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Stand by or Follow? Responsibility Diffusion Effects and Green Credit

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  • Ling-Yun He
  • Li Liu

Abstract

Understanding the behavior of private capital holders in green investment is a key to the success of green finance policies such as green credit policies. In current literature, there still remain unsettled controversies on the behaviors of private capital holders. The responsibility diffusion theory indicates that private capital holders do not follow commercial banks that issue green credit. However, the signal transmission theory implies that private capital holders may follow. Stand by or follow? We apply the two-way fixed-effects model to analyze the behavior pattern of private capital holders in green investment, using the panel data of 443 listed companies in China. The results show that the private capital holders’ behavior is affected by responsibility diffusion effect.

Suggested Citation

  • Ling-Yun He & Li Liu, 2018. "Stand by or Follow? Responsibility Diffusion Effects and Green Credit," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(8), pages 1740-1760, June.
    • Handle: RePEc:mes:emfitr:v:54:y:2018:i:8:p:1740-1760
    DOI: 10.1080/1540496X.2018.1430566
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    Cited by:

    1. Chuan Shao & Jia Wei & Chuanzhe Liu, 2021. "Empirical Analysis of the Influence of Green Credit on the Industrial Structure: A Case Study of China," Sustainability, MDPI, vol. 13(11), pages 1-15, May.
    2. Zhang, Dongyang, 2022. "Green financial system regulation shock and greenwashing behaviors: Evidence from Chinese firms," Energy Economics, Elsevier, vol. 111(C).
    3. Yang, Yuxue & Su, Xiang & Yao, Shuangliang, 2021. "Nexus between green finance, fintech, and high-quality economic development: Empirical evidence from China," Resources Policy, Elsevier, vol. 74(C).
    4. Shixian Ling & Guosheng Han & Dong An & William Cannon Hunter & Hui Li, 2020. "The Impact of Green Credit Policy on Technological Innovation of Firms in Pollution-Intensive Industries: Evidence from China," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
    5. Zhang, Dayong & Zhang, Zhiwei & Managi, Shunsuke, 2019. "A bibliometric analysis on green finance: Current status, development, and future directions," Finance Research Letters, Elsevier, vol. 29(C), pages 425-430.
    6. Wanying Song & Jian Min & Jianbo Yang, 2023. "Credit Risk Assessment of Heavy-Polluting Enterprises: A Wide- ℓ p Penalty and Deep Learning Approach," Mathematics, MDPI, vol. 11(16), pages 1-19, August.
    7. Lin, Boqiang & Chen, Yufang, 2019. "Impacts of policies on innovation in wind power technologies in China," Applied Energy, Elsevier, vol. 247(C), pages 682-691.
    8. Hu, Guoqiang & Wang, Xiaoqi & Wang, Yu, 2021. "Can the green credit policy stimulate green innovation in heavily polluting enterprises? Evidence from a quasi-natural experiment in China," Energy Economics, Elsevier, vol. 98(C).
    9. Xiaolei Yang & Lingyun He & Sihua Tian & Yufei Xia & Deqing Wang, 2021. "Construction of China’s Green Institutional Environmental Index: Using Functional Data Analysis method," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(2), pages 559-582, April.
    10. Luo, Sumei & Yu, Shenghui & Zhou, Guangyou, 2021. "Does green credit improve the core competence of commercial banks? Based on quasi-natural experiments in China," Energy Economics, Elsevier, vol. 100(C).
    11. Ming Chen & Lina Song & Xiaobo Zhu & Yanshuo Zhu & Chuanhao Liu, 2023. "Does Green Finance Promote the Green Transformation of China’s Manufacturing Industry?," Sustainability, MDPI, vol. 15(8), pages 1-22, April.

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