Category: Essential Economics for Business 7e and 6e

You may have recently noticed construction workers from different businesses digging up the roads/pavements near where you live. You may also have noticed them laying fibre optic cables. Why has this been happening? Does it make economic sense for different companies to dig up the same stretch of pavement and lay similar cables next to one another?

For many years the UK had one national fixed communication network that was owned by British Telecom (BT) – the traditional phone landline made from copper wire. This is now operated by OpenReach – part of the BT group but a legally separate division. In addition to this national infrastructure, Virgin Media (formed in 2007 from the merged cable operators, Telewest and NTL) has gradually built up a rival fixed broadband network that now covers just over 50 per cent of the country.

Although customers have only had very limited choice over which fixed communication network to use, they have had far greater choice over which Internet service provider (ISP) to sign up for. This has been possible as the industry regulator, Ofcom, forces OpenReach to provide rival ISPs such as Sky Broadband, TalkTalk and Zen with access to its network.

Expansion of the fibre optic network

Recent government policy has tried to encourage and incentivise the replacement of the copper wire network with one that is fully fibre. This is often referred to as Fibre to the Premises (FTTP) or Fibre to the Home (FTTH). A fixed network of fully fibre broadband enables much faster download speeds and many argue that it is vital for the future competitiveness of the UK economy.

Replacing the existing fixed communication network with fibre optic cables is expensive. It can involve major civil works: i.e. the digging up of roads and pavements to install new ducts to lay the fibre optic cables inside.

Over a hundred companies, that are not part of either OpenReach or Virgin Media O2 (the parent company of Virgin Media), have recently been digging up pavements/roads and laying new fibre optic cables. Known as alternative network providers (altnets) or independent networks, these businesses vary in size, with many of them securing large loans from banks and private investors. By the middle of 2023, 2.5 million premises in the UK had access to at least two or more of these independent networks.

After a slow initial response to the altnets, OpenReach has recently responded by rapidly installing FTTP. The business is currently building 62 000 connections every week and plans to have 25 million premises connected by the end of 2026. In July 2022, Virgin Media O2 announced that it was establishing a new joint venture with InfraVia Capital Partners. Called Nexfibre, this business aims to connect 5 million premises to FTTP by 2026.

Is the fibre optic network a natural monopoly?

Some people argue that the fixed communication network is an example of a natural monopoly – an industry where a single firm can supply the whole market at a lower average cost than two or more firms. To what extent is this true?

An industry is a natural monopoly where the minimum efficient scale of production (MES) is larger than the market demand for the good/service. This is more likely to occur where there are significant economies of scale. Digging up roads/pavements, installing new ducts and laying fibre optic cable are clear examples of fixed costs. Once the network is built, the marginal cost of supplying customers is relatively small. Therefore, this industry has significant economies of scale and a relatively large MES. This has led many people to argue that building rival fixed communication networks is wasteful duplication and will lead to higher costs and prices.

However, when judging if a sector is a natural monopoly, it is always important to remember that a comparison needs to be made between the MES and the size of the market. An industry could have significant economies of scale, but not be an example of a natural monopoly if the market demand is significantly larger than the MES.

In the case of the fixed communication network, the size of the market will vary significantly between different regions of the country. In densely populated urban areas, such as large towns and cities, the demand for services provided via these networks is likely to be relatively large. Therefore, the MES could be smaller than the size of the market, making competition between network suppliers both possible and desirable. For example, competition may incentivise firms to innovate, become more efficient and reduce costs.

Research undertaken for the government by the consultancy business, Frontier Economics, found that at least a third of UK households live in areas where competition between three or more different networks is economically desirable.

By contrast, in more sparsely populated rural areas, demand for the services provided by these networks will be smaller. The fixed costs per household of installing the network over longer distances will also be larger. Therefore, the MES is more likely to be greater than the size of the market.

The same research undertaken by Frontier Economics found that around 10 per cent of households live in areas where the fixed communication network is a natural monopoly. The demand and cost conditions for another 10 per cent of households meant it is not commercially viable to have any suppliers.

