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

Research output: Contribution to journalJournal article

<mark>Journal publication date</mark>02/2019
<mark>Journal</mark>Energy Economics
Number of pages20
Pages (from-to)109-128
Publication statusPublished
Early online date16/11/18
Original languageEnglish


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 15.2586 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 0.3, 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. © 2018 Elsevier B.V.