Category: Economics: Ch 10

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Will AI make the world less equal?

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.

Articles

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.
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How to increase productivity – the key to economic growth

The productivity gap between the UK and its main competitors is significant. In 2024, compared to the UK, output per hour worked was 10.0% higher in France, 19.8% higher in Germany and 41.1% higher in the USA. These percentages are in purchasing-power parity terms: in other words, they reflect the purchasing power of the respective currencies – the pound, the euro and the US dollar.

GDP per hour worked (in PPP terms) is normally regarded as the best measure of labour productivity. An alternative measure is GDP per worker, but this does not take into account the length of the working year. Using this measure, the gap with the USA is even higher as workers in the USA work longer hours and have fewer days holiday per year than in the UK.

The productivity gap is not a new phenomenon. It has been substantial and growing over the past 20 years. (The exception was in 2020 during lockdowns when many of the least productive sectors, such as hospitality, were forced to close temporarily.)

The productivity gap is shown in the two figures. Both figures show labour productivity for the UK, France, Germany and the USA from 1995 to 2024.

Figure 1 shows output (GDP) per hour, measured in US dollars in PPP terms.

Figure 2 shows output (GDP) per hour relative to the UK, with the UK set at 100. The gap narrowed somewhat up to the early 2000s, but since then has widened.

Low UK productivity has been a source of concern for UK governments and business for many years. Not only does it constrain the growth in living standards, it also make the UK less attractive as a source of inward investment and less competitive internationally.

Part of the reason for low UK productivity compared to that in other countries is a low level of investment. As a proportion of GDP, the UK has persistently had the lowest, or almost the lowest, level of investment of its major competitors. This is illustrated in Table 1.

It is generally recognised by government, business and economists that if the economy is to be successful, the productivity gap must be closed. But there is no ‘quick fix’. The policies necessary to achieve increased productivity are long term. There is also a recognition that the productivity problem is a multi-faceted one and that to deal with it requires policy initiatives on a broad front: initiatives that encompass institutional changes as well as adjustments in policy.

So what can be done to improve productivity and how can this be achieved at the micro as well as the macro level?

Improving productivity: things that government can do

Encouraging investment. Over the years, UK governments have increased investment allowances, enabling firms to offset the cost of investment against pre-tax profit, thereby reducing their tax liability. For example, in the UK, companies can offset a multiple of research and development costs against corporation tax. The rate of relief for small and medium-sized enterprises (SMEs) allows companies that work in science and technology to deduct an extra 86% of their qualifying expenditure from their trading profit in addition to the normal 100% deduction: i.e. a total of 186% deduction. Meanwhile, since April 2016, larger companies have been able to claim a R&D expenditure credit, initially worth 11 per cent of R&D expenditures, then 12 per cent from 2018 and 13 per cent from 2020. This was then raised to 20 per cent from 2023.

Strengthening competition. A number of studies have revealed that, with increasing market share, business productivity growth slows. As a result, government policy sought to strengthen competition policy. The Competition Act 1998, which came into force in March 2000, and the Enterprise Act of 2002, enhanced the powers of the Office of Fair Trading (OFT) (a predecessor to the Competition and Markets Authority) in respect to dealing with anti-competitive practices. It was given the ability to impose large fines on firms which had been found guilty of exploiting a dominant market position. Today, one of the strategic goals of the Competition and Markets Authority (CMA) is the aim of ‘extending competition frontiers’ in order to improve the way competition works.

Encouraging an enterprise culture. The creation of an enterprise culture is seen as a crucial factor not only to encourage innovation but also to stimulate technological progress. Innovation and technological progress are crucial to sustaining growth and raising living standards. The UK government launched the Small Business Service in April 2000, later renamed Business and Industry. Its role is to co-ordinate small-business policy within government and liaise with business, providing advice and information. However, according to the OECD, there remains considerable scope for increasing the level of government support for entrepreneurship in the UK.

