summary:The expected value of the share density of the income distribution can be expressed in terms of the Gini index. The variance of the share density of the income distribution is interesting because it gives a relationship between the first and the second order Gini indices. We find an expression for this variance and, as a result, we obtain some nontrivial bounds on these Gini indices. We propose new statistics on the income distribution based on the higher moments of the share density function. These new statistics are easily computable from the higher order Gini indices. Relating these moments to higher order Ginis suggests new estimates on these quantities
Abstract. The Gini index and its variant are widely used as a mea-sure of income inequality. Finding...
The Gini index is the most commonly used measure of income inequality. Like any single summary measu...
Classical measures of inequality use the mean as the benchmark of economic dispersion. They are not ...
summary:The expected value of the share density of the income distribution can be expressed in terms...
In the present paper, we define and study one of the most popular indices which measures the inequal...
The Gini index is a summary statistic that measures how fairly a resource is distributed in a popula...
There is a vast literature on the selection of an appropriate index of income inequality and on what...
Abstract: The purpose of this paper is to justify the use of the Gini coefficient and two close rel...
This paper discusses the Gini index when a mass of individuals in the population sharing the wealth ...
We show that the Gini coefficient is a simple linear transformation of the center of gravity of inco...
The Gini index is a measure of the inequality of a distribution that can be derived from Lorenz curv...
The Gini index underestimates inequality for heavy-tailed distributions: for example, a Pareto distr...
The inequality is computed through the so-called Gini index. The population is assumed to have the v...
Since Corrado Gini suggested the index that bears his name as a way of measuring inequality, the com...
ABSTRACT: A recent paper published in this journal (Bourguignon et al., 2016) introduces and studies...
Abstract. The Gini index and its variant are widely used as a mea-sure of income inequality. Finding...
The Gini index is the most commonly used measure of income inequality. Like any single summary measu...
Classical measures of inequality use the mean as the benchmark of economic dispersion. They are not ...
summary:The expected value of the share density of the income distribution can be expressed in terms...
In the present paper, we define and study one of the most popular indices which measures the inequal...
The Gini index is a summary statistic that measures how fairly a resource is distributed in a popula...
There is a vast literature on the selection of an appropriate index of income inequality and on what...
Abstract: The purpose of this paper is to justify the use of the Gini coefficient and two close rel...
This paper discusses the Gini index when a mass of individuals in the population sharing the wealth ...
We show that the Gini coefficient is a simple linear transformation of the center of gravity of inco...
The Gini index is a measure of the inequality of a distribution that can be derived from Lorenz curv...
The Gini index underestimates inequality for heavy-tailed distributions: for example, a Pareto distr...
The inequality is computed through the so-called Gini index. The population is assumed to have the v...
Since Corrado Gini suggested the index that bears his name as a way of measuring inequality, the com...
ABSTRACT: A recent paper published in this journal (Bourguignon et al., 2016) introduces and studies...
Abstract. The Gini index and its variant are widely used as a mea-sure of income inequality. Finding...
The Gini index is the most commonly used measure of income inequality. Like any single summary measu...
Classical measures of inequality use the mean as the benchmark of economic dispersion. They are not ...