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Gini coefficients are simple, and this simplicity can lead to oversights and can confuse the comparison of different populations; for example, while both Bangladesh (per capita income of $1,693) and the Netherlands (per capita income of $42,183) had an income Gini coefficient of 0.31 in 2010, [72] the quality of life, economic opportunity and ...
A complete handout about the Lorenz curve including various applications, including an Excel spreadsheet graphing Lorenz curves and calculating Gini coefficients as well as coefficients of variation. LORENZ 3.0 is a Mathematica notebook which draw sample Lorenz curves and calculates Gini coefficients and Lorenz asymmetry coefficients from data ...
Online calculator computes the Gini Coefficient, plots the Lorenz curve, and computes many other measures of concentration for any dataset Online calculator: Online (example for processing data from Table HINC-06 [ permanent dead link ] , U.S. Census Bureau, 2007: Income Distribution to $250,000 or More for Households) and downloadable ...
A more frequently encountered inequality measure is the Gini coefficient which is based on the summation, over all income-ordered population-percentiles, of the cumulative income up to each percentile. That sum is divided by the maximum value that it could have (its value with complete equality), to express it as a percentage of its maximum ...
This is a list of countries and territories by income inequality metrics, as calculated by the World Bank, UNU-WIDER, OCDE, and World Inequality Database, based on different indicators, like Gini coefficient and specific income ratios.
The Gini coefficient for a continuous probability distribution takes the form: G = 1 μ ∫ 0 ∞ F ( 1 − F ) d x {\displaystyle G={1 \over {\mu }}\int _{0}^{\infty }F(1-F)dx} where F {\displaystyle F} is the CDF of the distribution and μ {\displaystyle \mu } is the expected value.
The Gini coefficient is a measure of the deviation of the Lorenz curve from the equidistribution line which is a line connecting [0, 0] and [1, 1], which is shown in black (α = ∞) in the Lorenz plot on the right. Specifically, the Gini coefficient is twice the area between the Lorenz curve and the equidistribution line.
The relative mean absolute difference is equal to twice the Gini coefficient which is defined in terms of the Lorenz curve. This relationship gives complementary perspectives to both the relative mean absolute difference and the Gini coefficient, including alternative ways of calculating their values.