IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v290y2020i1d10.1007_s10479-018-3106-6.html
   My bibliography  Save this article

How ownership structure affects bank deposits and loan efficiencies: an empirical analysis of Chinese commercial banks

Author

Listed:
  • Xiaohong Liu

    (University of Science and Technology of China)

  • Jiasen Sun

    (Soochow University)

  • Feng Yang

    (University of Science and Technology of China)

  • Jie Wu

    (University of Science and Technology of China)

Abstract

This study explored how dramatic changes in ownership structure and operational technologies have influenced Chinese bank efficiency over the past decade. The study included an empirical analysis using 5 years (2011–2015) of operational data for 71 Chinese commercial banks. Two two-stage meta-frontier data envelopment analysis network models and multiple regression models were used to estimate and analyze impacts of variations in bank ownership structure. The main empirical results show that irrespective of deposits or loans efficiency, State-owned Banks (SOBs) have the highest technology and management levels. In contrast, City Commercial Banks should improve both technology and management levels, narrowing the gap with SOBs and Joint-stock Banks. The deposit efficiency of a bank was found to be mainly influenced by the nature of ownership (national shareholding ratio and the shareholding ratio of the domestic legal entities) and ownership concentration. The loan efficiency of a bank was mainly affected by the nature of ownership (the shareholding ratio of the foreign legal entities) and ownership liquidity.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:290:y:2020:i:1:d:10.1007_s10479-018-3106-6
    DOI: 10.1007/s10479-018-3106-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-018-3106-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-018-3106-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    2. Kao, Chiang, 2017. "Efficiency measurement and frontier projection identification for general two-stage systems in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 261(2), pages 679-689.
    3. Matthews, Kent, 2013. "Risk management and managerial efficiency in Chinese banks: A network DEA framework," Omega, Elsevier, vol. 41(2), pages 207-215.
    4. Athanassopoulos, Antreas D, 1998. "Nonparametric Frontier Models for Assessing the Market and Cost Efficiency of Large-Scale Bank Branch Networks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 30(2), pages 172-192, May.
    5. Maoyong Cheng & Hong Zhao & Junrui Zhang, 2014. "What precludes the development of noninterest activities in Chinese commercial banks from the perspective of the price of interest activities?," Applied Economics, Taylor & Francis Journals, vol. 46(21), pages 2453-2461, July.
    6. Park, Kang H. & Weber, William L., 2006. "A note on efficiency and productivity growth in the Korean Banking Industry, 1992-2002," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2371-2386, August.
    7. Subhash C. Ray, 1991. "Resource-Use Efficiency in Public Schools: A Study of Connecticut Data," Management Science, INFORMS, vol. 37(12), pages 1620-1628, December.
    8. Qingxian An & Haoxun Chen & Jie Wu & Liang Liang, 2015. "Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output," Annals of Operations Research, Springer, vol. 235(1), pages 13-35, December.
    9. DeYoung, Robert & Hasan, Iftekhar, 1998. "The performance of de novo commercial banks: A profit efficiency approach," Journal of Banking & Finance, Elsevier, vol. 22(5), pages 565-587, May.
    10. Robert Lensink & Aljar Meesters, 2014. "Institutions and Bank Performance: A Stochastic Frontier Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 67-92, February.
    11. Berger, Allen N. & Humphrey, David B., 1997. "Efficiency of financial institutions: International survey and directions for future research," European Journal of Operational Research, Elsevier, vol. 98(2), pages 175-212, April.
    12. 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.
    13. Lothgren, Mickael & Tambour, Magnus, 1999. "Productivity and customer satisfaction in Swedish pharmacies: A DEA network model," European Journal of Operational Research, Elsevier, vol. 115(3), pages 449-458, June.
    14. Dekker, David & Post, Thierry, 2001. "A quasi-concave DEA model with an application for bank branch performance evaluation," European Journal of Operational Research, Elsevier, vol. 132(2), pages 296-311, July.
    15. Fukuyama, Hirofumi & Matousek, Roman, 2017. "Modelling bank performance: A network DEA approach," European Journal of Operational Research, Elsevier, vol. 259(2), pages 721-732.
    16. 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.
    17. Chiang Kao, 2017. "General Two-Stage Systems," International Series in Operations Research & Management Science, in: Network Data Envelopment Analysis, chapter 0, pages 237-273, Springer.
    18. Xu, Lei & Lin, Chien-Ting, 2007. "Can Chinese banks compete after accession to WTO?," Journal of Asian Economics, Elsevier, vol. 18(6), pages 883-903, December.
