Category: Essentials of Economics: Ch 08

The approach towards mergers remains the most controversial area of competition policy. Some argue that policy makers in both the UK and EU have been too easily persuaded by the arguments put forward by firms and so have allowed too many mergers to proceed. Others claim that the opposite is true and that merger policy has prohibited mergers that should have been allowed to proceed. This, then, has a negative impact on investment, innovation, productivity and growth.

In recent years there has been more specific criticism of merger policy in the UK. The government has indicated that it wants the Competition and Markets Authority (CMA) to be less interventionist and take a more pro-growth approach.

In February 2025, in response to this criticism, the CMA launched its new ‘4 Ps’ approach to merger policy: Pace, Predictability, Proportionality and Process. Various changes to the investigation process have been proposed in the past 12 months using this framework.

Pace. The time taken by the CMA to initially assess a merger before deciding whether a Phase 1 investigation is necessary (i.e. the pre-notification procedure) was reduced from 65 to 40 working days. Also, the target to complete straightforward Phase 1 investigations was reduced from 35 to 25 days.

Predictability. The proposed merger guidelines, published in October 2025, provide more detail on (a) what criteria will be used to measure market shares when applying the ‘share of supply test’ (this is where the combined UK market share of two merging businesses is at least 25%, provided one business has a UK turnover of at least £10 million), and (b) the factors that are likely to lead to the competition authorities concluding that one business has gained ‘material influence over another’. Businesses had complained that there was too much uncertainty about the way the share of supply test and material influence were applied. The CMA is also considering greater alignment with other international regulators over decision making rather than its previous policy of acting independently. All these measures should increase the predictability of the investigation process.

Proportionality. Proportionality refers to the objective of addressing any competition issues in merger cases in a way that places the minimum burden on the businesses involved. To improve proportionality, the CMA has indicated that in future cases it will be more willing to use behavioural remedies – requiring firms to take or desist from certain actions. New draft guidelines identify more situations where the use of behavioural remedies may be appropriate. However, they also show that the CMA still views structural remedies (e.g. preventing the merger or requiring firms to demerge or to sell certain assets) as more effective in many situations. Another important measure to improve proportionality is the introduction of a new ‘wait and see’ approach to global mergers. The CMA will now wait to see if the actions taken by other competition authorities in global cases address any concerns in the UK market before deciding whether to launch a review.

Process. To improve the process, the CMA has announced plans to engage with businesses at a much earlier point in the process. For example, it has pledged to share its provisional thinking in the early stages of an investigation by implementing new ‘teach-in’ sessions and having more regular update meetings. Much earlier meetings that focus on possible remedies will also take place. This may make it possible for the CMA to assess the suitability of more complex remedies during a Phase 1 investigation rather than having to wait for a longer and more costly Phase 2 review. Phase 2 reviews will also no longer be managed by panels of independent experts. This role will now be carried out by the internal CMA board.

Some critics argue that the CMA has not fully considered the potential benefits of mergers in many cases. For example, a merger could (a) have procompetitive effects, known as rivalry enhancing efficiencies (REEs) and/or (b) benefits for consumers outside of the relevant market, known as relevant customer benefits (RCBs). In response to this criticism, the CMA is currently reassessing its approach to including evidence on REEs and RCBs.

The CMA is still currently consulting with interested parties about many of these proposed changes. It will be interesting to see what final decisions are made in the next couple of years.

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CMA documentation

Questions

  1. Of all the mergers considered by the CMA in 2024/25, find out what percentage were formally investigated. How many were blocked from taking place? Do you believe that this indicates that merger policy is too weak or too strong?
  2. What three criteria must be met for a business arrangement to be classed as a ‘relevant merger situation’ by the CMA?
  3. Identify some different methods that one business could use to gain material influence over the way another company operates.
  4. Outline the ‘turnover test’, the ‘share of supply test’ and the ‘hybrid test’.
  5. Discuss the potential advantages of using behavioural remedies as opposed to structural remedies in merger cases. Why has the CMA still preferred the use of structural remedies in most situations?

This Christmas, more people are considering giving second-hand (or ‘pre-loved’) goods as presents. This allows them to afford better-quality presents and to save money at a time when a large proportion of the population are finding that their finances are stretched. This continues a trend towards buying second-hand products – a trend driven by the rise of various online retailers, such as Vinted and Preloved, and a growing online presence of charity shops, as well as extensive use of established platforms, such as Facebook Marketplace, eBay, Depop, Gumtree and Nextdoor.

