Category: Economics for Business: Ch 23

With relentless bombing of Iran by Israel and the USA, and with Iranian counterattacks on Gulf states, the costs of the war are mounting. The most obvious are in terms of human lives, injuries and suffering. But there are significant economic costs too. Some of these are immediate, such as the rising price of oil and hence the costs of fuel, or the fall in stock market prices. Some will be longer term, depending on how the war develops. For example, prices could rise more generally as supply chains are disrupted.

The impacts will vary across the world and across markets. The most obvious markets to be affected are those where significant supply comes from the Persian Gulf. Approximately 20% of total global oil consumption passes through the Strait of Hormuz, which connects the Persian Gulf with the Arabian Sea and the Indian Ocean.

Oil prices rose considerably in the days following the start of the war on 28 February, with Brent crude, a key measure of international oil prices, rising from $71.3 on 27 February to a peak of $119.4 per barrel by the morning of 9 March – a rise of 67%. It was possible that they would rise even further in the short term. However, prices fell back substantially later on 9 March after G7 finance ministers declared that the group ‘stands ready’ to release oil from strategic reserves if needed. By late in the day, the price had fallen to below $85. (Click here for a PowerPoint of the chart.)

However, despite the announcement on 11 March that 32 countries had agreed to release 400m barrels of oil reserves, oil prices began rising again and reached $100 on 12 March after three tankers had been struck in the Gulf, two of them close to the Strait of Hormuz. With Iran pledging to keep the Strait closed, there were worries that the release of oil reserves would provide only temporary relief. Just over 20m barrels of oil normally pass through the Strait of Hormuz. The 400m barrels released from storage is the equivalent, therefore, of only 20 days’ worth of lost oil from the Gulf.

Not only did oil prices rise, but the price became much more volatile as markets reacted to the news on a continuous basis. Intra-day fluctuations in oil prices of several percentage points became typical, reflecting shifting expectations. The second chart shows daily fluctuations, with the highest and lowest prices for each day shown, along with the closing price. (Click here for a PowerPoint.)

The biggest fluctuation had been on 9 March when fears of the closing of the Strait of Hormuz saw the price of Brent crude rising to nearly $120 but falling to around $84 later in the day (a fall of around 30%) after the G7 announcement about releasing reserves.

There was another big fluctuation on 23 March. The previous day (Sunday), President Trump threatened to bomb Iran’s power plants if Iran did not allow free passage of ships through the Strait of Hormuz. Iran threatened to retaliate by striking Gulf countries’ energy and water systems. In early trading on Monday 23rd, Brent crude rose to over $115 per barrel. But later that day, Trump said that there had been constructive talks between the USA and Iran. The oil price immediately dropped to around $96 – a fall of 17% – before settling at around $100.

Rising oil prices will drive up inflation. For those countries with a heavy dependence on Gulf oil, particularly countries in Asia, there could be significant supply problems. For oil exporters in the Persian Gulf, with tankers unable to traverse the Strait of Hormuz, the economic impact is huge. Oil exporters outside the Gulf, such as Russia, Norway and Canada, however, will gain from the higher prices. Clearly the size of these effects will depend on how long the conflict continues and how long the Strait of Hormuz remains closed.

And it is not just oil that is affected. Other products, such as liquified natural gas (LNG), petrochemicals, industrial materials, fertilizers for food production, medicines, helium for microchip production, metals and minerals are transported through the Strait of Hormuz. Gulf countries import much of their food through the Strait. On 18 March, Israel struck Iran’s huge South Pars gas field off the Gulf coast. This is the largest gas field in the world and is a major source of export revenue for Iran. Iran responded by striking the Qatari gas hub in Ras Laffan. Donald Trump responded by threatening to ‘blow up’ the entire Iranian South Pars gas field if Iran made further strikes on Qatar. The effect of this escalation was to drive oil and gas prices up further. By the week ending 20 March, the oil price closed at just over $112 per barrel.

