We examine the statistical performance of inequality indices in the presence of extreme values in the data and show that these indices are very sensitive to the properties of the income distribution. Estimation and inference can be dramatically affected, especially when the tail of the income...

A random sample drawn from a population would appear to offer an ideal opportunity to use the bootstrap in order to perform accurate inference, since the observations of the sample are IID. In this paper, Monte Carlo results suggest that bootstrapping a commonly used index of inequality leads to...

We examine the sensitivity of estimates and inequality indices to extreme values, in the sense of their robustness properties and of their statistical performance. We establish that these measures are very sensitive to the properties of the income distribution. Estimation and inference can be...