Category: Essential Economics for Business: Ch 06

Posted on

A four-day week – a solution to sluggish productivity growth? (Updated)

In a blog from March 2023 (reproduced below), we saw how there has been growing pressure around the world for employers to move to a four-day week. Increasing numbers of companies have adopted the model of 80% of the hours for 100% of the pay.

As we see below, the model adopted has varied across companies, depending on what was seen as most suitable for them. Some give everyone Friday off; others let staff choose which day to have off; others let staff work 80% of the hours on a flexible basis. Firms adopting the model have generally found that productivity and revenue have increased, as has employee well-being. To date, over 200 employers in the UK, employing more than 5000 people, have adopted a permanent four-day week.

This concept of 100-80-100, namely 100% of pay for 80% of hours, but 100% of output, has been trialled in several countries. In Germany, after trials over 2024, 73% of the companies involved plan to continue with the new model, with the remaining 27% either making minor tweaks or yet to decide. Generally hourly productivity rose, and in many cases total output also rose. As the fourth article below states:

The primary causal factor for this intriguing revelation was simple – efficiency became the priority. Reports from the trial showed that the frequency and duration of meetings was reduced by 60%, which makes sense to anyone who works in an office – many meetings could have been a simple email. 25% of companies tested introduced new digitised ways of managing their workflow to optimise efficiency.

Original post

In two previous posts, one at the end of 2019 and one in July 2021, we looked at moves around the world to introduce a four-day working week, with no increase in hours on the days worked and no reduction in weekly pay. Firms would gain if increased worker energy and motivation resulted in a gain in output. They would also gain if fewer hours resulted in lower costs.

Workers would be likely to gain from less stress and burnout and a better work–life balance. What is more, firms’ and workers’ carbon footprint could be reduced as less time was spent at work and in commuting.

If the same output could be produced with fewer hours worked, this would represent an increase in labour productivity measured in output per hour.

The UK’s poor productivity record since 2008

Since the financial crisis of 2007–8, the growth in UK productivity has been sluggish. This is illustrated in the chart, which looks at the production industries: i.e. it excludes services, where average productivity growth tends to be slower. The chart has been updated to 2024 Q2 – the latest data available. (Click here for a PowerPoint of the chart.)

Prior to the crisis, from 1998 to 2006, UK productivity in the production industries grew at an annual rate of 6.9%. From 2007 to the start of the pandemic in 2020, the average annual productivity growth rate in these industries was a mere 0.2%.

It grew rapidly for a short time at the start of the pandemic, but this was because many businesses temporarily shut down or went to part-time working, and many of these temporary job cuts were low-wage/low productivity jobs. If you take services, the effect was even stronger as sectors such as hospitality, leisure and retail were particularly affected and labour productivity in these sectors tends to be low. As industries opened up and took on more workers, so average productivity rapidly fell back. Since then productivity has flatlined.

If you project the average productivity growth rate from 1998 to 2007 of 6.9% forwards (see grey dashed line), then by 2024 Q3, output per hour in the production industries would have been 3.26 times higher than it actually was: a gap of 226%. This is a huge productivity gap.

Productivity in the UK is lower than in many other competitor countries. According to the ONS, output per hour in the UK in 2021 was $59.14 in the UK. This compares with an average of $64.93 for the G7 countries, $66.75 in France, £68.30 in Germany, $74.84 in the USA, $84.46 in Norway and $128.21 in Ireland. It is lower, however, in Italy ($54.59), Canada ($53.97) and Japan ($47.28).

As we saw in the blog, The UK’s poor productivity record, low UK productivity is caused by a number of factors, not least the lack of investment in physical capital, both by private companies and in public infrastructure, and the lack of investment in training. Other factors include short-termist attitudes of both politicians and management and generally poor management practices. But one cause is the poor motivation of many workers and the feeling of being overworked. One solution to this is the four-day week.

Latest evidence on the four-day week

Results have just been released of a pilot programme involving 61 companies and non-profit organisations in the UK and nearly 3000 workers. They took part in a six-month trial of a four-day week, with no increase in hours on the days worked and no loss in pay for employees – in other words, 100% of the pay for 80% of the time. The trial was a success, with 91% of organisations planning to continue with the four-day week and a further 4% leaning towards doing so.

The model adopted varied across companies, depending on what was seen as most suitable for them. Some gave everyone Friday off; others let staff choose which day to have off; others let staff work 80% of the hours on a flexible basis.

