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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] The information was tabulated in 2019 from data from the American Community Survey (ACS) conducted by the US Census Bureau.
The states of Utah, Alaska and Wyoming have a market income Gini coefficient that is 10% lower than the average, while Washington D.C. and Puerto Rico are 10% higher. After-tax, the Federal Reserve estimated that 34 states in the US have a Gini index between 30 and 35, with Maine the lowest. [198]
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 ...
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).
Post-tax Gini coefficient: 0.39. Unemployment rate: 4.4%. GDP per capita: $53 632. Poverty rate: 11.1%. [43] Low unemployment rate and high GDP are signs of the health of the U.S. economy. But there is almost 18% of people living below the poverty line and the Gini coefficient is quite high. That ranks the United States 9th income inequal in ...
The Wealth Gini coefficients from 2008 are based on a working paper published by the National Bureau of Economic Research. [5] The Wealth Gini numbers for 2018, 2019, and 2021 come from the Global Wealth Databook by Credit Suisse. [6] [7] [8] * indicates "Wealth inequality in COUNTRY or TERRITORY" or "Income inequality in COUNTRY or TERRITORY ...
Compared to the Gini coefficient in practice, CV puts higher weight on the right tail of the scale, making it sensitive to the rich. Coefficient of variation may be a suitable choice of measure if the goal of a study is to analyze the wealth concentration at the top of the distribution. [17] [18]
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 ...