Category: Economics: Ch 17

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World Uncertainty Index

We continue to live through incredibly turbulent times. In the past decade or so we have experienced a global financial crisis, a global health emergency, seen the UK’s departure from the European Union, and witnessed increasing levels of geopolitical tension and conflict. Add to this the effects from the climate emergency and it easy to see why the issue of economic uncertainty is so important when thinking about a country’s economic prospects.

In this blog we consider how we can capture this uncertainty through a World Uncertainty Index and the ways by which economic uncertainty impacts on the macroeconomic environment.

World Uncertainty Index

Hites Ahir, Nicholas Bloom and Davide Furceri have constructed a measure of uncertainty known as the World Uncertainty Index (WUI). This tracks uncertainty around the world using the process of ‘text mining’ the country reports produced by the Economist Intelligence Unit. The words searched for are ‘uncertain’, ‘uncertainty’ and ‘uncertainties’ and a tally is recorded based on the number of times they occur per 1000 words of text. To produce the index this figure is then multiplied up by 100 000. A higher number therefore indicates a greater level of uncertainty. For more information on the construction of the index see the 2022 article by Ahir, Bloom and Furceri linked below.

Figure 1 (click here for a PowerPoint) shows the WUI both globally and in the UK quarterly since 1991. The global index covers 143 countries and is presented as both a simple average and a GDP weighted average. The UK WUI is also shown. This is a three-quarter weighted average, the authors’ preferred measure for individual countries, where increasing weights of 0.1, 0.3 and 0.6 are used for the three most recent quarters.

From Figure 1 we can see how the level of uncertainty has been particularly volatile over the past decade or more. Events such as the sovereign debt crisis in parts of Europe in the early 2010s, the Brexit referendum in 2016, the COVID-pandemic in 2020–21 and the invasion of Ukraine in 2022 all played their part in affecting uncertainty domestically and internationally.

Uncertainty, risk-aversion and aggregate demand

Now the question turns to how uncertainty affects economies. One way of addressing this is to think about ways in which uncertainty affects the choices that people and businesses make. In doing so, we could think about the impact of uncertainty on components of aggregate demand, such as household consumption and investment, or capital expenditures by firms.

As Figure 2 shows (click here for a PowerPoint), investment is particularly volatile, and much more so than household spending. Some of this can be attributed to the ‘lumpiness’ of investment decisions since these expenditures tend to be characterised by indivisibility and irreversibility. This means that they are often relatively costly to finance and are ‘all or nothing’ decisions. In the context of uncertainty, it can make sense therefore for firms to wait for news that makes the future clearer. In this sense, we can think of uncertainty rather like a fog that firms are peering through. The thicker the fog, the more uncertain the future and the more cautious firms are likely to be.

The greater caution that many firms are likely to adopt in more uncertain times is consistent with the property of risk-aversion that we often attribute to a range of economic agents. When applied to household spending decisions, risk-aversion is often used to explain why households are willing to hold a buffer stock of savings to self-insure against unforeseen events and their future financial outcomes being worse than expected. Hence, in more uncertain times households are likely to want to increase this buffer further.

The theory of buffer-stock saving was popularised by Christopher Carroll in 1992 (see link below). It implies that in the presence of uncertainty, people are prepared to consume less today in order to increase levels of saving, pay off existing debts, or borrow less relative to that in the absence of uncertainty. The extent of the buffer of financial wealth that people want to hold will depend on their own appetite for risk, the level of uncertainty, and the moderating effect from their own impatience and, hence, present bias for consuming today.

Risk aversion is consistent with the property of diminishing marginal utility of income or consumption. In other words, as people’s total spending volumes increase, their levels of utility or satisfaction increase but at an increasingly slower rate. It is this which explains why individuals are willing to engage with the financial system to reallocate their expected life-time earnings and have a smoother consumption profile than would otherwise be the case from their fluctuating incomes.

Yet diminishing marginal utility not only explains consumption smoothing, but also why people are willing to engage with the financial system to have financial buffers as self-insurance. It explains why people save more or borrow less today than suggested by our base-line consumption smoothing model. It is the result of people’s greater dislike (and loss of utility) from their financial affairs being worse than expected than their like (and additional utility) from them being better than expected. This tendency is only likely to increase the more uncertain times are. The result is that uncertainty tends to lower household consumption with perhaps ‘big-ticket items’, such as cars, furniture, and expensive electronic goods, being particularly sensitive to uncertainty.

