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Total-factor energy productivity growth of regions in Japan

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  • Honma, Satoshi
  • Hu, Jin-Li

Abstract

This article computes the energy productivity changes of regions in Japan using total-factor frameworks based on data envelopment analysis (DEA). Since the traditional DEA-Malmquist index cannot analyze changes in single-factor productivity changes under the total-factor framework, we apply a new index proposed by Hu and Chang [2009. Total-factor energy productivity growth of regions in China. Energy Policy, submitted for publication]: a total-factor energy productivity change index (TFEPI) that integrates the concept of the total-factor energy efficiency index into the Malmquist productivity index (MPI). Moreover, we separate TFEPI into change in relative energy efficiency, or the 'catching up effect,' and shift in the technology of energy use, or the 'innovation effect.' The data from 47 prefectures during the period of 1993-2003 are used to compute the TFEPI and its components for 4 kinds of energy. The TFEPI of electric power for commercial and industrial use changes -0.6% annually, which can be separated into a total-factor energy efficiency change of 0.2% and a technical change of -0.8%. The TFEPI for coal deteriorates by 1.0%/year, which is mostly caused by a decrease in relative energy efficiency change. We define and identify 'innovators' who cause the frontier to shift. Most regions identified as frontier shifters are located outside of Japan's four major industrial areas.

Suggested Citation

  • Honma, Satoshi & Hu, Jin-Li, 2009. "Total-factor energy productivity growth of regions in Japan," Energy Policy, Elsevier, vol. 37(10), pages 3941-3950, October.
  • Handle: RePEc:eee:enepol:v:37:y:2009:i:10:p:3941-3950
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    Cited by:

    1. Chang, Ming-Chung, 2016. "Applying the energy productivity index that considers maximized energy reduction on SADC (Southern Africa Development Community) members," Energy, Elsevier, vol. 95(C), pages 313-323.
    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. Chia-Jung Tu & Ming-Chung Chang & Chiang-Ping Chen, 2016. "Progressive Time-Weighted Dynamic Energy Efficiency, Energy Decoupling Rate, and Decarbonization: An Empirical Study on G7 and BRICS," Sustainability, MDPI, Open Access Journal, vol. 8(9), pages 1-17, September.
    4. repec:eee:energy:v:134:y:2017:i:c:p:991-1000 is not listed on IDEAS
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    6. Wang, Zhaohua & Feng, Chao, 2015. "Sources of production inefficiency and productivity growth in China: A global data envelopment analysis," Energy Economics, Elsevier, vol. 49(C), pages 380-389.
    7. repec:eee:rensus:v:80:y:2017:i:c:p:367-379 is not listed on IDEAS
    8. Lim, Seong-Rin & Schoenung, Julie M., 2011. "Measurement and analysis of product energy efficiency to assist energy star criteria development: An example for desktop computers," Energy Policy, Elsevier, vol. 39(12), pages 8003-8010.
    9. Satoshi Honma & Jin-Li Hu, 2011. "Industry-level Total-factor Energy Efficiency in Developed Countries," Discussion Papers 51, Kyushu Sangyo University, Faculty of Economics.
    10. repec:gam:jsusta:v:9:y:2017:i:9:p:1664-:d:112492 is not listed on IDEAS
    11. Sözen, Adnan & Alp, Ihsan, 2009. "Comparison of Turkey's performance of greenhouse gas emissions and local/regional pollutants with EU countries," Energy Policy, Elsevier, vol. 37(12), pages 5007-5018, December.
    12. Wang, Zhaohua & Feng, Chao, 2015. "A performance evaluation of the energy, environmental, and economic efficiency and productivity in China: An application of global data envelopment analysis," Applied Energy, Elsevier, vol. 147(C), pages 617-626.
    13. Andersson, Fredrik N.G. & Karpestam, Peter, 2013. "CO2 emissions and economic activity: Short- and long-run economic determinants of scale, energy intensity and carbon intensity," Energy Policy, Elsevier, vol. 61(C), pages 1285-1294.
    14. Honma, Satoshi & Hu, Jin-Li, 2014. "Industry-level total-factor energy efficiency in developed countries: A Japan-centered analysis," Applied Energy, Elsevier, vol. 119(C), pages 67-78.
    15. Zhang, Xing-Ping & Cheng, Xiao-Mei & Yuan, Jia-Hai & Gao, Xiao-Jun, 2011. "Total-factor energy efficiency in developing countries," Energy Policy, Elsevier, vol. 39(2), pages 644-650, February.
    16. Du, Huibin & Matisoff, Daniel C. & Wang, Yangyang & Liu, Xi, 2016. "Understanding drivers of energy efficiency changes in China," Applied Energy, Elsevier, vol. 184(C), pages 1196-1206.
    17. Apergis, Nicholas & Aye, Goodness C. & Barros, Carlos Pestana & Gupta, Rangan & Wanke, Peter, 2015. "Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs," Energy Economics, Elsevier, vol. 51(C), pages 45-53.
    18. Nela Vlahinic-Dizdarevic & Alemka Segota, 2012. "Total-factor energy efficiency in the EU countries," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics, vol. 30(2), pages 247-265.
    19. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    20. repec:eee:enepol:v:111:y:2017:i:c:p:179-192 is not listed on IDEAS
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    22. Halkos, George & Tzeremes, Nickolaos, 2011. "Regional environmental efficiency and economic growth: NUTS2 evidence from Germany, France and the UK," MPRA Paper 33698, University Library of Munich, Germany.
    23. Wang, Zhaohua & Feng, Chao & Zhang, Bin, 2014. "An empirical analysis of China's energy efficiency from both static and dynamic perspectives," Energy, Elsevier, vol. 74(C), pages 322-330.

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