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Users of the R data analysis software can install the "ineq" package which allows for computation of a variety of inequality indices including Gini, Atkinson, Theil. A MATLAB Inequality Package Archived 2008-10-04 at the Wayback Machine , including code for computing Gini, Atkinson, Theil indexes and for plotting the Lorenz Curve.
The inequality income metric should be independent of the aggregate level of income. This may be stated as: = where α is a positive real number. Population independence Similarly, the income inequality metric should not depend on whether an economy has a large or small population.
Income from black market economic activity is not included. The Gini coefficient is a number between 0 and 1 or 100, where 0 represents perfect equality (everyone has the same income). Meanwhile, an index of 1 or 100 implies perfect inequality (one person has all the income, and everyone else has no income).
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The findings from the index were then used in the World Economic Forum's Global Social Mobility Report 2020, which provided recommendations for governments and businesses. Researchers have used the index to analyze income inequality and have determined reasons for countries to improve social mobility.
CBO chart illustrating the percent reduction in income inequality due to Federal taxes and income transfers from 1979 to 2011 [16] Proposed tax plan payment rates by income group as a percentage of income, including mandatory health insurance, of four 2020 United States presidential election candidates
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. In 2018 U.S. income inequality as measured by the Gini index was close to the highest recorded values ever. [15] [16]