• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.291-297
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• 1996

In this paper, we propose the jackknife estimator and the bootstrap estimator of Gini index of the two-parameter exponential distribution when the location parameter $\theta$ is unknown and the scale parameter $\sigma$is known. Sinilarly, we propose the bias location parameter $\theta$ and the scale parameter $\sigma$ are unknown. The bootstrap estimator is more efficient than the other estimators when the location parameter $\theta$is unknown and the scale parameter $\sigma$ is known, and the bias corrected estimator is more efficient than the MLE when both the location parameter $\theta$ and the scale parameter $\sigma$are unknown.

• KDI Journal of Economic Policy
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• v.29 no.3
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• pp.1-28
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• 2007

Upon analyzing several Korean Income data sets, it is confirmed that the relationship between Gini coefficient and bi-polarization measure (EGR) is empirically not different although they each come from different theoretical basis. Furthermore, it is difficult to state that the degree of polarization of income distribution, measured by DER, in Korea has deepened more than that of income inequality, estimated by Gini coefficient, in the periods of before and after the economic crisis.

• Journal of Smart Tourism
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• v.2 no.3
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• pp.17-30
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• 2022

The tourism sector of the Maldives has seen rapid growth since its inception in 1972. One significant development is the transformation of the market composition in recent years. China has surpassed traditional European markets as the single largest source market. In this regard, this study seeks to assess the seasonality in the Maldivian tourism sector using a monthly dataset of visitor arrivals from 2003 to 2019. The seasonality ratio, the seasonality indicator, the Gini coefficient and the seasonal index were used to examine the seasonality patterns. The results of this study show that there are three distinct peaks (January to April, August, and November to December) and two off-peaks (May to July and September) periods. The findings also reveal that the rise of the Chinese market has significantly lessened the seasonality of Maldivian inbound tourism. Finally, some important implications are discussed.

• Journal of the Korean Regional Science Association
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• v.33 no.4
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• pp.3-17
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• 2017

This study ranks by developing an urban competitiveness index of major global cities, including seven cities in Korea using data from the Global Cities Forecast (2013) provided by Oxford Economics. The City competitiveness index is selected from 18 indicators including scale index, ratio index, growth rate index while Gini coefficient is used for distribution index. In order to analyze the relationship between the competitiveness index and the distribution index, we use the LOGIT panel regression model. As a result, the increase in income inequality (Gini coefficient) has a negative effect on the economic growth rate in 5-year time lag shown statistically significant. We have compiled global rankings of 770 city competitiveness based upon 19 indicators by combining the global competitiveness index and the distribution index. The trend of rank shows that 7 Metropolitan Korean Cities are expected to decline substantially over the period. In particular, Seoul ranked $59^{th}$ in 2010 and $74^{th}$ in 2015. Its ranking is expected to be decline to $185^{th}$ in 2030. The declining competitiveness of Korean cities is expected to lead to a weakening of Korea's national competitiveness in the long run. Accordingly, it is imperative to identify problems and seek strategic plans to secure global urban competitiveness.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.4
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• pp.29-47
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• 2020

This study uses Gini coefficient to index the inequality of academic information resource among universities to identify the areas where the gap is extremely severe, and analyzes the Gini coefficient over time for 10 years to show how the gap is changing. In addition, the degree and characteristics of the gap appearing by type of universities such as metropolitan universities, local national universities, private universities, and colleges were also compared. As a result, first, the university library academic information infrastructure showed a severe level of disparity (0.6 - 0.9), and the inequality was more severe in serials, electronic resources, and reference service. Even when the relative Gini coefficient was calculated considering the number of students, the inequality was over 0.4 in serial etc. Second, the Gini coefficient trend over the last decade shows that the inequality has decreased toward equality in the re-education time of employees and electronic information resources, but not in other sectors. Third, it was found that special universities and universities in the metropolitan area showed a large gap between universities of the same kind, and local national universities showed the best gap level as well as the best academic information infrastructure.

• Journal of Distribution Science
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• v.16 no.5
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• pp.45-59
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• 2018

Purpose - This paper aims to analyze the distinct pattern of clustering of imported automobile distributors and provide evidence for the phenomenon using Korean data. Research design, data, and methodology - In this paper, we use data from Korea Automobile Importers & Distributors Association of 23 foreign automobile brands to evaluate the degree of concentration of showrooms using locational Gini index. We identify possible causes for the high level of clustering from two perspectives; 1) on the distributors' side and 2) on the customers' side. Results - We find a very strong locational concentration of imported automobile showrooms within close vicinity in the major cities and districts in Korea. Locational Gini coefficients are 0.1024 at the national level, 0.1836~0.3763 at city level, and 0.3941~0.4311 at district level on a [0,0.5] scale. Conclusions - Luxury foreign automobile customers tend to shop extensively around multiple brands prior to their ideal model selection. Accordingly, the imported automobile distributors cluster together close to their direct competitors in order to give a good comparison opportunity for the potential customers. This will maximize the probability of the visits of potential customers and lead to successful sales performance.

