A New measure of income inequality

Abstract

A new measure of income inequality that captures the heavy tail behavior of the income distribution is proposed. We discuss two different approaches to find the estimators of the proposed measure. We show that these estimators are consistent and have an asymptotically normal distribution. We also obtain a jackknife empirical likelihood (JEL) confidence interval of the income inequality measure. A Monte Carlo simulation study is conducted to evaluate the finite sample properties of the estimators and JEL-based confidence inerval. Finally, we use our measure to study the income inequality of three states in India.