Tag: productivity

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UK enters recession: what does this mean for living standards?

Latest figures from the Office for National Statistics show that the UK was in recession at the end of 2023. The normal definition of recession is two quarters of falling real GDP. This is what happened to the UK in the last two quarters of 2023, with GDP falling by 0.1% in Q3 and 0.3% in Q4. In Q4, output of the service industries fell by 0.2%, production industries by 1.0% and construction by 1.3%.

But how bad is this? What are the implications for living standards? In some respects, the news is not as bad as the term ‘recession’ might suggest. In other respects, it’s worse than the headline figures might imply.

The good news (or not such bad news)

The first thing to note is that other countries too experienced a recession or slowdown in the second half of 2023. So, relative to these countries, the UK is not performing that badly. Japan, for example, also experienced a mild recession; Germany just missed one. These poor economic growth rates were caused largely by higher global energy and food prices and by higher central bank interest rates in response. The good news is that such cost pressures are already easing.

The second piece of good news is that GDP is expected to start growing again (modestly) in 2024. This will be helped by the Bank of England cutting interest rates. The Monetary Policy Committee is expected to do this at its May, June or August meetings provided that inflation falls. Annual CPI inflation was 4% in January – the same as in December. But it is expected to fall quite rapidly over the coming months provided that there are no serious supply-side shocks (e.g. from world political factors).

The third is that the recession is relatively modest compared with ones in the past. In the recession following the financial crisis, real GDP fell by 5.3% in 2009; during the pandemic, GDP fell by 10.7% in 2020. For this reason, some commentators have said that the last two quarters of 2023 represent a mere ‘technical recession’, with the economy expected to grow again in 2024.

Why things may be worse than the headline figures suggest

Real GDP per head
So far we have considered real GDP (i.e. GDP adjusted for inflation). But if changes in GDP are to reflect changes in living standards, we need to consider real GDP per head. Population is rising. This means that the rate of growth in real GDP per head is lower than the rate of growth in real GDP

For 2023 as a whole, while real GDP rose by 0.20%, real GDP per head fell by 0.67%. In the last two quarters of 2023, while real GDP fell by 0.1% and 0.3% respectively, real GDP per head fell by 0.4% and 0.6%, respectively, having already fallen in each of the previous five quarters. Chart 1 shows real GDP growth and real GDP growth per head from 2007 to 2023 (click here for a PowerPoint). As you can see, given population growth, real GDP per head has consistently grown slower than real GDP.

Long-term trends.
If we are assessing the UK’s potential for growth in GDP, rather than the immediate past, it is useful to look at GDP growth over a longer period. Looking at past trend growth rates and explaining them can give us an indication of the likely future path of the growth in GDP – at least in the absence of a significant change in underlying economic factors. Since 2007, the average annual rate of growth of real GDP has been only 1.1% and that of real GDP per head a mere 0.4%.

This compares unfavourably with the period from 1994 to 2007, when the average annual rate of growth of real GDP was 3.0% and that of real GDP per head was 2.5%.

This is illustrated in Chart 2 (click here for a PowerPoint). The chart also projects the growth rate in GDP per head of 2.5% forward from 2007 to 2023. Had this growth rate been achieved since 2007, GDP per head in 2023 would have been 41.4% higher than it actually was.

It is not only the UK that has seen low growth over the past 15 years compared to previous years. It has achieved a similar average annual growth rate over the period to Germany (1.1%), lower rates than the USA (1.8%) and Canada (1.6%), but higher than France (0.9%) and Japan (0.4%).

Low investment
A key determinant of economic growth is investment. Since 2008, the UK has invested an average of 17.3% of GDP. This is the lowest of the G7 countries and compares with 24.9% in Japan, 23.7% in Canada, 23.5% in France, 21.3% in Germany, 20.4% in the USA and 19.1% in Italy. If UK growth is to recover strongly over the longer term, the rate of investment needs to increase, both private and public. Of course, investment has to be productive, as the key underlying determinant of economic growth is the growth in productivity.

