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Decomposition of the Gini index by income source for aggregated data and its applications

The Gini index is well-known for a single measure of inequality. The purpose of this article is to explore a matrix structure of the Gini index in a setting of multiple source income. Using matrices, we analyze the decomposition of the Gini index by income source and derive an explicit formula for t...

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Detalles Bibliográficos
Autor principal: Shao, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7847717/
https://www.ncbi.nlm.nih.gov/pubmed/33551574
http://dx.doi.org/10.1007/s00180-021-01069-4
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author Shao, Bin
author_facet Shao, Bin
author_sort Shao, Bin
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description The Gini index is well-known for a single measure of inequality. The purpose of this article is to explore a matrix structure of the Gini index in a setting of multiple source income. Using matrices, we analyze the decomposition of the Gini index by income source and derive an explicit formula for the factors in terms of the associated percentile levels based on aggregated data reporting. Each factor is shown to be the sums of the two split off parts of the income within a percentile bracket. Both have unequalizing and equalizing contribution to the total inequality, respectively. We use R code and apply the methodology to several data sets including a sample of European aggregated income reporting in 2014 for illustration. A byproduct from the Gini decomposition provides a matrix approach to the decomposition of the associated Lorenz curve in terms of the density distribution matrix and a Toeplitz matrix.
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spelling pubmed-78477172021-02-01 Decomposition of the Gini index by income source for aggregated data and its applications Shao, Bin Comput Stat Original Paper The Gini index is well-known for a single measure of inequality. The purpose of this article is to explore a matrix structure of the Gini index in a setting of multiple source income. Using matrices, we analyze the decomposition of the Gini index by income source and derive an explicit formula for the factors in terms of the associated percentile levels based on aggregated data reporting. Each factor is shown to be the sums of the two split off parts of the income within a percentile bracket. Both have unequalizing and equalizing contribution to the total inequality, respectively. We use R code and apply the methodology to several data sets including a sample of European aggregated income reporting in 2014 for illustration. A byproduct from the Gini decomposition provides a matrix approach to the decomposition of the associated Lorenz curve in terms of the density distribution matrix and a Toeplitz matrix. Springer Berlin Heidelberg 2021-01-31 2021 /pmc/articles/PMC7847717/ /pubmed/33551574 http://dx.doi.org/10.1007/s00180-021-01069-4 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Shao, Bin
Decomposition of the Gini index by income source for aggregated data and its applications
title Decomposition of the Gini index by income source for aggregated data and its applications
title_full Decomposition of the Gini index by income source for aggregated data and its applications
title_fullStr Decomposition of the Gini index by income source for aggregated data and its applications
title_full_unstemmed Decomposition of the Gini index by income source for aggregated data and its applications
title_short Decomposition of the Gini index by income source for aggregated data and its applications
title_sort decomposition of the gini index by income source for aggregated data and its applications
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7847717/
https://www.ncbi.nlm.nih.gov/pubmed/33551574
http://dx.doi.org/10.1007/s00180-021-01069-4
work_keys_str_mv AT shaobin decompositionoftheginiindexbyincomesourceforaggregateddataanditsapplications