An upper bound and a characterization for Gini's mean difference based on correlated random variables

In this paper, we obtain an upper bound for the Gini mean difference based on mean, variance and correlation for the case when the variables are correlated. We also derive some closed-form expressions for the Gini mean difference when the random variables have an absolutely continuous joint distribution. We then examine some particular examples based on elliptically contoured distributions, and specifically multivariate normal and Student-$t$ distributions.

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