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Journal articles on the topic 'Gini coefficiency'

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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

Everett, Theodore J., and Bruce M. Everett. "Justice and Gini coefficients." Politics, Philosophy & Economics 14, no. 2 (2014): 187–208. http://dx.doi.org/10.1177/1470594x14528653.

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3

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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4

Ghosh, Sucharita. "Computation of Spatial Gini Coefficients." Communications in Statistics - Theory and Methods 44, no. 22 (2015): 4709–20. http://dx.doi.org/10.1080/03610926.2013.823211.

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5

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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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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7

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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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

Matsumoto, Kunichika, Kanako Seto, Eijiro Hayata, et al. "The geographical maldistribution of obstetricians and gynecologists in Japan." PLOS ONE 16, no. 1 (2021): e0245385. http://dx.doi.org/10.1371/journal.pone.0245385.

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Background In Japan, there is a large geographical maldistribution of obstetricians/gynecologists, with a high proportion of females. This study seeks to clarify how the increase in the proportion of female physicians affects the geographical maldistribution of obstetrics/gynecologists. Methods Governmental data of the Survey of Physicians, Dentists and Pharmacists between 1996 and 2016 were used. The Gini coefficient was used to measure the geographical maldistribution. We divided obstetricians/gynecologists into four groups based on age and gender: males under 40 years, females under 40 year
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11

Abuabara, Alexander, Allan Abuabara, and Carin Albino Luçolli Tonchuk. "Comparative analysis of death by suicide in Brazil and in the United States: descriptive, cross-sectional time series study." Sao Paulo Medical Journal 135, no. 2 (2017): 150–56. http://dx.doi.org/10.1590/1516-3180.2016.0207091216.

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ABSTRACT CONTEXT AND OBJECTIVE: The World Health Organization recognizes suicide as a public health priority. Increased knowledge of suicide risk factors is needed in order to be able to adopt effective prevention strategies. The aim of this study was to analyze and compare the association between the Gini coefficient (which is used to measure inequality) and suicide death rates over a 14-year period (2000-2013) in Brazil and in the United States (US). The hypothesis put forward was that reduction of income inequality is accompanied by reduction of suicide rates. DESIGN AND SETTING: Descriptiv
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12

Sudo, Akira, and Yoshiki Kuroda. "The Impact of Centralization of Obstetric Care Resources in Japan on the Perinatal Mortality Rate." ISRN Obstetrics and Gynecology 2013 (September 18, 2013): 1–5. http://dx.doi.org/10.1155/2013/709616.

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Objective. We investigated the effects of the centralization of obstetricians and obstetric care facilities on the perinatal mortality rate in Japan. Methods. We used the Gini coefficient as an index to represent the centralization of obstetricians and obstetric care facilities. The Gini coefficients were calculated for the number of obstetricians and obstetric care facilities of 47 prefectures using secondary medical care zones as units. To measure the effects of the centralization of obstetricians and obstetric care facilities on the outcomes (perinatal mortality rates), we performed multipl
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13

Kumor, Paweł. "Is there a growing social acceptance of earnings inequalities in Poland?" Annales. Etyka w Życiu Gospodarczym 21, no. 8 (2018): 79–88. http://dx.doi.org/10.18778/1899-2226.21.8.07.

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In our studies, we deal with the estimating of the optimal ranges of earnings – the optimal Gini indexes which are favourable to the maximisation of GDP growth in Poland. We suspect that the optimal Gini coefficients expressing the whole of society’s acceptance of earnings inequalities can increase. In the article, we formulated a hypothesis on society’s habituation to increasing earnings disparities. We verified the hypothesis on the basis of the model of economic growth using data from 1970 to 2007. We carried out econometric studies in two stages. In the first stage, we estimated the optima
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14

Öztürk, Latif, and Nimet Varlık. "Examination of Consumption Expenditure Distribution among NUTS-2 Regions in 2007-2018 with GINI Coefficient." EMAJ: Emerging Markets Journal 11, no. 1 (2021): 86–94. http://dx.doi.org/10.5195/emaj.2021.223.

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In this study, the distribution of 12 main expenditure categories included in the consumer price index (CPI) among NUTS-2 (Nomenclature of Territorial Units for Statistics-2) regions is examined. The study covers the years 2007-2018. In the study, interregional consumption expenditure rates are identified with the Gini coefficient, which is a measure of inequality and the obtained consumption expenditure rates through the years are interpreted. The coefficients calculated for each expenditure category are important in terms of revealing the course of consumption behavior of households in Turke
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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

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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17

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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18

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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19

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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20

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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21

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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22

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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23

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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24

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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25

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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26

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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27

Hay, M. J. M., V. J. Thomas, and J. L. Brock. "Frequency distribution of shoot weight of plants in populations ofTrifolium repenspersisting by clonal growth in grazed pastures." Journal of Agricultural Science 115, no. 1 (1990): 41–47. http://dx.doi.org/10.1017/s0021859600073895.

