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Energy conservation in China: Key provincial sectors at two-digit level

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Listed:
  • Hua Liao
  • Jian Du
  • Yi-Ming Wei

    (Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology)

Abstract

In March 2011, China's central government set a new challenging target of reducing its energy intensity by 16% during 2011-2015, after it had achieved a reduction of 19.1% during 2006-2010. And this new target was assigned to provincial authorities in August 2011. However, China's provincial energy-economic developments are unbalanced and different provinces have different key sectors for energy conservation. Most previous studies focused on provincial energy efficiency at the aggregate level, or the three-industry level (or one-digit level). However, whether for policy decision or academic research, it is necessary to further subdivide the sectors. In this paper, we use three indicators (Gini Coefficient, energy consumption share and energy intensity) to compare provincial energy conservation potentials at the two-digit sector level. To our knowledge, this paper is the first one to identify the keys for energy conversation across the 31 provinces ¡Á65 sectors. And the results are shown in visualized maps and matrix tables to help identify the key province¡Ásectors for energy conservation easier. This also helps the central and provincial governments to distinguish key sectors when they monitor the energy conservation progress.

Suggested Citation

  • Hua Liao & Jian Du & Yi-Ming Wei, 2012. "Energy conservation in China: Key provincial sectors at two-digit level," CEEP-BIT Working Papers 53, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    • Handle: RePEc:biw:wpaper:53
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    File URL: http://www.ceep.net.cn/docs/2014-11/20141110161410567766.pdf
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    References listed on IDEAS

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    1. Dorfman, Robert, 1979. "A Formula for the Gini Coefficient," The Review of Economics and Statistics, MIT Press, vol. 61(1), pages 146-149, February.
    2. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    3. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    4. Wang, Qunwei & Zhou, Peng & Zhou, Dequn, 2012. "Efficiency measurement with carbon dioxide emissions: The case of China," Applied Energy, Elsevier, vol. 90(1), pages 161-166.
    5. Liang, Qiao-Mei & Wei, Yi-Ming, 2012. "Distributional impacts of taxing carbon in China: Results from the CEEPA model," Applied Energy, Elsevier, vol. 92(C), pages 545-551.
    6. Donglan, Zha & Dequn, Zhou & Peng, Zhou, 2010. "Driving forces of residential CO2 emissions in urban and rural China: An index decomposition analysis," Energy Policy, Elsevier, vol. 38(7), pages 3377-3383, July.
    7. Tan, Zhongfu & Li, Li & Wang, Jianjun & Wang, Jianhui, 2011. "Examining the driving forces for improving China’s CO2 emission intensity using the decomposing method," Applied Energy, Elsevier, vol. 88(12), pages 4496-4504.
    8. Akkemik, K. Ali & Göksal, Koray & Li, Jia, 2012. "Energy consumption and income in Chinese provinces: Heterogeneous panel causality analysis," Applied Energy, Elsevier, vol. 99(C), pages 445-454.
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    Citations

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    Cited by:

    1. Jingjing Qu & Aijun Li & Morié Guy-Roland N’Drin, 2023. "Measuring technology inequality across African countries using the concept of efficiency Gini coefficient," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(5), pages 4107-4138, May.
    2. Zheng, Bo & Zhang, Qiang & Borken-Kleefeld, Jens & Huo, Hong & Guan, Dabo & Klimont, Zbigniew & Peters, Glen P. & He, Kebin, 2015. "How will greenhouse gas emissions from motor vehicles be constrained in China around 2030?," Applied Energy, Elsevier, vol. 156(C), pages 230-240.
    3. Yang, Yuan & Cai, Wenjia & Wang, Can, 2014. "Industrial CO2 intensity, indigenous innovation and R&D spillovers in China’s provinces," Applied Energy, Elsevier, vol. 131(C), pages 117-127.
    4. Herrerias, M.J. & Joyeux, R. & Girardin, E., 2013. "Short- and long-run causality between energy consumption and economic growth: Evidence across regions in China," Applied Energy, Elsevier, vol. 112(C), pages 1483-1492.
    5. Chen, Yaping & Guo, Zhanwei & Wu, Jiafeng & Zhang, Zhi & Hua, Junye, 2015. "Energy and exergy analysis of integrated system of ammonia–water Kalina–Rankine cycle," Energy, Elsevier, vol. 90(P2), pages 2028-2037.
    6. Li, Zheng & Pan, Lingying & Fu, Feng & Liu, Pei & Ma, Linwei & Amorelli, Angelo, 2014. "China's regional disparities in energy consumption: An input–output analysis," Energy, Elsevier, vol. 78(C), pages 426-438.
    7. Milin Lu & Zhaohua Wang, 2017. "Rebound effects for residential electricity use in urban China: an aggregation analysis based E-I-O and scenario simulation," Annals of Operations Research, Springer, vol. 255(1), pages 525-546, August.

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    More about this item

    Keywords

    Energy Conservation; China; Two-digit level;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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