Low productivity growth
This is a key issue for the government – how to encourage a growth in productivity. The UK’s record of productivity growth has been poor since 2008. The period from 1996 to 2006 saw an average annual growth in labour productivity of 6.4%. Since then, however, labour productivity has grown by an average annual rate of only 0.3%. This is illustrated in Chart 3 (click here for a PowerPoint). If the pre-2007 rate had continued to the end of 2023, labour productivity would be 189% higher. This would have made GDP per head today substantially higher. If GDP per head is to grow faster, then the underlying issue of a poor growth in labour productivity will need to be addressed.

Inequality and poverty
Then there is the issue of the distribution of national income. The UK has a high level of income inequality. In 2022 (the latest data available), the disposable income of the poorest 20% of households was £13 218; that for the richest 20% was £83 687. The top 1% of income earners’ share of disposable income is just under 9.0%. (Note that disposable income is after income taxes have been deducted and includes cash benefits and is thus more equally distributed than original income.)

The poorest 20% have been hit badly by the cost-of-living crisis, with many having to turn to food banks and not being able to afford to heat their homes adequately. They are also particularly badly affected by the housing crisis, with soaring and increasingly unaffordable rents. Many are facing eviction and others live in poor quality accommodation. Simple growth rates in real GDP do not capture such issues.

Limited scope for growth policies
Fiscal policy has an important role in stimulating growth. Conservatives stress tax cuts as a means of incentivising entrepreneurs and workers. Labour stresses the importance of public investment in infrastructure, health, education and training. Either way, such stimulus policy requires financing.

But, public finances have been under pressure in recent years, especially from COVID support measures. General government gross debt has risen from 27.7% of GDP in 1990/91 to 99.4% in 2022/23. This is illustrated in Chart 4 (click here for a PowerPoint). Although it has fallen from the peak of 107.6% of GDP in 2020/21 (during the COVID pandemic), according to the Office for Budget Responsibility it is set to rise again, peaking at 103.8% in 2026/27. There is thus pressure on the government to reduce public-sector borrowing, not increase it. This makes it difficult to finance public investment or tax cuts.

Measuring living standards

Questions about real GDP have huge political significance. Is the economy in recession? What will happen to growth in GDP over the coming months. Why has growth been sluggish in recent years? The implication is that if GDP rises, living standards will rise; if GDP falls, living standards will fall. But changes in GDP, even if expressed in terms of real GDP and even if the distribution of GDP is taken into account, are only a proxy for living standards. GDP measures the market value of the output of goods and services and, as such, may not necessarily be a good indicator of living standards, let alone well-being.

Produced goods and services that are not part of GDP
The output of some goods and services goes unrecorded. As we note in Economics, 11e (section 15.2), “If you employ a decorator to paint your living room, this will be recorded in the GDP statistics. If, however, you paint the room yourself, it will not. Similarly, if a childminder is employed by parents to look after their children, this childcare will form part of GDP. If, however, a parent stays at home to look after the children, it will not.

The exclusion of these ‘do-it-yourself’ and other home-based activities means that the GDP statistics understate the true level of production in the economy. If over time there is an increase in the amount of do-it-yourself activities that people perform, the figures will also understate the rate of growth of national output.” With many people struggling with the cost of living, such a scenario is quite likely.

There are also activities that go unrecorded in the ‘underground’ or ‘shadow’ economy: unemployed people doing casual jobs for cash in hand that they do not declare to avoid losing benefits; people doing extra work outside their normal job and not declaring the income to evade taxes; builders doing work for cash to save the customer paying VAT.

Externalities
Large amounts of production and consumption involve external costs to the environment and to other people. These externalities are not included in the calculation of GDP.

If external costs increase faster than GDP, then GDP growth will overstate the rise in living standards. If external costs rise more slowly than GDP (or even fall), then GDP growth will understate the rise in living standards. We assume here that living standards include social and environmental benefits and are reduced by social and environmental costs.

