Impact of Green Credit Policy on the sustainable growth of pollution-intensive industries: Evidence from China

被引:11
|
作者
Xue, Xinhong [1 ]
Luo, Jun [1 ]
Wang, Zhongcheng [2 ]
Ding, Hua [1 ]
机构
[1] Anhui Univ Finance & Econ, Sch Finance, Bengbu, Peoples R China
[2] Anhui Univ Finance & Econ, Sch Int Trade & Econ, Bengbu, Peoples R China
关键词
Green credit policy; Sustainable development; Innovation; Carbon emissions; Pollution-intensive industries; ECONOMIC-GROWTH; CONSTRAINTS; INVESTMENT;
D O I
10.1016/j.cie.2023.109371
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Based on the dataset of Chinese A-share market firms between 2004 and 2019 and the implementation of the Green Credit Guidelines, this study explores the impact of green credit policy (GCP) on the sustainable development of pollution-intensive enterprises (PIEs) in terms of their financing, growth, green technology progress, and environment protection. Using a Difference-in-Difference model, the empirical analysis reveals that GCP inhibits PIEs' financing and investment, and reduces employment opportunities. It hinders PIEs' green innovation, but does not reduce their investment in green technology projects. Though it does not encourage investment in environment protection, it drives PIEs to discharge fewer types of pollutants. The effect of GCP on PIEs' growth and green technology progress is similar across various enterprises. However, state-owned enterprises, large firms and those located in the eastern region are more likely to discharge fewer types of pollutants with the implementation of GCP. This study suggests that green finance has some limitations when promoting the sustainable development of pollution intensive industries. It is necessary to accelerate the development of transition finance to support the green transformation of PIEs, and prevent potential economic and social risks such as job losses due to the shrinkage of PIEs.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] Pollution haven or porter? The impact of environmental regulation on location choices of pollution-intensive firms in China
    Wang, Xueyuan
    Zhang, Chunting
    Zhang, Zhijian
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2019, 248
  • [42] The impact and transmission mechanism of green credit policy on energy efficiency: new evidence from China
    Liangwen Luo
    Yanqin Ma
    Qian Zhou
    Environmental Science and Pollution Research, 2023, 30 : 56879 - 56892
  • [43] The impact and transmission mechanism of green credit policy on energy efficiency: new evidence from China
    Luo, Liangwen
    Ma, Yanqin
    Zhou, Qian
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (19) : 56879 - 56892
  • [44] The impact of green credit policy on heavily polluting enterprises' financial risk: evidence from China
    Gu, Xuesong
    Wang, Yuanhui
    Xing, Xiaoyun
    Deng, Jing
    CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY, 2024,
  • [45] From brown to green: the role of green credit policy in fostering environmental responsibility in emissions-intensive industries
    Meng, Zhaosu
    Cao, Jingyu
    Li, Junyan
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2025,
  • [46] Exploring the impact of green credit policy on green transformation of heavy polluting industries
    Tian, Chao
    Li, Xiuqing
    Xiao, Liming
    Zhu, Bangzhu
    JOURNAL OF CLEANER PRODUCTION, 2022, 335
  • [47] Green credit policy and labor investment efficiency: evidence from China
    Ying Liu
    Junqiu Wang
    Canyu Xu
    Environmental Science and Pollution Research, 2023, 30 : 110461 - 110480
  • [48] Green credit policy and corporate charitable donations: Evidence from China
    Wang, Qun
    Zhao, Xiangfang
    Liu, Yuming
    JOURNAL OF CLEANER PRODUCTION, 2023, 415
  • [49] Green credit policy and corporate cash holdings: Evidence from China
    Li, Weiping
    Chen, Xiaoqi
    Yuan, Tao
    ACCOUNTING AND FINANCE, 2023, 63 : 2875 - 2903
  • [50] Green credit policy and labor investment efficiency: evidence from China
    Liu, Ying
    Wang, Junqiu
    Xu, Canyu
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (51) : 110461 - 110480