There was little difference in outcomes across different types of businesses. Compared with the same period last year, revenues rose by an average of 35%; sick days fell by two-thirds and 57% fewer staff left the firms. There were significant increases in well-being, with 39% saying they were less stressed, 40% that they were sleeping better; 75% that they had reduced levels of burnout and 54% that it was easier to achieve a good work–life balance. There were also positive environmental outcomes, with average commuting time falling by half an hour per week.

There is growing pressure around the world for employers to move to a four-day week and this pilot provides evidence that it significantly increases productivity and well-being.

Additional articles

Original set of articles

Questions

  1. What are the possible advantages of moving to a four-day week?
  2. What are the possible disadvantages of moving to a four-day week?
  3. What types of companies or organisations are (a) most likely, (b) least likely to gain from a four-day week?
  4. Why has the UK’s productivity growth been lower than that of many of its major competitors?
  5. Why, if you use a log scale on the vertical axis, is a constant rate of growth shown as a straight line? What would a constant rate of growth line look like if you used a normal arithmetical scale for the vertical axis?
  6. Find out what is meant by the ‘fourth industrial revolution’. Does this hold out the hope of significant productivity improvements in the near future? (See, for example, last link above.)
Posted on

Hybrid working: too much homework or the ‘new normal’?

During the pandemic, most people who were not furloughed were forced to work from home. After lockdown restrictions were lifted, many employers decided to continue with people working remotely, at least for some of the time.

Today, this hybrid model, whereby workers work partly from home or local workspaces and partly in the office/factory/warehouse etc., has become the ‘new normal’ for around 26% of the working population in Great Britain – up from around 10% at the end of the national lockdowns in the Spring of 2021.

Increasingly, however, employers who had introduced hybrid working are requiring their employees to return to the office, arguing that productivity and hence profits will rise as a result. Amazon is an example. Other employers, such as Asda, are increasing the time required in the office for hybrid workers.

Hybrid working had peaked at around 31% in November 2923 as the chart shows (click here for a PowerPoint). The chart is based on the December 20 database, Public opinions and social trends, Great Britain: working arrangements from the Office for National Statistics (see link under Data, below).

But why are some employers deciding that hybrid working is less profitable than working full time in the office. And does it apply to all employers and all employees or only certain types of firm and certain types of job?

The first thing to note is that hybrid work is more common among certain groups. These include older workers, parents, graduates and those with greater flexibility in scheduling their work, especially those in managerial or professional roles with greater flexibility. Certain types of work on the other hand do not lend themselves to hybrid work (or working completely from home, for that matter). Shop workers and those providing a direct service to customers, such as those working in the hospitality sector, cannot work remotely.

Benefits of hybrid working

For some employees and employers, hybrid working has brought significant benefits.

For employees, less time and money is spent on commuting, which accounts for nearly an hour’s worth of the average worker’s daily time. According to the ONS survey, respondents spent an additional 24 minutes per day on sleep and rest and 15 minutes on exercise, sports and other activities that improved well-being compared to those who worked on-site. Working at home can make juggling work and home life easier, especially when workers can work flexible hours during the day, allowing them to fit work around family commitments.

Employers benefit from a healthier and more motivated staff who are more productive and less likely to quit. Hybrid work, being attractive to many workers, could allow employers to attract and retain talented workers. Also, employees may work longer hours if they are keen to complete a task and are not ‘clocking off’ at a particular time. Working from home allows workers to concentrate (unless distracted by other family members!).

By contrast, office working can be very inefficient, especially in open offices, where chatty colleagues can be distracting and it is difficult to concentrate. What is more, employees who are slightly unwell may continue working at home but may feel unable to commute to the office. If they did, they could spread their illness to other colleagues. Not allowing people to work from home can create a problem of ‘presenteeism’, where people feeling under the weather turn up to work but are unproductive.

One of the biggest benefits to employers of hybrid work is that costs can be saved by having smaller offices and by spending less on heating, lighting and facilities.

With hybrid working, time spent on site can be devoted to collaborative tasks, such as meetings with colleagues and customers/suppliers and joint projects where face-to-face discussion is required, or at least desirable. Tasks can also be completed that required specialist equipment or software not available at home.

Problems of hybrid working

So, if hybrid working has benefits for both employers and employees, why are some employers moving back to a system where employees work entirely on site?

Some employers have found it hard to monitor and engage employees working from home. Workers may be easily distracted at home by other family members, especially if they don’t have a separate study/home office. People may feel detached from their co-workers on days they work from home. After a time, productivity may wane as workers find ways of minimising the amount of time actually working during declared work times.