Human costs of production
If production increases as a result of people having to work harder or longer hours, its net benefit will be less. Leisure is a desirable good, and so too are pleasant working conditions, but these items are not included in the GDP figures.

The production of certain ‘bads’ leads to an increase in GDP
Some of the undesirable effects of growth may in fact increase GDP! Take the examples of crime, stress-related illness and environmental damage. Faster growth may lead to more of all three. But increased crime leads to more expenditure on security; increased stress leads to more expenditure on health care; and increased environmental damage leads to more expenditure on environmental clean-up. These expenditures add to GDP. Thus, rather than reducing GDP, crime, stress and environmental damage actually increase it.

Alternative approaches to measuring production and income

There have been various attempts to adjust GDP (actual or potential) to make it a better indicator of total production or income or, more generally, of living standards.

Index of Sustainable Economic Welfare (ISEW)
As Case Study 9.20 in the Essentials of Economics (9e) website explains, ISEW starts with consumption, as measured in GDP, and then makes various adjustments to account for factors that GDP ignores. These include:

  • Inequality: the greater the inequality, the more the figure for consumption is reduced. This is based on the assumption of a diminishing marginal utility of income, such that an additional pound is worth less to a rich person than to a poor person.
  • Household production (such as childcare, care for the elderly or infirm, housework and various do-it-yourself activities). These ‘services of household labour’ add to welfare and are thus entered as a positive figure.
  • Defensive expenditures. This is spending to offset the adverse environmental effects of economic growth (e.g. asthma treatment for sufferers whose condition arises from air pollution). Such expenditures are taken out of the calculations.
  • ‘Bads’ (such as commuting costs). The monetary expense entailed is entered as a negative figure (to cancel out its measurement in GDP as a positive figure) and then an additional negative element is included for the stress incurred.
  • Environmental costs. Pollution is entered as a negative figure.
  • Resource depletion and damage. This too is given a negative figure, in just the same way that depreciation of capital is given a negative figure when working out net national income.

Productive Capacities Index (PCI)
In 2023, the United Nations Conference on Trade and Development (UNCTAD) launched a new index to provide a better measure of countries’ economic potential. What the index focuses on is not actual GDP but potential output: in other words, ‘countries’ abilities to produce goods and deliver services’.

The PCI comprises 42 indicators under eight headings: human capital, natural capital, information and communication technology (ICT), structural change (the movement of labour and other productive resources from low-productivity to high-productivity economic activities), transport infrastructure, institutions (political, legal and financial) and the private sector (ease of starting businesses, availability of credit, ease of cross-border trade, etc.). It covers 194 economies since 2000 (currently to 2022). As UNCTAD states, ‘The PCI can help diagnose the areas where countries may be leading or falling behind, spotlighting where policies are working and where corrective efforts are needed.’ Chart 5 shows the PCI for various economies from 2000 to 2022 (click here for a PowerPoint).

The UK, with a PCI of 65.8 in 2022, compares relatively favourably with other developed countries. The USA’s PCI is somewhat higher (69.2), as is The Netherlands’ (69.8); Germany’s is the same (65.8); France’s is somewhat lower (62.8). The world average is 46.8. For developing countries, China is relatively high (60.7); India’s (45.3) is close to the developing country average of 43.4.

Looked at over a longer time period, the UK’s performance is relatively weak. The PCI in 2022 (65.8) was below that in 2006 (66.9) and below the peak of 67.6 in 2018.

GDP and well-being

GDP is often used as a proxy for well-being. If real GDP per head increases, then it is assumed that well-being will increase. In practice, people’s well-being depends on many factors, not just their income, although income is one important element.

The UK Measuring National Well-being (MNW) programme
The MNW programme was established in 2010. This has resulted in Office for National Statistics developing new measures of national well-being. The ONS produces statistical bulletins and datasets with its latest results.

The aim of the programme is to provide a ‘fuller picture’ of how society is doing beyond traditional economic indicators. There are currently 44 indicators. These are designed to describe ‘how we are doing as individuals, as communities and as a nation, and how sustainable this is for the future’. The measures fall within a number of categories, including: personal well-being, relationships, health, what we do, where we live, personal finance, the economy, education and skills, governance and the natural environment.