Cuts in supplies of oil and other products represent an adverse supply shock. Such shocks push up prices (cost-push inflation), while adversely affecting aggregate output. This can lead to stagflation – a combination of higher inflation and stagnation or even falling output. Central banks with a simple mandate to keep inflation to a target are likely to raise interest rates, or at least delay in reducing them. In the USA, with a dual mandate of controlling inflation but also maximising employment, the response may be less deflationary, depending on the judgement of the Federal Reserve.

Uncertainty

There is great uncertainty about how long the conflict will last. There is also a lack of clarity and consistency from the US administration about its war aims. This uncertainty has affected financial markets, which have seen considerable volatility. Stock markets have seen widespread falls, with airline, travel and AI-heavy stocks being particularly vulnerable.

If the war is concluded relatively swiftly, the economic effects could be relatively small. If the war continues, and especially if the Gulf countries are drawn further into the conflict and if the conflict spreads to other countries, the economic effects could be much more substantial. A prolonged conflict could see oil prices remaining above $100 per barrel, potentially increasing global inflation by 1 percentage point or more. This would slow or halt the move by central banks to cut rates and thereby reduce global economic growth – potentially, as we have seen, leading to stagflation.

The uncertainty was reflected in the decision of the Fed to keep interest rates unchanged at its meeting on 17/18 March. The Fed has the twin targets of keeping inflation close to 2% and maximising employment. Fed Chair, Jay Powell, acknowledged the current tension between the two goals: ‘upward risks for inflation and downward risks for employment, and that puts us in a difficult situation’. He also recognised that the future for inflation and the economy was highly uncertain as the war developed. This made interest rate setting difficult.

Then there is the issue of a potential new international refugee crisis. If the economic and political system in Iran deteriorates rapidly, this could trigger a wave of migration to neighbouring countries, such as Turkey, already hosting large numbers of refugees. Many could seek sanctuary further afield in Europe, with several countries already facing a backlash against immigration. The political and economic effects of this on host countries could be significant – but as yet, highly uncertain.

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Questions

  1. Who are the biggest gainers and losers from disruption to oil supplies from the Persian Gulf?
  2. Illustrate the effect of the current oil price shock on an aggregate demand and supply diagram (either static or dynamic).
  3. Why is the Iranian war likely to be less damaging to the European economy than the Ukrainian war has been?
  4. Why have AI-related stock prices been vulnerable to the uncertainty caused by the Iranian war?
  5. How have the Bank of England and the Federal Reserve Bank responded to higher oil prices and the broader economic effects of the war? Why might their responses be different in the coming months?
  6. What is the likely impact of the Iranian war on global economic recovery?
  7. How might the Iranian war affect global economic alliances?
  8. How is the current oil price shock likely to affect the eurozone? Will it be different from the oil price shock that followed the Russian invasion of Ukraine?
  9. What are the likely economic effects of large-scale migration caused by the war?

At the fourth anniversary of Russia’s invasion of Ukraine, we look at the effect of the war on the Russian economy. Two years ago, in the blog The Russian economy after two years of war, we argued that the Russian economy had seemingly weathered the war successfully.

Unlike Ukraine, very little of its infrastructure had been destroyed; it had started the war with a current account balance of payments surplus, a budget surplus and a low general government debt-to-GDP ratio; it had achieved a lot of success in diverting its exports, including oil, away from countries imposing sanctions to countries such as China and India; it was the same with imports, with China especially becoming a major suppliers of machinery, components and vehicles; it has a strong central bank, which engenders a high level of confidence in managing inflation; the military expenditure provided a Keynesian boost to the economy, with production and employment rising.

The situation today

But two years further on, the Russian economy is looking a lot weaker and on the verge of recession. GDP growth fell to 0.6 per cent in 2025 and is forecast to be no more than 1 per cent for the next two years. (Click here for a PowerPoint of the chart.) And despite growth still being positive (just), this is largely because of the growth in military expenditure. Retail and wholesale trade fell by 1.1% in 2025, reflecting supply chain problems and high inflation dampening consumer demand.

