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
- Why is it beneficial to have MVNOs in the market for mobile phone services?
- Why is it important that MVNOs have a choice of mobile networks to supply their retail mobile services?
- How do you think the other mobile network operators will react to the Vodafone-Three merger?
- Compare the relative benefits of blocking a merger with requiring merging companies to adopt certain remedies.
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
- In what types of markets might it be more likely that artificial intelligence can facilitate collusion?
- How could AI pricing tools impact the factors that make collusion more or less sustainable in a market?
- What can competition authorities do to prevent AI-assisted collusion taking place?
The market for crude oil is usually a volatile one. Indeed, in the last few months, the market has seen prices rise and fall due to various supply and demand influences. Crude oil is coined the ‘King of Commodities’ due to the impact it has on consumers, producers and both the micro and macro economy. The price of crude oil affects everything from the cost of producing plastics, transportation, and food at the supermarket.
This makes the market for crude oil an economic powerhouse which is closely watched by businesses, traders, and governments. To gain a full understanding of the movements in this market, it is important to identify how demand and supply affect the price of crude oil.
What influences the demand and supply of crude oil?
The law of demand and supply states that if demand increases, prices will rise, and if supply increases, prices will fall. This is exactly what happens in the market for crude oil. The consumer side of the market consists of various companies and hundreds of millions of people. The producer side of the market is made up of oil-producing countries. Collectively, both consumers and producers influence the market price.
However, the demand and supply of crude oil, and therefore the price, is also affected by global economic conditions and geopolitical tensions. What happens in the world impacts the price of oil, especially since a large proportion of the world’s biggest oil producers are in politically unstable areas.
Over the past five years, global events have had a major impact on the price of oil. The economic conditions created by the impact of the COVID pandemic saw prices plummet from around $55 per barrel just before the pandemic in February 2020 to around $15 per barrel in April 2020. By mid-2021 they had recovered to around $75 per barrel. Then, in the aftermath of Russia’s invasion of Ukraine in February 2022, the price surged to reach $133 in June 2022. More recently, geopolitical tensions in the Middle East and concerns about China’s economic outlook have intensified concerns about the future direction of the market. (Click here for a PowerPoint of the chart.)
Geopolitical tensions
In the first week of October 2024, the price of crude oil rose by almost 10% to around $78 per barrel as the conflict in the Middle East intensified. It unfortunately comes at a time when many countries are starting to recover from the rise in oil prices caused by the pandemic and the war in Ukraine. Any increase in prices will affect the price that consumers pay to fill up their vehicles with fuel, just when prices of diesel and petrol had reached their lowest level for three years.
The Governor of the Bank of England, Andrew Bailey, has said that the Bank is monitoring developments in the Middle East ‘extremely closely’, as the conflict has the potential to have serious impacts in the UK. The Bank of England will therefore be watching for any movement in oil prices that could fuel inflation.
The main concerns stem from further escalation in the conflict between Israel and the Iran-backed armed group, Hezbollah, in Lebanon. If Israel decides to attack Iran’s oil sector, this is likely to cause a sharp rise in the price of oil. Iran is the world’s seventh largest oil exporter and exports over half of its production to China. If the oilfields of a medium-sized supplier, like Iran, were attacked, this could threaten general inflation in the UK, which could in turn influence any decision by the Bank of England to lower interest rates next month.
Supply deficits
This week (2nd week of October 2024) saw the price of crude oil surge above $81 per barrel to hit its highest level since August. This rise means that prices increased by 12% in a week. However, this surge in price also means that prices rose by almost 21% between the start September and the start of October alone. Yet it was only in early September when crude oil hit a year-to-date low, highlighting the volatility in the market.
As the Middle-East war enters a new and more energy-related phase, the loss of Iranian oil would leave the market in a supply deficit. The law of supply implies that such a deficit would lead to an increase in prices. This also comes at a time when the US Strategic Petroleum Reserve has also been depleted, causing further concerns about global oil supply.
However, the biggest and most significant impact would be a disruption to flows through the Strait of Hormuz. This is a relatively narrow channel at the east end of the Persian Gulf through which a huge amount of oil tanker traffic passes – about a third of total seaborne-traded oil. It is therefore known as the world’s most important oil transit chokepoint. The risk that escalation could block the Strait of Hormuz could technically see a halt in about a fifth of the world’s oil supply. This would include exports from big Gulf producers, including Saudi Arabia, UAE, Kuwait and Iraq. In a worst-case scenario of a full closure of the Strait, a barrel of oil could very quickly rise to well above $100.
