Estimation of the Gini coefficient based on two quantiles.

Abstract

Based on the Palma proposition and the Lorenz fitting curve, this paper estimates the sample Gini coefficient using the income share of the top 10% and bottom 40% of the population. Empirical research shows that the absolute error between the estimated value and sample Gini coefficient is within a hundredth. Monte Carlo simulation shows that the new method has good performance and robustness for estimating Gini coefficients with different sample sizes and different inequality levels. Using the two quantiles in the deciles to estimate the sample Gini coefficient and the Lorenz fitting curve is a practical method.