Calculating Gini Coefficient - Unbiased Estimator

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The discussion centers on the calculation of the Gini coefficient and the existence of unbiased estimators for population coefficients. One source claims that sample Gini coefficients require multiplication to become unbiased, while another asserts that no sample statistic can serve as a general unbiased estimator for the population Gini coefficient. The conflict may arise from the interpretation of population mean (μ) versus sample mean (X-bar). Participants are exploring the implications of these differing statements and the role of the relative mean difference in this context. The conversation highlights the complexity and nuances involved in accurately estimating the Gini coefficient.
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Hi I was looking at how to calculate the GINI coefficient and saw two different statements from two websites.

Statement 1:
It has been shown that the sample Gini coefficients defined above need to be multiplied by in order to become unbiased estimators for the population coefficients -http://mathworld.wolfram.com/GiniCoefficient.html

Statement 2:
There does not exist a sample statistic that is in general an unbiased estimator of the population Gini coefficient, like the relative mean difference.-http://en.wikipedia.org/wiki/Gini_coefficient


My assumption is because wolfram is using Mu and not X-bar. Any thoughts/help?
 
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That's an interesting conflict. Perhaps the \mu mentioned on the Wolfram page is the population mean instead of the sample mean.
 
that's what I thought; however, the relative mean difference doesn't have a mu in it, and it doesn't have a unbiased estimator either
 
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