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A Simple Consistent Nonparametric Estimator of the Lorenz Curve

Yu Yvette Zhang ^a

Ximing Wu ^a

Qi Li ^b,c

^aDepartment of Agricultural Economics, Texas A&M University, College Station, TX, U.S.A.

^bDepartment of Economics, Texas A&M University, College Station, TX, U.S.A.

^cDepartment of Economics, Tsinghua University, Beijing, People’s Republic of China

Essays in Honor of Aman Ullah

ISBN: 978-1-78560-787-5, eISBN: 978-1-78560-786-8

Publication date: 23 June 2016

Abstract

We propose a nonparametric estimator of the Lorenz curve that satisfies its theoretical properties, including monotonicity and convexity. We adopt a transformation approach that transforms a constrained estimation problem into an unconstrained one, which is estimated nonparametrically. We utilize the splines to facilitate the numerical implementation of our estimator and to provide a parametric representation of the constructed Lorenz curve. We conduct Monte Carlo simulations to demonstrate the superior performance of the proposed estimator. We apply our method to estimate the Lorenz curve of the U.S. household income distribution and calculate the Gini index based on the estimated Lorenz curve.

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Citation

Zhang, Y.Y., Wu, X. and Li, Q. (2016), "A Simple Consistent Nonparametric Estimator of the Lorenz Curve", Essays in Honor of Aman Ullah (Advances in Econometrics, Vol. 36), Emerald Group Publishing Limited, Leeds, pp. 635-653. https://doi.org/10.1108/S0731-905320160000036028

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Emerald Group Publishing Limited

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