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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

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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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Should train companies scrap peak-time fares?

In many countries, train fares at peak times are higher than at off-peak times. This is an example of third-degree price discrimination. Assuming that peak-time travellers generally have a lower price elasticity of demand, the policy allows train companies to increase revenue and profit.

If the sole purpose of ticket sales were to maximise profits, the policy would make sense. Assuming that higher peak-time fares were carefully set, although the number travelling would be somewhat reduced, this would be more than compensated for by the higher revenue per passenger.

But there are external benefits from train travel. Compared with travel by car, there are lower carbon emissions per person travelling. Also, train travel helps to reduce road congestion. To the extent that higher peak-time fares encourage people to travel by car instead, there will be resulting environmental and congestion externalities.

The Scottish experiment with abolishing higher peak-time fares

In October 2023, the Scottish government introduced a pilot scheme abolishing peak-time fares, so that tickets were the same price at any time of the day. The idea was to encourage people, especially commuters, to adopt more sustainable means of transport. Although the price elasticity of demand for commuting is very low, the hope was that the cross-price elasticity between cars and trains would be sufficiently high to encourage many people to switch from driving to taking the train.

One concern with scrapping peak-time fares is that trains would not have the capacity to cope with the extra passengers. Indeed, one of the arguments for higher peak-time fares is to smooth out the flow of passengers during the day, encouraging those with flexibility of when to travel to use the cheaper and less crowded off-peak trains.

This may well apply to certain parts of the UK, but in the case of Scotland it was felt that there would be the capacity to cope with the extra demand at peak time. Also, in a post-COVID world, with more people working flexibly, there was less need for many people to travel at peak times than previously.

Reinstatement of peak-time fares in Scotland

It was with some dismay, therefore, especially by commuters and environmentalists, when the Scottish government decided to end the pilot at the beginning of October 2024 and reinstate peak-time fares – in many cases at nearly double the off-peak rates. For example, the return fare between Glasgow and Edinburgh rose from £16.20 to £31.40 at peak times.

The Scottish government justified the decision by claiming that passenger numbers had risen by only 6.8%, when, to be self-financing, an increase of 10% would have been required. But this begs the question of whether it was necessary to be self-financing when the justification was partly environmental. Also, the 6.8% figure is based on a number of assumptions that could be challenged (see The Conversation article linked below). A longer pilot would have helped to clarify demand.

Other schemes

A number of countries have introduced schemes to encourage greater use of the railways or other forms of public transport. One of these is the flat fare for local journeys. Provided that this is lower than previously, it can encourage people to use public transport and leave their car at home. Also, its simplicity is also likely to be attractive to passengers. For example, in England bus fares are capped at £2. Currently, the scheme is set to run until 31 December 2024.

Another scheme is the subscription model, whereby people pay a flat fee per month (or week or year, or other time period) for train or bus travel or both. Germany, for example, has a flat-rate €49 per month ‘Deutschland-Ticket‘ (rising to €58 per month in January 2025). This ticket provides unlimited access to local and regional public transport in Germany, including trains, buses, trams, metros and ferries (but not long-distance trains). This zero marginal fare cost of a journey encourages passengers to use public transport. The only marginal costs they will face will be ancillary costs, such as getting to and from the train station or bus stop and having to travel at a specific time.

Articles

Questions

  1. Identify the arguments for and against having higher rail fares at peak times than at off-peak times
  2. Why might it be a good idea to scrap higher peak-time fares in some parts of a country but not in others?
  3. Provide a critique of the Scottish government’s arguments for reintroducing higher peak-time fares.
  4. With reference to The Conversation article, why is it difficult to determine the effect on demand of the Scottish pilot of scrapping peak-time fares?
  5. What are the arguments for and against the German scheme of having a €49 per month public transport pass for local and regional transport with no further cost per journey? Should it be extended to long-distance trains and coaches?
  6. In England there is a flat £2 single fare for buses. Would it be a good idea to make bus travel completely free?
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The ‘Basel Endgame’: how much capital is enough capital?

Recently, US regulators have decided not to impose further increases in capital requirements on US large and mid-sized banks. The increased requirements, proposed in late 2023, would have been stricter than required under the Bank for International Settlements’ Basel framework1 and provoked a fierce backlash, involving public statements by senior bank executives, aggressive lobbying and extensive media campaigns, including an ad-spot during the Superbowl.

