Gini Coefficient Calculator
To use this gini coefficient calculator, Enter a set of income or wealth values separated by commas (e.g., 5000, 10000, 20000, 15000, 25000).
The calculator finds Gini coefficient using advanced formula. It calculates Gini coefficient, which ranges from 0 (perfect equality) to 1 (perfect inequality).
- Below 0.20: Very low inequality
- 0.20 – 0.30: Low inequality
- 0.30 – 0.40: Moderate inequality
- 0.40 – 0.50: High inequality
- Above 0.50: Very high inequality
Gini Coefficient Table
Gini Coefficient Range | Level of Inequality | Interpretation |
---|---|---|
0.00 – 0.20 | Very Low Inequality | Income is distributed very evenly across the population. |
0.21 – 0.30 | Low Inequality | Minor differences in income levels; relatively equal wealth distribution. |
0.31 – 0.40 | Moderate Inequality | Noticeable income gaps; middle class is relatively strong. |
0.41 – 0.50 | High Inequality | Significant income disparity; wealth concentrated in fewer hands. |
0.51 – 0.70 | Very High Inequality | Severe income inequality; middle class diminishes; wealth highly concentrated. |
0.71 – 1.00 | Extreme Inequality | Virtually all wealth held by one individual or group; extreme poverty for others. |
Gini Coefficient by Country
Country/Region | Gini Coefficient (Typical Range) | Level of Inequality |
---|---|---|
Nordic Countries (e.g., Sweden, Norway) | 0.24 – 0.28 | Very Low to Low |
European Union (e.g., Germany, France) | 0.29 – 0.35 | Low to Moderate |
United States | 0.38 – 0.41 | Moderate to High |
Brazil, South Africa | 0.50 – 0.65 | Very High |
Sub-Saharan Africa (various) | 0.55 – 0.70 | Very High to Extreme |
Gini Coefficient Formula
The formula for calculating the Gini coefficient is:
G = 1 - (Σ (X{i-1} + X{i})(Y{i} - Y{i-1})) / Total Area
Where:
- X_i = cumulative proportion of the population.
- Y_i = cumulative proportion of income or wealth.
- n = number of data points.
Also equation for calculating the Gini coefficient is:
G = (Σ|xi - xj|)/(2n²μ)
Where:
- xi, xj are individual values
- n is the number of values
- μ is the mean value
For simplified calculation:
G = (2 × cumulative rank - n - 1) / n
Distribution Type Gini Coefficient Interpretation Perfect Equality 0.00 Complete equality Low Inequality 0.20-0.30 Typical developed nations Moderate 0.30-0.40 Most common range High Inequality 0.40-0.50 Developing economies Extreme Inequality > 0.50 Significant disparity
How to Find Gini Coefficient?
- Arrange values from lowest to highest
- Compute cumulative percentages for population and income
- Create the Lorenz curve visualization
- Measure the area differential between perfect equality and actual distribution
- Calculate final coefficient by dividing areas
The Gini ratio spans from 0 to 1, where:
- Zero indicates complete equality
- One represents absolute inequality
Most developed nations maintain coefficients between 0.24 and 0.49, reflecting varying degrees of economic disparity.
- Small Group Analysis Population: 4 families Incomes: $22,000, $32,000, $41,000, $105,000 Result: Gini = 0.43
- Equality Demonstration Population: 5 workers Incomes: $45,000 each Result: Gini = 0.00
- Severe Inequality Case Population: 4 households Incomes: $12,000, $16,000, $19,000, $460,000 Result: Gini = 0.85
- Balanced Distribution Population: 6 residents Incomes: $36,000, $42,000, $47,000, $51,000, $54,000, $70,000 Result: Gini = 0.15
- Large Sample Study 100 individuals: Incomes ranging $25,000 to $195,000 Result: Gini = 0.36
What Does 0.5 Gini Coefficient Mean?
A 0.5 Gini coefficient reveals substantial economic disparity within a population. This value indicates that wealth or income is concentrated among a relatively small percentage of individuals, creating notable social stratification.
This level exceeds typical values in developed economies but falls below extremely unequal societies.
What is the Gini Coefficient?
The Gini coefficient is a statistical measure of inequality in a distribution. It was developed by Italian statistician Corrado Gini in 1912 and is widely used for analyzing income inequality and wealth distribution.