What does the Gini coefficient measure and what do its values mean?

The Gini coefficient measures the degree of inequality in the distribution of income or wealth within an economy. It is derived from the Lorenz curve, which plots the cumulative share of income received against the cumulative share of the population ranked from poorest to richest. A Gini coefficient of 0 would indicate perfect equality, meaning every individual receives an identical share of income, whilst a coefficient of 1 would indicate that one person receives all income and everyone else receives nothing.

In practice, all economies fall somewhere between these extremes. This means that a higher Gini coefficient signals a more unequal distribution of income across the population. For example, the United Kingdom's Gini coefficient for disposable income has typically sat around 0.35 in recent decades, whereas Scandinavian countries such as Denmark record values closer to 0.28, reflecting more equal distributions achieved partly through progressive taxation and generous welfare transfers.

Comparing Gini coefficients across countries or tracking changes over time allows economists and policymakers to assess whether inequality is widening or narrowing and if a government introduces a more progressive income tax or increases means-tested benefits, and the Gini coefficient subsequently falls. This provides quantitative evidence that the policy has reduced income inequality.

However, the Gini coefficient does have limitations: it does not distinguish between different sources of inequality, nor does it reveal where in the income distribution the greatest disparities occur so it is often used alongside other measures such as decile ratios for a fuller picture.

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The Lorenz curve plots the cumulative percentage of total income (on the vertical axis) received by the cumulative percentage of the population (on the horizontal axis), ranked from lowest to highest income. The key area to focus on is the gap between the 45-degree line of perfect equality and the bowed Lorenz curve itself, since it is this area — expressed as a proportion of the total triangle beneath the 45-degree line — that gives the Gini coefficient its value. A Lorenz curve that bows further from the diagonal indicates greater inequality and a higher Gini coefficient.

• →The line of perfect equality is the 45-degree diagonal on a Lorenz curve diagram. The further the Lorenz curve bows away from this line, the greater the inequality — and the larger the Gini coefficient.
• →Calculating the Gini coefficient conceptually: it is the ratio of the area between the line of perfect equality and the Lorenz curve (area A) to the total area beneath the line of perfect equality (area A + area B). A larger area A relative to A + B means a higher Gini coefficient and greater inequality.
• →Pre- and post-tax Gini coefficients differ meaningfully. The pre-tax (market income) Gini is almost always higher than the post-tax and transfer Gini, illustrating the redistributive effect of fiscal policies.
• →A falling Gini coefficient does not necessarily mean poverty has been reduced — it means incomes have become more equal in relative terms, which could still be consistent with widespread absolute poverty.
• →Wealth inequality vs income inequality: Gini coefficients for wealth are typically much higher than those for income, because wealth accumulates over time and is more concentrated at the top of the distribution.

This question tests understanding of how economists quantify inequality in the distribution of income and wealth, and what movements in that measure signify about an economy's distributional outcomes. It draws directly on AQA spec point 4.1.7.1 — The distribution of income and wealth and Edexcel spec point 4.2.2.b, both of which require students to understand the tools used to measure inequality, interpret their values, and evaluate the impact of government policies designed to alter the distribution of income and wealth.

Examined 5 times across AQA and Edexcel since 2017.

The concept has appeared on both boards across multiple series, with questions ranging from single-mark identification tasks to more extended explanatory responses.

• →Poverty and Inequality — understanding absolute and relative poverty provides essential context for interpreting what a given Gini coefficient value means for living standards, and for evaluating whether a fall in the coefficient represents a genuine improvement in welfare across the population.