Tag: consumer confidence

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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.

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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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Risk aversion in late-cycle slowing economies: the US experience

In recent months there has been growing uncertainty across the global economy as to whether the US economy was going to experience a ‘hard’ or ‘soft landing’ in the current business cycle – the repeated sequences of expansion and contraction in economic activity over time. Announcements of macroeconomic indicators have been keenly anticipated for signals about how quickly the US economy is slowing.

Such heightened uncertainty is a common feature of late-cycle slowing economies, but uncertainty now has been exacerbated because it has been a while since developed economies have experienced a business cycle like the current one. The 21st century has been characterised by low inflation, low interest rates and recessions caused by various types of crises – a stock market crisis (2001), a banking crisis (2008) and a global pandemic (2020). In contrast, the current cycle is a throwback to the 20th century. The high inflation and the ensuing increases in interest rates have produced a business cycle which echoes the 1970s. Therefore, few investors have experience of such economic conditions.

The focus for investors during this stage of the cycle is when the slowing economy will reach the minimum. They will also be concerned with the depth of the slowdown: will there still be some growth in income, albeit low; or will the trough be severe enough to produce a recession, and, if so, how deep? Given uncertainty around the length and magnitude of business cycles, this leads to greater risk aversion among investors. This affects reactions to announcements of leading and lagging macroeconomic indicators.

This blog examines what sort of economic conditions we should expect in a late-cycle economy. It analyses the impact this has had on investor behaviour and the ensuing dynamics observed in financial markets in the USA.

The Business Cycle


The business cycle refers to repeated sequences of expansion and contraction (or slowdown) in economic activity over time. Figure 1 illustrates a typical cycle. Typically, these sequences include four main stages. In each one there are different effects on consumer and business confidence:

  • Expansion: During this stage, the economy experiences growth in GDP, with incomes and consumption spending rising. Business and consumer confidence are high. Unemployment is falling.
  • Peak: This is the point at which the economy reaches its maximum output, but growth has ceased (or slowed). At this stage, inflationary pressures peak as the economy presses against potential output. This tends to result in tighter monetary policy (higher interest rates).
  • Slowdown: The higher interest rates raise the cost of borrowing and reduce consumption and investment spending. Consumption and incomes both slow or fall. (Figure 1 illustrates the severe case of falling GDP (negative growth) in this stage.) Unemployment starts rising.
  • Trough: This is the lowest point of the cycle, where economic activity bottoms out and the economy begins to recover. This can be associated with slow but still rising national income (a soft landing) or national income that has fallen (a hard landing, as shown in Figure 1).

While business cycles are common enough to enable such characterisation of their temporal pattern, their length and magnitude are variable and this produces great uncertainty, particularly when cycles approach peaks and troughs.

As an economy’s cycle approaches a trough, such as US economy’s over the past few months, uncertainty is exacerbated. The high interest rates used to tackle inflation will have increased borrowing costs for businesses and consumers. Access to credit may have become more restricted. Profit margins are reduced, especially for industrial sectors sensitive to the business cycle, reducing expected cash flows.

The combination of these factors can increase the risk of a recession, producing greater volatility in financial markets. This manifests itself in increased risk aversion among investors.

Utility theory suggests that, in general, investors will exhibit loss aversion. This means that they do not like bearing risk, fearing that the return from an investment may be less than expected. In such circumstances, investors need to be compensated for bearing risk. This is normally expressed in terms of expected financial return. To bear more risk, investors require higher levels of return as compensation.

As perceptions of risk change through the business cycle, so this will change the return investors will require from the financial instruments they hold. Perceived higher risk raises the return investors will require as compensation. Conversely, lower perceived risk decreases the return investors expect as compensation.

Investors’ expected rate of return is manifested in the discount rate that they use to value the anticipated cash flows from financial instruments in discounted cash flow (DCF) analysis. Equation 1 is the algebraic expression of the present-value discounted series of cash flows for financial instruments:

 
 
Where:
V = present value
C = anticipated cash flows in each of time periods 1, 2, 3, etc.
r = expected rate of return

For fixed-income debt securities, the cash flow is constant, while for equity securities (shares), expectations regarding cash flows can change.

Slowing economies and risk aversion

In a slowing economy, with great uncertainty about the scale and timing of the bottom of the cycle, investors become more risk averse about the prospects of firms. This this leads to higher risk premia for financial instruments sensitive to a slowdown in economic activity.

