Category: Essential Economics for Business: Ch 06

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Rival bids for Warner Bros. face competition scrutiny

The television streaming market is currently attracting considerable attention from policy makers. This follows Warner Bros. accepting Netflix’s offer to buy part of the company for $72bn. To understand how this deal came about and why there is policy concern, we need to go back a few years.

The media and entertainment conglomerate Warner Bros. Discovery (WBD) was created in 2022 when AT&T sold Warner Bros to Discovery.1 However, in June 2025 the company announced that it would split the business into two parts. One would be (a) the studio for TV and movie production, where for example the Harry Potter franchises were made, and (b) the TV streaming business, home to for example the hit TV series Succession. The other, the more traditional and declining TV networks, including channels such as CNN, Discovery and TNT Sports, would form a new company called Discovery Global. David Zaslav, WBD President and Chief Executive stated that:

We are empowering these iconic brands with the sharper focus and strategic flexibility they need to compete most effectively in today’s evolving media landscape.2

Shortly afterwards, rival media and entertainment conglomerate, Paramount Skydance, made a series of bids to purchase the entire WBD business. But these were rejected by the WBD board. Despite this, in October 2025 WBD made public that it was open to a sale and had received unsolicited interest from several companies. It was believed that this included offers from Comcast and Netflix.

Recent developments

In December 2025, Netflix announced that it had agreed a deal with WBD to buy its studio and streaming service business, including its back catalogue of shows. The deal is planned to be put to WBD shareholders in the next few months.3 Netflix has over 300m subscribers across the globe and streams popular shows, such as Stranger Things and Squid Games.

Despite this accepted offer, Paramount has subsequently pursued a hostile takeover of WBD by going straight to its shareholders. In addition, Paramount launched a lawsuit to get further information on how Netflix was chosen as the buyer and to provide WBD shareholders with information on the value of the TV network business that WBD was selling. This, however, was quickly thrown out of the courts.

Over time, Netflix and Paramount have tinkered with their bids to make them more attractive to WBD. Whilst Paramount’s bid was all cash, originally Netflix was offering a mixture of cash and shares. However, in January, it switched this to an all-cash offer. In February, Paramount made clear that if WBD instead accepted its offer, it would pay the $2.8bn termination fee that would be owed to Netflix.4 Furthermore, from early 2027 Paramount would pay WBD shareholders payments of $650m per quarter, known as ticking fees, if combining WBD and Paramount faced regulatory delay.

In mid-February 2026, it emerged that, following a waiver from Netflix, WBD had reopened talks with Paramount. Paramount was given a week to make its offer. Then, under the agreed deal, Netflix would have the right to adjust its bid. This is an attempt by WBD to end the hostile bidding war Paramount is pursuing and to provide clarity for its shareholders. WBD has reiterated that it will:

continue to recommend and remain fully committed to our transaction with Netflix. [However], we welcome the opportunity to engage with you and expeditiously determine whether Paramount Skydance can deliver an actionable, binding proposal that provides superior value.5

The insertion of the ticking fees by Paramount is in response to the substantial attention competition authorities across the globe are paying to the acquisition of WBD. The deal is being investigated by the US Department of Justice and, in early February, Netflix was questioned by the US Senate Antitrust Sub-committee. During this hearing, one of the Senators expressed his anger with the country’s competition laws and raised concerns that the deal would result in Netflix getting:

more power over consumers and leaving fewer alternatives and streaming platforms.6

While Paramount did not attend this hearing, it is believed that it has raised concerns about the Netflix-WBD deal to regulators. Netflix co-CEO, Ted Sarandos, has also met with Donald Trump to discuss the deal. However, Trump subsequently stated that the deal ‘could be a problem’.7

The EU and UK markets

Furthermore, whilst all the companies involved are American, both the mergers with Netflix and Paramount are being investigated by the European Commission as markets in Europe would be affected.

In the UK, a group of politicians and former policymakers, have written to the Competition and Markets Authority urging it to conduct a full investigation of the Netflix-WBD merger. The letter argues that the merger could have:

damaging consequences for consumers, the UK’s world-leading creative industries and the UK cinema industry.

and that:

At a time when the British consumer can ill-afford more price increases, Netflix would possess an unprecedented ability to raise prices to access television and films.8

The letter comes at a time when pressure is being placed on the CMA to adopt a generally more business-friendly approach.

The impact of the merger on the UK market is particularly complicated since Warner Bros.’ streaming service, HBO Max, is only due to launch in the UK in March 2026. This is still the plan, with WBD’s head of global streaming, Jean-Briac Perette acknowledging that:

We are likely the last scaled global streamer to come to market. We’ve tried to learn from the rest. We’re a complementary and distinct service to the more volume-driven or basic cable-like streamers in the market. More is not better. Better is better.9

An alternative route to regulatory approval

An easier route to regulatory approval may well be instrumental in allowing Netflix or Paramount to win the battle for WBD. Netflix stresses that the deal will create economic growth and jobs. Netflix’s Sarandos highlighted that:

This is not a typical media merger where you end up with what’s called the Noah’s Ark problem — two of everything. We are buying a company that has assets that we do not, and we will keep investing in those.10

The problem of economic power

In contrast, critics argue that either of the deals would create a new company with too much power. However, given the nature of the firms involved, the competition issues will be fundamentally different between the two deals.

The Paramount deal would primarily reduce the number of studios in the market. This could provide the new merged studio with more bargaining power over distributors, advertisers and creators. Ultimately, this could negatively impact on the final product that consumers watch in the cinema and on television.

The Netflix deal on the other hand would impact directly on the streaming market. In the USA, 80% of consumers have both Netflix and HBO Max.11 After the merger, consumers would have less choice of competing services and Netflix-HBO Max combined may well have an incentive to raise its subscription prices.

In the UK, there are currently three leading streaming services: Netflix, Amazon Prime and Disney+, each with around 23% of the market.12 The merger with WBD could allow Netflix to become the clear market leader.

Concerns about YouTube

When examining streaming markets in all countries, an important factor will be whether to include YouTube in the market. Netflix certainly argues that it is a key competitor, at the hearing Sarandos stated that:

we are competing for the same content, we are competing for the same viewers, we are competing often for the same ad dollars. YouTube is not just cat videos anymore. YouTube is TV.13

If YouTube is included, in the USA it would be the market leader with 13%, ahead of Netflix on 9%. However, the competition authorities may conclude that YouTube’s product and business model is sufficiently different and so not include it in the streaming market.14

The issue of cinemas

A second concern in the Netflix deal will be the Warner Bros.’ studio content that Netflix would own. The merged business may have an incentive to discontinue, raise the price or reduce the quality of the studio output that it supplies to cinemas. Thus, the competition authorities’ investigations will also pay close attention to the impact on the cinema market.

In line with these arguments, the Hollywood screenwriters’ union, the Writers Guild of America, has indicated that the Netflix-WMD deal should be stopped and filmmakers are clearly concerned about Netflix prioritising streaming.15
 
 
The competition authorities may well consider imposing remedies before they are willing to allow either deal to go ahead. With this in mind, it is interesting that Netflix has already made clear that it will continue the 45-day exclusive window that Warner Bros. provides cinemas to show its films.

It will be fascinating to see how the competing bids play out and how the competition regulators view them.

References

  1. AT&T agrees deal to combine WarnerMedia with Discovery

    2. The Guardian, Mark Sweney (16/5/21)

  2. HBO and CNN owner to split streaming and cable businesses

    3. BBC News, Adam Hancock (10/6/25)

  3. Netflix’s co-CEO went to an antitrust hearing and a culture war broke out

    4. NBC News, Saba Hamedy (3/2/26)

  4. Warner Bros gives Paramount seven days to make ‘best and final’ offer

    5. The Guardian, Mark Sweney (17/2/26)

  5. ibid.

  6. NBC News, op. cit.

  7. Trump says $72bn Netflix-Warner Bros deal ‘could be a problem’

    8. BBC News, Osmond Chia (8/12/25)

  8. UK politicians call for competition review of Netflix bid for Warner Bros

    9. Financial Times (26/1/26)

  9. Warner streaming boss defends HBO Max UK launch ahead of Netflix takeover

    10. Financial Times (9/2/26)

  10. NBC News, op. cit.

  11. Netflix and Warner Bros struggle to defend merger

    12. BBC News, Danielle Kaye (3/2/26)

  12. Netflix, Disney+, Prime: Streaming platform market share report UK 2025
    InsiderMedia, Jennifer O’Keeffe (2/12/25)

  13. BBC News, Danielle Kaye op. cit.

  14. Paramount sweetens Warner Bros bid with offer to pay Netflix break-up cost, other fees

    15. Reuters, Harshita Mary Varghese and Aditya Soni (11/2/26)

  15. In a takeover of Warner Bros., Netflix makes a play for 21st century Hollywood’s throne

    16. NBC News, Daniel Arkin (5/12/25)

Articles

Questions

  1. What are the similarities and differences between Netflix’ and YouTube’s business models? How close substitutes do you think they are?
  2. Do you think cinemas are a closer or more distant substitute to Netflix than YouTube?
  3. Which deal do you think raises the most competition concerns? What might be a possible remedy that could alleviate these concerns?
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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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The 4Ps approach to merger policy in the UK

The approach towards mergers remains the most controversial area of competition policy. Some argue that policy makers in both the UK and EU have been too easily persuaded by the arguments put forward by firms and so have allowed too many mergers to proceed. Others claim that the opposite is true and that merger policy has prohibited mergers that should have been allowed to proceed. This, then, has a negative impact on investment, innovation, productivity and growth.

In recent years there has been more specific criticism of merger policy in the UK. The government has indicated that it wants the Competition and Markets Authority (CMA) to be less interventionist and take a more pro-growth approach.

In February 2025, in response to this criticism, the CMA launched its new ‘4 Ps’ approach to merger policy: Pace, Predictability, Proportionality and Process. Various changes to the investigation process have been proposed in the past 12 months using this framework.

Pace. The time taken by the CMA to initially assess a merger before deciding whether a Phase 1 investigation is necessary (i.e. the pre-notification procedure) was reduced from 65 to 40 working days. Also, the target to complete straightforward Phase 1 investigations was reduced from 35 to 25 days.

Predictability. The proposed merger guidelines, published in October 2025, provide more detail on (a) what criteria will be used to measure market shares when applying the ‘share of supply test’ (this is where the combined UK market share of two merging businesses is at least 25%, provided one business has a UK turnover of at least £10 million), and (b) the factors that are likely to lead to the competition authorities concluding that one business has gained ‘material influence over another’. Businesses had complained that there was too much uncertainty about the way the share of supply test and material influence were applied. The CMA is also considering greater alignment with other international regulators over decision making rather than its previous policy of acting independently. All these measures should increase the predictability of the investigation process.

Proportionality. Proportionality refers to the objective of addressing any competition issues in merger cases in a way that places the minimum burden on the businesses involved. To improve proportionality, the CMA has indicated that in future cases it will be more willing to use behavioural remedies – requiring firms to take or desist from certain actions. New draft guidelines identify more situations where the use of behavioural remedies may be appropriate. However, they also show that the CMA still views structural remedies (e.g. preventing the merger or requiring firms to demerge or to sell certain assets) as more effective in many situations. Another important measure to improve proportionality is the introduction of a new ‘wait and see’ approach to global mergers. The CMA will now wait to see if the actions taken by other competition authorities in global cases address any concerns in the UK market before deciding whether to launch a review.

Process. To improve the process, the CMA has announced plans to engage with businesses at a much earlier point in the process. For example, it has pledged to share its provisional thinking in the early stages of an investigation by implementing new ‘teach-in’ sessions and having more regular update meetings. Much earlier meetings that focus on possible remedies will also take place. This may make it possible for the CMA to assess the suitability of more complex remedies during a Phase 1 investigation rather than having to wait for a longer and more costly Phase 2 review. Phase 2 reviews will also no longer be managed by panels of independent experts. This role will now be carried out by the internal CMA board.

Some critics argue that the CMA has not fully considered the potential benefits of mergers in many cases. For example, a merger could (a) have procompetitive effects, known as rivalry enhancing efficiencies (REEs) and/or (b) benefits for consumers outside of the relevant market, known as relevant customer benefits (RCBs). In response to this criticism, the CMA is currently reassessing its approach to including evidence on REEs and RCBs.

The CMA is still currently consulting with interested parties about many of these proposed changes. It will be interesting to see what final decisions are made in the next couple of years.

