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Originally Posted by
tonton 
Basic standard of living for the majority of citizens.
Will you please objectively quantify "basic standard of living"?
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The weaknesses of Gini largely lie in its relative nature: It loses information about absolute national and personal incomes. Countries may have identical Gini coefficients, but differ greatly in wealth. Basic necessities may be equal (available to all) in a rich country, while in the poor country, even basic necessities are unequally available. In addition, Gini does not address causes: income equality may reflect differences in opportunity, or capability. For example, some countries may have a social class structure that presents barriers to upward mobility; some people may have more skills than others. By measuring inequality in income, the Gini ignores the differential efficiency of use of household income. By ignoring wealth (except as it contributes to income) the Gini can create the appearance of inequality when the people compared are at different stages in their life. Wealthy countries (e.g. Sweden) can appear more equal, yet have high Gini coefficients for wealth (for instance 77% of the share value owned by households is held by just 5% of Swedish shareholding households).[13][dead link] These factors are not assessed in income-based Gini.
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For a large, economically diverse country, a much higher coefficient will be calculated for the country as a whole than will be calculated for each of its regions. (The coefficient is usually applied to measurable nominal income rather than local purchasing power, tending to increase the calculated coefficient across larger areas.)
As is the case for any single measure of a distribution, economies with similar incomes and Gini coefficients can still have very different income distributions. This results from differing shapes of the Lorenz curve.
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Too often only the Gini coefficient is quoted without describing the proportions of the quantiles used for measurement. As with other inequality coefficients, the Gini coefficient is influenced by the granularity of the measurements. For example, five 20% quantiles (low granularity) will usually yield a lower Gini coefficient than twenty 5% quantiles (high granularity) taken from the same distribution. This is an often encountered problem with measurements.
Care should be taken in using the Gini coefficient as a measure of egalitarianism, as it is properly a measure of income dispersion. For example, if two equally egalitarian countries pursue different immigration policies, the country accepting a higher proportion of low-income or impoverished migrants will be assessed as less equal (gain a higher Gini coefficient).
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Comparing income distributions among countries may be difficult because benefits systems may differ. For example, some countries give benefits in the form of money while others give food stamps, which might not be counted by some economists and researchers as income in the Lorenz curve and therefore not taken into account in the Gini coefficient. Income in the United States is counted before benefits, while in France it is counted after benefits, which may lead the United States to appear somewhat more unequal vis-a-vis France.
