The life-cycle hypothesis states that a household can maximize its life-time utility through borrowing and debt financing which makes consumption smoothing possible.
When household debt surpasses a sustainable level, however, it increases interest repayment burden and worsens the financial position of a household. Still worse, it may increase the default risk, lead to insolvency of financial institutions, and cause adverse effects on the macro-economy.
Korea's household debt continues to increase in scale and speed, and its characteristics provoke a number of concerns. Household debt to income ratio in Korea is very high, compared with that of major OECD countries, and its growth rate also remains higher than that of income. This has been pointed out as the biggest potential risk factor for Korea's economy.
This paper examines the status and trends of Korean household debt and the determinants of insolvency risk using HDRI Index which simultaneously takes into account stock and flow aspects of debt. First, using data from Survey of Finances and Living Conditions we estimate factors that affect the insolvency risk index via a panel fixed effect model. The estimation results show that property income and savings reduce the risk of insolvency but income quintile 1-2 of default risk index increases the risk. And debt for business expenses, other debts repayments, medical expenses, and deposit for house increase the default risk. Looking at financial institution, debt from Mutual Aid Association and other borrowing increased default risk index but debt from non-banking finance, insurance company, workplace reduce default risk index. And if debtor's housing type was the apartments, default risk index is reduced but charter or rent with deposit, it is increased.
Second, panel logit analysis performed to identify determinants of default risk household shows the higher the business income ratio and the lower the income quintile and assets quintile, the greater the likelihood of default risk households. In terms of financial institution, debt from savings banks and Mutual Aid Association increases the likelihood of default risk households but debt from non-banking finance, insurance company, and workplace reduces the likelihood of default risk households. The purpose of debt turns out to be irrelevant to default risk. Apartments designed as housing reduce the probability of risky households.
Third, comparing the fiscal years 2013 and 2014, we make a distinction between two types of group. One is of households that kept good condition but were at risk of default in 2014. The other contains households with continued default risk that moved into good condition in 2014. The results of binomial logit analysis show that for each group, household financial risk increases when income quintile and assets quintile is low. And debt for real estate, education, business, living expenses, other debt payment, deposits for rent, and medical expenses, household increased financial risk. Business financing, loans for other debt repayments and low asset quintile decrease the probability of being in a good financial condition.
Finally, we conduct scenario analyses on various macroeconomic shocks that bring negative impacts on household debt. The results reveal that a fall in real estate prices has the greatest impact on household debt default risk, followed by declines in income and interest rate in order.