摘要
相比一般的DEA模型,超效率DEA模型能够对均处于效率前沿的决策单元进行有效评价,但是该模型无法剔除环境和随机误差因素对效率值的影响,从而无法得到真实的效率值。在超效率DEA模型的基础上,利用随机前沿方法(SFA)进行优化调整,分阶段对我国商业银行效率进行实证分析,结果表明:环境和随机误差因素对商业银行效率具有显著影响,超效率DEA三阶段模型较超效率DEA模型更具合理性,进行规范的股份制改革以及适度的机构规模调整是提升我国商业银行效率的有效途径。
Compared with general DEA model,super-efficiency DEA model can make an effective evaluation to every decision making unit.However,the model can not eliminate environmental factors and random error factors on the efficiency,which makes it is not able to get the true value of efficiency.Empirical research has been done to analyze the efficiency of commercial banks using the modified DEA model which is optimized by Stochastic frontier approach（SFA）.The results show that environmental factors and random error factors have significant effects on the efficiency of commercial banks,so super-efficiency data envelopment analysis model is more reasonable method.The joint-stock reform and appropriate size of institution adjustment is the efficient and effective way to enhance the efficiency of commercial banks in China.
出处
《财经理论与实践》
CSSCI
北大核心
2012年第6期17-21,共5页
The Theory and Practice of Finance and Economics
关键词
商业银行效率
超效率DEA三阶段模型
随机前沿方法(SFA)
模型优化
The efficiency of commercial banks
Super-efficiency Data Envelopment Analysis model
Stochastic frontier approach（SFA）
Model optimization
