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Sources of energy productivity change in China during 1997-2012: A decomposition analysis based on the Luenberger productivity indicator

机译:1997-2012年中国能源生产率变化的来源:基于Luenberger生产率指标的分解分析

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摘要

Given that different energy inputs play different roles in production and that energy policy decision making requires an evaluation of productivity change in individual energy input to provide insight into the scope for improvement of the utilization of specific energy input, this study develops, based on the Luenberger productivity indicator and data envelopment analysis models, an aggregated specific energy productivity indicator combining the individual energy input productivity indicators that account for the contributions of each specific energy input toward energy productivity change. In addition, these indicators can be further decomposed into four factors: pure efficiency change, scale efficiency change, pure technology change, and scale of technology change. These decompositions enable a determination of which specific energy input is the driving force of energy productivity change and which of the four factors is the primary contributor of energy productivity change. An empirical analysis of China's energy productivity change over the period 1997-2012 indicates that (i) China's energy productivity growth may be overestimated if energy consumption structure is omitted; (ii) in regard to the contribution of specific energy input toward energy productivity growth, oil and electricity show positive contributions, but coal and natural gas show negative contributions; (iii) energy-specific productivity changes are mainly caused by technical changes rather than efficiency changes; and (iv) the Porter Hypothesis is partially supported in China that carbon emissions control regulations may lead to energy productivity growth. (C) 2015 Elsevier B.V. All rights reserved.
机译:鉴于不同的能源输入在生产中扮演着不同的角色,并且能源政策决策需要评估单个能源输入的生产率变化以提供对特定能源输入利用的改善范围的见解,因此,基于Luenberger,本研究得以发展。生产率指标和数据包络分析模型,一个汇总的特定能量生产率指标,结合了各个能量输入生产率指标,这些指标说明了每个特定能量输入对能量生产率变化的贡献。此外,这些指标可以进一步分解为四个因素:纯效率变化,规模效率变化,纯技术变化和技术变化规模。这些分解使得能够确定哪个比能量输入是能量生产率变化的驱动力,以及四个因素中的哪个是能量生产率变化的主要贡献者。对中国1997年至2012年期间能源生产率变化的实证分析表明:(i)如果省略能源消费结构,中国的能源生产率增长可能会被高估; (ii)在特定能源输入对能源生产率增长的贡献方面,石油和电力显示出正贡献,而煤炭和天然气显示出负贡献; (iii)特定于能源的生产率变化主要是由技术变化​​而不是效率变化引起的; (iv)波特假说在中国得到部分支持,即碳排放控制法规可能导致能源生产率的增长。 (C)2015 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Energy economics》 |2016年第2期|50-59|共10页
  • 作者

    Wang Ke; Wei Yi-Ming;

  • 作者单位

    Beijing Inst Technol, Ctr Energy & Environm Policy Res, Beijing 100081, Peoples R China|Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China|Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing, Peoples R China;

    Beijing Inst Technol, Ctr Energy & Environm Policy Res, Beijing 100081, Peoples R China|Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China|Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing, Peoples R China;

  • 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

    Carbon emissions; Data envelopment analysis; Driving force; Input specific productivity indicator;

    机译:碳排放量;数据包络分析;驱动力;输入比生产率指标;

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