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Provincial allocation of coal de-capacity targets in China in terms of cost, efficiency, and fairness

机译:在成本,效率和公平性方面,中国煤炭去产能目标的省级分配

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摘要

Developing a de-capacity scheme that is economical, fair, and efficient, has become a key problem affecting the smooth achievement of coal de-capacity targets. It is also an important policy issue with regard to the overall implementation of China's supply-side structural reforms. In this study, we use the production function method as well as the panel variable coefficient model to calculate the 25 provinces' boundary production functions for the coal industry, which leads to the estimation of the coal capacity and capacity utilization rate of each province. Taking into account the labor resettlement cost and disposal cost of fixed assets, a total cost function of coal de-capacity is established. The growth rate function of total factor productivity (TFP) in the coal industry is constructed by the Solow residual value method. An allocation model of coal de-capacity is then proposed, based on multi-objective nonlinear optimization with constraint conditions on the total reduction amount and minimum output of coal in each region. Finally, using the relevant data of China's 25 coal-producing provinces in 1990-2015, the allocation of coal de-capacity is obtained under the goal of minimizing the total cost and maximizing the TFP growth rate. The results show that the capacity utilization rate of China's coal industry is much lower than the lower limit of the reasonable utilization ratio, while TFP shows negative growth over a long period. The comparative analytical results indicate that in terms of total cost, the optimal allocation scheme is 44.5335 billion yuan lower than the government allocation scheme. The disposal cost of fixed assets and labor resettlement costs decrease by 29.2749 billion yuan and 152586 billion yuan respectively. In terms of TFP growth, the optimal allocation scheme has a 1.54% higher TFP growth rate compared with the government allocation scheme. In terms of fairness, the Gini coefficients of the optimal scheme calculated by various indexes are all smaller than 03, placing the scheme within the category of considerable or absolute fairness. In addition, we calculate the optimal allocation ratio of coal de-capacity in the situation where cost preference and quality preference of central government are considered, to verify the intrinsic consistency of the model. In brief, the optimal allocation scheme proposed in this study effectively realizes the integration of economy, efficiency, and fairness. (C) 2018 Elsevier B.V. All rights reserved.
机译:制定经济,公平,高效的产能削减计划已经成为影响煤炭产能削减目标顺利实现的关键问题。对于全面实施中国供给侧结构性改革,这也是一个重要的政策问题。在这项研究中,我们使用生产函数方法和面板变量系数模型来计算25个省的煤炭工业边界生产函数,从而得出每个省的煤炭产能和产能利用率。考虑到劳动力安置成本和固定资产处置成本,建立了煤炭产能的总成本函数。煤炭行业全要素生产率(TFP)的增长率函数是通过Solow残值法构造的。在多目标非线性优化的基础上,提出了限制各地区煤炭总减量和最低产量的约束条件,建立了煤炭产能不足的分配模型。最后,利用1990-2015年中国25个产煤省的相关数据,以最小化总成本和最大化TFP增长率为目标,获得了煤炭去产能的分配。结果表明,中国煤炭行业的产能利用率远低于合理利用率的下限,而全要素生产率长期呈现负增长。对比分析结果表明,从总成本上看,最优分配方案比政府分配方案少443.335亿元。固定资产处置费用和劳务安置费用分别减少297.749亿元和152586亿元。在全要素生产率增长方面,最优分配方案的全要素生产率增长率比政府分配方案高1.54%。在公平性方面,由各种指标计算出的最优方案的基尼系数均小于03,这使该方案属于相当或绝对的公平性类别。此外,我们在考虑了中央政府的成本偏好和质量偏好的情况下,计算了煤炭产能的最优分配比例,以验证该模型的内在一致性。简而言之,本研究提出的最优分配方案有效地实现了经济,效率和公平的融合。 (C)2018 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Energy economics》 |2019年第2期|109-128|共20页
  • 作者单位

    China Univ Min & Technol, Sch Management, Xuzhou 221116, Jiangsu, Peoples R China;

    China Univ Min & Technol, Sch Management, Xuzhou 221116, Jiangsu, Peoples R China;

    Nanjing Univ Finance & Econ, Sch Management, Nanjing 210003, Jiangsu, Peoples R China;

    Univ Lancaster, Sch Management, Lancaster LA2 0PJ, England;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    De-capacity; Target allocation; Multi-objective nonlinear optimization; Coal industry;

    机译:容量不足;目标分配;多目标非线性优化;煤炭行业;
  • 入库时间 2022-08-18 04:13:38

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