## America's Insane Gini Coefficients

#### Geege Schuman stashed this in Economics

Source: http://www.businessinsider.com/americas-...

What's even scarier is that this data is from 2007 CBO data— the Great Recession is likely to have made these curves even steeper.

**Stashed in:** Economics!, Wealth!, Poverty, America, Mathy

Right! What's a Gini coefficient?

You're the Math One.

The **Gini coefficient** (also known as the **Gini index** or **Gini ratio**) (/ dʒ i n i /) is a measure of statistical dispersion intended to represent the income distribution of a nation's residents. It was developed by the Italian statistician and sociologist Corrado Gini and published in his 1912 paper "Variability and Mutability" (Italian: *Variabilità e mutabilità*).[1] [2]

The Gini coefficient measures the inequality among values of a frequency distribution (for example levels of income). A Gini coefficient of zero expresses perfect equality, where all values are the same (for example, where everyone has the same income). A Gini coefficient of one (or 100%) expresses maximal inequality among values (for example where only one person has all the income).[3] [4] However, a value greater than one may occur if some persons have negative income or wealth. For larger groups, values close to or above 1 are very unlikely in practice.

Gini coefficient is commonly used as a measure of inequality of income or wealth.[5] For OECD countries, in the late 2000s, considering the effect of taxes and transfer payments, the income Gini coefficient ranged between 0.24 to 0.49, with Slovenia the lowest and Chile the highest.[6] The countries in Africa had the highest pre-tax Gini coefficients in 2008–2009, with South Africa the world's highest at 0.7.[7] [8] The global income inequality Gini coefficient in 2005, for all human beings taken together, has been estimated to be between 0.61 and 0.68 by various sources.[9] [10]

There are some issues in interpreting a Gini coefficient. The same value may result from many different distribution curves. The demographic structure should be taken into account. Countries with an aging population, or with a baby boom, experience an increasing pre-tax Gini coefficient even if real income distribution for working adults remains constant. Scholars have devised over a dozen variants of the Gini coefficient.[11] [12] [13]

http://en.m.wikipedia.org/wiki/Gini_coefficient

Guessing the U.S. housing crisis, job losses and student debt created a lot households with negative income.

And health care costs. Geez, it seems like it's more expensive to live in this country than it ever was.

3:27 PM Dec 15 2013