Clearly, people gain from buying and selling second-hand items – part of the ‘circular economy’. But what are the implications for gross domestic product (GDP)? After all, GDP is one of the main indicators of the size of an economy, and growth in GDP is probably the most widely-used measure of economic progress. Are second-hand transactions captured in GDP?

If you directly sell your own second-hand items, this does not count towards GDP. There is no new product being made. The items are only counted when they are first produced. Any service you provide to the purchaser (and to yourself) is in a similar category to housework, childcare, DIY and other services that people provide to themselves, household members and friends. But like such services, there is a strong argument that they should be.

Likewise, the environmental benefits (positive externalities) of recycling products, rather than throwing them away or hoarding them, are not counted. In fact, if reusing products causes fewer new products to be made, this would be counted as subtracting from GDP.

If, however, you set up a business by buying and selling second-hand items, the service you provide would contribute towards GDP. What would be counted would the value added to the product – captured through the difference in the purchase and selling prices. In fact, HMRC has warned people that buying and selling second-hand items is taxable, as it counts as self-employment for tax purposes. But it is only this value added that counts. If you buy an item on Vinted, only the value added by Vinted counts towards GDP.

As no production takes place, the purchase of second-hand items adds either nothing to GDP or just the service of a retailer. It is effectively just a transfer of goods and money. If buying second-hand items means that you buy fewer new ones, then that would cause GDP to fall if the response of firms is to produce fewer newer items. However, the person selling the second-hand items will gain revenue, which could be used to buy new items. If that increased production, that would boost GDP. The net effect on GDP of this transfer of goods and money in the second-hand market will be pretty small.

Yet, clearly, the second-hand market provides a welfare gain to both sellers and purchasers – a gain that is likely to grow as the use of second-hand markets increases. At Christmas time, it provides a timely warning of the limitations of using GDP to measure wellbeing.

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Questions

  1. What other items or activities affecting human wellbeing are not counted in GDP?
  2. Name some goods and services that are produced, and hence are included in GDP, but which can be classed as ‘bads’.
  3. For what reasons might a country have a high GDP per capita but a poor average level of wellbeing?
  4. How might GDP figures be adjusted for international comparison purposes?
  5. Would it be possible to adjust GDP figures to take account of externalities in production (negative and positive)? If so, how?
  6. Production involves human costs. To what extent does GDP take this into account?
  7. What is meant by the circular economy? How might you have a ‘circular’ Christmas?

In my previous blog post on this site, I examined how AI-powered pricing tools can act as a ‘double-edged sword’: offering efficiency gains, while also creating opportunities for collusion. I referred to one of the early examples of this, which was the case involving Trod Ltd and GB Eye, where two online poster and frame sellers on Amazon used pricing algorithms to monitor and adjust their prices. However, in this instance there was also an explicit agreement between the firms. As some commentators put it, it was ‘old wine in new bottles‘, meaning a fairly conventional cartel that was simply facilitated through digital tools.

Since then, algorithms have increasingly become part of everyday life and are now embedded in routine business practice.

Some of the effects may have a positive effect on competition. For example, algorithms can help to lower barriers to entry. In some markets, incumbents benefit from long-standing experience, while new firms face significant learning costs and are at a disadvantage. By reducing these learning costs and supporting entry, algorithms could contribute to making collusion harder to sustain.

On the other hand, algorithms could increase the likelihood of collusion. For example, individual algorithms used by competing firms may respond to market conditions in predictable ways, making it easier for firms to collude tacitly over time.

Algorithms can also improve the ability of firms to monitor each other’s prices. This is particularly relevant for multi-product firms. Traditionally, we might expect these markets to be less prone to collusion because co-ordinating across many products is complex. AI can overcome this complexity. In the Sainsbury’s/Asda merger case, for example, the Competition and Markets Authority suggested that the main barrier to reaching and monitoring a pricing agreement was the complexity of pricing across such a wide range of products. However, the CMA also suggested that technological advances could increase its ability to do so in the future.

The ‘hub-and-spoke’ model

One of the other growing concerns is the ability of AI pricing algorithms to facilitate collusion by acting as a ‘hub’ in a ‘hub-and-spoke’ arrangement. In this type of collusion, competing firms (the ‘spokes’) need not communicate directly with one another. Instead, the ‘hub’ helps them to co-ordinate their actions.

While there have been only limited examples of an AI pricing algorithm acting as a hub in practice, what once seemed to be a largely theoretical concern has now become a live enforcement issue.

