The issue of inequality has come into increasing focus over recent years. The impact of the COVID-19 pandemic raises further concerns that these inequalities may be exacerbated further. Here we provide an overview of some of the key patterns in current levels of wealth and income inequality in Britain. They show, for example, the markedly higher degree of inequality in wealth relative to income, the importance of property wealth and private pension wealth in determining levels of wealth, and the considerable variation in average wealth levels of households by age and location.
According to the 6th round of the Wealth and Assets Survey the aggregate wealth of British households was £14.63 trillion in April 2016 to March 2018. This compares with £12.57 trillion in the previous survey which ran from April 2014 to March 2016. This amounts to a 16.3 per cent nominal increase. In real terms, after adjusting for consumer price inflation, the increase was 13.1 per cent. Furthermore, when compared with the first round of the survey in July 2006 to June 2008, there has been a nominal increase in the aggregate wealth of British households of 74 per cent and a real increase of 41 per cent.
What is wealth?
An important question to ask when reflecting on the growth and distribution of wealth across households is what wealth comprises. In fact, it comprises one of four components:
- Net Financial wealth – the value of financial assets (savings and financial investments) less any financial liabilities (loans and arrears)
- Physical wealth – the value of household contents, possessions, valuables and vehicles
- Private pension wealth – the value of private pensions, such as occupational pensions and personal pensions
- Net property wealth – the value of any property owned (including other land/properties owned abroad) less the value of any loans or mortgages secured on these properties.
Figure 1 shows the evolution of aggregate wealth over the last two surveys (at constant 2016-18 prices) by the four component parts. Two components dominate the aggregate wealth of British households: property wealth (35 per cent) and private pension wealth (41-42 per cent). Financial wealth is the third largest component (14 per cent), while property wealth is the smallest component (9 to 10 per cent). (Click here for a PowerPoint of the chart.)
Trends in the average wealth of households
To help contextualise the size of wealth and begin to think about its distribution, rather than look at aggregate household wealth we can instead look at the average wealth of British households.
Figure 2 shows the average wealth (at constant 2016-18 prices) as measured by the mean (aggregate divided by the number of households) and the median (the middle household). The mean wealth of households is seen to be greater than their median wealth. In April 2016 to March 2018, average wealth as measured by the mean was £564,300 (an increase of 40.3 per cent over July 2006 to June 2008), whilst the average wealth of each household as measured by the median was £286,600 (an increase of 28.5 per cent over July 2006 to June 2008). (Click here for a PowerPoint of the chart.)
The higher mean value of wealth relative to the median value shows that the distribution of wealth is unequal. Therefore, the mean-to-median ratio is an indicator of inequality. In April 2016 to March 2018 the mean-to-median ratio was 1.97, up from 1.94 in April 2014 to March 2016 and 1.77 in July 2008 to June 2010, and 1.8 in the first survey in July 2006 to June 2008. This metric is therefore consistent with a more unequal distribution of wealth having arisen since the second survey in July 2008 to June 2010, a period during which the UK and global economy was been buffeted by the effects of the financial crisis and the associated economic downturn.
Trends in the average income of households
Figure 3 shows the mean and median values of disposable income (adjusted for the number and age of individuals comprising each household). Mean disposable income of UK households in financial year ending (FYE) 2018 was £35,928, a 0.5 per cent real decrease over FYE 2017, whilst median wealth (middle household) was £29,598 in FYE 2018, a 1.5 per cent real increase over FYE 2017. (Click here for a PowerPoint of the chart.)
The higher mean value of disposable income relative to the median value is indicative of inequality in disposable income. In FYE 2018 the mean-to-median ratio for disposable income was 1.21, down from 1.24 in FYE 2017 and a peak of 1.27 in FYE 2014, but higher than the 1.10 in 1978. The longer-term growth in the inequality of income helps to exacerbate existing wealth inequalities.
Comparing the inequality of income and wealth
Figure 4 shows starkly the current inequality in wealth as compared to that in income. It does so by plotting their respective Lorenz curves. The curves show the proportion of overall wealth or income attributable to a given proportion of households. For example, 50 per cent of households have close to 28 per cent of total disposable income and a mere 8.5 per cent of aggregate wealth. (Click here for a PowerPoint of the chart.)
