• Health Policy and Management
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• v.3 no.2
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• pp.81-99
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• 1993

The purpose of this research is to assess the geographical distribution of physicians and dentists and the degree of maldistribution of the physician. Data were obtained form the Korean Medical Association's report on physicians registry and census for 1990. To assess the degree of disparity in the rural-urban distribution of physician manpower and to identify changes in the distribution pattern, the Gini index of concentration was used. Major findings are as follows; 1. Urban-rural disparity in the distribution of physician manpower exists in all categories of manpower, i.e. physician, dentist, oriental medical doctor, general practitioner, medical specialist, practitioner, public health physician and public health dentist. Urban area which had 74.4% of nation's population, accounted for over 90% of all physician manpower. 2. In terms of the ration of physician manpower per 10, 000 population, in urban area, they were 8.2 physicians, 2.7 general practitioners, 5.5 specialists, 3.0 practitioners, 1.8 dentists and 1.3 oriental medical doctors. In rural area, the ratios were 1.4 physicians, 0.6 general practitioners, 0.9 specialists, 1.0 practitioners, 0.4 dentists and 0.4 oriental medical doctors. 3. Gini indicies computed to measure inequality of physician manpower distribution were 0. 3675 for physicians, 0.3372 for general practitioners, 0.3338 for specialists, 0.2263 for practitioners, 0.3132 for dentists and 0.3293 for oriental medical doctors. 4. Inspite of increase in the number of physician manpower, urban concentration of physician manpower intensified from 1980 to 1990. However, the Gini index for all physician manpower fell by 18.3~36.7% from 1980 to 1990, indicating more even distribution. 5. In rural area, the public health physicians and dentists had increased the ratios of physicians, general practitioners, practitioners and dentists per 10, 000 population remarkebly, and had decreased the Gini indicies of physicians, general practitioners, practitioners and dentists. Thus, public health physicians and dentists contributed to improve the distribution of physician manpower in rural area. Based on the results of this study, long-term and rational manpower policies should be developed to solve the problem of geographical maldistribution of physician manpower as well as short-term policy for inducing physicians to the rural areas.

• The Journal of Fisheries Business Administration
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• v.45 no.1
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• pp.17-31
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• 2014

This study examines trends in the overall income inequality of fishery household from 2003 to 2012 with the panel data of the Fishery Household Economy Survey. To investigate the potential determinants of income inequality, we decomposes the Gini coefficients into five income sources, fishery income, non-fishery income(non-fishery business income, non-business income), transfer income, irregular income and calculate the impact of each income sources on total income inequality. An evident trend toward increasing inequality of household income was found. Also, we find rising fishery income and non-fishery income play important role in the rapid increase of income inequality. Only transfer income appear to reduce total income inequality.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1557-1564
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• 2017

We take genomic sequences of high-dimensional low sample size (HDLSS) without ordering of response categories into account. When constructing an appropriate test statistics in this model, the classical multivariate analysis of variance (MANOVA) approach might not be useful owing to very large number of parameters and very small sample size. For these reasons, we present a pseudo marginal model based upon the Gini-Simpson index estimated via Bayesian approach. In view of small sample size, we consider the permutation distribution by every possible n! (equally likely) permutation of the joined sample observations across G groups of (sizes $n_1,{\ldots}n_G$). We simulate data and apply false discovery rate (FDR) and positive false discovery rate (pFDR) with associated proposed test statistics to the data. And we also analyze real SARS data and compute FDR and pFDR. FDR and pFDR procedure along with the associated test statistics for each gene control the FDR and pFDR respectively at any level ${\alpha}$ for the set of p-values by using the exact conditional permutation theory.

• Journal of Families and Better Life
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• v.14 no.3
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• pp.223-236
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• 1996

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.

