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The Italian statistician Corrado Gini developed the Gini coefficient and published it in his 1912 paper Variabilità e mutabilità (English: variability and mutability). [16] [17] Building on the work of American economist Max Lorenz, Gini proposed using the difference between the hypothetical straight line depicting perfect equality and the actual line depicting people's incomes as a measure ...
A score of "0" on the Gini coefficient represents complete equality, i.e. every person has the same income. A score of 1 would represent the case in which one person would have all the income and others would have none. Therefore, a lower Gini score is roughly associated with a more equal distribution of income and vice versa.
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 1918 household Gini coefficient (excluding capital gains) was 40.8. A brief but sharp depression in 1920-1921 reduced incomes. Income inequality rose from 1913 to peaks in 1926 (1928 Gini 48.9, 1936 Gini 45.5) and 1941 (Gini 43.1), after which war-time measures of the Roosevelt administration began to equalize the income distribution. [20]
The Gini coefficient (also known as the Gini index or Gini ratio), is a measure of statistical dispersion intended to represent the income inequality, wealth inequality, or consumption inequality within a nation or a social group. It measures the inequality among the values of a frequency distribution, such as levels of income.
GDP is the mean (average) wealth rather than median (middle-point) wealth. Countries with a skewed income distribution may have a relatively high per-capita GDP while the majority of its citizens have a relatively low level of income, due to concentration of wealth in the hands of a small fraction of the population. See Gini coefficient.
Coefficient of variation (CV) used as a measure of income inequality is conducted by dividing the standard deviation of the income (square root of the variance of the incomes) by the mean of income. Coefficient of variation will be therefore lower in countries with smaller standard deviations implying more equal income distribution.
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 ...