Conclusions

In the light of the limitations of GDP as a measure of living standards, what can we make of the news that the UK entered recession in the last half of 2023? It does show that the economy is sluggish and that the production of goods and services that are included in the GDP measure declined.

But to get a fuller assessment of the economy, it is important to take a number of other factors into account. If we are to go further and ask what has happened to living standards or to well-being, then we have to look at a range of other factors. If we are to ask what the latest figures tell us about what is likely to happen in the future to production, living standards and well-being, then we will need to look further still.

Articles

Data and Analysis

Questions

  1. Using GDP and other data, summarise the outlook for the UK economy.
  2. Why is GDP so widely used as an indicator of living standards?
  3. Explain the three methods of measuring GDP?
  4. What key contributors to living standards are omitted from GDP?
  5. What are the ONS Satellite Accounts? Are they useful for measuring living standards?
  6. Assess the UK’s economic potential against each of the eight category indices in the Productive Capacities Index.
  7. What is the difference between ‘living standards’ and ‘well-being’?
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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 fiscal arithmetic of sustainable public debt: is the maths getting harder?

The past decade or so has seen large-scale economic turbulence. As we saw in the blog Fiscal impulses, governments have responded with large fiscal interventions. The COVID-19 pandemic, for example, led to a positive fiscal impulse in the UK in 2020, as measured by the change in the structural primary balance, of over 12 per cent of national income.

The scale of these interventions has led to a significant increase in the public-sector debt-to-GDP ratio in many countries. The recent interest rates hikes arising from central banks responding to inflationary pressures have put additional pressure on the financial well-being of governments, not least on the financing of their debt. Here we discuss these pressures in the context of the ‘r – g’ rule of sustainable public debt.

Public-sector debt and borrowing

Chart 1 shows the path of UK public-sector net debt and net borrowing, as percentages of GDP, since 1990. Debt is a stock concept and is the result of accumulated flows of past borrowing. Net debt is simply gross debt less liquid financial assets, which mainly consist of foreign exchange reserves and cash deposits. Net borrowing is the headline measure of the sector’s deficit and is based on when expenditures and receipts (largely taxation) are recorded rather than when cash is actually paid or received. (Click here for a PowerPoint of Chart 1)

Chart 1 shows the impact of the fiscal interventions associated with the global financial crisis and the COVID-19 pandemic, when net borrowing rose to 10 per cent and 15 per cent of GDP respectively. The former contributed to the debt-to-GDP ratio rising from 35.6 per cent in 2007/8 to 81.6 per cent in 2014/15, while the pandemic and subsequent cost-of-living interventions contributed to the ratio rising from 85.2 per cent in 2019/20 to around 98 per cent in 2023/24.

Sustainability of the public finances

The ratcheting up of debt levels affects debt servicing costs and hence the budgetary position of government. Yet the recent increases in interest rates also raise the costs faced by governments in financing future deficits or refinancing existing debts that are due to mature. In addition, a continuation of the low economic growth that has beset the UK economy since the global financial crisis also has implications for the burden imposed on the public sector by its debts, and hence the sustainability of the public finances. After all, low growth has implications for spending commitments, and, of course, the flow of receipts.

The analysis therefore implies that the sustainability of public-sector debt is dependent on at least three factors: existing debt levels, the implied average interest rate facing the public sector on its debts, and the rate of economic growth. These three factors turn out to underpin a well-known rule relating to the fiscal arithmetic of public-sector debt. The rule is sometimes known as the ‘r – g’ rule (i.e. the interest rate minus the growth rate).

