919 resultados para Coefficient Inequality
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MSC 2010: 30C45, 30C50
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Silveira Neto R. Da M. and Azzoni C. R. Non-spatial government policies and regional income inequality in Brazil, Regional Studies. This paper uses both macro- and micro-data to analyse the role of social programmes in the recent reduction in Brazilian regional income inequality. Convergence indicators are presented for different sources of regional income in the period 1995-2006. A decomposition of the Gini indicator allows the identification of the role of each of these income sources with respect to the reduction of regional inequality during the period. The results point out that both labour productivity and government non-spatial policies - mainly minimum wage changes and income transference programmes - do have a role in explaining regional inequality reduction during the period. [image omitted] Silveira Neto R. Da M. et Azzoni C. R. Les politiques gouvernementales non-spatiales et l`ecart des revenus regionaux au Bresil, Regional Studies. Cet article emploie des donnees a la fois macroeconomiques et microeconomiques afin d`analyser le role des programmes d`actions sociales quant a la baisse recente de l`ecart des revenus regionaux au Bresil. On presente des indicateurs de convergence pour diverses sources des revenus regionaux pour la periode allant de 1995 a 2006. Une decomposition du coefficient de Gini permet d`identifier le role de chacune de ces sources des revenus par rapport a la baisse de l`ecart des revenus pendant cette periode. Les resultats indiquent que la productivite du travail et les politiques gouvernementales non-spatiales - notamment la modification du salaire minimum et les programmes visant le transfert des revenus - ont un role a jouer pour expliquer la baisse de l`ecart des revenus regionaux pendant la periode en question. Convergence Productivite du travail Transfert des revenus Salaire minimum Effets spatiaux des politiques non-spatiales Silveira Neto R. Da M. und Azzoni C. R. Nicht raumliche Regierungspolitiken und das regionale Einkommensungleichgewicht in Brasilien, Regional Studies. In diesem Beitrag analysieren wir mit Hilfe von Makro- und Mikrodaten die Rolle von sozialen Programmen bei der unlangst erzielten Verringerung des regionalen Einkommensungleichgewichts in Brasilien. Wir stellen Konvergenz-Indikatoren fur verschiedene regionale Einkommensquellen im Zeitraum von 1995 bis 2006 vor. Eine Dekomposition des Gini-Indikators ermoglicht die Identifizierung der jeweiligen Rolle dieser Einkommensquellen fur die Verringerung des regionalen Ungleichgewichts im betreffenden Zeitraum. Die Ergebnisse weisen darauf hin, dass sowohl die Produktivitat der Arbeitskrafte als auch die nicht raumlichen Regierungspolitiken - in erster Linie Veranderungen beim Mindestlohn und Programme fur Einkommenstransfers - als Grunde fur die Verringerung des regionalen Ungleichgewichts in dieser Periode durchaus eine Rolle spielen. Konvergenz Arbeitsproduktivitat Einkommenstransfer Mindestlohn Raumliche Auswirkungen nicht raumlicher Politiken Silveira Neto R. Da M. y Azzoni C. R. Politicas gubernamentales no espaciales y desigualdades de ingresos regionales en Brasil, Regional Studies. En este articulo utilizamos datos macro y micro para analizar el papel de los programas sociales en la reciente reduccion en las desigualdades de ingresos regionales de Brasil. Presentamos los indicadores de convergencia para diferentes fuentes de ingresos regionales en el periodo de 1995 a 2006. Una descomposicion del indice Gini permite identificar el papel de cada una de estas fuentes de ingresos con respecto a la reduccion de las desiguadades regionales durante este periodo. Los resultados destacan que tanto la productividad laboral como las politicas no espaciales del gobierno - principalmente los cambios de salario minimo y los programas de transferencias de ingresos - desempenan una funcion a la hora de explicar la reduccion de las desigualdades regionales durante este periodo. Convergencia Productividad laboral Transferencias de ingresos Salario minimo Efectos espaciales de politicas no espaciales.
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OBJECTIVE: To analyze whether the relationship between income inequality and human health is mediated through social capital, and whether political regime determines differences in income inequality and social capital among countries. METHODS: Path analysis of cross sectional ecological data from 110 countries. Life expectancy at birth was the outcome variable, and income inequality (measured by the Gini coefficient), social capital (measured by the Corruption Perceptions Index or generalized trust), and political regime (measured by the Index of Freedom) were the predictor variables. Corruption Perceptions Index (an indirect indicator of social capital) was used to include more developing countries in the analysis. The correlation between Gini coefficient and predictor variables was calculated using Spearman's coefficients. The path analysis was designed to assess the effect of income inequality, social capital proxies and political regime on life expectancy. RESULTS: The path coefficients suggest that income inequality has a greater direct effect on life expectancy at birth than through social capital. Political regime acts on life expectancy at birth through income inequality. CONCLUSIONS: Income inequality and social capital have direct effects on life expectancy at birth. The "class/welfare regime model" can be useful for understanding social and health inequalities between countries, whereas the "income inequality hypothesis" which is only a partial approach is especially useful for analyzing differences within countries.
