This study identified the rate of income poverty and multidimensional poverty, correlation between income poverty and multidimensional poverty, and adjusted multidimensional poverty rate. We also analyzed the factors that affected the number of poverty dimension and the probability of belonging to the poor or not in 3,159 elderly households including 474 poor households and 2,685 middle class households. First, in poor households, the employment poverty rate was the highest and the housing poverty rate was the lowest. In middle class households, the relation poverty rate was the highest and the employment poverty rate was the lowest. Second, in poor households, correlation between asset poverty and relation poverty had the highest coefficient of .205 and asset poverty and housing poverty had the lowest coefficient of .149. In middle class households, the correlation between income poverty and relation poverty had highest coefficient of -.290 and employment poverty and relation poverty had the lowest coefficient of .038. Third, in poor households, the number of average poverty dimension was 4.30, but the number of average poverty dimensions of middle class households was 2.310. Fourth, the variable affecting the number of poverty dimensions in poor households were gender, age, level of education, marital status; however, the significant variables were gender, education level, marital status, income poverty in the middle class households. The variable that affected the probability of belonging to the poor or not in poor households was age. However, the significant variables were gender, education level, marital status, residence, and income poverty in middle class households.
Journal of Family Resource Management and Policy Review
/
v.18
no.1
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pp.93-114
/
2014
This study aims to investigate the levels of assets and debts that male- and female-headed households have in comparison to married-couple households. Toward this end, a series of analyses of data from the 2011 Korean Household Finance Survey on the assets and debts of single-parent households are conducted. The empirical results reveal that the amounts of assets and net worth of married-couple households were significantly larger than those of male- and female-headed households. A comparison between male- and female-headed households show that the latter were more likely to hold financial assets such as savings accounts, savings insurance and mutual funds. The amounts of assets of female-headed households were significantly larger than those of male-headed households. Furthermore, the amount of credit card debt in mele-headed households was significantly larger than that in female-headed households.
This study compared one-child households' economic structures between those who determined not to have more children and those who have a birth plan. This study examined the demographic characteristics and economic variables such as income, consumption expenditures, assets. debt, and a subjective evaluation of future economic status. Especially, it compared the effects of socioeconomic variables on expenditures on a child between low-fertility and birth-planned households. From a questionnaire completed by a husband or wife of one-child households, 154 low-fertility households and 201 birth-planned households were obtained. A t-test, chi-square test, multiple regression analysis and a dummy variable interaction technique were used. The findings of this study are as follows: First, low-fertility households were older, had higher income, and had more educated, employed wives. Their marital duration was longer, and their child was older than those of birth-planned households. Second, low-fertility households had higher consumption expenditures than did birth-planned households. Especially, expenditures of apparel and shoes, health care, education, and entertainment were significantly higher for low-fertility households. Also, low-fertility households spent more than did birth-planned households on a child. However, low-fertility households had significantly more debt than did their counterparts, and their expectation level of future economic status were lower than that of birth-planned households. Third, the effects of socioeconomic variables on expenditures on a child were different between low-fertility and birth-planned households. Age, education level, husband's occupation, wife's employment status, income, net asset, and subjective evaluation of future economic status showed significant differences. Income elasticity of expenditure on a child was significantly higher for low-fertility households than their counterparts.
Journal of Family Resource Management and Policy Review
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v.18
no.4
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pp.27-52
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2014
This study aims to investigate the financial soundness of Korean households and its effects on the retirement preparation of these households. The sample consisted of 1,031 households selected from the 4th Korean Retirement and Income Study (KReIS) by the National Pension Research Institute in 2012. The empirical results are as follows. According to the logistic regression model, the statistically significant factors affecting the retirement preparation of Korean households are gender, occupation type, residence, satisfaction with economic condition, and type of financial soundness-sound households or insolvency-risky households. In other words, more female-headed households and households with higher levels of occupation are less likely to prepare for retirement. The households that are more likely to prepare for retirement are those that are lived in metropolitan areas as opposed to the countryside; further, households that are more economically sound are also more likely to prepare for retirement. In particular, sound households and insolvency-risky households are less likely to prepare for retirement compared to liquidity-risky households.
The objective of this thesis is to analyse empirically the economic resource problems of the rural poor households. Data from 444 rural sample households in four provinces, divided into two subgroups, the poor and the non-poor households, were analysed and compared. The owned arable land size, level of agricultural and non-agricultural income, assets, debts and the sufficiency of living expenses of the poor households were measured and compared with those of non-poor households respectively. The significant findings and drawn conclusions are as follows : The rural poor households 1. tends to show smaller family size, older age and lower level of education of homemakers than the non-poor households, that might work as constraints to income sources and quality. 2. has not only small arable lands and agricultural income but also even smaller cash income, less than 50% of total income, with 27% of self-product consumption and depends more on non-agricultural income than the non-poor households. Such weakness of income structure might cause and increase the income instability of the rural poor households. 3. reveals significantly different level and components of assets from the non-poor households lower level of assets, less amounts of but more load of debt due to lower solvency that comes from low level of income and assets, higher debts for consumption and lower accessibility to credit. All these socio-demographic and economic characteristics of the rural poor households might have compound effects on the economic problems of the poor households and make vicious circle of poor.
