We continue to live through incredibly turbulent times. In the past decade or so we have experienced a global financial crisis, a global health emergency, seen the UK’s departure from the European Union, and witnessed increasing levels of geopolitical tension and conflict. Add to this the effects from the climate emergency and it easy to see why the issue of economic uncertainty is so important when thinking about a country’s economic prospects.
In this blog we consider how we can capture this uncertainty through a World Uncertainty Index and the ways by which economic uncertainty impacts on the macroeconomic environment.
World Uncertainty Index
Hites Ahir, Nicholas Bloom and Davide Furceri have constructed a measure of uncertainty known as the World Uncertainty Index (WUI). This tracks uncertainty around the world using the process of ‘text mining’ the country reports produced by the Economist Intelligence Unit. The words searched for are ‘uncertain’, ‘uncertainty’ and ‘uncertainties’ and a tally is recorded based on the number of times they occur per 1000 words of text. To produce the index this figure is then multiplied up by 100 000. A higher number therefore indicates a greater level of uncertainty. For more information on the construction of the index see the 2022 article by Ahir, Bloom and Furceri linked below.
Figure 1 (click here for a PowerPoint) shows the WUI both globally and in the UK quarterly since 1991. The global index covers 143 countries and is presented as both a simple average and a GDP weighted average. The UK WUI is also shown. This is a three-quarter weighted average, the authors’ preferred measure for individual countries, where increasing weights of 0.1, 0.3 and 0.6 are used for the three most recent quarters.
From Figure 1 we can see how the level of uncertainty has been particularly volatile over the past decade or more. Events such as the sovereign debt crisis in parts of Europe in the early 2010s, the Brexit referendum in 2016, the COVID-pandemic in 2020–21 and the invasion of Ukraine in 2022 all played their part in affecting uncertainty domestically and internationally.
Uncertainty, risk-aversion and aggregate demand
Now the question turns to how uncertainty affects economies. One way of addressing this is to think about ways in which uncertainty affects the choices that people and businesses make. In doing so, we could think about the impact of uncertainty on components of aggregate demand, such as household consumption and investment, or capital expenditures by firms.
As Figure 2 shows (click here for a PowerPoint), investment is particularly volatile, and much more so than household spending. Some of this can be attributed to the ‘lumpiness’ of investment decisions since these expenditures tend to be characterised by indivisibility and irreversibility. This means that they are often relatively costly to finance and are ‘all or nothing’ decisions. In the context of uncertainty, it can make sense therefore for firms to wait for news that makes the future clearer. In this sense, we can think of uncertainty rather like a fog that firms are peering through. The thicker the fog, the more uncertain the future and the more cautious firms are likely to be.
The greater caution that many firms are likely to adopt in more uncertain times is consistent with the property of risk-aversion that we often attribute to a range of economic agents. When applied to household spending decisions, risk-aversion is often used to explain why households are willing to hold a buffer stock of savings to self-insure against unforeseen events and their future financial outcomes being worse than expected. Hence, in more uncertain times households are likely to want to increase this buffer further.
The theory of buffer-stock saving was popularised by Christopher Carroll in 1992 (see link below). It implies that in the presence of uncertainty, people are prepared to consume less today in order to increase levels of saving, pay off existing debts, or borrow less relative to that in the absence of uncertainty. The extent of the buffer of financial wealth that people want to hold will depend on their own appetite for risk, the level of uncertainty, and the moderating effect from their own impatience and, hence, present bias for consuming today.
Risk aversion is consistent with the property of diminishing marginal utility of income or consumption. In other words, as people’s total spending volumes increase, their levels of utility or satisfaction increase but at an increasingly slower rate. It is this which explains why individuals are willing to engage with the financial system to reallocate their expected life-time earnings and have a smoother consumption profile than would otherwise be the case from their fluctuating incomes.
Yet diminishing marginal utility not only explains consumption smoothing, but also why people are willing to engage with the financial system to have financial buffers as self-insurance. It explains why people save more or borrow less today than suggested by our base-line consumption smoothing model. It is the result of people’s greater dislike (and loss of utility) from their financial affairs being worse than expected than their like (and additional utility) from them being better than expected. This tendency is only likely to increase the more uncertain times are. The result is that uncertainty tends to lower household consumption with perhaps ‘big-ticket items’, such as cars, furniture, and expensive electronic goods, being particularly sensitive to uncertainty.
Uncertainty and confidence
Uncertainty does not just affect risk; it also affects confidence. Risk and confidence are often considered together, not least because their effects in generating and transmitting shocks can be difficult to disentangle.