This translates into a higher expected return and higher discount rate used in the valuation of these instruments (r in equation 1). This produces decreases in perceived value, decreased demand and decreased prices for these financial instruments. This can be observed in the market dynamics for these instruments.

First, there may be a ‘flight to safety’. Investors attach a higher risk premium to risker financial instruments, such as equities, and seek a ‘safe-haven’ for their wealth. Therefore, we should observe a reorientation from more risky to less risky assets. Demand for equities falls, while demand for safer assets, such as government bonds and gold, rises.

There is some evidence for this behaviour as uncertainty about the US economic outlook has increased. Gold, long seen as a hedge against market decline, is at record highs. US Government bond prices have risen too.

To analyse whether this may be a flight to safety, I analysed the correlation between the daily US government bond price (5-year Treasury Bill) and share prices represented by the two more significant stock market indices in the USA: the S&P 500 and the Nasdaq Composite. I did this for two different time periods. Table 1 shows the results. Panel (a) shows the correlation coefficients for the period between 1 May 2024 and 31 July 2024; Panel (b) shows the correlation coefficients for the period between 1 August 2024 and 9 September 2024.

In the period between May and July 2024, the 5-year Treasury Bill and share price indices had significantly positive correlations. When share prices rose, the Treasury Bill’s price rose; when share prices fell, the bill’s price fell. During that period, expectations about falling interest rates dominated valuations and that effected the valuations of all financial instruments in the same way – lower expected interest rates reduce the opportunity cost of holding instruments and reduces the expected rates of return. Hence, the discount rate applied to cash flows is reduced, and present value rises. The opposite happens when macroeconomic indicators suggest that interest rates will stay high (ceteris paribus).

As the summer proceeded, worries about a ‘hard landing’ began to concern investors. A weak jobs report in early August particularly exercised markets, producing a ‘flight to safety’. Greater risk aversion among investors meant that they expect a higher return from equities. This reduced perceived value, reducing demand and price (ceteris paribus). To insulate themselves from higher risk, investors bought safer assets, like government bonds, thereby pushing up their prices. This behaviour was consistent with the significant negative correlation observed between US government debt prices and the S&P 500 and Nasdaq indices in Panel (b).

Another signal of increased risk aversion among investors is ‘sector rotation’ in their equity portfolios. Increased risk aversion among investors will lead them to divest from ‘cyclical’ companies. Such companies are in industrial sectors which are more sensitive to the changing economic conditions across the business cycle – consumer discretionary and communication services sectors, for example. To reduce their exposure to risk, investors will switch to ‘defensive’ sectors – those less sensitive to the business cycle. Examples include consumer staples and utility sectors.

Cyclical sectors will suffer a greater adverse impact on their cash flows and risk in a slowing economy. Consequently, investors expect higher return as compensation. This reduces the value of those shares. Demand for them falls, depressing their price. In contrast, defensive sectors will be valued more. They will see an increase in demand and price. This sector rotation seems to have happened in August (2024). Figure 2 shows the percentage change between 1 August and 9 September 2024 in the S&P 500 index and four sector indices, comprising companies from the communication services, consumer discretionary, consumer staples and utilities sectors.


Overall, the S&P 500 index was slightly higher, as shown by the first bar in the chart. However, while the cyclical sectors experienced decreases in their share prices, particularly communication services, the defensive companies experienced large price increases – nearly 3% for utilities and over 6% for consumer staples.

Conclusion

Economies experience repeated sequences of expansion and contraction in economic activity over time. At the moment, the US economy is approaching the end of its current slowing phase. Increased uncertainty is a common feature of late-cycle economies and this manifests itself in heightened risk aversion among investors. This produces certain dynamics which have been observable in US debt and equity markets. This includes a ‘flight to safety’, with investors divesting risky financial instruments in favour of safer ones, such as US government debt securities and gold. Also, investors have been reorientating their equity portfolios away from cyclicals and towards defensive securities.

