International comparison of total-factor energy productivity growth: A parametric Malmquist index approach

被引:74
|
作者
Du, Kerui [1 ,2 ]
Lin, Boqiang [2 ]
机构
[1] Shandong Univ, Ctr Econ Res, Jinan 250100, Peoples R China
[2] Xiamen Univ, China Inst Studies Energy Policy, Collaborat Innovat Ctr Energy Econ & Energy Polic, Xiamen 361005, Fujian, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Energy efficiency; Energy productivity; Fixed-effects; SFA; PANEL-DATA; RENEWABLE ENERGY; EFFICIENCY; DECOMPOSITION; CHINA; INTENSITY; HETEROGENEITY; EMISSIONS; OECD; CONSUMPTION;
D O I
10.1016/j.energy.2016.10.052
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper constructs a Malmquist energy productivity index based on the Shephard energy distance function to measure total-factor energy productivity change. In order to account for individual heterogeneities as well as statistical noises, we use a newly developed fixed-effects SFA model for estimation. Then it is applied to compare energy productivity growth across the world's 123 economies. The main findings are as follows. First, on average the world witnessed a 34.6% growth of energy productivity between 1990 and 2010 which was mainly driven by technological progress. Second, the developed countries achieved higher growth in energy productivity than the developing countries. Third, the developed countries took lead in technological progress while the developing countries performed better in efficiency improvement. Fourth, there are no evidences supporting sigma-convergence among countries' energy productivity growth.(C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:481 / 488
页数:8
相关论文
共 50 条
  • [31] Total agricultural productivity in the Mediterranean region using the Malmquist index approach
    Jeder, Houcine
    [J]. NEW MEDIT, 2023, 23 (02): : 51 - 61
  • [32] Analyzing total-factor energy efficiency in Croatian counties: evidence from a non-parametric approach
    Djula Borozan
    Luka Borozan
    [J]. Central European Journal of Operations Research, 2018, 26 : 673 - 694
  • [33] Total factor productivity growth in agriculture: Malmquist index analysis of 14 countries, 1979-2008
    Zuniga Gonzalez, Carlos Alberto
    [J]. REICE-REVISTA ELECTRONICA DE INVESTIGACION EN CIENCIAS ECONOMICAS, 2020, 8 (16): : 68 - 97
  • [34] The total-factor energy productivity growth of China’s construction industry: evidence from the regional level
    Tengfei Huo
    Hong Ren
    Weiguang Cai
    Wei Feng
    Miaohan Tang
    Nan Zhou
    [J]. Natural Hazards, 2018, 92 : 1593 - 1616
  • [35] Total-factor productivity analysis with optimal standards
    Rao, MP
    Kennedy, JM
    [J]. DECISION SCIENCES INSTITUTE 1998 PROCEEDINGS, VOLS 1-3, 1998, : 1752 - 1752
  • [36] Total factor productivity growth in agriculture: a Malmquist index analysis of 93 countries, 1980-2000
    Coelli, Tim J.
    Rao, D. S. Prasada
    [J]. AGRICULTURAL ECONOMICS, 2005, 32 : 115 - 134
  • [37] Measuring total factor productivity change of microfinance institutions in India using Malmquist productivity index
    Ambarkhane, Dilip
    Singh, Ardhendu Shekhar
    Venkataramani, Bhama
    [J]. INDIAN GROWTH AND DEVELOPMENT REVIEW, 2019, 12 (01) : 105 - 130
  • [38] MalmSoft: An Online Software for Computing Total Factor Productivity Using Malmquist Index
    Jain, Rajni
    Kumari, Sarita
    Arora, Alka
    Sudeep
    [J]. 2014 INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2014, : 468 - 473
  • [39] Empirical Study on Total Factor Productivity of Urban Agriculture Based on Malmquist Index
    Wang, Ling
    Tian, Yuan
    [J]. INTERNATIONAL CONFERENCE ON COMPLEX SCIENCE MANAGEMENT AND EDUCATION SCIENCE (CSMES 2013), 2013, : 514 - 519
  • [40] Total-factor energy efficiency with congestion
    P. Zhou
    F. Wu
    D. Q. Zhou
    [J]. Annals of Operations Research, 2017, 255 : 241 - 256