We can think of confidence as capturing our mood or sentiment, particularly with respect to future economic developments. Figure 3 plots the Uncertainty Index for the UK alongside the OECD’s composite consumer and business confidence indicators. Values above 100 for the confidence indicators indicate greater confidence about the future economic situation and near-term business environment, while values below 100 indicate pessimism towards the future economic and business environments.
Figure 3 suggests that the relationship between confidence and uncertainty is rather more complex than perhaps is generally understood (click here for a PowerPoint). Haddow, Hare, Hooley and Shakir (see link below) argue that the evidence tends to point to changes in uncertainty affecting confidence, but with less evidence that changes in confidence affect uncertainty.
To illustrate this, consider the global financial crisis of the late 2000s. The argument can be made that the heightened uncertainty about future prospects for households and businesses helped to erode their confidence in the future. The result was that people and businesses revised down their expectations of the future (pessimism). However, although people were more pessimistic about the future, this was more likely to have been the result of uncertainty rather than the cause of further uncertainty.
Conclusion
For economists and policymakers alike, indicators of uncertainty, such as the Ahir, Bloom and Furceri World Uncertainty Index, are invaluable tools in understanding and forecasting behaviour and the likely economic outcomes that follow. Some uncertainty is inevitable, but the persistence of greater uncertainty since the global financial crisis of the late 2000s compares quite starkly with the relatively lower and more stable levels of uncertainty seen from the mid-1990s up to the crisis. Hence the recent frequency and size of changes in uncertainty show how important it to understand how uncertainty effects transmit through economies.
Academic papers
- The World Uncertainty Index
National Bureau of Economic Research, Working Paper 29763, Hites Ahir, Nicholas Bloom and Davide Furceri (February 2022)
- The Buffer-Stock Theory of Saving: Some Macroeconomic Evidence
Brookings Papers on Economic Activity, Christopher D Carroll (Vol 2, 1992)
- Macroeconomic uncertainty: what is it, how can we measure it and why does it matter?
Bank of England Quarterly Bulletin, 2013 Q2, Abigail Haddow, Chris Hare, John Hooley and Tamarah Shakir (13/6/13)
Articles
Data
Questions
- (a) Explain what is meant by the concept of diminishing marginal utility of consumption.
(b) Explain how this concept helps us to understand both consumption smoothing and the motivation to engage in buffer-stock saving.
- Explain the distinction between confidence and uncertainty when analysing macroeconomic shocks.
- Discuss which types of expenditures you think are likely to be most susceptible to uncertainty shocks.
- Discuss how economic uncertainty might affect productivity and the growth of potential output.
- How might the interconnectedness of economies affect the transmission of uncertainty effects through economies?
In recent months there has been growing uncertainty across the global economy as to whether the US economy was going to experience a ‘hard’ or ‘soft landing’ in the current business cycle – the repeated sequences of expansion and contraction in economic activity over time. Announcements of macroeconomic indicators have been keenly anticipated for signals about how quickly the US economy is slowing.
Such heightened uncertainty is a common feature of late-cycle slowing economies, but uncertainty now has been exacerbated because it has been a while since developed economies have experienced a business cycle like the current one. The 21st century has been characterised by low inflation, low interest rates and recessions caused by various types of crises – a stock market crisis (2001), a banking crisis (2008) and a global pandemic (2020). In contrast, the current cycle is a throwback to the 20th century. The high inflation and the ensuing increases in interest rates have produced a business cycle which echoes the 1970s. Therefore, few investors have experience of such economic conditions.
The focus for investors during this stage of the cycle is when the slowing economy will reach the minimum. They will also be concerned with the depth of the slowdown: will there still be some growth in income, albeit low; or will the trough be severe enough to produce a recession, and, if so, how deep? Given uncertainty around the length and magnitude of business cycles, this leads to greater risk aversion among investors. This affects reactions to announcements of leading and lagging macroeconomic indicators.
This blog examines what sort of economic conditions we should expect in a late-cycle economy. It analyses the impact this has had on investor behaviour and the ensuing dynamics observed in financial markets in the USA.
The Business Cycle
The business cycle refers to repeated sequences of expansion and contraction (or slowdown) in economic activity over time. Figure 1 illustrates a typical cycle. Typically, these sequences include four main stages. In each one there are different effects on consumer and business confidence:
- Expansion: During this stage, the economy experiences growth in GDP, with incomes and consumption spending rising. Business and consumer confidence are high. Unemployment is falling.