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Questions

  1. What is risk aversion? Sketch an indifference curve for a risk-averse investor, treating expected return and risk as two-characteristics of a financial instrument.
  2. Show what happens to the slope of the indifference curve if the investor becomes more risk averse.
  3. Using demand and supply analysis, illustrate and explain the impact of a flight to safety on the market for (i) company shares and (ii) US government Treasury Bills.
  4. Use economic theory to explain why the consumer discretionary sector may be more sensitive than the consumer staples sector to varying incomes across the economic cycle.
  5. Research the point of the economic cycle that the US economy has reached as you read this blog. What is the relationship between bond and equity prices? Which sectors have performed best in the stock market?
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Worries about the Chinese economy

According to the IMF, Chinese GDP grew by 5.2% in 2023 and is predicted to grow by 4.6% this year. Such growth rates would be extremely welcome to most developed countries. UK growth in 2023 was a mere 0.5% and is forecast to be only 0.6% in 2024. Advanced economies as a whole only grew by 1.6% in 2023 and are forecast to grow by only 1.5% this year. Also, with the exception of India, the Philippines and Indonesia, which grew by 6.7%, 5.3% and 5.0% respectively in 2023 and are forecast to grow by 6.5%, 6.0% and 5.0% this year, Chinese growth also compares very favourably with other developing countries, which as a weighted average grew by 4.1% last year and are forecast to grow at the same rate this year.

But in the past, Chinese growth was much higher and was a major driver of global growth. Over the period 1980 to 2018, Chinese economic growth averaged 9.5% – more than twice the average rate of developing countries (4.5%) and nearly four times the average rate of advanced countries (2.4%) (see chart – click here for a PowerPoint of the chart).

Not only is Chinese growth now much lower, but it is set to decline further. The IMF forecasts that in 2025, Chinese growth will have fallen to 4.1% – below the forecast developing-country average of 4.2% and well below that of India (6.5%).

Causes of slowing Chinese growth

There are a number of factors that have come together to contribute to falling economic growth rates – growth rates that otherwise would have been expected to be considerably higher as the Chinese economy reopened after severe Covid lockdowns.

Property market
China has experienced a property boom over the past 20 years years as the government has encouraged construction in residential blocks and in factories and offices. The sector has accounted for some 20% of economic activity. But for many years, demand outstripped supply as consumers chose to invest in property, partly because of a lack of attractive alternatives for their considerable savings and partly because property prices were expected to go on rising. This lead to speculation on the part of both buyers and property developers. Consumers rushed to buy property before prices rose further and property developers borrowed considerably to buy land, which local authorities encouraged, as it provided a valuable source of revenue.

But now there is considerable overcapacity in the sector and new building has declined over the past three years. According to the IMF:

Housing starts have fallen by more than 60 per cent relative to pre-pandemic levels, a historically rapid pace only seen in the largest housing busts in cross-country experience in the last three decades. Sales have fallen amid homebuyer concerns that developers lack sufficient financing to complete projects and that prices will decline in the future.

As a result, many property developers have become unviable. At the end of January, the Chinese property giant, Evergrande, was ordered to liquidate by a Hong Kong court, after the judge ruled that the company did not have a workable plan to restructure around $300bn of debt. Over 50 Chinese property developers have defaulted or missed payments since 2020. The liquidation of Evergrande and worries about the viability of other Chinese property developers is likely to send shockwaves around the Chinese property market and more widely around Chinese investment markets.

Overcapacity
Rapid investment over many years has led to a large rise in industrial capacity. This has outstripped demand. The problem could get worse as investment, including state investment, is diverted from the property sector to manufacturing, especially electric vehicles. But with domestic demand dampened, this could lead to increased dumping on international markets – something that could spark trade wars with the USA and other trading partners (see below). Worries about this in China are increasing as the possibility of a second Trump presidency looks more possible. The Chinese authorities are keen to expand aggregate demand to tackle this overcapacity.

Uncertainty
Consumer and investor confidence are low. This is leading to severe deflationary pressures. If consumers face a decline in the value of their property, this wealth effect could further constrain their spending. This will, in turn, dampen industrial investment.

Uncertainty is beginning to affect foreign companies based in China. Many foreign companies are now making a loss in China or are at best breaking even. This could lead to disinvestment and add to deflationary pressures.

The Chinese stock market and policy responses
Lack of confidence in the Chinese economy is reflected in falling share prices. The Shanghai SSE Composite Index (an index of all stocks traded on the Shanghai Stock Exchange) has fallen dramatically in recent months. From a high of 3703 in September 2021, it had fallen to 2702 on 5 Feb 2024 – a fall of 27%. It is now below the level at the beginning of 2010 (see chart: click here for a PowerPoint). On 5 February alone, some 1800 stocks fell by over 10% in Shanghai and Shenzhen. People were sensing a rout and investors expressed their frustration and anger on social media, including the social media account of the US Embassy. The next day, the authorities intervened and bought large quantities of key stocks. China’s sovereign wealth fund announced that it would increase its purchase of shares to support the country’s stock markets. The SSE Composite rose 4.1% on 6 February and the Shenzhen Component Index rose 6.2%.