Therefore, policies towards the promotion of competition, regulation, and government support for the fixed communication network might have to be adjusted depending on the specific demand and cost conditions in a particular region.

Articles

Review

Questions

  1. Explain the difference between fixed and wireless communication networks.
  2. Draw a diagram to illustrate a profit-maximising natural monopoly. Outline some of the implications for allocative efficiency.
  3. Discuss some of the issues with regulating natural monopolies, paying particular attention to price regulation.
  4. The term ‘overbuild’ is often used to describe a situation where more than one fibre broadband network is being constructed in the same place. Some people argue that incumbent network suppliers deliberately choose to use this term to imply that the outcome is harmful for society. Discuss this argument.
  5. An important part of government policy in this sector has been the Duct and Pole Access Strategy (DPA). Illustrate the impact of this strategy on the average cost curve and the minimum efficient scale of production for fibre broadband networks.
  6. Draw a diagram to illustrate a region where (a) it is economically viable to have two or more fibre optic broadband network suppliers and (b) where it is commercially unviable to have any broadband network suppliers without government support.
  7. Some people argue that network competition provides strong incentives for firms to innovate, to become more efficient and reduce costs. Draw a diagram to illustrate this argument.
  8. Explain why many ‘altnets’ are so opposed to OpenReach’s new ‘Equinox 2’ pricing scheme for its fibre network.


Politicians, business leaders, climate scientists, interest groups and journalists from across the world have been meeting in Dubai at the COP28 climate summit (the 28th annual meeting of the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC)). The meeting comes at a time when various climate tipping points are being reached or approached – some bad, but some good. Understanding these tipping points and their implications for society and policy requires understanding not only the science, but also the various economic incentives affecting individuals, businesses, politicians and societies.

Tipping points

A recent report (see first reference in articles section below) identified various climate tipping points. These are when global temperatures rise to a point where various domino effects occur. These are adverse changes to the environment that gather pace and have major effects on ecosystems and the ability to grow food and support populations. These, in turn, will have large effects on economies, migration and political stability.

According to the report, five tipping points are imminent with the current degree of global warming (1.2oC). These are:

  • Melting of the Greenland ice sheet;
  • Melting of the West Antarctic ice sheet;
  • Death of warm-water coral reefs;
  • Collapse of the North Atlantic Subpolar Gyre circulation, which helps to drive the warm current that benefits Western Europe;
  • Widespread rapid thawing of permafrost, where tundra without snow cover rapidly absorbs heat and releases methane (a much more powerful source of global warming than CO2).

With global warming of 1.5oC, three more tipping points are likely: the destruction of seagrass meadows, mangrove swamps and the southern part of the boreal forests that cover much of northern Eurasia. As the temperature warms further, other tipping points can interact in ways that drive one another, resulting in tipping ‘cascades’.

But the report also strikes an optimistic note, arguing that positive tipping points are also possible, which will help to slow global warming in the near future and possibly reverse it further in the future.


The most obvious one is in renewable energy. Renewable power generation in many countries is now cheaper than generation from fossil fuels. Indeed, in 2022, over 80% of new electricity generation was from solar and wind. And as it becomes cheaper, so this will drive investment in new renewable plants, including in small-scale production suitable for use in developing countries in parts not connected to a grid. In the vehicle sector, improved battery technology, the growth in charging infrastructure and cheaper renewable sources of electricity are creating a tipping point in EV take-up.

Positive tipping points can take place as a result of changing attitudes, such as moving away from a meat-intensive diet, avoiding food waste, greater use of recycling and a growth in second-hand markets.

But these positive tipping points are so far not strong enough or quick enough. Part of the problem is with economic incentives in market systems and part is with political systems.

Market failures

Economic decisions around the world of both individuals and firms are made largely within a market environment. But the market fails to take into account the full climate costs and benefits of such decisions. There are various reasons why.

Externalities. Both the production and consumption of many goods, especially energy and transport, but also much of agriculture and manufacturing, involve the production of CO2. But the costs of the resulting global warming are not born directly by the producer or consumer. Instead they are external costs born by society worldwide – with some countries and individuals bearing a higher cost than others. The result is an overproduction or consumption of such goods from the point of view of the world.

