Category: Essential Economics for Business: Ch 05

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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?
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Crude oil – a volatile market

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.

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Questions

  1. 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.
  2. How are the price elasticities of demand and supply relevant to the size of any oil price change?
  3. What policy options do the governments have to deal with the potential of increasing energy prices?
  4. What are oil futures? What determines oil future prices?
  5. How does speculation affect oil prices?
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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.

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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?
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Should train companies scrap peak-time fares?

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.

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Questions

  1. Identify the arguments for and against having higher rail fares at peak times than at off-peak times
  2. Why might it be a good idea to scrap higher peak-time fares in some parts of a country but not in others?
  3. Provide a critique of the Scottish government’s arguments for reintroducing higher peak-time fares.
  4. 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?
  5. 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?
  6. In England there is a flat £2 single fare for buses. Would it be a good idea to make bus travel completely free?
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Disgruntled Oasis fans react to dynamic pricing

On Saturday 31 August, tickets for the much-heralded Oasis reunion tour went on sale through the official retailer, Ticketmaster. When the company sells tickets, the acts or their promoters can choose whether to use a static pricing system, where each type of ticket is sold at a set price until they have all been sold. Or they can use a dynamic pricing system (‘in-demand’ or ‘platinum’ tickets, as Ticketmaster calls them), where there is a starting price quoted, but where prices then rise according to demand. The higher the demand, the more the price is driven up. Acts or their promoters have the option of choosing an upper limit to the price.

Dynamic pricing

The Oasis tickets were sold under the dynamic pricing system, a system previously used for Harry Styles, Bruce Springsteen, Coldplay and Blackpink concerts, but one rejected by Taylor Swift for her recent Eras tour. Standing tickets for the Oasis concert with a face value of around £135 were quickly being sold for over £350. There were long online queues, with the prices rising as people slowly moved up the queue. When they reached the front, they had to decide quickly whether to pay the much higher price. Some people later suffered from buyer’s remorse, when they realised that in the pressure of the moment, they had paid more than they could afford.

Dynamic pricing is when prices change with market conditions: rising at times when demand exceeds supply and falling when supply exceeds demand. It is sometimes referred to as ‘surge pricing’ to reflect situations when price surges in times of excess demand.

Dynamic pricing is a form of price discrimination. It is an imperfect form of first-degree price discrimination, which is defined as people being charged the maximum price they are willing to pay for a product. Pricing in an eBay auction comes close to first-degree price discrimination. With dynamic pricing in the ticket market, some people may indeed pay the maximum, but others earlier in the queue will be lucky and pay less than their maximum.

Ticketmaster justifies the system of dynamic pricing, saying that it gives ‘fans fair and safe access to the tickets, while enabling artists and other people involved in staging live events to price tickets closer to their true market value’. The company argues that if the price is below the market value, a secondary market will then drive ticket prices up. Ticket touts will purchase large amounts of tickets, often using bots to access the official site and then resell them at highly inflated prices on sites such as Viagogo and Stubhub, where ticket prices for popular acts can sell for well over £1000. The day after Oasis tickets went on sale, Viagogo had seats priced at up to £26 000 each!

Oasis and Ticketmaster have tried to stamp out the unofficial secondary market by stating that only tickets bought through the official retailers (Ticketmaster, Gigsandtours and SeeTickets) will be valid. If fans want to resell a ticket – perhaps because they find they can no longer go – they can resell them on the official secondary market though Ticketmaster’s Fan-to-Fan site or Twickets. These official secondary sites allow holders of unwanted tickets to sell them for anything up to the original face value, but no more. Buyers pay a 12% handling fee. It remains to be seen whether this can be enforced with genuine tickets resold on the secondary market.

Examples of dynamic pricing

Dynamic pricing is not a new pricing strategy. It has been used for many years in the transport, e-commerce and hospitality sectors. Airlines, for example, have a pricing model whereby as a flight fills up, so the prices of the seats rise. If you book a seat on a budget airline a long time in advance, you may be able to get it at a very low price. If, on the other hand, you want a seat at the last minute, you may well have to pay a very high price. The price reflects the strength of demand and its price elasticity. The business traveller who needs to travel the next day for a meeting will have a very low price sensitivity and may well be prepared to pay a very high price indeed. Airlines also learn from past behaviour and so some popular routes will start at a higher price. A similar system of dynamic pricing is used with advance train tickets, with the price rising as trains get booked up.

The dynamic pricing system used by airlines and train companies is similar, but not identical, to first-degree price discrimination. The figure below illustrates first-degree price discrimination by showing a company setting the price for a particular product.

Assume initially that it sets a single profit-maximising price. This would be a price of P1, at an output of Q1, where marginal revenue (MR) equals marginal cost (MC). (We assume for simplicity that average and marginal costs are constant.) Total profit will be area 1: i.e. the blue area ((P1 – AC) × Q1). Area 2 represents consumer surplus, with all those consumers who would have been prepared to pay a price above P1, only having to pay P1.

Now assume that the firm uses first-degree price discrimination, selling each unit of the product at the maximum price each consumer is willing to pay. Starting with the consumer only willing to pay a price of P2, the price will go on rising up along the demand with each additional consumer being charged a higher price up to the price where the demand curve meets the vertical axis. In such a case, the firm’s profit would be not just the blue area, but also the green areas 2 and 3. Note that there is no consumer surplus as area 2 is now part of the additional profit to the firm.

