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The impact of gross domestic product on the financing and investment efficiency of China’s commercial banks

Author

Listed:
  • Zhen Shi

    (Hohai University)

  • Shijiong Qin

    (Hohai University)

  • Yung-ho Chiu

    (Soochow University)

  • Xiaoying Tan

    (Hohai University)

  • Xiaoli Miao

    (Hohai University)

Abstract

China’s commercial banks have developed at a very rapid speed in recent decades. However, with global economic development slowing down, the impact of gross domestic product growth as an exogenous factor cannot be ignored. Most existing studies only consider the internal factors of banks, and neglect their external economic factors. This study thus adopts an undesirable dynamic slacks-based measure under an exogenous model in combination with the Kernel density curve to explore the efficiency of state-owned commercial banks (SOCBs), joint-stock commercial banks (JSCBs), and urban commercial banks (UCBs) in China from 2012 to 2018. The results show that SOCBs have the highest overall efficiency, followed by JSCBs, then UCBs. The efficiencies of SOCBs, JSCBs, and UCBs in the financing stage are greater than those in the investment stage, indicating that the latter stage brings down overall efficiency. Thus, all commercial banks need to focus on the efficiency of non-performing loans and return on capital. Finally, SOCBs need to strengthen internal controls, reduce non-performing loans and improve return on capital. JSCBs should actively expand its business while controlling costs, and UCBs should optimize its management.

Suggested Citation

  • Zhen Shi & Shijiong Qin & Yung-ho Chiu & Xiaoying Tan & Xiaoli Miao, 2021. "The impact of gross domestic product on the financing and investment efficiency of China’s commercial banks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    • Handle: RePEc:spr:fininn:v:7:y:2021:i:1:d:10.1186_s40854-021-00251-3
    DOI: 10.1186/s40854-021-00251-3
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    References listed on IDEAS

    as
    1. Mester, Loretta J., 1997. "Measuring efficiency at U.S. banks: Accounting for heterogeneity is important," European Journal of Operational Research, Elsevier, vol. 98(2), pages 230-242, April.
    2. Xiaohong Liu & Jiasen Sun & Feng Yang & Jie Wu, 2020. "How ownership structure affects bank deposits and loan efficiencies: an empirical analysis of Chinese commercial banks," Annals of Operations Research, Springer, vol. 290(1), pages 983-1008, July.
    3. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Phan, Hien Thu & Anwar, Sajid & Alexander, W. Robert J. & Phan, Hanh Thi My, 2019. "Competition, efficiency and stability: An empirical study of East Asian commercial banks," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    6. Feifei Zhu & Jing Chen & Zihao Chen & Huixuan Li, 2019. "Shadow banking shadowed in banks’ balance sheets: Evidence from China’s commercial banks," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 59(5), pages 2879-2903, December.
    7. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    8. Qian Long Kweh & Wen-Min Lu & Mohammad Nourani & Mohd Hisyam Ghazali @ Mohd Zain, 2018. "Risk management and dynamic network performance: an illustration using a dual banking system," Applied Economics, Taylor & Francis Journals, vol. 50(30), pages 3285-3299, June.
    9. Chen Zhu & Guihong Hua, 2020. "The impact of China’s Internet Finance on the banking systemic risk – an empirical study based on the SCCA model and stepwise regression," Applied Economics Letters, Taylor & Francis Journals, vol. 27(4), pages 267-274, February.
    10. Ana Lozano-Vivas & Jesús Pastor & José Pastor, 2002. "An Efficiency Comparison of European Banking Systems Operating under Different Environmental Conditions," Journal of Productivity Analysis, Springer, vol. 18(1), pages 59-77, July.
    11. Zhang, Ailian & Wang, Shuyao & Liu, Bai & Fu, Jingyuan, 2020. "How government regulation of interbank financing impacts risk for Chinese commercial banks," Journal of Asian Economics, Elsevier, vol. 66(C).
    12. Chen, Zhongfei & Matousek, Roman & Wanke, Peter, 2018. "Chinese bank efficiency during the global financial crisis: A combined approach using satisficing DEA and Support Vector Machines☆," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 71-86.
    13. Shiyi Chen & Wolfgang K. Härdle & Li Wang, 2020. "Estimation and determinants of Chinese banks’ total factor efficiency: a new vision based on unbalanced development of Chinese banks and their overall risk," Computational Statistics, Springer, vol. 35(2), pages 427-468, June.
    14. Zhuming Chen & Yushan Li & Yawen Wu & Junjun Luo, 2017. "The transition from traditional banking to mobile internet finance: an organizational innovation perspective - a comparative study of Citibank and ICBC," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-16, December.
    15. Chao, Xiangrui & Kou, Gang & Peng, Yi & Viedma, Enrique Herrera, 2021. "Large-scale group decision-making with non-cooperative behaviors and heterogeneous preferences: An application in financial inclusion," European Journal of Operational Research, Elsevier, vol. 288(1), pages 271-293.
    16. Fang, Jianchun & Lau, Chi-Keung Marco & Lu, Zhou & Tan, Yong & Zhang, Hua, 2019. "Bank performance in China: A Perspective from Bank efficiency, risk-taking and market competition," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 290-309.
    17. Xing Zhang & Fengchao Li & Zhen Li & Yingying Xu, 2018. "Macroprudential Policy, Credit Cycle, and Bank Risk-Taking," Sustainability, MDPI, vol. 10(10), pages 1-18, October.
    18. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    19. Tan, Yong, 2016. "The impacts of risk and competition on bank profitability in China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 85-110.
    20. Guseon Ji & Daniel Sungyeon Kim & Kwangwon Ahn, 2019. "Financial Structure and Systemic Risk of Banks: Evidence from Chinese Reform," Sustainability, MDPI, vol. 11(13), pages 1-22, July.
    21. Calmès, Christian & Théoret, Raymond, 2020. "Bank fee-based shocks and the U.S. business cycle," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    22. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    23. Jason Allen & Walter Engert & Ying Liu, 2006. "Are Canadian Banks Efficient? A Canada--U.S. Comparison," Staff Working Papers 06-33, Bank of Canada.
    24. Jian Xue & Di Zhu & Laijun Zhao & Chenchen Wang & Hongyang Li, 2019. "Redundancy Identification and Optimization Scheme of Branches for Sustainable Operation of Commercial Banks," Sustainability, MDPI, vol. 11(15), pages 1-19, July.
    25. Martins, António Miguel & Serra, Ana Paula & Stevenson, Simon, 2019. "Determinants of real estate bank profitability," Research in International Business and Finance, Elsevier, vol. 49(C), pages 282-300.
    26. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    27. Qingxian An & Xuyang Liu & Yongli Li & Beibei Xiong, 2019. "Resource planning of Chinese commercial banking systems using two-stage inverse data envelopment analysis with undesirable outputs," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-20, June.
    28. Renata Karkowska & Jan Acedański, 2020. "The effect of corporate board attributes on bank stability," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 19(2), pages 99-137, May.
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