Named after Italian statistician Corrado Gini, the **Gini coefficient** is a way to measure the income distribution of a population.

The value for the Gini coefficient ranges from 0 to 1 where higher values represent greater income inequality and where:

**0**represents perfect income equality (everyone has the same income)**1**represents perfect income inequality (one individual has all the income)

You can find a list of Gini coefficients by country here.

The following step-by-step example shows how to calculate a Gini coefficient in Excel.

**Step 1: Enter the Data**

First, we must enter values for two columns: the cumulative population % and cumulative income % of individuals in a certain country:

Here’s how to interpret the values:

- The bottom 20% of individuals in this country account for
**10%**of the total income. - The bottom 50% of individuals in this country account for
**31%**of the total income. - The bottom 60% of individuals in this country account for
**40%**of the total income. - 100% of individuals in this country account for
**100%**of the total income.

**Step 2: Calculate Areas Under Lorenz Curve**

Next, we need to calculate the individual areas under the Lorenz curve, which is a curve we use to visualize the distribution of income in a country.

In our example, we’ll type the following formula in cell **C3**:

=(A3-A2)*(B3+B2)*0.5

We’ll then copy and paste this formula down to every remaining cell in column C:

**Step 3: Calculate Gini Coefficient**

Lastly, we can type the following formula into cell **D2 **to calculate the Gini coefficient for this population:

=1-2*SUM(C3:C6)

The following screenshot shows how to use this formula in practice:

The Gini coefficient for this population turns out to be **0.226**.

This is an extremely simple example of how to calculate a Gini coefficient but you can use these exact same formulas to calculate a Gini coefficient for a much larger dataset.