Author: Dean Garratt

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

ONS Bulletins

Questions

  1. In what ways can we use statistics to help measure and inform our analysis of inequality?
  2. In what ways can income inequality impact on wealth inequality?
  3. How can wealth inequality impact on income inequality?
  4. What might explain why wealth inequality is greater than income inequality?
  5. Explain how Lorenz curves help to generate Gini coefficients.
  6. 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?
  7. If you were advising a government on policies to reduce income and wealth inequalities what sort of measures might you suggest?
  8. What is the difference between original income and disposable income?
  9. What is the difference between disposable income and equivalised disposable income?
  10. What role does the housing market play in affecting wealth inequality?
  11. Why is net financial wealth so unequally distributed?
  12. What is meant by health inequality? Of what significance is this for income and wealth inequality?
  13. What is meant by social mobility? Of what significance is this for income and wealth inequality?

The monetary policy mandates of central banks have an impact on all our lives. While the terminology might not be familiar to many outside economics, their impact is, however, undeniably important. This is because they set out the objectives for the operation of monetary policy. Adjustments to interest rates or the growth of the money supply, which affect us all, reflect the mandate given to the central bank.

Since 1977 the mandate given to the Federal Reserve (the US central bank) by Congress has been to promote effectively the goals of maximum employment, stable prices, and moderate long-term interest rates. This mandate has become known as the dual mandate because it emphasises both employment and stable prices. Since 2012, the Federal Reserve’s Open Market Committee has issued an annual statemenent of its long-run goals. The latest was published in January 2019. Since this time, the Federal Reserve has explicitly set the ‘longer-run goal for inflation’ at 2 per cent. It has also emphasised that it would be ‘concerned’ if the inflation rate was persistently above or below this level.

In November 2018 the Federal Reserve began a review of its monetary policy strategy, its tools and how it communicates monetary policy. The review is being conducted within the guidelines that its statutory mandate gives and as well as the longer-term inflation goal of 2 per cent. However, one of the issues being addressed by the review is how the operation of monetary policy can avoid the rate of inflation frequently undershooting 2 per cent, as it has done since the financial crisis of the late 2000s and the introduction of the 2 per cent inflation rate target.

Chart 1 shows the annual rate of consumer price inflation in the US since 1998. It helps to illustrate the concern that low inflation rates can become entrenched. The chart shows that, while the average inflation rate from 1998 to 2008 was 2.7 per cent, from 2009 the average has been only 1.6 per cent. Interestingly, the average since 2012, when the explicit 2 per cent goal was introduced, to the present day is also 1.6 per cent. (Click here to download the PowerPoint chart.)

The concern going forward is that the natural or neutral rate of interest, which is the policy rate at which the rate of inflation is close to its target level and the level of output is close to its potential level, is now lower than in the recent past. Hence, when the next downturn occurs there is likely to be less room for cutting interest rates. Hence, the review is looking, in essence, to future-proof the conduct of monetary policy.

Chart 2 shows the Federal Fund rate since 1998. This is the rate at which commercial banks lend to each other the reserve balances they hold at the Federal Reserve in order to meet their reserve requirements. The Federal Reserve can affect this rate through buying or selling government securities. If it wants to drive up rates, it can sell holdings of government securities and reduce the money supply. If it wants to drive rates down, it can buy government securities and increase the money supply. The effects then ripple through to other interest rates and, in turn, aggregate demand and inflation. (Click here to download a copy of the PowerPoint chart.)

We can see from Chart 2 the dramatic cuts made by the Federal Reserve to interest rates as the financial crisis unfolded. The subsequent ‘normalisation’ of the Federal Funds rate in the 2010s saw the Federal Funds Rate rise to no higher than between 2.25 and 2.5 per cent. Then in 2019 the Federal Reserve began to cut rates again. This was despite historically-low unemployment rates. In November 2019 the unemployment rate fell to 3.5 per cent, its lowest since 1969. This has helped fuel the argument among some economists and financiers, which we saw earlier, that that the natural (or neutral) interest rate is now lower.