- Peak: This is the point at which the economy reaches its maximum output, but growth has ceased (or slowed). At this stage, inflationary pressures peak as the economy presses against potential output. This tends to result in tighter monetary policy (higher interest rates).
- Slowdown: The higher interest rates raise the cost of borrowing and reduce consumption and investment spending. Consumption and incomes both slow or fall. (Figure 1 illustrates the severe case of falling GDP (negative growth) in this stage.) Unemployment starts rising.
- Trough: This is the lowest point of the cycle, where economic activity bottoms out and the economy begins to recover. This can be associated with slow but still rising national income (a soft landing) or national income that has fallen (a hard landing, as shown in Figure 1).
While business cycles are common enough to enable such characterisation of their temporal pattern, their length and magnitude are variable and this produces great uncertainty, particularly when cycles approach peaks and troughs.
As an economy’s cycle approaches a trough, such as US economy’s over the past few months, uncertainty is exacerbated. The high interest rates used to tackle inflation will have increased borrowing costs for businesses and consumers. Access to credit may have become more restricted. Profit margins are reduced, especially for industrial sectors sensitive to the business cycle, reducing expected cash flows.
The combination of these factors can increase the risk of a recession, producing greater volatility in financial markets. This manifests itself in increased risk aversion among investors.
Utility theory suggests that, in general, investors will exhibit loss aversion. This means that they do not like bearing risk, fearing that the return from an investment may be less than expected. In such circumstances, investors need to be compensated for bearing risk. This is normally expressed in terms of expected financial return. To bear more risk, investors require higher levels of return as compensation.
As perceptions of risk change through the business cycle, so this will change the return investors will require from the financial instruments they hold. Perceived higher risk raises the return investors will require as compensation. Conversely, lower perceived risk decreases the return investors expect as compensation.
Investors’ expected rate of return is manifested in the discount rate that they use to value the anticipated cash flows from financial instruments in discounted cash flow (DCF) analysis. Equation 1 is the algebraic expression of the present-value discounted series of cash flows for financial instruments:
Where:
V = present value
C = anticipated cash flows in each of time periods 1, 2, 3, etc.
r = expected rate of return
For fixed-income debt securities, the cash flow is constant, while for equity securities (shares), expectations regarding cash flows can change.
Slowing economies and risk aversion
In a slowing economy, with great uncertainty about the scale and timing of the bottom of the cycle, investors become more risk averse about the prospects of firms. This this leads to higher risk premia for financial instruments sensitive to a slowdown in economic activity.
This translates into a higher expected return and higher discount rate used in the valuation of these instruments (r in equation 1). This produces decreases in perceived value, decreased demand and decreased prices for these financial instruments. This can be observed in the market dynamics for these instruments.
First, there may be a ‘flight to safety’. Investors attach a higher risk premium to risker financial instruments, such as equities, and seek a ‘safe-haven’ for their wealth. Therefore, we should observe a reorientation from more risky to less risky assets. Demand for equities falls, while demand for safer assets, such as government bonds and gold, rises.
There is some evidence for this behaviour as uncertainty about the US economic outlook has increased. Gold, long seen as a hedge against market decline, is at record highs. US Government bond prices have risen too.
To analyse whether this may be a flight to safety, I analysed the correlation between the daily US government bond price (5-year Treasury Bill) and share prices represented by the two more significant stock market indices in the USA: the S&P 500 and the Nasdaq Composite. I did this for two different time periods. Table 1 shows the results. Panel (a) shows the correlation coefficients for the period between 1 May 2024 and 31 July 2024; Panel (b) shows the correlation coefficients for the period between 1 August 2024 and 9 September 2024.
In the period between May and July 2024, the 5-year Treasury Bill and share price indices had significantly positive correlations. When share prices rose, the Treasury Bill’s price rose; when share prices fell, the bill’s price fell. During that period, expectations about falling interest rates dominated valuations and that effected the valuations of all financial instruments in the same way – lower expected interest rates reduce the opportunity cost of holding instruments and reduces the expected rates of return. Hence, the discount rate applied to cash flows is reduced, and present value rises. The opposite happens when macroeconomic indicators suggest that interest rates will stay high (ceteris paribus).
As the summer proceeded, worries about a ‘hard landing’ began to concern investors. A weak jobs report in early August particularly exercised markets, producing a ‘flight to safety’. Greater risk aversion among investors meant that they expect a higher return from equities. This reduced perceived value, reducing demand and price (ceteris paribus). To insulate themselves from higher risk, investors bought safer assets, like government bonds, thereby pushing up their prices. This behaviour was consistent with the significant negative correlation observed between US government debt prices and the S&P 500 and Nasdaq indices in Panel (b).
