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Access to drinking water is recognized as a human right, meaning that it is necessary to guarantee its universal and equitable access. Since analyzing only the average access rates to drinking water may obscure inequalities, studies have adapted socioeconomic inequalities indices to assess disparities. This research evaluated the Safe Drinking Water Access Index (SDWA) and inequalities access in all Brazilian municipalities using microdata from the 2010 Demographic Census. The inequalities were analyzed adapting indices derived from the Lorenz curve (Gini index, concentration coefficient and dissimilarity index). The results showed that the lowest SDWA rates and the highest inequality index values occurred in the north and northeast regions. The municipalities with significant inequality indexes values were rural with reduced gross domestic product (GDP) per capita. It was possible to punctuate municipalities that do not fit these rules but still need attention to safe water access guarantee. The amplitude of inequality index results reveals significant inequalities in the same regions or SDWA ranges. The inequalities in safe drinking water access were made more evident by the adapted Gini Index. This research contributes to the literature with an unprecedented analysis of Brazil and could be adapted to other countries and replicated to assess inequalities in sanitation access. [ABSTRACT FROM AUTHOR]

The objective of the paper is to show the increase in rural municipal inequality using fuzzy logic for the state of Jalisco, Mexico, from 2000 to 2015. Methodology: a fuzzy index was developed to measure municipal inequality, considering rural activity, both sugarcane and non-cane, public spending, economic performance, urbanization and the Gini Index. Results: the index showed a trend of increasing inequality between sugarcane and non-cane municipalities. Limitations: The study should ensure a clear conceptual relationship between the analysis tool and the measurement. Value: The use of fuzzy logic reveals that the role of the Mexican state has been important in this, and the proposed index highlights the pattern. Conclusions: during the first sixteen years of the 21st century, municipal and rural inequality in sugarcane and non-cane municipalities in Jalisco increased. [ABSTRACT FROM AUTHOR]

Access to drinking water is recognized as a human right, meaning that it is necessary to guarantee its universal and equitable access. Since analyzing only the average access rates to drinking water may obscure inequalities, studies have adapted socioeconomic inequalities indices to assess disparities. This research evaluated the Safe Drinking Water Access Index (SDWA) and inequalities access in all Brazilian municipalities using microdata from the 2010 Demographic Census. The inequalities were analyzed adapting indices derived from the Lorenz curve (Gini index, concentration coefficient and dissimilarity index). The results showed that the lowest SDWA rates and the highest inequality index values occurred in the north and northeast regions. The municipalities with significant inequality indexes values were rural with reduced gross domestic product (GDP) per capita. It was possible to punctuate municipalities that do not fit these rules but still need attention to safe water access guarantee. The amplitude of inequality index results reveals significant inequalities in the same regions or SDWA ranges. The inequalities in safe drinking water access were made more evident by the adapted Gini Index. This research contributes to the literature with an unprecedented analysis of Brazil and could be adapted to other countries and replicated to assess inequalities in sanitation access.

This study examined poverty and welfare status of urban farming households in Kaduna state. Multistage sampling procedure was used to collect data from 272 randomly selected urban households using structured questionnaire. The data was analyzed using descriptive statistics, Foster, Greer and Thorbecke poverty (FGT) index, Gini Coefficients and Tobit regression model. The results show a total per capita expenditure per year of N56, 993,133.76 and a mean per capital expenditure N209533.58 per year. The poverty incidence (P0), Poverty Gap (P1) and Severity of Poverty (P2) obtained for the area was 0.7348, 0.3667 and 0.2218 respectively. Also, an inequality index of 0.5397 recorded shows there is a wide divergence in spending among the urban households. Growth elasticities, and changes in inequality revealed that the poverty measures are more sensitive to inequality than to changes in mean income. Furthermore, poverty decomposition revealed that households with farming as primary occupation were poorer with an index of 0.8080 compared to 0.6995 incidence among those with other jobs. Age, household size, association membership, farming experience, income, expenditure on food and non-food items significantly determined poverty status. Pro-poor policies targeted at income redistribution in the state was recommended as this will have great impact on poverty. There is also the need to encourage more education among the faming families as welfare statuses of educated families were better off. [ABSTRACT FROM AUTHOR]