Uncertainty and confidence

Uncertainty does not just affect risk; it also affects confidence. Risk and confidence are often considered together, not least because their effects in generating and transmitting shocks can be difficult to disentangle.

We can think of confidence as capturing our mood or sentiment, particularly with respect to future economic developments. Figure 3 plots the Uncertainty Index for the UK alongside the OECD’s composite consumer and business confidence indicators. Values above 100 for the confidence indicators indicate greater confidence about the future economic situation and near-term business environment, while values below 100 indicate pessimism towards the future economic and business environments.

Figure 3 suggests that the relationship between confidence and uncertainty is rather more complex than perhaps is generally understood (click here for a PowerPoint). Haddow, Hare, Hooley and Shakir (see link below) argue that the evidence tends to point to changes in uncertainty affecting confidence, but with less evidence that changes in confidence affect uncertainty.

To illustrate this, consider the global financial crisis of the late 2000s. The argument can be made that the heightened uncertainty about future prospects for households and businesses helped to erode their confidence in the future. The result was that people and businesses revised down their expectations of the future (pessimism). However, although people were more pessimistic about the future, this was more likely to have been the result of uncertainty rather than the cause of further uncertainty.

Conclusion

For economists and policymakers alike, indicators of uncertainty, such as the Ahir, Bloom and Furceri World Uncertainty Index, are invaluable tools in understanding and forecasting behaviour and the likely economic outcomes that follow. Some uncertainty is inevitable, but the persistence of greater uncertainty since the global financial crisis of the late 2000s compares quite starkly with the relatively lower and more stable levels of uncertainty seen from the mid-1990s up to the crisis. Hence the recent frequency and size of changes in uncertainty show how important it to understand how uncertainty effects transmit through economies.

Academic papers

Articles

Data

Questions

  1. (a) Explain what is meant by the concept of diminishing marginal utility of consumption.
    (b) Explain how this concept helps us to understand both consumption smoothing and the motivation to engage in buffer-stock saving.
  2. Explain the distinction between confidence and uncertainty when analysing macroeconomic shocks.
  3. Discuss which types of expenditures you think are likely to be most susceptible to uncertainty shocks.
  4. Discuss how economic uncertainty might affect productivity and the growth of potential output.
  5. How might the interconnectedness of economies affect the transmission of uncertainty effects through economies?
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Getting real with retail sales

In the third of our series on the distinction between nominal and real values we show its importance when analysing retail sales data. In the UK, such data are available from the Office for National Statistics. This blog revisits an earlier one, Nominal and real retail sales figures: interpreting the data, written in October 2023. We find that inflation-adjusted retail sales data reveal some stark patterns in the sector. They help contextualise some of the challenges faced by high streets up and down the UK.

The Retail Sales Index

Retail sales relate to spending on items such as food, clothing, footwear and household goods. They involve sales by retailers directly to final consumers, whether in store or online. Spending on services such as holidays, air fares and train tickets, insurance, banking, hotels and restaurants are not included, as are sales of motor vehicles. The Retail Sales Index for Great Britain is based on a monthly survey of around 5000 retailers across England, Scotland and Wales and is thought to capture around three-quarters of turnover in the retail industry.

Estimates of retail sales are published in index form. There are two indices published by the ONS: a value and volume measure. The value index reflects the total turnover of business, while the volume index adjusts the value index for price changes. Hence, the value estimates are nominal, while the volume estimates are real. The key point here is that the nominal estimates reflect both price and volume changes, whereas the real estimates adjust for price movements to capture only volume changes.

The headline ONS figures for May 2024 showed a rise by 2.9 per cent in the volume of retail sales, following a 1.8 per cent fall in April. In value terms, May saw a 3.3 per cent rise in retail sales following a 2.3 fall in March. Monthly changes can be quite volatile, even after seasonal adjustment, and sensitive to peculiar factors. For example, the poor weather in April 2024 helped to depress retail spending. It is, therefore, sensible to take a longer-term view when looking for clearer patterns in spending behaviour.