Another signal of increased risk aversion among investors is ‘sector rotation’ in their equity portfolios. Increased risk aversion among investors will lead them to divest from ‘cyclical’ companies. Such companies are in industrial sectors which are more sensitive to the changing economic conditions across the business cycle – consumer discretionary and communication services sectors, for example. To reduce their exposure to risk, investors will switch to ‘defensive’ sectors – those less sensitive to the business cycle. Examples include consumer staples and utility sectors.
Cyclical sectors will suffer a greater adverse impact on their cash flows and risk in a slowing economy. Consequently, investors expect higher return as compensation. This reduces the value of those shares. Demand for them falls, depressing their price. In contrast, defensive sectors will be valued more. They will see an increase in demand and price. This sector rotation seems to have happened in August (2024). Figure 2 shows the percentage change between 1 August and 9 September 2024 in the S&P 500 index and four sector indices, comprising companies from the communication services, consumer discretionary, consumer staples and utilities sectors.
Overall, the S&P 500 index was slightly higher, as shown by the first bar in the chart. However, while the cyclical sectors experienced decreases in their share prices, particularly communication services, the defensive companies experienced large price increases – nearly 3% for utilities and over 6% for consumer staples.
Conclusion
Economies experience repeated sequences of expansion and contraction in economic activity over time. At the moment, the US economy is approaching the end of its current slowing phase. Increased uncertainty is a common feature of late-cycle economies and this manifests itself in heightened risk aversion among investors. This produces certain dynamics which have been observable in US debt and equity markets. This includes a ‘flight to safety’, with investors divesting risky financial instruments in favour of safer ones, such as US government debt securities and gold. Also, investors have been reorientating their equity portfolios away from cyclicals and towards defensive securities.
Articles
- America’s recession signals are flashing red. Don’t believe them
The Economist (22/8/24)
- The most well-known recession indicator stopped flashing red, but now another one is going off
CNN, Elisabeth Buchwald (13/9/24)
- World’s largest economy will still achieve soft landing despite rising unemployment, most analysts believe
Financial Times, Claire Jones, Delphine Strauss and Martha Muir (6/8/24)
- We’re officially on slowdown watch
Financial Times, Robert Armstrong and Aiden Reiter (30/8/24)
- Anatomy of a rout
Financial Times, Robert Armstrong and Aiden Reiter (6/8/24)
- Reasons why investors need to prepare for a US recession
Financial Times, Peter Berezin (5/9/24)
- Business Cycle: What It Is, How to Measure It, and Its 4 Phases
Investopedia, Lakshman Achuthan (6/6/24)
- Risk Averse: What It Means, Investment Choices, and Strategies
Investopedia, James Chen (5/8/24)
Data
Questions
- What is risk aversion? Sketch an indifference curve for a risk-averse investor, treating expected return and risk as two-characteristics of a financial instrument.
- Show what happens to the slope of the indifference curve if the investor becomes more risk averse.
- Using demand and supply analysis, illustrate and explain the impact of a flight to safety on the market for (i) company shares and (ii) US government Treasury Bills.
- Use economic theory to explain why the consumer discretionary sector may be more sensitive than the consumer staples sector to varying incomes across the economic cycle.
- Research the point of the economic cycle that the US economy has reached as you read this blog. What is the relationship between bond and equity prices? Which sectors have performed best in the stock market?
Sustainability has become one of the most pressing issues facing society. Patterns of human production and consumption have become unsustainable. On the environmental front, climate change, land-use change, biodiversity loss and depletion of natural resource are destabilising the Earth’s eco-system.
Furthermore, data on poverty, hunger and lack of healthcare show that many people live below minimum social standards. This has led to greater emphasis being placed on sustainable development: ‘development that meets the needs of the present without compromising the ability of future generations to meet their own needs’ (The Brundtland Report, 1987: Ch.2, para. 1).
The financial system has an important role to play in channelling capital in a more sustainable way. Since current models of finance do not consider the welfare of future generations in investment decisions, sustainable finance has been developed to analyse how investment and lending decisions can manage the trade-off inherent in sustainable development: sacrificing return today to enhance the welfare of future generations.
However, some commentators argue that such trade-offs are not required. They suggest that investors can ‘do well by doing good’. In this blog, I will use ‘green’ bonds (debt instruments which finance projects or activities with positive environmental and social impacts) to explain the economics underpinning sustainable finance and show that doing good has a price that sustainable investors need to be prepared to pay.
