Category: Essential Economics for Business: Ch 05

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Shrinkflation, skimpflation and sneakflation: ways of hiding inflation

Have you noticed that many products in the supermarket seem to be getting smaller or are poorer quality, or that special offers are not as special as they used to be? When you ring customer services, does it seem that you have to wait longer than you used to? Do you now have to pay for extras that used to be free? These are all ways that producers try to pass on cost increases to consumers without rising prices. There are three broad ways in which producers try to hide inflation.

The first is called ‘shrinkflation’. It is defined as having less product in the same package or a smaller package for the same price. For example, reducing the number of chocolates in a tub, reducing the size of a can of beans, jar of coffee or block of butter, reducing the number of sheets in a toilet roll, or the length of a ride in a fairground or portion sizes in a restaurant or takeaway. A 2023 YouGov poll revealed that 75% of UK adults are either ‘very’ or ‘fairly’ concerned about shrinkflation. A similar poll in 2025 showed that this figure had increased to 80%. The product category with the greatest concerns was snack foods (e.g. crisps, confectionery items, nuts, etc.).1

The second form of hidden inflation is called ‘skimpflation’. This is defined as decreasing the quality of a product or service without lowering the price. Examples include cheaper ingredients in food or confectionery, such as using palm oil instead of butter, or reducing the cocoa content in chocolate or the meat content in sausages and pies, or package holidays reducing the quality of meals, or customer service centres or shops reducing the number of staff so that people have to wait longer on the phone or to be served.

The third is called ‘sneakflation’. This is similar to skimpflation but normally refers to reducing what you get when you pay for a service, such as a flight, by now charging for extras, such as luggage or food. Sometimes shrinkflation or skimpflation are seen as subsets of sneakflation.

These practices have had a lot of publicity in recent months, with consumers complaining that they are getting less for their money. Many people see them as a sneaky way of passing on cost increases without raising the price. But the changes are often subtle and difficult for shoppers to spot when they are buying an item. Skimpflation especially is difficult to observe at the time of purchase. It’s only when people consume the product that they think that it doesn’t seem as good as it used to be. Even shrinkflation can be hard to spot if the package size remains the same but there is less in it, such as fewer biscuits in a tin or fewer crisps in a packet. People would have to check the weight or volume, while also knowing what it used to be.

If firms are legitimately passing on costs and are up-front about what they are doing, then most consumers would probably understand it even if they did not like it. It’s when firms do it sneakily that many consumers get upset. Also, firms may do it to increase profit margins – in other words, by reducing the size or quality beyond what is necessary to cover the cost increase.

Does the official rate of inflation take such practices into account?

The answer is that some of the practices are taken into account – especially shrinkflation. The Office for National Statistics (ONS) accounts for shrinkflation by monitoring price changes per unit of weight or volume, rather than just the price. Data collectors track the weight, volume or count of item. When a product’s size is reduced, the ONS records this as a price increase in CPI or CPIH inflation statistics. This is known as a ‘quality adjustment’ process and allows the ONS to isolate price changes from product size changes. As CPI data from the ONS is used by the Bank of England in monitoring its 2% inflation target, it too is incorporating shrinkflation.

ONS quality adjustments are also applied to non-market public services, such as healthcare, education and policing to measure changes in service quality rather than just volume. This allows a more accurate measurement of productivity as it focuses on outcomes and user experience per pound spent rather than just focusing on costs.

Skimpflation is more difficult to monitor. The quality adjustment process may miss some quality changes and hence some skimpflation goes unrecorded. This means that the headline inflation rate might understate the true decline in purchasing power felt by consumers.

How extensive is hidden inflation?