Disruption to shipments would also lead to higher gas prices and therefore lead to a rise in household gas and electricity bills. As with oil, gas prices filter down supply chains, affecting the cost of virtually all goods, resulting in a further rise in the cost of living. With energy bills in the UK having already risen by 10% for this winter, an escalation to the conflict could see prices rise further still.
China’s economic outlook
Despite the concern for the future supply of oil, there is also a need to consider how the demand for oil could impact price changes in the market. The price of oil declined on 14 October 2024 in light of concerns over China’s struggling economy. As China is the world’s largest importer of crude oil, there are emerging fears about the potential limits on fuel demand. This fall in price reversed increases made the previous week as investors become concerned about worsening deflationary pressures in China.
Any reduced demand from China could indicate an oversupply of crude oil and therefore potential price declines. Official data from China reveal a sharp year-on-year drop in the producer price index of 2.8% – the fastest decline in six months. These disappointing results have stirred uncertainty about the Chinese government’s economic stimulus plans. Prices could fall further if there are continuing doubts about the government’s ability to implement effective fiscal measures to promote consumer spending and, in turn, economic growth.
As a result of the 2% price fall in oil prices on 14 October, OPEC (the Organization of the Petroleum Exporting Countries) has lowered its 2024 and 2025 global oil demand growth. This negative news outweighed market concerns over the possibility that an Israeli response to Iran’s missile attack could disrupt oil production.
What is the future for oil prices?
It is expected that the market for oil will remain a volatile one. Indeed, the current uncertainties around the globe only highlight this. It is never a simple task to predict what will happen in a market that is influenced by so many global factors, and the current global landscape only adds to the complexity.
There’s a wide spectrum of predictions about what could come next in the market for crude oil. Given the changes in the first two weeks of October alone, supply and demand factors from separate parts of the globe have made the future of oil prices particularly uncertain. Callum Macpherson, head of commodities at Investec, stated in early October that ‘there is really no way of telling where we will be this time next week’ (see the first BBC News article linked below).
Despite the predominately negative outlook, this is all based on potential scenarios. Caroline Bain, chief commodities economist at Capital Economics suggests that if the ‘worst-case scenario’ of further escalation in the Middle East conflict does not materialise, oil prices are likely to ‘ease back quite quickly’. Even if Iran’s supplies were disrupted, China could turn to Russia for its oil. Bain says that there is ‘more than enough capacity’ globally to cover the gap if Iranian production is lost. However, this does then raise the question of where the loyalty of Saudi Arabia, the world’s second largest oil producer, lies and whether it will increase or restrict further production.
What is certain is that the market for crude oil will continue to be a market that is closely observed. It doesn’t take much change in global activity for prices to move. Therefore, in the current political and macroeconomic environment, the coming weeks and months will be critical in determining oil prices and, in turn, their economic effects.
Articles
- How worried should I be about rising oil prices?
BBC News, Michael Race (4/10/24)
- Interest rates could fall more quickly, hints Bank
BBC News, Dearbail Jordan (3/10/24)
- Oil Prices Eye $100 A Barrel As War Risk Premium Returns
FX Empire, Phil Carr (8/10/24)
- Crude oil futures reverse previous gains following disappointing economic data from China
London Loves Business, Hamza Zraimek (14/10/24)
- Oil falls 2% as OPEC cuts oil demand growth view, China concerns
Reuters, Arathy Somasekhar (14/10/24)
- Could war in the Gulf push oil to $100 a barrel?
The Economist (7/10/24)
- The Commodities Feed: Oil remains volatile
ING Think, Ewa Manthey and Warren Patterson (8/10/24)
- Who and what is driving oil price volatility
FT Alphaville, George Steer (9/10/24)
- Brent crude surges above $80 as conflict and storm spark supply fears
Financial Times, Rafe Uddin and Jamie Smyth (7/10/24)
Questions
- Use a demand and supply diagram to illustrate what has happened to oil prices in the main two scenarios:
(a) Conflict in the Middle East;
(b) Concerns about China’s economic performance.
- How are the price elasticities of demand and supply relevant to the size of any oil price change?
- What policy options do the governments have to deal with the potential of increasing energy prices?
- What are oil futures? What determines oil future prices?
- How does speculation affect oil prices?
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 many countries, train fares at peak times are higher than at off-peak times. This is an example of third-degree price discrimination. Assuming that peak-time travellers generally have a lower price elasticity of demand, the policy allows train companies to increase revenue and profit.
If the sole purpose of ticket sales were to maximise profits, the policy would make sense. Assuming that higher peak-time fares were carefully set, although the number travelling would be somewhat reduced, this would be more than compensated for by the higher revenue per passenger.