I will analyse why investors might not be doing so and point to changes which may be required to ensure financial markets channel capital in a way consistent with sustainable development.
The growth of sustainable finance
Sustainable finance has grown rapidly over the past decade as concerns about climate change have intensified. A significant element of this growth has been in global debt markets.
Figure 1 illustrates the rapid growth in the issuance of sustainability-linked debt instruments since 2012. While issuance fell in 2022 due to concerns about rising inflation and interest rates reducing the real return of fixed-income debt securities, it rebounded in 2023 and is on course for record levels in 2024. (Click here for a PowerPoint.)
Green bonds are an asset class within sustainability-linked debt. Such bonds focus on financing projects or activities with positive environmental and social impacts. They are typically classified as ‘use-of-proceeds’ or asset-linked bonds, meaning that the proceeds raised from their issuance are earmarked for green projects, such as renewable energy, clean transportation, and sustainable agriculture. Such bonds should be attractive to investors who want a financial return but also want to finance investments with a positive environmental and/or social impact.
One common complaint from commentators and investors is the ‘greenium’ – the price premium investors pay for green bonds over conventional ones. This premium reduces the borrowing costs of the issuers (the ‘counterparties’) compared to those of conventional counterparties. This produces a yield advantage for issuers of green bonds (price and yield have a negative relationship), reducing their borrowing costs compared to issuers of conventional bonds.
An analysis by Amundi in 2023 using data from Bloomberg estimated that the average difference in yield in developed markets was –2.2 basis points (–0.022 percentage points) and the average in emerging markets was –5.6 basis points (–0.056 percentage points). Commentators and investors suggest that the premium is a scarcity issue and once there are sufficient green bonds, the premium over non-sustainable bonds should disappear.
However, from an economics perspective, such interpretations of the greenium ignore some fundamentals of economic valuation and the incentives and penalties through which financial markets will help facilitate more sustainable development. Without the price premium, investors could buy sustainable debt at the same price as unsustainable debt, earn the same financial return (yield) but also achieve environmental and social benefits for future generations too. Re-read that sentence and if it sounds too good to be true, it’s because it is too good to be true.
‘There is no such thing as a free lunch’
In theory, markets are institutional arrangements where demand and supply decisions produce price signals which show where resources are used most productively. Financial markets involve the allocation of financial capital. Traditional economic models of finance ignore sustainability when appraising investment decisions around the allocation of capital. Consequently, such allocations do not tend to be consistent with sustainable development.
In contrast, economic models of sustainable finance do incorporate such impacts of investment decisions and they will be reflected in the valuation, and hence pricing, of financial instruments. Investors, responding to the pricing signals will reallocate capital in a more sustainable manner.
Let’s trace the process. In models of sustainable finance, financial instruments such as green bonds funding investments with positive environmental impacts (such as renewable energy) should be valued more, while instruments funding investments with negative environmental impacts (such as fossil fuels) should be valued less. The prices of the green bonds financing renewable energy projects should rise while the prices of conventional bonds financing fossil-fuel companies should fall.
As this happens, the yield on the green bonds falls, lowering the cost of capital for renewable-energy projects, while yields on the bonds financing fossil-fuel projects rise, ceteris paribus. As with any market, these differential prices act as signals as to where resources should be allocated. In this case, the signals should result in an allocation consistent with sustainable development.
The fundamental point in this economic valuation is that sustainable investors should accept a trade-off. They should pay a premium and receive a lower rate of financial return (yield) for green bonds compared to conventional ones. The difference in price (the greenium), and hence yield, represents the return investors are prepared to sacrifice to improve future generations’ welfare. Investors cannot expect to have the additional welfare benefit for future generations reflected in the return they receive today. That would be double counting. The benefit will accrue to future generations.
A neat way to trace the sacrifice sustainable investors are prepared to make in order to enhance the welfare of future generations is to plot the differences in yields between green bonds and their comparable conventional counterparts. The German government has issued a series of ‘twin’ bonds in recent years. These twins are identical in every respect (coupon, face value, credit risk) except that the proceeds from one will be used for ‘green’ projects only.
Figure 2 shows the difference in yields on a ‘green bond’ and its conventional counterpart, both maturing on 15/8/2050, between June 2021 and July 2024. The yield on the green bond is lower – on average about 2.2 basis points (0.022 percentage points) over the period. This represents the sacrifice in financial return that investors are prepared to trade off for higher environmental and social welfare in the future. (Click here for a PowerPoint.)