Underpinning the fiscal arithmetic that determines the path of public-sector debt is the concept of the ‘primary balance’. This is the difference between the sector’s receipts and its expenditures less its debt interest payments. A primary surplus (a positive primary balance) means that receipts exceed expenditures less debt interest payments, whereas a primary deficit (a negative primary balance) means that receipts fall short. The fiscal arithmetic necessary to prevent the debt-to-GDP ratio rising produces the following stable debt equation or ‘r – g’ rule:

On the left-hand side of the stable debt equation is the required primary surplus (PS) to GDP (Y) ratio. Moving to the right-hand side, the first term is the existing debt-to-GDP ratio (D/Y). The second term ‘r – g’, is the differential between the average implied interest rate the government pays on its debt and the growth rate of the economy. These terms can be expressed in either nominal or real terms as this does not affect the differential.

To illustrate the rule consider a country whose existing debt-to-GDP ratio is 1 (i.e. 100 per cent) and the ‘r – g’ differential is 0.02 (2 percentage points). In this scenario they would need to run a primary surplus to GDP ratio of 0.02 (i.e. 2 percent of GDP).

The ‘r – g‘ differential

The ‘r – g’ differential reflects macroeconomic and financial conditions. The fiscal arithmetic shows that these are important for the dynamics of public-sector debt. The fiscal arithmetic is straightforward when r = g as any primary deficit will cause the debt-to-GDP ratio to rise, while a primary surplus will cause the ratio to fall. The larger is g relative to r the more favourable are the conditions for the path of debt. Importantly, if the differential is negative (r < g), it is possible for the public sector to run a primary deficit, up to the amount that the stable debt equation permits.

Consider Charts 2 and 3 to understand how the ‘r – g’ differential has affected debt sustainability in the UK since 1990. Chart 2 plots the implied yield on 10-year government bonds, alongside the annual rate of nominal growth (click here for a PowerPoint). As John explains in his blog The bond roller coaster, the yield is calculated as the coupon rate that would have to be paid for the market price of a bond to equal its face value. Over the period, the average annual nominal growth rate was 4.5 per cent, while the implied interest rate was almost identical at 4.6 per cent. The average annual rate of CPI inflation over this period was 2.8 per cent.

Chart 3 plots the ‘r – g’ differential which is simply the difference between the two series in Chart 2, along with a 12-month rolling average of the differential to help show better the direction of the differential by smoothing out some of the short-term volatility (click here for a PowerPoint). The differential across the period is a mere 0.1 percentage points implying that macroeconomic and financial conditions have typically been neutral in supporting debt sustainability. However, this does mask some significant changes across the period.

We observe a general downward trend in the ‘r – g’ differential from 1990 up to the time of the global financial crisis. Indeed between 2003 and 2007 we observe a favourable negative differential which helps to support the sustainability of public debt and therefore the well-being of the public finances. This downward trend of the ‘r – g’ differential was interrupted by the financial crisis, driven by a significant contraction in economic activity. This led to a positive spike in the differential of over 7 percentage points.

Yet the negative differential resumed in 2010 and continued up to the pandemic. Again, this is indicative of the macroeconomic and financial environments being supportive of the public finances. It was, however, largely driven by low interest rates rather than by economic growth.

Consequently, the negative ‘r – g’ differential meant that the public sector could continue to run primary deficits during the 2010s, despite the now much higher debt-to-GDP ratio. Yet, weak growth was placing limits on this. Chart 4 indeed shows that primary deficits fell across the decade (click here for a PowerPoint).

The pandemic and beyond

The pandemic saw the ‘r – g’ differential again turn markedly positive, averaging 7 percentage points in the four quarters from Q2 of 2020. While the differential again turned negative, the debt-to-GDP ratio had also increased substantially because of large-scale fiscal interventions. This made the negative differential even more important for the sustainability of the public finances. The question is how long the negative differential can last.

Looking forward, the fiscal arithmetic is indeed uncertain and worryingly is likely to be less favourable. Interest rates have risen and, although inflationary pressures may be easing somewhat, interest rates are likely to remain much higher than during the past decade. Geopolitical tensions and global fragmentation pose future inflationary concerns and a further drag on growth.