    19. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    20. Chiu, Ching-Ren & Liou, Je-Liang & Wu, Pei-Ing & Fang, Chen-Ling, 2012. "Decomposition of the environmental inefficiency of the meta-frontier with undesirable output," Energy Economics, Elsevier, vol. 34(5), pages 1392-1399.
    21. Paradi, Joseph C. & Zhu, Haiyan, 2013. "A survey on bank branch efficiency and performance research with data envelopment analysis," Omega, Elsevier, vol. 41(1), pages 61-79.
    22. Chien Wang & Ram Gopal & Stanley Zionts, 1997. "Use of Data Envelopment Analysis in assessing Information Technology impact on firm performance," Annals of Operations Research, Springer, vol. 73(0), pages 191-213, October.
    23. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    24. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    25. Sherman, H. David & Gold, Franklin, 1985. "Bank branch operating efficiency : Evaluation with Data Envelopment Analysis," Journal of Banking & Finance, Elsevier, vol. 9(2), pages 297-315, June.
    26. Oh, Dong-hyun, 2010. "A metafrontier approach for measuring an environmentally sensitive productivity growth index," Energy Economics, Elsevier, vol. 32(1), pages 146-157, January.
    27. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    28. Bonin, John P. & Hasan, Iftekhar & Wachtel, Paul, 2005. "Bank performance, efficiency and ownership in transition countries," Journal of Banking & Finance, Elsevier, vol. 29(1), pages 31-53, January.
    29. Ahmet Faruk Aysan & Mustafa Mete Karakaya & Metin Uyanik, 2011. "Panel stochastic frontier analysis of profitability and efficiency of turkish banking sector in the post crisis era," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 12(4), pages 629-654, March.
    30. Ariff, Mohamed & Can, Luc, 2008. "Cost and profit efficiency of Chinese banks: A non-parametric analysis," China Economic Review, Elsevier, vol. 19(2), pages 260-273, June.
    31. Camanho, A. S. & Dyson, R. G., 2005. "Cost efficiency measurement with price uncertainty: a DEA application to bank branch assessments," European Journal of Operational Research, Elsevier, vol. 161(2), pages 432-446, March.
    32. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    33. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    34. Barros, C.P. & Emrouznejad, Ali, 2016. "Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banksAuthor-Name: Wanke, Peter," European Journal of Operational Research, Elsevier, vol. 249(1), pages 378-389.
    35. Yang, Chyan & Liu, Hsian-Ming, 2012. "Managerial efficiency in Taiwan bank branches: A network DEA," Economic Modelling, Elsevier, vol. 29(2), pages 450-461.
    36. Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
    37. Rolf Fare & Shawna Grosskopf & William Weber, 2004. "The effect of risk-based capital requirements on profit efficiency in banking," Applied Economics, Taylor & Francis Journals, vol. 36(15), pages 1731-1743.
    38. Zha, Yong & Liang, Nannan & Wu, Maoguo & Bian, Yiwen, 2016. "Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach," Omega, Elsevier, vol. 60(C), pages 60-72.
    39. Camanho, A.S. & Dyson, R.G., 2008. "A generalisation of the Farrell cost efficiency measure applicable to non-fully competitive settings," Omega, Elsevier, vol. 36(1), pages 147-162, February.
    40. Aggelopoulos, Eleftherios & Georgopoulos, Antonios, 2017. "Bank branch efficiency under environmental change: A bootstrap DEA on monthly profit and loss accounting statements of Greek retail branches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1170-1188.
    41. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    42. Wang, Ke & Huang, Wei & Wu, Jie & Liu, Ying-Nan, 2014. "Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA," Omega, Elsevier, vol. 44(C), pages 5-20.
    43. Ruggiero, John, 1996. "On the measurement of technical efficiency in the public sector," European Journal of Operational Research, Elsevier, vol. 90(3), pages 553-565, May.
    44. Fethi, Meryem Duygun & Pasiouras, Fotios, 2010. "Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey," European Journal of Operational Research, Elsevier, vol. 204(2), pages 189-198, July.
    45. Chang, Tzu-Pu & Hu, Jin-Li & Chou, Ray Yeutien & Sun, Lei, 2012. "The sources of bank productivity growth in China during 2002–2009: A disaggregation view," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1997-2006.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sunil Mohanty & Hong-Jen Lin, 2021. "Efficiency in China’s Banking Sector: A Comparative Analysis of Pre- and Post-Basel II Eras," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 24(02), pages 1-29, June.
    2. Doumpos, Michalis & Zopounidis, Constantin & Gounopoulos, Dimitrios & Platanakis, Emmanouil & Zhang, Wenke, 2023. "Operational research and artificial intelligence methods in banking," European Journal of Operational Research, Elsevier, vol. 306(1), pages 1-16.
    3. Faten Ben Bouheni & Hassan Obeid & Elena Margarint, 2022. "Nonperforming loan of European Islamic banks over the economic cycle," Annals of Operations Research, Springer, vol. 313(2), pages 773-808, June.