Despite public perception, shrinkflation has a relatively small impact on the headline CPI and CPIH inflation rate in the UK because it is largely confined to certain sectors, such as bread and cereals, personal care products, meat products, and sugar, jams, syrups, chocolate & confectionery. Nevertheless, in these sectors it is particularly prevalent, especially in the packaged foodstuffs and confectionery sector. The latest research by the ONS in 2019 covered the period June 2015 to June 2017 and is shown in the following figure.2

According to research in the USA by Capital One Shopping, some major brands reduced product sizes by over 30% in 2025 without reducing prices, with shrinkflation averaging 14.8% among selected national grocery brands.3 Shrinkflation had been observed by 74% of Americans at their grocery store. Of these, 81% took some kind of action as a result, with 48% abandoning a brand. Nevertheless, across all products, shrinkflation accounts for quite a small percentage of any overall price rises.

A US Government Accountability Office (GAO) report found that shrinkflation accounted for less than 1/10 of a percentage point of the 34.5% increase in overall consumer prices from 2019 to 2024.4 The reason is that the items that were downsized comprised a small percentage of goods and services. Indeed, many goods and services, such as housing, cannot be downsized in the same way that household products can.

Nevertheless, with consumer budgets being squeezed by the inflation that followed the pandemic and the Russian invasion of Ukraine, hidden inflation has become more prevalent in many countries and an increasing concern of consumers.

References

  1. Shrinkflation concern rises in 2025, but fewer Britons are changing shopping habits

    2. YouGov (15/8/25)

  2. Shrinkflation: How many of our products are getting smaller?

    3. Office for National Statistics (21/1/19)

  3. Shrinkflation Statistics

    4. Capital One Shopping (30/12/25)

  4. What is “Shrinkflation,” And How Has It Affected Grocery Store Items Recently?

    5. U.S. Government Accountability Office (12/8/25)

Videos

Articles

Journal Article

Questions

  1. If shrinkflation, when included in CPI statistics, accounts for such a small percentage of inflation, why are people so concerned about it?
  2. From a company’s perspective, is it a good idea to engage in (a) shrinkflation; (b) skimpflation?
  3. Go round you local supermarket and identify examples of shrinkflation and skimpflation.
  4. How are various EU countries attempting to inform consumers of shrinkflation?
  5. Why is skimpflation often harder to detect than shrinkflation?
  6. Give some other examples of sneakflation in the provision of services.
  7. How could behavioural economists help firms decide whether or how to engage in shrinkflation or skimpflation?
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The 4Ps approach to merger policy in the UK

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.

Articles

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?
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Age-old problems but new technology: developments in collusion in the algorithmic era

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.

Articles

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.
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Commercial banking: the emerging risks from the shadow-banking sector

Recently, a flurry of bankruptcies among non-bank financial intermediaries (NBFIs) in the USA has drawn attention to the risks associated with alternative credit channels in the shadow-banking sector – lending which is not financed with deposits. There is concern that this could be the start of a wave of bankruptcies among such NBFIs, especially given concerns about a potential downswing in the economic cycle – a time when defaults are more likely.

While providing alternative sources of funding, the opacity of lending in the shadow-banking sector means it is not clear what risks NBFIs face themselves and, more significantly, what risks they pose to the financial system as a whole. There is particular concern about the impact on regulated banks.

Already, JP Morgan Chase in its third quarter earnings report announced a $170m charge stemming from the bankruptcy of Tricolor, which specialised in sub-prime car financing. Mid-sized banks, Western Alliance and Zions Bancorp, have reported losses from loans to a group of distressed real estate funds. This has highlighted the interconnectedness between NBFIs and regulated banking, and the potential for problems in the shadow-banking sector to have a direct impact on mainstream banks.

In this blog, we will trace the secular trends in the financial systems of more advanced economies which have given rise to alternative credit channels and, in turn, to potential banking crises. We will explain the relationship between regulated banks and shadow banks, analysing the risks involved, the potential impact on the financial system and the policy implications.

What are the secular trends in banking?

The traditional model of commercial banking involved taking deposits and using them to finance loans to households and firms. However, cycles of banking crises, regulatory changes and financial innovation over the past 50 years produced new models.