However, the rally eased as investors waited to see what more fundamental measures the authorities would take to support the stock markets and the economy more generally. Policies are needed to boost the wider economy and encourage a growth in consumer and business confidence.

Interest rates have been cut four times since the beginning of 2022, when the prime loan rate was cut from 3.85% to 3.7%. The last cut was from 3.55% to 3.45% in August 2023. But this has been insufficient to provide the necessary boost to aggregate demand. Further cuts in interest rates are possible and the government has said that it will use proactive fiscal and effective monetary policy in response to the languishing economy. However, government debt is already high, which limits the room for expansionary fiscal policy, and consumers are highly risk averse and have a high propensity to save.

Graduate unemployment
China has seen investment in education as an important means of increasing human capital and growth. But with a slowing economy, there are are more young people graduating each year than there are graduate jobs available. Official data show that for the group aged 16–24, the unemployment rate was 14.9% in December. This compares with an overall urban unemployment rate of 5.1%. Many graduates are forced to take non-graduate jobs and graduate jobs are being offered at reduced salaries. This will have a further dampening effect on aggregate demand.

Demographics
China’s one-child policy, which it pursued from 1980 to 2016, plus improved health and social care leading to greater longevity, has led to an ageing population and a shrinking workforce. This is despite recent increases in unemployment in the 16–24 age group. The greater the ratio of dependants to workers, the greater the brake on growth as taxes and savings are increasingly used to provide various forms of support.

Effects on the rest of the world

China has been a major driver of world economic growth. With a slowing Chinese economy, this will provide less stimulus to growth in other countries. Many multinational companies, including chip makers, cosmetics companies and chemical companies, earn considerable revenue from China. For example, the USA exports over $190 billion of goods and services to China and these support over 1 million jobs in the USA. A slowdown in China will have repercussions for many companies around the world.

There is also the concern that Chinese manufacturers may dump products on world markets at less than average (total) cost to shift stock and keep production up. This could undermine industry in many countries and could initiate a protectionist response. Already Donald Trump is talking about imposing a 10% tariff on most imported goods if he is elected again in November. Such tariffs could be considerably higher on imports from China. If Joe Biden is re-elected, he too may impose tariffs on Chinese goods if they are thought to be unfairly subsidised. US (and possibly EU) tariffs on Chinese goods could lead to a similar response from China, resulting in a trade war – a negative sum game.

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Questions

  1. Why is China experiencing slowing growth and is growth likely to pick up over the next five years?
  2. How does the situation in China today compare with that in Japan 30 years ago?
  3. What policies could the Chinese government pursue to stimulate economic growth?
  4. What policies were enacted towards China during the Trump presidency from 2017 to 2020?
  5. Would you advise the Chinese central bank to cut interest rates further? Explain.
  6. Should China introduce generous child support for families, no matter the number of children?
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Financial resilience needed as confidence weakens

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.

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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?
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Desperately seeking confidence, again

It is perhaps timely given the ongoing uncertainty around Brexit to revisit and update our blog Desperately seeking confidence written back in January. Consumer and business confidence reflects the sentiment, emotion, or anxiety of consumers and businesses. Confidence surveys therefore try to capture these feelings of optimism or pessimism. They may then provide us with timely information for the short-term prospects for private-sector spending. For example, declining levels of confidence might be expected to play a part in weakening the growth of consumption and investment spending.

Attempts are made to measure confidence through the use of surveys. One long-standing survey is that conducted for the European Commission. Each month consumers and firms across the European Union are asked a series of questions, the answers to which are used to compile indicators of consumer and business confidence. For instance, consumers are asked about how they expect their financial position to change. They are offered various options such as ‘get a lot better, ‘get a lot worse’ and balances are then calculated on the basis of positive and negative replies.

The chart plots confidence in the UK for consumers and different sectors of business since the mid 1990s. The chart captures the volatility of confidence. This volatility is generally greater amongst businesses than consumers, and especially so in the construction sector. (Click here to download a PowerPoint copy of the chart.)