As well as the short-term concerns over growth, there remain long-standing issues of low productivity which must be tackled if the growth of the UK economy’s potential output is to be raised. These concerns all point to the important ‘r – g’ differential become increasingly less negative, if not positive. If so the fiscal arithmetic could mean increasingly hard maths for policymakers.

Articles

Data

Questions

  1. What is meant by each of the following terms: (a) net borrowing; (b) primary deficit; (c) net debt?
  2. Explain how the following affect the path of the public-sector debt-to-GDP ratio: (a) interest rates; (b) economic growth; (c) the existing debt-to-GDP ratio.
  3. Which factors during the 2010s were affecting the fiscal arithmetic of public debt positively, and which negatively?
  4. Discuss the prospects for the fiscal arithmetic of public debt in the coming years.
  5. Assume that a country has an existing public-sector debt-to-GDP ratio of 60 percent.
    (a) Using the ‘rule of thumb’ for public debt dynamics, calculate the approximate primary balance it would need to run in the coming year if the expected average real interest rate on the debt were 3 per cent and real economic growth were 2 per cent?
    (b) Repeat (a) but now assume that real economic growth is expected to be 4 per cent.
    (c) Repeat (a) but now assume that the existing public-sector debt-to-GDP ratio is 120 per cent.
    (d) Using your results from (a) to (c) discuss the factors that affect the fiscal arithmetic of the growth of public-sector debt.
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The UK’s poor productivity record

In its latest World Economic Outlook update, the IMF forecasts that the UK in 2023 will be the worst performing economy in the G7. Unlike all the other countries and regions in the report, only the UK economy is set to shrink. UK real GDP is forecast to fall by 0.6% in 2023 (see Figure 1: click here for a PowerPoint). In the USA it is forecast to rise by 1.4%, in Germany by 0.1%, in France by 0.7% and in Japan by 1.8%. GDP in advanced countries as a whole is forecast to grow by 1.2%, while world output is forecast to grow by 2.9%. Developing countries are forecast to grow by 4.0%, with China and India forecast to grow by 5.2% and 6.1%, respectively. And things are not forecast to be a lot better for the UK in 2024, with growth of 0.9% – bottom equal with Japan and Italy.

Low projected growth in the UK in part reflects the tighter fiscal and monetary policies being implemented to curb inflation, which is slow to fall thanks to tight labour markets and persistently higher energy prices. The UK is particularly exposed to high wholesale gas prices, with a larger share of its energy coming from natural gas than most countries.

But the UK’s lower forecast growth relative to other countries reflects a longer-term problem in the UK and that is the slow rate of productivity growth. This is illustrated in Figure 2, which shows output (GDP) per hour worked in major economies, indexed at 100 in 2008 (click here for a PowerPoint). As you can see, the growth in productivity in the UK has lagged behind that of the other economies. The average annual percentage growth in productivity is shown next to each country. The UK’s growth in productivity since 2008 has been a mere 0.3% per annum.

Causes of low productivity/low productivity growth

A major cause of low productivity growth is low levels of investment in physical capital. Figure 3 shows investment (gross capital formation) as a percentage of GDP for the G7 countries from the 2007–8 financial crisis to the year before the pandemic (click here for a PowerPoint). As you can see, the UK performs the worst of the seven countries.

Part of the reason for the low level of private investment is uncertainty. Firms have been discouraged from investing because of a lack of economic growth and fears that this was likely to remain subdued. The problem was compounded by Brexit, with many firms uncertain about their future markets, especially in the EU. COVID affected investment, as it did in all countries, but supply chain problems in the aftermath of COVID have been worse for the UK than many countries. Also, the UK has been particularly exposed to the effects of higher gas prices following the Russian invasion of Ukraine, as a large proportion of electricity is generated from natural gas and natural gas is the major fuel for home heating.

Part of the reason is an environment that is unconducive for investment. Access to finance for investment is more difficult in the UK and more costly than in many countries. The financial system tends to have a short-term focus, with an emphasises on dividends and short-term returns rather than on the long-term gains from investment. This is compounded by physical infrastructure problems with a lack of investment in energy, road and rail and a slow roll out of advances in telecoms.


