Economic inequality in the UK is measurable, has identifiable causes and carries real costs. In this February 2019 report for the UK Government, MCC Economics & Finance concludes that the UK Government could achieve, and the UK population would benefit from, reduced levels of inequality, with tax the most direct lever available.
This report was prepared for the UK Government to answer two questions: what causes economic inequality, and why does it matter? Inequality shapes decisions that MCC's readers make every day: how tax and spending policy is designed, how regulators weigh affordability when setting the prices utilities may charge, and whether those decisions are judged fair to customers. Although its consequences fall most heavily on low earners and their households, they affect society more broadly through weaker economic growth, lower financial stability, higher crime and poorer health.
The report finds that UK income inequality is lower than in the USA, but that the UK tax and transfer system does less to reduce inequality than those of comparable countries such as Ireland. It identifies the main drivers of inequality as political systems and taxation, technology and rising life expectancy, globalisation, childhood development and family background, and finds that education runs through them all as one of the strongest single influences on differences in income.
The report concludes that the UK Government could achieve, and the UK population would benefit from, reduced levels of inequality, with tax the most direct lever available.
Inequality can be defined in terms of income, wealth, education, happiness or health. This report measures income and wealth, since both are positively correlated with the other three, while recognising some circularity between the factors: income and wealth are much more difficult to obtain without good health, so measuring income or wealth may in some ways measure education, happiness or health indirectly.
We begin with a simple measure of inequality, household income. Dividing UK households into five equally sized population groups (quintiles), the top 20% receive about 12 times the original income of the bottom 20%, about 6 times on gross income and about 5 times on disposable income (Figure 1).
Figure 1: Original, gross and disposable income by quintile group, UK, financial year end 2017.
Average income per UK household in £ per year across the five quintiles, on three definitions of income, showing the gap between top and bottom narrowing as state benefits are added and direct taxes deducted.
What the chart shows is the state at work between the three bars. Cash benefits lift the bottom quintile's income substantially, and direct taxes then trim the top, which is why the gap narrows from 12 times on original income to 6 times on gross income and about 5 times on disposable income. Most of that compression comes from benefits rather than from taxes. The disposable multiple is the fairest single number for UK income inequality, since it measures what households actually have to live on, and 5 times is the figure to carry forward; where the comparison is with the USA, the gross multiple of 6 times is the like-for-like one.
The gap between the gross and disposable multiples in Figure 1 shows how far direct taxes narrow the difference between the highest and lowest earning households.
In the USA, the disparity between the highest and lowest quintile is greater. In 2017 the top 20% of the population in the USA earned, on average, 17 times more than the lowest 20% (Figure 2, Figure 3 and Table 1). Household income in the UK in 2017 was therefore markedly less unequal than in the USA, and less unequal than the USA at any point in this series, including 1967. The USA is the natural benchmark: it is a large, rich, English-speaking economy with half a century of directly comparable data, and it sits at the high-inequality end of the developed world. The comparison matters for policymakers because it places the two countries on the same road at different points. The UK has followed the same upward path as the other English-speaking countries since 1980, and the USA shows how much further that path can run.
Figure 2: Gross income by quintile group, USA, 1967, 1982, 2002, and 2017. Average gross income per US household in $ per year across the five quintiles at four points over fifty years, showing growth concentrated in the highest quintile.
Read the two ends of the chart across fifty years and the story is growth concentrated at the top: average income in the lowest quintile rose about 35% in real terms between 1967 and 2017, while the highest quintile's more than doubled, up about 103%. Inequality in the USA widened not because the bottom fell but because the top pulled away, a pattern that recurs throughout this report.
Table 1: Gross household income, USA, 1967 and 2017. The end points of Figure 2 in table form: average gross household income in the lowest and highest quintiles, and the widening multiple between them.
Figure 3: Household income at selected percentiles, USA, 1968-2017. US household income at nine percentile points over fifty years, inflation adjusted, showing strong growth at the top percentiles and near-flat income at the bottom.
