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

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  • 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
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    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.
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