• Journal of Families and Better Life
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• v.33 no.5
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• pp.1-24
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• 2015

The purpose of this study was to investigate the effects of Engel coefficient, Angel coefficient and Schwabe index influencing Household head's life satisfaction. For this study, the data from the 8th analysis of the 2013 Korea Welfare Panel Survey conducted by Korea Institute for Health and Social Affairs were used. For the sample, 903 male Household heads with children under the age of 18, were selected. For statistical analysis, SPSS program (Ver. 21.0) was used. And for statistical methods, frequency and percentile, mean and standard deviation, Pearson's correlation, one way analysis of variance, Duncan's multiple range tests, multiple regression analysis were used. The findings are as follows. First, as a results of analyzing the food costs, education costs and housing costs depending on Income Quintile, the food costs and education costs in the 5th Income Quintile compared with other Income Quintile, were highest. Also, the highest housing cost was in the 2nd Income Quintile, while the least housing cost was in the 1st Income Quintile. Second, by analyzing the differences of Engel coefficient, Angel coefficient and Schwabe index according to Income Quintile, the results show that Engel coefficient and Schwabe index decreases as Income Quintile increases, and Angel coefficient increases as Income Quintile becomes higher. Third, the level of HH's life satisfaction according to Income Quintile, 1st Income Quintile, 2nd Income Quintile, 4th Income Quintile, 3rd Income Quintile, 5th Income Quintile in order, increased. Fourth, as the result of analyzing the influence of Variables related to household and demographics about Engel coefficient, Angel coefficient and Schwabe index, it was shown that the variables effecting Engel coefficient, Angel coefficient, and Schwabe index are age, occupations, Number of workers, House ownership, Income Quintile. Fifth, As a result of analyzing the Variables effecting life satisfaction, especially while Schwabe index is not that significant, Engel coefficient and Angel coefficient are shown to have a significant influence. Therefore, the influence of Food costs and education costs can be confirmed.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.392-404
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• 2019

The purpose of this study was to identify the impact of various income sources on income inequality of forestry households. Data from the Forestry Household Economy Survey from 2013-2016 were analyzed using the Gini coefficient decomposition method via income source. In particular, the income inequality analysis of forestry households was broken down into separate analyses based on group, i.e., the whole of forestry households and the five income quintile classes. The results of the analyses showed that income inequality of forestry households is primarily affected by forestry and nonforestry incomes and income quintile class. Moreover, income inequality of the highest income quintile class was largely affected by forestry income compared with other sources of income, whereas that of other income quintile classes was largely affected by nonforestry income. Therefore, in order to reduce income inequality in forestry households, it is necessary to increase the proportion of forestry income in the lower four quintile classes. Given that the income of the lowest quintile class is negative, it is necessary to devise ways to improve the proportion and quantity of forestry income. At the same time, as forestry income increases, a policy alternative is also required to improve inequality in forestry income.

• Human Ecology Research
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• v.56 no.6
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• pp.573-588
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• 2018

This study analyzed per capita consumption expenditure by the consumption quintile of Middle and Older Elderly Households and the variables that affected it. Sample of 2,983 households was collected from the 6th KLoSA in 2016. First, when comparing the HH's living expenses by the number of family members, two persons to a person ratio, more than six persons to a person ratio were 2.007 and 4.148, respectively. The ratio increased as the number of family member increased; however, the rate of ratio increase decreased. Second, the per capita living expenses for the first and fifth quintile were 5.11 million won and 16.93 million won at the per capita living expenses that applied the OECD's equivalence scale to the HH's living expenses. The per capita living expenses for the fifth quintile was 3.31 times higher than in the first quintile. Third, among the variables influencing per capita living expenses by the consumption quintile, the marital status was the significant for all consumption quintiles; however, HH's income, HH's total asset, HH's financial asset, pension, subjective perception of the economy class, home ownership, residence (metropolitan or small city), education (elementary school), participation groups were significant in some quintiles among all quintiles. Fourth, of the significant variables influencing per capita living expenses, the most influential variables were first quintile followed by second quintile, third quintile, fourth quintile, marital status, HH's income, home ownership, HH's total asset, participation groups, residence (metropolitan), subjective perception of the economy class, in order.