The fan shape is the insight: the higher the percentile, the steeper its fifty-year climb, while the bottom lines run nearly flat. That confirms the quintile reading at finer resolution and locates the driver of US inequality at the top of the distribution rather than in falling incomes at the bottom.
Comparing countries over 114 years shows two distinct patterns (Figure 4). In the English-speaking countries (USA, UK, Australia, Canada and Ireland), the income share of the top 1% traces a U-shape: high at the start of the twentieth century, falling steadily to a trough around the late 1970s, then rising again from 1980. In continental Europe and Japan the pattern is an L-shape: a similar long decline, but no comparable rebound. The decline to 1980 was common to all countries, which suggests world factors at work. The two world wars and the depression of the 1930s destroyed and taxed away large private fortunes, and the post-war decades added high top rates of income tax, strong trade unions and expanding welfare states, which held top income shares down through the 1950s and 1960s. The rebound from 1980 was not common to all countries, which points to national policy rather than global forces. The countries where top shares rose sharply, led by the USA and the UK, were those that cut top tax rates, deregulated finance and saw union membership decline from the 1980s onwards, while continental Europe and Japan, which retained more redistributive systems, saw little rebound. The divergence itself is evidence that inequality responds to policy choices. Policy is not the whole story, however: the trends also reflect interacting forces examined later in this report, in particular the rising premium paid for education as technology increases the demand for skills, alongside globalisation, childhood development and family background.
Figure 4: Income inequality, UK compared with other countries, share of total income going to top 1%, 1900-2014 Caption: Two panels covering 114 years: the U-shaped path of top 1% income shares in the English-speaking countries against the L-shaped path in continental Europe and Japan.
Comparing population groups is indicative but not comprehensive, so an overall measure is needed. The most popular is the Lorenz curve, from which the Gini coefficient is derived (Figure 5); Our World in Data maintains an accessible explainer of how the Gini coefficient works. The Lorenz curve would be a straight line under perfect equality; the steeper the curve, the higher the inequality, and the Gini coefficient is the area between the curve and the line of equality divided by the total area beneath that line.
Figure 5: The Lorenz 'curve' and the Gini coefficient. The construction of the Gini coefficient: cumulative income share plotted against cumulative population share, with the Gini equal to area A divided by areas A plus B.
The Gini's appeal is that it compresses an entire income distribution into one number between 0 (perfect equality) and 1, which is what makes the cross-country and cross-decade comparisons in the rest of this report possible. Its limit is worth knowing too: two differently shaped distributions can share the same Gini, so the report pairs it with the group comparisons above rather than relying on it alone. The World Bank address cited in 2019 no longer resolves; this archived copy at the Munich Personal RePEc Archive replaces it.
The Lorenz curve applies to both income and wealth, and comparing the two is revealing. The Office for National Statistics reports that wealth in the UK is distributed far more unequally than income: the poorest half of households hold about 31 per cent of total income, but only 20 per cent of physical wealth, 7 per cent of net property wealth and 3 per cent of private pension wealth. Within wealth, concentration varies by asset type: physical wealth is the least concentrated, followed by property wealth, while pension wealth and financial wealth are the most concentrated of all. Net financial wealth is the extreme case, and the poorest half of households hold less than none of it, because their debts exceed their savings and investments. This matters for the discussion that follows because tax and transfer policy works mainly on income, so even a system that redistributes income effectively leaves the larger wealth gap largely untouched, a point that returns in the wealth tax debate below and in the relationship between income and wealth inequality in Appendix 3.
Figure 6: Lorenz curve of UK income (2009/10) and UK wealth (2008/2010). Five Lorenz curves on one chart: UK income against four categories of UK wealth, with financial and pension wealth bowing furthest from the line of equality.
