Consistent multi-level energy efficiency indicators and their policy implications

被引:24
|
作者
Bor, Yunchang Jeffrey [1 ]
机构
[1] Chinese Culture Univ, Dept Econ, Taipei, Taiwan
关键词
energy efficiency indicator; energy conservation policy; multi-level analysis; consistent decomposition methodology;
D O I
10.1016/j.eneco.2007.11.005
中图分类号
F [经济];
学科分类号
02 ;
摘要
In order to cope with the global warming issue, most of the Asia-Pacific Economic Cooperation (APEC) economies have made energy conservation policy a top priority in terms of their energy policies. The energy efficiency indicators included in the present paper focus on the micro-foundation aspects. There are basically two types of energy efficiency indicators, namely, the economic-thermodynamic energy efficiency indicators (that use real GDP as the denominator), and the physical-thermodynamic energy efficiency indicators (that are based on the output volume index). While the common definitions and consistent methodology used in the present paper fulfill the TEA pyramid EEI concept, the new methodology in this paper compares the decomposition effects between upstream and downstream industries when aggregating efficiency, changes. These decomposition effects can thereby provide valuable explanations for the energy conservation policy needed by energy policy and government administrators. (C) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:2401 / 2419
页数:19
相关论文
共 50 条
  • [21] Learning Economic Indicators by Aggregating Multi-Level Geospatial Information
    Park, Sungwon
    Han, Sungwon
    Ahn, Donghyun
    Kim, Jaeyeon
    Yang, Jeasurk
    Lee, Susang
    Hong, Seunghoon
    Kim, Jihee
    Park, Sangyoon
    Yang, Hyunjoo
    Cha, Meeyoung
    [J]. THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2022, : 12053 - 12061
  • [22] Indicators in a research institute: A multi-level classification of scientific journals
    Bassecoulard, E
    Zitt, M
    [J]. SCIENTOMETRICS, 1999, 44 (03) : 323 - 345
  • [23] Policy advice as policy work: a conceptual framework for multi-level analysis
    Vesely, Arnost
    [J]. POLICY SCIENCES, 2017, 50 (01) : 139 - 154
  • [24] Yardstick Competition and Policy Learning in Multi-level Systems
    Benz, Arthur
    [J]. REGIONAL AND FEDERAL STUDIES, 2012, 22 (03): : 251 - 267
  • [25] The multi-level policy learning of environmental policy: insights from Izmir
    Velibeyoglu, Koray
    Mengi, Onur
    [J]. TURKISH STUDIES, 2019, 20 (04) : 619 - 636
  • [26] Energy security in a multi-level governance perspective
    Hermanson, Ann-Sofie
    [J]. MARINE POLICY, 2018, 98 : 301 - 308
  • [27] Multi-level climate adaptation policy and causation narratives
    Patt, Anthony
    [J]. GEOGRAFISK TIDSSKRIFT-DANISH JOURNAL OF GEOGRAPHY, 2012, 112 (02) : 174 - 182
  • [28] Policy advice as policy work: a conceptual framework for multi-level analysis
    Arnošt Veselý
    [J]. Policy Sciences, 2017, 50 : 139 - 154
  • [29] The Efficiency Analysis of the Multi-level Consensus Determination Method
    Kozierkiewicz-Hetmanska, Adrianna
    Sitarczyk, Mateusz
    [J]. COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2017, PT I, 2017, 10448 : 103 - 112
  • [30] Hierarchical Multi-Level Information Fusion for Robust and Consistent Visual SLAM
    Yu, Jingrui
    Xiang, ZhenZhen
    Su, Jianbo
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (01) : 250 - 259