Far from improving work-life balance, for some workers the boundaries between work and personal life can become blurred, which can erode the value of personal and family time. This can create a feeling of never escaping from work and be demotivating and reduce productivity. Employees may stay logged on longer and work evenings and weekends in order to complete tasks.

Unless carefully planned, on days when people do go into the office they might not work effectively. They may be less likely to have profitable ad hoc conversations with co-workers, and meetings may be harder to arrange. Misunderstandings and miscommunication can occur when some employees are in the office but others are at home.

Some employers have found that the problems of hybrid working in their organisations have outweighed the benefits and that productivity has fallen. In justifying its ending of hybrid working from 1 January 2025, Amazon CEO, Andy Jessy, wrote in a memo to staff in September 2024:

To address the … issue of being better set up to invent, collaborate, and be connected enough to each other and our culture to deliver the absolute best for customers and the business, we’ve decided that we’re going to return to being in the office the way we were before the onset of COVID. When we look back over the last five years, we continue to believe that the advantages of being together in the office are significant.1

But is the solution to do as Amazon is doing and to abandon hybrid working and have a mass ‘return to the office’?

Improving hybrid working

There are ways of making hybrid working more effective so that the benefits can be maximised and the costs minimised.

Given that there are specific benefits from home working and other specific benefits from working on-site, it would be efficient to allocate time between home and office to maximise these benefits. The optimum balance is likely to vary from employer to employer, job to job and individual to individual.

Where work needs to be done in teams and where team meetings are an important element of that work, it would generally make sense for such meetings to be held in person, especially when there needs to be a lot of discussion. If the team requires a brief catch up, however, this may be more efficiently done online via Teams or Zoom.

Individual tasks, on the other hand, which don’t require consultation with colleagues or the use of specific workplace facilities, are often carried out more efficiently when there is minimum chance of interruption. For many workers, this would be at home rather than in an office – especially an open-plan office. For others without a protected work space at home or nearby, it might be better to come into the office.

The conclusion is that managers need to think carefully about the optimum distribution between home and office working and accept that a one-size-fits-all model may not be optimum for all types of job and all workers. Recognising the relative benefits and costs of working in different venues and over different hours may help to achieve the best balance, both for employers and for workers. A crucial element here is the appropriate use of incentives. Workers need to be motivated. Sometimes this may require careful monitoring, but often a more hands-off approach by management, with the focus more on output and listening to the concerns of workers, rather than on time spent, may result in greater productivity.

1Message from CEO Andy Jassy: Strengthening our culture and teams, Amazon News (16/9/24)

Articles

Data

Questions

  1. Why may hybrid working be better for (a) employees and (b) employers than purely home working or purely working in the office?
  2. Why are many firms deciding that workers who were formerly employed on a hybrid basis should now work entirely from the office?
  3. What types of job are better performed on site, or with only a small amount of time working from home?
  4. What types of job are better performed by working at home with just occasional days in the office?
  5. Does the profile of workers (by age, qualifications, seniority, experience, family commitments, etc) affect the likelihood that they will work from home at least some of the time?
  6. How would you set about measuring the marginal productivity of a worker working from home? Is it harder than measuring the marginal productivity of the same worker doing the same job but working in the office?
  7. How may working in the office increase network effects?
  8. How may behavioural economics help managers to understand the optimum balance of home and on-site working?
Posted on

The merger of Vodafone and Three: competition implications

In September 2023, UK mobile phone network operators Vodafone and Three (owned by CK Hutchinson) announced their intention to merge. At the time, in terms of total revenue from the supply of mobile phone services to consumers, Vodafone and Three had market shares of 23% and 12%, respectively.

In addition to Vodaphone and Three, there are two other major network operators – the BT Group (BT & EE) and Virgin-media 02, with market shares of around 31% and 23%, respectively, with other operators having a combined market share of 12%. As we shall see below, these other operators use one of the four major networks. Therefore, the merged entity of Vodafone-Three would become the market leader with a share of around 35% and there would only be three major network operators competing in the UK.

Not surprisingly, the UK competition agency, the Competition and Markets Authority (CMA), decided to conduct a detailed investigation into whether the merger would harm competition. However, in early December 2024 the CMA announced its decision to allow the merger to go ahead, subject to several important commitments by the merging parties.

CMA’s phase 1 findings

The CMAs phase 1 investigation raised several concerns with the merger (see fifth CMA link below).

First, it was worried that retail and business customers would have to pay higher prices for mobile services after the merger.

