The Gini index or Gini coefficient is a term used in statistical science and demonstrates an indicator of the stratification of the population of a particular country or region within a certain characteristic. Most often, this index is used to look at economic development with a basis in the form of annual income.
History of the statistical criterion
If we turn to the specific definition of the application of the Gini coefficient, then it is used to differentiate the material incomes of the population, as well as to determine the degree of deviation of their actual distribution from the absolutely possible. This indicator is used when it is necessary to identify the level of inequality in terms of the degree of wealth accumulated by the population.
The pioneer of this coefficient is the Italian statistician and demographer Corrado Gini, who lived from 1884 to 1965 and proposed the developed system in 1912 as part of his work entitled Variation and Variability of a Trait.
The description of the calculation of the Gini coefficient is as follows: the ratio of the area of the figure, which is formed by the Lorentz curve and the inequality curve, to the area of the triangle, which was also formed by two curves - equality and inequality. Thus, first the area of the first figure is found, then it is divided by the area of the second. If they are equal, the coefficient will be 0, and if they are not equal, it will be 1.
Pros and cons of Lorentz coefficient
The main advantage of this method of analyzing statistical reality is considered to be important anonymity and the absence of the need to provide personal data. The pluses also include - the ability to supplement data on GDP and average income of the population, can also act as their amendment; allows you to compare and indicators of different regions with different numbers of the population; as in the previous advantage, comparison is possible between different countries, with different degrees of economic development; also the Gini coefficient allows tracking the dynamics of unevenness and the degree of distribution of income at different time or other stages.
But this coefficient has its drawbacks. This is the lack of accounting for the source of income for a certain region, where the same indicator can be achieved both at the expense of a very heavy income and at the expense of existing property; the Gini coefficient can be applied only when income is generated in money, and not in food, stocks or other goods; the existing differences in the methodologies for collecting statistical data for further calculation can lead to serious difficulties or complete impossibility of comparing the available coefficients.