The inequality shown by the Lorenz curves is especially startling when we look at the top and bottom deciles. The bottom decile has just 2.9 per cent of income and only 0.07 per cent of wealth. Meanwhile the top 10 per cent of households have 28.5 per cent of income, almost the same as the first 50 percent of households, and some 44.6 per cent of wealth, with the previous 90 per cent of households having 55.4 per cent of wealth.
The Lorenz curves allow for the calculation of the Gini coefficient. It measures the area between the Lorenz curve and the 45 degree line consistent with zero inequality relative to the total area below the 45 degree line. Therefore, the Gini coefficient can take a value of between 0% (no inequality) and 100% (total inequality – where one person has all the wealth). Unsurprisingly whilst the Gini coefficient for disposable income in the UK in FYE 2018 was 34.7 per cent, that for aggregate wealth in Great Britain in April 2016 to March 2018 was significantly higher at 63.3 per cent.
The Gini coefficient for disposable income has risen from 25.5 per cent in 1977 to a peak in FYE 2008 of 38.6 per cent. It has therefore eased during the 2010s, but is nonetheless 13 percentage points higher today than it was four decades ago. Meanwhile, the Gini coefficient for wealth at the time of the first survey from July 2006 to June 2008 was 61 per cent. It has been unchanged at 63 percent over the last three surveys.
Inequality in wealth by component, location and age
It is important to recognise the inequalities in the components of wealth. This has particular importance when we are trying to understand how wealth varies by household characteristics, such as age and location.
Figure 5 shows that the highest Gini coefficient is for net financial wealth. This stood at 91 per cent in April 2016 to March 2018. This extremely high figure shows the very high levels of inequatity in net financial wealth. This reflects the fact that some households find themselves with negative net financial wealth, such that their debts exceed their assets, whilst, on the other hand, some households can have large sums in financial investments. (Click here for a PowerPoint of the chart.)
We saw at the outset that the largest two components of wealth are property wealth and private pension wealth. The Gini coefficients of these two have in recent times moved in opposite directions by roughly similar magnitudes. This means that their effects on the overall Gini coefficient have offset one another. Perhaps for many people the rise in Gini coeffcient for property from 62 per cent in July 2006 to June 2008 to 66 per cent in April 2016 to March 2018 is the inequality measure that resonates most. This is reflected in regional disparities in wealth.
Figure 6 shows the geographical disparity of median household wealth across Britain. The regions with the highest median wealth are the South East, South West, London and the East of England. They have the highest contributions from net property wealth (40.4 per cent, 35.6 per cent, 41.7 per cent and 37.2 per cent respectively). The region with the lowest median total wealth, the North East, has the least total wealth in net property wealth (24.8 per cent). (Click here for a PowerPoint of the chart.)
Property wealth and private pension wealth also contribute to disparities in wealth by the age of the head of the household, also known as the household reference person or HRP. In April 2016 to March 2018 the mean wealth where the HRP is 25-34 was £125,700, rising to £859,200 where the HRP is 55-64 and then falling to £692,300 when the HRP is 65 or over. This is consistent with households accruing wealth over time and the using wealth to help fund retirement.
Where the age of the HRP is 55-64, mean property wealth in April 2016 to March 2018 was £255,800 compared to £53,700 where the HRP is 25-34. Meanwhile, where the age of the HRP is 55-64, mean private pension wealth was £449,100 compared to just £32,300 where the HRP is 25-34. In respect of property wealth, the deterioration in the affordability of owner-occupied housing over many years will impact especially hard on younger households. This will therefore tend to exacerbate inter-generational wealth inequality.
Whilst this briefing provides an overview of recent patterns in income and wealth inequality in Britain, the articles and press releases below consider the impact that the COVID-19 pandemic may have on inequalities.