Growth of retail sales

Chart 1 plots the monthly value and volume of retail sales in Great Britain since 1996. (Click here to download a PowerPoint of the chart). In value terms, monthly spending in the retail sector has increased by 169 per cent since January 1996, whereas in volume terms, spending has increased by 77 per cent. Another way of thinking about this is in terms of the average annual rate of increase. This shows that the value of spending has risen at an annual rate of 3.5 per cent while the volume of spending has risen at an annual rate of 2.0 per cent. This difference is to be expected in the presence of rising prices, since nominal growth, as we have just noted, reflects both price and volume changes.

Chart 1 helps to identify two periods where the volume of retail spending ceased to grow. The first of these is following the global financial crisis of the late 2000s. The period from 2008 to 2013 saw the volume of retail sales stagnate and flatline, with a recovery in volumes only really starting to take hold in 2014. Yet in nominal terms retail sales grew by around 14 per cent.

The second of the two periods is from 2021. Chart 2 helps to demonstrates the extent of the struggles of the retail sector in this period. It shows a significant divergence between the volume and value of retail sales. Indeed, between April 2021 and October 2023, while the value of retail sales increased by 8.0 per cent the volume of retail sales fell by 11.0 per cent.

The recent value-volume divergence reflects the inflation shock that began to emerge in 2021. This saw consumer prices, as measured by the Consumer Prices Index (CPI), rise across 2022 and 2023 by 9.1 per cent and 7.3 per cent respectively, with the annual rate of CPI inflation hitting 11.1 per cent in October 2022. Hence, while inflation was a drag on the volume of spending it nonetheless meant that the value of spending continued to rise. Once more this demonstrates why understanding the distinction between nominal and real is important. (Click here to download a PowerPoint of the chart).

To illustrate the longer-term trend in the volume of retail spending alongside its volatility, Chart 3 plots yearly retail sales volumes and also their percentage change on the previous year.

The chart nicely captures the prolonged halt to retail sales growth following the global financial crisis, the fluctuations caused by COVID and then the sharp falls in the volume of retail spending in 2022 and 2023 as the effects of the inflationary shock on peoples’ finances bit sharply. This cost-of-living crisis significantly affected many people’s disposable income. (Click here to download a PowerPoint of the chart).

Categories of retail sales

We conclude by considering categories of retail spending. Chart 4 shows volumes of retail sales by four broad categories since 1996. (Click here to download a PowerPoint of the chart). These are food stores, predominantly non-food stores, non-store retail and automotive fuel (i.e. sales of petrol and diesel “at the pumps”).

Whilst all categories have seen an increase in their spending volumes over the period as a whole, there are stark differences in this rate of growth. Perhaps not surprisingly, the most rapid growth is in non-store retail. This includes online retailing, as well as market stalls and catalogues.

The volume of retail spending in the non-store sector has grown at an average annual rate over this period of 6.3 per cent, compared with 2.6 per cent for non-food stores, 1.2 per cent for predominantly food stores and 1.0 per cent for automotive fuels. The growth of non-store retail has been even more rapid since 2010, when the average annual rate of growth in the volume of purchases has been 10.2 per cent, compared to 1.8 per cent for non-food stores, 1.0 per cent for automotive fuels and zero growth for food stores.

If we focus on the most recent patterns in the categories of retail sales, we see that the monthly volume of spending in all categories except non-store retail is now lower than the average in 2019. Specifically, when compared to 2019 levels, the volume of spending in non-food stores in May 2024 was 2.6 per cent lower, while that in food stores was 4.4 per cent lower, and the volume of spending on automotive fuels was 10.8 per cent lower. In contrast, spending in non-store retail was 21.2 per cent higher. Yet this is not to imply that this sector has been immune to the pressures faced by their high-street counterparts. Although it is difficult to disentangle fully the effects of the pandemic and lockdowns on non-store retail sales data, the downward trajectory in the volume of retail sales in the sector that occurred as the economy ‘reopened’ in 2021 and 2022 continued into 2023 when purchases fell by 3.5 per cent.

