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Journal articles on the topic 'Coefficient Gini'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Gsteiger, Sandro, Nicola Low, Pam Sonnenberg, Catherine H. Mercer, and Christian L. Althaus. "Gini coefficients for measuring the distribution of sexually transmitted infections among individuals with different levels of sexual activity." PeerJ 8 (January 20, 2020): e8434. http://dx.doi.org/10.7717/peerj.8434.

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Objectives Gini coefficients have been used to describe the distribution of Chlamydia trachomatis (CT) infections among individuals with different levels of sexual activity. The objectives of this study were to investigate Gini coefficients for different sexually transmitted infections (STIs), and to determine how STI control interventions might affect the Gini coefficient over time. Methods We used population-based data for sexually experienced women from two British National Surveys of Sexual Attitudes and Lifestyles (Natsal-2: 1999–2001; Natsal-3: 2010–2012) to calculate Gini coefficients f

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2

Kanel, Nav Raj. "Gini Coefficient and Kandel's Reduction." Economic Journal of Nepal 18, no. 4 (1995): 173–85. http://dx.doi.org/10.3126/ejon.v18i4.71930.

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3

Hong, Minki. "Corrected Gini Coefficient in Korea." Korean Development Economics Association 23, no. 3 (2017): 1–22. http://dx.doi.org/10.20464/kdea.2017.23.3.1.

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4

Mukhopadhaya, Pundarik, and V. V. Bhanoji Rao. "The Gini Coefficient: A Note." Indian Economic Journal 48, no. 4 (2001): 65–67. http://dx.doi.org/10.1177/0019466220010408.

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5

Yazgan, Şekip. "Kamu yatırımları dağılımının gini katsayısı ile ölçülmesi: Türkiye üzerine bir uygulama (1999-2017)." International Journal of Economics, Politics, Humanities & Social Sciences 1, no. 1 (2017): 35–44. https://doi.org/10.5281/zenodo.2539195.

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In this study, the extent of unequal distribution of public investments among provinces in Turkey between the years of 1999 and 2017 is measured with Gini Coefficient. Empirical findings show that Gini Coefficient calculated for all public investments other than manufacturing industry showed a decrease in the said period. This result means that public investments were distributed relatively more equally among the provinces in 2017. According to decomposition results of Gini Coefficient conducted to reveal the amount of inequality in total public investments is originated from other public inve

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6

Dai, Pingsheng, and Sitong Shen. "Estimation of the Gini coefficient based on two quantiles." PLOS ONE 20, no. 2 (2025): e0318833. https://doi.org/10.1371/journal.pone.0318833.

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Based on the Palma proposition and the Lorenz fitting curve, this paper estimates the sample Gini coefficient using the income share of the top 10% and bottom 40% of the population. Empirical research shows that the absolute error between the estimated value and sample Gini coefficient is within a hundredth. Monte Carlo simulation shows that the new method has good performance and robustness for estimating Gini coefficients with different sample sizes and different inequality levels. Using the two quantiles in the deciles to estimate the sample Gini coefficient and the Lorenz fitting curve is

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7

Zhao, Xiaomeng, and Lin Liu. "Income Gap Equalization Based on PSO Algorithm in Edge Computing Environment." Journal of Environmental and Public Health 2022 (August 10, 2022): 1–12. http://dx.doi.org/10.1155/2022/8316982.

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In order to explore the current income gap, a method based on the PSO algorithm in the edge computing environment is proposed. PSO calculates and simulates bird flock foraging activities, the Frank Heppner biological group model, and the three rules in bird activities. After studying the activities of these natural creatures, abstract problems are quantified and similar models established. The Gini coefficient is calculated by using grouped data, and the grouping basis is also innovative. The quantile grouping method is adopted, which can effectively solve the difference between the concentrat

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8

Dixon, Philip M., Jacob Weiner, Thomas Mitchell-Olds, and Robert Woodley. "Bootstrapping the Gini Coefficient of Inequality." Ecology 68, no. 5 (1987): 1548–51. http://dx.doi.org/10.2307/1939238.

