基于两阶段非期望DEA模型的商业银行效率评估

楚雪芹, 李勇军, 崔峰, 梁樑

系统工程理论与实践 ›› 2021, Vol. 41 ›› Issue (3) : 636-648.

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系统工程理论与实践 ›› 2021, Vol. 41 ›› Issue (3) : 636-648. DOI: 10.12011/SETP2019-0130
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基于两阶段非期望DEA模型的商业银行效率评估

    楚雪芹1, 李勇军1, 崔峰2, 梁樑1
作者信息 +

Efficiency evaluation of commercial banks based on two-stage DEA model with undesirable output

    CHU Xueqin1, LI Yongjun1, CUI Feng2, LIANG Liang1
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摘要

本文将两阶段非期望DEA模型引入银行效率评估，从银行系统内部运营结构入手，构建符合银行结构特征的两阶段网络DEA非线性模型.基于合作共赢的思想，该模型使中间产出在两个子系统的权重相等，将关系模型从规模报酬不变扩展到规模报酬可变的情形，每个银行的系统效率分解为两个子系统的乘积，启发式搜索方法被用来求解新提出的模型.本文将银行经营过程分为筹资阶段和运营阶段，分别应用加权和两阶段模型与该模型对23家商业银行的效率进行测算，验证了提出新模型的合理性.

Abstract

Considering the non-performing loan, this paper introduces the undesirable output into the bank efficiency assessment and constructs a two-stage network DEA model that conforms to the characteristics of the bank structure. This study assumes variable returns to scale, because the input and output of commercial bank vary greatly. However, there is the product of unknown variables in the extended VRS relational model, that is, the objective function is nonlinear. In order to convert it into a linear model, this paper applies a heuristic search to calculating the optimal solution for the new model. Based on the win-win cooperation, the intermediate output is equal in weight of the two subsystems, the system efficiency of each bank is a product of two subsystems. Thus, the extended relational model. Based on the business characteristics of the bank, the bank operation process is divided into the phase of money-raising and the operation. The new model and additive weighting of two-stage model are used to measure the efficiency of the 23 commercial banks, and the rationality of the proposed model is verified. As the national economy and policies, we evaluated efficiency analysis for 4 years based on the intertemporal data, and observe the trends of three different banks. The result of an empirical study reveals that the our proposed model can better reflect the current development trend of the banking industry, the average annual efficiency of state-owned bank is higher than that of joint-stock commercial banks, which is higher than that of urban commercial banks. In terms of the stability of efficiency fluctuations, joint-stock commercial banks are better than urban banks, and urban banks are superior to state-owned banks. Due to differences in management levels and strategy, the efficiency levels of different banks of the same nature are also uneven, and finally considering the current policy we make an analysis and give the corresponding strategies.

关键词

非期望产出 / 两阶段网络DEA模型 / 规模报酬可变

Key words

undesirable output / network DEA model / variable return to scale

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楚雪芹 , 李勇军 , 崔峰 , 梁樑. 基于两阶段非期望DEA模型的商业银行效率评估. 系统工程理论与实践, 2021, 41(3): 636-648 https://doi.org/10.12011/SETP2019-0130
CHU Xueqin , LI Yongjun , CUI Feng , LIANG Liang. Efficiency evaluation of commercial banks based on two-stage DEA model with undesirable output. Systems Engineering - Theory & Practice, 2021, 41(3): 636-648 https://doi.org/10.12011/SETP2019-0130
中图分类号： C934   