With labour being diverted into the armaments and allied industries or into the armed forces, this has led to labour shortages. This has been compounded by the emigration of up to 1 million people by 2025 – often young, educated and skilled professionals.

Official CPI inflation averaged 8.7 per cent in 2025, although the prices of food and other consumer essentials rose by more, especially in recent months. At the beginning of 2026, supermarket prices rose by 2.3% in just one month, made worse by a rise in VAT from 20% to 22%. The central bank has responded to the high inflation with high interest rates, which averaged 19.2% in 2025, giving a real rate of 10.5%. With such a high real rate, the response of households has been to save. This has masked the constraints on production, or imports, of consumer goods. Savings have also been boosted by large payments to soldiers and bereaved families, with the money saved by the recipients being used in part to fund future such payments. So far there has been trust in the banking system, but if that trust waned and people starting making large withdrawals of savings, it could be seriously destabilising.

Whilst the high real interest rates have helped to mask shortages of consumer goods, they have had a seriously dampening effect on investment by domestic companies. Gross capital formation fell by 3% in 2025, not helped by an increase in the corporation tax from 20% to 25%. At the same time, foreign direct investment remains subdued due to high perceived risks. The lack of investment, plus the labour shortages, will have profound effects on the supply side of the economy, with potential output in the non-military sector likely to decline over the medium term.

The balance of payments and government finances are turning less favourable. The balance of trade surplus has declined from US$173bn in 2021 to US$67bn in 2025. This could decline further, or even become a deficit, if oil prices continue to be weak, if Western sanctions are tightened (such as stopping the flow of Russian oil exports in the ‘shadow’ fleet of tankers) or if major importing countries stop buying Russian oil. Indian refiners have announced that they are not taking Russian crude in March/April as India seeks to finalise a trade deal with the USA.

The budget balance has moved from a small surplus of 0.8% of GDP in 2021 to a deficit of 2.9% in 2025. Although the government debt-to-GDP ratio remains low by international standards at 23.1% of GDP in 2025, this was up from 16.5% in 2021 and is set to rise further as budget deficits deepen. Nevertheless, as long as the saving rate remains high, the debt can be serviced by domestic bond purchase.

Russia’s economy is definitely weakening and labour shortages and low investment will create major problems for the future. But whether this deterioration will be enough to change Russia’s stance on the war in Ukraine remains to be seen.

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Questions

  1. What constraints are there currently on the supply side of the Russian economy?
  2. Some economists have argued that the economic effects of a stalemate in the Ukraine war would suit the Russian leadership more than peace or victory. Why might this be so?
  3. Under what circumstances might a deep recession in Russia be more likely than stagnation?
  4. In what ways does Russia’s current financial system resemble a pyramid scheme?
  5. What cannot a Keynesian boost contunue to support the Russian economy indefinitely?

With businesses increasing their use of AI, this is likely to have significant effects on employment. But how will this affect the distribution of income, both within countries and between countries?

In some ways, AI is likely to increase inequality within countries as it displaces low-skilled workers and enhances the productivity of higher-skilled workers. In other ways, it could reduce inequality by allowing lower-skilled workers to increase their productivity, while displacing some higher-skilled workers and managers through the increased adoption of automated processes.

The effect of AI on the distribution of income between countries will depend crucially on its accessibility. If it is widely available to low-income countries, it could significantly enhance the productivity of small businesses and workers in such countries and help to reduce the income gap with the richer world. If the gains in such countries, however, are largely experienced by multinational companies, whether in mines and plantations, or in labour-intensive industries, such as garment production, few of the gains may accrue to workers and global inequality may increase.