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9

Dixon, Philip, Jacob Weiner, Thomas Mitchell-Olds, and Robert Woodley. "Bootstraping the Gini Coefficient of Inequality." Ecology 69, no. 4 (1988): 1307. http://dx.doi.org/10.2307/1941290.

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10

Ryu, Hang K., Daniel J. Slottje, and Hyeok Y. Kwon. "A New Logit-Based Gini Coefficient." Entropy 21, no. 5 (2019): 488. http://dx.doi.org/10.3390/e21050488.

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The Gini coefficient is generally used to measure and summarize inequality over the entire income distribution function (IDF). Unfortunately, it is widely held that the Gini does not detect changes in the tails of the IDF particularly well. This paper introduces a new inequality measure that summarizes inequality well over the middle of the IDF and the tails simultaneously. We adopt an unconventional approach to measure inequality, as will be explained below, that better captures the level of inequality across the entire empirical distribution function, including in the extreme values at the t

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11

Lyu, Juncheng, Jie Zhang, and Dorian A. Lamis. "A Worldwide Study of the Relationship Between Gini Coefficients and Suicide Rates." International Journal of Environmental Research and Public Health 22, no. 7 (2025): 1110. https://doi.org/10.3390/ijerph22071110.

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Background: The Gini coefficient measures how much the distribution of income or consumption within an economy deviates from an equal distribution. However, there has been a paucity of research examining the association between Gini coefficients and suicide rates in the countries of the world. Objective: To prove the hypothesis that the higher the Gini coefficient, the larger the relative deprivation and the higher the suicide rate, and further to verify the effect of relative deprivation on suicidality. Methods: Suicide rates for different countries were obtained from the World Health Organiz

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12

Zeffora, Joylin, and Shobarani Shobarani. "Optimizing random forest classifier with Jenesis-index on an imbalanced dataset." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 1 (2022): 505–11. https://doi.org/10.11591/ijeecs.v26.i1.pp505-511.

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Random forest is an ensemble algorithm for machine learning. In decision trees, the splitting criteria is built on the prediction of the nodal points and formation of rules by Gini index and Information Gain. Gini index is a measure of inequality. Gini index does not take into consideration the structural changes in the dataset, and inaccurate data can distort the validity of the gini-coefficient. For data with the same feature but different outcomes, the gini-coefficient remained the same. The proposed method for attribute selection measure takes into consideration that there may be structura

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13

Santos, Carla Carla Maria Lopes da Silva Afonso dos, and Cristina Paula Silva Dias. "An assessment of the true Gini coefficient regarding the fulfilment of the basic criteria for inequality measures." Acta Scientiarum. Technology 46, no. 1 (2023): e64563. http://dx.doi.org/10.4025/actascitechnol.v46i1.64563.

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The Gini coefficient emerged more than a hundred years ago, but it is still the well-known and most used measure for assessing the degree of inequality in a distribution. Historically, the Gini coefficient has mainly been used to study income or wealth distributions, but, as highlighted by Gini himself, the coefficient's power to measure inequality extends to other contexts. In order to adapt it to the needs and points of view of those who use it, both in its classical and non-traditional applications, the Gini coefficient is frequently modified and extended, which resulted in a multitude of m

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14

j, j., and j. j. "A Study about Inequality in the Scholarly Publishing of Korean Research Institutions using the Gini Coefficient." Korean Data Analysis Society 25, no. 5 (2023): 1609–21. http://dx.doi.org/10.37727/jkdas.2023.25.5.1609.

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This study uses the Gini coefficient to examine the inequality in scholarly publishing for research institutions that have published articles in international journals in Korea for the past 20 years. The Gini coefficient was calculated using the number of papers and the cited-by counts, and the academic fields in which the Gini coefficient changed over time was identified. The result show that the inequality among Korean research institutions did not decrease compared to the 2000s, showing an inequality of g = 0.75-0.82. Broken down by academic fields, clinical medicine has the largest inequal

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15

Binay, Murat, and Ahmet Yalçın Yalçınkaya. "Gini Coefficient Analysis for Pensioners in Turkey." Global Journal of Business, Economics and Management: Current Issues 6, no. 2 (2016): 232–37. http://dx.doi.org/10.18844/gjbem.v6i2.1402.

