Michele Zenga
Titoli dell'autore
Decomposition by sources, by subpopulations and joint
decomposition by subpopulations and sources of Gini, Bonferroni
and Zenga 2007 inequality indexes
digital
Anno:
2021
Recently, the authors have illustrated the decompositions by subpopulations of the Gini (1914), Bonferroni (1930) and Zenga (2007) inequality measures. These decompositions were illustrated by a numerical example involving non-overlapping subpopulations and by a numerical example involving overlapping subpopulations...
Gratis
Decomposition by subpopulations of Gini, Bonferroni
and Zenga inequality measures
digital
Anno:
2020
This paper presents a common framework for the decompositions by subpopulations of Gini, Bonferroni and Zenga synthetic inequality measures. These three synthetic indexes are the weighted arithmetic means of the corresponding point measures and applying the Zenga two-step approach, decompositions based on means comparison are obtained. In the first step additive decompositions are derived for the point indexes and in the second step, using the decompositions of the point measures, we obtain the decompositions by subpopulations of the synthetic indexes...
Joint decomposition by subpopulations and sources
of the point and synthetic Bonferroni inequality measures
digital
Anno:
2017
The total income Y is the sum of c sources Xj : Y = X1 + . . . + Xc: The N units of the population are partitioned in k different subpopulations. In the frequency distribution framework the Bonferroni (1930) point inequality index is given by Vh(Y) = [M(Y) - ̅Mh.(Y)]/M(Y), M(Y) and ̅Mh.(Y)are the mean and the lower mean of Y...
Decomposition by subpopulations of the point and the synthetic
Gini inequality indexes
digital
Anno:
2016
Keywords: Gini Index, Point Inequality Index, Synthetic Inequality Index, Decomposition by Subpopulatios
On the decomposition by subpopulations of the point and synthetic
Bonferroni inequality measures
digital
Anno:
2016
This paper, by using the ‘‘two-step’’ approach proposed in Radaelli (2008, 2010) and in Zenga (2016) for the decomposition of the Zenga (2007) index, obtains the decomposition of the Bonferroni (1930) inequality measure. In the first step the Bonferroni point measure Vh(Y) is decomposed in a weighted mean of k x k relative differences between the mean Mg(Y) of subpopulation g and the lower mean Mhl(Y) of the subpopulation l...
Joint decomposition by subpopulations and sources of the Zenga
inequality index I(Y)
digital
Anno:
2015
Keywords: Zenga Inequality Index, Income Inequality, Joint Decomposition by Subpopulations and Sources, Point and Synthetic Inequality Indexes.
The reordering variates in the decomposition by sources of
inequality indexes
digital
Anno:
2015
Keywords: Reordering Variate, Income Inequality, Decomposition by Sources, Point Inequality, Uniform Cograduation
A longitudinal decomposition of Zenga’s new inequality Index
Gratis
digital
Anno:
2013
The paper proposes a three-term decomposition of Zenga’s new inequality index over time. Given
an initial and a final time, the link among inequality trend, re-ranking, and income growth is explained
by decomposing the inequality index at the final time into three components: one measuring
the effect of re-ranking between individuals, a second term gauging the effect of disproportional
growth between individuals’ incomes, and a third component measuring the impact of the inequality
existing at the initial time. The decomposition allows one to distinguish the determinants of inequality
change from the contribution of the inequality at the initial time to the inequality at the final
time. We applied the decomposition to Italian household income data collected by the Survey on
Household Income and Wealth of the Bank of Italy, waves 2008-2010.
Application of Zenga’s distribution to a panel survey on household incomes of European Member States
Gratis
digital
Anno:
2013
In this paper Zenga’s distribution is applied to 114 household incomes distributions from a panel
survey conducted by Eurostat. Previous works showed the good behaviour of the model to describe
income distributions and analyzed the possibility to impose restrictions on the parametric space so
that the fitted models comply with some characteristics of interest of the samples. This work is the
first application of the model on a wide number of distributions, showing that it can be used to describe
incomes distributions of several countries. Maximum likelihood method on grouped data and
methods based on the minimization of three different goodness of fit indexes are used to estimate
parameters. The restriction that imposes the equivalence between the sample mean and the expected
value of the fitted model is also considered. It results that the restriction should be used and the
changes in fitting are analyzed in order to suggest which estimation method use jointly to the restriction.
A final section is devoted to the direct proof that Zenga’s distribution has Paretian right-tail.
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