Second, in addition to the four mobile network operators, the UK market is served by a number of mobile ‘virtual’ network operators (MVNOs), for example Sky Mobile and Lyca Mobile. As we saw above, these suppliers account for around 12% of the consumer retail market. The MVNOs do not own their own networks and instead agree wholesale terms with one of the network operators to access their network and supply their own retail mobile services. The CMA was concerned that since the merger would reduce the number of networks competing to host these MVNOs from four to three, it would result in MVNOs paying higher wholesale access prices.

Vodafone and Three did not offer any remedies to the CMA to address these competition concerns. Consequently, the CMA referred the case to phase 2 for a more thorough investigation.

CMA’s phase 2 findings

The CMA’s analysis in phase 2 confirmed its earlier concerns (see linked report below). It was still worried that because the merged entity would become the largest network operator, retail customers would face higher prices or get a poorer service – for example, a reduced data allowance in their contract. In addition, the CMA remained concerned that the MVNOs would be negatively impacted and that this would lessen their ability to offer the best deals to retail customers.

However, during the phase 2 investigation, the merging parties put forward various efficiency justifications for the merger. They argued that the merger would provide them with much needed scale and investment capacity to improve their network and roll-out 5G technology. The CMA recognised these claims but questioned the merging parties’ incentives to go through with the investment once the merger was approved. Furthermore, it was concerned that if they did invest, this would be funded by raising the prices charged to consumers.

As a result, the CMA only agreed to allow the merger once Vodafone and Three accepted remedies that would address these concerns.

The remedies necessary for the merger to proceed

First, the merged entity must cap a range of tariffs and data plans it offers in the retail market for three years.

Second, again for three years, it must commit to maintain the wholesale contract terms it offers to MNVOs.

Finally, over the next eight years, the merged entity must deliver the network upgrade plans that it claimed the merger would allow. The CMA believes that in the long run this network development would significantly boost competition between the three remaining mobile network operators.

The acceptance of remedies of this nature was unusual for the CMA. Typically, like other competition agencies, the CMA has favoured divestment remedies in which the merging parties are required to sell-off some of the assets or capacity acquired. In contrast, the remedies in the Vodafone-Three deal impact on the merging parties’ behaviour.

One clear disadvantage of such remedies is that they require the merged firm’s actions to be monitored, in this case for eight years, to make sure it adheres to the agreed behaviour. One reason why the CMA may have been willing to accept this is that the communications industries regulator, OFCOM, will be able to assist with this monitoring.

It was also surprising that the CMA was willing to allow the number of network operators to decrease to three. Previously, there had been a perception that it was important to maintain four networks. This was certainly the view in 2016 when Three’s attempted merger with O2 was prohibited. This decision was made by the European Commission (EC). However, the CMA raised serious concerns to the EC and when the merging parties offered behavioural remedies argued that these were:

materially deficient as they will not lead to the creation of a fourth Mobile Network Operator (MNO) capable of competing effectively and in the long-term with the remaining three MNOs such that it would stem the loss of competition caused by the merger.

Why has the authorities’ attitude towards the merger changed?

So why has there been a change of stance in this latest attempted merger in the mobile phone sector?

One explanation is that the market has fundamentally changed over time. The margins for network operators have declined, network usage has grown and there has been a lack of investment in expensive 5G technology. This would certainly fit with the CMA’s desire to use the remedies to facilitate network investment.

A second possible explanation is that the CMA has recently faced criticism from UK Prime Minister, Keir Starmer (see third Guardian article below). In a speech at the International Investment Summit in London in October 2024, he said that

We will rip out the bureaucracy that blocks investment and we will make sure that every regulator in this country take growth as seriously as this room does.

In response to this, the CMA has indicated that in 2025 it will review its approach to mergers, ensuring that only truly problematic mergers don’t proceed, and reconsider when behavioural remedies may be appropriate (see final CMA link below).

The CMA’s decision in the Vodafone-Three case certainly demonstrates that it is now willing to accept behavioural remedies when there is a regulator in place to support the subsequent monitoring.

It will be interesting to see how this merger affects competition in the mobile phone market and, more generally, whether the CMA starts to implement behavioural remedies more widely, especially in markets where it would have to do all the subsequent monitoring.

Articles

CMA reports, etc

Questions

  1. Why is it beneficial to have MVNOs in the market for mobile phone services?
  2. Why is it important that MVNOs have a choice of mobile networks to supply their retail mobile services?
  3. How do you think the other mobile network operators will react to the Vodafone-Three merger?
  4. Compare the relative benefits of blocking a merger with requiring merging companies to adopt certain remedies.
Posted on

Artificial intelligence in pricing: a double-edged sword?