To help fund investment and drive economic growth, in 2021 the UK government established a government-owned UK Infrastructure Bank. This has access to £22 billion of funds. However, as The Conversation article below points out:

According to a January 2023 report from Westminster’s Public Accounts Committee, 18 months after its launch the bank had only deployed ‘£1 billion of its £22 billion capital to 10 deals’, and had employed just 16 permanent staff ‘against a target of 320’. The committee also said it was ‘not convinced the bank has a strategic view of where it best needs to target its investments’.

Short-termism is dominant in politics, with ministers keen on short-term results in time for the next election, rather than focusing on the long term when they may no longer be in office. When the government is keen to cut taxes and find ways of cutting government expenditure, it is often easier politically to cut capital expenditure rather than current expenditure. The Treasury oversees fiscal policy and its focus tends to be short term. What is needed is a government department where the focus is on the long term.

One problem that has impacted on productivity is the relatively large number of people working for minimum wages or a little above. Low wages discourage firms from making labour-saving investment and thereby increasing labour productivity. It will be interesting to see whether the labour shortages in the UK, resulting from people retiring early post-COVID and EU workers leaving, will encourage firms to make labour-saving investment.

Another issue is company taxation. Until recently, countries have tended to compete corporate taxes down in order to attract inward investment. This was stemmed somewhat by the international agreement at the OECD that Multinational Enterprises (MNEs) will be subject to a minimum 15% corporate tax rate from 2023. The UK is increasing corporation tax from 19% to 25% from April 2023. It remains to be seen what disincentive effect this will have on inward investment. Although the new rate is similar to, or slightly lower, than other major economies, there are some exceptions. Ireland will have a rate of just 15% and is seen as a major alternative to the UK for inward investment, especially with its focus on cheaper green energy. AstraZeneca has just announced that instead of building its new ‘state-of-the-art’ manufacturing plant in England close to its two existing plats in NW England, it will build it in Ireland instead, quoting the UK’s ‘discouraging’ tax rates and price capping for drugs by the NHS.

And it is not just physical investment that affects productivity, it is the quality of labour. Although a higher proportion of young people go to university (close to 50%) than in many other countries, the nature of the skills sets acquired may not be particularly relevant to employers.

What is more, relatively few participate in vocational education and training. Only 32% of 18-year olds have had any vocational training. This compares with other countries, such as Austria, Denmark and Switzerland where the figure is over 65%. Also a greater percentage of firms in other countries, such as Germany, employ people on vocational training schemes.

Another aspect of labour quality is the quality of management. Poor management practices in the UK and inadequate management training and incentives have resulted in a productivity gap with other countries. According to research by Bloom, Sadun & Van Reenen (see linked article below, in particular Figure A5) the UK has an especially large productivity gap with the USA compared with other countries and the highest percentage of this gap of any country accounted for by poor management.

Solutions

Increasing productivity requires a long-term approach by both business and government. Policy should be consistent, with no ‘chopping and changing’. The more that policy is changed, the less certain will business be and the more cautious about investing.

As far a government investment is concerned, capital investment needs to be maintained at a high level if significant improvements are to be made in the infrastructure necessary to support increased growth rates. As far as private investment is concerned, there needs to be a focus on incentives and finance. If education and training are to drive productivity improvements, then there needs to be a focus on the acquisition of transferable skills.

Such policies are not difficult to identify. Carrying them out in a political environment focused on the short term is much more difficult.

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Questions

  1. What features of the UK economic and political environment help to explain its poor productivity growth record?
  2. What are the arguments for and against making higher education more vocational?
  3. Find out what policies have been adopted in a country of your choice to improve productivity. Are there any lessons that the UK could learn from this experience?
  4. How could the UK attract more inward foreign direct investment? Would the outcome be wholly desirable?
  5. What is the relationship between inequality and labour productivity?
  6. What are the arguments for and against encouraging more immigration in the current economic environment?
  7. Could smarter taxes ease the UK’s productivity crisis?