Gini Coefficient Research Articles

The allocation and fairness of hospital pharmacist human resources in China: a time-series study

BackgroundTo address the rational use of medicines in healthcare institutions, the Chinese government enacted legislation for pharmacists in 2021, emphasizing the importance of pharmacists in medical services. The allocation and equity of pharmacist human resources in healthcare institutions directly affect people’s accessibility to pharmaceutical services. The study aims to analyze the supply and demand of pharmacist human resources in Chinese healthcare institutions and evaluate the equity of their distribution to provide a reference for the rational management of pharmacist resources.MethodsThis was a time-series study that was conducted using data obtained from Health and Health Statistical Yearbook that is performed every year by the National Health Commission of the People’s Republic of China. The study included 31 provinces, municipalities, and autonomous regions and 34,354 medical institutions in mainland China, which were classified into different economic regions based on their level of economic development. The study collected healthcare technicians and pharmacist data from national healthcare institutions between 2016 and 2020. The study evaluated the level of pharmacist human resource allocation using the health resource density index. The study explored the equity of pharmacist human resource allocation from two aspects: population and geographic area, using the Gini coefficient and Theil index.ResultsThe average annual growth rates of healthcare technical staff and pharmacists in Chinese medical institutions from 2016 to 2020 were 5.67% and 3.03%, respectively. The Gini coefficients of healthcare personnel resources based on population distribution were all below 0.119, while those based on geographical area were all above 0.655. The total Theil indexes of pharmacist human resources based on population distribution were all below 0.010, while those based on geographical area were all above 0.511. In addition, the contribution rates of the within-group Theil indexes of pharmacist human resources based on population and geographical area distributions to the total Theil index were all greater than or equal to 50%.ConclusionsThe allocation level of pharmacist human resources in China continues to improve, but there are differences in different economic development areas. Currently, allocation based on population shows equity, but allocation based on geographic area shows inequity. In the future, more attention should be paid to the geographic accessibility of pharmacist human resources, and resource allocation should consider both the population served and geographic area.

Tourism Development Impact on Economic Growth and Poverty Alleviation in West Java

Poverty alleviation is on the agenda of regional development in West Java. One of the priority sectors is tourism development, which supports inclusive economic growth and is expected to address poverty. Through various unit analyses, the study analyzed how tourism development in West Java impacts economic growth and poverty alleviation. These included indicators such as the number of tourist visits, hotel room occupancy rate, the number of hotels and restaurants, average length of stay, and the tourism sector's contribution to Original Local Government Revenue (PAD). Economic growth was assessed using indicators such as Gross Regional Domestic Product (GRDP), unemployment rate, Gini Index, and regional investment value. In contrast, the poverty variable used the percentage and number of people living in poverty, poverty line statistics, Poverty Depth Index, and Poverty Severity Index. Inferential statistical analysis, specifically Partial Least Square (PLS), was conducted using a quantitative approach and data from BPS - Statistics of West Java. Hypotheses were formulated based on the literature review, asserting that tourism development significantly and positively impacted economic growth and poverty alleviation in West Java. Results showed that tourism development significantly boosted economic performance, directly influencing economic growth. Additionally, high economic growth correlated with reduced poverty rates, highlighting the importance of inclusive growth for alleviation. Key indicators played crucial roles in poverty alleviation, including the number of hotels and restaurants, the tourism sector's contribution to regional revenue, GRDP, and regional investment value. These findings provided valuable insights for policymakers and stakeholders to develop effective strategies for leveraging tourism potential to promote inclusive economic growth and alleviate poverty in West Java.

On the issue of impact of income inequality on the socio-economic development of territories

The issues of economic inequality and justice were considered in the works of the philosophers of Ancient Greece. Over time, the problem of income inequality has not lost its relevance, which is confirmed by domestic and foreign studies. Until 2015, the capital of the Russian Federation had the highest value of the Gini index, which indicates a high degree of inequality in income distribution in the territory of this subject. Over time, the situation has changed, in particular, by increasing the incomes of the least well-off groups of the population, providing them with subsidies and payments. The purpose of the study is to analyse to what extent these changes have an impact on the socio-economic development of the region. With the help of econometric calculations, the degree of dependence between the equity index and the value of the gross regional product per capita has been determined. It is revealed that there is an inverse relationship between the considered indicators, that is, a reduction in income inequality has an impact on the growth of regional production. The high value of the coefficient of determination indicates the high quality of the constructed model. The possibility of using the simulation results in practice is confirmed by calculations of the average approximation error and the Fisher criterion.