• The Korean Journal of Health Service Management
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• v.11 no.1
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• pp.117-130
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• 2017

Objectives : In this study, 3,107 patients were used to evaluate the impact based on raw data of 2014 and the health status and medical expenses income quintile was collected and data was analyzed. Methods : Analysis method was the average comparison, ANOVA, subjected to a multiple logistic regression analysis, the statistical test was the t-test and the scheffe post verification. Results : Gender(p<.000), age(p<.000), marital status(p<.000) educational status (p<.000), easement(p<.000), medication(p<.000), subjective health status(p<.005) were analyzed. First quintile identified that the highest amount was spent in the Chungcheong region, the 2nd quintile showed that the highest output was in the Gyeongsang region. The 3rd and 4th quintiles indicated that the highest expenditure was in the Seoul metropolitan region. The 5th quintile showed that the Chungcheong was the highest once again and the Jeolla region was the lowest in terms of expediture. Conclusions : Future medical research on income will require the government's Big Data collection to create the primary basis for policy making in order to improve the efficiency, effectiveness and equity of medicine spending.

• Human Ecology Research
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• v.57 no.1
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• pp.143-157
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• 2019

This study analyzed per capita expenditure (food expenses, housing expenses, health care costs, and cultural & entertainment expenses) by the consumption quintile for middle and older elderly households in addition to personal characteristics, household characteristics and economic factors affecting it. A sample collected from the 6th KLoSHA in 2016, was 2,983 households. First, among each per capita expenditure, the largest expenditure was food expenses, followed by housing expenses, health care costs and cultural & entertainment expenses. Compared with the first quintile of personal consumption expenditure, the largest increase in the fifth quintile was food expenses, followed by cultural & entertainment expenses, housing expenses, and health care costs. Second, compared to the fifth quintile of per capita food expenses, all other quintile had negative effects, and only the first quintile showed a negative effect compared to the fifth quintile of per capita housing expenses. The first, the second, and third quintile had a negative effect compared to the fifth quintile of per capita health care costs. Compared with the fifth quintile of per capita cultural & entertainment expenses, only the third quintile showed a negative effect. Third, in all quintile of per capita food expenses, the most influential variable from the first quintile to the third quintile was marital status, while in the fourth and fifth quintile included household income. In all quintile of per capita health care costs, health status was the most influential variable from the first quintile to the fourth quintile, and residence was in the fifth quintile.

• 한국사회정책
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• v.23 no.3
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• pp.17-47
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• 2016

This paper aims to analysis working-time of Korea focusing on "the difference and the distribution" by a stratum. Classifying working-time into four categories including marginal part-time, part-time work, standard-time work and long-time working, it compares the relative distribution by income quintile. The outcome is as following : 20% of low-ranking income quintile are (marginal) part-time working, 60% from income quintile 2 to 4 are in long-time working and 20% of top-ranking income quintile are in the standard-time working in overall. Working-time classes can be divided up into three: short time-low income of type 1, long time-medium income of type 2 and standard time-high income of type 3. Analysing working time type, the low wage-short time, medium wage-long time and high wage-standard time by the wage per month and low wage-very long time, medium wage-long time and high wage-standard time by the wage per hours are confirmed. Also, stratification of working-time has been intensified in terms of age, jobs and work status. Policy implication from this study is that the increase of minimum wage to the lowest income class and creation of employment by the reduction of working-time to the medium income class could be effective policies.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.145-158
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• 2017

Lately, rapid increase of household debt and economic change has affected cash flow of household, insolvent risk has increased by high repayment burden of the principal and interest. Previous researches was progressing various discussion, composed objective repayment burden index about household debt. But it was relatively insufficient about perception of consumer. This research compare and analysis determinants of subjective repayment burden in household debt by income quintile, using 2016 Household Financial Welfare Survey. The research result is follows. The income 1 and 2 quartile groups have the higher monthly rent and credit card loan and the housing preparation loan ratio, the higher burden on repayment of the principal and interest. The Income 3 and 4 quartile groups have the higher 60s or older and member of household and real estate mortgage loan, the higher burden on repayment of the principal and interest. The Income 5 quartile group has the higher loan ratio for debt repayment preparation, the higher burden on repayment of the principal and interest.