The environment as a common resource. The air, the seas and many other parts of the environment are not privately owned. They are a global ‘commons’. As such, it is extremely difficult to exclude non-payers from consuming the benefits they provide. Because of this property of ‘non-excludability’, it is often possible to consume the benefits of the environment at a zero price. If the price of any good or service to the user is zero, there is no incentive to economise on its use. In the case of the atmosphere as a ‘dump’ for greenhouse gases, this results in its overuse. Many parts of the environment, however, including the atmosphere, are scarce: there is rivalry in their use. As people increase their use of the atmosphere as a dump for carbon, so the resulting global warming adversely affects the lives of others. This is an example of the tragedy of the commons – where a free resource (such as common land) is overused.

Inter-generational problems. The effect of the growth in carbon emissions is long term, whereas the benefits are immediate. Thus consumers and firms are frequently prepared to continue with various practices, such as driving, flying and using fossil fuels for production, and leave future generations to worry about their environmental consequences. The problem, then, is a reflection of the importance that people attach to the present relative to the future.

Ignorance. People may be contributing to global warming without realising it. They may be unaware of which of the goods they buy involve the release of carbon in their production or how much carbon they release when consumed.

Political failures

Governments, whether democratic or dictatorships, face incentives not to reduce carbon emissions – or to minimise their reduction, especially if they are oil producing countries. Reducing carbon involves short-term costs to consumers and this can make them unpopular. It could cost them the next election or, in the case of dictatorships, make them vulnerable to overthrow. What is more, the oil, coal and gas industries have a vested interest in continuing the use of fossil fuels. Such industries wield considerable political power.

Even if governments want the world to reduce carbon emissions, they would rather that the cost of doing so is born less by their own country and more by other countries. This creates a prisoner’s dilemma, where the optimum may be for a large global reduction in carbon emissions, but the optimum is not achieved because countries individually are only prepared to reduce a little, expecting other countries to reduce more. Getting a deal that is deemed ‘fair’ by all countries is very difficult. An example is where developing countries, may feel that it is fair that the bulk of any cuts, if not all of them, should be made by developed countries, while developed countries feel that fixed percentage cuts should be made by all countries.

Policy options

If the goal is to tackle climate change, then the means is to reduce the amount of carbon in the atmosphere (or at the least to stop its increase – the net zero target). There are two possibilities here. The first is to reduce the amount of carbon emissions. The second is to use carbon capture and storage or carbon sequestration (e.g. through increased forestation).

In terms of reducing carbon emissions, the key is reducing the consumption of carbon-producing activities and products that involve emissions in their production. This can be achieved through taxes on such products and/or subsidies on green alternatives (see the blog ‘Are carbon taxes a solution to the climate emergency?‘). Alternatively carbon-intensive consumption can be banned or phased out by law. For example, the purchase of new petrol or diesel cars cold be banned beyond a certain date. Or some combination of taxation and regulation can be used, such as in a cap-and-trade system – for example, the EU Emissions Trading System (EU ETS) (see the blog ‘Carbon pricing in the UK‘). Then there is government investment in zero carbon technologies and infrastructure (e.g. electrifying railways). In practice, a range of policy instruments are needed (see the blog ‘Tackling climate change: “Everything, everywhere, all at once”‘).

With carbon capture, again, solutions can involve a mixture of market mechanisms and regulation. Market mechanisms include subsidies for using carbon capture systems or for afforestation. Regulation includes policies such as requiring filters to be installed on chimneys or banning the felling of forests for grazing land.

The main issue with such policies is persuading governments to adopt them. As we saw above, governments may be unwilling to bear the short-term costs to consumers and the resulting loss in popularity. Winning the next election or simple political survival may be their number-one priority.

COP28

The COP28 summit concluded with a draft agreement which called for the:

transitioning away from fossil fuels in energy systems, in a just, orderly and equitable manner, accelerating action in this critical decade, so as to achieve net zero by 2050 in keeping with the science.