What are the main factors of fuzzy inequality in Chad?

The purpose of this study is to identify the effects of multidimensional (fuzzy) inequalities and marginal changes on the Gini coefficients of various factors. This allows a range of social policies to be specifically targeted to reduce broader inequalities, but these policies are focused primarily on health, education, housing, sanitation, energy and drinking water. It is necessary to target policy areas that are unequally distributed, such as those with access to unevenly distributed drinking water policies. The data are from the Household and Consumption Survey of 6695 households in 2003 and 9259 households in 2011. This paper uses Lerman and Yitzhaki’s method. The results revealed that the main contributors to inequalities over the two periods were health and education. These sources have a potentially significant effect on total inequality. Health increases overall inequalities, but sources such as housing, sanitation and energy reduce them. This article provides resources to disadvantaged and vulnerable target groups. Multiple inequalities are analyzed for different subgroups of households, such as place of residence and the gender of the head of household. Analyzing fuzzy poverty inequalities makes it possible to develop targeted measures to combat poverty and inequality. This study is the first to investigate the sources of Gini’s fuzzy inequality in Chad via data analysis techniques, and in general, it is one of the few studies in Saharan Africa to be interested in this subject. Some development policies in sub-Saharan Africa should therefore focus on different sources (negative effect), sources (positive effect) and the equalization effect.

The Distribution of Land in Luxembourg (1766–1872): Family-Level Wealth Persistence in the Midst of Institutional Change

The paper analyzes family-level wealth inequality and social mobility in Dudelange (Luxembourg) over five generations between 1766 and 1872, a period that saw the end of feudal social relations. While the integration of Luxembourg into the French revolutionary regime produced a reduction in the Gini coefficient for the ownership of land, the social mobility analysis reveals a relative stability of family positions within the land-wealth distribution throughout the period. This shows that family-level transmission mechanisms limit social mobility and strongly advantage those with ancestors owning property wealth, even when there are significant changes in the organization of property relations.

Pendapatan dalam Hubungannya dengan Perencanaan Ekonomi Kabupaten Muaro Jambi dilihat dari Sisi Perkembangan Indeks Gini Kabupaten Muaro Jambi

Analysis of the Gini index based on education level shows significant inequality in the distribution of education in society. Higher levels of education tend to be accessed by groups with higher incomes, while groups with lower incomes often face barriers to obtaining quality education. This is reflected in the Gini index, which shows that the gap between groups with good and limited access to education is widening. This inequality has an impact on economic opportunities and social mobility, suggesting that improvements in a more inclusive education system and equal access to education across all levels of society are essential to reducing inequality and achieving greater social justice. The secondary sector in Muaro Jambi also shows significant levels of inequality. In the manufacturing and processing industries, large companies that produce goods on a large scale often make substantial profits, while small and medium enterprises struggle to compete. Inequality is also reflected in the construction sector, where the income gap between skilled and unskilled construction workers, and between large and small contractors, is quite striking. This contributes to the high Gini index in this sector, reflecting income inequality among workers and employers. In the tertiary sector, which includes services, retail, finance, and insurance, income inequality tends to be higher. In the service sector, the difference in income between workers in customer service and managers or professionals is very large. In the finance and insurance sector, income inequality is also significant because wages in this sector are often very high compared to other sectors, creating a large gap between workers in these fields and those in lower-wage sectors. This unequal distribution of income leads to a high Gini index in the tertiary sector. The quaternary sector in Muaro Jambi, which includes technology, information, and research and development, shows high levels of inequality. This inequality is caused by the large differences in wages between technology professionals and workers in non-technology sectors, as well as between workers in large technology companies and small businesses. Specialized skills and high levels of education in this sector are often directly related to high incomes, while those in less skilled or educated positions earn much lower wages. This creates a clear inequality in the distribution of income in this sector.