参考文献

[1] 陈其安, 刘艾萍. 公司治理与银行效率:来自中国上市商业银行的经验证据[J]. 中国管理科学, 2015, 23(1):437-444. Chen Q A, Liu A P. Corporate governance and bank efficiency:Evidence from Chinese listed commercial banks[J]. Chinese Journal of Management Science, 2015, 23(1):437-444.
[2] 谭政勋, 李丽芳. 中国商业银行的风险承担与效率——货币政策视角[J]. 金融研究, 2016(6):112-126. Tan Z X, Li L F. Risk and efficiency for Chinese commercial banks:From the perspective of monetary policy[J]. Journal of Financial Research, 2016(6):112-126.
[3] 刘孟飞, 张晓岚. 风险约束下的商业银行效率及其影响因素研究[J]. 金融研究, 2013(7):113-125. Liu M F, Zhang X L. On the efficiency of commercial banks and its influencing factors under risk constraints[J]. Journal of Financial Research, 2013(7):113-125.
[4] Berger A N, Humphrey D B. Efficiency of financial institutions:International survey and directions for future research[J]. European Journal of Operational Research, 1997, 98:175-212.
[5] 周小燕. 经济转型中我国商业银行效率与相关因素研究[D]. 上海:复旦大学, 2007.
[6] Sherman H D, Gold F. Bank branch operating efficiency:Evaluation with data envelopment analysis[J]. Journal of Banking and Finance, 1985, 9(2):297-315.
[7] 郭捷, 周婧. 互联网金融背景下我国上市商业银行的效率实证研究[J]. 运筹与管理, 2016, 25(6):120-127. Guo J, Zhou J. An empirical study on commercial banks' efficiency in China under the background of internet finance[J]. Operations Research and Management Science, 2016, 25(6):120-127.
[8] 宋增基,张宗益, 袁茂. 中国银行业DEA效率实证分析[J]. 系统工程理论与实践, 2009, 29(12):105-110.Song Z J, Zhang Z Y, Yuan M. DEA efficiency analysis of Chinese bank companies[J]. Systems Engineering-Theory & Practice, 2009, 29(12):105-110.
[9] 刘瑞波, 潘光杰, 苑晓平. 金融危机后大型中资银行跨国并购效率研究[J]. 经济与管理评论, 2017, 33(6):77-83. Liu R B, Pan G J, Yuan X P. Research on the efficiency of cross-border merger and acquisition of large Chinese banks after the financial crisis[J]. Review of Economy and Management, 2017, 3(6):77-83.
[10] 赵永乐, 王均坦. 商业银行效率、影响因素及其能力模型的解释结果[J]. 金融研究, 2008(3):58-69. Zhao Y L, Wang J T. Commercial bank's efficiency, affecting factors and the explain results from ability model[J]. Journal of Financial Research, 2008(3):58-69.
[11] 朱宁, 梁林, 沈智扬, 等. 经济新常态背景下中国商业银行内生性效率变化及分解[J]. 金融研究, 2018(7):108-123. Zhu N, Liang L, Shen Z Y, et al. Endogenous efficiency of Chinese commercial banks and its decomposition under the China's new normal economy[J]. Journal of Financial Research, 2018(7):108-123.
[12] Färe R, Grosskopf S. Productivity and intermediate products:A frontier approach[J]. Economics Letters, 1996, 50(1):65-70.
[13] Färe R, Grosskopf S. Network DEA[J]. Socio-Economic Planning Sciences, 2000, 34(1):35-49.
[14] Seiford L M, Zhu J. Profitability and marketability of the top 55 US commercial banks[J]. Management Science, 1999, 45(9):1270-1288.
[15] 毕功兵, 梁樑, 杨锋.两阶段生产系统的DEA效率评价模型[J].中国管理科学, 2007, 15(2):92-96. Bi G B, Liang L, Yang F. A DEA-based efficiency-measuring model for a two-stage production system[J]. Chinese Journal of Management Science, 2007, 15(2):92-96.
[16] 芦锋, 刘维奇, 史金凤.我国商业银行效率研究——基于储蓄新视角下的网络DEA方法[J]. 中国软科学, 2012(2):174-184. Lu F, Liu W Q, Shi J F. Research on Chinese commercial banks' efficiency based on network DEA method under the new perspective of savings[J]. China Soft Science, 2012(2):174-184.
[17] Zhang L Y, Chen Y. Equivalent solutions to additive two-stage network data envelopment analysis[J]. European Journal of Operational Research, 2018, 264(3):1189-1191.
[18] Wang K, Huang W, Wu J, et al. Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA[J]. Omega, 2014(44):5-20.
[19] Kao C, Hwang S N. Efficiency decomposition in two-stage data envelopment analysis:An application to non-life insurance companies in Taiwan[J]. European Journal of Operational Research, 2008, 185(1):418-429.
[20] Wanke P, Barros C. Two-stage DEA:An application to major Brazilian banks[J]. Expert Systems with Applications, 2014, 41(5):2337-2344.
[21] 曾薇, 陈收, 周忠宝. 金融监管对商业银行产品创新影响——基于两阶段DEA模型的研究[J]. 中国管理科学, 2016, 24(5):1-7. Zeng W, Chen S, Zhou Z B. The impact of financial supervision on commercial bank's product innovation-The research based on two-stage DEA model[J]. Chinese Journal of Management Science, 2016, 24(5):1-7.
[22] 胡晓燕, 程希骏, 马利军. 考虑非期望产出的两阶段DEA模型及其在银行效率评价中的应用[J]. 中国科学院大学学报, 2013, 30(4):462-471. Hu X Y, Cheng X J, Ma L J. Efficiency evaluation of commercial banks based on two-stage DEA model considering undesirable outputs[J]. Journal of University of Chinese Academy of Sciences, 2013, 30(4):462-471.
[23] 纪建悦, 孔胶胶.利益相关者关系视角下考虑非期望产出的商业银行效率问题研究[J].中国管理科学, 2013, 21(6):30-37. Ji J Y, Kong J J. The study on the efficiency evaluation considered undesirable output and its influencing factors of commercial banks from the perspective of stakeholder relationships[J]. Chinese Journal of Management Science, 2013, 21(6):30-37.
[24] 张浩, 杨慧敏. 基于考虑非期望产出的超效率网络SBM模型的我国商业银行效率[J]. 系统工程, 2017, 35(4):17-24. Zhang H, Yang H M. Efficiency evaluation of Chinese commercial banks based on the super-efficiency network SBM model with considering undesirable outputs[J]. Systems Engineering, 2017, 35(4):17-24.
[25] Li Y J, Chen Y, Liang L, et al. DEA models for extended two-stage network structures[J]. Omega, 2012, 40(5):611-618.
[26] Liang L, Yang F, Cook W D, et al. DEA models for supply chain efficiency evaluation[J]. Annals of Operations Research, 2006, 145(1):35-49.
[27] Golany B, Roll Y. An application procedure for DEA[J]. Omega, 1989, 17(3):237-250.
[28] Sun S. Measuring the relative efficiency of police precincts using data envelopment analysis[J]. Socio-Economic Planning Sciences, 2002, 36(1):51-71.
[29] Tone K, Kweh Q L, Lu W M, et al. Modeling investments in the dynamic network performance of insurance companies[J]. Omega, 2018:1-11.
[30] Chen Y, Cook W D, Kao C, et al. Network DEA pitfalls:Divisional efficiency and frontier projection under general network structures[J]. European Journal of Operational Research, 2013, 226:507-515.
[31] Wu J, Zhu Q Y, Chu J F, et al. Measuring energy and environmental efficiency of transportation systems in China based on a parallel DEA approach[J]. Transportation Research Part D, 2016, 48:460-472.

基金

国家自然科学基金（71671172）；国家自然科学基金重点项目（71631006）
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