Articles and Press Releases
- Many better-off households may increase savings as spending on ‘banned’ activities falls. Poorer households spend much more of their income on necessities and will be less resilient to any falls in income
IFS Press Release, Rowena Crawford, Alex Davenport, Robert Joyce and Peter Levell (08/04/20)
- Sector shut-downs during the coronavirus crisis affect the youngest and lowest paid workers, and women, the most
IFS Press Release, Robert Joyce and Xiaowei Xu (06/04/20)
- Coronavirus downturn ‘will exacerbate UK health inequality’
City A.M., James Warrington (09/04/20)
- Coronavirus pandemic exacerbates inequalities for women, UN warns
Guardian, Alexandra Villarreal (11/04/20)
- Inequality doesn’t just make pandemics worse – it could cause them
Guardian, Laura Spinney (12/04/20)
- The Coronavirus Will Be a Catastrophe for the Poor
The Atlantic, Derek Thompson (20/03/20)
- EU-wide inequality is back to pre-crisis levels
Social Europe, Michael Dauderstädt (15/04/20)
- Coronavirus makes inequality a public health issue
World Economic Forum, Alexandre Kalache (President, International Longevity Centre-Brazil) (13/04/20)
- Economist Joseph Stiglitz says coronavirus is ‘exposing’ health inequality in US
- CNBC, Jesse Pound (14/04/20)
- In what ways can we use statistics to help measure and inform our analysis of inequality?
- In what ways can income inequality impact on wealth inequality?
- How can wealth inequality impact on income inequality?
- What might explain why wealth inequality is greater than income inequality?
- Explain how Lorenz curves help to generate Gini coefficients.
- Why would we expect the wealth of households with a younger household reference person (HRP) to be lower than that of a household with an older HRP? Would we expect this average to rise over all age ranges?
- If you were advising a government on policies to reduce income and wealth inequalities what sort of measures might you suggest?
- What is the difference between original income and disposable income?
- What is the difference between disposable income and equivalised disposable income?
- What role does the housing market play in affecting wealth inequality?
- Why is net financial wealth so unequally distributed?
- What is meant by health inequality? Of what significance is this for income and wealth inequality?
- What is meant by social mobility? Of what significance is this for income and wealth inequality?
What is the relationship between the degree of inequality in a country and the rate of economic growth? The traditional answer is that there is a trade off between the two. Increasing the rewards to those who are more productive or who invest encourages a growth in productivity and capital investment, which, in turn, leads to faster economic growth. Redistribution from the rich to the poor, by contrast, is argued to reduce incentives by reducing the rewards from harder work, education, training and investment. Risk taking, it is claimed, is discouraged.
Recent evidence from the OECD and the IMF, however, suggests that when income inequality rises, economic growth falls. Inequality has grown massively in many countries, with average incomes at the top of the distribution seeing particular gains, while many at the bottom have experienced actual declines in real incomes or, at best, little or no growth. This growth in inequality can be seen in a rise in countries’ Gini coefficients. The OECD average Gini coefficient rose from 0.29 in the mid-1980s to 0.32 in 2011/12. This, claims the OECD, has led to a loss in economic growth of around 0.35 percentage points per year.
But why should a rise in inequality lead to lower economic growth? According to the OECD, the main reason is that inequality reduces the development of skills of the lower income groups and reduces social mobility.
By hindering human capital accumulation, income inequality undermines education opportunities for disadvantaged individuals, lowering social mobility and hampering skills development.
The lower educational attainment applies both to the length and quality of education: people from poorer backgrounds on average leave school or college earlier and with lower qualifications.
But if greater inequality generally results in lower economic growth, will a redistribution from rich to poor necessarily result in faster economic growth? According to the OECD:
Anti-poverty programmes will not be enough. Not only cash transfers but also increasing access to public services, such as high-quality education, training and healthcare, constitute long-term social investment to create greater equality of opportunities in the long run.
Thus redistribution policies need to be well designed and implemented and focus on raising incomes of the poor through increased opportunities to increase their productivity. Simple transfers from rich to poor via the tax and benefits system may, in fact, undermine economic growth. According to the IMF:
That equality seems to drive higher and more sustainable growth does not in itself support efforts to redistribute. In particular, inequality may impede growth at least in part because it calls forth efforts to redistribute that themselves undercut growth. In such a situation, even if inequality is bad for growth, taxes and transfers may be precisely the wrong remedy.
