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Industrial carbon abatement allocations and regional collaboration: Re-evaluating China through a modified data envelopment analysis

机译:工业碳减排的分配和区域合作:通过修改后的数据包络分析对中国进行重新评估

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摘要

China’s commitment to significantly reducing carbon emissions faces the twin challenges of focusing costly reduction efforts, whilst preserving the rapid growth that has defined the country’s recent past. However, little work has been able to meaningfully reflect the collaborative way in which provinces are assigned targets on a sub-national regional basis. Suggesting a modified data envelopment analysis (DEA) approach which recognises the two objectives of income maximization and pollution abatement cost minimisation, this paper introduces the potential collaboration between industrial units to the modelling framework. Our theoretical work exposits the roles collectives of industrial decision making units may play in optimising against multiple target functions. Considering the period 2012–2014, we illustrate clearly how China’s three regional collaborations interact with the stated aims of national policy. Developed eastern China may take on greater abatement tasks in the short-term, thus freeing central and western China to pursue the economic growth which will then support later abatement. Policy-makers are thus given a tool through which an extra layer of implementation can be evaluated between the national allocation and setting targets for regional individual decision making units. China’s case perfectly exemplifies the conflicts which must be accounted for if the most economical and efficient outcomes are to be achieved.
机译:中国致力于大幅减少碳排放的承诺面临着双重挑战,即着力进行昂贵的减排工作,同时又要保持已定义了中国近代发展的快速增长。但是,很少有工作能够有意义地反映出在省以下区域范围内为省分配目标的协作方式。提出了一种改进的数据包络分析(DEA)方法,该方法可以识别收入最大化和污染消除成本最小化的两个目标,本文将工业部门之间的潜在协作引入了建模框架。我们的理论工作阐明了工业决策部门的集体在针对多个目标功能进行优化时可能发挥的作用。考虑到2012-2014年,我们清楚地说明了中国的三个区域合作如何与既定的国家政策目标互动。发达的华东地区可能会在短期内承担更大的减排任务,从而使中部和西部地区有能力追求经济增长,从而为以后的减排提供支持。因此,为决策者提供了一种工具,通过该工具,可以在国家分配和设定区域性个人决策单位的目标之间评估实施的额外层面。中国的案例完美地说明了要实现最经济,最有效的结果所必须解决的冲突。

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