Inequality measures are often used to summarise information about empirical income distributions. However , the resulting picture of the distribution and of the changes in the distribution can be severely distorted if the data are contaminated. The nature of this distortion will in general...

Lorenz curves and associated tools for ranking income distributions are commonly estimated on the assumption that full, unbiased samples are available. However, it is common to find income and wealth distributions that are routinely censored or trimmed. We derive the sampling distribution for a...

Drawing on recent work concerning the statistical robustness of inequality statistics we examine the sensitivity of poverty indices to data contamination using the concept of the influence function. We show that poverty and inequality indices have fundamentally different robustness properties,...

Lorenz curves and second-order dominance criteria are known to be sensitive to data contamination in the right tail of the distribution. We propose two ways of dealing with the problem: (1) Estimate Lorenz curves using parametric models for income distributions, and (2) Combine empirical...

Distributional dominance criteria are commonly applied to draw welfare in- ferences about comparisons, but conclusions drawn from empirical imple- mentations of dominance criteria may be inßuenced by data contamination. We examine a non-parametric approach to reÞning Lorenz-type comparisons...