Following bank insolvencies in the USA during 2023, such as Silicon Valley Bank (SVB) and First Republic, which required bailouts from US banking authorities, many commentators argued that the failures were caused by the institutions having insufficient capital to cover losses on their portfolios of US Treasuries. The implication was that banks, particularly mid-sized ones (which were exempt from the Basel framework), needed to have more capital.

US regulators duly responded by proposing what was officially known as ‘the finalisation of Basel III’, but was commonly referred to as ‘the Basel Endgame’. The proposed system-wide reforms involved more conservative calculations of the risk-weighted value of assets such as mortgages, corporate loans and loans to other financial institutions. Further, the proposals also sought to subject banks with $100bn to $250bn of assets to Basel capital adequacy requirements for the first time. Previously they applied only to banks with $250 of assets.

The issue focused attention on the capital banks hold to protect against insolvency and provoked discussion about how much of a capital buffer these institutions should have.

Critics argued the changes would lead to significant increases in the capital required to be held by all US banks compared to international rivals and have an adverse effect on their profitability and international competitiveness. Further, critics pointed out that problems at SVB and First Republic were down to confidence issues and it was argued that more capital would not have saved those institutions from insolvency.

This blog examines these issues. It analyses the role of capital in banks and discusses the trade-off that banks face between profitability and security in their activities which underpinned their resistance to the proposed increases. I will also discuss the other trade-off that banks face – between liquidity and profitability – and how liquidity is just as important an influence on bank’s survival in times of crisis.

The role of capital in banks

As with any limited company, a bank’s capital is the difference between total assets and its liabilities. It is the funding provided by long-term investors. These are primarily shareholders, but also long-term debtholders. Bank capital acts as a buffer to prevent insolvency. Capital represents the amount that the value of assets have to fall before the bank is insolvent (value of assets is below liabilities). Higher capital provides a greater buffer. Lower capital provides a smaller buffer.

Capital is uniquely important for commercial banks compared to non-financial companies because of the nature of the assets banks hold – financial securities and loans. Banks are susceptible to losses from financial securities and ‘bad debts’, which are directly reflected in the value of their capital. Further, unlike non-financial companies, the failure of a bank has a significantly negative impact on wider economic activity.

The trade-off between profitability and security

As limited companies, banks face a trade-off between profitability and security in lending. The more profitable a loan, the more risky (less secure) it is likely to be. This creates the potential for the interests of deposit holders and regulators on the one hand and bank executives and shareholders on the other to diverge.

Depositors place their funds with banks and will want the bank to be secure, holding lots of capital to prevent insolvency. However, bank executives and shareholders have a strong incentive to lower the capital buffer, particularly equity, because it produces a higher return for shareholders.

Let’s analyse the implications of different capital buffers on profitability and return, particularly the return to shareholders. A performance measure used to analyse the return to shareholders is Return on Equity (RoE) – the amount of profit each pound of equity capital generates, expressed as a percentage. It is calculated by dividing net profit by equity capital and multiplying by 100.


If a bank has a net profit of £1m and holds £10m of equity capital, the RoE is:


If it has a net profit of £1m and holds £5m of equity capital, the RoE is:


In the first case, the capital buffer generates a 10 per cent RoE. In the second case, the lower capital buffer generates a higher RoE of 20 per cent. This provides a simple illustration of the trade-off banks face. The lower the amount of capital they hold, the higher the return to shareholders but the lower capital buffer, which increases the risk of insolvency.

In different time periods, banks have held varying percentages of capital. For much of the 20th century, banks had capital ratios of around 20 per cent, generating a return on equity of between 5 and 10 per cent. Bank lending was restricted, with shareholders accepting a lower return on equity, while holding a higher amount of capital to cover potential losses from financial assets. Indeed, in the 19th century, banks typically held even more capital, amounting to about 50 per cent of their assets, making bank lending even more restricted.

