Income Distribution, 2003

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Compare income distribution within or between countries. Based on data from Professor Xavier Sala-i-Martin.


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Mac version

14 thoughts on “Income Distribution, 2003

  1. I agree with the above comment. Data post 2000 for India would be very useful indeed. The rise in the mid section of the distribution is a little misleading, given the log scale on the x-axis (and the population growing anyway), indicating that not a lot has changed i.e. the relative cooperative levels are still the same – just a few zeros have been added across the population, which obviously does not change anything for the majority which interacts amongst themselves.

  2. Dear Gapminders,

    Your work is really important. Thank you.

    One point however. In many instances you log the x axis. This can be misleading to many people unfamiliar with transformations. Some may even be left with the feeling that global concerns such as inequality are rapidly dissolving.


  3. i got very curious about the pattern check barzil & mexico and notice the same pattern.

    great data.

  4. agree with Tom about the log scale; it distorts both the distribution and relative populations; eg the population of Indonesia is about 10 times that of Japan but it looks less than twice it on the motion chart.

    but the principle of graphing time as time is so sensible – might it be even more informative to map space to space – then map the indicator such as income (or, more appropriately, assets per person) to a colour gradient on a geographical map that varies over simulated time?

  5. What about expressing the income with respect to some indices such as the “consumer price index” instead of dollars.

    It would be more meaningful.

  6. Hey Folks,
    I tried to download the PC version of this presentation (Income Distribution, 2003 ), but it looks like you may have the link set up incorrectly. Both links point to the Mac version of the app. FYI.

  7. The time series data sets are so well presented using these visualization technique. I see some mention of Flash software in case of “Human Development Trend” and “Income Distribution”. I want to know some more about the software used and how these visualization has been developed.

  8. Well not to mention, the work is great. Thanks.

    And same as Surajit’s interest. I curious to know about the software.

  9. A parallel presentation of the proportion or % of each population at different levels of income over time, rather than the absolute number, would also be useful and would address some of the concerns about misinterpreting (in)equitable distribution between countries.

  10. Clearly what is not shown here are very large incomes i.e. the ever larger inequality of income distribution. Salaries, for example in many European countries as well as the US have not risen as much for the larger population as compared to the incomes of capital owners. To the right the incomes above 1 Mio. plus are not shown? Why? What does income mean on this site?

  11. Very cool. What’s missing is any entry in Europe – you probably need to add the EU-as-whole. It’s hardly a tiddler.

  12. Thank you for this graph. It is one of the most enlightening graphs on gapminder. I would love to see an updated version with more countries. Here are some ideas

    * It would be nice to be able to draw the data with a linear axis.
    * It would be nice to be able to draw the cumulative distribution graph that you use to get the GINI coeficient.
    * It would be to be able to draw a probability density graph coresponding to the graph that you use to calculate the GINI coeficient. (In other words. take the present graph, multiply the probabilities with the income, and then normalize the data)

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