Gini Coefficient Calculator
Calculate the Gini coefficient, a measure of income inequality within a population. The Gini coefficient ranges from 0 (perfect equality) to 1 (perfect inequality).
Income Distribution Data
Enter income values for different population groups (from lowest to highest income). You can enter up to 10 income groups.
Population Shares (%)
Enter the percentage of population in each income group (must sum to 100%).
Gini Coefficient Results
Gini Coefficient:
0.000
Inequality Level:
N/A
Equality Status:
N/A
Income Distribution Analysis
Top 10% Share:
Bottom 50% Share:
Income Ratio (Top/Bottom):
0.00
Policy Implications
Redistribution Need:
N/A
Social Welfare:
Economic Stability:
N/A
Understanding the Gini Coefficient
The Gini coefficient is a statistical measure of income inequality within a population. It ranges from 0 (perfect equality, where everyone has the same income) to 1 (perfect inequality, where one person has all the income).
Gini Coefficient Formula
Mathematical Formula
- G = S|y? - y?| / (2n²µ)
- G = Gini coefficient
- y?, y? = income of individuals i and j
- n = number of individuals
- µ = mean income
Simplified Calculation
- G = 1 - S(L? × w?)
- L? = cumulative income share
- w? = population weight
- Based on Lorenz curve
Gini Coefficient Interpretation
Inequality Levels by Gini Coefficient
Low Inequality (0.0 - 0.3)
- High income equality
- Strong social welfare systems
- Progressive taxation
- Examples: Denmark, Sweden
- Good social cohesion
Moderate Inequality (0.3 - 0.4)
- Balanced income distribution
- Mixed economic systems
- Moderate social programs
- Examples: USA, UK, Germany
- Market-driven economies
High Inequality (0.4 - 0.6)
- Significant income gaps
- Developing economies
- Limited social safety nets
- Examples: Brazil, South Africa
- Economic transition
Extreme Inequality (0.6+)
- Severe income concentration
- Weak institutions
- High poverty rates
- Examples: Some African nations
- Social instability risks
The Lorenz Curve
| Concept | Perfect Equality | Perfect Inequality | Real World |
|---|---|---|---|
| Lorenz Curve | 45-degree line | Bottom-left to top-right | Bow-shaped curve |
| Gini Coefficient | 0.0 | 1.0 | 0.3 - 0.5 |
| Area Ratio | Area A = Area B | Area A = 0.5 | G = Area A / (Area A + Area B) |
Applications in Economics
Policy Analysis
- Tax policy evaluation
- Redistribution programs
- Social welfare assessment
- Economic development planning
Social Research
- Mobility studies
- Poverty analysis
- Social cohesion measurement
- Economic disparity trends
Investment Analysis
- Market size assessment
- Consumer spending patterns
- Economic stability evaluation
- Risk assessment
International Comparisons
- Cross-country analysis
- Development indicators
- Global inequality trends
- Policy effectiveness
Limitations of Gini Coefficient
Data Issues
- Underground economy
- Top income underreporting
- Data collection challenges
- Cross-country comparability
Interpretation Challenges
- Doesn't show poverty levels
- Ignores absolute income levels
- No information on causes
- Static measure of inequality
Gini Coefficient and Economic Growth
Positive Effects of Inequality
- Incentives for innovation
- Capital accumulation
- Entrepreneurial activity
- Economic dynamism
Negative Effects of Inequality
- Social unrest
- Reduced consumer spending
- Political instability
- Human capital underinvestment
Key Takeaways for Gini Coefficient Calculator
- The Gini coefficient measures income inequality from 0 (perfect equality) to 1 (perfect inequality)
- It is calculated based on the Lorenz curve, which plots cumulative income against cumulative population
- Lower Gini coefficients indicate more equal income distribution
- The calculator uses income groups and population shares to compute the coefficient
- Gini coefficients vary widely across countries and over time
- The measure helps assess social welfare, policy effectiveness, and economic development
- While useful, the Gini coefficient has limitations and should be used with other indicators
- Use the calculator to analyze income distribution patterns and inequality trends