If the natural rate is lower, then this raises concerns about the effectiveness of monetary policy in future economic downturns. In this context, the review is considering ways in which the operation of monetary policy would be able to prevent the rate of inflation consistently undershooting its target. This includes a discussion of how the Fed can prevent inflationary expectations becoming anchored below 2 per cent. This is important because, should they do so, they help to anchor the actual rate of inflation below 2 per cent. One possibility being considered is an inflation make-up strategy. In other words, a period of below-target inflation rates would need to be matched by a period where inflation rates could exceed the 2 per cent target in order that the long-term average of 2 per cent is met.

An inflation make-up policy would work like forward guidance in that people and markets would know know that short-term interest rates would be kept lower for longer. This would then help to force longer-term interest rates lower as well as providing people and businesses with greater certainty that interest rates will be lower for longer. This could help to encourage spending, raise economic growth and prevent inflation from overshooting its target for any extensive period of time.

An inflation make-up strategy would, in part, help to cement the idea that the inflation target is effectively symmetrical and that 2 per cent is not an upper limit for the inflation rate. But, it would do more than that: it would allow the Fed to deliberately exceed the 2 per cent target.

An inflation make-up strategy does raise issues. For example, how would the Fed determine the magnitude of any inflation make-up and for how long would a looser monetary stance be allowed to operate? In other words, would an inflation make-up strategy be determined by a specific rule or formula? Or, would the principle be applied flexibly? Finally, could a simpler alternative be to raise the target rate itself, given the tendency to undershoot the 2 per cent target rate? If so, what should that the rate be?

We should know by the end of 2020 whether the Federal Reserve will adopt, when necessary, an inflation make-up monetary policy.

Articles

Questions

  1. What do you understand by the monetary policy mandate of a central bank?
  2. Explain the ways in which the monetary policy mandate of the central bank affects our everyday lives.
  3. Why are inflation-rate expectations important in determining actual inflation rates?
  4. Why is the Federal Reserve concerned about its ability to use monetary policy effectively during future economic downturns?
  5. Discuss the economic arguments for and against central banks operating strict inflation-rate targets.
  6. Does the case for adopting an inflation make-up monetary policy mandate show that the argument for inflation-rate targeting has been lost?
  7. What do you understand by the idea of a natural or neutral policy interest rate? Would the actual rate be expected to be above or below this if the rate of inflation was below its target level?

The latest UK house price index reveals that annual house price growth in the UK slowed to just 1.2 per cent in May. This is the lowest rate of growth since January 2013. This is being driven, in part, by the London market where annual house price inflation rates have now been negative for 15 consecutive months. In May the annual rate of house price inflation in London fell to -4.4 per cent, it lowest since August 2009 as the financial crisis was unfolding. However, closer inspection of the figures show that while many other parts of the country continue to experience positive rates of annual house price inflation, once general inflation is accounted for, there is widespread evidence of widespread real house price deflation.

The average UK house price in May 2019 was £229,000. As Chart 1 shows, this masks considerable differences across the UK. In England the average price was £246,000 (an annual increase of 1.0 per cent), in Scotland it was £153,000 (an increase of 2.8 per cent), in Wales £159,000 (an increase of 3.0 per cent) and in Northern Ireland it was £137,000 (an increase of 2.1 per cent). (Click here to download a PowerPoint copy of the chart.)

The London market distorts considerably the English house price figures. In London the average house price in May 2019 was £457,000 (an annual decrease of 4.4 per cent). House prices were lowest in the North East region of England at £128,000. The North East was the only other English region alongside London to witness a negative rate of annual house price inflation, with house prices falling in the year to May 2019 by 0.7 per cent.