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One of the main objectives of economic policy is to make the fair distribution of income. To provide fair distribution of income, how the revenue is shared must be based on certain criteria. Products and services are not shared in any society indiscriminately. There is a mechanisms governing the distribution of income in every society. Production factors increase the value created for themselves and how to divide this value is complex phenomenon which has technical, economic, social and political dimensions. There are a lot of criterias about how to divide the created value like change interva

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16

Wang, Lifeng, Jinwu Gao, Hamed Ahmadzade, and Zezhou Zou. "Partial Gini Coefficient for Uncertain Random Variables with Application to Portfolio Selection." Mathematics 11, no. 18 (2023): 3929. http://dx.doi.org/10.3390/math11183929.

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The partial Gini coefficient measures the strength of dispersion for uncertain random variables, while controlling for the effects of all random variables. Similarly to variance, the partial Gini coefficient plays an important role in uncertain random portfolio selection problems, as a risk measure to find the optimal proportions for securities. We first define the partial Gini coefficient as a risk measure in uncertain random environments. Then, we obtain a computational formula for computing the partial Gini coefficient of uncertain random variables. Moreover, we apply the partial Gini coeff

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17

Pavlov, Oleg I., and Olga Yu Pavlova. "Group averaging and the Gini deviation." RUDN Journal of Economics 29, no. 3 (2021): 595–605. http://dx.doi.org/10.22363/2313-2329-2021-29-3-595-605.

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It is known that partitioning a society into groups with subsequent averaging in each group decreases the Gini coefficient. The resulting Lorenz function is piecewise linear. This study deals with a natural question: by how much the Gini coefficient could decrease when passing to a piecewise linear Lorenz function? Obtained results are quite illustrative (since they are expressed in terms of the geometric parameters of the polygon Lorenz curve, such as the lengths of its segments and the angles between successive segments) upper bound estimates for the maximum possible change in the Gini coeff

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18

Pavlov, Oleg I., and Olga Yu Pavlova. "Group averaging and the Gini deviation." RUDN Journal of Economics 29, no. 3 (2021): 595–605. http://dx.doi.org/10.22363/2313-2329-2021-29-3-595-605.

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It is known that partitioning a society into groups with subsequent averaging in each group decreases the Gini coefficient. The resulting Lorenz function is piecewise linear. This study deals with a natural question: by how much the Gini coefficient could decrease when passing to a piecewise linear Lorenz function? Obtained results are quite illustrative (since they are expressed in terms of the geometric parameters of the polygon Lorenz curve, such as the lengths of its segments and the angles between successive segments) upper bound estimates for the maximum possible change in the Gini coeff

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19

Shang, Songpu, and Songhao Shang. "Estimating Gini Coefficient from Grouped Data Based on Shape-Preserving Cubic Hermite Interpolation of Lorenz Curve." Mathematics 9, no. 20 (2021): 2551. http://dx.doi.org/10.3390/math9202551.

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The Lorenz curve and Gini coefficient are widely used to describe inequalities in many fields, but accurate estimation of the Gini coefficient is still difficult for grouped data with fewer groups. We proposed a shape-preserving cubic Hermite interpolation method to approximate the Lorenz curve by maximizing or minimizing the strain energy or curvature variation energy of the interpolation curve, and a method to estimate the Gini coefficient directly from the coefficients of the interpolation curve. This interpolation method can preserve the essential requirements of the Lorenz curve, i.e., no

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20

Allen, Edward. "Relation Between Two Income Inequality Measures: The Gini coefficient and the Robin Hood Index." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 19 (March 8, 2022): 760–70. http://dx.doi.org/10.37394/23207.2022.19.67.

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The objective of this investigation is to study the relation between two common measures of income inequality, the Gini coefficient and the Robin Hood index. An approximate formula for the Robin Hood index in terms of the Gini coefficient is developed from 100,000 Lorenz curves that are randomly generated based on 100 twenty-parameter families of income distributions. The approximate formula is tested against Robin Hood indexes of commonly-used one-parameter Lorenz curves, income data of several countries, and reported results of Robin Hood indexes. The approximate formula is also tested again

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21

Shkolnikov, Vladimir, Evgueni Andreev, and Alexander Z. Begun. "Gini coefficient as a life table function." Demographic Research 8 (June 17, 2003): 305–58. http://dx.doi.org/10.4054/demres.2003.8.11.