Inequality ‘significantly’ curbs economic growth – OECD BBC News (9/12/14)
Is inequality the enemy of growth? BBC News, Robert Peston (6/10/14)
Income inequality damages growth, OECD warns Financial Times, Chris Giles (8/10/14)
OECD finds increasing inequality lowers growth Deutsche Welle, Jasper Sky (10/12/14)
Revealed: how the wealth gap holds back economic growth The Guardian, Larry Elliott (9/12/14)
Inequality Seriously Damages Growth, IMF Seminar Hears IMF Survey Magazine (12/4/14)
Warning! Inequality May Be Hazardous to Your Growth iMFdirect, Andrew G. Berg and Jonathan D. Ostry (8/4/11)
Economic growth more likely when wealth distributed to poor instead of rich The Guardian, Stephen Koukoulas (4/6/15)
So much for trickle down: only bold reforms will tackle inequality The Guardian, Larry Elliott (21/6/15)
Record inequality between rich and poor OECD on YouTube (5/12/11)
The Price of Inequality The News School on YouTube, Joseph Stiglitz (5/10/12)
Reports and papers
FOCUS on Inequality and Growth OECD, Directorate for Employment, Labour and Social Affairs (December 2014)
Trends in Income Inequality and its Impact on Economic Growth OECD Social, Employment and Migration Working Papers, Federico Cingano (9/12/14)
An Overview of Growing Income Inequalities in OECD Countries: Main Findings OCED (2011)
Redistribution, Inequality, and Growth IMF Staff Discussion Note, Jonathan D. Ostry, Andrew Berg, and Charalambos G. Tsangarides (February 2014)
Measure to Measure Finance and Development, IMF, Jonathan D. Ostry and Andrew G. Berg (Vol. 51, No. 3, September 2014)
OECD Income Distribution Database: Gini, poverty, income, Methods and Concepts OECD
The effects of taxes and benefits on household income ONS
- Explain what are meant by a Lorenz curve and a Gini coefficient? What is the relationship between the two?
- The Gini coefficient is one way of measuring inequality. What other methods are there? How suitable are they?
- Assume that the government raises taxes to finance higher benefits to the poor. Identify the income and substitution effects of the tax increases and whether the effects are to encourage or discourage work (or investment).
- Distinguish between (a) progressive, (b) regressive and (c) proportional taxes?
- How will the balance of income and substitution effects vary in each of the following cases: (a) a cut in the tax-free allowance; (b) a rise in the basic rate of income tax; (c) a rise in the top rate of income tax? How does the relative size of the two effects depend, in each case, on a person’s current income?
- Identify policy measures that would increase both equality and economic growth.
- Would a shift from direct to indirect taxes tend to increase or decrease inequality? Explain.
- By examining Tables 3, 26 and 27 in The Effects of Taxes and Benefits on Household Income, 2012/13, (a) explain the difference between original income, gross income, disposable income and post-tax income; (b) explain the differences between the Gini coefficients for each of these four categories of income in the UK.
In his 1971 book, Income Distribution, Jan Pen, a Dutch economist, gave a graphic illustration of inequality in the UK. He described a parade of people marching by. They represent the whole population and the parade takes exactly one hour to pass by. The height of each person represents his or her income. People of average height are the people with average incomes – the observer is of average height. The parade starts with the people on the lowest incomes (the dwarfs), and finishes with those on the highest incomes (the giants).
Because income distribution is unequal, there are many tiny people. Indeed, for the first few minutes of the parade, the marchers are so small they can barely be seen. Even after half an hour, when people on median income pass by, they are barely waist high to the observer.
The height is growing with tantalising slowness, and forty-five minutes have gone by before we see people of our own size arriving. To be somewhat more exact: about twelve minutes before the end the average income recipients pass by.
In the final minutes, giants march past and then in the final seconds:
the scene is dominated by colossal figures: people like tower flats. Most of them prove to be businessmen, managers of large firms and holders of many directorships and also film stars and a few members of the Royal Family.
The rear of the parade is brought up by a few participants who are measured in miles. Indeed they are figures whose height we cannot even estimate: their heads disappear into the clouds and probably they themselves do not even know how tall they are.
Pen’s description could be applied to most countries – some with even more dwarfs and even fewer but taller giants. Generally, over the 43 years since the book was published, countries have become less equal: the giants have become taller and the dwarfs have become smaller.
The 2011 Economist article, linked below, uses changes in Gini coefficients to illustrate the rise in income inequality. A Gini coefficient shows the area between the Lorenz curve and the 45° line. The figure will be between 0 and 1 (or 0% and 100%). a figure of 0 shows total equality; a figure of 1 shows a situation of total inequality, where one person earns all the nation’s income. The higher the figure, the greater the inequality.
