考虑不良贷款时滞效应的中国商业银行绩效分析
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摘要
本文将不良贷款纳入银行经营绩效的评价中,考虑不良贷款在银行下一个生产周期中的时滞效应,建立了基于不良贷款时滞效应的DEA银行效率评价模型和DEA-Malmquist生产率指数模型,对银行生产效率及生产率指数进行测算和分析。研究结果表明,不考虑不良贷款时滞效应易低估银行实际生产效率。不良贷款时滞效应对股份制商业银行和城市商业银行的效率影响较为明显,而对国有商业银行的效率影响较不明显。中国商业银行生产率指数变化主要受技术进步影响。
In this paper,non-performing loans are included in the evaluation of bank performance.Considering the time lag effect of non-performing loans into bank efficiency and productivity analysis,the DEA efficiency evaluation model and DEA-Malmquist productivity index model based on non-performing loans time lag effect are established.The results show that without considering the time lag effect of bad loans,it is easy to underestimate the actual production efficiency of banks.The time lag effect of non-performing loans has a prominent impact on the efficiency of joint-stock commercial banks and urban commercial banks,but not on the efficiency of state-owned commercial banks.The productivity index of commercial banks in China is mainly affected by technological progress.
In this paper,non-performing loans are included in the evaluation of bank performance.Considering the time lag effect of non-performing loans into bank efficiency and productivity analysis,the DEA efficiency evaluation model and DEA-Malmquist productivity index model based on non-performing loans time lag effect are established.The results show that without considering the time lag effect of bad loans,it is easy to underestimate the actual production efficiency of banks.The time lag effect of non-performing loans has a prominent impact on the efficiency of joint-stock commercial banks and urban commercial banks,but not on the efficiency of state-owned commercial banks.The productivity index of commercial banks in China is mainly affected by technological progress.
引文
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[15]张炳,毕军,黄和平,等.基于DEA的企业生态效率评价:以杭州湾精细化工园区企业为例[J].系统工程理论与实践,2008,(4):159～166.
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[17]Zha Y,Liang N,Wu M,et al.Efficiency Evaluation of Banks in China:A Dynamic Two-stage Slacks-based Measure Approach[J].Omega,2016,60:60～72.
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[20]Chen Y,Ali A I.DEA Malmquist Productivity Measure:New Insights with an Application to Computer Industry[J].European Journal of Operational Research,2004,159(1):239～249.
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[22]张健华,王鹏,冯根福.银行业结构与中国全要素生产率——基于商业银行分省数据和双向距离函数的再检验[J].经济研究,2016,51(11):110～12.
[2]Charnes A,Cooper W W,Rhodes E.Measuring the Efficiency of Decision Making Units[J].European Journal of Operational Research,1978,2(6):429～444.
[3]Zha Y,Liang N,Wu M,et al.Efficiency Evaluation of Banks in China:A Dynamic Two-stage Slacks-based Measure Approach[J].Omega,2016,60:60～72.
[4]Lozano S.Slacks-based Inefficiency Approach for General Networks with Bad Outputs:An Application to the Banking Sector[J].Omega,2016,60:73～84.
[5]Wanke P,Maredza A,Gupta R.Merger and Acquisitions in South African Banking:A Network DEA Model[J].Research in International Business and Finance,2017,41:362～376.
[6]Izadikhah M,Tavana M,Di Caprio D,et al.A Novel Two-stage DEA Production Model with Freely Distributed Initial Inputs and Shared Intermediate Outputs[J].Expert Systems with Applications,2018,99:213～230.
[7]柯孔林,冯宗宪.中国银行业全要素生产率测度:基于Malmquist-Luenberger指数研究[J].数量经济技术经济研究,2008,(4):110～120.
[8]Arabi B,Munisamy S,Emrouznejad A.A New Slacks-based Measure of Malmquist——Luenberger Index in the Presence of Undesirable Outputs[J].Omega,2015,51:29～37.
[9]Aghayi N,Maleki B.Efficiency Measurement of DMUs with Undesirable Outputs Under Uncertainty Based on the Directional Distance Function:Application on Bank Industry[J].Energy,2016,112:376～387.
[10]Tone K,Tsutsui M.Dynamic DEA with Network Structure:A Slacks-based Measure Approach[J].Omega,2014,42(1):124～131.
[11]Akther S,Fukuyama H,Weber W L.Estimating Two-stage Network Slacks-based Inefficiency:An Application to Bangladesh Banking[J].Omega,2013,41(1):88～96.
[12]Fukuyama H,Weber W L.A Slacks-based Inefficiency Mea-sure for a Two-stage System with Bad Outputs[J].Omega,2010,38(5):398～409.
[13]Zha Y,Liang N,Wu M,et al.Efficiency Evaluation of Banks in China:A Dynamic Two-stage Slacks-based Measure Approach[J].Omega,2016,60:60～72.
[14]韩松,苏熊.中国商业银行结构效率研究:基于复杂网络DEA模型[J].中国管理科学,2016,24(8):1～9.
[15]张炳,毕军,黄和平,等.基于DEA的企业生态效率评价:以杭州湾精细化工园区企业为例[J].系统工程理论与实践,2008,(4):159～166.
[16]陈磊,王应明.基于环境绩效视角的交叉效率评价方法[J].系统工程学报,2016,31(5):700～709.
[17]Zha Y,Liang N,Wu M,et al.Efficiency Evaluation of Banks in China:A Dynamic Two-stage Slacks-based Measure Approach[J].Omega,2016,60:60～72.
[18]F?re R,Grosskopf S,Lindgren B,et al.Productivity Changes in Swedish Pharamacies 1980～1989:A Non-parametric Malmquist Approach[M].Springer Netherlands,1992:102～136.
[19]Caves D W,Christensen L R,Diewert W E.The Economic Theory of Index Numbers and the Measurement of Input,Output,and Productivity[J].Econometrica:Journal of the Econometric Society,1982,50(6):1393～1414.
[20]Chen Y,Ali A I.DEA Malmquist Productivity Measure:New Insights with an Application to Computer Industry[J].European Journal of Operational Research,2004,159(1):239～249.
[21]Matthews K,Guo J,Zhang N.Rational Inefficiency and Non-performing Loans in Chinese Banking:A Non-parametric Bootstrapping Approach[R].Cardiff Economics Working Papers,2007,2.
[22]张健华,王鹏,冯根福.银行业结构与中国全要素生产率——基于商业银行分省数据和双向距离函数的再检验[J].经济研究,2016,51(11):110～12.