Improving productivity: things that organisations can do

In the podcast from the BBC’s The Bottom Line series, titled ‘Productivity: How Can British Business Work Smarter’ (see link below), Evan Davis and guests discuss what productivity really looks like in practice – from offices and factories, to call centres and operating theatres.’ The episode identifies a number of ways in which labour productivity can be improved. These include:

  • People could work harder;
  • Workers could be better trained and more skilled and thus able to produce more per hour;
  • Capital could be increased so that workers have more equipment or tools to enable them to produce more, or there could be greater automation, releasing labour to work on other tasks;
  • Workplaces could be arranged more efficiently so that less time is spent moving from task to task;
  • Systems could put in place to ensure that tasks are done correctly the first time and that time is not wasted having to repeat them or put them right;
  • Workers could be better incentivised to work efficiently, whether through direct pay or promotion prospects, or by increasing job satisfaction or by management being better attuned to what motivates workers and makes them feel valued;
  • Firms could move to higher-value products, so that workers produce a greater value of output per hour.

The three contributors to the programme discuss various initiatives in their organisations (an electronics manufacturer, NHS foundation trusts and a provider of office services to other organisations).

They also discuss the role that AI plays, or could play, in doing otherwise time-consuming tasks, such as recording and paying invoices and record keeping in offices; writing grants or producing policy documents; analysing X-ray results in hospitals and performing preliminary diagnoses when patients present with various symptoms; recording conversations/consultations and then sorting, summarising and transcribing them; building AI capabilities into machines or robots to enable them to respond to different specifications or circumstances; software development where AI writes the code. Often, there is a shortage of time for workers to do more creative things. AI can help release more time by doing a lot of the mundane tasks or allowing people to do them much quicker.

There are huge possibilities for increasing labour productivity at an organisational level. The successful organisations will be those that can grasp these possibilities – and in many cases they will be incentivised to so so as it will improve their profitability or other outcomes.

Podcast

Articles

Data

Questions

  1. In what different ways can productivity be measured? What is the most appropriate measure for assessing the effect of productivity on (a) GDP and (b) human welfare generally?
  2. Why has the UK had a lower level of labour productivity than France, Germany and the USA for many years? What can UK governments do to help close this gap?
  3. Find out how Japanese labour productivity has compared with that in the UK over the past 30 years and explain your findings.
  4. Research an organisation of your choice to find out ways in which labour productivity could be increased.
  5. Identify various ways in which AI can improve productivity. Will organisations be incentivised to adopt them?
  6. Has Brexit affected UK labour productivity and, if so, how and why?
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Low UK business investment: the problem of high minimum expected rates of return

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.

Articles

Data

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.
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Rising global uncertainty and its effects

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.

Articles

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?
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A four-day week – a solution to sluggish productivity growth? (Updated)

In a blog from March 2023 (reproduced below), we saw how there has been growing pressure around the world for employers to move to a four-day week. Increasing numbers of companies have adopted the model of 80% of the hours for 100% of the pay.

As we see below, the model adopted has varied across companies, depending on what was seen as most suitable for them. Some give everyone Friday off; others let staff choose which day to have off; others let staff work 80% of the hours on a flexible basis. Firms adopting the model have generally found that productivity and revenue have increased, as has employee well-being. To date, over 200 employers in the UK, employing more than 5000 people, have adopted a permanent four-day week.

This concept of 100-80-100, namely 100% of pay for 80% of hours, but 100% of output, has been trialled in several countries. In Germany, after trials over 2024, 73% of the companies involved plan to continue with the new model, with the remaining 27% either making minor tweaks or yet to decide. Generally hourly productivity rose, and in many cases total output also rose. As the fourth article below states:

The primary causal factor for this intriguing revelation was simple – efficiency became the priority. Reports from the trial showed that the frequency and duration of meetings was reduced by 60%, which makes sense to anyone who works in an office – many meetings could have been a simple email. 25% of companies tested introduced new digitised ways of managing their workflow to optimise efficiency.

Original post

In two previous posts, one at the end of 2019 and one in July 2021, we looked at moves around the world to introduce a four-day working week, with no increase in hours on the days worked and no reduction in weekly pay. Firms would gain if increased worker energy and motivation resulted in a gain in output. They would also gain if fewer hours resulted in lower costs.