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22

CHEN, CHAU-NAN, TIEN-WANG TSAUR, and TONG-SHIENG RHAI. "THE GINI COEFFICIENT AND NEGATIVE INCOME: REPLY." Oxford Economic Papers 37, no. 3 (1985): 527–28. http://dx.doi.org/10.1093/oxfordjournals.oep.a041708.

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23

Kanel, Nav Raj. "Lorenz Curve and Gini Coefficient: Conceptual Considerations." Economic Journal of Nepal 16, no. 4 (1993): 221–30. http://dx.doi.org/10.3126/ejon.v16i4.71678.

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24

Gerber, Leon. "A Quintile Rule for the Gini Coefficient." Mathematics Magazine 80, no. 2 (2007): 133–35. http://dx.doi.org/10.1080/0025570x.2007.11953468.

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25

Rey, Sergio J., and Richard J. Smith. "A spatial decomposition of the Gini coefficient." Letters in Spatial and Resource Sciences 6, no. 2 (2012): 55–70. http://dx.doi.org/10.1007/s12076-012-0086-z.

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26

Rycroft, Robert. "The Lorenz Curve and the Gini Coefficient." Journal of Economic Education 34, no. 3 (2003): 296. http://dx.doi.org/10.1080/00220480309595224.

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27

Chotikapanich, Duangkamon, and William Griffiths. "On Calculation of the Extended Gini Coefficient." Review of Income and Wealth 47, no. 4 (2001): 541–47. http://dx.doi.org/10.1111/1475-4991.00033.

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28

Lambert, Peter J. "Social welfare and the gini coefficient revisited." Mathematical Social Sciences 9, no. 1 (1985): 19–26. http://dx.doi.org/10.1016/0165-4896(85)90003-4.

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29

Sen, Pranab Kumar. "The harmonic Gini coefficient and affluence indexes." Mathematical Social Sciences 16, no. 1 (1988): 65–76. http://dx.doi.org/10.1016/0165-4896(88)90005-4.

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30

Barrett, C. R., and Maurice Salles. "On a generalisation of the Gini coefficient." Mathematical Social Sciences 30, no. 3 (1995): 235–44. http://dx.doi.org/10.1016/0165-4896(95)00787-3.

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31

Barrett, C. R., and M. Salles. "On a generalisation of the Gini coefficient." Mathematical Social Sciences 31, no. 1 (1996): 56. http://dx.doi.org/10.1016/0165-4896(96)88677-x.

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32

Luptáčik, Mikuláš, and Eduard Nežinský. "Measuring income inequalities beyond the Gini coefficient." Central European Journal of Operations Research 28, no. 2 (2019): 561–78. http://dx.doi.org/10.1007/s10100-019-00662-9.

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AbstractGrowing interest in the analysis of interrelationships between income distribution and economic growth has recently stimulated new theoretical and empirical research. Measures such as the head-count ratio for the poverty index or the widely used Gini coefficient are aggregated indicators describing the general extent of inequality without deeper insights into income distribution among households. To derive an indicator accounting for income distribution among income groups, we propose a new approach based on an output oriented DEA model where the input value is unitized to 1 for each c

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33

Przekota, Grzegorz. "Wybrane koncepcje pomiaru nierówności dochodowych." Nierówności społeczne a wzrost gospodarczy 66, no. 2 (2021): 16–32. http://dx.doi.org/10.15584/nsawg.2021.2.2.

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Determining the level of income inequality requires the adoption of a specific measurement methodology. The aim of the study was to review and discuss the methodologies used to measure income inequality. Four measures are presented, each based on different assumptions. These measures were the Gini coefficient, Theil coefficient, Kukuła coefficient and unevenness coefficient. The first three measures, and in particular the Gini coefficient, are commonly described in the literature, while the unevenness coefficient is the author’s proposal for measuring income inequality. The empirical material

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34

Wang, Ziang. "The Impact Factors of Gini Coefficient: Taking the US as an Example." Advances in Economics, Management and Political Sciences 59, no. 1 (2024): 208–15. http://dx.doi.org/10.54254/2754-1169/59/20231121.