However, starting from the 1960s, but accelerating during the 1980s, banks began to change their view of the trade-off between profitability and security. This coincided with the liberalisation of credit markets and a greater emphasis on ‘shareholder value’ in business. Average capital ratios fell from over 20 per cent in the 1960s to below 10 per cent in the early 2000s. The return on equity went in the opposite direction. In the 1960s, it was typically between 5 and 10 per cent; by the decade before the 2008 financial crisis it had risen to above 20 per cent. The trade-off had shifted in favour of profitability.

However, the dangers of this shift were exposed during the 2008 financial crisis. The capital held by banks was very thin and not designed to cope with extremely stressful economic circumstances. Banks found they had insufficient capital to cover losses from big decreases in the value of their securitised debt instruments like CDOs (collateralised debt obligations) and struggled to raise additional capital from worried investors.

After the crisis, the Bank of International Settlements (BIS) determined that banks needed to hold sufficient capital, not just to cope with the ebbs and flows of the business cycle but also as a buffer in the rare, yet extremely stressful, economic circumstances that might arise. Therefore, international bank regulations were redrafted under the auspices of the BIS’s Basel Committee. The third version of these regulations is known as ‘Basel III’. It was agreed in 2017, with the measures being phased in from 2022. Basel III significantly raised the capital buffers for large global banks, known as ‘globally systemically-important banks’ (G-SIBs) and the use of stress-tests to model the robustness of banks’ balance sheets to cope with severe economic pressures.

Figure 1 shows the changes to the average return on equity (RoE) and average tier 1 capital ratios for a sample of 10 G-SIBs as a result of Basel III. By 2022, all the banks had capital buffers which were well above the minimum required under Basel III for tier 1 capital – 8.5 per cent. The trade-off was that banks’ average return on equity was much lower – around 8 per cent in 2022, compared to 16 per cent in 2007.

How much capital is enough capital?

Ever since the Basel III agreement, there had been discussions around tightening capital requirements further but no agreement had been reached. One aspect of Basel III was that increased capital was only required of the largest banks. Mid-sized and smaller banks, which are a significant part of the US market, were exempt. The failures of the mid-sized US Silicon Valley Bank (SVB) and First Republic Bank provoked unilateral proposals by the US authorities through the ‘Basel Endgame’. This would raise capital requirements for large banks and extend capital requirements to mid-sized institutions.

But large US banks resisted these proposals, arguing that the authorities were pushing the trade-off too far in favour of security, attempting to make banks very safe but offering a poor return for investors and decreasing the amount of lending banks would conduct.

The furore raises the question as to what is an adequate amount of capital. One reference point is non-financial institutions. These typically hold much more capital relative to the value of total assets – in the range from 30 per cent to 40 per cent. If banks had capital ratios at that level, or even higher, they would be perceived as extremely safe, but might not offer much return to shareholders, impinging on the ability of banks to raise additional capital when they needed it.

Further, other critics argue that there is too much emphasis placed on capital adequacy. Focusing on capital ignores the other significant trade-off banks face in their activities – between liquidity and profitability. Indeed, recent bank failures were not due to insufficient capital but other problems relating to the management of the institution, which led to a loss of confidence by not only by investors, but primarily, deposit-holders.

The other trade-off: liquidity and profitability

While banks have to be solvent, they have to manage their trade-off between liquidity and profitability carefully too. A commercial bank’s basic business model involves maturity transformation – transforming liquid deposits into illiquid assets, such as government bonds and loans, to generate profit. This requires balancing the desire for profitability with the liquidity needs of depositors. If banks get it wrong, then it can lead to a loss of confidence and a ‘run’ on deposits. This is what happened to both Silicon Valley Bank (SVB) and Credit Suisse. The failures of both institutions were not due to insufficient capital but poor liquidity management, which eventually caused a loss of confidence.

Silicon Valley Bank (SVB) demonstrated poor liquidity management, involving a narrow depositor base which was very responsive to changes in interest rates, and an illiquid asset portfolio. During the coronavirus pandemic, tech start-ups received substantial venture capital funding and deposited it with SVB. SVB did not have the capacity or inclination to lend all of the extensive deposits which they were receiving. Instead, the management decided to invest in long-term fixed rate government debt securities. Such securities represented 56 per cent of SVB’s assets in 2020.