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SUMMARYOver two years (1984/85 and 1986/87), monthly sampling of shoots of white clover plants compared the populations of white clover in mixed swards at Palmerston North, New Zealand, under set stocking, rotational grazing and a combination of both systems, at a common stocking rate of 22·5 ewe equivalents/ha.The frequency distributions of shoot (or stolon) dry weight per plant in each population over the study period was described by a log-normal model, which indicated that the populations consisted of many small individuals and few large individuals. Such inequality of shoot dry weight wit
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28

Zhou, Qingfeng, Xianqiang Wu, Xian Zhang, and Yan Song. "Investigating the Spatiotemporal Disparity and Influencing Factors of Urban Construction Land Utilization Efficiency: Empirical Evidence from Panel Data of China." Advances in Civil Engineering 2021 (January 23, 2021): 1–17. http://dx.doi.org/10.1155/2021/1613978.

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This paper corrected the long-term misunderstanding of the land utilization efficiency concept. The Undesirable-Window-DEA model, Dagum Gini coefficient, and spatial panel autoregressive model with fixed effect were used to explore the spatial heterogeneity and influencing factors of urban construction land utilization efficiency in China from 2004 to 2016. The results show the following: (1) China’s overall utilization of urban construction land is still at a low level. It decreased first and then rose, with a “flat V-shaped” evolution pattern. (2) During the study period, the Gini coefficien
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29

Loffredo, Filomena, Antonio Scala, Guido Maria Adinolfi, Federica Savino, and Maria Quarto. "A new geostatistical tool for the analysis of the geographical variability of the indoor radon activity." Nukleonika 65, no. 2 (2020): 99–104. http://dx.doi.org/10.2478/nuka-2020-0015.

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AbstractThe population is continuously exposed to a background level of ionizing radiation due to the natural radioactivity and, in particular, with radon (222Rn). Radon gas has been classified as the second leading cause of lung cancer after tobacco smoke [1]. In the confined environment, radon concentration can reach harmful level and vary accordingly to many factors. Since the primary source of radon in dwellings is the subsurface, the risk assessment and reduction cannot disregard the identification of the local geology and the environmental predisposing factors. In this article, we propos
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30

Baikov, I. R., S. V. Kitaev, and O. V. Smorodova. "Set of indicators for dependability evaluation of gas compression units." Dependability 18, no. 4 (2018): 16–21. http://dx.doi.org/10.21683/1729-2646-2018-18-4-16-21.

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The paper is dedicated to the improvement of the evaluation methods of one of the most important operating characteristics of gas compression units (GCUs), i.e. dependability, under the conditions of decreasing pipeline utilization rate. Currently, the dependability of units is characterized by a set of parameters based on the identification of the time spent by a unit in certain operational state. The paper presents the primary findings regarding the dependability coefficients of GPA-Ts-18 units, 41 of which are operated in multi-yard compressor stations (CSs) of one of Gazprom’s subsidiaries
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Zhou, Shenbei, Amin Du, and Minghao Bai. "Application of the environmental Gini coefficient in allocating water governance responsibilities: a case study in Taihu Lake Basin, China." Water Science and Technology 71, no. 7 (2015): 1047–55. http://dx.doi.org/10.2166/wst.2015.069.

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The equitable allocation of water governance responsibilities is very important yet difficult to achieve, particularly for a basin which involves many stakeholders and policymakers. In this study, the environmental Gini coefficient model was applied to evaluate the inequality of water governance responsibility allocation, and an environmental Gini coefficient optimisation model was built to achieve an optimal adjustment. To illustrate the application of the environmental Gini coefficient, the heavily polluted transboundary Taihu Lake Basin in China, was chosen as a case study. The results show
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32

BADHAM, JENNIFER M. "Commentary: Measuring the shape of degree distributions." Network Science 1, no. 2 (2013): 213–25. http://dx.doi.org/10.1017/nws.2013.10.

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AbstractDegree distribution is a fundamental property of networks. While mean degree provides a standard measure of scale, there are several commonly used shape measures. Widespread use of a single shape measure would enable comparisons between networks and facilitate investigations about the relationship between degree distribution properties and other network features. This paper describes five candidate measures of heterogeneity and recommends the Gini coefficient. It has theoretical advantages over many of the previously proposed measures, is meaningful for the broad range of distribution
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33

Genèev, Marian. "A note on a property of the Gini coefficient." Communications in Mathematics 27, no. 2 (2019): 81–88. http://dx.doi.org/10.2478/cm-2019-0008.

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AbstractThe scope of this note is a self-contained presentation of a mathematical method that enables us to give an absolute upper bound for the difference of the Gini coefficients|G(σ1, . . ., σn) − G(γ1, . . . , γn)| ,where (γ1, . . . , γn) represents the vector of the gross wages and (σ1, . . . , σn) represents the vector of the corresponding super-gross wages that is used in the Czech Republic for calculating the net wage. Since (as of June 2019) σi = 100 ⎡ 1.34 γi/100⎤, the study of the above difference seems to be somewhat inaccessible for many economists. However, our estimate based on
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34

Utt, Joshua, and Rodney Fort. "Pitfalls to Measuring Competitive Balance With Gini Coefficients." Journal of Sports Economics 3, no. 4 (2002): 367–73. http://dx.doi.org/10.1177/152700250200300406.

