<abstract xmlns="http://www.w3.org/1999/xhtml"><p> We propose a convenient method of estimating the within-group, between-group, and interaction components of the overall traditional Gini index from the estimated parameters of underlying “trick regression models” involving known forms of heteroscedasticity related to income. Two illustrative examples involving both real and artificial data are provided. The issue of appropriate standard error of the subgroup decomposition is also discussed.</p></abstract>

We propose a convenient method of estimating the within-group, between-group, and interaction components of the overall traditional Gini index from the estimated parameters of underlying “trick regression models” involving known forms of heteroscedasticity related to income. Two illustrative examples involving both real and artificial data are provided. The issue of appropriate standard error of the subgroup decomposition is also discussed.

A Convenient Method of Decomposing the Gini Index by Population Subgroups

Department of Economics, Brock University, 500 Glenridge Avenue, St. Catharines, Ontario, Canada L2S 3A1

Journal of Official Statistics

{"article-title":"A Convenient Method of Decomposing the Gini Index by Population Subgroups"}

We propose a convenient method of estimating the within-group, between-group, and interaction components of the overall traditional Gini index from the...

A Convenient Method of Decomposing the Gini Index by Population Subgroups

Online veröffentlicht: 14. Feb. 2014

Seitenbereich: 91 - 105

DOI: https://doi.org/10.2478/jos-2014-0005

Schlüsselwörter
Subgroup decomposition, Stochastic approach, Gini index, pseudo-Gini

This content is open access.

A Convenient Method of Decomposing the Gini Index by Population Subgroups

Online veröffentlicht: 14. Feb. 2014

Seitenbereich: 91 - 105

DOI: https://doi.org/10.2478/jos-2014-0005

SchlüsselwörterSubgroup decomposition, Stochastic approach, Gini index, pseudo-Gini

This content is open access.

Schlüsselwörter
Subgroup decomposition, Stochastic approach, Gini index, pseudo-Gini