You are viewing a free preview of this lesson.
Subscribe to unlock all 10 lessons in this course and every other course on LearningBro.
How a society shares out its economic resources is one of the most contested questions in economics — and one of the few where positive analysis (measuring what is) and normative judgement (deciding what ought to be) sit uncomfortably close together. Before any of those value-laden debates can be had, however, inequality must be measured, and measuring it well is harder than it looks. This lesson builds the two essential tools the AQA specification requires — the Lorenz curve, a picture of the whole distribution, and the Gini coefficient, a single number summarising it — and then deploys them to describe UK income and wealth inequality, explain its causes, and confront the central normative question: how much inequality matters, and how we should distinguish inequality of outcome from inequality of opportunity, and equality from equity. The connective idea, running through every later policy lesson, is that you cannot evaluate redistribution until you can measure the thing being redistributed.
This lesson sits within Section 4.1.7 — The distribution of income and wealth: poverty and inequality of the AQA A-Level Economics (7136) specification, the part of the microeconomics course that draws together wage determination (Lessons 1–7) into the economy-wide distribution of resources. It is the analytical foundation for the lessons on poverty (Lesson 9) and on redistributive policy (Lesson 10).
Exam Tip: Examiners reward precision about the measure. A Gini coefficient is meaningless without specifying which income concept (original, gross, disposable, post-tax) and which year. Stating "the UK Gini for disposable income is around 0.33" is an AO1/AO2 mark that a vague "the UK Gini is 0.33" forfeits.
The single most common error in this topic is to conflate income and wealth. They are different things, measured differently, and distributed very differently.
Key Definition: Income is a flow of money received over a period of time — wages, salaries, interest, dividends, rent, pensions and benefits, measured in £ per week, month or year.
Key Definition: Wealth is a stock of assets owned at a point in time — property, savings, shares, pension entitlements and physical assets, minus any debts (i.e. net worth).
| Feature | Income | Wealth |
|---|---|---|
| Type | Flow (per period) | Stock (at a point in time) |
| Measurement | £ per year | Net worth (assets minus liabilities) |
| Main sources | Wages, benefits, investment income | Property, pensions, financial assets |
| UK data source | HMRC, ONS earnings surveys, DWP HBAI | ONS Wealth and Assets Survey |
| Distribution | Unequal | Much more unequal |
The relationship runs in both directions, which is why inequality tends to be self-reinforcing. Wealth generates income (assets pay rent, dividends and interest), and income generates wealth (saved income accumulates into assets). A household with no assets receives no investment income, finds it harder to save, and so struggles to build wealth — while a household with assets earns investment income on top of any wages, saves more easily, and accumulates faster. The decisive empirical fact, which you should always state, is that wealth is far more unequally distributed than income: the wealthiest tenth of households hold a far larger share of total wealth than of total income, while the least wealthy half hold only a small fraction of total wealth. This is why a country can look only moderately unequal on income but highly unequal on wealth.
The Lorenz curve, due to Max Lorenz (1905), is a graphical picture of an entire distribution.
Key Definition: The Lorenz curve plots the cumulative percentage of income (vertical axis) received by the cumulative percentage of the population ranked from poorest to richest (horizontal axis). The further the curve bows away from the diagonal line of perfect equality, the more unequal the distribution.
To construct it: rank everyone from lowest to highest income; on the horizontal axis plot the cumulative share of the population; on the vertical axis plot the cumulative share of total income they receive; join the points. The benchmark is the 45-degree line of perfect equality, on which the poorest 20% of people receive exactly 20% of income, the poorest 50% receive 50%, and so on. A real distribution always lies below this line — the poorest 20% receive much less than 20% of income — so the Lorenz curve bows downward, and the size of the bow is the amount of inequality.
A representative (illustrative) UK income distribution makes the bow concrete:
| Cumulative % of population | Cumulative % of income — perfect equality | Cumulative % of income — UK (approx.) |
|---|---|---|
| Bottom 20% | 20% | ~7% |
| Bottom 40% | 40% | ~18% |
| Bottom 60% | 60% | ~34% |
| Bottom 80% | 80% | ~56% |
| All 100% | 100% | 100% |
Exam Tip: When you draw a Lorenz curve, always include (1) the 45-degree line of equality drawn corner-to-corner, (2) the curve bowing below it, (3) both axes labelled "cumulative % of population" and "cumulative % of income", and (4) the area between the two clearly identified as inequality. A second Lorenz curve closer to the diagonal is the standard way to show inequality falling — for example after redistribution.
The Lorenz curve is a picture; the Gini coefficient (Corrado Gini, 1912) compresses it into a single number for comparison over time and across countries.
Key Definition: The Gini coefficient is the ratio of the area between the Lorenz curve and the line of equality to the total area beneath the line of equality. It runs from 0 (perfect equality — Lorenz curve on the diagonal) to 1 (perfect inequality — one person has everything).
