Gini Coefficient

Inequality can be difficult to measure as there are many variables to take into account. How do economists do it and how reliable are their methods? This explanation will show you how to estimate inequality through the Gini coefficient, or the Gini index.

What is the Gini coefficient?

The Gini coefficient is a measure of income or wealth inequality within a population. It ranges from 0 to 1, where 0 means perfect equality (everyone has the same income or wealth) and 1 means perfect inequality (one person has all the income or wealth).

Lorenz curve and the Gini coefficient

The Lorenz curve and the Gini coefficient are closely related. The Lorenz curve is a graphical representation of income or wealth distribution within a population. It visualises the degree of income or wealth inequality within a population. A perfectly equal distribution of income or wealth would result in a straight diagonal line, while a perfectly unequal distribution would result in a curve that hugs the horizontal axis before sharply rising to the top right corner of the graph.

The Gini coefficient is calculated by dividing the area between the Lorenz curve and the line of perfect equality by the total area under the line of perfect equality. The Lorenz curve and the line of perfect equality are plotted on the same graph, with the cumulative share of income or wealth on the y-axis and the cumulative share of the population on the x-axis. The Lorenz curve represents the actual income or wealth distribution, while the line of perfect equality represents the hypothetical distribution if everyone had an equal share of income or wealth.

Fig. 1 - Lorenz curve

How to calculate Gini coefficient?

To calculate the Gini coefficient, we need to calculate the area between the Lorenz curve and the line of perfect equality. We can do this by dividing the area between the Lorenz curve and the line of perfect equality by the total area under the line of perfect equality.

Gini coefficient formula

The Gini coefficient formula is:

\(\hbox{Gini coefficient}=\frac{\hbox{Area A}}{\hbox{Area A + Area B}}\)

where:

• G is the Gini coefficient,
• Area A is the area between the Lorenz curve and the line of perfect equality,
• Area B is the area under the line of perfect equality.

Fig. 1 - Gini coefficient

Fig. 1 - Gini coefficient

Gini coefficient calculation

How to interpret the Gini coefficient?

You're probably wondering if a higher Gini coefficient is better. In general, no, the higher the Gini coefficient, the higher inequality in population. Take a look at the Gini coefficient range below (Figure 2), it will help you interpret the Gini coefficients in different countries.

The Gini coefficient range

The value of the Gini coefficient ranges from 0 to 1. A coefficient of 0 indicates perfect equality. It means that every 1% of the population has access to 1% of national income, which is unrealistic. A coefficient of 1 indicates perfect inequality. It means that 1 individual has access to 100% of the country’s national income.

Fig. 2 - The Gini coefficient range

As the figure above shows, a coefficient between 0–0.3 indicates relative equality. Relative to a Gini coefficient of 0, income or wealth is distributed quite equally. A coefficient between 0.3–0.4 indicates that there is adequate equality. This means that income or wealth is distributed in a suitable way, but can be distributed more equally. A coefficient greater than 0.4 is an important point and indicates that there is a big income gap. Inequality above this level often means that there is social and political instability or tension. A coefficient between 0.5–1 means that there is severe inequality within an economy.

Why is the Gini coefficient important?

The Gini coefficient is important because it helps economists measure income or wealth inequality. Economists are interested in how income and wealth inequality change over time in an economy as well as the difference in economic inequality between different countries.

Limitations of the Gini coefficient

Whilst the Gini coefficient has proved to be beneficial to help measure income and wealth inequality, it does have some limitations.

One significant limitation is that a lot of information can be lost. For example, in 2016, Turkey and the US had the same Gini coefficient. While both countries may experience similar levels of inequality, the Gini coefficient fails to account for the differences in population size, and how large each economy is.

Like many other measures of inequality, the Gini coefficient shouldn’t be used as the sole measure of income inequality. It could be used alongside other measures, such as the decile ratio or the Palma ratio, to look at the broader scope of inequality within an economy.

Gini coefficient by country

The list of countries and their corresponding Gini coefficient values reveals that some of the countries commonly thought of as being "developed" have relatively high levels of income inequality compared to other countries that are less developed. For instance, the United States, which is often seen as an economic powerhouse, has a Gini index of 41.5, which indicates higher income inequality than that of Mexico (45.4), Brazil (48.9), and Hong Kong (53.9). Meanwhile, some countries with lower levels of income inequality include Slovakia (23.2), Slovenia (24.4), and Denmark (27.7).

The Gini coefficient in the UK over time

The Gini coefficient in the UK has changed significantly over the past few decades (figure 3). In the most reWe will try to examine some of the factors that have contributed to these changes.

Fig. 3 - The Gini coefficient in the UK in the years 1961-2021¹

The UK experienced a sharp increase in inequality from 1978 until the 1980s. Some of the reasons that explain that rise in inequality are:

• Reduced power of trade unions: trade unions help protect workers and strengthen their bargaining power. Weakening trade unions mean that employers are able to exploit workers through lower wages, affecting the poorest significantly.
• Reduction in higher income taxes: income taxes became more regressive and placed a smaller burden on higher earners. The poorest in society were burdened more than the rich.

From the mid-1970s to the 1990s, the top 1% saw increased access to the UK’s national income. This was largely due to:

• Growth of the financial sector: the growth in this sector caused an increase in wages. Already high-earners earned even more while the poor saw little to no change in their wages.
• Increase in house prices: an increase in house prices causes homeowners to feel richer due to the wealth effect. This could have increased wealth inequality.