The Gini coefficient can also be tracked over time, and is conventionally expressed as a Gini index on a scale of 0 to 100, which allows inequality to be compared across countries and across decades (Figure 7). Figure 7 shows the USA above both the UK and Ireland in every year from 1980, consistent with the quintile comparison above. The distance between them is not constant, however. UK inequality rose steeply through the 1980s and 1990s, reaching 38.9 in 2000 against 40.1 in the USA, before falling back to 33.1 by 2014, so the transatlantic gap narrowed almost to nothing and then reopened. Because the Gini is the most widely used summary measure of inequality, this report relies on it rather than on alternatives such as the Theil or Atkinson indices.
Figure 7: The GINI Index for the UK, USA, and Ireland, 1980-2014. Gini index values for the three countries over 34 years, with the USA persistently the most unequal of the three.
Table 2: UK Gini index since the report was published, 2015 to 2021 The same World Bank Gini series shown in Figure 7, updated at republication. UK income inequality on this measure has changed little since the report was written, drifting slightly down from its 2018 peak.
The update matters because the report’s argument was not that UK inequality was rising rapidly, but that inequality remained higher than the level the tax and transfer system should leave after redistribution. Five more years of a broadly flat Gini strengthen that framing; the gap between the UK and the best redistributors (Table 4) is a policy choice that has persisted, not a trend correcting itself.
Political systems, technology, globalisation, childhood and family all contribute, and education is consistently identified as one of the main factors behind differences in income.
Taxes have a material effect on inequality for two reasons: they allow redistribution of income from the highest earners to the lowest, and the lowest earners can pay a much smaller proportion of tax than the highest earners.
Relative to other countries, the UK tax and transfers system is less powerful at reducing inequality. Using the latest data available at the time, drawn from 2012 to 2014 depending on the country, taxes and transfers in Ireland reduce the Gini coefficient from 0.58 to 0.31, cutting inequality by almost half, whereas the impact in the UK is much smaller, reducing the Gini from 0.53 to 0.36 which represents a reduction of about a third (Figure 9). Ireland starts from higher market inequality than the UK and ends with lower disposable-income inequality, so the difference between the two countries is not their economies but what their tax and transfer systems do.
Figure 8: Inequality of incomes before and after redistribution. One bar per country showing the percentage by which taxes and transfers reduce the Gini coefficient, at the latest year available; Ireland is among the largest reducers, the UK well down the range.
The length of each bar is its tax and transfer system at work. The UK's striking feature is the combination: market income inequality among the highest in the developed world, paired with a redistribution effort well short of countries such as Ireland and Finland, which cut their Gini by close to half against the UK's roughly one third. The chart is the visual case for the report's conclusion that tax has room to do more in the UK.
Growing inequality in the USA has produced political pressure to update the tax system, perhaps to focus on wealth rather than income. US senator Elizabeth Warren has called for an annual levy of 2% on wealth above $50m and 3% on wealth above $1bn, which supporters say could raise $210bn a year, although they assume, implausibly, limited avoidance and no economic damage. An alternative proposal by congresswoman Alexandria Ocasio-Cortez, a top tax rate of 70% on the highest incomes, is estimated to raise only $12bn, around 5% of the wealth tax figure.
Table 3: Two 2019 US proposals for taxing the richest, compared The two proposals discussed in the report, side by side: what each would tax, at what rate, and the annual revenue supporters estimated.
The comparison explains why the political debate moved from income to wealth: at the very top, wealth is a far larger base than annual income, so even a modest levy on it is estimated to raise an order of magnitude more than a steep tax on incomes. The report's caveat still applies, since the larger figure rests on optimistic avoidance assumptions.
Figure 9: Inequality of incomes before and after taxes and transfers, 2014 Caption: Each country's Gini before taxes and transfers plotted against its Gini after, by continent; countries furthest below the diagonal redistribute the most.
