This study is intended to explore an income level necessart for the old-age by income Status. Firstly, it is verified whether there is significant difference between old-age and working age or not. Secondly, if their difference is found, it will be identified that it is determined by certain factors. Thirdly, it is brought out needful income level for the old-age living through analysing old-age consumption expenditure level over working age. The results in this research are as follows. Firstly, there is a significant difference between old-age and working age. Secondly, the major factors which generated difference between old-age and working age consumption expenditure are income, household size, and age. Thirdly, the income level necessary for oldage living is on average 61 %. By income status, it is 90-100% for low income status, 60-70% for middle income status, 50-60% for high income status.
Based on household characteristics, this study analyzes the sources of changes in income class. Using KLI panel data in 1998 and 2001, household equivalent income is calculated and households whose income class is changed are identified. Various household characteristics are examined to understand which characteristics are influential in income class changes. Empirical estimations are carried out by employing an ordered probit model. Region of residence, age of household head, education level of the head, the number of employed family members in 1998, and a change in the number of employed family members are shown to be statistically significant. Calculation of marginal probability based on the ordered probit estimation results show that the probability of upward movement in income class decreases as a household lives in rural areas, while the probability of upward movement increases as the household's head is better educated, the number of employed family members are higher and there is a higher increase in the number of employed family members. Age of the head has mixed results; while the probability of upward movement in income class decreases as the head gets older for the households in middle and high income classes, that probability increases as the head is in the range of the 40s and the 50s in low income class households.
The purpose of this study is to investigate the effect of private insurance revenues and household spending on household income inequality. To this end, we conducted a concentration index and concentration curve analysis for the income level of medical panel survey data in 2015. The main results are as follows. First, the household income concentration ratio is 0.3580, which means that income is concentrated in the high income group, and the degree of inequality is considerably large. Second, although the portion of the private insurance benefits was small on the high-income household, it helped to strengthen the benefits concentration on this group. Third, the low income group has a large self-pay medical expense. Finally, the index of the income excluding the burden of the total medical expenses in the household income was 0.3676, so that even accounting for medical expenses, the income was concentrated in the high income class. Therefore, private insurance benefits and medical expenses were all contributing factors to the inequality of household income, and this study provides the essential materials for research and policy planning which could lead to the convergence of different fields.
This paper examines the impact of the Basic Pension scheme in terms of poverty reduction and income distribution among elderly households by focusing on the differences in the household type. It compares the data before (2013) and after (2016, 2019) the introduction of Basic Pension by using Household Income and Expenditure Survey data. Empirical analyses indicate that, first, the overall income and the public income transfer of the elderly households increased during the period compared. Second, the poverty rate was considerably higher for the elderly living alone than for other household types. The government policy led to poverty-reduction for all types of elderly households, wherein the effect was most profound in the case of elderly living with spouse. Third, income distribution improved for all types of elderly households, though maximum margin was observed in the case of the elderly living alone. Fourth, according to the multivariate logit regression, the Basic Pension had a positive impact on reducing the risk of poverty (defined as below 40% of median income) among the elderly households.
This study is an empirical research to analyze how many private income transfers in Korea decrease poverty rate, to compare the effects of private income transfers' decreasing poverty rate with income classes. This study has utilised the Family Income and Expenditure Survey to estimate the poverty ratio in urban areas and Unemployment Household Survey which Korea Institute for Health and Social Affairs has investigated at 1998. Majour findins are these. First, Sizes of private transfers incomes are much than that of public transfers incomes. The rates in receiving private transfers income are ten times higher than that in receiving public transfers income among urban worker's household. The mean of private transfer income are about six times larger than that of public transfer income among urban worker's household. Second, the effects of private income transfers' reducing poverty rates are not large. After private transfers, urbarn workers' households are about 10 per cent away from its poverty line, and unemploy households are only 3 per cent away from its poverty line. Third, especially, private income transfers are hardly reducing poverty rates among extreme poverty class. After private transfers, urban workers' households which their incomes are within low 5%, are not away from its poverty line at all.
As the basic old-age pension system was enforced in 2008, the base for old-age income security was founded. However, due to the basic old-age pension played a minor role as assistant allowance, it did not reach to sufficient level to cover full income security system. It is estimated that the dependency on private transfer income among the elderly who are difficult to be economically independent is still high. Therefore the poverty rate of the elderly households, who are not economically active or who are not protected by old-age income security system, is more likely to be higher than that of non-elderly households. Based on the assumption that public transfer income system should become a central means of old-age life guarantee, this study examined the poverty mitigation effects among the elderly households by comparing the private transfer income and the public transfer income. For this purpose, we selected single-elderly-households who have been considered the most vulnerable to poverty. We used 2006- 2008 Household Income and Expenditure Survey dataset that contained single-elderly who were older than 65 years old. To understand the conditions of poverty among single-elderly-households and the degree of poverty-reducing effect originated from income transfer system, we compared the poverty rates of total households and the whole elderly households. Next, we analysed the poverty of the single-elderly-households by social demographic factors such as gender, age, and economic activity. Our major findings are as follows: First, the poverty rate of the whole elderly households were not reduced, even though the basic old-age pension and long-term care management system were enforced in 2008. Second, half of the elderly households including single-elderly-households belonged to the absolute poverty line. Relatively higher level of poverty among the single-elderly-households was found especially those who were female, unemployed, low-educated, older, and rural single-elderly-households. Third, the effect of the public transfer income on mitigating the single-elderly-households poverty showed a little progress. However, even greater poverty reducing effect was found by the private transfer income system. Fourth, in a group of the public transfer systems, the public assistance such as supporting living costs contributed more to reduce poverty of the elderly population than the public pension system did.