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The study aims to explore multiple variables affecting the Gini coefficient in the United States, including economic expansion, governmental measures, urban development, quality of life, and global trade. The research methodology involves using publicly accessible data from the official online portal of the United Nations, covering a wide array of economic, societal, and regulatory parameters. Through regression analysis, the study delves into the relationship between variables such as GDP, urbanization, living standards, global trade, and net migration with the Gini coefficient. The purpose i

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35

Kumor, Paweł. "Przyzwyczajenie społeczne do rosnących dysproporcji płac." Wiadomości Statystyczne. The Polish Statistician 2010, no. 6 (2010): 12–24. http://dx.doi.org/10.59139/ws.2010.06.2.

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In the article a hypothesis is formulated concering the social habit to increasing disproportions of earnings. The hypothesis is verified based on the economic growth model using data from 1970 to 2007. Econometric studies were carried out in two stages. The first stage covered estimating the optimal Gini coefficients for short sub-periods being moved increasingly in time. The second stage covered researches on the character of changes of the optimal Gini coefficients. In the studies we proved the hypothesis on the habit of society to increasing disproportions of earnings. The optimal Gini coe

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36

Matsumoto, Kunichika, Kanako Seto, Shigeru Fujita, Takefumi Kitazawa, and Tomonori Hasegawa. "Population aging and physician maldistribution: A longitudinal study in Japan." Journal of Hospital Administration 5, no. 1 (2015): 29. http://dx.doi.org/10.5430/jha.v5n1p29.

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Background: Over the past two decades, population aging and the introduction of the new postgraduate medical education program in 2004 have impacted on the geographic maldistribution of physicians in Japan. The purpose of this study was to evaluate recent changes in physician distribution across municipalities from 1996 to 2012 using Gini coefficients and to clarify the impact of the new medical education program on physician distribution.Methods: We extracted the number of physicians classified by type of medical institution and municipal bodies. Gini coefficients were calculated using both p

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37

Sultanova, N., A. Tulegenova, and B. Suleimen. "USING THE GINI COEFFICIENT TO BUILD A CREDITSCORING MODEL." Suleyman Demirel University Bulletin Natural and Technical Sciences 55, no. 2 (2024): 5–10. https://doi.org/10.47344/sdubnts.v55i2.538.

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The credit scoring model is widely used to predict the likelihood of a customer default. To measure the quality of such scoring models, you can use quantitative indicators such as the GINI index, KolmogorovSmirnov (KS) statistics, Lift, Mahalanobis distance, information statistics. This article discusses and illustrates the practical use of the GINI index.

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38

Kumor, Paweł. "Czy w Polsce rośnie akceptacja społeczna dla nierówności płac?" Annales. Etyka w Życiu Gospodarczym 14, no. 1 (2011): 171–79. http://dx.doi.org/10.18778/1899-2226.14.1.15.

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In our studies we deal with estimating of the optimal ranges of earnings – the optimal of Gini indexes which are favourable to maximization of the GDP growth in Poland. We suspect that the optimal Gini coefficients expressing the acceptance of the whole of society for earnings inequalities can increase. In the article we formulated a hypothesis on the social habit to increasing disproportions of earnings. We verified the hypothesis on the basis of the model of the economic growth using data from 1970 to 2007. We carried out econometric studies in two stages. In the first stage we estimated the

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39

HU, HAI-BO, and LIN WANG. "THE GINI COEFFICIENT'S APPLICATION TO GENERAL COMPLEX NETWORKS." Advances in Complex Systems 08, no. 01 (2005): 159–67. http://dx.doi.org/10.1142/s0219525905000385.

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The Gini coefficient, which was originally used in microeconomics to describe income inequality, is introduced into the research of general complex networks as a metric on the heterogeneity of network structure. Some parameters such as degree exponent and degree-rank exponent were already defined in the case of scale-free networks also as a metric on the heterogeneity. In scale-free networks, the Gini coefficient is proved to be equivalent to the parameters mentioned above, and moreover, a classification of infinite scale-free networks is given according to the value of the Gini coefficient.