• Journal of Agricultural Extension & Community Development
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• v.30 no.4
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• pp.229-241
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• 2023

This study aims to examine the farm household income and consumption structure change as well as farm income inequality. Data from the Agricultural Household Survey for the years 2016, 2021, and 2022 were hired to analyze farm income inequality by the Gini coefficient decomposition method. Results show that from 2016 to 2021, all income quintiles exhibited an increasing trend, but in 2022, income decreased across all quintiles. As a result of analyzing farm household consumption expenditure, consumption expenditure increased in all income quintiles in 2021 and 2022 compared to 2016, but consumption of optional goods decreased in the fifth quintile. In addition, it was found that farmers in the first quartile had higher consumption expenditures and expenditures on options than those in the second quartile. The analysis of farm income by region show that public subsidies increased significantly for general rural farmers than for farmers in special and metropolitan areas in all income quintiles during the period. In the case of the first quintile, farm household income in rural areas in special and metropolitan cities increased compared to general rural areas. In the fifth quartile, agricultural income and sideline income in general rural areas increased compared to rural areas in special and metropolitan cities, while rural areas in special and metropolitan cities increased non-business income compared to rural areas. Results of farming income inequality by income type show a steady decline in inequality from 2016 to 2022, indicating that the decreasing gini coefficinet of public subsidies is contributing to the decline in farm income inequality. Private subsidies and side income are shown to increase inequality.

• Journal of Preventive Medicine and Public Health
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• v.54 no.5
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• pp.352-359
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• 2021

Objectives: The aim of this study was to examine the geographic distribution of diabetes mortality in Japan and identify socioeconomic factors affecting differences in municipality-specific diabetes mortality. Methods: Diabetes mortality data by year and municipality from 2013 to 2017 were extracted from Japanese Vital Statistics, and the socioeconomic characteristics of municipalities were obtained from government statistics. We calculated the standardized mortality ratio (SMR) of diabetes for each municipality using the empirical Bayes method and represented geographic differences in SMRs in a map of Japan. Multiple linear regression was conducted to identify the socioeconomic factors affecting differences in SMR. Statistically significant socioeconomic factors were further assessed by calculating the relative risk of mortality of quintiles of municipalities classified according to the degree of each socioeconomic factor using Poisson regression analysis. Results: The geographic distribution of diabetes mortality differed by gender. Of the municipality-specific socioeconomic factors, high rates of single-person households and unemployment and a high number of hospital beds were associated with a high SMR for men. High rates of fatherless households and blue-collar workers were associated with a high SMR for women, while high taxable income per-capita income and total population were associated with low SMR for women. Quintile analysis revealed a complex relationship between taxable income and mortality for women. The mortality risk of quintiles with the highest and lowest taxable per-capita income was significantly lower than that of the middle-income quintile. Conclusions: Socioeconomic factors of municipalities in Japan were found to affect geographic differences in diabetes mortality.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.31-39
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• 2015

This paper examines trends of the income inequality index and the income quintile share ratios, using the Household Survey released by Statistics Korea. We discuss their respective effects on total income inequality and the income disparity, as a contribution concept defined in this paper for 1990-2014 periods. Main findings are as follows. First, the contribution of 2-person families to total inequality with the current income or the disposable income becomes bigger, and growth rates have been above 10% since 2003. Second, the contribution of 1-person families to income inequality is greater than that of 2-person families. Policy implication is such that the government had better investigate the 1 or 2 person families in-depth to set up the policy measures for weakening the income inequality.