A very recent example is the RealPage case in the United States. The Department of Justice (DOJ) filed an antitrust lawsuit against RealPage Inc. in August 2024, alleging that RealPage, acting as the ‘hub’, facilitated collusion between landlords (the ‘spokes’).

RealPage provided pricing software to numerous landlords, including the largest landlord in the USA, which manages around 950 000 rental units across the country. These landlords would normally compete independently in setting rental prices, discounts and lease terms to win consumers. However, by feeding competitively sensitive information that would not usually be shared between rivals into RealPage’s system, the software generated pricing recommendations that, according to the DOJ, led to co-ordinated rent increases across competing apartment complexes.

In the RealPage case, the authorities reported that they had access to internal documents and statements from the parties involved, which helped support their allegations. These included references within RealPage to helping landlords ‘avoid the race to the bottom’ and comments from a landlord describing the software as ‘classic price fixing’.

Evidence in these cases really matters because the standard of proof required to establish a hub-and-spoke arrangement is much higher than for traditional cases of explicit collusion. This is because it can be difficult to distinguish between legitimate and anti-competitive communication between retailers and suppliers. Also, proving ‘anti-competitive intent’ is inherently challenging.

Other competition authorities around the world are also turning their attention to these issues. For example, the European Commission recently announced that a number of investigations into algorithmic pricing are underway, signalling a clear shift toward more active scrutiny. As technology continues to advance, it is clear that algorithmic pricing will remain an area where both firms and authorities must move and adapt quickly.

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Questions

  1. In what ways does the RealPage case differ from the earlier Trod Ltd and GB Eye Ltd case? Consider the roles played by the firms, the nature of the alleged co-ordination, and the extent to which pricing algorithms were used to facilitate the conduct.
  2. How might the use of pricing algorithms affect the likelihood of firms colluding, either explicitly or tacitly? Consider ways that algorithms may make collusion easier to sustain but also ways in which they may reduce its likelihood.
  3. Should firms be held liable for anti-competitive outcomes produced by algorithms that ‘self-learn’, even if they did not intend those outcomes? Explain why or why not.

Examples of rent seeking in economic theory

In March 2024, two people were convicted of running a business that used dishonest and illegal methods to buy and sell tickets for popular live events such as Ed Sheeran, Lady Gaga and Little Mix concerts. Between June 2015 and December 2017, this business purchased 47 000 tickets using 127 names and 187 different e-mail addresses.

Economists refer to these actions as examples of rent seeking. However, many rent-seeking activities are not illegal.

What is rent seeking?

Rent seeking in economic theory refers to costly actions taken by people (i.e. they involve effort and expertise) to try to gain a greater share of a given level of profit /surplus. These actions do not generate any extra surplus or value for society and typically involve people trying to game or manipulate a situation or system for their own personal gain.

In many cases, the opportunity cost of these actions can be considerable. In this case, the opportunity cost is the surplus for society that could have been gained if this effort/expertise had been used to carry out more productive tasks.

A widely cited example of rent seeking is where firms exert time and effort to try to influence government policy through lobbying. Most lobbying activities in the UK are not illegal.

Non-price allocation

When prices are set below the market-clearing rate, by either the government or a private organisation, the quantity demanded of the good/service will exceed the quantity supplied. Therefore, non-price allocation must play a role. In other words, some method other than willingness to pay the price, must be used to determine which consumers receive the goods.

In some instances, such as visits to the GP or places at state schools, the good or service has a zero monetary price. In these cases. non-price allocation methods completely replace the role of the price in determining which consumers obtain the goods/services.

In other examples, a positive monetary price is set, but below the market-clearing rate. In these cases, the price partly determines who get the good/service (i.e. people must be willing to pay the non-market-clearing price), but non-price allocation also plays a role. The further below the market-clearing level the price is set, the greater the potential role for non-price methods.

Some common methods of non-price allocation include:

  • First-come first served. This typically results in some type of queueing, either in person or online (a virtual queue).
  • A random selection process. For example, some goods/services are allocated via a lottery, with names of consumers being randomly drawn.
  • The government or other public bodies in charge of allocating the good develop a set of rules to determine which consumers/people get the good. For example, when allocating places at popular state schools, priority is often given to children who live close to the school (i.e. in the catchment area) or who live in families with certain religious beliefs.

Examples of rent seeking

When non-price methods of allocation are implemented, can consumers engage in activities that increase their chances of getting hold of the good/service? Can they manipulate the system for their own advantage and gain a greater share of any surplus? This is rent seeking.