Final thoughts

The retail sector is an incredibly important part of the economy. A recent research briefing from the House of Commons Library reports that there were 2.7 million jobs in the UK retail sector in 2022, equivalent to 8.6 per cent of the country’s jobs with 314 040 retail businesses as of January 2023. Yet the importance of the retail sector cannot be captured by these statistics alone. Some would argue that the very fabric and wellbeing of our towns and cities is affected by the wellbeing of the sector and, importantly, by structural changes that affect how people interact with retail.

Articles

Research Briefing

Statistical bulletin

Data

Questions

  1. Which of the following is/are not counted in the UK retail sales data: (i) purchase of furniture from a department store; (ii) weekly grocery shop online; (iii) a stay at a hotel on holiday; (iv) a meal at your favourite café or restaurant?
  2. Why does an increase in the value of retail sales not necessarily mean that their volume has increased?
  3. In the presence of deflation, which will be higher: nominal or real growth rates?
  4. Discuss the factors that could explain the patterns in the volume of spending observed in the different categories of retail sales in Chart 4.
  5. Discuss what types of retail products might be more or less sensitive to changes in the macroeconomic environment.
  6. Conduct a survey of recent media reports to prepare a briefing discussing examples of retailers who have struggled or thrived in the recent economic environment.
  7. What do you understand by the concepts of ‘consumer confidence’ and ‘economic uncertainty’? How might these affect the volume of retail spending?
  8. Discuss the proposition that the retail sales data cast doubt on whether people are ‘forward-looking consumption smoothers’.
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Getting real with growth

In the second of a series of blogs looking at applications of the distinction between nominal and real indicators, we revisit the blog Getting Real with Growth last updated in October 2021.

In this blog, we discuss how, in making a meaningful comparison over time of a country’s national income and, therefore, the aggregate purchasing power of its people, we need to take inflation into account. Likewise, if we want to analyse changes in the volume of production, we need to eliminate the effects of price changes on GDP. This is important when analysing the business cycle and identifying periods of boom or bust. Hence, in this updated blog we take another look at what real GDP data reveal about both longer-term economic growth and the extent of economic volatility – or what we refer to as the twin characteristics of economic growth.

Real and nominal GDP

The nominal (or current-price) estimate for UK gross domestic product in 2023 was £2.687 trillion. The estimate of national output or national income is based primarily on the production of final goods and services and, hence, purchased by the final user. It therefore largely excludes intermediate goods and services: i.e. goods and services that are transformed or used up in the process of making something else, although data on imports and exports do include intermediate goods and services. The 2023 figure represents a nominal increase in national income of 7.2 per cent on the £2.51 trillion recorded in 2022. These values make no adjustment for inflation and therefore reflect the prices of output that were prevailing at the time.

Chart 1 shows current-price estimates of GDP from 1955, when the value of GDP was estimated at £19.2 billion. The £2.687 trillion figure recorded for 2023 is an increase of over 140 times that in 1955, a figure that rises to 160 times if we compare the 1950 value with the latest IMF estimate for 2027. However, if we want to make a more meaningful comparison of the country’s national income we need to adjust for inflation. (Click here to download a PowerPoint of the chart.)

Long-term growth in real GDP

If we measure GDP at constant prices, we eliminate the effect of inflation. To construct a constant-price series for GDP, a process known as chain-linking is used. This involves taking consecutive pairs of years, e.g. 2022 and 2023, and estimating what GDP would be in the most recent year (in this case, 2023) if the previous year’s prices (i.e. 2022) had continued to prevail. By calculating the percentage change from the previous year’s GDP value we have an estimate of the volume change. If this is repeated for other pairs of years, we have a series of percentage changes that capture the volume changes from year-to-year. Finally, a reference year is chosen and the percentage volume changes are applied backwards and forwards from the nominal GDP value for the reference year.

In effect, a real GDP series creates a quantity measure in monetary terms. Chart 1 shows GDP at constant 2019 prices (real GDP) alongside GDP at current prices (nominal GDP). Consider first the real GDP numbers for 1955 and 2023. GDP in 1950 at 2019 prices was £491.2 billion. This is higher than the current-price value because prices in 2019 (the reference year) were higher than those in 1955. Meanwhile, GDP in 2023 when measured at 2019 prices was £2.273 trillion. This constant-price value is smaller than the corresponding current-price value because prices in 2019 where lower than those in 2023.