Redistribution within a country

The deployment of AI may result in labour displacement. AI is likely to replace both manual and white-collar jobs that involve straightforward and repetitive tasks. These include: routine clerical work, such as data entry, filing and scheduling; paralegal work, contract drafting and legal research; consulting, business research and market analysis; accounting and bookkeeping; financial trading; proofreading, copy mark-up and translation; graphic design; machine operation; warehouse work, where AI-enabled warehouse robots do many receiving, sorting, stacking, retrieval, carrying and loading tasks (e.g. Amazon’s Sequoia robotic system); basic coding or document sifting; market research and advertising design; call-centre work, such as enquiry handling, sales, telemarketing and customer service; hospitality reception; sales cashiers in supermarkets and stores; analysis of health data and diagnosis. Such jobs can all be performed by AI assistants, AI assisted robots or chat bots.

Women are likely to be disproportionately affected because they perform a higher share of the administrative and service roles most exposed to AI.

Workers displaced by AI may find that they can find employment only in lower-paid jobs. Examples include direct customer-facing roles, such as bar staff, shop assistants, hairdressers and nail and beauty consultants.

Such job displacement by AI is likely to redistribute income from relatively low-skilled labour to capital: a redistribution from wages to profits. This will tend to lead to greater inequality.

AI is also likely to lead to a redistribution of income towards certain types of high-skilled labour that are difficult to replace with AI but which could be enhanced by it. Take the case of skilled traders, such as plumbers, electricians and carpenters. They might be able to use AI in their work to enhance their productivity, through diagnosis, planning, problem-solving, measurement, etc. but the AI would not displace them. Instead, it could increase their incomes by allowing them to do their work more efficiently or effectively and thus increase their output per hour and enhance their hourly reward. Another example is architecture, where AI can automate repetitive tasks and open up new design possibilities, allowing architects to focus on creativity, flexibility, aesthetics, empathy with clients and ethical decision-making.

An important distinction is between disembodied and embodied AI investment. Disembodied AI investment could include AI ‘assistants’, such as ChatGPT and other software that can be used in existing jobs to enhance productivity. Such investment can usually be rolled out relatively quickly. Although the extra productivity may allow some reduction in the number of workers, disembodied AI investment is likely to be less disruptive than embodied AI investment. The latter includes robotics and automation, where workers are replaced by machines. This would require more investment and may be slower to be adopted.

Then there are jobs that will be created by AI. These include prompt engineers, who develop questions and prompt techniques to optimise AI output; health tech experts, who help organisations implement new medical AI products; AI educators, who train people in the uses of AI in the workplace; ethics advisors, who help companies ensure that their uses of AI are aligned with their values, responsibilities and goals; and cybersecurity experts who put systems in place to prevent AI stealing sensitive information. Such jobs may be relatively highly paid.

In other cases, the gains from AI in employment are likely to accrue mainly to the consumer, with probably little change in the incomes of the workers themselves. This is particularly the case in parts of the public sector where wages/salaries are only very loosely related to productivity and where a large part of the work involves providing a personal service. For example, health professionals’ productivity could be enhanced by AI, which could allow faster and more accurate diagnosis, more efficient monitoring and greater accuracy in surgery. The main gainers would be the patients, with probably little change in the incomes of the health professionals themselves. Teachers’ productivity could be improved by allowing more rapid and efficient marking, preparation of materials and record keeping, allowing more time to be spent with students. Again, the main gainers would be the students, with little change in teachers’ incomes. Other jobs in this category include social workers, therapists, solicitors and barristers, HR specialists, senior managers and musicians.

Thus there is likely to be a distribution away from lower-skilled workers to both capital and higher-skilled workers who can use AI, to people who work in new jobs created by AI and to the consumers of certain services.

AI will accelerate productivity growth and, with it, GDP growth, but will probably displace workers faster than new roles emerge. This is likely to increase inequality and be a major challenge for society. Can the labour market adapt? Could the effects be modified if people moved to a four- or three-day week? Will governments introduce statutory limits to weekly working hours? Will training and education adapt to the new demands of employers?

