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Manchesterism: will greater devolution boost economic growth and help tackle inequality?


Andy Burnham is set to become UK Prime Minister on 20 July if no-one else stands to replace Keir Starmer. In a speech on 29 June, he outlined his economic vision. Central to this is devolution, where a greater number of economic decisions would be taken locally rather than by central government. This approach has been dubbed ‘Manchesterism’, in reference to his time as Mayor of Greater Manchester from 2017 to earlier this year. Under his mayoralty, Greater Manchester (GM) achieved faster economic growth than other regions or cities in the UK. From 2017 to 2023, GM’s gross value added grew by an average of 6.6% per annum and the city of Manchester’s by 8.4% – the highest of any city in the UK. The UK average was 4.9% and London’s was 4.6%.

The UK, especially England, is one of the least devolved of the OECD countries. One aspect of this is taxation. The chart shows local taxes and, in the case of federal countries, state/regional/provincial taxes too. (Click here for a PowerPoint.)

Only 4.9% of UK tax revenue is in the form of local taxes (council tax and 50% of business rates) and the amount that can be raised in council tax is capped by the central government. The remainder of UK tax revenue goes to central government in the form of income taxes, social security taxes (national insurance), VAT, excise duties, etc. This compares with an average of 7.1% local taxes and 24.5% local plus regional taxes across the 17 OECD countries shown in the chart.

Andy Burnham plans to shift some of the spending and tax-raising powers from Whitehall to metro mayors and local councils. The aim is to stimulate productivity and economic growth at a regional and local level by tailoring support and incentives to local needs and strengths. Local leaders will be best positioned to understand these needs and strengths and will be able to customise spending and support appropriately.

Examples of the types of greater autonomy over decision making would include:

  • Control over adult education budgets to allow them to be tailored to provide training and apprenticeships to meet the skills requirements of existing and emerging industries in the area;
  • Forming partnerships with local universities to support research and development that complements regional economic growth;
  • Providing greater funding for and control over local transport infrastructure, including roads, buses, trams, trains, etc., with local consultation to make them fit for the local population and businesses;
  • Tailoring business incentives to local needs and to the needs of the businesses themselves so as to attract an increase in investment;
  • Greatly expanding council house building, which has virtually dried up in recent years, with mayors and/or local authorities empowered to develop local housing strategies, including affordable housing programmes, and to direct housing investment funding to particular housing developments in areas of greatest need.

Andy Burnham has pledged to stick to the government’s two existing fiscal rules:
a) The Stability Rule (Fiscal Mandate): the current (day-to-day) budget must be in balance or surplus. In other words the provision of salaries, public services, state pensions, welfare, etc. must be covered by government revenues (largely taxation). The government should borrow only to fund long-term investment.
b) The Debt Rule (Stock Mandate): each year, public-sector net financial liabilities (PSNFL) must be forecast by the OBR to be falling as a share of GDP compared to the previous year in three years’ time. This acts as a break on the amount of borrowing for long-term investment.

It is likely, therefore, that there will be little extra government money for investment. Rather, the policy involves a redistribution of public-sector investment from central government to mayoral/local authorities.

In theory, such a policy of devolution need not see a redistribution from richer to poorer regions, but that might be part of the policy when the details are published. The UK has a bigger gap in productivity (GDP per worker) between its capital city and other large cities than in do other countries. Birmingham, Sheffield, Leeds, Newcastle, etc., as well as Cardiff, Glasgow, Edinburgh and Belfast, lag further behind London in output per head and economic growth than do other European countries lag behind their capital city. Thus the gap between Paris and Lyon, Toulouse and Marseille is narrower; as is that between Belin and Munich, Hamburg and Frankfurt. It is a similar picture in Spain and Italy. In the USA, some cities, such as San Francisco, outperform Washington DC and New York. A redistribution of government funding from London to the regions could see their incomes rise faster without having too much impact on London, which would still continue to attract large amounts of private investment.

Overall, there would be little increase in government funding. ‘Manchesterism’ is not, therefore, a demand-side policy. It is a supply-side policy – directing funds to areas where, combined with local incentives and local knowledge, the funding could yield greater returns and thereby increase potential GDP.

But this is not to say that there is no effect on aggregate demand. The hope is that devolution along the lines outlined by Andy Burnham will attract increased private investment, thereby increasing actual GDP as well as further increasing potential GDP.

We wait to see the details over the coming weeks.

Articles

Videos

Data

Questions

  1. Use an aggregate demand and supply diagram (simple or dynamic) to illustrate the effects on real GDP of a successful devolution strategy.
  2. Find out the details of the last Conservative government’s ‘levelling up’ policy. Was it similar in aims to that of ‘Manchesterism’?
  3. How could a policy of devolution as outlined by Andy Burnham affect income distribution within regions?
  4. Find out about the approach to regional policy in the EU. Is it similar to that being advocated by Andy Burnham?
  5. What is meant by ‘regional multipliers’? Why might they differ from the national multiplier?
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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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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.)
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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?