Chart 2 allows us to see more readily the rates of house price growth. It plots the annual rates of house price inflation across London, the UK and its nations. What is readily apparent is the volatility of house price growth. This is evidence of frequent imbalances between the flows of property on to the market to sell (instructions to sell) and the number of people looking to buy (instructions to buy). An increase in instructions to buy relative to those to sell puts upwards pressure on prices whereas an increase in the relative number of instructions to sell puts downward pressure on prices. (Click here to download a PowerPoint copy of the chart.)

Despite the volatility in house prices, the longer-term trend in house prices is positive. The average annual rate of growth in house prices between January 1970 and May 2019 in the UK is 9.1 per cent. For England the figure is 9.4 per cent, for Wales 8.8 per cent, for Scotland 8.5 per cent and for Northern Ireland 8.3 per cent. In London the average rate of growth is 10.4 per cent per annum.

As Chart 3 illustrates, the longer-term growth in actual house prices cannot be fully explained by the growth in consumer prices. It shows house price values as if consumer prices, as measured by the Retail Prices Index (RPI), were fixed at their January 1987 levels. We see real increases in house prices or, expressed differently, in house prices relative to consumer prices. In real terms, UK house prices were 3.6 times higher in May 2019 compared to January 1970. For England the figure is 4.1 times, for Wales 3.1 times, for Scotland 2.9 times and for Northern Ireland 2.1 times. In London inflation-adjusted house prices were 5.7 times higher. (Click here to download a PowerPoint copy of the chart.)

The volatility in house prices continues to be evident when adjusted for changes in consumer prices. The UK’s annual rate of real house price inflation was as high as 40 per in January 1973, yet, on the other hand, in June 1975 inflation-adjusted house prices were 16 per cent lower than a year earlier. Over the period from January 1970 to May 2019, the average annual rate of real house price inflation was 3.2 per cent. Hence house prices have, on average, grown at an annual rate of consumer price inflation plus 3.2 per cent.

Chart 4 shows annual rates of real house price inflation since 2008 and, hence, from around the time the financial crisis began to unfold. The period is characterised by acute volatility and with real house prices across the UK falling at an annual rate of 16 per cent in 2009 and by as much 29 per cent in Northern Ireland. (Click here to download a PowerPoint copy of the chart.)

The UK saw a rebound in nominal and real house price growth in the period from 2013, driven by a strong surge in prices in London and the South East, and supported by government initiatives such as Help to Buy designed to help people afford to buy property. But house price growth then began to ease from early/mid 2016. Some of the easing may be partly due to any excessive fizz ebbing from the market, especially in London, and the impact on the demand for buy-to-let investments resulting from reductions in tax relief on interest payments on buy-to-let mortgages.

However, the housing market is notoriously sensitive to uncertainty, which is not surprising when you think of the size of the investment people are making when they enter the market. The uncertainty surrounding Brexit and the UK’s future trading relationships will have been a drag on demand and hence on house prices.

Chart 4 shows that by May 2019 all the UK nations were experiencing negative rates of real house price inflation, despite still experiencing positive rates of nominal house price inflation. In Wales the real annual house price inflation rate was -0.1 per cent, in Scotland -0.2 per cent, in Northern Ireland -0.9 per cent and in England -2.0 per cent. Meanwhile in London, where annual house price deflation has been evident for 15 consecutive months, real house prices in May 2019 were falling at an annual rate of 7.2 per cent.

Going forward the OBR’s Fiscal Risks Report predicts that, in the event of a no-deal, no-transition exit of the UK from the European Union, nominal UK house prices would fall by almost 10 per cent between the start of 2019 and mid-2021. This forecast is driven by the assumption that the UK would enter a year-long recession from the final quarter of 2019. It argues that property transactions and prices ‘move disproportionately’ during recessions. (See John’s blog The costs of a no-deal Brexit for a fuller discussion of the economics of a no-deal Brexit). The danger therefore is that the housing market becomes characterised by both nominal and real house price falls.