Redistribution between countries

AI threatens to widen the global rich–poor divide. It will give wealthier nations a productivity and innovation edge, which could displace low-skilled jobs in low-income nations. Labour-intensive production could be replaced by automated production, with the capital owned by the multinational companies of just a few countries, such as the USA and China, which between them account for 40% of global corporate AI R&D spending. For some companies, it would make sense to relocate production to rich countries, or certain wealthier developing countries, with better digital infrastructure, advanced data systems and more reliable power supply.

For other companies, however, production might still be based in low-income countries to take advantage of low-cost local materials. But there would still be a redistribution from wages in such countries to the profits of multinationals.

But it is not just in manufacturing where low-income countries are vulnerable to the integration of AI. Several countries, such as India, the Philippines, Mexico and Egypt have seen considerable investment in call centres and IT services for business process outsourcing and customer services. AI now poses a threat to employment in this industry as it has the potential to replace large numbers of workers.

AI-related job losses could exacerbate unemployment and deepen poverty in poorer countries, which, with limited resources, limited training and underdeveloped social protection systems, are less equipped to absorb economic and social shocks. This will further widen the global divide. In the case of embodied AI investment, it may only be possible in low-income countries through multinational investment and could displace many traditional jobs, with much of the benefit going in additional multinational profit.

But it is not all bad news for low-income countries. AI-driven innovations in healthcare, education, and agriculture, if adopted in poor countries, can make a significant contribution to raising living standards and can slow, or even reverse, the widening gap between rich and poor nations. Some of the greatest potential is in small-scale agriculture. Smallholders can boost crop yields though precision farming powered by AI; AI tools can help farmers buy seeds, fertilisers and animals and sell their produce at optimum times and prices; AI-enabled education tools can help farmers learn new techniques.

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Questions

  1. What types of job are most vulnerable to AI?
  2. How will AI change the comparative advantage of low-income countries and what effect will it be likely to have on the pattern of global trade?
  3. Assess alternative policies that governments in high-income countries can adopt to offset the growth in inequality caused by the increasing use of AI.
  4. What policies can governments in low-income countries or aid agencies adopt to offset the growth in inequality within low-income countries and between high- and low-income countries?
  5. How might the growth of AI affect your own approach to career development?
  6. Is AI likely to increase or decrease economic power? Explain.

The UK’s poor record on productivity since the 2008 financial crisis is well documented, not least in this blog series. Output per worker has flatlined over the 17 years since the crisis. As was noted in the blog, The UK’s poor productivity record, low UK productivity is caused by a number of factors, including the lack of investment in training, the poor motivation of many workers and the feeling of being overworked, short-termism among politicians and management, and generally poor management practices.

One of the most significant issues identified by analysts and commentators is the lack of investment in physical capital, both by private companies and by the government in infrastructure. Gross fixed capital formation (a measure of investment) has been much lower in the UK compared to international competitors.

From Figure 1 it can be observed that, since the mid-1990s, the UK has consistently had lower investment as a percentage of GDP compared to other significant developed market economies. The cumulative effect of this gap has contributed to lower productivity and lower economic growth.

Interestingly, since the financial crisis, UK firms have had high profitability and associated high cash holdings. This suggests that firms have had a lot of financial resources to reinvest. However, data from the OECD suggests that reinvestment rates in the UK, typically 40–50% of profit, are much lower than in many other OECD countries. In the USA the rate is 50%, in Germany 60–70% and in Japan 70%+. There is much greater emphasis in the UK on returning funds to shareholders through dividends and share buybacks. However, the reinvestment of much of this cash within firms could have gone some way to addressing the UK’s investment gap – but, it hasn’t been done.

Analysis by the OECD suggest that, while the cost of financing investment has declined since the financial crisis, the gap between this and the hurdle rate used to appraise investments has widened. Between 2010 and 2021 the difference nearly doubled to 4%. This increase in the hurdle rate can be related to increases in the expected rate of return by UK companies and their investors.