Between 1955 and 2023 real GDP increased 4.6 times. If we extend the period to 2027, again using the latest IMF estimates, the increase is 4.9 times. Because we have removed the effect of inflation, the real growth figure is much lower than the nominal growth figure.

Crucially, what we are left with is an indicator of the long-term growth in the volume of the economy’s output and hence an increase in national income that is backed up by an increase in production. Whereas nominal growth rates are affected by changes in both volumes and prices, real growth rates reflect only changes in volumes.

The upward trajectory observed in constant-price GDP is therefore evidence of positive longer-term growth. This is one of the twin characteristics of growth.

Short-term fluctuations in the growth of real GDP

The second characteristic is fluctuations in the rate of growth from period to period. We can see this second characteristic more clearly by plotting the percentage change in real GDP from year to year.

Chart 2 shows the annual rate of growth in real GDP each year from 1955 to 2025. From it, we see the inherent instability that is a key characteristic of the macroeconomic environment. This instability is, of course, mirrored in the output path of real GDP in Chart 1, but the annual rates of growth show the instability more clearly. We can readily see the impact on national output of the global financial crisis of 2007–8 and the global COVID pandemic.

In 2009, constant-price GDP in the UK fell by 4.6 per cent, whereas current-price GDP fell by 2.8 per cent. Then, in 2020, constant-price GDP and, hence, the volume of national output fell by 10.4 per cent, as compared to a 5.8 per cent fall in current-price GDP. These global, ‘once-in-a-generation’ shocks are stark examples of the instability that characterises economies and which generate the ‘ups and downs’ in an economy’s output path, known more simply as ‘the business cycle’. (Click here to download a PowerPoint copy of the chart.)

Determinants of long-and short-term growth

The twin characteristics of growth can be seen simultaneously by combining the output path (shown by the levels of real GDP) with the annual rates of growth. This is shown in Chart 3. The longer-term growth seen in the economy’s output path is generally argued to be driven by the quantity and quality of the economy’s resources, and their effectiveness when combined in production (i.e. their productivity). In other words, it is the supply side of the economy that determines the trajectory of the output path over the longer term. (Click here to download a PowerPoint copy of the chart.)

However, the fluctuations we observe in short-term growth rates tend to reflect shocks, also known as impulses, that originate either from the ability and or willingness of purchasers to consume (demand-side shocks) or producers to supply (supply-side shocks). These impulses are then amplified (or ‘propagated’) via the multiplier, expectations and other factors, and their effects, therefore, transmitted through the economy. Unusually in the case of the pandemic, the lockdown measures employed by governments around the world resulted in simultaneous negative aggregate demand and aggregate supply shocks.

Persistence effects

Explanations of the business cycle and of long-term growth are not mutually exclusive. The shocks and the propagation mechanisms that help to create and shape the business cycle can themselves have enduring or persistent effects on output. The global financial crisis, fuelled by unsustainable lending and the overstretch of private-sector balance sheets, which then spilt over to the public sector as governments attempted to stabilise the financial system and support aggregate demand, is argued by some to have created the conditions for low-growth persistence seen in many countries in the 2010s. This type of persistence is known as hysteresis as it originates from a negative demand shock.

Economists and policymakers were similarly concerned that the pandemic would also generate persistence in the form of scarring effects that might again affect the economy’s output path. Such concerns help to explain why many governments introduced furlough schemes to protect jobs and employment income, as well as provide grants or loans to business.

Per capita output

To finish, it is important to recognise that, when thinking about living standards, it is the growth in real GDP per capita that we need to consider. A rise in real GDP will only lead to a rise in overall living standards if it is faster than the rise in population.

Our final chart therefore replicates Chart 3 but for real GDP per capita. Between 1955 and 2023 real GDP per capita grew by a factor of 3.45, which increases to 3.6 when we consider the period up to 2027. The average rate of growth of real GDP per capita up to 2023 was 1.87 per cent (lower than the 2.34 per cent increase in real GDP).

But the rate of increase in real GDP per capita was much higher before 2007 than it has been since. If we look at the period up to 2007 and, hence, before the global financial crisis, the figure is 2.32 per cent (2.7 per cent for real GDP), whereas from 2008 to 2023 the average rate of growth of real GDP per capita was a mere 0.42 per cent (1.1 per cent for real GDP). (Click here to download a PowerPoint copy of the chart.)