Articles

Questions

  1. Explain the difference between a rise in the rate of house price inflation a rise in the level of house prices.
  2. Explain the difference between nominal and real house prices.
  3. If nominal house prices rise can real house price fall? Explain your answer.
  4. What do you understand by the terms instructions to buy and instructions to sell?
  5. What factors are likely to affect the levels of instructions to buy and instructions to sell?
  6. How does the balance between instructions to buy and instructions to sell affect house prices?
  7. How can we differentiate between different housing markets? Illustrate your answer with examples.

Confidence figures suggest that sentiment weakened across several sectors in June with significant falls recorded in retail and construction. This is consistent with the monthly GDP estimates from the ONS which suggest that output declined in March and April by 0.1 per cent and 0.4 per cent respectively. The confidence data point to further weakness in growth down the line. Furthermore, it poses the risk of fuelling a snowball effect with low growth being amplified and sustained by low confidence.

Chart 1 shows the confidence balances reported by the European Commission each month since 2007. It highlights the collapse in confidence across all sectors around the time of the financial crisis before a strong and sustained recovery in the 2010s. However, in recent months confidence indicators have eased significantly, undoubtedly reflecting the heightened uncertainty around Brexit. (Click here to download a PowerPoint copy of the chart.)

Between June 2016 and June 2019, the confidence balances have fallen by at least 8 percentage points. In the case of the construction the fall is 14 points while in the important service sector, which contributes about 80 per cent of the economy’s national income, the fall is as much as 15 points.

Changes in confidence are thought, in part, to reflect levels of economic uncertainty. In particular, they may reflect the confidence around future income streams with greater uncertainty pulling confidence down. This is pertinent because of the uncertainty around the UK’s future trading relationships following the 2016 referendum which saw the UK vote to leave the EU. In simple terms, uncertainty reduces the confidence people and businesses have when forming expectations of what they can expect to earn in the future.

Greater uncertainty and, hence, lower confidence tend to make people and businesses more prudent. The caution that comes from prudence counteracts the inherent tendency of many of us to be impatient. This impatience generates an impulse to spend now. On the other hand, prudence encourages us to take actions to increase net worth, i.e. wealth. This may be through reducing our exposure to debt, perhaps by looking to repay debts or choosing to borrow smaller sums than we may have otherwise done. Another option may be to increase levels of saving. In either case, the effect of greater prudence is the postponement of spending. Therefore, in times of high uncertainty, like those of present, people and businesses would be expected to want to have greater financial resilience because they are less confident about what the future holds.

To this point, the saving ratio – the proportion of disposable income saved by households – has remained historically low. In Q1 2019 the saving ratio was 4.4 per cent, well below its 60-year average of 8.5 per cent. This appears to contradict the idea that households respond to uncertainty by increasing saving. However, at least in part, the squeeze seen over many years following the financial crisis on real earnings, i.e. inflation-adjusted earnings, restricted the ability of many to increase saving. With real earnings having risen again over the past year or so, though still below pre-crisis levels, households may have taken this opportunity to use earnings growth to support spending levels rather than, as we shall see shortly, looking to borrow.

Another way in which the desire for greater financial resilience can affect behaviour is through the appetite to borrow. In the case of consumers, it could reduce borrowing for consumption, while in the case of firms it could reduce borrowing for investment, i.e. spending on capital, such as that on buildings and machinery. The reduced appetite for borrowing may also be mirrored by a tightening of credit conditions by financial institutions if they perceive lending to be riskier or want to increase their own financial capacity to absorb future shocks.

Chart 2 shows consumer confidence alongside the annual rate of growth of consumer credit (net of repayments) to individuals by banks and building societies. Consumer credit is borrowing by individuals to finance current expenditure on goods and services and it comprises borrowing through credit cards, overdraft facilities and other loans and advances, for example those financing the purchase of cars or other large ticket items. (Click here to download a PowerPoint copy of the chart.)