Artificial Intelligence (AI) is transforming the way we live and work, with many of us knowingly or unknowingly using some form of AI daily. Businesses are also adopting AI in increasingly innovative ways. One example of this is the use of pricing algorithms, which use large datasets on market conditions to set prices.

While these tools can drive innovation and efficiency, they can also raise significant competition concerns. Subsequently, competition authorities around the world are dedicating efforts to understanding how businesses are using AI and, importantly, the potential risks its use may pose to competition.

How AI pricing tools can enhance competition

The use of AI pricing tools offers some clear potential efficiencies for firms, with the potential to reduce costs that can potentially translate into lower prices for consumers.

Take, for instance, industries with highly fluctuating demand, such as airlines or hotels. Algorithms can enable businesses to monitor demand and supply in real time and respond more quickly, which could help firms to respond more effectively to changing consumer preferences. Similarly, in industries which have extensive product ranges, like supermarkets, algorithms can significantly reduce costs and save resources that are usually required to manage pricing strategies across a large range of products.

Furthermore, as pricing algorithms can monitor competitors’ prices, firms can more quickly respond to their rivals. This could promote competition by helping prices to reach the competitive level more quickly, to the benefit of consumers.

How AI pricing tools can undermine competition

However, some of the very features that make algorithms effective can also facilitate anti-competitive behaviour that can harm consumers. In economic terms, collusion occurs when firms co-ordinate their actions to reduce competition, often leading to higher prices. This can happen both explicitly or implicitly. Explicit collusion, commonly referred to as illegal cartels, involves firms agreeing to co-ordinate their prices instead of competing. On the other hand, tacit collusion occurs when firms’ pricing strategies are aligned without a formal agreement.

The ability for these algorithms to monitor competitors’ prices and react to changes quickly could work to facilitate collusion, by learning to avoid price wars to maximise long-term profits. This could result in harm to consumers through sustained higher prices.

Furthermore, there may be additional risks if competitors use the same algorithmic software to set prices. This can facilitate the sharing of confidential information (such as pricing strategies) and, as the algorithms may be able to predict the response of their competitors, can facilitate co-ordination to achieve higher prices to the detriment of consumers.

This situation may resemble what is known as a ‘hub and spoke’ cartel, in which competing firms (the ‘spokes’) use the assistance of another firm at a different level of the supply chain (e.g. a buyer or supplier that acts as a ‘hub’) to help them co-ordinate their actions. In this case, a shared artificial pricing tool can act as the ‘hub’ to enable co-ordination amongst the firms, even without any direct communication between the firms.

In 2015 the CMA investigated a cartel involving two companies, Trod Limited and GB Eye Limited, which were selling posters and frames through Amazon (see linked CMA Press release below). These firms used pricing algorithms, similar to those described above, to monitor and adjust their prices, ensuring that neither undercut the other. In this case, there was also an explicit agreement between the two firms to carry out this strategy.

What does this mean for competition policy?

Detecting collusion has always been a significant challenge for the competition authorities, especially when no formal agreement exists between firms. The adoption of algorithmic pricing adds another layer of complexity to detection of cartels and could raise questions about accountability when algorithms inadvertently facilitate collusion.

In the posters and frames case, the CMA was able to act because one of the firms involved reported the cartel itself. Authorities like the CMA depend heavily on the firms involved to ‘whistle blow’ and report cartel involvement. They incentivise firms to do this through leniency policies that can offer firms reduced penalties or even complete immunity if they provide evidence and co-operate with the investigation. For example, GB eye reported the cartel to the CMA and therefore, under the CMA’s leniency policy, was not fined.

But it’s not all doom and gloom for competition authorities. Developments in Artificial Intelligence could also open doors to improved detection tools, which may have come a long way since the discussion in a blog on this topic several years ago. Competition Authorities around the world are working diligently to expand their understanding of AI and develop effective regulations for these rapidly evolving markets.

Articles

Questions

  1. In what types of markets might it be more likely that artificial intelligence can facilitate collusion?
  2. How could AI pricing tools impact the factors that make collusion more or less sustainable in a market?
  3. What can competition authorities do to prevent AI-assisted collusion taking place?
Posted on

World Uncertainty Index

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

Articles

Data

Questions

  1. (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.
  2. Explain the distinction between confidence and uncertainty when analysing macroeconomic shocks.
  3. Discuss which types of expenditures you think are likely to be most susceptible to uncertainty shocks.
  4. Discuss how economic uncertainty might affect productivity and the growth of potential output.
  5. How might the interconnectedness of economies affect the transmission of uncertainty effects through economies?