22 Facts About Gini coefficient

In economics, the Gini coefficient, known as the Gini index or Gini ratio, is a measure of statistical dispersion intended to represent the income inequality or the wealth inequality within a nation or a social group.

The Gini coefficient was developed by the statistician and sociologist Corrado Gini.

Gini coefficient was proposed by Corrado Gini as a measure of inequality of income or wealth.

Gini coefficient was developed by the Italian statistician Corrado Gini and published in his 1912 paper Variability and Mutability.

Gini coefficient is usually defined mathematically based on the Lorenz curve, which plots the proportion of the total income of the population that is cumulatively earned by the bottom x of the population (see diagram).

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Since the Gini coefficient is half the relative mean absolute difference, it can be calculated using formulas for the relative mean absolute difference.

Gini coefficient can be calculated directly from the cumulative distribution function of the distribution .

In that case, the Gini coefficient can be approximated using various techniques for interpolating the missing values of the Lorenz curve.

Gini coefficient calculated from a sample is a statistic, and its standard error, or confidence intervals for the population Gini coefficient, should be reported.

However, it should be borne in mind that the Gini coefficient can be misleading when used to make political comparisons between large and small countries or those with different immigration policies.

Gini coefficient is widely used in fields as diverse as sociology, economics, health science, ecology, engineering, and agriculture.

Education Gini coefficient index estimates the inequality in education for a given population.

When men and women are considered together, the Gini coefficient-based Shorrocks index trends imply long-term income inequality has been substantially reduced among all workers, in recent decades for the United States.

Gini coefficient has features that make it useful as a measure of dispersion in a population, and inequalities in particular.

Gini coefficient measure gives different results when applied to individuals instead of households, for the same economy and same income distributions.

Deininger and Squire show that the income Gini coefficient based on individual income rather than household income is different.

The theoretical model of the Gini coefficient is limited to accepting correct or incorrect subjective assumptions.

Gini coefficient index is related to the Pietra index — both of which measure statistical heterogeneity and are derived from the Lorenz curve and the diagonal line.

For example, in ecology, the Gini coefficient has been used as a measure of biodiversity, where the cumulative proportion of species is plotted against the cumulative proportion of individuals.

Gini coefficient is sometimes used for the measurement of the discriminatory power of rating systems in credit risk management.

Gini coefficient has been applied to analyze inequality in dating apps.

The Gini coefficient is defined between -1 and 1 and can be used in both empirical and parametric life distributions.