The chart allows us to view the confidence-borrowing relationship for the past 25 years or so. It suggests a fairly close association between consumer confidence and consumer credit growth. Whether changes in confidence occur ahead of changes in borrowing is debatable. However, the easing of confidence following the outcome of the EU referendum vote in June 2016 does appear to have led subsequently to an easing in the annual growth of consumer credit. From its peak of 10.9 per cent in the autumn of 2016, the annual growth rate of consumer credit dropped to 5.6 per cent in May 2019.

The easing of credit growth helps put something of a brake on consumer spending. It is, however, unlikely to affect all categories of spending equally. Indeed, the ONS figures for May on retail sales shows a mixed picture for the retail sector. Across the sector as a whole, the 3 month-on-3 month growth rate for the volume of purchases stood at 1.6 per cent, having fallen as low as 0.1 percent in December of last year. However, the 3 month-on-3 month growth rate for spending volumes in department stores, which might be especially vulnerable to a slowdown in credit, fell for the ninth consecutive month.

Going forward, the falls in confidence might be expected to lead to further efforts by the household sector, as well as by businesses, to ensure their financial resilience. The vulnerability of households, despite the slowdown in credit growth, so soon after the financial crisis poses a risk for a hard landing for the sector. After falls in national output in March and April, the next monthly GDP figures to be released on 10 July will be eagerly anticipated.

Articles

Questions

  1. Which of the following statements is likely to be more accurate: (a) Confidence drives economic activity or (b) Economic activity drives confidence?
  2. Explain the difference between confidence as a source of economic volatility as compared to an amplifier of volatility?
  3. Discuss the links between confidence, economic uncertainty and financial resilience.
  4. Discuss the ways in which people and businesses could improve their financial resilience to adverse shocks.
  5. What are the potential dangers to the economy of various sectors being financially distressed or exposed?

Latest resesarch from the independent American think tank The Conference Board paints a worrying picture about the growth of UK labour productivity. While global growth in labour productivity has weakened following the financial crisis, its weakness in the UK is singled out in the Board’s 2019 Productivity Brief. It finds that amongst large mature economies the decline in labour productivity growth rates has been greatest in the UK. This has important implications for the country’s longer-term well-being and, specifically, it peoples’ living standards.

The UK saw the growth in real GDP (national output) fall from 1.8 per cent in 2017 to 1.4 per cent in 2018. The Conference Board predicts that this will fall further to 0.8 per cent in 2019. In the context of living standards, the growth in real GDP per capita is particularly important. An increase in the population will, other things being equal, lower living standards because more people will be sharing a given amount of real national income. The growth in real GDP per capita fell from 1.1 per cent in 2017 to 0.7 per cent in 2018 and is predicted to fall to just 0.1 per cent in 2019.

Chart 1 shows the annual rates of growth in real GDP and real GDP per capita from the 1950s. The average growth rates are 2.4 and 1.9 per cent respectively. The other series shown is the annual growth in real GDP per person employed. This is a measure of the growth in labour productivity. Its average annual growth rate is also 1.9 per cent. This illustrates the intrinsic long-run relationship between labour productivity growth and the growth rate of GDP per capita and hence in general living stanadards. (Click here to download a PowerPoint copy of the chart.)

In the short term, rates of growth in output per worker (labour productivity) and GDP per capita (general living standards) can be less similar. For example, when unemployment rates rise labour productivity rates may be little affected despite GDP per capita falling. Nonetheless, the important point here is the close long-run relationship between the growth in labour productivity and GDP per capita. This then raises an important question: what factors contribute to the growth in output and labour productivity?

An approach known as growth accounting helps to identify four key contributors to the growth of total output. The first is the quantity of labour, commonly measured in labour hours. The second is the quality of labour, also known as labour composition. Third is capital services which are physical inputs into production and include machinery, structures and IT capital. Capital services are affected by quantity and quality, but, unlike labour, it is practically more difficult to separate out these dimensions. Fourth, is Total Factor Productivity (TFP).