• The Journal of Fisheries Business Administration
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• v.39 no.3
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• pp.25-47
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• 2008

The Fishing Communities (so-called Uchongae) in Korea was legally established in 1962. It has been gradually expanded by quantity, and we have total 1,969 communities in 2006. The major establishment purpose of Uchongae was put 2 functions. The first function is to make up the double industry structure in coastal region, and second function is to make economical condition for Uchongae. Nevertheless the Fishing Communities System in Korea was not successfully developed after first beginning. The Income gap have become heavily between fishing area and non - fishing area, including agricultural area. The income gap has been due to rapid industrialization and urbanization in Korea. And the income gap even have become heavily among Uchongaes. In this paper, It have been researched the degree of Income inequality among Uchongaes in Korea during 1986-2006. The income inequality degree was analyzed by Gini coefficient and Mean Log Deviation (MLD) using Lorenz Curve. According to analysis result, the Gini coefficient of Uchongaes in Korea has been about 2-times high from 0.0847 to 0.1770 during 20 years. And the MLD has been 5.4 times from 0.0125 to 0.0679 during same periods. This means to more wide the general Income Inequality among the Uchongaes in Korea. Especially, It means to more wide the gap of high ranking Uchongaes and low ranking Uchongaes that MLD index multiplier has been more high.

• Korea journal of population studies
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• v.26 no.2
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• pp.33-62
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• 2003

The purpose of this study is to analyze the relative importance of three factor -socioeconomic development, public health development, egalitarian nature of socioeconomic development- affecting mortality declines. Infant mortality rate and life expectancy at birth are used as the mortality index, that is the dependent variables, while GNP is used as the indicator of socioeconomic development, primary school enrollment ratio of female as the indicator of egalitarian nature of socioeconomic development, population per hospital bed as the indicator of public health. The data of these variables are collected two time-periods -before 1970 and during 1970-1980- over 50 countries. The explanatory data analysis is used as the statistical technique. We can find whether the relationship between dependent variable and independent variables are linear or nonlinear, and which case is the influential case in our model. The main results of this study are followings. First, the association between infant mortality rates and four indices are not linear. The most important factor explaining the variation of infant mortality is GNP, while primary enrollment of female is the second and GINI is the third important factor. However, population per hospital bed does not have a significant effect on the infant mortality rates in this study. Second, life expectancy at birth is log-linearly related to GNP. Unlike infant mortality rates, the most important factor explaining the variation of life expectance at birth is women's education and the next important factor GNP, and then the third one GINI. But, still population per hospital bed is not significantly related to the variation of life expectance in this study.

• Journal of Preventive Medicine and Public Health
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• v.55 no.4
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• pp.379-388
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• 2022

Objectives: Throughout history, societies have been impacted by inequality. Many studies have been conducted on the topic more broadly, but only a few have investigated inequalities in out-of-pocket health payments (OHP). This study measures OHP inequality trends among the Iranian households. Methods: This study used data from the Iranian Statistics Center on Iranian household income and expenditures. The analysis included a total of 995 300 households during the 36 years from 1984 to 2019. The Gini coefficient, Atkinson index, and Theil index were calculated for Iranian OHP. Results: Average Iranian household OHP increased from 33 US dollar (USD) in 1984 to 47 USD in 2019. During this 36-year span, the average±standard deviation Gini coefficient for OHP was 0.73±0.04, and the Atkinson and Theil indexes were 0.68±0.05 and 1.14±0.29, respectively. The Gini coefficients for the subcategories of OHP of outpatient diagnostic services, medical assistant accessories, hospital inpatient services, and addiction cessation were 0.70, 0.61, 0.84, and 0.64, respectively. Conclusions: In this study, we scrutinized trends of inequality in the OHP of Iranian households. Inequality in OHP decreased slightly over the past four decades. An analysis of trends among different subgroups revealed that affluent households, such as households with insurance coverage and households in higher income deciles, experienced higher inequality. Therefore, lower inequality in health care expenditures may be related to restricted access to health care services in Iran.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.497-508
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• 2017

This study conducted to examine about the income inequality and bi-polarization for forestry household. For this purpose, Gini coefficient and Atkinson index were used to analyze the income inequality for forestry household. Also, DER index were employed to show their income bi-polarization. Before using these methodologies, forestry household income was divided into three parts that was forestry income, non forestry business income and transfer income. And then, income inequality and bi-polarization were analyzed respectively. The result shows that forestry household income inequality was higher than whole household inequality. Apart from transfer income, forestry household income, forestry income and non forestry business income inequality was aggravated. At the same time, these tendency was able to observe the bi-polarization for forestry household income and other income sources.