First, banks diversified away from direct lending to providing other banking services – on-balance sheet activities, such as investing in financial securities, and off-balance sheet activities, such as acting as agents in the sale of financial securities.

Second, alternative credit channels based on financial markets have grown in significance.

In the 1980s, international regulations around traditional banking activities – taking deposits and making loans – were being formalised by the Bank for International Settlements (BIS) under what became known as the Basel framework (see, for example, Economics section 18.2 or Economics for Business section 28.2). For the first time, this stipulated liquidity and capital requirements for international banks relating to their traditional lending activities. However, at the same time the deregulation of financial markets and financial innovation provided banks with opportunities to derive revenues from a range of other financial services.

After the financial crisis, liquidity and capital requirements for banks were tightened further through the Basel III regulations. Commercial banks had to have even higher levels of capital as a buffer for bad debts associated with direct lending. A higher level of capital to cover potential losses increases the marginal cost of lending, since each pound of additional loan requires additional capital. This reduced the marginal return, and consequently, the incentive to lend directly.

These regulatory developments created an incentive to pursue activities which do not require as much capital, since their marginal cost is lower and potential return is higher. Consequently, banks have placed less emphasis on lending and more on purchasing short-term and long-term financial securities and generating non-interest income from off-balance sheet activities. For instance, research by the Bank of England found that during the 1980s, interest income accounted for more than two-thirds of total income for large international banks. In contemporary times, non-interest income tends to be greater than interest income. Figure 1 illustrates the declining proportion of total assets represented by commercial and consumer loans for all regulated US banks. (Click here for a PowerPoint.)

With banks originating less lending, activity has migrated to different avenues in the shadow-banking sector. This sector has always existed, but deregulation and financial innovation created opportunities for the growth of shadow banking – lending which is not financed with deposits. Traditionally, non-bank financial intermediaries (NBFIs), such as pension funds, hedge funds and insurance companies, use funds from investors to buy securities through financial markets. However, new types of NBFIs have emerged which originate loans themselves, notably private credit institutions. As Figure 2 illustrates, a lot of the expansion in the activities of NBFIs has been the due to increased lending by these institutions (defined as ‘other financial institutions (OFIs)). Note that the NBFI line includes OFIs. (Click here for a PowerPoint.)

Since, NBFIs operate outside conventional regulatory frameworks, their credit intermediation and maturity transformation are not subject to the same capital requirements or oversight that banks are. As a result, they do not need to have the same level of capital to insulate against loan losses. Therefore, lending in the shadow-banking sector has a lower marginal cost compared to equivalent lending in the banking sector. Consequently, it generates a higher rate of return. This can explain the large growth in the assets of OFIs illustrated in Figure 2.

Risks in shadow banking

Banking involves trade-offs and this is the case whether the activities happen in the regulated or shadow-banking sector. Increasing lending increases profitability. But as lending continues to increase, at some point the risk-return profile becomes less favourable since institutions are lending to increasingly higher-risk borrowers and for higher-risk projects.

In downturns, when rates of defaults rise, such risks become apparent. Borrowers fail and default, causing significant loan losses for lenders. With lower levels of capital, NBFIs will have a lower buffer to insulate investors from these losses, increasing the likelihood of default.

Is this a problem? Well, for a long-time regulators thought not. It was thought that failures in the shadow-banking sector would have no implications for deposit-holders in regulated banks and the payments mechanism. Unfortunately, current developments in the USA have highlighted that this is unlikely to be the case.

The connections between regulated and shadow banking

The financial system is highly interconnected, and each successive financial crisis has shown that systemic risks lurk in obscure places. On the face of it, NBFIs appear separate from regulated banks. But banks’ new business models have not removed them from the lending channel, merely changed their role. Short-term financing used to be conducted and funded by banks. Now, it is conducted by NBFIs, but still financed by banks. Long-term loan financing is no longer on banks’ balance sheets. However, while the lending is conducted by NBFIs, it is largely funded by banks.

