Gini index or Gini coefficient is a statistical measure of distribution which was developed by the Italian statistician Corrado Gini in 1912.

It is used as a gauge of economic inequality, measuring income distribution among a population.

The coefficient ranges from 0 (or 0%) to 1 (or 100%), with 0 representing perfect equality and 1 representing perfect inequality. Values over 1 are not practically possible as we don’t take into account the negative incomes. (Income can be 0 at its lowest but not negative)

Thus, a country in which every resident has the same income would have an income Gini coefficient of 0. A country in which one resident earned all the income, while everyone else earned nothing, would have an income Gini coefficient of 1.

As we know now, the Gini coefficient is an important tool for analyzing income or wealth distribution within a country or region, but,

Gini should not be mistaken for an absolute measurement of income or wealth.

A high-income country and a low-income one can have the same Gini coefficient, as long as incomes are distributed similarly within each country:

Use of Gini index in data modelling

The Gini Coefficient or Gini Index measures the inequality among the values of a variable. Higher the value of an index, more dispersed is the data. Alternatively, the Gini coefficient can also be calculated as the half of the relative mean absolute difference.

Graphical Representation of the Gini Index (Lorenz curve)

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

The line at 45 degrees thus represents perfect equality of incomes.