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OBJECTIVE: To analyze cause-specific mortality rates according to the relative income hypothesis. METHODS: All 96 administrative areas of the city of São Paulo, southeastern Brazil, were divided into two groups based on the Gini coefficient of income inequality: high (>0.25) and low (<0.25). The propensity score matching method was applied to control for confounders associated with socioeconomic differences among areas. RESULTS: The difference between high and low income inequality areas was statistically significant for homicide (8.57 per 10,000; 95%CI: 2.60;14.53); ischemic heart disease (5.47 per 10,000 [95%CI 0.76;10.17]); HIV/AIDS (3.58 per 10,000 [95%CI 0.58;6.57]); and respiratory diseases (3.56 per 10,000 [95%CI 0.18;6.94]). The ten most common causes of death accounted for 72.30% of the mortality difference. Infant mortality also had significantly higher age-adjusted rates in high inequality areas (2.80 per 10,000 [95%CI 0.86;4.74]), as well as among males (27.37 per 10,000 [95%CI 6.19;48.55]) and females (15.07 per 10,000 [95%CI 3.65;26.48]). CONCLUSIONS: The study results support the relative income hypothesis. After propensity score matching cause-specific mortality rates was higher in more unequal areas. Studies on income inequality in smaller areas should take proper accounting of heterogeneity of social and demographic characteristics.
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The paper demonstrates that the ratio of the Yitzhaki (1994) to the conventional measure of between-group inequality is in general equal to one minus twice the weighted average probability that a random member of a richer (on average) group is poorer than a random member of a poorer (on average) group, and may therefore be interpreted as an index of stratification in its own right.
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In this paper we study a behavioral model of conflict that provides a basis for choosing certain indices of dispersion as indicators for conflict. We show that the (equilibrium) level of conflict can be expressed as an (approximate) linear function of the Gini coefficient, the Herfindahl-Hirschman fractionalization index, and a specific measure of polarization due to Esteban and Ray
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BACKGROUND: International comparisons of social inequalities in alcohol use have not been extensively investigated. The purpose of this study was to examine the relationship of country-level characteristics and individual socio-economic status (SES) on individual alcohol consumption in 33 countries. METHODS: Data on 101,525 men and women collected by cross-sectional surveys in 33 countries of the GENACIS study were used. Individual SES was measured by highest attained educational level. Alcohol use measures included drinking status and monthly risky single occasion drinking (RSOD). The relationship between individuals' education and drinking indicators was examined by meta-analysis. In a second step the individual level data and country data were combined and tested in multilevel models. As country level indicators we used the Purchasing Power Parity of the gross national income, the Gini coefficient and the Gender Gap Index. RESULTS: For both genders and all countries higher individual SES was positively associated with drinking status. Also higher country level SES was associated with higher proportions of drinkers. Lower SES was associated with RSOD among men. Women of higher SES in low income countries were more often RSO drinkers than women of lower SES. The opposite was true in higher income countries. CONCLUSION: For the most part, findings regarding SES and drinking in higher income countries were as expected. However, women of higher SES in low and middle income countries appear at higher risk of engaging in RSOD. This finding should be kept in mind when developing new policy and prevention initiatives.
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We use aggregate GDP data and within-country income shares for theperiod 1970-1998 to assign a level of income to each person in theworld. We then estimate the gaussian kernel density function for theworldwide distribution of income. We compute world poverty rates byintegrating the density function below the poverty lines. The $1/daypoverty rate has fallen from 20% to 5% over the last twenty five years.The $2/day rate has fallen from 44% to 18%. There are between 300 and500 million less poor people in 1998 than there were in the 70s.We estimate global income inequality using seven different popularindexes: the Gini coefficient, the variance of log-income, two ofAtkinson s indexes, the Mean Logarithmic Deviation, the Theil indexand the coefficient of variation. All indexes show a reduction in globalincome inequality between 1980 and 1998. We also find that most globaldisparities can be accounted for by across-country, not within-country,inequalities. Within-country disparities have increased slightly duringthe sample period, but not nearly enough to offset the substantialreduction in across-country disparities. The across-country reductionsin inequality are driven mainly, but not fully, by the large growth rateof the incomes of the 1.2 billion Chinese citizens. Unless Africa startsgrowing in the near future, we project that income inequalities willstart rising again. If Africa does not start growing, then China, India,the OECD and the rest of middle-income and rich countries diverge awayfrom it, and global inequality will rise. Thus, the aggregate GDP growthof the African continent should be the priority of anyone concerned withincreasing global income inequality.
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This paper presents a method for the measurement of changes in health inequality and income-related health inequality over time in a population.For pure health inequality (as measured by the Gini coefficient) andincome-related health inequality (as measured by the concentration index),we show how measures derived from longitudinal data can be related tocross section Gini and concentration indices that have been typicallyreported in the literature to date, along with measures of health mobilityinspired by the literature on income mobility. We also show how thesemeasures of mobility can be usefully decomposed into the contributions ofdifferent covariates. We apply these methods to investigate the degree ofincome-related mobility in the GHQ measure of psychological well-being inthe first nine waves of the British Household Panel Survey (BHPS). Thisreveals that dynamics increase the absolute value of the concentrationindex of GHQ on income by 10%.
