Efficiency and equity in regional coal de-capacity allocation in China: A multiple objective programming model based on Gini coefficient and Data Envelopment Analysis
Both governments and enterprises are giving increasing attention to creating efficient policies for coal de-capacity allocation across Chinese regions. In contrast to existing studies, we consider both efficiency and equity in the allocation of coal capacity reduction for streamlining the implementa...
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| Veröffentlicht in: | Resources policy Jg. 66; S. 101621 |
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01.06.2020
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| Abstract | Both governments and enterprises are giving increasing attention to creating efficient policies for coal de-capacity allocation across Chinese regions. In contrast to existing studies, we consider both efficiency and equity in the allocation of coal capacity reduction for streamlining the implementation of coal de-capacity reform. First, the coal production capacity and overcapacity in the coal production regions was estimated using the boundary production function model. Then, we constructed a multiple objective programming model based on the Gini coefficient and Data Envelopment Analysis (Gi-DEA), and applied it to coal de-capacity allocation. The main results are as follows: (1) The coal production capacity in China exceeded 5.7 billion tons by the end of 2015, and coal overcapacity is prevalent across the country. (2) The optimal allocation plan based on the Gi-DEA model achieve efficiency across the regions, and the Gini coefficient is 0.231, indicating this allocation scheme is efficient and fair. Specifically, the large coal production regions should undertake the majority of coal de-capacity, such as Shanxi, Shandong, and Guizhou, while the small and old coal production regions might undertake a heavier capacity reduction burden, such as Fujian, Guangxi, and Jiangxi. (3) The multiple objective programming model, Gi-DEA, using common weights, achieved overall efficiency of the DMUs, and generated a unique allocation plan.
•We considered both efficiency and equity principles in coal de-capacity allocation.•An index system was used for evaluating the backward coal capacity and zombie enterprises in each region.•A multiple objective programming model based on Gini coefficient and DEA was proposed.•The large coal production regions should undertake the majority of coal de-capacity, while the small and old ones undertake a heavier reduction burden. |
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| AbstractList | Both governments and enterprises are giving increasing attention to creating efficient policies for coal de-capacity allocation across Chinese regions. In contrast to existing studies, we consider both efficiency and equity in the allocation of coal capacity reduction for streamlining the implementation of coal de-capacity reform. First, the coal production capacity and overcapacity in the coal production regions was estimated using the boundary production function model. Then, we constructed a multiple objective programming model based on the Gini coefficient and Data Envelopment Analysis (Gi-DEA), and applied it to coal de-capacity allocation. The main results are as follows: (1) The coal production capacity in China exceeded 5.7 billion tons by the end of 2015, and coal overcapacity is prevalent across the country. (2) The optimal allocation plan based on the Gi-DEA model achieve efficiency across the regions, and the Gini coefficient is 0.231, indicating this allocation scheme is efficient and fair. Specifically, the large coal production regions should undertake the majority of coal de-capacity, such as Shanxi, Shandong, and Guizhou, while the small and old coal production regions might undertake a heavier capacity reduction burden, such as Fujian, Guangxi, and Jiangxi. (3) The multiple objective programming model, Gi-DEA, using common weights, achieved overall efficiency of the DMUs, and generated a unique allocation plan.
•We considered both efficiency and equity principles in coal de-capacity allocation.•An index system was used for evaluating the backward coal capacity and zombie enterprises in each region.•A multiple objective programming model based on Gini coefficient and DEA was proposed.•The large coal production regions should undertake the majority of coal de-capacity, while the small and old ones undertake a heavier reduction burden. Both governments and enterprises are giving increasing attention to creating efficient policies for coal de-capacity allocation across Chinese regions. In contrast to existing studies, we consider both efficiency and equity in the allocation of coal capacity reduction for streamlining the implementation of coal de-capacity reform. First, the coal production capacity and overcapacity in the coal production regions was estimated using the boundary production function model. Then, we constructed a multiple objective programming model based on the Gini coefficient and Data Envelopment Analysis (Gi-DEA), and applied it to coal de-capacity allocation. The main results are as follows: (1) The coal production capacity in China exceeded 5.7 billion tons by the end of 2015, and coal overcapacity is prevalent across the country. (2) The optimal allocation plan based on the Gi-DEA model achieve efficiency across the regions, and the Gini coefficient is 0.231, indicating this allocation scheme is efficient and fair. Specifically, the large coal production regions should undertake the majority of coal de-capacity, such as Shanxi, Shandong, and Guizhou, while the small and old coal production regions might undertake a heavier capacity reduction burden, such as Fujian, Guangxi, and Jiangxi. (3) The multiple objective programming model, Gi-DEA, using common weights, achieved overall efficiency of the DMUs, and generated a unique allocation plan. |
| ArticleNumber | 101621 |
| Author | Zheng, Jianping Li, Xu Ma, Gang |
| Author_xml | – sequence: 1 givenname: Gang surname: Ma fullname: Ma, Gang email: 17110690033@fudan.edu.cn – sequence: 2 givenname: Xu surname: Li fullname: Li, Xu – sequence: 3 givenname: Jianping surname: Zheng fullname: Zheng, Jianping |
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