Wu, F. & Fan, L.W. & Zhou, P. & Zhou, D.Q., 2012. "Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis," Energy Policy, Elsevier, vol. 49(C), pages 164-172.
    7. Jie Wu & Qingyuan Zhu & Pengzhen Yin & Malin Song, 2017. "Measuring energy and environmental performance for regions in China by using DEA-based Malmquist indices," Operational Research, Springer, vol. 17(3), pages 715-735, October.
    8. Zhang, Linyan & Chen, Kun, 2019. "Hierarchical network systems: An application to high-technology industry in China," Omega, Elsevier, vol. 82(C), pages 118-131.
    9. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    10. Long, Xingle & Wu, Chao & Zhang, Jijian & Zhang, Jing, 2018. "Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: A metafrontier directional slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3962-3971.
    11. He, Feng & Zhang, Qingzhi & Lei, Jiasu & Fu, Weihui & Xu, Xiaoning, 2013. "Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs," Energy Policy, Elsevier, vol. 54(C), pages 204-213.
    12. Feng, Chao & Wang, Miao, 2018. "Analysis of energy efficiency in China's transportation sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 565-575.
    13. Bi, Gong-Bing & Song, Wen & Zhou, P. & Liang, Liang, 2014. "Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model," Energy Policy, Elsevier, vol. 66(C), pages 537-546.
    14. Bian, Yiwen & Hu, Miao & Wang, Yousen & Xu, Hao, 2016. "Energy efficiency analysis of the economic system in China during 1986–2012: A parallel slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 990-998.
    15. Surakiat PARICHATNON & Kamonthip MAICHUM & Ke-Chung PENG, 2018. "Measuring technical efficiency of Thai rubber production using the three-stage data envelopment analysis," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(5), pages 227-240.
    16. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    17. Yu, Yu & Wang, Derek D. & Li, Shanling & Shi, Qinfen, 2016. "Assessment of U.S. firm-level climate change performance and strategy," Energy Policy, Elsevier, vol. 92(C), pages 432-443.
    18. Xiaoyang Zhou & Hao Chen & Hao Wang & Benjamin Lev & Lifang Quan, 2019. "Natural and Managerial Disposability Based DEA Model for China’s Regional Environmental Efficiency Assessment," Energies, MDPI, vol. 12(18), pages 1-20, September.
    19. Zhou, Guanghui & Chung, William & Zhang, Xiliang, 2013. "A study of carbon dioxide emissions performance of China's transport sector," Energy, Elsevier, vol. 50(C), pages 302-314.
    20. Bian, Yiwen & Yang, Feng, 2010. "Resource and environment efficiency analysis of provinces in China: A DEA approach based on Shannon's entropy," Energy Policy, Elsevier, vol. 38(4), pages 1909-1917, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecanpo:v:70:y:2021:i:c:p:514-528. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/economic-analysis-and-policy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.