• Title/Summary/Keyword: 가계부실 위험지수

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The study on insolvency prediction for Korean households across income levels (소득계층별 한국 차입 가계의 부실화 가능성 연구)

  • Lee, Jong-hee
    • Journal of Family Resource Management and Policy Review
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    • v.22 no.1
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    • pp.63-78
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    • 2018
  • This study examined the insolvency of debtors using multiple-indicator approaches and compared the outcomes across income levels with the 2016 'Household Financial and Welfare Survey'. This study used (1) the total debt to total assets ratio (DTA), (2) the total debt service ratio (DSR), and (3) the Household Default Risk Index (HDRI) recently developed by the Bank of Korea. Households in the lowest income quintile were more likely to be insolvent than any other income group. Demographics, such as age and gender of the household head, and most of the financial variables significantly increased the likelihood of insolvency based on the DTA. The number of household members and job status increased the likelihood of insolvency based on the DSR. Also, age, gender of the household head, and most of the financial variables increased the likelihood of household insolvency based on the HDRI after controlling for other demographics and financial variables.

Studies on Insolvency Prediction for young Korean debtor (한국 청년가계의 부실화 가능성 연구)

  • Lee, Jonghee
    • Journal of Family Resource Management and Policy Review
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    • v.23 no.2
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    • pp.99-115
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    • 2019
  • This study examined the insolvency likelihood of young debtors from the 2018 Household Financial and Welfare Survey. This study used the Household Default Risk Index (HDRI), which considers the ratio of total debt to total assets (DTA), and a total debt service ratio (DSR) to examine the insolvency level of debtors. The descriptive analyses showed no difference in frequency of households with a high probability of insolvency between those less than 35 years of age and those over 35 years of age. However, the median HDRI value for those less than 35 years of age was higher than those over 35 years of age. The multivariate analyses indicated that educational expenses for young Korean debtors was a factor that increased their probability of insolvency, while income was the only variable that decreased their insolvency likelihood.

Predicting Default Risk among Young Adults with Random Forest Algorithm (랜덤포레스트 모델을 활용한 청년층 차입자의 채무 불이행 위험 연구)

  • Lee, Jonghee
    • Journal of Family Resource Management and Policy Review
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    • v.26 no.3
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    • pp.19-34
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    • 2022
  • There are growing concerns about debt insolvency among youth and low-income households. The deterioration in household debt quality among young people is due to a combination of sluggish employment, an increase in student loan burden and an increase in high-interest loans from the secondary financial sector. The purpose of this study was to explore the possibility of household debt default among young borrowers in Korea and to predict the factors affecting this possibility. This study utilized the 2021 Household Finance and Welfare Survey and used random forest algorithm to comprehensively analyze factors related to the possibility of default risk among young adults. This study presented the importance index and partial dependence charts of major determinants. This study found that the ratio of debt to assets(DTA), medical costs, household default risk index (HDRI), communication costs, and housing costs the focal independent variables.

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.