In this blog we will analyse (re)investment decisions by firms, discussing how increases in the expected rate of return in the UK raise the hurdle rate used to appraise investments. This reduces the incentive to engage in long-term investment. We also discuss policy prescriptions to improve reinvestment rates in the UK.

Investment and the expected rate of return

Investment involves the commitment of funds today to reap rewards in the future. This includes spending on tangible and intangible resources to improve the productive capacity of firms. Firms must decide whether the commitment of funds is worthwhile. To do so, economic theory suggests that they need to consider the compensation required by their provider of finance – namely, investors.

What rewards do investors require to keep their funds invested with the firm?

When conducting investment appraisal, firms compare the estimated rate of return from an investment with the minimum return investors are prepared to receive (termed the ‘expected return’). Normally this is expressed as a percentage of the initial outlay. Firms have to offer returns to investors which are equal to or greater than the minimum expected return – the return that is sufficient to keep funds invested in the firm. Therefore, returns above this minimum expected level are termed ‘excess returns’.

When firms conduct appraisals of potential investments, be it in tangible or intangible capital, they need to take into account the fact that net benefits, expressed as cash flows, will accrue over the life of the investment, not all at once. To do this, they use discounted cash flow (DCF) analysis. This converts future values of the net benefits to their present value. This is expressed as follows:

Where:
NPV = Net present value (discounted net cash flows);
K = Capital outlay (incurred at the present time);
C = Net cash flows (occur through the life of the investment project);
r = Minimum expected rate of return.

In this scenario, the investment involves an initial cash outlay (K), followed in subsequent periods by net cash inflows each period over the life of the investment, which in this case is 25 years. All the cash flows are discounted back to the present so that they can be compared at the same point in time.

The discount rate (r) used in appraisals to determine the present value of net cash flows is determined by the minimum expected return demanded by investors. If at that hurdle rate there are positive net cash flows (+NPV), the investment is worthwhile and should be pursued. Conversely, if at that hurdle rate there are negative net cash flows (–NPV), the investment is not worthwhile and should not be pursued.

According to economic theory, if a firm cannot find any investment projects that produce a positive NPV, and therefore satisfy the minimum expected return, it should return funds to shareholders through dividends or share buybacks so that they can invest the finance more productively.

Firm-level data from the OECD suggest that UK firms have had higher profits and this has been associated with increased cash holdings. But, due to the higher hurdle rate, less investment is perceived to be viable and thus firms distribute more of their profits through dividends and share buybacks. These payouts represent lost potential investment and cumulatively produce a significant dent in the potential output of the UK economy.

Why are expected rates of return higher in the UK?

This higher minimum rate of expected return can be explained by factors influencing its determinants; opportunity cost and risk/uncertainty.

Higher opportunity cost.  Opportunity cost relates to the rate of return offered by alternatives. Investors and, by implication firms, will have to consider the rate of return offered by alternative investment opportunities. Typically, investors have focused on interest rates as a measure of opportunity cost. Higher interest rates raise the opportunity cost of an investment and increase the minimum expected rate of return (and vice versa with lower interest rates).

However, it is not interest rates that have increased the opportunity cost, and hence the minimum expected rate of return associated with investment, in the UK since the financial crisis. For most of the period since 2008, interest rates have been extremely low, sitting at below 1%, only rising significantly during the post-pandemic inflationary surge in 2022. This indicates that this source of opportunity cost for the commitment of business investment has been extremely low.

However, there may be alternative sources of opportunity cost which are pushing up the expected rate of return. UK investors are not restricted to investing in the UK and can move their funds between international markets determined by the rate of return offered. The following table illustrates the returns (in terms of percentage stock market index gain) from investing in a sample of UK, US, French and German stock markets between August 2010 and August 2025.

