首页> 外文期刊>Journal of Cleaner Production >Regional low-carbon economy efficiency in China: analysis based on the Super-SBM model with CO2 emissions
【24h】

Regional low-carbon economy efficiency in China: analysis based on the Super-SBM model with CO2 emissions

机译:中国区域低碳经济效率:基于Super-SBM模型的CO2排放量分析

获取原文
获取原文并翻译 | 示例
           

摘要

As the largest energy consumer and CO2 emitting country, the Chinese government is committing to a low-carbon economy. It is meaningful and contributes to evaluate and analyze the low-carbon economy efficiency (LCEE) of China. A Super-slack-based measure (Super-SBM) model with undesirable outputs, as combined with the Malmquist productivity index, is proposed to measure the LCEE and the dynamic low-carbon economy efficiency (DLCEE) of 30 provinces in mainland China from 2005 to 2012. The Theil index is also used to measure the rationalization level of industrial structure (RLIS) for discussing the improvements to the LCEE in China. The results indicate that the proposed undesirable outputs SuperSBM model can effectively rank the SBM-efficient provinces. China's regional economic development does not follow a low-carbon pattern, with an average LCEE of 0.517. As a whole, the China's economic development is gradually following a low-carbon development pattern with an annual LCEE improvement of 4.5%. The RLIS of China is also gradually changing better, as well. Through acomparative analysis of the LCEE and RLIS, the 30 provinces are divided into three sub-areas, and relevant suggestions are presented for improving the LCEE of different sub-areas in the future. (C) 2015 Elsevier Ltd. All rights reserved.
机译:作为最大的能源消费国和二氧化碳排放国,中国政府致力于发展低碳经济。这是有意义的,有助于评估和分析中国的低碳经济效率(LCEE)。提出了一种具有超预期产出的基于超松弛的测度(Super-SBM)模型,并结合Malmquist生产率指数,用于测量2005年以来中国大陆30个省的LCEE和动态低碳经济效率(DLCEE)到2012年。Theil指数还用于衡量产业结构的合理化水平(RLIS),以讨论中国LCEE的改进。结果表明,所提出的不良产出SuperSBM模型可以有效地对SBM效率高的省进行排名。中国的区域经济发展没有遵循低碳模式,平均LCEE为0.517。总体而言,中国的经济发展正逐步遵循低碳发展模式,LCEE每年提高4.5%。中国的RLIS也正在逐渐改善。通过对LCEE和RLIS的比较分析,将30个省划分为三个子区域,并提出了相关建议,以改善未来不同子区域的LCEE。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号