The chart opposite shows changes in the Gini coefficient in the UK (see Table 27 in the ONS link below for an Excel file of the chart). As this chart and the blog post Rich and poor in the UK show, inequality rose rapidly during the years of the 1979–91 Thatcher government, and especially in the years 1982–90. This was associated with cuts in the top rate of income tax and business deregulation. It fell in the recession of the early 1990s as the rich were affected more than the poor, but rose with the recovery of the mid- to late 1990s. It fell again in the early 2000s as tax credits helped the poor. It fell again following the financial crisis as, once more, the rich were affected proportionately more than the poor.
The most up-to-date international data for OECD countries can be found on the OECD’s StatExtracts site (see chart opposite: click here for a PowerPoint). The most unequal developed county is the USA, with a Gini coefficient of 0.389 in 2012 (see The end of the American dream?), and US inequality is rising. Today, the top 1% of the US population earns some 24% of national income. This compares with just 9% of national income in 1976.
Many developing countries are even less equal. Turkey has a Gini coefficient of 0.412 and Mexico of 0.482. The figure for South Africa is over 0.6.
When it comes to wealth, distribution is even less equal. The infographic, linked below, illustrates the position today in the USA. It divides the country into 100 equal-sized groups and shows that the top 1% of the population has over 40% of the nation’s wealth, whereas the bottom 80% has only 7%.
So is this inequality of income and wealth desirable? Differences in wages and salaries provide an incentive for people to work harder or more effectively and to gain better qualifications. The possibility of increased wealth provides an incentive for people to invest.
But are the extreme differences in wealth and income found in many countries today necessary to incentivise people to work, train and invest? Could sufficient incentives exist in more equal societies? Are inequalities in part, or even largely, the result of market imperfections and especially of economic power, where those with power and influence are able to use it to increase their own incomes and wealth?
Could it even be the case that excessive inequality actually reduces growth? Are the huge giants that exist today accumulating too much financial wealth and creating too little productive potential? Are they spending too little and thus dampening aggregate demand? These arguments are considered in some of the articles below. Perhaps, by paying a living wage to the ‘tiny’ people on low incomes, productivity could be improved and demand could be stimulated.
Wealth Inequality in America YouTube, Politizane (20/11/12)
The rise and rise of the cognitive elite The Economist (20/1/11)
Inequality in America: Gini in the bottle The Economist (26/11/13)
Pen’s Parade: do you realize we’re mostly dwarves? LVTFan’s Blog (21/2/11)
Here Are The Most Unequal Countries In The World Business Insider, Andy Kiersz (8/11/14)
Inequality in the World Dollars & Sense, Arthur MacEwan (Nov/Dec 14)
Britain is scared to face the real issue – it’s all about inequality The Observer, Will Hutton (19/1/14)
The tame inequality debate FundWeb, Daniel Ben-Ami (Nov 14)
Is inequality the enemy of growth? BBC News, Robert Peston (6/10/14)
GINI index World Bank data
List of countries by income equality Wikipedia
The Effects of Taxes and Benefits on Household Income, 2012/13 ONS (see table 27)
Income Distribution and Poverty: Gini (disposale income) OECD StatExtract
- Distinguish between income and wealth. Is each one a stock or a flow?
- Explain how (a) a Lorenz curve and (b) a Gini coefficient are derived.
- What other means are there of measuring inequality of income and wealth other than using Gini coefficients (and giants and dwarfs!)?
- Why has inequality been rising in many countries over the years?
- How do (a) periods of rapid economic growth and (b) recessions affect income distribution?
- Define ‘efficiency wages’. How might an increase in wages to people on low incomes result in increased productivity?
- What is the relationship between the degree of inequality and household debt? What implications might this have for long-term economic growth and future financial crises? Is inequality the ‘enemy of growth’?
The ONS has just released its annual publication, The Effects of Taxes and Benefits on Household Income. The report gives data for the financial year 2012/13 and historical data from 1977 to 2012/13.
The publication looks at the distribution of income both before and after taxes and benefits. It divides the population into five and ten equal-sized groups by household income (quintiles and deciles) and shows the distribution of income between these groups. It also looks at distribution within specific categories of the population, such as non-retired and retired households and different types of household composition.
