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Comparing the Influence of Green Credit on Commercial Bank Profitability in China and Abroad: Empirical Test Based on a Dynamic Panel System Using GMM

Author

Listed:
  • Xiaoling Song

    (Business School, Beijing Language and Culture University, Beijing 100083, China)

  • Xin Deng

    (School of Finance, Hunan University of Technology and Business; Post-Doctoral Research Station of Management Science and Engineering, National University of Defense Technology, Changsha 410205, China)

  • Ruixue Wu

    (Beijing Jingdong Shangke Information Technology Co., LTD., Beijing 100086, China)

Abstract

This study establishes a dynamic panel model for 12 Chinese-listed commercial banks and seven international commercial banks. More specifically, it examines the impact of green credit on the profitability of commercial banks and the differences between China and other countries while using the generalized method of moments. The research shows that the Equatorial Principles project-financing ratio of international banks positively affects bank profitability, while the ratio of green credit for Chinese commercial banks is inversely related to their profitability. Further, a comparative study of China and other countries highlights that the green credit business is at significantly different stages in China and the rest of the world. This study also finds that the profitability of China’s banking sector is positively affected by asset size, management expense ratio, cash ratio, and GDP growth rate, in addition to the common influencing factor of non-performing loan ratio, whereas asset size and capital adequacy ratio negatively affects the international banking sector. Drawing on these empirical conclusions, this study offers suggestions for the further development of green credit in Chinese commercial banks.

Suggested Citation

  • Xiaoling Song & Xin Deng & Ruixue Wu, 2019. "Comparing the Influence of Green Credit on Commercial Bank Profitability in China and Abroad: Empirical Test Based on a Dynamic Panel System Using GMM," IJFS, MDPI, vol. 7(4), pages 1-16, November.
    • Handle: RePEc:gam:jijfss:v:7:y:2019:i:4:p:64-:d:282744
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    References listed on IDEAS

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    Cited by:

    1. Teresa C. Herrador-Alcaide & Montserrat Hernández-Solís & Susana Cortés Rodríguez, 2023. "Mapping barriers to green supply chains in empirical research on green banking," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    2. Habib-ur Rahman & Muhammad Waqas Yousaf & Nageena Tabassum, 2020. "Bank-Specific and Macroeconomic Determinants of Profitability: A Revisit of Pakistani Banking Sector under Dynamic Panel Data Approach," IJFS, MDPI, vol. 8(3), pages 1-19, July.
    3. Qilun Li & Zhaoyi Xu & Xiaoqin Shen & Jiacheng Zhong, 2022. "Predicting Business Risks of Commercial Banks Based on BP-GA Optimized Model," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1423-1441, April.
    4. Vera Mirovic & Branimir Kalas & Ines Djokic & Nikola Milicevic & Nenad Djokic & Milos Djakovic, 2023. "Green Loans in Bank Portfolio: Financial and Marketing Implications," Sustainability, MDPI, vol. 15(7), pages 1-14, March.
    5. Viacheslav M. Shavshukov & Natalia A. Zhuravleva, 2020. "Global Economy: New Risks and Leadership Problems," IJFS, MDPI, vol. 8(1), pages 1-17, February.
    6. Myvel Nabil, 2023. "The Impact of Green Bonds on Banking Sector Performance: A Comparative Study on Developed and Emerging Markets," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 13(3), pages 1-4.

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