When expressed in sterling, returns offered by UK-listed companies are lower across the whole period and in most of the five-yearly sub-periods. Indeed, the annual equivalent rate of return (AER) for the FTSE 100 index across the whole period is less than half that of the S&P 500. The index offered a paltry annual return of 2.57% between 2015 and 2020, while the US index offered a return of 16.48%. Both the French and German indices offered higher rates of return, in the latter part of the period particularly. This represents a higher opportunity cost for UK investors and may have increased their expectations about the return they require for UK investments.

Greater perceived risk/uncertainty.  Expected rates of return are also determined by perceptions of risk and uncertainty – the compensation investors need to bear the perceived risk associated with an investment. Investors are risk averse. They demand higher expected return as compensation for higher perceived risk. Higher levels of risk aversion increase the expected rate of return and related investment hurdle rates.

There has been much discussion of increased uncertainty and risk aversion among global investors and firms (see the blogs Rising global uncertainty and its effects, World Uncertainty Index, The Chancellor’s fiscal dilemma and Investment set to fall as business is baffled by Trump). The COVID-19 pandemic, inflation shocks, the war in Ukraine, events across the Middle East and the trade policies adopted by the USA in 2025 have combined to produce a very uncertain business environment.

While these have been relatively recent factors influencing world-wide business uncertainty, perceptions of risk and uncertainty concerning the UK economy seem to be longer established. To measure policy-related economic uncertainty in the UK, Baker, Bloom and Davis at www.PolicyUncertainty.com construct an index based on the content analysis of newspaper articles mentioning terms reflecting policy uncertainty.

Figure 2 illustrates the monthly index from 1998 to July 2025. The series is normalised to standard deviation 1 prior to 2011 and then summed across papers, by month. Then, the series is normalised to mean 100 prior to 2011.

Some of the notable spikes in uncertainty in the UK since 2008 have been labelled. Beginning with the global financial crisis, investors and firms became much more uncertain. This was exacerbated by a series of economic shocks that hit the economy, one of which, the narrow vote to leave the European Union in 2016, was specific to the UK. This led to political turmoil and protracted negotiations over the terms of the trade deal after the UK left. This uncertainty has been exacerbated recently by the series of global shocks highlighted above and also the budget uncertainty of Liz Truss’s short-lived premiership and now the growing pressure to reduce government borrowing.

While spikes in uncertainty occurred before the financial crises, the average level of uncertainty, as measured by the index, has been much higher since the crisis. From 1998 to 2008, the average value was 89. Since 2008, the average value has been 163. Since the Brexit vote, the average value has been 185. This indicates a much higher perception of risk and uncertainty over the past 15 year and this translates into higher minimum expected return as compensation. Consequently, this makes many long-term investment projects less viable because of higher hurdle rates. This produces less productive investment in capital, contributing significantly to lower productivity.

Policy proposals

There has been much debate in the UK about promoting greater long-term investment. Reforms have been proposed to improve public participation in long-term investment through the stock market. To boost investment, this would require the investing public to be prepared to accept lower expected returns for a given level of risk or accept higher risk for a given level of returns.

Evidence suggests that the appetite for this may be very low. UK savers tend to favour less risky and more liquid cash deposits. It may be difficult to encourage them to accept higher levels of risk. In any case, even if they did, many may invest outside the UK where the risk-return trade-off is more favourable.

Over the past 10 years, policy uncertainty has played a significant role in deterring investment. So, if there is greater continuity, this may then promote higher levels of investment.

The Labour government has proposed policies which aim to share or reduce the risk/uncertainty around long-term investment for UK businesses. For instance, a National Wealth Fund (NWF) has been established to finance strategic investment in areas such as clean energy, gigafactories and carbon capture. Unfortunately, the Fund is financed by borrowing through financial markets and the amount expected to be committed over the life of the current Parliament is only £29 billion, assuming that private capital matches public commitments in the ratio expected. It is questionable whether the Fund’s commitment will be sufficient to attract private capital.

