한국해양대학교

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한국과 중국 은행의 효율성변화에 관한 비교 분석

Title
한국과 중국 은행의 효율성변화에 관한 비교 분석
Author(s)
이중하
Keyword
DEA,SFA,Malmquist product index,Efficiency,technical efficiency,pure technical efficiency,scale efficiency,returns to scale
Issued Date
2017
Publisher
한국해양대학교 대학원
URI
http://repository.kmou.ac.kr/handle/2014.oak/11429
http://kmou.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002333296
Abstract
A Comparative Analysis of the Efficiency Changes of Banks in Korea and China



Lee, Joong Ha



Department of Economy and Industry Graduate School of Korea Maritime and Ocean University



Abstract

This study used DEA, SFA and MPI to analyze the efficiency and changes in efficiency of Korean and Chinese banks. The analysis period was from 2010 to 2014 for five years and the study analyzed 22 Korean and Chinese banks. The inputs for the analysis were the number of employees, the number of branches, fixed assets and deposits and the outputs were total loans, investment in securities and net profits. The results of the study are summarized as follows.

First, the results are from the comparative analysis of efficiency of Korean and Chinese banks. In terms of technical efficiency, the banks in Korea declined within the analysis period and also technical efficiency decreased for the Chinese banks. In terms of net technical efficiency, the banks in Korea declined during the analysis period, whilst net technical efficiency of the Chinese banks decreased from 2010 to 2013 but rose in 2014. In terms of scale efficiency, the banks in China decreased during the analysis period while the banks in Korea showed both increase and decrease.

Second, the results are from the comparative analysis of economies of scale between the banks in Korea and China. From 2010 to 2014, many banks in Korea experienced increasing returns to sale (IRS) while many banks in China experienced decreasing returns to scale (DRS).

Third, the efficiency of the banks in Korea and China by using the SFA analysis shows that the efficiency in the Korean banks increased from 2010 to 2013 and decreased in 2014. The efficiency in the Chinese banks from 2010 to 2014 generally decreased.

Fourth, the efficiency of DEA and SFA are compared. Since there is no statistically significant difference between the CCR value calculated by DEA and the efficiency of SFA, it shows that there is a similar trend. In terms of correlation, there is a relevance in efficiencies between CCR and SFA.

Fifth, we examined the changes in efficiency of the Chinese and Korean banks by using Malmquist Productivity Index (MPI) between 2010 and 2014. In terms of the changes in efficiency of the banks in Korea, the productivity index value exceeded 1 between 2010-2011 period and 2012-2013 period, indicating that the efficiency increased from the previous year. However, the productivity index was less than 1 during 2013-2014 period and the efficiency decreased from the previous year. In the case of Chinese banks, the productivity index exceeded 1 from 2010-2011 period to 2013-2014 period and the efficiency increased from the previous year.

Sixth, the portfolio analysis was used to compare the technical analysis and productivity index. Jeju, Jeonbuk, Gyeongnam and Hana Bank were the most likely banks with high competitiveness and high growth potential. For Chinese banks, Shanghai Pudong Development Bank and China Minsheng Banking Corporation were the most likely banks with high competitiveness and high growth potential. There were no banks with high competitiveness and low growth potential. The banks with low competitiveness and low growth potential were Kookmin Bank and Shinhan Bank.

This study suggests the following limitations. First, DEA, SFA and MPI for efficiency analysis only analyses relative efficiency, so banks’ absolute efficiency cannot be measured. Therefore, the efficiency and its changes can vary depending on input and output variables. In order to measure efficiency more accurately, qualitative evaluation such as AHP technique and management evaluation should be taken into account, so they can complement each other.

Second, the efficiency and the efficiency changes of banks can be measured more accurately when more variables are added. However, for DEA, SFA and MPI have limitations that not only the number of variables but also the number of decision units should be taken into consideration. Therefore, both input and output variables need to be carefully considered in order to measure the efficiency and the efficiency changes for conducting a comparative analysis, such as the number of banks, the global financial environment variables during the analysis period, and economic policy variables of both countries.

KEY WORDS: DEA, SFA, Malmquist product index, Efficiency, technical efficiency, pure technical efficiency, scale efficiency, returns to scale
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