The yield spread fluctuates through time, reflecting changing perceptions of environmental concerns and hence the changing value that sustainable investors attach to future generations. The spread tends to widen when there are heightened environmental concerns and to narrow when such concerns are not in the news. For example, the spread on the twin German bonds reached a maximum of 0.045 percentage points in November 2021. This coincided with the 26th UN Climate Change Conference of the Parties (COP26) in Glasgow. The spread has narrowed significantly since early 2022 as rising interest rates and falling real rates of return on bonds in the near-term seem to have dominated investors’ concerns.
These data suggest that, rather than being too large, the greeniums are too small. The spreads suggest that markets in debt instruments do not seem to attach much value to future generations. The valuation, price and yield of green bonds are not significantly different from their conventional counterparts. This narrow gap indicates insufficient reward for better sustainability impact and little penalty for worse sustainability impact.
This pattern is repeated across financial markets and does not seem to be stimulating the necessary investment to achieve sustainable development. An estimate of the scale of the deficit in green financing is provided by Bloomberg NEF (2024). While global spending on the green energy transition reached $1.8 trillion in 2023, Bloomberg estimates that $4.8 trillion needs to be invested every year for the remainder of this decade if the world is to remain on track under the ‘net zero’ scenario. Investors do not seem to be prepared to accept the trade-off needed to provide the necessary funds.
Can financial markets deliver sustainable development?
Ultimately, the hope is that all financial instruments will be sustainable. In order to achieve that, access to finance would require all investors to incorporate the welfare of future generations in their investment decisions and accept sacrificing sufficient short-term financial return to ensure long-term sustainable development. Unfortunately, the pricing of green bonds suggests that investors are not prepared to accept the trade-off. This restricts the ability of financial markets to deliver an allocation of resources consistent with sustainable development.
There are several reasons why financial markets may not be valuing the welfare of future generations fully.
- Bounded rationality means that it is difficult for sustainable investors to assign precise values to future and distant benefits.
- There are no standardised sustainability metrics available. This produces great uncertainty in the valuation of future welfare.
- Investors also exhibit cognitive biases, which means they may not value the welfare of future generations properly. These include present bias (favouring immediate rewards) and hyperbolic discounting (valuing the near future more than the distant future).
- Economic models of financial valuation use discount rates to assess the value of future benefits. Higher discount rates reduce the perceived value of benefits occurring in the distant future. As a result, long-term impacts (such as environmental conservation) may be undervalued.
- There may be large numbers of investors who are only interested in financial returns and so do not consider the welfare of future generations in their investment decisions.
Consequently, investors need to be educated about the extent of trade-offs required to achieve the necessary investments in sustainable development. Furthermore, practical models which better reflect the welfare of future generations in investment decisions need to be employed. However, challenges persist in fully accounting for future generations and it may need regulatory frameworks to provide appropriate incentives for effective sustainable investment.
Articles
- The fallacy of ESG investing
Financial Times, Robert Armstrong (23/10/20)
- Energy Transition Investment Trends 2024: Executive Summary
BloombergNEF (30/1/24)
- ESG metrics trip up factor investors
Financial Times, Emma Boyde (1/11/21)
- Our Common Future: Report of the World Commission on Environment and Development
United Nations, Gro Harlem Brundtland (chair) (20/3/87)
Who killed the ESG party?FT Film, Daniel Garrahan (17/7/24)
- Green bond issuance surges as investors hunt for yield
Financial Times, Lee Harris (19/6/24)
- Investing for long-term value creation
Journal of Sustainable Finance & Investment, 9(4), Dirk Schoenmaker and Willem Schramade (19/6/19)
- Facts and Fantasies about the Green Bond Premium
Amundi working paper 102-2020, Mohamed Ben Slimane, Dany Da Fonseca and Vivek Mahtani (December 2020)
- Climate change and growth
Industrial and Corporate Change, 32 (2), 2023, Nicholas Stern and Joseph E Stiglitz (30/7/24)
Report
Data
Questions
- Using demand and supply analysis, illustrate and explain the impact of sustainable investing on the markets for (i) green bonds and (ii) conventional bonds. Highlight how this should produce an allocation of finance capital consistent with sustainable development.
- Research the yields on the twin bonds issued by Germany since this blog was published. Can you identify any association between heightened environmental concerns and the spread between the ‘green’ and conventional bond?
- Analyse the issues which prevent financial markets from producing the pricing signals which produce an allocation of resources consistent with sustainable development.
- Research some potential regulatory policies which may provide appropriate incentives for sustainable investment.