The data show that the richest fifth of households had an average pre-tax-and-benefit income of £81,284 in 2012/13, 14.7 times greater than average of £5536 for the poorest fifth. The richest tenth had an average pre-tax-and-benefit income of £104,940, 27.1 times greater than the average of £3875 for the poorest tenth.
After the receipt of cash benefits, these gaps narrow to 6.6 and 11.0 times respectively. When the effect of direct taxes are included (giving ‘disposable income’), the gaps narrow further to 5.6 and 9.3 times respectively. However, when indirect taxes are also included, the gaps widen again to 6.9 and 13.6 times.
This shows that although direct taxes are progressive between bottom and top quintiles and deciles, indirect taxes are so regressive that the overall effect of taxes is regressive. In fact, the richest fifth paid 35.1% of their income in tax, whereas the poorest fifth paid 37.4%.
Taking the period from 1977 to 2012/13, inequality of disposable income (i.e. income after direct taxes and cash benefits) increased from 1977 to 1988, especially during the second two Thatcher governments (1983 to 1990) (see chart opposite). But then in the first part of the 1990s inequality fell, only to rise again in the late 1990s and early 2000s. However, with the Labour government giving greater cash benefits for the poor, inequality reduced once more, only to widen again in the boom running up to the banking crisis of 2007/8. But then, with recession taking hold, the incomes of many top earners fell and automatic stabilisers helped protect the incomes of the poor. Inequality consequently fell. But with the capping of benefit increases and a rise in incomes of many top earners as the economy recovers, so inequality is beginning to rise once more – in 2012/13, the Gini coefficient rose to 0.332 from 0.323 the previous year.
As far as income after cash benefits and both direct and indirect taxes is concerned, the average income of the richest quintile relative to that of the poorest quintile rose from 7.2 in 2002/3 to 7.6 in 2007/8 and then fell to 6.9 in 2012/13.
Other headlines in the report include:
Since the start of the economic downturn in 2007/08, the average disposable income has decreased for the richest fifth of households but increased for the poorest fifth.
Cash benefits made up over half (56.4%) of the gross income of the poorest fifth of households, compared with 3.2% of the richest fifth, in 2012/13.
The average disposable income in 2012/13 was unchanged from 2011/12, but it remains lower than at the start of the economic downturn, with equivalised disposable income falling by £1200 since 2007/08 in real terms. The fall in income has been largest for the richest fifth of households (5.2%). In contrast, after accounting for inflation and household composition, the average income for the poorest fifth has grown over this period (3.5%).
This is clearly a mixed picture in terms of whether the UK is becoming more or less equal. Politicians will, no doubt, ‘cherry pick’ the data that suit their political position. In general, the government will present a good news story and the opposition a bad news one. As economists, it is hoped that you can take a dispassionate look at the data and attempt to relate the figures to policies and events.
The Effects of Taxes and Benefits on Household Income, 2012/13 ONS (26/6/14)
Reference tables in The Effects of Taxes and Benefits on Household Income, 2012/13 ONS (26/6/14)
The Effects of Taxes and Benefits on Household Income, Historical Data, 1977-2012/13 ONS (26/6/14)
Rates of Income Tax: 1990-91 to 2014-15 HMRC
Inequality is on the up again – Osborne’s boast is over New Statesman, George Eaton (26/6/14)
Disposable incomes rise for richest fifth households only Money.com, Lucinda Beeman (26/6/14)
Half of families receive more from the state than they pay in taxes but income equality widens as rich get richer Mail Online, Matt Chorley (26/6/14)
Rich getting richer as everyone else is getting poorer, Government’s own figures reveal Mirror, Mark Ellis (26/6/14)
The Richest Households Got Richer Last Year, While Everyone Else Got Poorer The Economic Voice (27/6/14)
- Define the following terms: original income, gross income, disposable income, post-tax income, final income.
- How does the receipt of benefits in kind vary across the quintile groups? Explain.
- What are meant by the Lorenz curve and the Gini coefficient and how is the Gini coefficient measured? Is it a good way of measuring inequality?
- Paint a picture of how income distribution has changed over the past 35 years.
- Can changes in tax be a means of helping the poorest in society?
- What types of income tax cuts are progressive and what are regressive?
- Why are taxes in the UK regressive?