Since SVB’s depositors were businesses, unlike retail depositors they were more sensitive to changing interest rates. As rates rose, businesses moved their funds out in search of higher rates, creating a liquidity problem for SVB. The bank was forced to sell $21bn of its long-dated bonds to provide liquidity. However, it endured losses when it sold the bonds as bond prices had fallen, reflecting higher interest rates. Therefore, it needed to raise capital to replace the losses from those sales.

Investors baulked at this, however, particularly when they observed the accelerating deposit outflows. It was the ‘run’ on deposits that was the problem ($42 billion on 8 March 2023 alone), not the unrealised losses on government bonds relative to capital. It was only when the losses were realised that the problem arose. Indeed, Bank of America was in a similar situation with a substantial portfolio of long-term government debt. However, it did not have to realise its ‘paper losses’ since its deposits were more ‘sticky’.

Once confidence is lost and there is a run on deposits, even a bank which has a capital buffer deemed to be more than sufficient is doomed to fail. Take Credit Suisse. It was subject to the Basel framework and had capital ratios similar to its ultimate acquirer UBS. However, it had a risky business culture that pushed the trade-off too much towards profitability. This led to repeated scandals, fines and losses, which caused investors to lose confidence in the institution.

But, once again, it was not the financial losses that was the problem. It was the loss of confidence by depositors. The institution suffered deposit withdrawals of CHF 67 billion in the first three months of 2023. Attempts to stem the outflow with a ‘liquidity backstop’ provided by the Swiss National Bank on 15 March 2023 failed to reassure investors and depositors. Instead, the bank run intensified, with daily withdrawals of demand deposits topping CHF 10bn in the week afterwards. Credit Suisse failed and the Swiss banking regulators quickly forced its acquisition by UBS.

Conclusion

Bank capital is important. After the financial crisis, banks needed to redress the trade-off between profitability and security in lending. However, while the US authorities desire to improve the security of their banking system is laudable, the focus on capital is misplaced. Ever-increasing capital is not the solution to every banking crisis.

Ultimately, banks depend on confidence. Once that confidence is lost, there is little an institution can do to prevent failure. More emphasis needs to be placed on better management of assets and liabilities to maintain sufficient profitability, while at the same time being both liquid and secure. This will maintain confidence, not only by investors, but particularly by deposit-holders.

1 See Economics 11e, section 18.2; Economics for Business 9e, section 28.2; Essentials of Economics 9e, section 11.2.

Articles

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Information

Questions

  1. Explain the role of capital for a commercial bank.
  2. Research the ‘Basel Endgame’ proposals. Why would US regulators want banks to hold more capital?
  3. Explain the trade-off between profitability and security that banks face.
  4. Explain the trade-off between profitability and liquidity that banks face.
  5. Research Silicon Valley Bank’s failure and trace the ‘run’ on deposits in the bank. Explain why investors baulked at injecting more capital.
  6. Research Credit Suisse’s demise and trace the ‘run’ on deposits in that bank. Explain why investors baulked at injecting more capital.
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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.

Articles

Data

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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Disgruntled Oasis fans react to dynamic pricing

On Saturday 31 August, tickets for the much-heralded Oasis reunion tour went on sale through the official retailer, Ticketmaster. When the company sells tickets, the acts or their promoters can choose whether to use a static pricing system, where each type of ticket is sold at a set price until they have all been sold. Or they can use a dynamic pricing system (‘in-demand’ or ‘platinum’ tickets, as Ticketmaster calls them), where there is a starting price quoted, but where prices then rise according to demand. The higher the demand, the more the price is driven up. Acts or their promoters have the option of choosing an upper limit to the price.

Dynamic pricing

The Oasis tickets were sold under the dynamic pricing system, a system previously used for Harry Styles, Bruce Springsteen, Coldplay and Blackpink concerts, but one rejected by Taylor Swift for her recent Eras tour. Standing tickets for the Oasis concert with a face value of around £135 were quickly being sold for over £350. There were long online queues, with the prices rising as people slowly moved up the queue. When they reached the front, they had to decide quickly whether to pay the much higher price. Some people later suffered from buyer’s remorse, when they realised that in the pressure of the moment, they had paid more than they could afford.

Dynamic pricing is when prices change with market conditions: rising at times when demand exceeds supply and falling when supply exceeds demand. It is sometimes referred to as ‘surge pricing’ to reflect situations when price surges in times of excess demand.

