Combining the biennial Malmquist-Luenberger index and panel quantile regression to analyze the green total factor productivity of the industrial sector in China

被引:137
|
作者
Wang, Ke-Liang [1 ]
Pang, Su-Qin [1 ]
Ding, Li-Li [1 ]
Miao, Zhuang [2 ]
机构
[1] Ocean Univ China, Sch Econ, Qingdao 266100, Peoples R China
[2] Southwestern Univ Finance & Econ, China Western Econ Res Ctr, Chengdu 611130, Peoples R China
基金
中国国家自然科学基金;
关键词
Green total factor productivity (GTFP); Industrial sector; Biennial Malmquist-Luenberger (BML) productivity index; Fixed-effect panel quantile regression; DATA ENVELOPMENT ANALYSIS; UNIT-ROOT TESTS; ENVIRONMENTAL-REGULATION; ECO-EFFICIENCY; EMPIRICAL-ANALYSIS; ENERGY EFFICIENCY; DEVELOPMENT LEVEL; CO2; EMISSIONS; GROWTH; PERFORMANCE;
D O I
10.1016/j.scitotenv.2020.140280
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Improving the green total-factor productivity (GTFP) is a key measure to coordinate industrial development and environmental protection in China. This study adopts the biennial Malmquist-Luenberger (BML) productivity index to estimate the GTFP change of China's 34 industrial subsectors covering the period 2005-2015. Subsequently, fixed-effect panel quantile regression is applied to analyze the heterogeneous effects of eight selected influencing factors on China's industrialGTFP change. The results showthat China's overall industrialGTFP exhibited an increasing trend during the study period and varied greatly in different sub-sectors. Moreover, technological innovation rather than efficiency promotionwas the main contributor to the improvement of industrial GTFP in China. The impact of the scale structure (SS) was significantly positive across the quantiles and maintained a slightly downward trend. The impact of the property rights structure (PTS) was significantly negative and showed an increasing trend across the quantiles. The impact of the energy intensity (EI) slightly increased and was significantly negative at most quantiles. The energy consumption structure (ECS) exhibited an increasing trend and had a significantly negative effect at the middle quantiles. Technological innovation (TI) exerted a significantly positive effect and displayed a downward trend across the quantiles, and itwas themost important factor to drive industrial GTFP growth. The "pollution halo" hypothesis and the Porter hypothesis were both verified with a certain range from the analysis of foreign direct investment (FDI) and environmental regulation (ER), as well as the interaction between ER and TI. Our results stress the importance of the heterogeneous effects of these influencing factors on different quantile subsectors when formulating the related measures and policies. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] The impacts of land misallocation on urban industrial green total-factor productivity in China
    Deng C.
    Zhao H.
    Xie B.
    Li Z.
    Li K.
    Dili Xuebao/Acta Geographica Sinica, 2021, 76 (08): : 1865 - 1881
  • [32] Green Total Factor Productivity Growth and Its Determinants in China's Industrial Economy
    Chen, Chaofan
    Lan, Qingxin
    Gao, Ming
    Sun, Yawen
    SUSTAINABILITY, 2018, 10 (04)
  • [33] Which factors stimulate industrial green total factor productivity growth rate in China? An industrial aspect
    Cui, Herui
    Wang, Haoran
    Zhao, Qiaozhi
    GREENHOUSE GASES-SCIENCE AND TECHNOLOGY, 2019, 9 (03) : 505 - 518
  • [34] Industrial green total factor productivity based on an MML index in the Yangtze River Economic Belt
    Shen Zhong
    Lang Wang
    Fengge Yao
    Environmental Science and Pollution Research, 2022, 29 : 30673 - 30696
  • [35] Industrial green total factor productivity based on an MML index in the Yangtze River Economic Belt
    Zhong, Shen
    Wang, Lang
    Yao, Fengge
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (20) : 30673 - 30696
  • [36] Green total factor productivity growth and its driving forces in China's fisheries sector
    Shen, Weiteng
    Ge, Haoran
    Bao, Junyao
    FRONTIERS IN SUSTAINABLE FOOD SYSTEMS, 2023, 7
  • [37] Does industrial robot adoption affect green total factor productivity? – Evidence from China
    Chen, Siying
    Mu, Siying
    He, Xingwang
    Han, Jingwei
    Tan, Zhixiong
    Ecological Indicators, 2024, 161
  • [38] Accountability audits of natural resources and industrial green total factor productivity: evidence from China
    Huang, Rongbing
    Zou, Xiaomin
    HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS, 2025, 12 (01):
  • [39] Does industrial robot adoption affect green total factor productivity? - Evidence from China
    Chen, Siying
    Mu, Siying
    He, Xingwang
    Han, Jingwei
    Tan, Zhixiong
    ECOLOGICAL INDICATORS, 2024, 161
  • [40] How does green finance influence industrial green total factor productivity? Empirical research from China
    Yue, Hu
    Zhou, Zizhuo
    Liu, Hanwen
    ENERGY REPORTS, 2024, 11 : 914 - 924