A Note on the asymptotic equivalence of jackknife and linearization variance estimation for the Gini Coefficient

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Description/Abstract

The Gini coefficient has proved valuable as a measure of income inequality. In cross-sectional studies of the Gini coefficient, information about the accuracy of its estimate is crucial. We show how to use jackknife and linearization to estimate the variance of the Gini coefficient, allowing for the effect of the sampling design. The aim is to show the asymptotic equivalence (or consistency) of the generalised jackknife estimator and the Taylor linearization estimator for the variance of the Gini coefficient. A brief simulation study supports our findings.