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Gini Index: True or False

Does a country’s Gini index have any correlation to its number of people per square mile?

The Gini index has been a statistic relied upon to indicate the distribution of wealth among the citizens of a country since developed by Italian statistician and sociologist Corrado Gini in 1912. The index is based on a scale from 0 to 1 where a 0 would mean “perfect income equality” while 1 would imply the opposite or all the money resting with a single citizen.

According to tradingeconomics.com, “The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.”

To see whether GINI index was an apt statistic for its purpose, it is apt to compare it to each country’s population per square mile as population density as land is obtainable by wealth and is a basic necessity for all humans.

The plot indicates that there is no correlation between a country’s GINI index and number of people per square mile. Regardless of the GINI index, the population density seems to be relatively similar. There are outliers representing low GINI index coupled with high population density which signifies a highly populated area with a low GINI index. This may represent a P5 nation or any highly populated country with high levels of infrastructure (ex: United States of America). However, these outliers provide little to no meaning as these countries are a rarity and therefore are not represented of the world. It is also clearly visible that there are GINI indices that have multiple varying data points regarding the number of people per square mile. This occurrence signifies minimal connection between the two variables.

To support this data, limitations have already been found regarding the premise of this index. According to the Human Sciences Research Council, one of the main limitations is the fact that the index is derived from income. The Gini Index is different when you take household incomes instead of individual incomes in comparison to taking individual incomes into consideration instead of household incomes. This subjectivity has sparked debate on whether the statistic can be believed upon.

Furthermore, the Human Sciences Research Council  mention that the informal sector of each nation is not taken into consideration when using the Gini index. The informal sector is the biggest sector of any less economically developed countries due to the lack of corporations, minimal technology, and consequent importance of man labor in its GDP per capita. This makes any LEDCs data a poor reflection of the actual situation in that nation. This is even before taking the variation income tax between countries that is not taken into consideration in the Gini index as well.

So, what pros does the GINI index hold when discussing economic stability and wealth distribution in a nation? The GINI index should not be relied upon to form predictions as they would merely be conjectures of little meaning and hence, cease in usage.

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COMMENTS: 6
  1. April 28, 2019 by Samiha.Datta Reply

    Nice article, Tarun! It was really cool to learn about the Gini Index, and I found your comparison of it to number of people per square mile really interesting. Your argument for why the Gini Index should “cease in usage” was quite compelling.

  2. April 28, 2019 by Eva Batelaan Reply

    You did a great gob of arguing the inadequacies of the GINI index. Your article was very informative and well organized.

  3. April 29, 2019 by Annie Ma Reply

    Wow, this is really cool! I’d never heard about the Gini index until now, so thanks for teaching me something new!

    • April 29, 2019 by Haley Reply

      I’d never heard of it either! Thanks for sharing – what an interesting comparison between density and economic distribution.

  4. April 30, 2019 by Nikhil Reply

    I had heard about the Gini index, so it was interesting to read more about it.

  5. May 02, 2019 by Joseph.Wang Reply

    Very interesting article! I’ve never heard of the GINI index, so your explanation and interpretation of the data is very informative and enlightening.

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