The goal of many randomized experiments and quasi-experimental studies in economics is to inform policies that aim to raise incomes and reduce economic inequality. A policy maximizing the sum of individual incomes may not be desirable if it magnifies economic inequality and post-treatment redistribution of income is infeasible. This article develops a method to estimate the optimal treatment assignment policy based on observable individual covariates when the policy objective is to maximize an equality-minded rank-dependent social welfare function, which puts higher weight on individuals with lower-ranked outcomes. We estimate the optimal policy by maximizing a sample analog of the rank-dependent welfare over a properly constrained set of policies. We show that the average social welfare attained by our estimated policy converges to the maximal attainable welfare at n − 1 / 2 rate uniformly over a large class of data distributions when the propensity score is known. We also show that this rate is minimax optimal. We provide an application of our method using the data from the National JTPA Study. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

Trade between regions not only brings about the exchange of goods and services but also leads to the transfer of emissions. As one of the larger emitting industries, the unequal exchange between environmental costs and economic benefits embodied in trade of the Construction industry has rarely been quantified. This paper applied a multi-regional input-output model to quantify the Construction -related carbon footprint (CF) and carbon emission flows among Chinese provinces. Subsequently, a regional environmental index was built to investigate the unbalanced exchange between Construction -related environmental costs and economic benefits embodied in the interprovincial trade. We found that the provincial per capita CF of Construction was unevenly distributed, with wealthier coastal regions generally having larger CF than poor inland regions. Compared with inland provinces, coastal ones have gained more economic benefits and lower environmental pressure. For example, over 75% of Construction -related carbon emissions in wealthier provinces (Beijing and Shanghai) were outsourced, while 60% of the value-added triggered by these provinces' Construction was retained within the region. However, with the progress of technology and the optimization of trade structure, the REI index decreased by about 30% during 2012–2017. This inequality problem gradually alleviated. Addressing these inequality issues could provide a basis for developing mitigation strategies across different provinces in the Construction industry. • The inequality of carbon footprint of Construction in China's provinces was analyzed. • A regional environmental inequality index was used to measure the inequality. • Developing provinces suffered both economic and environmental losses in interprovincial trade. • The inequality problem gradually alleviated during 2012–2017. [ABSTRACT FROM AUTHOR]

In order to bolster the concept of sustainable territorial development in conjunction with the three capitals — natural, social, and built capital —, a conceptual methodology was elaborated. It utilized the infrastructure systems to group indicator dimensions of built capital, highlighting what actually corresponds to the territorial development reality and not just economic growth. This resulted in the selection of 70 indicators that were tested with data from the Curitiba Metropolitan Region (CMR). Thirty-five indicators were selected from the data available to evaluate the development in 29 municipalities that form the CMR. Finally, the Sustainable Territorial Development Index (INFRASTDI) and Inequality Index (II) were proposed to summarize the information collected.

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Abstract As energy saving and emission reduction become a global action, the disparity in energy intensity between different regions is a new rising problem that stems a country's or region's energy‐saving potential. Here we collect China's provincial panel data (1995–2017) of primary and final energy consumption to evaluate China's unequal and polarized regional pattern in energy intensity, decompose the inequality index into contributing components, and investigate possible driving factors behind the unequal pattern both regionally and structurally, for the first time. The results show that China's interprovince disparities in energy intensity increase and are exacerbated by the enlarging disparities in energy intensity between the least developed and most developed regions of China. The causes for this phenomenon are as follows: (i) rather loose regulatory measures on mitigating coal consumption; (ii) inferior energy processing technology in areas specializing in energy‐intensive industries; (iii) increasing interregional energy fluxes embodied in trade; and (iv) separate jurisdictions at provincial administrative levels. These factors can synthetically result in unintended spillover to areas with inferior green technologies, suggesting an increasingly uneven distribution of energy‐intensive and carbon‐intensive industries and usage of clean energy. The results reveal the necessities of regional coordination and cooperation to achieve a green economy.