Distance below the diagonal is redistribution: countries on the line redistribute nothing, and the further below it a country sits, the more its taxes and transfers reduce inequality. Ireland sits furthest below the line, the USA stays high on both axes, and the UK lands in between, more redistributive than the USA, well short of the strongest European systems.
Yes: advances in technology increase inequality because those with higher education find it easier to gain employment and to command higher salaries. Figure 10 sets out the relationship for the USA in 2010: unemployment falls and earnings rise with every step up in education, and the gap between the top and bottom of the scale is wide on both measures. Technological advances worldwide raise demand for professional and technical skills, and rising life expectancy raises demand for healthcare professionals and associated technologies.
Figure 10: Education, unemployment and earnings, USA, 2010. Unemployment rate and median weekly earnings by education level in the USA in 2010, from professional degree to less than a high school diploma.
The gradient runs unbroken in both columns: each additional level of education cuts unemployment and raises pay, with no exceptions across eight rungs. At the extremes, a professional degree paid 3.6 times the weekly earnings of someone without a high school diploma and carried one sixth of the unemployment risk, which is why education recurs as the strongest single explanatory variable throughout this report; it works as both insurance against joblessness and a premium on earnings.
It can: trade liberalisation, immigration and tax avoidance, the three main channels of globalisation, can all increase inequality in the UK. Trade liberalisation, for example, can increase trade with developing nations, reducing world inequality, but can decrease the wages of low-skilled domestic workers, increasing inequality in developed countries like the UK and the USA [Wood, North-South Trade, Employment and Inequality, 1994].
Research suggests the impact of immigration is small. In 2005 the International Organisation for Migration concluded, in the words the report quotes in full:
Childhood development is strongly correlated with education outcomes, which are in turn strongly correlated with income. If the supply of high-skilled labour kept pace with demand, childhood development would matter less for inequality, but this has not been the case: although the supply of college skills has increased, so has the wage premium paid for those skills (Figures 11 and 12).
Figure 11: Relative Supply of College Skills and College Premium, US, 1939-1996. The college wage premium and the relative supply of college skills in the US over six decades, rising together from around 1980.
The surprise in this chart is that both lines rise together from around 1980. Ordinarily a rising supply of graduates should compress the graduate premium; instead the premium rose as supply rose, which means demand for skills grew faster still. The implication for policy is uncomfortable: expanding education alone does not quickly close income gaps when technology keeps raising the price of skill.
Figure 12: Using supply and demand curves to understand the rising return to education. Paired supply and demand diagrams for high school and college graduate labour, showing the demand shift for college skills outrunning the supply shift and raising the college wage.
The diagrams formalise Figure 11: in the college graduate market the demand curve shifts out further than the supply curve, so both the quantity of graduates and the graduate wage rise together. The takeaway is that the rising return to education is a market outcome, driven by technology's demand for skills, not an artefact of credential inflation.
Björklund and Jäntti, reviewing the evidence on intergenerational income mobility, find that up to half of the difference in incomes can be due to family factors. These factors are diverse: family wealth, family income, local environment, social connections, genetics and family culture. The genetics and culture factors are a timely reminder that inequality is not the same as unfairness.
Wealth inequality is less severe in the UK than in the USA, France or China, although it has risen since the mid-1980s, from a low of 17.8% of net personal wealth held by the top 1% in 1984 to 22.6% in 2014 (Appendix 2). Income inequality and wealth inequality are typically, but not always, positively correlated (Appendix 3). The turning points support the idea that income inequality is a pre-requisite, and thus a leading indicator, of wealth inequality: the UK top 1% income share reached its low in 1978, six years before the wealth share did. Higher income is required before wealth-generating capital such as property, machinery or shares can be purchased.
Yes: research links higher inequality to weaker economic growth, inefficiency, instability, more crime and worse health.