• KIEAE Journal
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• v.17 no.2
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• pp.45-51
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• 2017

Purpose: Housing is the most essential element for well-being in a society. The government would continuously supply decent housings to make a better living condition for people. As various housing policies have been implemented into practice, the effectiveness of policies need to be assessed and improved to rearrange the financial resources. The indicators, such as quality of life, housing supply amount and etc, could be used to estimate housing policy to provide a guidance for a new policy direction. Though various indicators are utilized to assess the policy effect, most of the items are depend upon a relativeness in aspect to assessment goal, items, time and its weighting. Therefore, it needs an absolute indicator to compare the policy effectiveness regardless of time elapse or items. In this paper, it developed the housing welfare indicator to assess the level of living condition, utilizing the Gini coefficient which is used for explanation on income distribution. Method: To suggest an inequity indicator, this paper used Gini coefficient to explain the level of living condition which is used on economics to provide the level of income distribution. Data are collected through the Korea Housing Survey by Ministry of Land, Infrastructure and Transport between 2006 and 2014. Indicators of living condition focused on the development of the estimation model using the frequency of room use. Result: Gini coefficient between 2004 and 2014 is about 1.5 score except in year 2013, and the trend of score has been decreased slowly which means the inequality gradually improved. In this result, it implies the living condition and distribution level would be improved than before.

• Health Policy and Management
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• v.12 no.1
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• pp.84-101
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• 2002

This study collected and analyzed the datum related to consultation fee in National Health Insurance Corporation and characteristics of dental clinics for 819 dental clinics in Daegu and Kyungpook districts to specify the distribution and concentration rate of health insurance consultation fee and the critical elements of insurance consultation fee income. The average health insurance consultation fee per one dental clinics is 77.2 million won and the case of women dentists is 78.7 million won. That is higher than 79.9 million won that the case of man dentist. According to age, under 39 is 85.5 million won that is highest, declining little by little above 60s the number decreased to merely 23.9 million won. And the dentists whose business years from 5 to 10 are the highest and declining gradually. The more of engaging members to dental clinics is the larger the income. The average insurance consultation fee of Daegu province is 69.3 million won, but that of Kyungpook is 89.6 million won. Decile distribution ratio of dental clinics consultation fee income is 0.526 and Gini coefficient is 0.303. Decile distribution ratio of Daegu district is 0.489, Gini coefficient is 0.320. This explain the larger inequality compared with Kyungpook(0.623, 0.273). With age, Gini coefficient of below 39 is 0.260, the higher age is, the larger the number is, up to abode 60 the coefficient is 0.504, the degree of inequality is most extremely. insurance consultation fee and the number of cases of consultation is related to the age of dentists, duration of practice, the number of dentists and staffs engaging and provinces. That is, the lesser the age is, the longer the years of engaging are, the more the number of dentists and staffs we, the larger insurance consultation fee income and the number of cases of consultations we. And the fee fur one case is closely related to age and provinces. The fee for one case is higher in lower age, and that of in Daegu dental clinics is higher than in Kyungpook.

• Journal of Korean Society of Forest Science
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• v.109 no.1
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• pp.99-108
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• 2020

Although the relationship between income and income inequality has previously been discussed, the present study applies a dynamic approach to analyze the specific relationship between forest household income and income inequality. For this analysis, a unit root test and a cointegration test were conducted to characterize the nature of income time-series data. After converting unstable time-series data into stable time-series data, a VAR model was estimated. Based on this model, an impulse-response was generated and variance-decomposition analysis was performed. These analyses showed that the effect of forest household income was relatively larger than that of the Gini coefficient, and that the impact of forest household income not only caused income to increase but also caused the Gini coefficient to decrease. In addition, the impact of the Gini coefficient had an impact on reducing forest household income and further increasing income inequality. We conclude that, with the aim of alleviating the inequality of forest household income, an income growth policy would be more effective than an income distribution policy.

