한국해양대학교

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한국과 중국 은행의 효율성변화에 관한 비교 분석

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dc.contributor.advisor 나호수 -
dc.contributor.author 이중하 -
dc.date.accessioned 2019-12-16T02:43:27Z -
dc.date.available 2019-12-16T02:43:27Z -
dc.date.issued 2017 -
dc.identifier.uri http://repository.kmou.ac.kr/handle/2014.oak/11429 -
dc.identifier.uri http://kmou.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002333296 -
dc.description.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 -
dc.description.tableofcontents - 목차 - 제1장 서론 1 제1절 연구배경 및 목적 1 제2절 연구방법 및 구성 5 제2장 한국과 중국의 은행산업 동향 7 제1절 한국의 은행산업 7 1. 한국 은행산업의 구조 7 2. 한국 은행산업의 발전과정 9 제2절 중국의 은행산업 13 1. 중국 은행산업의 구조 13 2. 중국 은행산업의 발전과정 19 제3장 연구방법론 23 제1절 효율성 이론 23 1. 효율성 개념 23 2. 효율성 종류 24 제2절 분석 모형 33 1. 자료포락분석 33 2. 확률변경분석 34 3. Malmqusit 생산성지수 35 제3절 선행연구 고찰 36 1. 자료포락분석을 활용한 선행연구 36 2. 확률변경분석을 활용한 선행연구 40 3. Malmquist 생산성지수를 활용한 선행연구 44 제4장 실증분석 47 제1절 분석개요 47 1. 투입 및 산출 변수 47 2. 연구대상 50 3. 기초통계량 51 제2절 실증분석 55 1. DEA를 이용한 효율성 분석 55 2. SFA를 이용한 효율성 분석 66 3. Malmquist 생산성지수를 이용한 효율성 변화 분석 76 제5장 결론 90 제1절 연구결과 요약 90 제2절 연구의 시사점과 향후과제 93 참 고 문 헌 99 국내문헌 99 국외문헌 102 -
dc.format.extent 107 -
dc.language kor -
dc.publisher 한국해양대학교 대학원 -
dc.rights 이중하 -
dc.title 한국과 중국 은행의 효율성변화에 관한 비교 분석 -
dc.type Dissertation -
dc.date.awarded 2017-02 -
dc.contributor.alternativeName Lee, Joong ha -
dc.contributor.department 대학원 경제산업학과 -
dc.contributor.affiliation 하림개발(주) -
dc.description.degree Doctor -
dc.subject.keyword DEA,SFA,Malmquist product index,Efficiency,technical efficiency,pure technical efficiency,scale efficiency,returns to scale -
dc.type.local Text -
dc.title.translated A Comparative Analysis of the Efficiency Changes of Banks in Korea and China -
dc.contributor.specialty 경제학 -
dc.identifier.holdings 000000001979▲000000006780▲000002333296▲ -
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