The evidence is real but weaker than the correlation often claimed. Simple comparisons across countries show nothing: inequality in 2010 plotted against growth in GDP per capita over the following nine years, across 37 OECD members, gives an almost flat line with no statistically significant relationship (Figure 14). The stronger evidence concerns the durability of growth rather than its rate. Berg and Ostry find that longer growth spells are robustly associated with more equality in the income distribution, and estimate that closing half the inequality gap between Latin America and emerging Asia would more than double the expected duration of a growth spell, a result that survives controlling for external shocks, initial income, institutional quality, openness to trade and macroeconomic stability.
The counter-argument is that inequality is not a bad thing if it produces growth and societal benefits for all, even if unequally shared: global daily income per capita has risen above the poverty line even as inequality increased (Figure 13). Neither correlation should be assumed to be causation.
Figure 13: Global income distribution in 1800, 1975, and 2015. The world distribution of daily income per capita at three points across more than two centuries, shifting rightward past the international poverty line as incomes grew.
Across the three panels the whole world distribution shifts right, past the poverty line, even as it spreads out. That is the strongest version of the case that inequality can coexist with broad progress, and the report presents it deliberately before answering it: the shift shows growth lifting absolute incomes, but it says nothing about whether less inequality would have lifted them further. Answering that needs evidence on the growth process itself.
Figure 14: Correlation between Gini coefficients and GDP growth. European sub-national regions' 2007 Gini coefficients plotted against their average annual GDP per capita growth in 2008 to 2012, showing higher inequality associated with weaker subsequent growth.
The scatter is flat. Across 37 OECD members there is no visible relationship between inequality in 2010 and growth in GDP per capita over the nine years that followed. Changing the window does not rescue a downward slope: using 2007 and the crisis years 2008 to 2012, as earlier versions of this chart did, makes the slope significantly positive, because the most unequal members grew through a crisis that fell hardest on the middle of the distribution. The reason the cross-section cannot settle the question is convergence: poorer members are both more unequal and faster-growing, because they started further behind. The evidence that inequality shortens growth comes instead from work on the duration of growth spells, which controls for initial income directly.
Only up to a point. Some argue it is efficient, in terms of overall human welfare, for income and wealth to be unevenly distributed: put simply, some people want to work and grow successful businesses more than others. On the other hand, where inequality leads to poverty there is inefficiency for society overall, because those who could contribute positively may not, because they cannot.
Yes: increased inequality can lead to financial crises, as Kumhof & Rancière showed for the run-ups to 1929 and 2008. Their abstract states:
Increased inequality can also lead to unsustainable growth, with Berg & Ostry finding that longer growth spells are robustly associated with more equal income distributions, and to increased rates of inflation. This literature most often cites the Berg & Ostry finding:
Fajnzylber, Lederman and Loayza, studying homicide and robbery rates across around 40 countries, find that inequality and violent crime are positively correlated, and that the relationship holds even after controlling for other determinants of crime such as low income and unemployment. They estimate that a small but permanent fall in inequality, from the Spanish level of 0.35 to the Canadian level of 0.32 in Figure 9, would reduce homicides by 20% and, over the long run, robberies by 23%.
De Vogli and colleagues, comparing the 21 wealthiest countries and the regions of Italy, find that higher income inequality goes with shorter life expectancy. Pickett and Wilkinson, drawing together evidence from developed countries and from US states in The Spirit Level, extend the pattern to physical health, mental health and infant mortality, concluding that health outcomes on all these measures are worse in more unequal societies.
Given available research and international comparisons, we conclude it is likely that the UK Government could achieve, and the UK population would benefit from, reduced levels of inequality.
In particular, there is scope for tax to play a greater role in equality, and we note the positive impact that reduced inequality, as measured by the Gini coefficient, would have on crime and health.
All ten appendix charts draw on the World Inequality Database, the open database of income and wealth distribution series maintained at the Paris School of Economics. The series were downloaded on 30 July 2026 and cover shares of pre-tax national income for equal-split adults. Note that this income concept is broader than the household income measured in Figure 1, since it includes undistributed corporate profits and imputed rent on owner-occupied housing.
