Talk:Gini coefficient

Limitations not convincing

Many of the arguments under the "limitations" section boil down to: the Gini measures inequality, not poverty (e.g. "for example, while both Bangladesh (per capita income of $1,693) and the Netherlands (per capita income of $42,183) had an income Gini index of 0.31 in 2010,[54] the quality of life, economic opportunity and absolute income in these countries are very different"; also the "Gini coefficient falls yet the poor get poorer, Gini coefficient rises yet everyone getting richer" section). But of course, it's *meant* to measure inequality, not poverty. I don't think this is a limitation of the measure. Perhaps it's a critique of people misusing the measure, but I'm not sure I've actually seen anyone misusing it in this way.

Countries by Gini Index

Main article: List of countries by income equality

A Gini coefficient above 50 is considered high; countries like Chile, USA, Russia, China, Bolivia, Mexico and Central America countries can be found in this category. A Gini coefficient of 30 or above is considered medium; countries like USA and Venezuela can be found in this category. A Gini coefficient lower than 30 is considered low; countries like Austria and Denmark can be found in this category.[55]

30 and above should be changed to 30 to 50. Then USA should be only in high gini index list.

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Gini index not the same as the Gini coefficient?

I'm currently reading "Machine Learning" by Peter Flach and I came across the footnote:

"When I looked up 'Gini index' on Wikipedia I was referred to a page describing the Gini coefficient, which - in a machine learning context - is a linear rescaling of the AUC to the interval [-1,1]. This is quite a different concept, and the only thing that the Gini index and the Gini coefficient have in common is that they were both proposed by the Italian statistician Corrado Gini, so it is good to be aware of potential confusion."

131.252.200.140 (talk) 21:31, 24 October 2015 (UTC)

Known distribution function

How can it be that the uniform distribution and the delta distribution produce the same index? Indeed how can it be that the explanation for the delta distributions says:

   The Dirac delta function represents the case where everyone has the same wealth (or income)

If the argument of the delta is the fraction of the population then the explanation is incorrect. If the argument of the delta is the income, then the explanation is correct. So it seems that the relation between the tables is an exchange of the axis. What ever it is, it would be good that some expert revise these tables and explain what is each of them properly. Kakila (talk) 21:55, 28 October 2015 (UTC)