Confidence measures rebounded across all sectors during the 2010s, with positive balances being recorded consistently from 2013 to 2016 in services, retail and industry. Subsequently, confidence indicators became more erratic though often remaining at above-average levels. However, confidence indicators have eased across the board in recent months. In some cases the easing has been stark. For example, the confidence balance in the service sector, which contributes about 80 per cent of the economy’s national income, fell from +10.9 in February 2018 to -16.2 in February 2019, though recovering slightly to -9.2 in March 2019.

Chart 2 shows how the recent easing of consumer confidence has seen the confidence balance fall below its long-term (median) average of -7. In March 2019 the balance stood at -11.7 the lowest figure since November 2013. To put the easing into further perspective, the consumer confidence balance had been as high as +8.2 in September 2015. (Click here to download a PowerPoint copy of the chart.)

Changes in confidence are used frequently as an example of a demand shock. In reality changes in consumer confidence are often likely to be an amplifier of shocks rather than the source. For example, the collapse in aggregate demand in 2007/8 that followed the ‘credit crunch’, the severe tightening of credit conditions and financial distress of many sectors of the economy is likely to have been amplified by the collapse in consumer confidence. The weakening of confidence since 2016 is perhaps a purer example of a ‘confidence shock’. Nonetheless, falls in confidence, whether they amplify existing shocks or are the source of shocks, are often a signal of greater economic uncertainty.

Greater uncertainty is likely to go and hand in hand with lower confidence and is likely to reflect greater uncertainty about future income streams. The result is that people and businesses become more prudent. In the context of households this implies a greater willingness to engage in self-insurance through increased saving. This is known as buffer stock or precautionary saving. Alternatively, people may reducing levels of borrowing. In uncertain times prudence can dominate our impatience that encourages us to spend.

Chart 3 plots the paths of the UK household-sector saving ratio and consumer confidence. The saving ratio approximates the proportion of disposable income saved by the household sector. What we might expect to see, if greater uncertainty induces buffer-stock saving, is for falls in confidence to lead to a rise in the saving ratio. Conversely, less uncertainty as proxied by a rise in confidence would lead to a fall in the saving ratio. (Click here to download a PowerPoint of the chart.)

The chart provides some evidence of this. The early 1990s and late 2000s coincided with both waning confidence and a rising saving ratio, whilst the rising confidence seen in the late 1990s coincided with a fall in the saving ratio. However, the easing of confidence since 2016 has coincided with a period where the saving ratio has been historically low. In the first quarter of 2017 the saving ratio was just 3.3 per cent. Although the saving ratio has ticked up a little, in the final quarter of 2018 it remained historically low at just 4.9 per cent. Hence, the available data on the saving ratio does not provide clear evidence of the more cautious behaviour we might expect with waning confidence.

Consider now patterns in the consumer confidence balance 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.

Data on consumer credit is more timely than that for the saving ratio. Therefore, Chart 4 shows the relationship between consumer confidence and consumer credit into 2019. We observe a reasonably close association consumer credit growth and consumer confidence. Certainty, the recent easing in confidence is mirrored by an easing in the annual growth of net consumer credit. (Click here to download a PowerPoint of the chart.)

The year-to-year growth in net consumer credit has eased considerably since the peak of 10.9 per cent in November 2016. In February 2019 the annual growth rate of net consumer credit had fallen back to 6.3 per cent, its lowest rate since September 2014. As we noted in our recent blog Riding the consumer credit cycle (again) it is hard to look much past the effect of Brexit in acting as a lid on the growth in consumer credit. Therefore, while the recent falls in consumer confidence have yet to markedly affect the saving ratio they may instead be driving the slowdown in consumer credit. The effect will be to weaken the growth of consumer spending.

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Questions

  1. Draw up a series of factors that you think might affect both consumer and business confidence. How similar are both these lists?
  2. Which of the following statements is likely to be more accurate: (a) Confidence drives economic activity or (b) Economic activity drives confidence?
  3. What macroeconomic indicators would those compiling the consumer and business confidence indicators expect each indicator to predict?
  4. What is meant by the concept of ‘prudence’ in the context of spending? What factors might determine the level of prudence
  5. How might prudence be expected to affect spending behaviour?
  6. How might we distinguish between confidence ‘shocks’ and confidence as a ‘propagator’ of shocks?
  7. What is meant by buffer stock or precautionary saving? Draw up a list of factors that are likely to affect levels of buffer stock saving.
  8. If economic uncertainty is perceived to have increased how could this affect the consumption, saving and borrowing decisions of people?