essay about the limitation of the gini coefficient
Read the material bellow. And write a 4 pages essay to support the idea —Gini coefficient has many limitations.
Use 3 main points and examples to explain.
Some useful main points:1. small sample bias, 2. the original goal to set Gini coefficient is for EU countries, not suitable for every countries in the world. 3. People always use Gini coefficient to judge a country’s inequality, but ignore many other standard.(like Pew research center–popular will and feeling, UNESCO–education problem) 4.You could also use ur own opinion.
Tip:You can find the bellow material in wikipedia, Gini limitation part, and find some useful material to support the essay.
But avoid plagiarism.
Material:
- Small sample bias – sparsely populated regions more likely to have low Gini coefficient
Gini index has a downward-bias for small populations.[58] Counties or states or countries with small populations and less diverse economies will tend to report small Gini coefficients. For economically diverse large population groups, a much higher coefficient is expected than for each of its regions. Taking world economy as one, and income distribution for all human beings, for example, different scholars estimate global Gini index to range between 0.61 and 0.68.[10][11] 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) for the same distribution. Philippe Monfort has shown that using inconsistent or unspecified granularity limits the usefulness of Gini coefficient measurements.[59]
The Gini coefficient measure gives different results when applied to individuals instead of households, for the same economy and same income distributions. If household data is used, the measured value of income Gini depends on how the household is defined. When different populations are not measured with consistent definitions, comparison is not meaningful.
Deininger and Squire (1996) show that income Gini coefficient based on individual income, rather than household income, are different. For example, for the United States, they find that the individual income-based Gini index was 0.35, while for France it was 0.43. According to their individual focused method, in the 108 countries they studied, South Africa had the world’s highest Gini coefficient at 0.62, Malaysia had Asia’s highest Gini coefficient at 0.5, Brazil the highest at 0.57 in Latin America and Caribbean region, and Turkey the highest at 0.5 in OECD countries.[60]
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