两阶段DEA前沿面投影问题研究——兼对我国上市银行运营绩效进行评价

DEA方法,即数据包络分析方法,是一种用于评价决策单元(Decision Making Units,DMUs)相对有效性的实证方法。近年来DEA方法已经广泛的应用于各行各业的绩效评价中,并发展出两阶段DEA方法。两阶段DEA方法相对于传统DEA方法的优势在于,它不但可以提供被评价对象的总体效率值,还可以分别生成每一阶段的效率值。但正是由于中间要素的存在,按照传统的DEA方法来调整两阶段DEA投入、产出要素的优化过程已不能成功投影在有效前沿面上。本文基于两阶段DEA方法,通过加入"虚拟中间要素"在两阶段DEA中嵌入一个"虚拟阶段",这样不但完善了两阶段DEA的逻辑结构,而且成功的将被评价单元投影到有效前沿面。最后本文应用以上方法对我国上市银行的运营绩效进行了实证分析。实证结果令我们意外的是,国有商业银行运营绩效优于股份制银行。

The Research on Two-stage DEA Projection Generation Problems--Evaluate the Operational Performance of List Bank in China Stock Market

DEA(data envelopment analysis)is an empirical method which is used to evaluate the relative effectiveness of decision-making units(DMUs).The DEA has long been applied to assess operational performance in public and private sectors and a two-stage DEA method has been developed.Relative to the traditional DEA approach,two-stage DEA method has the advantage that it can not only provide the overall efficiency values of the evaluated objects,but also the values of each stage.But because of the existence of intermediate elements,two-stage DEA method can not follow the way which the traditional method does to adjust the inputs and outputs of the optimization process to project onto the effective frontier.Based on two-stage DEA method,by adding "virtual intermediate elements",we embed a "virtual stage" into the stages.Thus we can not only improve the logical structure of two-stage DEA,but also yield a frontier projection successfully.We apply the method to accomplish empirical analysis of operating performance of listed banks in China stock market.The empirical results surprise us that the operating performances of state-owned commercial banks are superior than the joint-stock banks.