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Critics of genetically modified (GM) crops often contend that their introduction enhances the gap between rich and poor farmers, as the former group are in the best position to afford the expensive seed as well as provide other inputs such as fertilizer and irrigation. The research reported in this paper explores this issue with regard to Bt cotton (cotton with the endotoxtin gene from Bacillus thuringiensis conferring resistance to some insect pests) in Jalgaon, Maharashtra State, India, spanning the 2002 and 2003 seasons. Questionnaire–based survey results from 63 non–adopting and 94 adopting households of Bt cotton were analyzed, spanning 137 Bt cotton plots and 95 non–Bt cotton plots of both Bt adopters and non–adopters. For these households, cotton income accounted for 85 to 88% of total household income, and is thus of vital importance. Results suggest that in 2003 Bt adopting households have significantly more income from cotton than do non–adopting households (Rp 66,872 versus Rp 46,351) but inequality in cotton income, measured with the Gini coefficient (G), was greater amongst non–adopters than adopters. While Bt adopters had greater acreage of cotton in 2003 (9.92 acres versus 7.42 for non–adopters), the respective values of G were comparable. The main reason for the lessening of inequality amongst adopters would appear to be the consistency in the performance of Bt cotton along with the preferred non–Bt cultivar of Bt adopters—Bunny. Taking gross margin as the basis for comparison, Bt plots had 2.5 times the gross margin of non–Bt plots of non–adopters, while the advantage of Bt plots over non–Bt plots of adopters was 1.6 times. Measured in terms of the Gini coefficient of gross margin/acre it was apparent that inequality was lessened with the adoption of Bunny (G = 0.47) and Bt (G = 0.3) relative to all other non–Bt plots (G = 0.63). Hence the issue of equality needs to be seen both in terms of differences between adopters and non–adopters as well as within each of the groups.
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This paper explores the relationship between the growth rate of the average income and income inequality using data at the municipal level in Sweden for the period 1992-2007. We estimate a fixed effects panel data growth model where the within-municipality income inequality is one of the explanatory variables. Different inequality measures (Gini coefficient, top income shares, and measures of inequality in the lower and upper ends of the income distribution) are also examined. We find a positive and significant relationship between income growth and income inequality, measured as the Gini coefficient and top income shares, respectively. In addition, while inequality at the upper end of the income distribution is positively associated with the income growth rate, inequality at the lower end of the income distribution seems to be negatively related to the growth rate. Our findings also suggest that increased income inequality enhances growth more in municipalities with a high level of average income than in those with a low level of average income.
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Our work is based on a simpliÖed heterogenous-agent shoppingtime economy in which economic agents present distinct productivities in the production of the consumption good, and di§erentiated access to transacting assets. The purpose of the model is to investigate whether, by focusing the analysis solely on endogenously determined shopping times, one can generate a positive correlation between ináation and income inequality. Our main result is to show that, provided the productivity of the interest-bearing asset in the transacting technology is high enough, it is true true that a positive link between ináation and income inequality is generated. Our next step is to show, through analysis of the steady-state equations, that our approach can be interpreted as a mirror image of the usual ináation-tax argument for income concentration. An example is o§ered to illustrate the mechanism.
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Several empirical studies in the literature have documented the existence of a positive correlation between income inequalitiy and unemployment. I provide a theoretical framework under which this correlation can be better understood. The analysis is based on a dynamic job search under uncertainty. I start by proving the uniqueness of a stationary distribution of wages in the economy. Drawing upon this distribution, I provide a general expression for the Gini coefficient of income inequality. The expression has the advantage of not requiring a particular specification of the distribution of wage offers. Next, I show how the Gini coefficient varies as a function of the parameters of the model, and how it can be expected to be positively correlated with the rate of unemployment. Two examples are offered. The first, of a technical nature, to show that the convergence of the measures implied by the underlying Markov process can fail in some cases. The second, to provide a quantitative assessment of the model and of the mechanism linking unemployment and inequality.
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This work investigates the effects of inflation on income distribution. We use a dynamic shopping-time model to show that a differentiated access to transacting technologies by poor and rich consumers is enough to generate a positive link between inflation and the Gini coefficient of income distribution.
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In this paper I claim that, in a long-run perspective, measurements of income inequality, under any of the usual inequality measures used in the literature, are upward biased. The reason is that such measurements are cross-sectional by nature and, therefore, do not take into consideration the turnover in the job market which, in the long run, equalizes within-group (e.g., same-education groups) inequalities. Using a job-search model, I show how to derive the within-group invariant-distribution Gini coefficient of income inequality, how to calculate the size of the bias and how to organize the data in arder to solve the problem. Two examples are provided to illustrate the argument.