TFP it is essentially the residual contribution to output growth that cannot be explained by changes in the quantity and quality of the individual inputs. Hence, in principle, it is capturing changes in how effectively the labour and capital inputs are being employed and combined in production. The Conference Board’s Productivity Brief describes the growth in TFP as providing ‘a more accurate picture of the overall efficiency by which capital, labour and skills are combined in the production process’.

Chart 2 shows Conference Board estimates of the percentage point contribution of these four sources of growth since 1990. Over this period, output growth averaged 2 per cent per year. The contribution of capital services and, hence, what is known as capital accumulation is particularly significant at 1.5 percentage points per year. This has been significantly larger than the contribution of labour hours which averaged only 0.3 percentage points per year since 1990. This evidences the importance played by capital deepening for output growth in the UK. (Click here to download a PowerPoint copy of the chart.)

Capital deepening captures the growth in capital services relative to the growth in the labour input. It takes on even greater significance when we think about the growth in labour productivity since, after all, this is the growth in output relative to the quantity of labour. It is significant though that since 2015 the growth of capital services has contributed only 1 percentage point to output growth while the growth of labour hours has contributed an average of 0.7 percentage points. This points to a slowdown in capital deepening and hence in the growth of labour productivity.

Chart 2 also illustrates the importance of TFP growth to overall output growth. It is also important (along with capital deepening and the growth in labour quality) for the growth in labour productivity. Interestingly, we observe significant fluctuations in the growth of TFP. This is thought to reflect fluctuations in the utilisation of inputs. For example, if the utilisation of inputs falls (rises) when output falls (increases) this will be mirrored by a disproportionately large fall (increase) in TFP. In the longer-term, however, changes in TFP capture aspects of technological progress and advancement that enable more effective production methods and techniques to be deployed. In other words, the growth of TFP captures the ability of production to benefit from the advancement in ideas, products, processes and know-how.

A decline in the growth in TFP growth following the financial crisis is found quite widely in mature economies. The annual rate of growth of TFP across mature economies fell from 0.5 per cent year in 2000-2007 to 0.2 per cent in 2010-2017. In the UK this fall was from 0.5 per cent to -0.1 per cent. Hence, the decline in TFP growth of 0.6 percentage points between 2010 and 2017 was double the 0.3 percentage point fall across all mature economies. In 2018 the Conference Board estimate that TFP in the UK fell by 0.1 percent further exacerbating the downward pressure on labour productivity.

As our final chart shows, it is the magnitude to which labour productivity has eased following the financial crisis that sets the UK apart. While across all mature economies the growth of output per labour hour (another measure of labour productivity growth) fell from an average of 2.3 per cent per year in 2000-2007 to 1.2 per cent in 2010-2017, in the UK the fall was from 2.2 per cent to 0.5 per cent per year. (Click here to download a PowerPoint copy of the chart.)

While the productivity problem facing the UK is not new, the latest figures comes as a very timely reminder of the extent of the problem. To some extent the uncertainty around Brexit and the negative impact on capital accumulation has only helped to exacerbate the problem. But, this may mask a more systemic problem facing the UK. Getting to the root of this problem matters. It matters most significantly for our long-term wellbeing and prosperity. The productivity gap with our major industrial competitors is a gap that policymakers need not only to be mindful of but one that needs closing.

Articles

Questions

  1. What do you understand by the term labour productivity. How could we measure it?
  2. Why is it important to look at the growth of output per capita when assessing the benefits of long-term growth?
  3. Why is labour productivity important for the long-term well-being of a country?
  4. What do you understand by the method of growth accounting?
  5. What is the distinction between capital accumulation and capital deepening?
  6. What might explain why the growth of labour productivity has been lower in the years following the post-financial crisis?
  7. What do you understand by Total Factor Productivity (TFP)?
  8. What does the long-term growth of TFP attempt to capture?
  9. If you were an economic advisor to the government, what types of policy initiatives might you recommend for a government concerned about low rates of growth of labour productivity?