Dynamic pricing is a form of price discrimination. It is an imperfect form of first-degree price discrimination, which is defined as people being charged the maximum price they are willing to pay for a product. Pricing in an eBay auction comes close to first-degree price discrimination. With dynamic pricing in the ticket market, some people may indeed pay the maximum, but others earlier in the queue will be lucky and pay less than their maximum.

Ticketmaster justifies the system of dynamic pricing, saying that it gives ‘fans fair and safe access to the tickets, while enabling artists and other people involved in staging live events to price tickets closer to their true market value’. The company argues that if the price is below the market value, a secondary market will then drive ticket prices up. Ticket touts will purchase large amounts of tickets, often using bots to access the official site and then resell them at highly inflated prices on sites such as Viagogo and Stubhub, where ticket prices for popular acts can sell for well over £1000. The day after Oasis tickets went on sale, Viagogo had seats priced at up to £26 000 each!

Oasis and Ticketmaster have tried to stamp out the unofficial secondary market by stating that only tickets bought through the official retailers (Ticketmaster, Gigsandtours and SeeTickets) will be valid. If fans want to resell a ticket – perhaps because they find they can no longer go – they can resell them on the official secondary market though Ticketmaster’s Fan-to-Fan site or Twickets. These official secondary sites allow holders of unwanted tickets to sell them for anything up to the original face value, but no more. Buyers pay a 12% handling fee. It remains to be seen whether this can be enforced with genuine tickets resold on the secondary market.

Examples of dynamic pricing

Dynamic pricing is not a new pricing strategy. It has been used for many years in the transport, e-commerce and hospitality sectors. Airlines, for example, have a pricing model whereby as a flight fills up, so the prices of the seats rise. If you book a seat on a budget airline a long time in advance, you may be able to get it at a very low price. If, on the other hand, you want a seat at the last minute, you may well have to pay a very high price. The price reflects the strength of demand and its price elasticity. The business traveller who needs to travel the next day for a meeting will have a very low price sensitivity and may well be prepared to pay a very high price indeed. Airlines also learn from past behaviour and so some popular routes will start at a higher price. A similar system of dynamic pricing is used with advance train tickets, with the price rising as trains get booked up.

The dynamic pricing system used by airlines and train companies is similar, but not identical, to first-degree price discrimination. The figure below illustrates first-degree price discrimination by showing a company setting the price for a particular product.

Assume initially that it sets a single profit-maximising price. This would be a price of P1, at an output of Q1, where marginal revenue (MR) equals marginal cost (MC). (We assume for simplicity that average and marginal costs are constant.) Total profit will be area 1: i.e. the blue area ((P1 – AC) × Q1). Area 2 represents consumer surplus, with all those consumers who would have been prepared to pay a price above P1, only having to pay P1.

Now assume that the firm uses first-degree price discrimination, selling each unit of the product at the maximum price each consumer is willing to pay. Starting with the consumer only willing to pay a price of P2, the price will go on rising up along the demand with each additional consumer being charged a higher price up to the price where the demand curve meets the vertical axis. In such a case, the firm’s profit would be not just the blue area, but also the green areas 2 and 3. Note that there is no consumer surplus as area 2 is now part of the additional profit to the firm.

Although dynamic pricing by airlines is similar to this model of first-degree price discrimination, in practice some people will be paying less than they would be willing to pay and the price goes up in stages, not continuously with each new sale of a ticket. Thus, compared with a fixed price per seat, the additional profit will be less than areas 2 + 3, but total profit will still be considerably greater than area 1 alone. Note also that there is a maximum quantity of seats (Qmax), represented by a full flight. The airline would hope that demand and its pricing model are such that Qmax is less than Q2.

Dynamic pricing also applies in the hospitality sector, as hotels raise the prices for rooms according to demand, with prices at peak times often being considerably higher than off-season prices. Rather then pre-setting prices for particular seasons, dates or weekends/weekdays, many hotels, especially chains and booking agents, adjust prices dynamically as demand changes. Airbnb offers property owners what it calls ‘Smart Pricing’, where nightly prices change automatically with demand.

