| Summary: | 碩士 === 東吳大學 === 經濟學系 === 107 === This paper divides 88 commercial banks in China from 2015 to 2017 into state-owned commercial banks, joint-stock commercial banks, city commercial banks, rural commercial banks and foreign banks. The dynamic two-stage SBM model is used to explore the operational and profit efficiency of the above five types of commercial banks. Then we use Boston matrix to analyze the efficiency value of commercial banks that mainly to explore the difference in performance between different 5 types of banks in operation and profit efficiency. Finally, the sensitivity analysis of dynamic setting and weight setting are performed by kendall's coefficient of rank correlation and Wilcoxon test.
In the first stage of operation, commercial banks, joint-stock commercial banks and foreign banks’ scores are higher than average annual efficiency values. The performance of foreign banks at this stage is good and have better management capabilities, due to their past experience. In the second stage of profit, state-owned commercial banks, joint-stock commercial banks and foreign banks’ scores are higher than annual average efficiency value. Foreign banks have the smallest scale, but the profitability is higher than that of city and rural commercial banks. The reason is low non-performing loan ratio.
According to the Boston Matrix, state-owned commercial banks have high operations and high profitability. Joint-stock commercial banks are comparable to state-owned commercial banks but must be aware of operations. Nearly 50% of city commercial banks have high operations and high profitability, but more than 50% require special attention in operations and profitability. More than 50% of rural commercial banks have performed poorly in both operation and profitability. More than 50% of foreign banks have excellent performance in operations and profits, and a few banks need to pay attention to their operational performance.
For sensitivity analysis, according to the Wilcoxon test and the dynamic two-stage model Carry-over setting, rural commercial banks operating non-performing loans, total loans and securities investment have a significant influence in 2016. For two-stage weight setting, with the setting of “0.2 and 0.8” and “0.8 and 0.2” in rural commercial banks in 2016, and “0.8 and 0.2” in rural commercial banks in 2017, there is a significant difference. The rest is not significantly different from the model in this paper.
|
|---|