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35

Lerman, Robert I., and Shlomo Yitzhaki. "Improving the accuracy of estimates of Gini coefficients." Journal of Econometrics 42, no. 1 (1989): 43–47. http://dx.doi.org/10.1016/0304-4076(89)90074-2.

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36

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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37

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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38

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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39

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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40

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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41

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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42

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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43

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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Sun, Liang, Na Zhang, Ning Li, Zhuo-ran Song, and Wei-dong Li. "A Gini Coefficient-Based Impartial and Open Dispatching Model." Energies 13, no. 12 (2020): 3146. http://dx.doi.org/10.3390/en13123146.

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According to the existing widely applied impartial and open dispatching models, operation fairness was mainly emphasized, which severely restricted the optimization space of the economy of the overall system operation and affected the economic benefits. To solve the above problems, a scheduling model based on Gini coefficient under impartial and open dispatching principle is proposed in this paper, which can consider the balance between the fairness and economy of system operation. In the proposed model, the Gini coefficient is introduced to describe the fairness of electric energy completion
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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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WEN, FENGHUA, and ZHIFENG LIU. "A COPULA-BASED CORRELATION MEASURE AND ITS APPLICATION IN CHINESE STOCK MARKET." International Journal of Information Technology & Decision Making 08, no. 04 (2009): 787–801. http://dx.doi.org/10.1142/s0219622009003612.

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In this paper, a copula-based correlation measure is proposed to test the interdependence among stochastic variables in terms of copula function. Based on a geometric analysis of copula function, a new derivation method is introduced to derive the Gini correlation coefficient. Meantime theoretical analysis finds that the Gini correlation coefficient tends to overestimate the tail interdependence in the case of stochastic variables clustering at the tails. For this overestimation issue, a fully new correlation coefficient called Co is developed and extended to measure the tail interdependence.
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Wang, Jueyu, and Greg Lindsey. "Equity of Bikeway Distribution in Minneapolis, Minnesota." Transportation Research Record: Journal of the Transportation Research Board 2605, no. 1 (2017): 18–31. http://dx.doi.org/10.3141/2605-02.

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Governments and nonprofit organizations are investing in the bicycling infrastructure. However, the benefits of the bicycling infrastructure have not always been distributed equally among neighborhoods, and the equity of the distribution has been a major concern. This study used two measures, the Gini coefficient and the loss of accessibility to jobs via bikeways, to assess both the horizontal and the vertical equity of the bicycling infrastructure's distribution in Minneapolis, Minnesota. Gini coefficients, calculated from Lorenz curves, provide a single flexible measure that allows compariso
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48

Marriott, James J., Muhammad Mamdani, Gustavo Saposnik, Tara Gomes, Michael Manno, and Paul W. O'Connor. "Multiple Sclerosis Disease-Modifying Therapy Prescribing Patterns in Ontario." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 40, no. 1 (2013): 67–72. http://dx.doi.org/10.1017/s031716710001297x.

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Abstract:Background:Differences in Multiple sclerosis (MS) disease-modifying therapy (DMT) prescribing patterns between different groups of neurologists have not been explored.Objective:To examine concentrations of prescribing patterns and to assess if MS-specialists use a broader range of DMTs relative to general neurologists.Methods:We conducted a cross-sectional study using administrative claims databases in Ontario, Canada to link neurologists to 2009 DMT prescription data. MS specialization was defined using both practice location and prescription patterns. Lorenz curves and Gini coeffici
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Mirzaei, Shahryar, Gholam Reza Mohtashami Borzadaran, and Mohammad Amini. "A comparative study of the Gini coefficient estimators based on the linearization and U-statistics Methods." Revista Colombiana de Estadística 40, no. 2 (2017): 205–21. http://dx.doi.org/10.15446/rce.v40n2.53399.

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In this paper, we consider two well-known methods for analysis of the Gini index, which are U-statistics and linearization for some incomedistributions. In addition, we evaluate two different methods for some properties of their proposed estimators. Also, we compare two methods with resampling techniques in approximating some properties of the Gini index. A simulation study shows that the linearization method performs 'well' compared to the Gini estimator based on U-statistics. A brief study on real data supports our findings.
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50

Thompson, Amy E., Gary M. Feinman, and Keith M. Prufer. "Assessing Classic Maya multi-scalar household inequality in southern Belize." PLOS ONE 16, no. 3 (2021): e0248169. http://dx.doi.org/10.1371/journal.pone.0248169.

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Inequality is present to varying degrees in all human societies, pre-modern and contemporary. For archaeological contexts, variation in house size reflects differences in labor investments and serves as a robust means to assess wealth across populations small and large. The Gini coefficient, which measures the degree of concentration in the distribution of units within a population, has been employed as a standardized metric to evaluate the extent of inequality. Here, we employ Gini coefficients to assess wealth inequality at four nested socio-spatial scales–the micro-region, the polity, the d
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