Although dynamic pricing by airlines is similar to this model of first-degree price discrimination, in practice some people will be paying less than they would be willing to pay and the price goes up in stages, not continuously with each new sale of a ticket. Thus, compared with a fixed price per seat, the additional profit will be less than areas 2 + 3, but total profit will still be considerably greater than area 1 alone. Note also that there is a maximum quantity of seats (Qmax), represented by a full flight. The airline would hope that demand and its pricing model are such that Qmax is less than Q2.

Dynamic pricing also applies in the hospitality sector, as hotels raise the prices for rooms according to demand, with prices at peak times often being considerably higher than off-season prices. Rather then pre-setting prices for particular seasons, dates or weekends/weekdays, many hotels, especially chains and booking agents, adjust prices dynamically as demand changes. Airbnb offers property owners what it calls ‘Smart Pricing’, where nightly prices change automatically with demand.

Another example is Uber, which uses dynamic pricing to balance demand and supply location by location. In times of peak demand on any route, the company’s algorithm will raise the price. This will encourage people to delay travelling if they can or use alternative means of transport. It will also encourage more Uber drivers to come to that area. In times of low demand, the price will fall. This will encourage more people to use the service (rather than regular taxis or buses) and discourage drivers from working in that area.

Where dynamic pricing varies with the time or date when the purchase is made, it is sometimes referred to as inter-temporal pricing. It is a form of second-degree price discrimination, which is where a firm offers consumers a range of different pricing options for the same or similar products.

Another example of dynamic pricing, which is closer to first-degree price discrimination is the use of sophisticated algorithms and AI by Amazon, allowing it to update the prices of millions of products many times a day according to market conditions. Another is eBay auctions, where the price rises as the end date is reached, according to the willingness to pay of the bidders.

Attitudes to dynamic pricing

Consumers have grown accustomed to dynamic pricing in many industries. People generally accept the pricing model of budget airlines, for example. What makes it acceptable is that most people feel that they can take advantage of early low-priced seats and can compare the current prices on different flights and airlines when making their travel plans. Pricing is transparent. With the Oasis concert, however, there wasn’t the same degree of price transparency. Many people were surprised and dismayed to find that when they got to the front of the online queue, the price had risen dramatically.

People are familiar of dynamic pricing in the context of price cuts to shift unsold stock. Supermarkets putting stickers on products saying ‘reduced for quick sale’ is an example. Another is seasonal sales. What is less acceptable to many consumers is firms putting up prices when demand is high. They see it a profiteering. Many supermarkets are introducing electronic shelf labels (ESLs), where prices can be changed remotely as demand changes. Consumers may react badly to this if they see the prices going up. The supermarket, however, may find it a very convenient way of reducing prices to shift stock – something consumers are hardly likely to complain about.

Returning to the Oasis tour, the UK government responded to the outrage of fans as ticket prices soared. Culture Secretary, Lisa Nandy, announced that the government will investigate how surge pricing for concert tickets is used by official retailers, such as Ticketmaster. This will be part of a planned review of ticket sales that seeks to establish a fairer and more transparent system of pricing.

The problem is that, with some fans being prepared to pay very high prices indeed to see particular acts and with demand considerably exceeding supply at prices that fans would consider reasonable, some way needs to be found of rationing demand. If it is not price, then it will inevitably involve some form of queuing or rationing system, with the danger that this encourages touts and vastly inflated prices on the secondary market.

Perhaps a lesson can be drawn from the Glastonbury Festival, where prices are fixed, people queue online and where security systems are in place to prevent secondary sales by ticket touts. The 2024 price was set at £355 + a £5 booking fee and purchasers were required to register with personal details and a photo, which was checked on admission.

Update

On 5 September, the CMA announced that it was launching an investigation into Ticketmaster over the Oasis concert sales. Its concerns centred on ‘whether buyers were given clear and timely information, and whether consumer protection law was breached’. This followed complaints by fans that (i) they were not given clear and timely information beforehand that the tickets involved dynamic pricing and warned about the possible prices they might have to pay and (ii) on reaching the front of the queue they were put under pressure to buy tickets within a short period of time.

Meanwhile, band member stated that they were unaware that dynamic pricing would be used and that the decision to use the system was made by their management.

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Questions

  1. What is the difference between dynamic pricing and surge pricing?
  2. What is buyer’s remorse? How could dynamic pricing be used while minimising the likelihood of buyer’s remorse?
  3. Distinguish between first-degree, second-degree and third-degree price discrimination. Do the various forms of dynamic pricing correspond to one or more of these three types?
  4. Distinguish between consumer and producer surplus. How may dynamic pricing lead to a reduction in consumer surplus and an increase in producer surplus?
  5. Should Ticketmaster sell tickets on the same basis as tickets for the Glastonbury Festival?
  6. Is Oasis a monopoly? What are the ticket pricing implications?
  7. Are there any industries where firms would not benefit from dynamic pricing? Explain.
  8. What are the arguments for and against allowing tickets to be sold on the secondary market for whatever price they will fetch?
  9. How powerful is Ticketmaster in the primary and secondary ticket markets?