Using the labelled areas in the diagram — A between the line of equality and the Lorenz curve, B beneath the Lorenz curve:
Gini=A+BA
Because A+B is the whole triangle beneath the diagonal, the Gini is simply the share of that triangle taken up by the inequality gap A. A larger bow means a larger A, a larger ratio, and a higher Gini. Two readings help build intuition: a Gini of 0 means the Lorenz curve coincides with the diagonal (A=0); a Gini approaching 1 means the curve hugs the bottom and right axes (B→0), so one person receives almost all the income.
The figures are illustrative. Take the representative distribution above, where the poorest 20% of the population receive about 7% of income. Under perfect equality they would receive 20%. The shortfall of the bottom quintile is therefore:
20%−7%=13 percentage points
and the richest quintile, who under equality would also receive 20%, in fact receive the residual 100%−56%=44% — more than six times the share of the poorest quintile. A compact way to summarise this is the quintile ratio: the top quintile's share divided by the bottom quintile's, here 44÷7≈6.3. The larger this ratio, the more bowed the Lorenz curve and the higher the Gini. This kind of quick computation — turning the cumulative shares into a shortfall or a ratio — is exactly the AO2/AO3 work that examiners reward in data-response questions, and it shows you can interpret a distribution rather than merely describe its shape.
The UK's Gini for disposable income is around the low 0.30s. The headline historical fact you should know is that UK income inequality rose sharply in the 1980s — one of the largest increases in any advanced economy over that period — driven by tax cuts at the top, the decline of trade-union wage compression (Lesson 5) and deregulation, and has been broadly stable at that historically high level since. Internationally, the UK is more unequal than most of continental Western Europe but less unequal than the United States, with several emerging economies considerably more unequal still. (Treat such cross-country figures as broad orderings rather than precise values, since methods differ.)
For all its convenience, the Gini coefficient is a summary statistic, and summarising a whole distribution in one number throws information away — a point that earns real evaluation marks. Three limitations matter most. First, the Gini is insensitive to where in the distribution inequality changes: a transfer from a middle-income to a lower-income household can produce the same Gini change as a transfer from the very top to the middle, even though most people would judge these very differently. Second, two different distributions can share the same Gini — if their Lorenz curves cross, one society might have a poorer bottom decile and the other a richer top decile, yet the single number conceals this. Third, the Gini says nothing about absolute living standards: a poor country and a rich country can have identical Ginis while one's poorest are destitute and the other's are merely behind the median. For these reasons economists supplement the Gini with measures that target particular parts of the distribution — for example the share of income going to the top 1% or 10%, or decile and quintile ratios such as the ratio of the 90th-percentile income to the 10th-percentile income (the "90:10 ratio"). The mature analytical stance is to treat the Gini as a useful headline that should be read alongside the Lorenz curve and at least one distributional ratio, never as the last word.
Exam Tip: Citing a limitation of the Gini — its insensitivity to where inequality changes, or the fact that crossing Lorenz curves can share a Gini — is a high-value AO4 point. Pair the Gini with a top-share or 90:10 ratio to show you understand that a single number cannot capture a whole distribution.
A single country has several Gini coefficients, because income can be measured at different stages of the tax-and-benefit process. Distinguishing them is essential and frequently examined:
As we move from original to final income, the Gini falls substantially — the tax-and-benefit system compresses the distribution. Cash benefits, especially the state pension and means-tested support, do most of the equalising work, with direct taxes adding more. This is exactly what Lesson 10 evaluates as redistribution. Graphically, redistribution pulls the Lorenz curve toward the diagonal:
Exam Tip: If a question gives you a Gini for "original income" and another for "final income", the gap between them is the redistributive effect of the state. Quantifying that gap — "taxes and benefits cut the Gini by roughly 0.18" — turns a recall point into applied analysis.
Inequality has structural roots that connect directly to earlier lessons:
| Cause | Mechanism |
|---|---|
| Wage differentials | Differences in human capital, MRPL, occupation and bargaining power (Lessons 1–5) |
| Ownership of assets | The wealthy receive investment income (rent, dividends, capital gains) the asset-poor do not |
| Tax and benefit design | Progressive taxes and benefits compress the distribution; regressive taxes (VAT) widen it |
| Skill-biased technological change | Technology raises demand for skilled labour and erodes demand for routine work, widening the wage gap (Goldin and Katz, 2008) |
| Globalisation | Offshoring depresses low-skill wages while raising returns to capital and high-skill labour |
| Declining union membership | Unions compress wages; their decline since the 1980s has widened the distribution (Lesson 5) |
| Executive pay | Top pay has risen far faster than median pay, stretching the top of the distribution |
| Housing and asset prices | Rising house prices enrich owners relative to renters, widening the wealth gap especially across generations |
Subscribe to continue reading
Get full access to this lesson and all 10 lessons in this course.