African Journal of Applied Statistics

Measuring inequality: application of semi-parametric methods to real life data

Tchilabalo Abozou KPANZOU, Tertius DE WET, and Gane Samb LO

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A number of methods have been introduced in order to measure the inequality in various situations such as income and expenditure. In order to curry out statistical inference, one often needs to estimate the available measures of inequality. Many estimators are available in the literature, the most used ones being the non parametric estimators. Kpanzou and De Wet (2011) has developed semi-parametric estimators for measures of inequality and showed that these are very appropriate especially for heavy tailed distributions. In this paper we apply such semi-parametric methods to two practical data sets and show how they compare to the non parametric estimators. A guidance is also given on the choice of parametric distributions to fit in the tails of the data.


Des méthodes ont été introduites en vue de mesurer l'inégalité dans diverses situations comme, par exemple, dans la répartition du revenu. Pour faire de l'inférence statistique, l'on a souvent besoin d'estimer les mesures d'inégalité disponibles. Des estimateurs ont été developpés, les plus utilisés étant les estimateurs non paramétriques. Kpanzou and De Wet (2011) a developpé des estimateurs semi-paramétriques, estimateurs qui sont beaucoup plus appropriés surtout quand l'on a à traiter avec les distributions à queue épaisse. Dans cet article, nous appliquons ces estimateurs semi-paramétriques à des données de la vie réelle et les comparons à leurs équivalents non paramétriques. Une indication est aussi donnée sur le choix des distributions paramétriques à ajuster à la queue.

Article information

Afr. J. Appl. Stat., Volume 4, Number 1 (2017), 157-164.

First available in Project Euclid: 16 May 2019

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Digital Object Identifier

Primary: 62F10: Point estimation 62G05: Estimation 62P05: Applications to actuarial sciences and financial mathematics

income distribution inequality measures confidence intervals extreme value theory


KPANZOU, Tchilabalo Abozou; DE WET, Tertius; LO, Gane Samb. Measuring inequality: application of semi-parametric methods to real life data. Afr. J. Appl. Stat. 4 (2017), no. 1, 157--164. doi:10.16929/ajas/2017.157.207.

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