A new class of inequality measures based on weighted conditional incomplete moments

Abstract

In the previous few decades, inequality measurements have particularly been interested in statistics and economics research. Among the foremost widely used measures of inequality are the measures based on complete, incomplete, and conditional moments. In this investigation, we introduce a new class of inequality measures based on weighted conditional incomplete moments. Also, we compare the new class of measures with the class of inequality measures based on weighted incomplete moments introduced by Abouelmagd and Ahmed (2014). The new class measures are shown to include many previously discussed ones such as Butler and McDonald (1987), Ahmad (1998), Lorenz measures as well as others. A statistical analysis of the new measures is presented. The new measures also characterize the income distributions well. We study these new measures under Pareto distribution. A real data application is given to illustrate the benefits of the proposed inequality measures based on weighted conditional over the previous measures.