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40

Furman, Edward, and Ričardas Zitikis. "BEYOND THE PEARSON CORRELATION: HEAVY-TAILED RISKS, WEIGHTED GINI CORRELATIONS, AND A GINI-TYPE WEIGHTED INSURANCE PRICING MODEL." ASTIN Bulletin 47, no. 3 (2017): 919–42. http://dx.doi.org/10.1017/asb.2017.20.

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AbstractGini-type correlation coefficients have become increasingly important in a variety of research areas, including economics, insurance and finance, where modelling with heavy-tailed distributions is of pivotal importance. In such situations, naturally, the classical Pearson correlation coefficient is of little use. On the other hand, it has been observed that when light-tailed situations are of interest, and hence when both the Gini-type and Pearson correlation coefficients are well defined and finite, these coefficients are related and sometimes even coincide. In general, understanding

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41

Choi, Don-seung, Dong-Seok Oh, and Gwang-Heon Hong. "The Relationship between Trade Openness and Gini Coefficient." Journal of Korea Research Association of International Commerce 22, no. 1 (2022): 73–91. http://dx.doi.org/10.29331/jkraic.2022.2.22.1.73.

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42

Sandström, Arne, Jan H. Wretman, Bertil Waldén, Arne Sandstrom, and Bertil Walden. "Variance Estimators of the Gini Coefficient: Probability Sampling." Journal of Business & Economic Statistics 6, no. 1 (1988): 113. http://dx.doi.org/10.2307/1391424.

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43

Lambert, Peter J., and J. Richard Aronson. "Inequality Decomposition Analysis and the Gini Coefficient Revisited." Economic Journal 103, no. 420 (1993): 1221. http://dx.doi.org/10.2307/2234247.

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44

BERREBI, Z. M., and JACQUES SILBER. "THE GINI COEFFICIENT AND NEGATIVE INCOME: A COMMENT." Oxford Economic Papers 37, no. 3 (1985): 525–26. http://dx.doi.org/10.1093/oxfordjournals.oep.a041707.

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45

Sandström, Arne, Jan H. Wretman, and Bertil Walden. "Variance Estimators of the Gini Coefficient—Probability Sampling." Journal of Business & Economic Statistics 6, no. 1 (1988): 113–19. http://dx.doi.org/10.1080/07350015.1988.10509643.

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46

Sen, Pranab Kumar. "The Gini Coefficient and Poverty Indexes: Some Reconciliations." Journal of the American Statistical Association 81, no. 396 (1986): 1050–57. http://dx.doi.org/10.1080/01621459.1986.10478372.

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47

Fabrizi, Enrico, and Carlo Trivisano. "Small area estimation of the Gini concentration coefficient." Computational Statistics & Data Analysis 99 (July 2016): 223–34. http://dx.doi.org/10.1016/j.csda.2016.01.010.

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48

Rogerson, Peter A. "The Gini coefficient of inequality: a new interpretation." Letters in Spatial and Resource Sciences 6, no. 3 (2013): 109–20. http://dx.doi.org/10.1007/s12076-013-0091-x.

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49

Rodríguez, Juan Gabriel, and Rafael Salas. "The Gini coefficient: Majority voting and social welfare." Journal of Economic Theory 152 (July 2014): 214–23. http://dx.doi.org/10.1016/j.jet.2014.04.012.

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50

E., Appah, and Iweias S.S. "Taxes and Income Inequality in Nigeria: 1980 – 2020." African Journal of Economics and Sustainable Development 6, no. 1 (2023): 100–128. http://dx.doi.org/10.52589/ajesd-kknb1wp3.

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This study investigated the relationship between taxes and income inequality in Nigeria from 1980 to 2020. The specific objectives were to investigate the relationship between personal income tax and Gini coefficient, evaluate the relationship between company’s income tax and Gini coefficient, assess the relationship between petroleum profit tax and Gini coefficient, determine the relationship between capital gain tax and Gini coefficient, investigate the relationship between value added tax and Gini coefficient, evaluate the relationship between custom and excise duty and Gini coefficient fro

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