Alternatively, Invest 2035 is a proposal to create a stable, long-term policy environment for business investment. It aims to establish an Industrial Strategy Council for policy continuity and to tackle issues like improving infrastructure, reducing energy costs and addressing skills gaps. Unfortunately, even if there is some attempt at domestic policy stability, the benefits may be more than offset by perceptions around global uncertainty, which may mean that UK investors’ minimum expected rates of return remain high and long-term investment low for the foreseeable future.

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Questions

  1. Use the marginal efficiency of capital framework to illustrate the ‘lost’ investment spending in the UK due to the investment hurdle rate being higher than the cost of capital.
  2. Explain the arbitrage process which produces the differences in valuations of UK securities and foreign ones due to differences in the expected rate of return.
  3. Sketch an indifference curve for a risk-averse investor, treating expected return and risk as two characteristics of a financial instrument.
  4. How does higher uncertainty affect the slope of an indifference curve for such an investor? How does this affect their investment hurdle rate?
  5. Analyse the extent to which the proposed polices can reduce the investment hurdle rate for UK companies and encourage greater levels of investment.

In a blog in October 2024, we looked at global uncertainty and how it can be captured in a World Uncertainty Index. The blog stated that ‘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’.

Since then, Donald Trump has been elected for a second term and has introduced sweeping tariffs. What is more, the tariffs announced on so-called ‘Liberation Day‘ have not remained fixed, but have fluctuated with negotiations and threatened retaliation. The resulting uncertainty makes it very hard for businesses to plan and many have been unwilling to commit to investment decisions. The uncertainty has been compounded by geopolitical events, such as the continuing war in Ukraine, the war in Gaza and the June 13 Israeli attack on Iran.

The World Uncertainty Index (WUI) tracks uncertainty around the world by applying a form of text mining known as ‘term frequency’ to the country reports produced by the Economist Intelligence Unit (EIU). The words searched for are ‘uncertain’, ‘uncertainty’ and ‘uncertainties’ and the number of times they occur as percentage of the total words is recorded. To produce the WUI this figure is then multiplied by 1m. A higher WUI number indicates a greater level of uncertainty.

The monthly global average WUI is shown in Chart 1 (click here for a PowerPoint). It is based on 71 countries. Since 2008 the WUI has averaged a little over 23 000: i.e. 2.3 per cent of the text in EIU reports contains the word ‘uncertainty’ or a close variant. In May 2025, it was almost 79 000 – the highest since the index was first complied in 2008. The previous highest was in March 2020, at the start of the COVID-19 outbreak, when the index rose to just over 56 000.

The second chart shows the World Trade Uncertainty Index (WTUI), published on the same site as the WUI (click here for a PowerPoint). The method adopted in its construction therefore mirrors that for the WUI but counts the number of times in EIU country reports ‘uncertainty’ is mentioned within proximity to a word related to trade, such as ‘protectionism’, ‘NAFTA’, ‘tariff’, ‘trade’, ‘UNCTAD’ or ‘WTO.’

The chart shows that in May 2025, the WTUI had risen to just over 23 000 – the second highest since December 2019, when President Trump imposed a new round of tariffs on Chinese imports and announced that he would restore steel tariffs on Brazil and Argentina. Since 2008, the WTUI has averaged just 2228.

It remains to be seen whether more stability in trade relations and geopolitics will allow WUI and WUTI to decline once more, or whether greater instability will simply lead to greater uncertainty, with damaging consequences for investment and also for consumption and employment.

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Uncertainty Indices

Questions

  1. Explain what is meant by ‘text mining’. What are its strengths and weaknesses in assessing business, consumer and trade uncertainty?
  2. Explain how the UK Monthly EPU Index is derived.
  3. Why has uncertainty increased so dramatically since the start of 2025?
  4. Compare indices based on text mining with confidence indices.
  5. Plot consumer and business/industry confidence indicators for the past 24 months, using EC data. Do they correspond with the WUI?
  6. How may uncertainty affect consumers’ decisions?