The final chart therefore reiterates the messages from recent blogs, such as Getting Real with Pay and The Productivity Puzzle, that long-term economic growth and the growth of real wages have slowed dramatically since the financial crisis. This has had important implications for the wellbeing of all sectors of the economy. The stagnation of living standards is therefore one of the most important economic issues of our time. It is one that the incoming Labour government will be keen to address.

Data and Reports

Articles

Questions

  1. What do you understand by the term ‘macroeconomic environment’? What data could be used to describe the macroeconomic environment?
  2. When a country experiences positive rates of inflation, which is higher: nominal economic growth or real economic growth?
  3. Does an increase in nominal GDP mean a country’s production has increased? Explain your answer.
  4. Does a decrease in nominal GDP mean a country’s production has decreased? Explain your answer.
  5. Why does a change in the growth of real GDP allow us to focus on what has happened to the volume of production?
  6. What does the concept of the ‘business cycle’ have to do with real rates of economic growth?
  7. When would falls in real GDP be classified as a recession?
  8. Distinguish between the concepts of ‘short-term growth’ and ‘longer-term growth’.
  9. What do you understand by the term ‘persistence’ in macroeconomics? Given examples of persistence effects and the means by which they can be generated?
  10. Discuss the proposition that the pandemic could have a positive effect on longer-term growth rates because of the ways that people and business have had to adapt.
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Getting real with pay

In the first of a series of updated blogs focusing on the importance of the distinction between nominal and real values we look at the issue of earnings. Here we update the blog Getting Real with Pay written back in February 2019. Then, we noted how the macroeconomic environment since the financial crisis of the late 2000s had continued to affect people’s pay. Specifically, we observed that there had been no growth in real or inflation-adjusted pay. In other words, people were no better off in 2019 than in 2008.

In this updated blog, we consider to what extent the picture has changed five years down the line. While we do not consider the distributional impact on pay, the aggregate picture nonetheless continues to paint a very stark picture, with consequences for living standards and financial wellbeing.

While the distinction between nominal and real values is perhaps best known in relation to GDP and economic growth, the distinction is also applied frequently to analyse the movement of one price relative to prices in general. One example is that of movements in pay (earnings) relative to consumer prices.

Pay reflects the price of labour. The value of our actual pay is our nominal pay. If our pay rises more quickly than consumer prices, then our real pay increases. This means that our purchasing power rises and so the volume of goods and services we can afford increases. On the other hand, if our actual pay rises less quickly than consumer prices then our real pay falls. When real pay falls, purchasing power falls and the volume of goods and services we can afford falls.

Figures from the Office for National Statistics show that in January 2000 regular weekly pay (excluding bonuses and before taxes and other deductions from pay) was £293. By April 2024 this had risen to £640. This is an increase of 118 per cent. Over the same period, the consumer prices index known as the CPIH, which, unlike the better-known CPI, includes owner-occupied housing costs and council tax, rose by 82 per cent. Therefore, the figures are consistent with a rise both in nominal and real pay between January 2000 to April 2024. However, this masks a rather different picture that has emerged since the global financial crisis of the late 2000s.

Chart 1 shows the annual percentage changes in actual (nominal) regular weekly pay and the CPIH since January 2001. Each value is simply the percentage change from 12 months earlier. The period up to June 2008 saw the annual growth of weekly pay outstrip the growth of consumer prices – the blue line in the chart is above the red dashed line. Therefore, the real value of pay rose. However, from June 2008 to August 2014 pay growth consistently fell short of the rate of consumer price inflation – the blue line is below the red dashed line. The result was that average real weekly pay fell. (Click here to download a PowerPoint copy of the chart.)

Chart 2 show the average levels of nominal and real weekly pay. The real series is adjusted for inflation. It is calculated by deflating the nominal pay values by the CPIH. Since the CPIH is a price index whose value averages 100 across 2015, the real pay values are at constant 2015 consumer prices. From the chart, we can see that the real value of weekly pay peaked in April 2008 at £473 at 2015 prices. The subsequent period saw rates of pay increases that were lower than rates of consumer price inflation. This meant that by March 2014 the real value of weekly pay had fallen by 6.3 per cent to £443 at 2015 prices. (Click here to download a PowerPoint copy of the chart.)

