TITLE:
Regression Analyses of Income Inequality Indices
AUTHORS:
Johan Fellman
KEYWORDS:
Gini Index, Income Distribution, Lorenz Curve, Regression Models, Trapezium Rule, Simpson Rule, Lagrange Rule, Newton-Cotes Method
JOURNAL NAME:
Theoretical Economics Letters,
Vol.8 No.10,
June
21,
2018
ABSTRACT: Scientists have analysed
different methods for numerical estimation of Gini coefficients. Using Lorenz
curves, various numerical integration attempts have been made to identify
accurate estimates. Central alternative methods have been the trapezium,
Simpson and Lagrange rules. They are all special cases of the Newton-Cotes
methods. In this study, we approximate the Lorenz curve by polynomial
regression models and integrate optimal regression models for numerical
estimation of the Gini coefficient. The attempts are checked on theoretical
Lorenz curves and on empirical Lorenz curves with known Gini indices. In all
cases the proposed methods seem to be a good alternative to earlier methods
presented in the literature.