Global long-term economic growth has slowed dramatically since the financial crisis of 2007–8. This can be illustrated by comparing the two 20-year periods 1988 to 2007 and 2009 to 2028 (where IMF forecasts are used for 2024 to 2028: see WEO Database under the Data link below). Over the two periods, average annual world growth fell from 3.8% to 3.1%. In advanced countries it fell from 2.9% to 1.6% and in developing countries from 4.8% to 4.3%. In the UK it fell from 2.4% to 1.2%, in the USA from 3.1% to 1.8% and in Japan from 1.9% to 0.5%.
In the UK, labour productivity growth in the production industries was 6.85% per annum from 1998 to 2006. If this growth rate had been maintained, productivity would have been 204% higher by the end of 2023 than it actually was. This is shown in the chart (click here for a PowerPoint).
The key driver of long-term economic growth is labour productivity, which can best be measured by real GDP per hour worked. This depends on three things: the amount of capital per worker, the productivity of this capital and the efficiency of workers themselves – the latter two giving total factor productivity (TFP). Productivity growth has slowed, and with it the long-term rate of economic growth.
If we are measuring growth in output per head of the population, as opposed to simple growth in output, then another important factor is the proportion of the population that works. With ageing populations, many countries are facing an increase in the proportion of people not working. In most countries, these demographic pressures are likely to increase.
A major determinant of long-term economic growth and productivity is investment. Investment has been badly affected by crises, such as the financial crisis and COVID, and by geopolitical tensions, such as the war in Ukraine and tensions between the USA and China and potential trade wars. It has also been adversely affected by government attempts to deal with rising debt caused by interventions following the financial crisis and COVID. The fiscal squeeze and, more recently higher interest rates, have dampened short-term growth and discouraged investment, thereby dampening long-term growth.
Another factor adversely affecting productivity has been a lower growth of allocative efficiency. Competition in many industries has declined as the rate of new firms entering and exiting markets has slowed. The result has been an increase in concentration and a growth in supernormal profits.
In the UK’s case, growth prospects have also been damaged by Brexit. According to Bank of England and OBR estimates, Brexit has reduced productivity by around 4% (see the blog: The costs of Brexit: a clearer picture). For many companies in the UK, Brexit has hugely increased the administrative burdens of trading with the EU. It has also reduced investment and led to a slower growth in the capital stock.
The UK’s poor productivity growth over many yeas is examined in the blog The UK’s poor productivity record.
Boosting productivity
So, how could productivity be increased and what policies could help the process?
Artificial intelligence. One important driver of productivity growth is technological advance. The rapid advance in AI and its adoption across much of industry is likely to have a dramatic effect on working practices and output. Estimates by the IMF suggest that some 40% of jobs globally and 60% in advanced countries could be affected – some replaced and others complemented and enhanced by AI. The opportunities for raising incomes are huge, but so too are the dangers of displacing workers and deepening inequality, as some higher-paid jobs are enhanced by AI, while many lower paid jobs are little affected and other jobs disappear.
AI is also likely to increase returns to capital. This may help to drive investment and further boost economic growth. However, the increased returns to capital are also likely to exacerbate inequality.
To guard against the growth of market power and its abuse, competition policies may need strengthening to ensure that the benefits of AI are widely spread and that new entrants are encouraged. Also training and retraining opportunities to allow workers to embrace AI and increase their mobility will need to be provided.
Training. And it is not just training in the use of AI that is important. Training generally is a key ingredient in encouraging productivity growth. In the UK, there has been a decline in investment in adult education and training, with a 70% reduction since the early 2000s in the number of adults undertaking publicly-funded training, and with average spending on training by employers decreasing by 27% per trainee since 2011. The Institute for Fiscal Studies identifies five main policy levers to address this: “public funding of qualifications and skills programmes, loans to learners, training subsidies, taxation of training and the regulation of training” (see link in articles below).
Competition. Another factor likely to enhance productivity is competition, both internationally and within countries. Removing trade restrictions could boost productivity growth; erecting barriers to protect inefficient domestic industry would reduce it.
Investment. Policies to encourage investment are also key to productivity growth. Private-sector investment can be encouraged by tax incentives. For example, in the UK the Annual Investment Allowance allows businesses to claim 100% of the cost of plant and machinery up to £1m in the year it is incurred. However, for tax relief to produce significant effects on investment, companies need to believe that the policy will stay and not be changed as economic circumstances or governments change.
Public-sector investment is also key. Good road and rail infrastructure and public transport are vital in encouraging private investment and labour mobility. And investment in health, education and training are a key part in encouraging the development of human capital. Many countries, the UK included, cut back on public-sector capital investment after the financial crisis and this has had a dampening effect on economic growth.