The purpose of this study was to compare the financial status between Aged Households and Non-aged households. The sample obtained from 1993 KHPS, consisted of 3,425 Korean married couples including 2,915 of non-aged households and 510 aged households. Statistics employed for the analysis were frequencies percentile and t-test And Lorenz curve and Gini coefficient were used to compare the financial status of two groups. The results of this study were as follows. First financial status of aged households specially annual total income annual current income earned income and annual total expenditure were lower than those of non-aged households. Second Gini-coefficients of aged households' income and expenditure were greater than expenditure of them. Moreover Gini-coefficients of aged households' total asset and total debt were greater than those of non-aged households' However total asset of aged and non-aged households were smaller than total debt of two groups.
The purpose of this study is to investigate the effects of wife's employment status on the household expenditures of timesaving market substitutes for houseworks. Seven expenditure categories were considered such as food away from home, convenient/prepared food, housing care service, clothing care service, childcare, supplemental education, and domestic services. The data were taken from 1999 Family Expenditure Survey by National Statistical Office. The sample consisted of 29,963 households with 33.2% dual-income households. The average monthly expenditure for food away from home was 127,795 won for dual-income households, while 103.100 won for single-income households. The expenditure for childcare of dual-income households was over six times of single-income households'. Dual-income households spent over ten times of single-income households for domestic services. For most expenditure categories, households with wife working at white-color jobs spent more than other dual-income households. After being other household characteristics to be constant, wife's occupation had found to be related with the household expenditures for most market substitutes. For the expenditures on both food away from home and childcare, employed-wife households with any kind of jobs were found to have higher possibility to spend and to be spent more than non-employed-wife households. The households with wife employed at white-color jobs spent more on clothing care service and domestic services than the households with the not working. Employed-wife households had higher possibility to spend on supplemental education, but they did not spend more on the expenditure, compared to nonemployed-wife households.
Recently, one-person households have surpassed nuclear families. One-person households are expected to have many problems with health due to an irregular life style and a tendency to be more isolated from society. In addition, we need to divide the generations and survey each generation due to differences in one-person household factors and characteristics as well as the unique physical conditions of each generation. Therefore, based on the sixth Korea National Health and Nutrition Examination Survey, this survey examined health behavior differences between one-person households and non-one-person households according to generation (respectively) as well as studied how one-person households and health behavior influence subjective health conditions. The major result of this survey is as follows. First, one-person households reveal a higher rate in the negative health behavior than non-one-person households. Second, the physical activity of all households reveals a high rate of non-activity. Third, health scores of one-person households are lower than that of non-one-person households; consequently, the analysis of health scores for one-person households and non-one-person households indicated that the middle age health scores for one-person households have been lowest in generations. Fourth, the factors that influence subjective health conditions indicated that one-person household and health behavior has meaningful influence; in addition, the subjective health condition of one-person households are lower than non-one-person households under controlled health behavior.
Objectives: This study was performed to compare the dietary life of single- and non single-person households in the Korea National Health and Nutrition Examination Survey (KNHANES). Methods: A nationally representative sample of 20,421 19-64-year-olds who had 24-hour recall data was taken from the 2014-2016 Korea National Health and Nutrition Examination Survey (KNHANES). Single- and non single-persons were compared for nutrient intake, dietary behaviors, food consumption patterns, nutrition education and confirm nutrition label. Results: The dietary intakes of dietary fiber and iron were lower in single-person households than in non single-person households. The lower the level of education and income, the lower the nutrient intake of single-person households. In the case of those aged 19 to 29, the breakfast skipping rate was higher in single-person households than in non single-person households. The higher the education level, the higher the breakfast skipping rate and the eating out frequency in the single-person households. In the food intake survey, the frequency of healthy food intake in single-person households was much lower than that of non single-person households. The confirmation rate of nutrition labeling was lower in single-person households than in non single-person households. Conclusions: This study shows that single-person households have poorer health-nutritional behaviors than multi-person households. Therefore, a nutrition education program based on the data of this study needs to be developed for health promotion of single-person households.
The purpose of this study was to investigate the determinants of households with risky debt loads. The study used financial ratios to determine which households were over-indebted. The 3 ratios used were Debt to Asset ratio, Debt to Financial asset ratio, and Debt Service ratio. Data for this study was the 2011 Survey of Household Finance. Households that demonstrated total debts of 70% or more when compared to total assets were 8.8%. Households that demonstrated a debt load totaling 5 or more times their total financial assets were 19%. Households with monthly repayment obligations of 40% or more of disposable income were 20%. Households that fulfilled all 3 financial ratio criteria were 1.5% of total indebted households. Over-indebted households demonstrated severe economic condition in terms of debt, but not all over-indebted households were categorized as being in economically vulnerable group. The major determinants of households with risky debts were income, asset, purpose of loans, and spending behavior of the households.
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