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Optimal Path for Controlling Sectoral CO 2 Emissions Among China’s Regions: A Centralized DEA Approach

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  • Zuoren Sun

    () (Business School, Shandong University,Weihai, No. 180 West Culture Road,Weihai 264209, China)

  • Rundong Luo

    () (Business School, Shandong University,Weihai, No. 180 West Culture Road,Weihai 264209, China)

  • Dequn Zhou

    () (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, 29 Jiangjun Avenue, Nanjing 211106, China)

Abstract

This paper proposes a centralized data envelopment analysis (DEA) model for industrial optimization based on several different production technologies among several regions. We developed this model based on improved Kuosmanen environmental DEA technology, which avoids positive shadow price on undesirable outputs. We also designed a dual model for our centralized DEA model, and used it to analyze shadow prices on CO 2 emissions. We further employed the proposed model to determine the optimal path for controlling CO 2 emissions at the sector level for each province in China. At sectoral level, manufacturing showed the highest potential emissions reduction, and transportation was the largest accepter of emission quotas. At regional level, western and northeastern areas faced the largest adjustments in allowable emissions, while central and eastern areas required the least amount of adjustment. Because our model represents increase or decrease in emissions bidirectionally in terms of shadow price analysis, this setting makes the shadow price on CO 2 emissions lower than strong regulation (decreasing CO 2 emissions along with increasing value added) used by directional distance function (DDF).

Suggested Citation

  • Zuoren Sun & Rundong Luo & Dequn Zhou, 2015. "Optimal Path for Controlling Sectoral CO 2 Emissions Among China’s Regions: A Centralized DEA Approach," Sustainability, MDPI, Open Access Journal, vol. 8(1), pages 1-20, December.
  • Handle: RePEc:gam:jsusta:v:8:y:2015:i:1:p:28-:d:61444
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    References listed on IDEAS

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    Cited by:

    1. Gang Tian & Jian Shi & Licheng Sun & Xingle Long & Benhai Guo, 2017. "Dynamic changes in the energy–carbon performance of Chinese transportation sector: a meta-frontier non-radial directional distance function approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(2), pages 585-607, November.
    2. Ke Wang & Linan Che & Chunbo Ma & Yi-Ming Wei, 2017. "The Shadow Price of CO2 Emissions in China's Iron and Steel Industry," CEEP-BIT Working Papers 105, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.

    More about this item

    Keywords

    CO 2 emissions; allocation; data envelopment analysis; undesirable outputs;

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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