Home > Graphics, income inequality > Global map of income inequality

Global map of income inequality

  1. henry1941
    August 20, 2012 at 11:27 pm

    What do these figures mean precisely? It looks as if Sweden it top of the league anyway, now I wonder why that is?

  2. Geoff Davies
    August 21, 2012 at 1:27 am

    According to the source, the measure is the GINI coefficient which, if I remember, is the ratio of the top/bottom income quintile, or is it decile? Anyway I think it’s much too coarse a measure.

    The idea that India and Indonesia, which have fabulously rich elites, have only moderate income equality is a bit of a joke. You need to look at the top 1%.

    • August 21, 2012 at 10:13 am

      http://en.wikipedia.org/wiki/Gini_coefficient#Definition

      “The Gini coefficient is usually defined mathematically based on the Lorenz curve, which plots the proportion of the total income of the population (y axis) that is cumulatively earned by the bottom x% of the population (see diagram). The line at 45 degrees thus represents perfect equality of incomes. The Gini coefficient can then be thought of as the ratio of the area that lies between the line of equality and the Lorenz curve (marked A in the diagram) over the total area under the line of equality (marked A and B in the diagram); i.e., G = A / (A + B).

      The Gini coefficient can theoretically range from 0 to 1; it is sometimes expressed as a percentage ranging between 0 and 100. In a finite population both extreme values are not quite reached.

      A low Gini coefficient indicates a more equal distribution, with 0 corresponding to complete equality, while higher Gini coefficients indicate more unequal distribution, with 1 corresponding to complete inequality.”

    • Alice
      August 21, 2012 at 11:20 am

      The gini co-efficient measures the widest area between the lorenz curve and the line of equality. If it is zero it means the bottom ten percent earn 10% of the income, and twenty percent of people earn twenty percent of the income and ninety percent of people earn 90% of all income etc.
      In the example above the lorenz curve will correspond to the line of equality and there will be zero distance between them, hence the gini will be zero.
      However if the first cumm 10% of all people earn only cumm .05% of all income and so on then the lorenz curve will be lower than the line of equality hence the Gini will be higher.

      The gini is only one measure of inequality and there are others that supplement its use like Theils T statistic.

      The top 1% can be a well camouflaged distortion. So well camouflaged you may not even find it in the income statistics released by government departments at all (apparently privacy rules work to keep the owners of that income hidden totally). So the Gini in the US and other countries may actually be worse than we think.

      In addition there are people missing at the bottom eg in jail or homeless and just dont appear in income counts (and dont forget the people who hide their incomes – cash at the bottom or tax havens at the top)

  3. Deniz Kellecioglu
    August 22, 2012 at 9:49 am

    Please note that dataset should be assessed very cautiously. The data points range over a wide time period, mostly over 2000-2012, but some of them go all the way back to the 1990s. I am aware of some important updates and some that should have happened. Also, note that the value for USA is from 2007 – just before the onset of the financial meltdown.

    Unfortunately, it is difficult to obtain datasets on poverty and inequality, especially at the global level. For some reason (irony) governments are not as interested in statistics for poverty and inequality as in GDP and other macroeconomic variables. Plus, there are consultancy firms producing weekly (!) GDP growth updates.

    The inequality in statistics.

  4. Alice
    August 22, 2012 at 10:15 am

    Yup – Deniz. They have been trying to kill the measurement of inequality for only about…og twenty years and if they coukdnt get away with that – then kill the science that used to study it. Economic historians.

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