As energy saving and emission reduction become a global action, the disparity in energy intensity between different regions is a new rising problem that stems a country's or region's energy‐saving potential. Here we collect China's provincial panel data (1995–2017) of primary and final energy consumption to evaluate China's unequal and polarized regional pattern in energy intensity, decompose the inequality index into contributing components, and investigate possible driving factors behind the unequal pattern both regionally and structurally, for the first time. The results show that China's interprovince disparities in energy intensity increase and are exacerbated by the enlarging disparities in energy intensity between the least developed and most developed regions of China. The causes for this phenomenon are as follows: (i) rather loose regulatory measures on mitigating coal consumption; (ii) inferior energy processing technology in areas specializing in energy‐intensive industries; (iii) increasing interregional energy fluxes embodied in trade; and (iv) separate jurisdictions at provincial administrative levels. These factors can synthetically result in unintended spillover to areas with inferior green technologies, suggesting an increasingly uneven distribution of energy‐intensive and carbon‐intensive industries and usage of clean energy. The results reveal the necessities of regional coordination and cooperation to achieve a green economy. Key Points: This study aims to explore the regional disparities in energy intensity and its driving factors both regionally and structurallyRegional disparities in energy intensities are enlarging, especially after China introduced more stringent energy conservation policyThe causes are ineffective regulatory measures, unbalanced technologies, interregional energy fluxes, and separate jurisdictions [ABSTRACT FROM AUTHOR]

In this paper, a method for evaluating systemic risk in different geographic areas is presented. The proposed methodology is based on the decomposition by subpopulations of the Gini index, largely used to assess the inequality of income and wealth. This decomposition procedure follows a two-step approach that goes beyond the "classical" decomposition Within and Between components, also allowing the assessment of the contribution to the total inequality for each subpopulation. [ABSTRACT FROM AUTHOR]

Inequality and its analysis have received increasing attention in the literature over the last decades, which has led to the development of a large number of inequality measurement methodologies. In the analysis of inequality, results rely heavily on the choice of a measurement methodology and, very often, different methodologies do not lead to the same rankings. Therefore, in the assessment of inequality, the choice of an appropriate measure is crucial. Important as this choice may be, to the best of the authors' knowledge, there exists no research on the development of a systematic and unified framework for the selection of an adequate inequality measure depending on the context. In consideration of the foregoing, this paper provides a framework with practical guidelines for researchers and practitioners to facilitate the task of choosing the most appropriate inequality measure for their specific needs. The proposed guidelines are based on seven main properties of inequality indexes and are preceded by a comprehensive review of the different methods developed so far, focusing specifically on the advantages and drawbacks of each. Besides, they are accompanied by an empirical application of the different methodologies reviewed in order to better illustrate the various properties of the different inequality measures. [ABSTRACT FROM AUTHOR]

In this paper, we consider two well-known methods for analysis of the Gini index, which are U-statistics and linearization for some income distributions. 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.

Copyright of Revista Chapingo Serie Ciencias Forestales is the property of Universidad Autonoma Chapingo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main goal of this paper is evaluate inequality and technical efficiency of federal health financing for population without social security per federative entity. Were estimated two inequality measures of federal financing for population without social security per Federal Entity: the Gini coefficient and the Theil entropy index. Four stochastic frontier models were calculated to measure technical efficiency of health production per federative entity (2004-2012). Information on health expenditure, physical and human resources yielded by the Ministry of Health through SINAIS was used. The federal financing for population without social security has reduced inequality among Federal Entities due to the incorporation of the SPSS (Mexican system of social protection in terms of health). The estimate of technical efficiency of Federal Entities through stochastic frontiers shows that most of these entities have health production inefficiencies both at outpatient and hospital levels, being the outpatient level the one with more inefficiency. Not necessarily entities that receive greater resources produce more health. The existence of multiple financing sources has limited the effect of the SPSS to reduce inequality in financing for population without social security among Federal Entities. More health resources are needed in order to face demographic and epidemiological transitions, but it is necessary to spend the available resources in a more efficient way. There are three main lines of action in terms of financing: structuring financing sources and improving the allocation mechanisms; and strengthening evaluation and monitoring resources exercise. [ABSTRACT FROM AUTHOR]

The underlying idea behind the construction of indices of economic inequality is based on measuring deviations of various portions of low incomes from certain references or benchmarks, which could be point measures like the population mean or median, or curves like the hypotenuse of the right triangle into which every Lorenz curve falls. In this paper, we argue that, by appropriately choosing population-based references (called societal references) and distributions of personal positions (called gambles, which are random), we can meaningfully unify classical and contemporary indices of economic inequality, and various measures of risk. To illustrate the herein proposed approach, we put forward and explore a risk measure that takes into account the relativity of large risks with respect to small ones. [ABSTRACT FROM AUTHOR]

