Decomposition of the Gini coefficient using Stata

The Gini coefficient is widely used to measure inequality in the distribution of income, consumption, and other welfare proxies. Decomposing this measure can help you understand the determinants of inequality. In this presentation, I will use income data from Mexico to illustrate a user-written command, descogini, that implements the Gini decomposition proposed by Lerman and Yitzhaki (1985, Review of Economics and Statistics 67: 151–156). Using this command, the Gini coefficient for total income can be decomposed in three terms: how important the income source is with respect to total income; how equally or unequally distributed the income source is; and how the income source and the distribution of total income are correlated. In the presentation, I will also illustrate how to obtain the impact that a marginal change in a particular income source will have on total income inequality, as well as how to obtain bootstrap standard errors.