• Title/Summary/Keyword: 가중평균 러셀 방향거리함수 모형

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Analysis of influencing on Inefficiencies of Korean Banking Industry using Weighted Russell Directional Distance Model (가중평균 러셀(Russell) 방향거리함수모형을 이용한 은행산업의 비효율성 분석)

  • Yang, Dong-Hyun;Chang, Young-Jae
    • Journal of Digital Convergence
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    • v.17 no.5
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    • pp.117-125
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    • 2019
  • This study measured inefficiencies of Korean banks with weighted Russell directional distance function, WRDDM, for the years of 2004-2013. Checking contributions of inputs and outputs to these inefficiencies, we found that non-performing loan as undesirable output was the most influential factor. The annual average of inefficiencies of Korean banks was 0.3912, and it consisted of non-performing loan 0.1883, output factors 0.098 except non-performing loan, input factors 0.098. The annual average inefficiency went sharply up from 0.2995 to 0.4829 mainly due to the sharp increase of inefficiency of non-performing loan from 0.1088 to 0.2678 before and after 2007-2008 Global financial crisis. We empirically showed the non-performing loan needed to be considered since it was the most important factor among the influential factors of technical inefficiency such as manpower, total deposit, securities, and non-performing loan. This study had some limitation since we did not control financial environment factor in WRDDM.

Inefficiencies and Productivity Change of Domestic Banks including Non-performing Loan with Normal Output after Financial Crisis (금융위기 이후 부실채권을 고려한 국내 은행의 비효율성과 생산성 변화)

  • Chang, Young-Jae;Yang, Dong-Hyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.6
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    • pp.91-102
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    • 2020
  • This study constructed production frontiers of inputs and outputs in a sequential manner, measured inefficiencies by applying a non-radial sequential weighted Russell directional distance function to these frontiers, and analyzed Luenberg productivity indices and the contribution of each of input and output factor based on these distances. The results are as follows. First, the productivity of banks increased due to technical changes after the global financial crisis. Second, productivity growth decreased between 2009 and 2014 due to technical changes after the recession, as previous studies have shown that technology progressed before the global financial crisis but then largely decreased or remained the same thereafter. After 2014, the productivity of banks improved. This result may be due to both technology improvement after 10 years of stagnation and reduction of inputs and non-performing loans. Third, the 3.6% annual of productivity growth for 10 years was comprised of 1.77% household loans, 0.67% corporate loans, 0.98% manpower, 1.18% non-performing loans, -0.5% total deposits, and -1.25% securities. Finally, this study has limitations since it could not control risks such as capital structure and interest volatility.