Measuring regional inequality: to weight or not to weight?Spatial Economic Analysis. When estimating regional inequality, many economists use inequality indices weighted by regions’ proportion of the national population. Although this approach is widespread, its adequacy has not received attention in the regional science literature. This paper proves that such an approach is conceptually inconsistent, yielding an estimate of interpersonal inequality among the whole population of the country rather than an estimate of regional inequality. Nevertheless, as a measure of interpersonal inequality, such an estimate is very rough (even misleading) and does not always have an intuitive interpretation. Moreover, population-weighted inequality indices do not meet the requirements for an adequate measure of inequality. [ABSTRACT FROM AUTHOR]

Mounting evidence over the past several decades has demonstrated inequitable distribution of pollutants of ambient origin between sociodemographic groups in the United States. Most environmental inequality studies to date are cross-sectional and used proximity-based methods rather than modeled air pollution concentrations, limiting the ability to examine trends over time or the factors that drive exposure inequalities. In this paper, we use 1 km 2 modeled PM 2.5 and NO 2 concentrations in Massachusetts over an 8-year period and Census demographic data to quantify inequality between sociodemographic groups and to develop a more nuanced understanding of the drivers and trends in longitudinal air pollution inequality. Annual-average population-weighted PM 2.5 and NO 2 concentrations were highest for urban non-Hispanic black populations (11.8 µg/m 3 in 2003 and 8.4 µg/m 3 in 2010, vs. 11.3 µg/m 3 and 8.1 µg/m 3 for urban non-Hispanic whites) and urban Hispanic populations (15.9 ppb in 2005 and 13.0 ppb in 2010, vs. 13.0 ppb and 10.2 ppb for urban non-Hispanic whites), respectively. While population groups experienced similar absolute decreases in exposure over time, disparities in population-weighted concentrations increased over time when quantified by the Atkinson Index, a relative inequality measure. Exposure inequalities were approximately one order of magnitude greater for NO 2 compared to PM 2.5 , were more pronounced in urban compared to rural geographies, and between racial/ethnic groups compared to income and educational attainment groups. Our results also revealed similar longitudinal PM 2.5 and NO 2 inequality trends using Census 2000 and Census 2010 data, indicating that spatio-temporal shifts in air pollution may best explain observed trends in inequality. These findings enhance our understanding of factors that contribute to persistent inequalities and underscore the importance of targeted exposure reduction strategies aimed at vulnerable populations and neighborhoods. [ABSTRACT FROM AUTHOR]

In this work we provide a decomposition by sources of the inequality index $$\zeta $$ defined by Zenga (Giornale degli Economisti e Annali di economia 43(5-6):301-326, 1984). The source contributions are obtained with the method proposed in Zenga et al. (Stat Appl X(1):3-31, 2012) and Zenga (Stat Appl XI(2):133-161, 2013), that allows to compare different inequality measures. This method is based on the decomposition of inequality curves. To apply this decomposition to the index $$\zeta $$ and its inequality curve, we adapt the method to the 'cograduation' table. Moreover, we consider the case of linear transformation of sources and analyse the corresponding results. [ABSTRACT FROM AUTHOR]

Since soccer is the most prominent sport in Europe—not to mention the world—it is no wonder that deep strategizing has become the norm in its management models. In this study we extract from real data the hidden and nontrivial relationships that have developed within the game in order to further the current understanding of how a team's performance is premised on its tactical and financial choices. We adopt, for the first time—in combination with an ordered logit model—inequality indexes at the team level. Our analysis uses a large and unique dataset that includes all of the teams from the top five European national championship leagues, including detailed player and team statistics. The results differ between the top-tier and medium-to-bottom tier teams and highlight an overall strategic evolution over the last decade. • This research has contributed to filling the gap that exists in the current literature on the key success factors of soccer teams • Our results highlight a change that has occurred in Europe over the last decade • In recent years, winning teams have adopted a community-based game system that features leaders who trigger this mechanism • The implication of our research is that leadership is just one element required to achieve success. • Our paper highlights the necessary levers for the creation of sporting and financial value for sporting enterprises. [ABSTRACT FROM AUTHOR]