Another example is Uber, which uses dynamic pricing to balance demand and supply location by location. In times of peak demand on any route, the company’s algorithm will raise the price. This will encourage people to delay travelling if they can or use alternative means of transport. It will also encourage more Uber drivers to come to that area. In times of low demand, the price will fall. This will encourage more people to use the service (rather than regular taxis or buses) and discourage drivers from working in that area.

Where dynamic pricing varies with the time or date when the purchase is made, it is sometimes referred to as inter-temporal pricing. It is a form of second-degree price discrimination, which is where a firm offers consumers a range of different pricing options for the same or similar products.

Another example of dynamic pricing, which is closer to first-degree price discrimination is the use of sophisticated algorithms and AI by Amazon, allowing it to update the prices of millions of products many times a day according to market conditions. Another is eBay auctions, where the price rises as the end date is reached, according to the willingness to pay of the bidders.

Attitudes to dynamic pricing

Consumers have grown accustomed to dynamic pricing in many industries. People generally accept the pricing model of budget airlines, for example. What makes it acceptable is that most people feel that they can take advantage of early low-priced seats and can compare the current prices on different flights and airlines when making their travel plans. Pricing is transparent. With the Oasis concert, however, there wasn’t the same degree of price transparency. Many people were surprised and dismayed to find that when they got to the front of the online queue, the price had risen dramatically.

People are familiar of dynamic pricing in the context of price cuts to shift unsold stock. Supermarkets putting stickers on products saying ‘reduced for quick sale’ is an example. Another is seasonal sales. What is less acceptable to many consumers is firms putting up prices when demand is high. They see it a profiteering. Many supermarkets are introducing electronic shelf labels (ESLs), where prices can be changed remotely as demand changes. Consumers may react badly to this if they see the prices going up. The supermarket, however, may find it a very convenient way of reducing prices to shift stock – something consumers are hardly likely to complain about.

Returning to the Oasis tour, the UK government responded to the outrage of fans as ticket prices soared. Culture Secretary, Lisa Nandy, announced that the government will investigate how surge pricing for concert tickets is used by official retailers, such as Ticketmaster. This will be part of a planned review of ticket sales that seeks to establish a fairer and more transparent system of pricing.

The problem is that, with some fans being prepared to pay very high prices indeed to see particular acts and with demand considerably exceeding supply at prices that fans would consider reasonable, some way needs to be found of rationing demand. If it is not price, then it will inevitably involve some form of queuing or rationing system, with the danger that this encourages touts and vastly inflated prices on the secondary market.

Perhaps a lesson can be drawn from the Glastonbury Festival, where prices are fixed, people queue online and where security systems are in place to prevent secondary sales by ticket touts. The 2024 price was set at £355 + a £5 booking fee and purchasers were required to register with personal details and a photo, which was checked on admission.

Update

On 5 September, the CMA announced that it was launching an investigation into Ticketmaster over the Oasis concert sales. Its concerns centred on ‘whether buyers were given clear and timely information, and whether consumer protection law was breached’. This followed complaints by fans that (i) they were not given clear and timely information beforehand that the tickets involved dynamic pricing and warned about the possible prices they might have to pay and (ii) on reaching the front of the queue they were put under pressure to buy tickets within a short period of time.

Meanwhile, band member stated that they were unaware that dynamic pricing would be used and that the decision to use the system was made by their management.

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Questions

  1. What is the difference between dynamic pricing and surge pricing?
  2. What is buyer’s remorse? How could dynamic pricing be used while minimising the likelihood of buyer’s remorse?
  3. Distinguish between first-degree, second-degree and third-degree price discrimination. Do the various forms of dynamic pricing correspond to one or more of these three types?
  4. Distinguish between consumer and producer surplus. How may dynamic pricing lead to a reduction in consumer surplus and an increase in producer surplus?
  5. Should Ticketmaster sell tickets on the same basis as tickets for the Glastonbury Festival?
  6. Is Oasis a monopoly? What are the ticket pricing implications?
  7. Are there any industries where firms would not benefit from dynamic pricing? Explain.
  8. What are the arguments for and against allowing tickets to be sold on the secondary market for whatever price they will fetch?
  9. How powerful is Ticketmaster in the primary and secondary ticket markets?