## What is the Gini Coefficient?

The Gini coefficient (Gini index or Gini ratio) is a statistical measure of economic inequality in a population. The coefficient measures the dispersion of income or distribution of wealth among the members of a population.

The Gini coefficient is one of the most frequently used measures of economic inequality. The coefficient can take any values between 0 to 1 (or 0% to 100%). A coefficient of zero indicates a perfectly equal distribution of income or wealth within a population. A coefficient of one represents a perfect inequality when one person in a population receives all the income, while other people earn nothing. In addition, in some rare cases, the coefficient can exceed 100%. This may theoretically occur when the income or wealth of a population is negative.

However, the abovementioned scenarios are extremely rare in the real world. The data shows that the coefficient generally ranges from 24% to 63%.

Please note that the Gini coefficient is not an absolute measure of a country’s income or wealth. The coefficient only measures the dispersion of income or wealth within a population.

### Principles of the Gini Coefficient

The Gini coefficient is one of the most utilized measures of economic inequality because it aligns with the following principles:

#### 1. Anonymity

The coefficient does not disclose the identities of high-income and low-income individuals in a population.

#### 2. Scale of independence

The calculation of the Gini coefficient does not depend on how large the economy is, how it is measured, or how wealthy a country is. For example, both rich and poor countries may show the same coefficient due to similar income distribution.

#### 3. Population independence

The coefficient does not depend on the size of the population.

#### 4. Transfer principle

The coefficient reflects situations when income is transferred from a rich to a poor individual.

### Limitations of the Gini Coefficient

Despite its numerous advantages such as universality and scalability, there are still some limitations to the Gini coefficient:

#### 1. Sample bias

The validity of Gini coefficient calculations can be dependent on the size of a sample. For example, small countries or countries with less economic diversity frequently tend to show low coefficients, while large economically diverse countries usually demonstrate high coefficients.

#### 2. Data inaccuracy

The Gini coefficient is prone to systematic and random data errors. Therefore, inaccurate data can distort the validity of the coefficient.

#### 3. Same Gini coefficient but different income distribution

In some cases, the coefficient can be the same for countries with different income distributions but equal levels of income.

#### 4. Does not reflect the structural changes in a population

One of the drawbacks of the coefficient is that it does not take into consideration the structural changes in a population. Such changes can significantly influence the economic inequality in a population. Generally, the situation arises because young people tend to earn less relative to older people.

### Related Readings

CFI offers the Financial Modeling & Valuation Analyst (FMVA)™ certification program for those looking to take their careers to the next level. To keep learning and advancing your career, the following CFI resources will be helpful: