Tag: innovation

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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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The AI revolution

Artificial intelligence is having a profound effect on economies and society. From production, to services, to healthcare, to pharmaceuticals; to education, to research, to data analysis; to software, to search engines; to planning, to communication, to legal services, to social media – to our everyday lives, AI is transforming the way humans interact. And that transformation is likely to accelerate. But what will be the effects on GDP, on consumption, on jobs, on the distribution of income, and human welfare in general? These are profound questions and ones that economists and other social scientists are pondering. Here we look at some of the issues and possible scenarios.

According to the Merrill/Bank of America article linked below, when asked about the potential for AI, ChatGPT replied:

AI holds immense potential to drive innovation, improve decision-making processes and tackle complex problems across various fields, positively impacting society.

But the magnitude and distribution of the effects on society and economic activity are hard to predict. Perhaps the easiest is the effect on GDP. AI can analyse and interpret data to meet economic goals. It can do this much more extensively and much quicker than using pre-AI software. This will enable higher productivity across a range of manufacturing and service industries. According to the Merrill/Bank of America article, ‘global revenue associated with AI software, hardware, service and sales will likely grow at 19% per year’. With productivity languishing in many countries as they struggle to recover from the pandemic, high inflation and high debt, this massive boost to productivity will be welcome.

But whilst AI may lead to productivity growth, its magnitude is very hard to predict. Both the ‘low-productivity future’ and the ‘high-productivity future’ described in the IMF article linked below are plausible. Productivity growth from AI may be confined to a few sectors, with many workers displaced into jobs where they are less productive. Or, the growth in productivity may affect many sectors, with ‘AI applied to a substantial share of the tasks done by most workers’.

Growing inequality?

Even if AI does massively boost the growth in world GDP, the distribution is likely to be highly uneven, both between countries and within countries. This could widen the gap between rich and poor and create a range of social tensions.

In terms of countries, the main beneficiaries will be developed countries in North America, Europe and Asia and rapidly developing countries, largely in Asia, such as China and India. Poorer developing countries’ access to the fruits of AI will be more limited and they could lose competitive advantage in a number of labour-intensive industries.

Then there is growing inequality between the companies controlling AI systems and other economic actors. Just as companies such as Microsoft, Apple, Google and Meta grew rich as computing, the Internet and social media grew and developed, so these and other companies at the forefront of AI development and supply will grow rich, along with their senior executives. The question then is how much will other companies and individuals benefit. Partly, it will depend on how much production can be adapted and developed in light of the possibilities that AI presents. Partly, it will depend on competition within the AI software market. There is, and will continue to be, a rush to develop and patent software so as to deliver and maintain monopoly profits. It is likely that only a few companies will emerge dominant – a natural oligopoly.

Then there is the likely growth of inequality between individuals. The reason is that AI will have different effects in different parts of the labour market.

The labour market

In some industries, AI will enhance labour productivity. It will be a tool that will be used by workers to improve the service they offer or the items they produce. In other cases, it will replace labour. It will not simply be a tool used by labour, but will do the job itself. Workers will be displaced and structural unemployment is likely to rise. The quicker the displacement process, the more will such unemployment rise. People may be forced to take more menial jobs in the service sector. This, in turn, will drive down the wages in such jobs and employers may find it more convenient to use gig workers than employ workers on full- or part-time contracts with holidays and other rights and benefits.

But the development of AI may also lead to the creation of other high-productivity jobs. As the Goldman Sachs article linked below states:

Jobs displaced by automation have historically been offset by the creation of new jobs, and the emergence of new occupations following technological innovations accounts for the vast majority of long-run employment growth… For example, information-technology innovations introduced new occupations such as webpage designers, software developers and digital marketing professionals. There were also follow-on effects of that job creation, as the boost to aggregate income indirectly drove demand for service sector workers in industries like healthcare, education and food services.

Nevertheless, people could still lose their jobs before being re-employed elsewhere.

The possible rise in structural unemployment raises the question of retraining provision and its funding and whether workers would be required to undertake such retraining. It also raises the question of whether there should be a universal basic income so that the additional income from AI can be spread more widely. This income would be paid in addition to any wages that people earn. But a universal basic income would require finance. How could AI be taxed? What would be the effects on incentives and investment in the AI industry? The Guardian article, linked below, explores some of these issues.

The increased GDP from AI will lead to higher levels of consumption. The resulting increase in demand for labour will go some way to offsetting the effects of workers being displaced by AI. There may be new employment opportunities in the service sector in areas such as sport and recreation, where there is an emphasis on human interaction and where, therefore, humans have an advantage over AI.

Another issue raised is whether people need to work so many hours. Is there an argument for a four-day or even three-day week? We explored these issues in a recent blog in the context of low productivity growth. The arguments become more compelling when productivity growth is high.

Other issues

AI users are not all benign. As we are beginning to see, AI opens the possibility for sophisticated crime, including cyberattacks, fraud and extortion as the technology makes the acquisition and misuse of data, and the development of malware and phishing much easier.

Another set of issues arises in education. What knowledge should students be expected to acquire? Should the focus of education continue to shift towards analytical skills and understanding away from the simple acquisition of knowledge and techniques. This has been a development in recent years and could accelerate. Then there is the question of assessment. Generative AI creates a range of possibilities for plagiarism and other forms of cheating. How should modes of assessment change to reflect this problem? Should there be a greater shift towards exams or towards project work that encourages the use of AI?

Finally, there is the issue of the sort of society we want to achieve. Work is not just about producing goods and services for us as consumers – work is an important part of life. To the extent that AI can enhance working life and take away a lot of routine and boring tasks, then society gains. To the extent, however, that it replaces work that involved judgement and human interaction, then society might lose. More might be produced, but we might be less fulfilled.

Articles

Questions

  1. Which industries are most likely to benefit from the development of AI?
  2. Distinguish between labour-replacing and labour-augmenting technological progress in the context of AI.
  3. How could AI reduce the amount of labour per unit of output and yet result in an increase in employment?
  4. What people are most likely to (a) gain, (b) lose from the increasing use of AI?
  5. Is the distribution of income likely to become more equal or less equal with the development and adoption of AI? Explain.
  6. What policies could governments adopt to spread the gains from AI more equally?
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The engine of global productivity stuck in first gear

According to Christine Lagarde, Managing Director of the IMF, the slow growth in global productivity is acting as a brake on the growth in potential income and is thus holding back the growth in living standards. In a recent speech in Washington she said that:

Over the past decade, there have been sharp slowdowns in measured output per worker and total factor productivity – which can be seen as a measure of innovation. In advanced economies, for example, productivity growth has dropped to 0.3 per cent, down from a pre-crisis average of about 1 per cent. This trend has also affected many emerging and developing countries, including China.

We estimate that, if total factor productivity growth had followed its pre-crisis trend, overall GDP in advanced economies would be about 5 percent higher today. That would be the equivalent of adding another Japan – and more – to the global economy.

So why has productivity growth slowed to well below pre-crisis rates? One reason is an ageing working population, with older workers acquiring new skills less quickly. A second is the slowdown in world trade and, with it, the competitive pressure for firms to invest in the latest technologies.

A third is the continuing effect of the financial crisis, with many highly indebted firms forced to make deep cuts in investment and many others being cautious about innovating. The crisis has dampened risk taking – a key component of innovation.

What is clear, said Lagarde, is that more innovation is needed to restore productivity growth. But markets alone cannot achieve this, as the benefits of invention and innovation are, to some extent, public goods. They have considerable positive externalities.

She thus called on governments to give high priority to stimulating productivity growth and unleashing entrepreneurial energy. There are several things governments can do. These include market-orientated supply-side policies, such as removing unnecessary barriers to competition, driving forward international free trade and cutting red tape. They also include direct intervention through greater investment in education and training, infrastructure and public-sector R&D. They also include giving subsidies and/or tax relief for private-sector R&D.

Banks too have a role in chanelling finance away from low-productivity firms and towards ‘young and vibrant companies’.

It is important to recognise, she concluded, that innovation and structural change can lead to some people losing out, with job losses, low wages and social deprivation. Support should be given to such people through better education, retraining and employment incentives.

Articles

IMF chief warns slowing productivity risks living standards drop Reuters, David Lawder (3/4/17)
Global productivity slowdown risks social turmoil, IMF warns Financial Times, Shawn Donnan (3/4/17)
Global productivity slowdown risks creating instability, warns IMF The Guardian, Katie Allen (3/4/17)
The Guardian view on productivity: Britain must solve the puzzle The Guardian (9/4/17)

Speech
Reinvigorating Productivity Growth IMF Speeches, Christine Lagarde, Managing Director, IMF(3/4/17)

Paper
Gone with the Headwinds: Global Productivity IMF Staff Discussion Note, Gustavo Adler, Romain Duval, Davide Furceri, Sinem Kiliç Çelik, Ksenia Koloskova and Marcos Poplawski-Ribeiro (April 2017)

Questions

  1. What is the relationship between actual and potential economic growth?
  2. Distinguish between labour productivity and total factor productivity.
  3. Why has total factor productivity growth been considerably slower since the financial crisis than before?
  4. Is sustained productivity growth (a) a necessary and/or (b) a sufficient condition for a sustained growth in living standards?
  5. Give some examples of technological developments that could feed through into significant growth in productivity.
  6. What is the relationship between immigration and productivity growth?
  7. What policies would you advocate for increasing productivity? Explain why.
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Up in the cloud

Cloud computing is growing rapidly and has started to dominate many parts of the IT market. Cloud revenues are rising at around 25% per year and, according to Jeremy Duke of Synergy Research Group:

“Major barriers to cloud adoption are now almost a thing of the past, especially on the public-cloud side. Cloud technologies are now generating massive revenues for technology vendors and cloud service providers, and yet there are still many years of strong growth ahead.”

The market leader in cloud services (as opposed to cloud hardware) is Amazon Web Services (AWS), a subsidiary of Amazon. At the end of 2016, it had a market share of around 40%, larger than the next three competitors (Microsoft, Google and IBM), combined. AWS originated cloud computing some 10 years ago. It is set to have generated revenue of $13 billion in 2016.

The cloud computing services market is an oligopoly, with a significant market leader, AWS. But is the competition from other players in the market, including IT giants, such as Google, Microsoft, IBM and Oracle, enough to guarantee that the market stays competitive and that prices will fall as technology improves and costs fall?

Certainly all the major players are investing heavily in new services, better infrastructure and marketing. And they are already established suppliers in other sectors of the IT market. Microsoft and Google, in particular, are strong contenders to AWS. Nevertheless, as the first article states:

Neither Google nor Microsoft have an easy task since AWS will continue to be an innovation machine with a widely recognized brand among the all-important developer community. Both Amazon’s major competitors have an opportunity to solidify themselves as strong alternatives in what is turning into a public cloud oligopoly.

Articles

While Amazon dominates cloud infrastructure, an oligopoly is emerging. Which will buyers bet on? diginomica, Kurt Marko (16/2/17)
Study: AWS has 45% share of public cloud infrastructure market — more than Microsoft, Google, IBM combined GeekWire, Dan Richman (31/10/16)
Cloud computing revenues jumped 25% in 2016, with strong growth ahead, researcher says GeekWire, Dan Richman (4/1/17)

Data

Press releases Synergy Research Group

Questions

  1. Distinguish the different segments of the cloud computing market.
  2. What competitive advantages does AWS have over its major rivals?
  3. What specific advantages does Microsoft have in the cloud computing market?
  4. Is the amount of competition in the cloud computing market enough to prevent the firms from charging excessive prices to their customers? How might you assess what is ‘excessive’?
  5. What barriers to entry are there in the cloud computing market? Should they be a worry for competition authorities?
  6. Are the any network economies in cloud computing? What might they be?
  7. Cloud computing is a rapidly developing industry (for example, the relatively recent development of cloud containers). How does the speed of development impact on competition?
  8. How would market saturation affect competition and the behaviour of the major players?
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Low global growth – the new norm?

In the blog post, Global warning, we looked at the use of unconventional macroeconomic policies to deal with the slow pace of economic growth around the world. One of the articles was by Nouriel Roubini. In the linked article below, he argues that slow economic growth may be the new global norm.

At the centre of the problem is a fall in the rate of potential economic growth. This has been caused by a lack of investment, which has slowed the pace of innovation and the growth in labour productivity.

The lack of investment, in turn, has been caused by a lack of spending by both households and governments. What is the point in investing in new capacity, argue firms, if they already have spare capacity?

Low consumer spending is partly the result of a redistribution of income from low- and middle-income households (who have a high marginal propensity to consume) to high-income households and corporations (who have a low mpc). Low spending is also the result of both consumers and governments attempting to reduce their levels of debt by cutting back spending.

Low growth leads to hysteresis – the process whereby low actual growth leads to low potential growth. The reason is that the unemployed become deskilled and the lack of investment by firms reduces the innovation that is necessary to embed new technologies.

Read Roubini’s analysis and consider the policy implications.

Article

Has the global economic growth malaise become the ‘new normal’? The Guardian, Nouriel Roubini (2/5/16)

Questions

  1. Explain what is meant by ‘hysteresis’ and how the concept is relevant in explaining low global economic growth.
  2. Why has there been a reduction in the marginal propensity to consume in recent years? What is the implication of this for the multiplier and economic recovery?
  3. Explain what Roubini means by ‘a painful de-leveraging process’. What are the implications of this process?
  4. How important are structural reforms and what forms could these take? Why has there been a reluctance for governments to institute such reforms?
  5. ‘Asymmetric adjustment between debtor and creditor economies has also undermined growth.’ Explain what Roubini means by this.
  6. Why are governments reluctant to use fiscal policy to boost both actual and potential economic growth?
  7. What feasible policy measures could be taken to boost actual and potential economic growth?