1. What is the Gini Coefficient?

The Gini coefficient is a measure of statistical dispersion intended to represent income inequality or wealth inequality within a nation or any other group of people. A Gini coefficient of 0 expresses perfect equality, while a coefficient of 1 expresses maximal inequality.

2. How Does the Calculator Work?

The calculator uses the standard Gini coefficient formula:

Where:

• The Lorenz curve plots the cumulative percentage of income against the cumulative percentage of population
• The area between the line of equality and the Lorenz curve is calculated
• The Gini coefficient is derived from this area

Explanation: The calculation involves sorting incomes, calculating cumulative percentages, and using the trapezoidal rule to compute the area under the Lorenz curve.

3. Interpretation of Results

Details:

• 0 = Perfect equality (everyone has exactly the same income)
• 0.2-0.3 = Relatively equal income distribution
• 0.3-0.4 = Moderate inequality
• 0.4-0.5 = High inequality
• 0.5+ = Very high inequality

4. Using the Calculator

Tips: Enter income values separated by commas (e.g., 25000,30000,45000,60000,120000). The calculator will automatically sort and process the values.

5. Frequently Asked Questions (FAQ)

Q1: What is considered a "good" Gini coefficient?
A: Most developed nations have coefficients between 0.24 and 0.36. Values above 0.4 are often considered problematic for social stability.

Q2: How does this compare to other inequality measures?
A: The Gini coefficient is more comprehensive than simple ratios (like 90/10 ratio) as it considers the entire distribution.

Q3: What are limitations of the Gini coefficient?
A: It doesn't show where the inequality occurs in the distribution and can be sensitive to changes in the middle of the distribution.

Q4: Can it be used for wealth inequality?
A: Yes, the same calculation applies when using wealth data instead of income data.

Q5: How often should Gini coefficients be calculated?
A: For tracking trends, annual calculation is typical, though quarterly estimates might be useful in rapidly changing economies.