Workers would be likely to gain from less stress and burnout and a better work–life balance. What is more, firms’ and workers’ carbon footprint could be reduced as less time was spent at work and in commuting.

If the same output could be produced with fewer hours worked, this would represent an increase in labour productivity measured in output per hour.

The UK’s poor productivity record since 2008

Since the financial crisis of 2007–8, the growth in UK productivity has been sluggish. This is illustrated in the chart, which looks at the production industries: i.e. it excludes services, where average productivity growth tends to be slower. The chart has been updated to 2024 Q2 – the latest data available. (Click here for a PowerPoint of the chart.)

Prior to the crisis, from 1998 to 2006, UK productivity in the production industries grew at an annual rate of 6.9%. From 2007 to the start of the pandemic in 2020, the average annual productivity growth rate in these industries was a mere 0.2%.

It grew rapidly for a short time at the start of the pandemic, but this was because many businesses temporarily shut down or went to part-time working, and many of these temporary job cuts were low-wage/low productivity jobs. If you take services, the effect was even stronger as sectors such as hospitality, leisure and retail were particularly affected and labour productivity in these sectors tends to be low. As industries opened up and took on more workers, so average productivity rapidly fell back. Since then productivity has flatlined.

If you project the average productivity growth rate from 1998 to 2007 of 6.9% forwards (see grey dashed line), then by 2024 Q3, output per hour in the production industries would have been 3.26 times higher than it actually was: a gap of 226%. This is a huge productivity gap.

Productivity in the UK is lower than in many other competitor countries. According to the ONS, output per hour in the UK in 2021 was $59.14 in the UK. This compares with an average of $64.93 for the G7 countries, $66.75 in France, £68.30 in Germany, $74.84 in the USA, $84.46 in Norway and $128.21 in Ireland. It is lower, however, in Italy ($54.59), Canada ($53.97) and Japan ($47.28).

As we saw in the blog, The UK’s poor productivity record, low UK productivity is caused by a number of factors, not least the lack of investment in physical capital, both by private companies and in public infrastructure, and the lack of investment in training. Other factors include short-termist attitudes of both politicians and management and generally poor management practices. But one cause is the poor motivation of many workers and the feeling of being overworked. One solution to this is the four-day week.

Latest evidence on the four-day week

Results have just been released of a pilot programme involving 61 companies and non-profit organisations in the UK and nearly 3000 workers. They took part in a six-month trial of a four-day week, with no increase in hours on the days worked and no loss in pay for employees – in other words, 100% of the pay for 80% of the time. The trial was a success, with 91% of organisations planning to continue with the four-day week and a further 4% leaning towards doing so.

The model adopted varied across companies, depending on what was seen as most suitable for them. Some gave everyone Friday off; others let staff choose which day to have off; others let staff work 80% of the hours on a flexible basis.

There was little difference in outcomes across different types of businesses. Compared with the same period last year, revenues rose by an average of 35%; sick days fell by two-thirds and 57% fewer staff left the firms. There were significant increases in well-being, with 39% saying they were less stressed, 40% that they were sleeping better; 75% that they had reduced levels of burnout and 54% that it was easier to achieve a good work–life balance. There were also positive environmental outcomes, with average commuting time falling by half an hour per week.

There is growing pressure around the world for employers to move to a four-day week and this pilot provides evidence that it significantly increases productivity and well-being.

Additional articles

Original set of articles

Questions

  1. What are the possible advantages of moving to a four-day week?
  2. What are the possible disadvantages of moving to a four-day week?
  3. What types of companies or organisations are (a) most likely, (b) least likely to gain from a four-day week?
  4. Why has the UK’s productivity growth been lower than that of many of its major competitors?
  5. Why, if you use a log scale on the vertical axis, is a constant rate of growth shown as a straight line? What would a constant rate of growth line look like if you used a normal arithmetical scale for the vertical axis?
  6. Find out what is meant by the ‘fourth industrial revolution’. Does this hold out the hope of significant productivity improvements in the near future? (See, for example, last link above.)