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Gini decomposition by gender: Turkish case

Kaya, Ezgi 2010. Gini decomposition by gender: Turkish case. Brussels Economic Review 53 (1) , pp. 59-83.

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Abstract

The aim of this paper is to reveal the gender inequalities in income distribution for Turkey by using decomposition of Gini coefficient, a common income inequality measure. A new decomposition method, Dagum's approach for decomposition of the Gini coefficient is used in the study. In the analysis, the decomposition of the Gini coefficient by gender is applied to Turkish individuals twice. First Gini coefficient for total disposable income is decomposed to examine the gender disparities in individual income distribution. Here disposable income inequality is examined on the basis of female-male, illiterate-primary-secondary-tertiary education levels, urban-rural areas, agricultural-non-agricultural sectors. Second, Gini coefficient for wage-income is partitioned to its components to define wage gap between males and females. The wage-income inequality is also examined on the basis of gender, education levels, urban-rural areas, as well as public, private and state economic enterprises (SEE). The data used here are the incomes of Turkish individuals and come from 2005 Household Budget Survey conducted by Turkish Statistical Institute (TURKSTAT). The decomposition of Gini coefficient presented that the contribution of inequalities between genders is more influential in income distribution than in wage-income distribution and the portion of inequality between genders in other income factors to the total income inequality is more than it is in wage-income. Lastly, another class of decomposable income inequality measures, generalized entropy indexes are decomposed by gender and the differences between Gini decomposition and generalized entropy indexes are examined.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Publisher: Universite Libre de Bruxelles
Date of First Compliant Deposit: 15 March 2017
Last Modified: 04 Jun 2017 09:45
URI: http://orca.cf.ac.uk/id/eprint/99019

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