Analysis of green total factor productivity in OECD and BRICS countries: based on the Super-SBM model

被引:11
作者
Sun, Xiangxiang [1 ]
机构
[1] Minjiang Univ, Sch Econ & Management, Fuzhou 350108, Peoples R China
关键词
BRICS; green total factor productivity; OECD; PM2; 5; Super-SBM model; ENVIRONMENTAL EFFICIENCY EVALUATION; STOCHASTIC FRONTIER ANALYSIS; DATA ENVELOPMENT ANALYSIS; MALMQUIST INDEX ANALYSIS; UNDESIRABLE OUTPUTS; ENERGY EFFICIENCY; CO2; EMISSION; CHINA; GROWTH; IMPACT;
D O I
10.2166/wcc.2022.149
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
To address the conflict between environmental constraints and fast economic growth, as well as to coordinate green growth strategies between developing and developed countries, improving green total factor productivity (GTFP) is an important way to accelerate the green and low-carbon transformation and get rid of the problems of environment and resources. Therefore, it is significant to analyze and compare the GTFP of Organization for Economic Cooperation and Development (OECD) and BRICS (i.e. Brazil, Russia, India, China and South Africa) countries. By applying the Super-SBM model, our study analyzes the distribution characteristics and the evolving trend of GTFP. The empirical results indicate that: (1) The GTFP of BRICS countries has significantly improved, but there is still a significant gap compared with OECD countries. (2) Brazil, Luxembourg and Norway's GTFP values are higher than others. (3) Among the BRICS countries, Brazil exhibits the highest value and China has the minimum value, which was far ahead in energy consumption and PM2.5. (4) In the analysis of OECD countries, Hungary displays the lowest average value and Luxembourg has the highest average value. As such, some policy implications improve green and low-carbon development.
引用
收藏
页码:3400 / 3415
页数:16
相关论文
共 63 条
[1]   Green TFP Intensity Impact on Sustainable East Asian Productivity Growth [J].
Ahmed, Elsadig M. .
ECONOMIC ANALYSIS AND POLICY, 2012, 42 (01) :67-78
[2]   Green growth and OECD countries: measurement of country performances through distance-based analysis (DBA) [J].
Ates, Seyithan Ahmet ;
Derinkuyu, Kursad .
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2021, 23 (10) :15062-15073
[3]   Analysis of Environmental Total Factor Productivity Evolution in European Agricultural Sector [J].
Balezentis, Tomas ;
Blancard, Stephane ;
Shen, Zhiyang ;
Streimikiene, Dalia .
DECISION SCIENCES, 2021, 52 (02) :483-511
[4]   Energy efficiency analysis of G7 and BRICS considering total-factor structure [J].
Camioto, Flavia de Castro ;
Moralles, Herick Fernando ;
Mariano, Enzo Barberio ;
do Nascimento Rebelatto, Daisy Aparecida .
JOURNAL OF CLEANER PRODUCTION, 2016, 122 :67-77
[6]   Stochastic frontier analysis of productive efficiency in China's Forestry Industry [J].
Chen, Jiandong ;
Wu, Yinyin ;
Song, Malin ;
Zhu, Zunhong .
JOURNAL OF FOREST ECONOMICS, 2017, 28 :87-95
[7]   Regional green development level and its spatial relationship under the constraints of haze in China [J].
Chen, Lili ;
Zhang, Xiaodan ;
He, Feng ;
Yuan, Runsong .
JOURNAL OF CLEANER PRODUCTION, 2019, 210 :376-387
[8]   Total factor productivity growth in China's agricultural sector [J].
Chen, Po-Chi ;
Yu, Ming-Miin ;
Chang, Ching-Cheng ;
Hsu, Shih-Hsun .
CHINA ECONOMIC REVIEW, 2008, 19 (04) :580-593
[9]   'Green' productivity growth in China's industrial economy [J].
Chen, Shiyi ;
Golley, Jane .
ENERGY ECONOMICS, 2014, 44 :89-98
[10]   Measuring green total factor productivity of China's agricultural sector: A three-stage SBM-DEA model with non-point source pollution and CO2 emissions [J].
Chen, Yufeng ;
Miao, Jiafeng ;
Zhu, Zhitao .
JOURNAL OF CLEANER PRODUCTION, 2021, 318