Regional policy. External economies of scale could be encouraged by setting up development areas in various regions. Particular industries could be attracted to specific areas, where local skilled workers, managerial expertise and shared infrastructure can benefit all the firms in the industry. These ‘agglomeration economies’ have been very limited in the UK compared with many other countries with much stronger regional economies.
Changing the aims and governance of firms. A change in corporate structure and governance could also help to drive investment and productivity. According to research by the think tank, Demos (see the B Lab UK article and the second report below), if legislation required companies to consider the social, economic and environmental impact of their business alongside profitability, this could have a dramatic effect on productivity. If businesses were required to be ‘purpose-led’, considering the interests of all their stakeholders, this supply-side reform could dramatically increase growth and well-being.
Such stakeholder-governed businesses currently outperform their peers with higher levels of investment, innovation, product development and output. They also have higher levels of staff engagement and satisfaction.
Articles
- World Must Prioritize Productivity Reforms to Revive Medium-Term Growth
IMF Blog, Nan Li and Diaa Noureldin (10/4/24)
- Why has productivity slowed down?
Oxford Martin School News, Ian Goldin, Pantelis Koutroumpis, François Lafond and Julian Winkler (18/3/24)
- How can the UK revive its ailing productivity?
Economics Observatory, Michelle Kilfoyle (14/3/24)
- With the UK creeping out of recession, here’s an economist’s brief guide to improving productivity
The Conversation, Nigel Driffield (13/3/24)
- UK economy nearly a third smaller thanks to ‘catastrophically bad’ productivity slowdown
City A.M., Chris Dorrell (12/3/24)
- Can AI help solve the UK’s public sector productivity puzzle?
City A.M., Chris Dorrell (11/3/24)
- AI Will Transform the Global Economy. Let’s Make Sure it Benefits Humanity
IMF Blog, Kristalina Georgieva (14/1/24)
- Productivity and Investment: Time to Manage the Project of Renewal
NIESR, Paul Fisher (12/3/24)
- Productivity trends using key national accounts indicators
Eurostat (15/3/24)
- New report says change to company law could add £149bn to the UK economy
B Lab UK (28/11/23)
- Investment in training and skills: Green Budget Chapter 9
Institute for Fiscal Studies, Imran Tahir (12/10/23)
Reports
Data
Questions
- Why has global productivity growth been lower since 2008 than before 2008?
- Why has the UK’s productivity growth been lower than many other advanced economies?
- How does the short-run macroeconomic environment affect long-term growth?
- Find out why Japan’s productivity growth has been so poor compared with other countries.
- What are likely to be the most effective means of increasing productivity growth?
- How may demand management policies affect the supply side of the economy?
- How may the adoption of an ESG framework by companies for setting objectives affect productivity growth?
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
- The Macroeconomics of Artificial Intelligence
IMF publications, Erik Brynjolfsson and Gabriel Unger (December 2023)
- Economic impacts of artificial intelligence (AI)
European Parliamentary Research Service, Marcin Szczepański (July 2019)
- Artificial intelligence: A real game changer
Chief Investment Office, Merrill/Bank of America (July 2023)
- Generative AI could raise global GDP by 7%
Goldman Sachs, Joseph Briggs (5/4/23)
- The macroeconomic impact of artificial intelligence
PwC, Jonathan Gillham, Lucy Rimmington, Hugh Dance, Gerard Verweij, Anand Rao, Kate Barnard Roberts and Mark Paich (February 2018)
- How genAI is revolutionizing the field of economics
CNN, Bryan Mena and Samantha Delouya (12/10/23)
- AI-powered digital colleagues are here. Some ‘safe’ jobs could be vulnerable.
BBC Worklife, Sam Becker (30/11/23)
- Generative AI and Its Economic Impact: What You Need to Know
Investopedia, Jim Probasco (1/12/23)
- AI is coming for our jobs! Could universal basic income be the solution?
The Guardian Philippa Kelly (16/11/23)
- CFPB chief’s warning: AI is a ‘natural oligopoly’ in the making
Politico, Sam Sutton (21/11/23)
Questions
- Which industries are most likely to benefit from the development of AI?
- Distinguish between labour-replacing and labour-augmenting technological progress in the context of AI.
- How could AI reduce the amount of labour per unit of output and yet result in an increase in employment?
- What people are most likely to (a) gain, (b) lose from the increasing use of AI?
- Is the distribution of income likely to become more equal or less equal with the development and adoption of AI? Explain.
- What policies could governments adopt to spread the gains from AI more equally?