Temporal inequality of RR intervals like a new psychophysiological indicator of mental stress

Introduction: Gini coefficient (Gini index or Gini ratio) is a parameter that is normally used in economy to measure the income distribution in a country or in the whole wide world, but it can be used to measure any kind of distribution. In the present study it is exposed an innovative proposal of application of the Gini coefficient to Heart Rate Variability (HRV) like a psychophysiological indicator of mental stress.Objective: to assess the application of the Gini coefficient as a psychophysiological indicator of mental stress.Methods: a non-observational crossover study, carried out in the biomedical laboratory of the Medical University of Santiago de Cuba. The involved participants are 13 healthy individuals (age 19 ± 1,5 years). Heart rate was continuously recorded at rest (5 minutes) and during a mental stress (5 minutes). Linear and nonlinear methods of heart rate variability were assessed, and 2 new indicators (Sequential and Non-Sequential Gini) were calculated and proposed to measure HRV differences between states.Results: when comparing rest and mental stress conditions, a sensible decrease of the traditional indicators of the HRV was founded (p<0,05), an increase of the heart rate (p=0,004) and of the Sequential Gini (p=0,004) and Non-Sequential Gini (p=0,04).Conclusions: the results suggest that temporary inequality of the RR intervals analyzed from the Gini coefficient could be an adequate indicator of sympathetic activity present during the mental stress

Unveiling driving disparities between satisfaction and equity of ecosystem services in urbanized areas

Rapid urbanization intensifies the challenges of achieving satisfaction and equity in ecosystem services (ESs). Beginning with a theoretical overview, we identify five pivotal challenges in managing urban ESs, forming the basis for our integrative analysis. Employing a multi-level analytical perspective, our research quantifies ESs satisfaction through supply–demand ratios and evaluates ESs equity via supply–demand Gini coefficient. Simultaneously explored the driving force relationship between these two dimensions. This study uses Guangdong Province, a typical urbanized area in China, as a case study to assess the supply and demand relationships of four regulating ESs: water retention, soil retention, carbon storage, and water purification. Our results highlight the disparity in ES management effectiveness across different scales while the overall assessments might suggest adequate or equitable ESs, localized assessments within cities and regions often uncover specific ESs issues. A pivotal aspect is that single-factor critical to ESs satisfaction or equity dimension may have limited or opposing importance in another, but interactive effects of multiple factors can effectively mitigate these divergent impacts through non-linear synergies. These insights not only reveal the multiplex impacts of natural–social–economic drivers on urban expansion but also guide the targeted development in different management scale, multi-dimensional management strategies to address these disparities. This approach enriches the discourse on sustainable urban development and provides a robust framework for addressing the nuanced challenges of urban ESs management.

The interaction of income inequality and energy poverty on global carbon emissions: A dynamic panel data approach

Income inequality and energy poverty are critical obstacles to the worldwide low-carbon transformation and deeply affect human behavior. Applying a dynamic panel data model, this study investigates the effect of income inequality and energy poverty on global carbon emissions. We determine the effect of the interaction between income inequality and energy poverty on the global low-carbon transformation based on a panel data set of 193 countries from 1990 to 2019. A one standard deviation decrease in the Gini coefficient causes a 2.98 % decrease in carbon emissions per capita, with the median value of energy poverty. However, in poor countries where the proportion of population with access to electricity is less than 86.0 %, reducing income inequality will increase carbon emissions. The role of energy poverty on carbon emissions per capita is also affected by income inequality. When the Gini coefficient is lower than 0.461, increasing access to electricity will reduce carbon emissions. In contrast, when the Gini coefficient is higher than the critical value of 0.461, increased access to electricity will raise carbon emissions. These findings indicate a new strategy for advancing low-carbon transformation based on the interrelationship between income equality and energy poverty eradication.