    4. J. David Cummins & María Rubio-Misas, 2022. "Integration and convergence in efficiency and technology gap of European life insurance markets," Annals of Operations Research, Springer, vol. 315(1), pages 93-119, August.
    5. Fukuyama, Hirofumi & Tsionas, Mike & Tan, Yong, 2023. "Dynamic network data envelopment analysis with a sequential structure and behavioural-causal analysis: Application to the Chinese banking industry," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1360-1373.
    6. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vaneet Bhatia & Sankarshan Basu & Subrata Kumar Mitra & Pradyumna Dash, 2018. "A review of bank efficiency and productivity," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 557-600, November.
    2. Jiawei Yang, 2023. "Disentangling the sources of bank inefficiency: a two-stage network multi-directional efficiency analysis approach," Annals of Operations Research, Springer, vol. 326(1), pages 369-410, July.
    3. Xie, Qiwei & Xu, Qifan & Chen, Lifan & Jin, Xi & Li, Siqi & Li, Yongjun, 2022. "Efficiency evaluation of China's listed commercial banks based on a multi-period leader-follower model," Omega, Elsevier, vol. 110(C).
    4. Xiaohong Liu & Feng Yang & Jie Wu, 2020. "DEA considering technological heterogeneity and intermediate output target setting: the performance analysis of Chinese commercial banks," Annals of Operations Research, Springer, vol. 291(1), pages 605-626, August.
    5. Dan Li & Yanfeng Li & Yeming Gong & Jiawei Yang, 2021. "Estimation of bank performance from multiple perspectives: an alternative solution to the deposit dilemma," Journal of Productivity Analysis, Springer, vol. 56(2), pages 151-170, December.
    6. Fukuyama, Hirofumi & Matousek, Roman & Tzeremes, Nickolaos G., 2020. "A Nerlovian cost inefficiency two-stage DEA model for modeling banks’ production process: Evidence from the Turkish banking system," Omega, Elsevier, vol. 95(C).
    7. Chih-Ching Yang, 2010. "Service, investment, and risk management performance in commercial banks," The Service Industries Journal, Taylor & Francis Journals, vol. 32(12), pages 2005-2025, December.
    8. Partovi, Elmira & Matousek, Roman, 2019. "Bank efficiency and non-performing loans: Evidence from Turkey," Research in International Business and Finance, Elsevier, vol. 48(C), pages 287-309.
    9. Manh D. Pham & Valentin Zelenyuk, 2018. "Slack-based directional distance function in the presence of bad outputs: theory and application to Vietnamese banking," Empirical Economics, Springer, vol. 54(1), pages 153-187, February.
    10. Chiu, Ching-Ren & Chiu, Yung-Ho & Chen, Yu-Chuan & Fang, Chen-Ling, 2016. "Exploring the source of metafrontier inefficiency for various bank types in the two-stage network system with undesirable output," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 1-13.
    11. Kounetas, Konstantinos & Zervopoulos, Panagiotis D., 2019. "A cross-country evaluation of environmental performance: Is there a convergence-divergence pattern in technology gaps?," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1136-1148.
    12. Gulati, Rachita, 2022. "Global and local banking crises and risk-adjusted efficiency of Indian banks: Are the impacts really perspective-dependent?," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 23-39.
    13. Mohammad Nourani & Qian Long Kweh & Wen-Min Lu & Ikhlaas Gurrib, 2022. "Operational and investment efficiency of investment trust companies: Do foreign firms outperform domestic firms?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-26, December.
    14. Wang, Ke & Huang, Wei & Wu, Jie & Liu, Ying-Nan, 2014. "Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA," Omega, Elsevier, vol. 44(C), pages 5-20.
    15. Kounetas, Kostas & Zervopoulos, Panagiotis, 2017. "Annex I and non-Annex I countries’productive performance revisited using a generalized directional distance function under a metafrontier framework: Is there any convergence-divergence pattern for tec," MPRA Paper 80904, University Library of Munich, Germany.
    16. Fukuyama, Hirofumi & Matousek, Roman, 2018. "Nerlovian revenue inefficiency in a bank production context: Evidence from Shinkin banks," European Journal of Operational Research, Elsevier, vol. 271(1), pages 317-330.
    17. 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.
    18. Paradi, Joseph C. & Zhu, Haiyan, 2013. "A survey on bank branch efficiency and performance research with data envelopment analysis," Omega, Elsevier, vol. 41(1), pages 61-79.
    19. H Fukuyama & W L Weber, 2009. "Estimating indirect allocative inefficiency and productivity change," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(11), pages 1594-1608, November.
    20. Gulati, Rachita & Kumar, Sunil, 2016. "Assessing the impact of the global financial crisis on the profit efficiency of Indian banks," Economic Modelling, Elsevier, vol. 58(C), pages 167-181.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:290:y:2020:i:1:d:10.1007_s10479-018-3106-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.