Figure 15: Income inequality, top 1% and bottom 50%, USA, 1990-2014 Figure 16: Income inequality, top 1% and bottom 50%, UK, 1990-2014. Pre-tax national income shares of the top 1% and bottom 50% over 24 years, with the top 1% share rising in both countries and overtaking the bottom 50% share in the USA.
Figure 17: Income inequality, top 1%, USA, UK, France and China, 1990-2014 Figure 18: Income inequality, top 1%, USA, UK and France, 1900-2014. Top 1% national income shares compared across countries, over 24 years and over the full century.
Two readings matter. In the USA the top 1% share overtakes the bottom 50% share in 1997, and by 2014 one person in the top group receives, on average, more than seventy times the income of one in the bottom group. The UK does not follow. Its top 1% share rises by a comparable amount, but the bottom 50% share is essentially unchanged across the period, at a little over 19%, so the gain came from the middle of the distribution rather than from the bottom. The century-long panel shows the post-1980 rise is far steeper in the English-speaking countries: between 1980 and 2014 the American share rises by 8.6 points and the British by 6.5, against 2.3 in France, where the share peaked in 2008 and has fallen back since.
These charts use shares of net personal wealth for equal-split adults, from the World Inequality Database, downloaded on 30 July 2026. Wealth here is personal wealth net of debts, so the shares are not directly comparable with the income shares in Appendix 1.
Figure 19: Wealth inequality, top 1% and middle 40%, USA, 1990-2014 Net personal wealth shares: the top 1% against the middle 40% in the USA, and the UK top 1% share rising over two decades.
Figure 20: Wealth inequality, top 1%, UK, 1990-2012.
Figure 21: Wealth inequality, top 1%, USA, UK and France, 1900-2014. Top 1% net personal wealth shares compared across countries, over the full century and over 24 years.
Figure 22: Wealth inequality, top 1%, USA, UK, France and China, 1990-2014
Wealth concentration runs far above income concentration everywhere. The American top 1% share climbs from 29.0% to 35.8%, overtaking the middle 40% in 1998, so the wealthiest one per cent now hold more wealth than the middle four tenths of the population combined. The British share moves within a narrow band, from 18.7% to 20.7% by 2012, with no sustained trend after the late 1990s. UK wealth inequality remains lower than in the USA, France or China, but the report's suggestion that it has been rising for three decades is not borne out here: the British share stood at 21.1% in 1980, fell through that decade, and has since recovered to roughly where it began.
The long view in Figure 21 shows how far these shares have travelled. In 1900 the British top 1% held 71.6% of personal wealth, against 55.0% in France and 35.4% in the USA. All three fall steeply to around 1980, after which the American share rises furthest.
These charts place the British income and wealth series side by side, both from the World Inequality Database, downloaded on 30 July 2026. Both begin in 1900, which is where the underlying British estimates start.
Figure 23: Income inequality and wealth inequality, top 1%, UK, 1895-2014. UK top 1% and top 10% shares of pre-tax income and net personal wealth over 119 years, with wealth consistently more concentrated than income.
Figure 24: Income inequality and wealth inequality, top 10%, UK, 1895-2014
The wealth line sits above the income line across all 114 years, at both the top 1% and the top 10%, and the two broadly move together. The turning points support the report's suggestion that income inequality acts as a leading indicator of wealth inequality: the top 1% income share bottomed out in 1978 and the wealth share not until 1984, and at the top 10% the gap is wider still, income turning in 1979 and wealth in 1990. Income is the tap, wealth is the tank, and sustained differences in the flow accumulate into larger differences in the stock.
The two also converge. In 1900 the top 1% held 44 percentage points more of Britain's wealth than of its income; by 2014 that gap was 9 points. At the top 10% it narrows from 43 points to 21. So wealth remains the more concentrated of the two, but by nothing like the margin it once was.
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