Some Notes on the Gini Index and New Inequality Measures: The nth Gini Index

A new family of inequality indices based on the deviation between the expected maximum and the expected minimum of random samples, called the nth Gini index is presented. These indices generalize the Gini index. At the same time, this family of indices and the S-Gini index are generalized by proposing the uv-Gini index, which turns out to be a convex combination of the S-Gini index and the Lorenz family of inequality measures. This family of Gini indices provides a methodology for achieving perfect equality in a given distribution of incomes. This is achieved through a series of successive and equal increases in the incomes of each individual.

Estimation Methods of Reproduction Numbers for Epidemics of Varying Strains of COVID-19

The estimation methods of reproduction numbers and serial intervals are important in the early stages of infectious diseases. During the COVID pandemic, China implemented a dynamic zero-COVID policy on the Chinese mainland until the end of 2022. This study compares three estimation methods of reproduction numbers on small-scale, short-duration COVID-19 epidemics in Fujian province. Basic reproduction numbers were investigated using a varying-strain model via a next-generation matrix method. Serial intervals were derived using the infector–infectee pairs of two epidemics from the Fujian Provincial Center for Disease Control and Prevention. Basic reproduction numbers were estimated using maximum likelihood estimation and an exponential growth method. The curves of the effective reproduction numbers of the three epidemics were plotted by utilizing daily cases and the EpiEstim R package. The spatial heterogeneity of infection cases was described using the Gini coefficient. This study provides significant insights on the estimation methods of reproduction numbers for policymakers in the local government. The results reveal that social contacts between infectors and susceptible individuals should be reduced to avoid an increase in deaths and to fight against the spread of infectious diseases.

Machine learning in obsessive-compulsive disorder medications

Obsessive-compulsive disorder (OCD) is the fourth most common psychiatric disorder with a significant morbidity rate. Despite various treatment modalities and medications, some patients show no definitive response. The aim of this study is to classify the medications of OCD with machine learning (ML) methods and to compare the classification performances of the decision tree (DT), chi-square automatic interaction detection (CHAID) algorithm, and linear model in ML methods. This research is a descriptive analytical study based on co-word and artificial intelligence methods. The DT models were created with a target (total weight link strength). For hyperparameter optimization, the Gini index was used as the weight total link strength. The performance of the DT model was evaluated based on the prediction model. A total of 116 drugs were extracted from 6574 articles based on co-word analysis, and 56 drugs were classified as the DT's root. These drugs were categorized into six groups in the EWKM diagram. The DT was constructed using the weight.total.link index, with 7 items in Label 3 and 42 items in Label 5 serving as DT leaves. The ML analysis provided valuable insights into the efficacy of various medications such as clomipramine, duloxetine, and pindolol, as well as supplements such as folate, in the treatment of OCD. Treating concomitant diseases, namely hypothyroidism and streptococcal infection could improve the efficacy of treatment.

The evolution of inequality in Mozambique 1996/97–2019/20

ABSTRACT After decades of war, Mozambique experienced sustained economic growth and poverty reduction from the mid-1990s. However, these positive dynamics started to revert from 2015. Meanwhile, inequality stagnated in the period 1996/97–2008/09, before markedly increasing afterwards. In this study, we analyse some of the most relevant indicators of inequality for Mozambique and their trends over the last 25 years. Using real per capita consumption as the main welfare aggregate, we look at various indicators of inequality, including the consumption distribution, percentiles and percentile ratios, growth incidence curves, Lorenz curves, and Gini indices. In addition, we discuss spatial inequality. Overall, we find that until 2014/15, consumption increased for the whole population, but it did so much more for richer households; conversely, in the last few years, consumption has reduced across the distribution, but the relative consumption-gap between better- and worse-off people has continued to increase.