Although real (inflation-adjusted) pay recovered a little after 2014, 2017 again saw consumer price inflation rates greater than those of pay inflation (see Chart 1). This meant that at the start of 2018 real earnings were 3.2 per cent lower than their 2008-peak (see Chart 2). Real earnings then began to recover, buoyed by the economic rebound following the relaxation of COVID lockdown measures and increasing staffing pressures. Real earnings finally passed their 2008-peak in August 2020. By April 2021 regular weekly pay reached £491 at 2015 prices which was 3.8 per cent above the pre-global financial crisis peak.

However, the boost to real wages was to be short-lived as inflationary pressures rose markedly. While some of this was attributable to the same pressures that were driving up wages, inflationary pressures were fuelled further by the commodity price shock arising from Russia’s invasion of Ukraine and, in particular, its impact on energy prices. This saw the CPIH inflation rate rise to 9.6 per cent in October 2022 (while the CPI inflation rate peaked in the same month at 11.1 per cent). The result was that real weekly earnings fell by 2.7 per cent between January and October 2022 to stand at £471 at 2015 consumer prices. Consequently, average pay was once again below its pre-global financial crisis level.

Although inflationary pressures have recently weakened and real earnings have begun to recover, real regular weekly earnings in April 20024 (£486 at 2015 prices) were a mere 2.7 per cent higher than back in the first half of 2008. This compares to a nominal increase of around 58 per cent over the same period thereby demonstrating the importance of the distinction between nominal and real values in understanding what developments in pay mean for the purchasing power of households.

Chart 3 reinforces the importance of the nominal-real distinction. It shows nicely the sustained period of real pay deflation (negative rates of pay inflation) that followed the financial crisis, and the significant rates of real pay deflation associated with the recent inflation shock.

The result is that since June 2008 the average annual rate of growth of real regular weekly pay has been 0.1 per cent, despite nominal pay increasing at an annual rate of 2.9 per cent. In contrast, the period from January 2001 to May 2008 saw real regular weekly pay grow at an annual rate of 2.1 per cent with nominal pay growing at an annual rate of 4.0 per cent. (Click here to download a PowerPoint copy of the chart.)

If we think about the growth of nominal earnings, we can identify two important determinants.

The first is the expected rate of inflation. Workers will understandably want wage growth at least to match the growth in prices so as to maintain their purchasing power.

The second factor is the growth in labour productivity. Firms will be more willing to grant pay increases if workers are more productive, since productivity helps to offset pay increases and maintain firms’ profit margins. Consequently, since over time the actual rate of inflation will tend to mirror the expected rate, the growth of real pay is closely related to the growth of labour productivity. This is significant because, as John discusses in his blog The Productivity Puzzle (14 April 2024), labour productivity growth in the UK, as measured by national output per worker hour, has stalled since the global financial crisis.

Understanding the stagnation of real earnings therefore nicely highlights the interconnectedness of economic variables. In this case, it highlights the connections between productivity, levels of investment and people’s purchasing power. It is not surprising, therefore, that the stagnation of both real earnings and productivity growth since the global financial crisis have become two of the most keenly debated macroeconomic issues of recent times. Indeed, it is likely that their behaviour will continue to shape macroeconomic debates and broader conversations around government policy for some time.

Articles

Questions

  1. Using the examples of both GDP and earnings, explain how the distinction between nominal and real relates to the distinction between values and volumes.
  2. In what circumstances would an increase in actual pay translate into a reduction in real pay?
  3. In what circumstances would a decrease in actual pay translate into an increase in real pay?
  4. What factors might explain the reduction in real rates of pay seen in the UK following the financial crisis of 2007–8?
  5. Of what importance might the growth in real rates of pay be for consumption and aggregate demand?
  6. Why is the growth of real pay an indicator of financial well-being? What other indicators might be included in measuring financial well-being?
  7. Assume that you have been asked to undertake a distributional analysis of real earnings since the financial crisis. What might be the focus of your analysis? What information would you therefore need to collect?