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Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model

Author

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  • Siqin Xiong

    (School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
    College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China)

  • Yushen Tian

    (School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
    College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China)

  • Junping Ji

    (School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
    College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China)

  • Xiaoming Ma

    (School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
    College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China)

Abstract

To realize the sustainable development of energy, the Chinese government has formulated a series of national goals of total energy control and energy structure optimization. Under the national constraints, how to efficiently allocate the constrained total amount of energy consumption to each province is a fundamental problem to be solved. Based on a data envelopment analysis (DEA) model and a zero-sum game theory (ZSG), this paper constructs a weighted zero-sum game data envelopment analysis (ZSG-DEA) model to allocate the energy consumption quota. Additionally, this paper compares the results with the current administrative targets, to examine the efficiency and feasibility of each allocation mechanism. Finally, this paper employs the proposed model to determine the optimal energy structure for each province in China. The results indicate that by 2020, the national goal of energy structure adjustment will be realized, and energy structure will be diversified in most regions, whereas the coal-dominated status in primary energy consumption will not change. Additionally, the weighted ZSG-DEA model focuses on allocation efficiency while the government considers more regional economic disparity. Therefore, this study suggests a mixture of the two allocation mechanisms in accordance with specific conditions.

Suggested Citation

  • Siqin Xiong & Yushen Tian & Junping Ji & Xiaoming Ma, 2017. "Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model," Sustainability, MDPI, vol. 9(11), pages 1-12, November.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:11:p:2115-:d:119392
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    References listed on IDEAS

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    Cited by:

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    2. Fei Ye & Lixu Li & Zhiqiang Wang & Yina Li, 2018. "An Asymmetric Nash Bargaining Model for Carbon Emission Quota Allocation among Industries: Evidence from Guangdong Province, China," Sustainability, MDPI, vol. 10(11), pages 1-18, November.
    3. Wei Yang & Zudi Lu & Di Wang & Yanmin Shao & Jinfeng Shi, 2020. "Sustainable Evolution of China’s Regional Energy Efficiency Based on a Weighted SBM Model with Energy Substitutability," Sustainability, MDPI, vol. 12(23), pages 1-22, December.
    4. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    5. Feng Dong & Bolin Yu & Jixiong Zhang, 2018. "What Contributes to Regional Disparities of Energy Consumption in China? Evidence from Quantile Regression-Shapley Decomposition Approach," Sustainability, MDPI, vol. 10(6), pages 1-26, May.
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    7. Jianguo Zhou & Yushuo Li & Xuejing Huo & Xiaolei Xu, 2019. "How to Allocate Carbon Emission Permits Among China’s Industrial Sectors Under the Constraint of Carbon Intensity?," Sustainability, MDPI, vol. 11(3), pages 1-21, February.

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