Pre-disaster income inequality and post-disaster mental health: A natural experiment from the 2011 Great East Japan Earthquake and Tsunami

BackgroundWe sought to test the hypothesis that communities with a high degree of income inequality are ill-equipped to deal with crises. Specifically, we tested whether pre-disaster higher income inequality increases the risk of worse mental health conditions in the aftermath of disaster. MethodsWe examined the association between pre-disaster community income inequality and post-disaster mental health outcomes in a prospective cohort study of older adults (≥65 years) who survived the 2011 Great East Japan Earthquake. The baseline survey of participants (completed in 2010) predated the disaster by seven months. Survivors completed three waves of post-disaster surveys in 2013, 2016, and 2019. To assess the level of income inequality, the Gini index was calculated using individual income data in 2010 aggregated to 98 communities (range 0.05–0.50: median = 0.32) and categorized into tertiles (low, middle, high). Depressive symptoms and post-traumatic stress symptoms (PTSS) were assessed in the three post-disaster surveys using validated instruments. Multilevel analysis was conducted adjusting for pre-disaster characteristics. ResultsHigher levels of community income inequality were associated with higher PTSS scores across time (2013: β = 0.14, 95%CI = −0.01, 0.29; 2016: β = 0.16, 95%CI = 0.03, 0.29; 2019: β = 0.12, 95%CI = −0.01, 0.24). The association between income inequality and mental health was partly attenuated by adding the change in social capital to the model (2013: β = 0.14, 95%CI = -0.01, 0.29; 2016: β = 0.15, 95%CI = 0.03, 0.28; 2019: β = 0.11, 95%CI = -0.01, 0.22). ConclusionOur findings suggest that pre-disaster income inequality may explain PTSS symptoms in the aftermath of a disaster, and the relation may be mediated by disaster-related change. Further study to reveal its mechanism is needed for the policy recommendation.

Aligning common prosperity with sustainable development goals 3 and 7 through sustainable insurance

This paper develops a capped-call option model to evaluate sustainable insurance for achieving common prosperity. It integrates policyholder protection (Sustainable Development Goal 3 (SDG 3)) and the cap-and-trade mechanism (SDG 7) in modeling the Gini coefficient, thereby connecting SDGs 3 and 7 with common prosperity. The main findings are as follows. Life insurance policies that prioritize saving features enhance policyholder protection (SDG 3) but can detract from common prosperity. This impact is magnified when the regulatory cap within the cap-and-trade scheme for carbon-intensive manufacturers becomes stricter. High investment risks for carbon-intensive manufacturers reduce policyholder protection but support common prosperity. A stricter cap-and-trade scheme (SDG 7) also reduces policyholder protection and contradicts common prosperity. This paper avoids concluding any inherent inconsistency between the SDGs and common prosperity, as our analysis is based on the structure-conduct-performance paradigm rather than a macro perspective. Policymakers should carefully balance objectives between SDG 3 and common prosperity to ensure that policies promoting individual security do not compromise broader societal well-being and economic equality, as outlined by the SDGs.

The research on the factors affecting the World Happiness index

Abstract. The purpose of this study was to use data from the World Happiness Report to conduct an in-depth analysis of the factors that influence the World Happiness Index (WHI) and to look for other factors that may influence happiness. In this paper, the correlation graph shows that among the original six variables, Social Support has the strongest correlation with the ladder score, which means that Social Support has the greatest impact on the happiness index, followed by GDP per capita; Generosity, on the other hand, was the weakest associated with ladder scores and had the least effect on happiness. Then the linear regression and scatter plot are used to prove this conclusion. Therefore, this paper can consider whether to delete Generosity as an influential factor. A map was then used to show happiness levels and geographical distribution in different countries. At the same time, the distribution of the Gini coefficient is also shown by a regional distribution map. From the perspective of the Gini coefficient and education level, these two factors also have a certain positive correlation with the happiness index, which are likely to be the potential influencing factors of the happiness index. From a global map perspective, the happiest countries are mostly located in Europe, North America and Oceania, while the happiest countries are mostly located in Africa. The study's sample size was not large enough, it was prone to make errors and raise questions about happiness scores in some countries.

Social Learning for the Masses

I consider a plausible role for social learning as implemented in the work of Jasmina Arifovic in a complex macroeconomic environment. The model is DSGE with considerable heterogeneity, enough to approach Gini coefficients for income, wealth, and consumption in the U.S. data. The economy has an ambient stochastic structure, and I consider transition dynamics following exceptionally large shocks like the global financial crisis or the global pandemic. These shocks are large enough to plausibly perturb the economy out of the rational expectations equilibrium associated with more ordinary shocks. How is equilibrium re-established? I argue that a social learning construct may be more appropriate in this environment, as opposed to the econometric learning constructs often used to analyze departures from rational expectations in the literature. I also argue that a “DNA” feature of social learning may have led to relatively fast convergence to rational expectations observed following these large shocks in the U.S. data.

