Abstract:
Methods to measure income inequality have for quite some time now been an important subject in statistics and econometric research. Some measures are based on incomplete moments or incomplete conditional moments and they take into consideration the shape of the income distribution but suffer sometimes from low efficiency and or lack or robustness. On the other hand, in recent years a new inferential method called “the probability weighted moments” (PWM) was introduced and studies as a competitor to more traditional inferential methods such as the method of moments or the maximum likelihood method. A class of generalized measures of income inequalities using the PWM are introduced and studied. The new measures are also shown to characterize the income distributions well.
