GiniInc: a Stata package for measuring inequality from incomplete income and survival data

Quite often, observed income and survival data are incomplete due to left- or right-censoring or truncation. Measuring inequality, for instance by the Gini index of concentration, from incomplete data like this will produce biased results. We describe the Stata package GiniInc, which contains three independent functions to estimate the Gini concentration index under different conditions. First, survgini computes a test statistic for the comparison of two (survival) distributions based on the non-parametric estimation of the restricted Gini index for right-censored data, using both asymptotic and permutation inference. Second, survbound computes non-parametric bounds for the unrestricted Gini index from censored data. Finally, survlsl implements maximum likelihood estimation for three commonly used parametric models to estimate the unrestricted Gini Index, both from censored and truncated data. We briefly discuss the methods, describe the package, and illustrate its use through simulated data and examples from an oncology and a historical income study.