Gini Coefficient Calculator

Calculate Gini coefficient for income inequality.

Gini Coefficient Calculator - Income Inequality Analysis

Gini Coefficient Calculator

Measure income inequality and wealth distribution using the Gini coefficient. Analyze economic disparity and understand wealth concentration in populations.

Input Method

Individual Income Values

Income Groups

Income by Percentiles

Gini Coefficient Results

Gini Coefficient
As Percentage
Mean Income
Median Income

Lorenz Curve Points

Population % Income % Cumulative Income

Interpretation

Note: A Gini coefficient of 0 represents perfect equality, while 1 represents maximum inequality.

How the Gini Coefficient Works

The Gini coefficient is a measure of statistical dispersion used to represent income inequality within a nation or group. It was developed by Italian statistician Corrado Gini in 1912.

Calculation Method

The Gini coefficient is calculated as the ratio of the area between the line of equality and the Lorenz curve to the total area under the line of equality:

G = (A) / (A + B)

Where A is the area between the line of equality and the Lorenz curve, and B is the area under the Lorenz curve.

Interpretation Guide

Inequality Levels

  • 0.00 - 0.25: Very Low Inequality
  • 0.25 - 0.35: Low Inequality
  • 0.35 - 0.45: Moderate Inequality
  • 0.45 - 0.60: High Inequality
  • 0.60 - 1.00: Very High Inequality

Country Examples

  • Denmark (0.25): Very equal distribution
  • Germany (0.32): Low inequality
  • United States (0.41): Moderate inequality
  • Brazil (0.53): High inequality
  • South Africa (0.63): Very high inequality

Use Cases

Economic Analysis

  • • Compare inequality between countries
  • • Track inequality changes over time
  • • Evaluate policy effectiveness
  • • Research economic development

Business Applications

  • • Analyze salary distributions
  • • Study market concentration
  • • Evaluate resource allocation
  • • Assess customer wealth distribution

Tips for Accurate Analysis

  • • Ensure income data is comprehensive and representative
  • • Consider using household income rather than individual income
  • • Account for regional cost of living differences
  • • Include all income sources (wages, investments, transfers)
  • • Use consistent time periods for comparisons
  • • Consider complementary measures like the Palma ratio
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