Journal of the Economic Geographical Society of Korea
/
v.17
no.3
/
pp.502-516
/
2014
This study has decomposed the Gini coefficient using Korean Labor & Income Panel Study data and empirically analyzed the impact of demographic characteristics and source-specific income of householder on the household income gap using panel analysis. The scope of areas were divided into 'nationwide,' 'metropolitan areas,' and 'non-metropolitan areas,' and the period before and after the global financial crisis was examined. The analysis findings are as follows. First, when the entire period was examined by income source using Gini decomposition with division of areas into 'nationwide,' 'metropolitan areas,' and 'non-metropolitan areas', the following results were revealed. The absolute and relative contribution level of property income to the gross income was the largest in the category of 'nationwide' and 'metropolitan areas,' while the contribution level of earned income was the largest in the category of 'non-metropolitan areas'. In addition, property income worsened the household income gap the most in the category of 'nationwide' and 'metropolitan areas.' Second, property income worsened the household income gap less after the financial crisis than before the crisis. It is probably because the price of real estate skyrocketed before the global financial crisis, worsening the household income gap, whereas the price drop after the crisis temporarily alleviated the gap. Third, a correlation analysis revealed that households with older householders whose education is high school graduation or below had relatively low gross income, and households with higher source-specific income, especially earned income, had relatively high gross income. Fourth, when the household income determinants were compared through panel analysis with division of areas into 'nationwide,' 'metropolitan areas,' and 'non-metropolitan areas,' the following results were obtained. While the impact of earned income, financial income, and other incomes was greater in non-metropolitan areas than in metropolitan areas, the impact of property income was greater in metropolitan areas than in non-metropolitan areas. To reduce the income gap, the government should impose higher taxes on the high-income class and provide tax benefits to the low-income class, with efforts to create a wide variety of jobs. In addition, since income inequality gets worse as the proportion of incomes generated through asset holdings becomes higher, the government should focus on stabilizing property prices while paying attention to the regional differentiation when carrying out related policies.
This study examined the effects of depression by household's economic factors with income levels using the wave 1, 2 of Korean Welfare Panel Study. As a result, changes in income satisfaction have significant effects on depression levels. In non-poor households, the income and comsumption expenditure have effects on depression levels. But poor households do not have any effects. Among the control variables, age, marital status, and education level are influential factors on the depression levels. Based on the results, the author was able to recognize the economic factors in household that influnce the depression levels. and The policy directios for household's economic support were discussed.
This study analyzed the factors associated with residential mobility based on the data from the 11th to the 19th wave of the Korean Labor & Income Panel Study (KLIPS). After grouping low-income households within the first to the fourth income bracket into households that exhibited no income bracket change and those with income bracket changes during the research period, this study examined the effects of the income situation of each group on residential mobility. According to the results of the analysis, in the group of households that showed no low-income bracket change, significant effects were found only in the age of the head of the household, housing cost, and rental deposit (Jeonse) and monthly rental of the household. In the group of households that showed low-income bracket changes, findings were generally in line with those of the whole household, where total income and the number of full-time employees in the household were the same as those of the whole household, indicating that it would be necessary to improve the employment stability of low-income households. Based on the findings of this study, housing inequality is intensifying within low-income households, and, thus, housing policies, based on continuing surveys, must be implemented to enhance income opportunities and stabilize the housing needs of low-income households.
The purpose of this analysis is to examine the effects of health expenditure on income inequality on household income after the financial crisis by using the household income survey form 1996 to 2016. The main results are as follows. First, after the financial crisis, the gross income inequality of households has been changing steadily, though there has been a slight change in each year. Second, high-income earners spend more on health care expenditure by income level. Therefore, unequal levels are maintained. Third, the Gini coefficient of income excluding health care expenditure was calculated. The results of the analysis are larger than the Gini coefficient of total income. Income inequality is intensified by the expenditure of health care expenditure of households. The inequality of household income due to health care expenditure has been increasing steadily since the financial crisis. Efforts such as strengthening the protection of health insurance have been continuously carried out for the purpose of reducing the burden of the national medical expenses. However, it does not contribute to resolving income inequality. In the future, it will be necessary to provide a more selective medical support system to reduce the medical expenditure of the low income class.
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