Title : ( Entropy maximization under the constraints on the generalized Gini index and its application in modeling income distributions )
Authors: Ali Khosravi Tanak , Gholam Reza Mohtashami Borzadaran , Jafar Ahmadi ,
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Abstract
In economics and social sciences, the inequality measures such as Gini index, Pietra index etc., are commonly used to measure the statistical dispersion. There is a generalization of Gini index which includes it as special case. In this paper, we use principle of maximum entropy to approximate the model of income distribution with a given mean and generalized Gini index. Many distributions have been used as descriptive models for the distribution of income. The most widely known of these models are the generalized beta of second kind and its subclass distributions. The obtained maximum entropy distributions are fitted to the US family total money income in 2009, 2011 and 2013 and their relative performances with respect to generalized beta of second kind family are compared.
Keywords
Maximum entropy Inequality measures Generalized Gini index Euler’s equation Income distribution Generalized beta of second type distribution
@article{paperid:1049022,
author = {Khosravi Tanak, Ali and Mohtashami Borzadaran, Gholam Reza and Ahmadi, Jafar},
title = {Entropy maximization under the constraints on the generalized Gini index and its application in modeling income distributions},
journal = {Physica A: Statistical Mechanics and its Applications},
year = {2015},
volume = {438},
month = {August},
issn = {0378-4371},
pages = {657--666},
numpages = {9},
keywords = {Maximum entropy
Inequality measures
Generalized Gini index
Euler’s equation
Income distribution
Generalized beta of second type
distribution},
}
%0 Journal Article
%T Entropy maximization under the constraints on the generalized Gini index and its application in modeling income distributions
%A Khosravi Tanak, Ali
%A Mohtashami Borzadaran, Gholam Reza
%A Ahmadi, Jafar
%J Physica A: Statistical Mechanics and its Applications
%@ 0378-4371
%D 2015
