This paper introduces in statistics the notion of the barycenter of the distribution of a non-negative random variable Y with a positive finite mean μY and the quantile function Q(x). The barycenter is denoted by μX and defined as the expected value of the random variable X having the...

This paper is a review of recent developments of parametric and non-parametric approaches to decompose inequality by subgroups, income sources, causal factors and other unit characteristics. Different methods of decomposing changes in poverty into growth, redistribution, poverty standard and...

The nature of global and regional income distributions and the extent of inequality are examined using country-level data on income distributions drawn from World Bank studies and the World Institute for Development Economics Research for the period 1993 - 2000. Beta-2 income distributions are...

This article presents a simple non-polynomial spline that may be used to construct Lorenz curves from grouped data. The spline is naturally convex and works by determining a series of piecewise segments that may be joined to give a smooth and continuous Lorenz curve. The method is illustrated...

This note documents the method for calculating Gini Coefficients in R using 2000 Census data. Many people have use this method for computing Ginis for ZCTA’s for example. You can find these estimates for both the 50 states, as well as all US counties and additional information about Gini...

This paper focuses on the importance data issues to the analysis of growth, poverty and economic inequality. We introduce a number of major databases frequently used in applied research on growth, poverty and global and international inequality. A discussion of data quality, data consistency,...

This paper focuses on the importance data issues to the analysis of growth, poverty and economic inequality. We introduce a number of major databases frequently used in applied research on growth, poverty and global and international inequality. A discussion of data quality, data consistency,...

The basic approach to estimating the Gini and extended Gini indices is to approximate the Lorenz curve by a number of linear segments, and then estimate the Gini coefficients as the areas (or weighted areas) between the linear segments and the 45-degree line. We show that the estimator for the...