A survey carried out in January 2025 provides some interesting evidence of rent-seeking actions taken by parents to try to secure a place for their child at a popular school. Twenty-seven per cent of the respondents admitted they had tried to manipulate the system to get their child into their preferred school. Out of those who admitted attempting to manipulate the system:

  • 30 per cent registered a child at either another family member’s or friend’s address that was closer to a popular school.
  • 25 per cent exaggerated religious beliefs and attended church services to try to secure a school place.
  • 9 per cent temporarily rented a second home inside the catchment area for the school.
  • 7 per cent moved into the catchment area for the application, only to move out once their child’s place was secured.

Some of these actions may be dishonest but are not illegal.

Rent-seeking activities in the ticketing market for live events

In the primary market for tickets, prices for popular live events are often set below market-clearing levels. Therefore, non-price methods, such as first come, first served, are used to allocate the tickets. This typically results in some type of queueing. Rent-seeking activities include actions taken by consumers to increases their chances of getting nearer to the front of the queue.

If the tickets are being sold from a physical outlet (i.e. a sales kiosk), then some consumers may start queueing many hours before the kiosk opens – in some cases camping overnight. An example is the ‘The Queue’ for Wimbledon tennis matches. Rather than queueing themselves, some people might pay others to queue on their behalf.

People who are paid to queue are sometimes referred to as a ‘line stander’, ‘queue stander’, ‘line sitter’ or ‘queue professional’. Line standers offer their services via market platforms, such as TaskRabbit.

When tickets are sold online, non-market allocation includes both queuing and random selection. Typically, people have to create an account with the primary market ticketing website (Ticketmaster, See Tickets, Eventbrite or AXS) before the sale begins. Then, using this account, they can enter an online waiting room around 15 minutes before the tickets are available to purchase. There is thus an element of first come, first served. When the sale starts, people in the waiting room are randomly allocated a place in the online queue. Once they reach the front of the online queue, the event organiser normally places limits on the number of tickets they can purchase.

What can people do to manipulate this system and so increase their chances of purchasing tickets? In other words, what are the possible rent-seeking activities? One possibility is to create multiple accounts using the details of friends/family and then join the waiting room with each of these accounts using separate devices. Professional resellers often try to use specialist software, called bots, that can create thousands of fake accounts and so significantly increase the chances of getting to the front of the queue. Once they get to the front of the queue, an account created by a bot can proceed through the purchasing process much faster than a person can. The tickets can then be sold for a profit in the uncapped secondary market via websites such as Stubhub and Viagogo.

The UK government passed a law in 2017 that made the use of bots to circumvent ticket purchase limits an illegal activity. The use of ticket bots in the EU became illegal in 2022. Primary market ticketing websites have also invested in technology that tries to detect and block the use of this type of software.

Government policy in the resale of tickets

Should the government prohibit the resale of tickets or implement a resale price cap to try to deter this rent-seeking activity?

Many economists would oppose this policy because of the benefits of the secondary market. For example, resale helps to reallocate tickets to those consumers with the highest willingness to pay. Therefore, the secondary-ticketing market can have a positive impact on allocative efficiency, but it comes at a cost – rent-seeking activities.

Research by economists published more than ten years ago found that the positive impact of the resale market on allocative efficiency outweighed the rent-seeking costs. However, developments in technology have increased the level of rent seeking in recent years, making it easier and less costly for professional resellers to purchase large amounts of tickets in the primary market. Therefore, it is possible that the rent-seeking cost of the secondary market now exceeds its positive impact on allocative efficiency. A case can thus be made for greater intervention by the government.

Recent accusations have also been made about possible rent-seeking activities by sellers in the primary ticketing market too, adding to concerns.

Some of the problems of implementing a resale price cap were discussed in a previous post: Ticket resales – is it time to introduce a price cap?

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Information

Questions

  1. Compare and contrast the meaning of the word ‘rent’ in everyday language with its use in economic theory.
  2. Give examples of some policies that a business might lobby the government to implement. What arguments might the business make to justify each of these policies?
  3. Outline some of the non-price methods that are used to allocate health care in the UK.
  4. Draw a demand and supply diagram to illustrate the incentives for rent-seeking activities when prices are set below market-clearing levels.
  5. Outline some potential rent-seeking activities by sellers in the primary ticketing market.
  6. Discuss some of the opportunity costs of rent-seeking activity in the market for tickets.
  7. Explain why the growing use of paid line standers might increase the demand for a good/service.
  8. Explain why the percentage of tickets for popular live events purchased by professional resellers has increased in the past 10 years.