Articles

CMA documentation

Questions

  1. Of all the mergers considered by the CMA in 2024/25, find out what percentage were formally investigated. How many were blocked from taking place? Do you believe that this indicates that merger policy is too weak or too strong?
  2. What three criteria must be met for a business arrangement to be classed as a ‘relevant merger situation’ by the CMA?
  3. Identify some different methods that one business could use to gain material influence over the way another company operates.
  4. Outline the ‘turnover test’, the ‘share of supply test’ and the ‘hybrid test’.
  5. Discuss the potential advantages of using behavioural remedies as opposed to structural remedies in merger cases. Why has the CMA still preferred the use of structural remedies in most situations?
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Age-old problems but new technology: developments in collusion in the algorithmic era

In my previous blog post on this site, I examined how AI-powered pricing tools can act as a ‘double-edged sword’: offering efficiency gains, while also creating opportunities for collusion. I referred to one of the early examples of this, which was the case involving Trod Ltd and GB Eye, where two online poster and frame sellers on Amazon used pricing algorithms to monitor and adjust their prices. However, in this instance there was also an explicit agreement between the firms. As some commentators put it, it was ‘old wine in new bottles‘, meaning a fairly conventional cartel that was simply facilitated through digital tools.

Since then, algorithms have increasingly become part of everyday life and are now embedded in routine business practice.

Some of the effects may have a positive effect on competition. For example, algorithms can help to lower barriers to entry. In some markets, incumbents benefit from long-standing experience, while new firms face significant learning costs and are at a disadvantage. By reducing these learning costs and supporting entry, algorithms could contribute to making collusion harder to sustain.

On the other hand, algorithms could increase the likelihood of collusion. For example, individual algorithms used by competing firms may respond to market conditions in predictable ways, making it easier for firms to collude tacitly over time.

Algorithms can also improve the ability of firms to monitor each other’s prices. This is particularly relevant for multi-product firms. Traditionally, we might expect these markets to be less prone to collusion because co-ordinating across many products is complex. AI can overcome this complexity. In the Sainsbury’s/Asda merger case, for example, the Competition and Markets Authority suggested that the main barrier to reaching and monitoring a pricing agreement was the complexity of pricing across such a wide range of products. However, the CMA also suggested that technological advances could increase its ability to do so in the future.

The ‘hub-and-spoke’ model

One of the other growing concerns is the ability of AI pricing algorithms to facilitate collusion by acting as a ‘hub’ in a ‘hub-and-spoke’ arrangement. In this type of collusion, competing firms (the ‘spokes’) need not communicate directly with one another. Instead, the ‘hub’ helps them to co-ordinate their actions.

While there have been only limited examples of an AI pricing algorithm acting as a hub in practice, what once seemed to be a largely theoretical concern has now become a live enforcement issue.

A very recent example is the RealPage case in the United States. The Department of Justice (DOJ) filed an antitrust lawsuit against RealPage Inc. in August 2024, alleging that RealPage, acting as the ‘hub’, facilitated collusion between landlords (the ‘spokes’).

RealPage provided pricing software to numerous landlords, including the largest landlord in the USA, which manages around 950 000 rental units across the country. These landlords would normally compete independently in setting rental prices, discounts and lease terms to win consumers. However, by feeding competitively sensitive information that would not usually be shared between rivals into RealPage’s system, the software generated pricing recommendations that, according to the DOJ, led to co-ordinated rent increases across competing apartment complexes.

In the RealPage case, the authorities reported that they had access to internal documents and statements from the parties involved, which helped support their allegations. These included references within RealPage to helping landlords ‘avoid the race to the bottom’ and comments from a landlord describing the software as ‘classic price fixing’.

Evidence in these cases really matters because the standard of proof required to establish a hub-and-spoke arrangement is much higher than for traditional cases of explicit collusion. This is because it can be difficult to distinguish between legitimate and anti-competitive communication between retailers and suppliers. Also, proving ‘anti-competitive intent’ is inherently challenging.

Other competition authorities around the world are also turning their attention to these issues. For example, the European Commission recently announced that a number of investigations into algorithmic pricing are underway, signalling a clear shift toward more active scrutiny. As technology continues to advance, it is clear that algorithmic pricing will remain an area where both firms and authorities must move and adapt quickly.

Articles

Questions

  1. In what ways does the RealPage case differ from the earlier Trod Ltd and GB Eye Ltd case? Consider the roles played by the firms, the nature of the alleged co-ordination, and the extent to which pricing algorithms were used to facilitate the conduct.
  2. How might the use of pricing algorithms affect the likelihood of firms colluding, either explicitly or tacitly? Consider ways that algorithms may make collusion easier to sustain but also ways in which they may reduce its likelihood.
  3. Should firms be held liable for anti-competitive outcomes produced by algorithms that ‘self-learn’, even if they did not intend those outcomes? Explain why or why not.
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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?