- Why has the fall in income been largest for the richest fifth of households since 2007/8? Does this mean that, as the economy recovers, the richest fifth of households are likely to experience the fastest increase in disposable incomes?
Inequality is growing in most countries. This can be illustrated by examining what has been happening to countries’ Gini coefficient. The Gini coefficient measures income inequality, where 0.00 represents perfect equality, with everyone in the country earning the same, and 1.00 represent perfect inequality, with one person earning all the country’s income. (Note that sometimes it is expressed as the ‘Gini index’, with 100 representing perfect inequality). In virtually all countries, the Gini coefficient has been rising. In the OECD countries it has risen by an average of 0.3% per annum over the past 25 years. The OECD average is now 0.31.
But despite the fact that the Gini coefficient has been rising, its value differs markedly from one country to another, as does its rate of change. For example, Finland’s Gini coefficient, at 0.26, is below the average, but it has been rising by 1.2% per annum. By contrast, Turkey’s Gini coefficient, at 0.41, is above the average and yet has been falling by 0.3% per annum.
The most unequal of the developed countries is the USA. According to OECD data, its Gini coefficient is 0.38, well above the values in the UK (0.34), Japan (0.33), Germany (0.30) France (0.29) and Denmark (0.26). What is more, inequality in the USA has been increasing by an average of 0.5% per annum since the mid 1980s.
According to the United Nations’ Human Development Report 2010, the USA’s Gini coefficient is even higher, at 0.41 (see Table 3 of the report). But this is still below that of Russia, with a figure of 0.44, a figure that has markedly worsened over time, along with those of other former Soviet countries. According to the report (page 72):
The worsening is especially marked in countries that were part of the former Soviet Union – which still have relatively low Gini coefficients because they started with low inequality. Transition has eroded employment guarantees and ended extensive state employment. Before the fall of the Berlin Wall, 9 of 10 people in socialist countries were employed by the state, compared with 2 of 10 in Organisation for Economic Co-operation and Development economies. While the privileged elite (the nomenklatura) often attained higher material well-being, the measured differences in income were narrow.
The Gini coefficient for Russia is the same as the average of the 39 developing countries with the lowest level of human development &nbash; and developing countries are generally much less equal than developed ones. Of course, some developing countries have an even higher Gini coefficient: for Angola the figure is 0.59; for Haiti it is 0.60.
The following three webcasts look at aspects of the growing inequality in Russia.
Gap between rich and poor widens in Russia BBC News, Jamie Robertson (29/5/11)
Corruption slows Russian modernisation BBC News, Emma Simpson (29/5/11)
Corruption and poverty in Russia’s far east Al Jazeera (28/2/11)
Russia’s rich double their wealth, but poor were better off in 1990s Guardian, Tom Parfitt (11/4/11)
Russia’s growing wealth gap BBC News, Jamie Robertson (28/5/11)
A Country of Beggars and Choosers Russia Profile, Svetlana Kononova (16/5/11)
Rich and poor, growing apart The Economist (3/5/11)
Distribution of family income – Gini Index CIA World Factbook (ranked by country in desending order)
Society at a Glance 2011 – OECD Social Indicators OECD: see particularly the Excel file 6. Equity Indicators: Income inequality (click on No if prompted about a linked workbook)
Russia Distribution of family income – Gini index Index Mundi
Chart of the week: inflation stoking inequality in China and India Financial Times, Andrew Whiffin (24/5/11)
List of countries by income equality Wikipedia
Growing Income Inequality in OECD Countries: What Drives it and How Can Policy Tackle it? OECD Forum on Tackling Inequality (2/5/11)
Human Development Report 2010 United Nations Development Programme
- Explain what is meant by the Gini coefficient. How does it relate to the Lorenz curve? What does a figure of 0.31 mean?
- Why has income inequality been growing in most countries of the world? Has the process of globalisation dampened or exacerbated this trend?
- What specific factors in Russia can explain the growing inequality?
- How is privatisation likely to affect income distribution??
- Why is it difficult to quantify the extent of inequality in Russia?
- What maxim of taxation has been used in setting income tax rates in Russia?
- What role does corruption play in determining the degree of inequality in Russia?
- What policy measures, if any, could realistically be adopted in Russia to reduce inequality? What constraints are there on adopting such policies?