This was the first COP summit that called on all nations to transition away from fossil fuels for energy generation. It was thus hailed as the biggest step forward on tackling climate change since the 2015 Paris agreement. However, there was no explicit commitment to phase out or even ‘phase down’ fossil fuels. Many scientists, climate interest groups and even governments had called for such a commitment. What is more, there was no agreement to transition away from fossil fuels for transport, agriculture or the production of plastics.

If the agreement is to be anything more than words, the commitment must now be translated into specific policy actions by governments. This is where the real test will come. It’s easy to make commitments; it’s much harder to put them into practice with policy measures that are bound to impose costs on various groups of people. What is more, there are powerful lobbies, such as the oil, coal and steel industries, which want to slow any transition away from fossil fuels – and many governments of oil producing countries which gain substantial revenues from oil production.

One test will come in two years’ time at the COP30 summit in the Amazonian city of Belém, Brazil. At that summit, countries must present new nationally determined commitments that are economy-wide, cover all greenhouse gases and are fully aligned with the 1.5°C temperature limit. This will require specific targets to be announced and the measures required to achieve them. Also, it is hoped that by then there will be an agreement to phase out fossil fuels and not just to ‘transition away’ from them.

Reasons for hope

Despite the unwillingness of many countries, especially the oil and coal producing countries, to phase out fossil fuels, there are reasons for hope that global warming may be halted and eventually even reversed. Damage will have been done and some tipping points may have been reached, but further tipping points may be averted.

The first reason is technological advance. Research, development and investment in zero carbon technologies is advancing rapidly. As we have seen, power generation from wind and solar is now cheaper than from fossil fuels. And this cost difference is likely to grow as technology advances further. This positive tipping point is becoming more rapid. Other technological advances in transport and industry will further the shift towards renewables and other advances will economise on the use of power.

The second is changing attitudes. With the environment being increasingly included in educational syllabuses around the world and with greater stress on the problems of climate change in the media, with frequent items in the news and with programmes such as the three series of Planet Earth, people are becoming more aware of the implications of climate change and how their actions contribute towards the problem. People are likely to put increasing pressure on businesses and governments to take action. Growing awareness of the environmental impact of their actions is also affecting people’s choices. The negative externalities are thus being reduced and may even become positive ones.

Articles

Questions

  1. Use a diagram to demonstrate the effects of negative externalities in production on the level of output and how this differs from the optimum level.
  2. Use another diagram to demonstrate the effects of negative externalities in consumption on the level of consumption and how this differs from the optimum level.
  3. What was agreed at COP28?
  4. What incentives were included in the agreement to ensure countries stick to the agreement? Were they likely to be sufficient?
  5. What can governments do to encourage positive environmental tipping points?
  6. How may carbon taxes be used to tackle global warming? Are they an efficient policy instrument?
  7. What can be done to change people’s attitudes towards their own carbon emissions?

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?

Since 2019, UK personal taxes (income tax and national insurance) have been increasing as a proportion of incomes and total tax revenues have been increasing as a proportion of GDP. However, in his Autumn Statement of 22 November, the Chancellor, Jeremy Hunt, announced a 2 percentage point cut in the national insurance rate for employees from 12% to 10%. The government hailed this as a significant tax cut. But, despite this, taxes are set to continue increasing. According to the Office for Budget Responsibility (OBR), from 2019/20 to 2028/29, taxes will have increased by 4.5 per cent of GDP (see chart below), raising an extra £44.6 billion per year by 2028/29. One third of this is the result of ‘fiscal drag’ from the freezing of tax thresholds.

According to the OBR

Fiscal drag is the process by which faster growth in earnings than in income tax thresholds results in more people being subject to income tax and more of their income being subject to higher tax rates, both of which raise the average tax rate on total incomes.

Income tax thresholds have been unchanged for the past three years and the current plan is that they will remain frozen until at least 2027/28. This is illustrated in the following table.

If there were no inflation, fiscal drag would still apply if real incomes rose. In other words, people would be paying a higher average rate of tax. Part of the reason is that some people on low incomes would be dragged into paying tax for the first time and more people would be paying taxes at higher rates. Even in the case of people whose income rise did not pull them into a higher tax bracket (i.e. they were paying the same marginal rate of tax), they would still be paying a higher average rate of tax as the personal allowance would account for a smaller proportion of their income.

