Different types of environmental regulations and carbon intensity: empirical analysis of China's garment industry

被引:1
作者
Zhang, Jianlei [1 ]
He, Lin [1 ]
Shen, Pandeng [2 ]
机构
[1] Jiaxing Univ, Coll Business, Fac Mkt, 899 Guangqiong Rd, Jiaxing 314001, Peoples R China
[2] Jiaxing Vocat & Tech Coll, Coll Fash Design, Fac Fash Design, 547 Tongxiang Ave, Jiaxing 314036, Peoples R China
来源
INDUSTRIA TEXTILA | 2024年 / 75卷 / 02期
关键词
China's garment industry; carbon intensity; environmental regulation; green paradox effect; forced emission reduction effect; POLICY;
D O I
10.35530/IT.075.02.20239
中图分类号
TB3 [工程材料学]; TS1 [纺织工业、染整工业];
学科分类号
0805 ; 080502 ; 0821 ;
摘要
Environmental regulation is an important tool to mitigate carbon emissions. To explore the relationships between different types of environmental regulations and carbon intensity (CI) of China's garment industry, this paper uses multiple econometric models to study the effects of command -and -control environmental regulation (CER), market -incentive environmental regulation (MER) and public -participation environmental regulation (PER) the carbon intensity of China's garment industry and analyses their regional heterogeneity. The results show that at the national level, both CER and MER have a green paradox effect on CI of China's garment industry, while the effect of PER is not significant. At regional level, in the eastern garment industry the influence of CER on CI is dominated by the forced emission reduction effect, while MER pushes up the emission intensity within a certain range. Increasing PER helps to reduce the CI of western and North-eastern garment industry. The potential for implications from the results and policy recommendations are also discussed.
引用
收藏
页码:164 / 170
页数:7
相关论文
共 17 条
[1]   The effect of renewable energy development, market regulation, and environmental innovation on CO2 emissions in BRICS countries [J].
Abbas, Shah ;
Gui, Peng ;
Chen, Ai ;
Ali, Najabat .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (39) :59483-59501
[2]  
ALMEIDA N, 2020, ECON ANAL POLICY, V68, P114
[3]  
Dong Z.Q, 2021, Statistical Research, V38, P48
[4]  
[巩小曼 Gong Xiaoman], 2021, [丝绸, Journal of Silk], V58, P79
[5]   Assessing the efficiency of China's environmental regulation on carbon emissions based on Tapio decoupling models and GMM models [J].
Guo Wenbo ;
Chen Yan .
ENERGY REPORTS, 2018, 4 :713-723
[6]   Threshold effects in non-dynamic panels: Estimation, testing, and inference [J].
Hansen, BE .
JOURNAL OF ECONOMETRICS, 1999, 93 (02) :345-368
[7]  
Lu A., 2016, Wool. Spinn. Technol, V44, P65, DOI [10.19333/j.mfkj.2016.04.016, DOI 10.19333/J.MFKJ.2016.04.016]
[8]  
Min W., 2018, METEOROLOGICAL ENV R, V9, P23
[9]   Informal regulation of industrial pollution in developing countries: Evidence from Indonesia [J].
Pargal, S ;
Wheeler, D .
JOURNAL OF POLITICAL ECONOMY, 1996, 104 (06) :1314-1327
[10]   Unilateral Climate Policy: Harmful or Even Disastrous? [J].
Ritter, Hendrik ;
Schopf, Mark .
ENVIRONMENTAL & RESOURCE ECONOMICS, 2014, 58 (01) :155-178