• Journal of the Korean Home Economics Association
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• v.37 no.2
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• pp.127-144
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• 1999

The purposes of this study were to identify the housing maintenance cost, imputed rent fee and total housing cost of households living in rental house, to analyze the factors related to their housing maintenance cost, imputed rent fee and total housing cost and to investigate the factors contributing to total housing cost to total household income ratio. The data used for these purposes, was 97 KHPS of Daewoo Economic Research Institute. Sample size of households living in rental house, was 663. Statistics performed for the analysis were frequencies, percentiles, t-test, Lorenz cutie and Gini coefficient, Tobit analysis, OLS and Logistic analysis. The results of this study were as fellows: First, monthly cost of monthly rent & maintenance and repairs of households living in rental house with a deposit was lower than rental house, while the imputed rent fee of households living rental house with a deposit was higher than monthly rent households'And, total housing cost of households living in rental house with a deposit was higher than monthly rent households'. Second, Gini coefficient of the housing maintenance cost was 0.440, Gini coefficient of imputed rent fee was 0.362, and Gini coefficient of total housing cost was 0.291. Third, the variables related to their housing maintenance cost were family type, total household expenditure of socio-demographic characteristics and residence, type of rent, housing type of housing environmental factor. Also, the variables contributing to imputed rent fee were job type and educational attainment of household hearts, the number of family members, total household expenditure, residence, type of rent, housing type and tole number of rooms. In addition, the variables associated with total housing cost were job type and educational attainment of household head, total household income and residence, type of rent, housing type and the number of room. Finally, age, job type, educational attainment of household head, wife's employment status, the number of family members, family type, total household expenditure, residence, rent type of rent, housing type, the size of living space, and the number of room were significant variables contributing to total household cost to total household income ratio.

• Land and Housing Review
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• v.11 no.3
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• pp.11-19
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• 2020

This study aims to examine the relationship between the improvement of the income distribution index from the late 1980s to the 1990s and large-scale housing supply projects such as the 2 million housing construction project. Looking at Korea's economic development in terms of income growth and distribution, GDP has continuously increased since the establishment of the government, especially in the late 1980s. The Gini Index, a representative income inequality index, rapidly deteriorated in the early 1970s, and gradually improved from the late 1980s. The 2 million housing construction project, announced in 1988, supplied a third of the existing nationwide housing stock of 6.5 million units in three years. The project cost was 65 trillion won, equivalent to 50% of Korea's GDP at the time. This study questioned whether the ratio of the number of employed workers in the construction industry was a variable directly affecting the Gini Index. To verify this, the causal relationship between the proportion of employed workers in the construction and manufacturing industries and the Gini Index from 1979 to 2008 was statistically analyzed. For this, the ARIMA model was established for each variable, and the correlation of their residuals was verified. The 2 million housing construction project had the effect of improving income inequality in terms of rising wages for production workers and creating jobs for the low-educated and low-income class. During the project period, the number of middle-income earners increased sharply, and the income gap between the high-income and low-income earners greatly decreased. The expansion of the construction volume can be used as a powerful and direct policy tool for improving income distribution. However, the effect may be limited. When the proportion of workers exceeds the threshold, the effect is weakened.

• Journal of Korea Port Economic Association
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• v.20 no.1
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• pp.1-20
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• 2004

The purpose of this paper is to analyze the degree of cargo concentration at Korean ports using Theil's Entropy and to compare the results with those of Gini coefficient, Hoyle(1983), and Hirshmann-Herfindahl models. The entropy indices were compared with other models after measuring the cargo concentration for the period of 1981-2000 among the 18 Korean ports. The core results of empirical analysis are as follows: first, the empirical results of entropy indices show the following trends: all the ports(concentration except 1996's slight deconcentration), ports in Western area(deconcentration in 1990s and slight concentration in 2000), ports in Southern area(deconcentration in 1980s and 1990s except concentration in 2000), and ports in Eastern area(continuous trends of concentration). However, competition power will be decreased if concentration is increased, because of the character of entropy index. The empirical results of 4 indices except Hoyle model show the comparatively same directions in terms of trends. This study found out the similar results among the following models: All the ports(entropy index & Gini coefficient & H-H model), ports in Western area(Entropy index &Hoyle model), ports in Southern area(Entropy index & Gini coefficient), and ports in Eastern area(Entropy index & H-H index).The policy planner of Korean ports should find out the determination factors of concentration and deconcentration of each ports and decide the investment priority, size and scope for balancing the development of regional ports.