Inflation compounds this effect. Tax bands are in nominal not real terms. Assume that real incomes stay the same and that tax bands are frozen. Nominal incomes will rise by the rate of inflation and thus fiscal drag will occur: the real value of the personal allowance will fall and a higher proportion of incomes will be paid at higher rates. Since 2021, some 2.2 million workers, who previously paid no income taxes as their incomes were below the personal allowance, are now paying tax on some of their wages at the 20% rate. A further 1.6 million workers have moved to the higher tax bracket with a marginal rate of 40%.

The net effect is that, although national insurance rates have been cut by 2 percentage points, the tax burden will continue rising. The OBR estimates that by 2027/28, tax revenues will be 37.4% of GDP; they were 33.1% in 2019/20. This is illustrated in the chart (click here for a PowerPoint).

Much of this rise will be the result of fiscal drag. According to the OBR, fiscal drag from freezing personal allowances, even after the cut in national insurance rates, will raise an extra £42.9 billion per year by 2027/28. This would be equivalent of the amount raised by a rise in national insurance rates of 10 percentage points. By comparison, the total cost to the government of the furlough scheme during the pandemic was £70 billion. For further analysis by the OBR of the magnitude of fiscal drag, see Box 3.1 (p 69) in the November 2023 edition of its Economic and fiscal outlook.

Political choices

Support measures during the pandemic and its aftermath and subsidies for energy bills have led to a rise in government debt. This has put a burden on public finances, compounded by sluggish growth and higher interest rates increasing the cost of servicing government debt. This leaves the government (and future governments) in a dilemma. It must either allow fiscal drag to take place by not raising allowances or even raise tax rates, cut government expenditure or increase borrowing; or it must try to stimulate economic growth to provide a larger tax base; or it must do some combination of all of these. These are not easy choices. Higher economic growth would be the best solution for the government, but it is difficult for governments to achieve. Spending on infrastructure, which would support growth, is planned to be cut in an attempt to reduce borrowing. According to the OBR, under current government plans, public-sector net investment is set to decline from 2.6% of GDP in 2023/24 to 1.8% by 2028/29.

The government is attempting to achieve growth by market-orientated supply-side measures, such as making permanent the current 100% corporation tax allowance for investment. Other measures include streamlining the planning system for commercial projects, a business rates support package for small businesses and targeted government support for specific sectors, such as digital technology. Critics argue that this will not be sufficient to offset the decline in public investment and renew crumbling infrastructure.

To support public finances, the government is using a combination of higher taxation, largely through fiscal drag, and cuts in government expenditure (from 44.8% of GDP in 2023/24 to a planned 42.7% by 2028/29). If the government succeeds in doing this, the OBR forecasts that public-sector net borrowing will fall from 4.5% of GDP in 2023/24 to 1.1% by 2028/29. But higher taxes and squeezed public expenditure will make many people feel worse off, especially those that rely on public services.

Videos

  • Fiscal drag
  • Sky News Politics Hub on X, Sophy Ridge (22/11/23)

  • Fiscal drag
  • Sky News Politics Hub on X, Beth Rigby (22/11/23)

Articles

Report and data from the OBR

Questions

  1. Would fiscal drag occur with frozen nominal tax bands if there were zero real growth in incomes? Explain.
  2. Examine the arguments for continuing to borrow to fund a Budget deficit over a number of years.
  3. When interest rates rise, how much does this affect the cost of servicing public-sector debt? Why is the effect likely to be greater in the long run than in the short run?
  4. If the government decides that it wishes to increase tax revenues as a proportion of GDP (for example, to fund increased government expenditure on infrastructure and socially desirable projects and benefits), examine the arguments for increasing personal allowances and tax bands in line with inflation but raising the rates of income tax in order to raise sufficient revenue?
  5. Distinguish between market-orientated and interventionist supply-side policies? Why do political parties differ in their approaches to supply-side policy?

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.