사교육비 불평등도에 대한 연구: 사교육비 지니 계수, 후버 지수, 팔마 비율을 중심으로

Objectives This study aims to find a way to measure the degree of inequality in private education expenditures in Korea and to analyze trends in inequality. Methods We analyzed the private education expenditures survey conducted by the Ministry of Education to find an index that indicates the inequality of private education expenditures, and obtained each index by year to under-stand the trend. Results The average private education expenditures per person is increasing, and the analysis of private education expenditures inequality using the Gini coefficient, the Hoover index, and the Palma ratio shows that inequality is increasing, especially in elementary schools. In 2020, during the COVID-19 situation, the private education Gini coefficient increased rapidly as the private education participation rate decreased in elementary and middle schools, but this phenomenon was not found in high schools. Conclusions The Gini coefficient, Hoover index, and Palma ratio, which indicate the degree of inequality in private education, can be obtained for the entire population and participants, but considering that the case where private education expenditures are 0 has a significant impact, it may be more appropriate to limit it to participants. The Gini coefficient, which indicates income inequality, is on the decline, but the Gini coefficient for private education expenditures for participants is increasing, and since private education is linked to the problems of low birth rate and local extinction that our society faces, special measures are needed to reduce private education.

Uncertain multi‐objective programming approach for planning supplementary irrigation areas in rainfed agricultural regions

AbstractRainfed agriculture is crucial for ensuring global food and water security, and supplementary irrigation is an effective means of improving the economic benefits in rainfed agricultural regions. This study proposes a novel uncertain optimization approach to optimize supplementary irrigation areas in rainfed agricultural regions. The approach incorporates multi‐objective linear programming, interval linear programming, fuzzy goal programming and stochastic expected value programming. In the proposed interval multi‐fuzzy goal stochastic expected‐value programming, uncertainties are expressed in the form of discrete intervals, probability distributions and fuzzy goals. This approach, which considers the randomness of precipitation during the optimization process and allocates limited irrigation water resources to different subareas and crops, was applied to a case study of crop irrigation area planning in Guyuan City, Ningxia Hui Autonomous Region, northwestern China. The maximum economic benefits and the minimum sum of the Gini coefficients among the different subareas and crops were regarded as the planning objectives, and a series of optimal irrigation areas with different crops and subareas under different water levels were obtained. The optimization results revealed that vegetables and fruits consumed large amounts of irrigation water to increase their economic benefits. In addition, allocating a large amount of irrigation water to wheat is essential to decrease the Gini coefficient and meet food security constraints, particularly at extremely low water levels. Compared with current management, the optimized irrigation area decreased by 30%, the crop water deficit index increased by 9%, the economic benefits increased by 3% and the total Gini coefficient of crops decreased by 17%, indicating that the optimization approach could fairly and reasonably allocate irrigation water resources. Our research provides a mathematical approach for decision‐makers to plan supplementary irrigation areas in rainfed agricultural regions.

Analyzing the Dynamics of Inflation, Exchange Rates and Economic Growth through the Gini Index: Modeling VAR in Morocco

In this study, we analyze the cross-impact of inflation, exchange rates and economic growth on income inequality in Morocco between 2000 and 2022, based on the GINI index as a measure of inequality. Its main objective is to understand how these macroeconomic variables influence income disparities. Our methodology is based on a VAR model to capture dynamic interactions between variables. To validate the robustness of the model, Granger causality tests and specification tests, including tests of homoscedasticity and autocorrelation of residuals, were used. The result is that inflation has a significant positive impact on income inequality, and exchange rate fluctuations directly influence inequality. Furthermore, economic growth helps to reduce inequality, although this effect depends on the distribution of the benefits of this growth. This study contributes to the existing literature by providing empirical evidence of the importance of macroeconomic stability and educational and fiscal policies in reducing income inequality.