But there are external benefits from train travel. Compared with travel by car, there are lower carbon emissions per person travelling. Also, train travel helps to reduce road congestion. To the extent that higher peak-time fares encourage people to travel by car instead, there will be resulting environmental and congestion externalities.
The Scottish experiment with abolishing higher peak-time fares
In October 2023, the Scottish government introduced a pilot scheme abolishing peak-time fares, so that tickets were the same price at any time of the day. The idea was to encourage people, especially commuters, to adopt more sustainable means of transport. Although the price elasticity of demand for commuting is very low, the hope was that the cross-price elasticity between cars and trains would be sufficiently high to encourage many people to switch from driving to taking the train.
One concern with scrapping peak-time fares is that trains would not have the capacity to cope with the extra passengers. Indeed, one of the arguments for higher peak-time fares is to smooth out the flow of passengers during the day, encouraging those with flexibility of when to travel to use the cheaper and less crowded off-peak trains.
This may well apply to certain parts of the UK, but in the case of Scotland it was felt that there would be the capacity to cope with the extra demand at peak time. Also, in a post-COVID world, with more people working flexibly, there was less need for many people to travel at peak times than previously.
Reinstatement of peak-time fares in Scotland
It was with some dismay, therefore, especially by commuters and environmentalists, when the Scottish government decided to end the pilot at the beginning of October 2024 and reinstate peak-time fares – in many cases at nearly double the off-peak rates. For example, the return fare between Glasgow and Edinburgh rose from £16.20 to £31.40 at peak times.
The Scottish government justified the decision by claiming that passenger numbers had risen by only 6.8%, when, to be self-financing, an increase of 10% would have been required. But this begs the question of whether it was necessary to be self-financing when the justification was partly environmental. Also, the 6.8% figure is based on a number of assumptions that could be challenged (see The Conversation article linked below). A longer pilot would have helped to clarify demand.
Other schemes
A number of countries have introduced schemes to encourage greater use of the railways or other forms of public transport. One of these is the flat fare for local journeys. Provided that this is lower than previously, it can encourage people to use public transport and leave their car at home. Also, its simplicity is also likely to be attractive to passengers. For example, in England bus fares are capped at £2. Currently, the scheme is set to run until 31 December 2024.
Another scheme is the subscription model, whereby people pay a flat fee per month (or week or year, or other time period) for train or bus travel or both. Germany, for example, has a flat-rate €49 per month ‘Deutschland-Ticket‘ (rising to €58 per month in January 2025). This ticket provides unlimited access to local and regional public transport in Germany, including trains, buses, trams, metros and ferries (but not long-distance trains). This zero marginal fare cost of a journey encourages passengers to use public transport. The only marginal costs they will face will be ancillary costs, such as getting to and from the train station or bus stop and having to travel at a specific time.
Articles
- Why a pilot scheme removing peak rail fares should have been allowed to go the distance
The Conversation, Rachel Scarfe (8/10/24)
- Return of peak rail fares a costly blow for commuters and climate, Scottish Greens say
Bright Green, Chris Jarvis (6/10/24)
Commuters react to return of peak train fares in ScotlandBBC News (1/10/24)
- Perth peak rail fares to Edinburgh rise by almost 60 percent as pilot scheme ends
Daily Record, Alastair McNeill (4/10/24)
- Ditch peak-time rail fares across UK, campaigners say
iNews, Adam Forrest (30/9/24)
- Train fares reduced by up to 20% in East Yorkshire
Rail Advent, Roger Smith (26/9/24)
- Deutschland-Ticket: Germany’s popular monthly transport pass will soon be more expensive
Euronews, Angela Symons (24/9/24)
- Fare Britannia: a new approach to public transport ticketing for the UK
Greenpeace report, Leo Eyles, Tony Duckenfield and Jim Steer (19/9/24)
- Ministers urged to trial monthly ‘climate card’ in North of England to save rail commuters money and cut emissions
About Manchester, Nigel Barlow (20/9/24)
Questions
- Identify the arguments for and against having higher rail fares at peak times than at off-peak times
- Why might it be a good idea to scrap higher peak-time fares in some parts of a country but not in others?
- Provide a critique of the Scottish government’s arguments for reintroducing higher peak-time fares.
- With reference to The Conversation article, why is it difficult to determine the effect on demand of the Scottish pilot of scrapping peak-time fares?
- What are the arguments for and against the German scheme of having a €49 per month public transport pass for local and regional transport with no further cost per journey? Should it be extended to long-distance trains and coaches?
- In England there is a flat £2 single fare for buses. Would it be a good idea to make bus travel completely free?