NBFIs cannot be repositories of liquidity. Since they do not have deposits and are not part of the payments system, they have no access to official liquidity backstops. So, they do so indirectly by using deposit-taking banks as liquidity insurance. Banks provide this liquidity in a variety of ways:

  • Investing in the securities issued by private capital funds;
  • Providing bridge financing to credit managers to securitise credit card receivables;
  • Providing prime broker financing to a hedge fund engaged in proprietary trading.

Furthermore, banks have increasingly made loans to NBFIs. Data for US commercial banks lending to the shadow-banking sector are publicly available only since 2015. But, as Figure 3 illustrates, it has seen a steady upward trend with a surge in activity in 2025. (Click here for a PowerPoint.)

Banks had an incentive to diversify into these activities since they are a source of revenue requiring less regulatory capital. The model requires risk and return to follow capital out of the banking system into the shadow-banking sector. However, while risky capital and its associated expected return have moved in the shadow-banking system, not all of the liquidity and credit default risk may have done so. Ultimately, some of that risk may be borne by the deposit-holders of the banks.

This is not an issue if banks are fully aware of the risks. However, problems arise when banks do not know the full risks they are taking.

There are reasons why this may be the case. Credit markets involve significant asymmetric information between lenders and borrowers. This creates conditions for the classic problems of moral hazard and adverse selection.

Moral hazard is a hidden action problem, whereby borrowers take greater risks because they share the possible downside losses with the lender. Adverse selection is the hidden information problem, whereby lenders do not have full information about the riskiness of borrowers or their activities.

The economics of information suggests that banks exploit scale, scope and learning economies to overcome the costs associated with asymmetric information in lending. However, that applies to direct lending when banks have full information about credit default risk on their loan book. When banks finance lending indirectly through NBFIs, there is an extension of the intermediation chain, and while banks may know the NBFIs, they will have much less information about the risks associated with the lending they are ‘underwriting’. This heightens their problems of asymmetric information associated with credit default risk.

What are the risks at present?

The level of debt in the global economy is at unprecedented levels. Data from the International Monetary Fund (IMF) show that it rose to $351 trillion dollars in 2024, approximately 235% of weighted global gross domestic product (GDP). It is in this environment that private credit channels through NBFIs have been expanding. With this, it is more likely that NBFIs’ trade-off between credit risk and return has tilted greatly in favour of the former. Some point to the recent collapse of Tricolor and First Brands – both intermediary financing companies funded by private credit – as evidence of elevated levels of risk.

Many are pointing out that the failures observed in the USA so far have a whiff of fraud associated with them, with suggestions of multiple loans being secured against the same working capital. However, such behaviour is symptomatic of ‘late-cycle’ lending, where the incentive to squeeze more profit from lending in a more competitive environment leads to short-cuts – short-cuts that banks, at one stage removed along the intermediation chain, will have less information about.

It is in a downturn that such risks become apparent. Widening credit spreads and the reduced availability of credit causes financial stress for higher-risk borrowers. Inevitably, that higher risk will lead to higher defaults, more provision for loan losses and write-downs in the value of loan assets.

While investors in NBFIs are first in line to bear the losses, they are not the only ones exposed. At moments of stress, the credit lines that banks have provided get drawn and that increases the exposure of banks to the risks associated with NBFIs and whoever they have lent to. As NBFIs fail, the financing provided by banks will not be repaid and they will thus have to absorb losses associated with the lending of the NBFIs. So, while it appears that risk has left the banking system, it hasn’t. Ultimately, the liquidity and credit default risk of the non-bank sector is financed by bank deposits.

Furthermore, the opaqueness of the exposure of banks to risks in the shadow-banking sector may have issues for the wider financial system. In 2008, banks became wary of lending to each other during the financial crisis because they didn’t know the exposure of counterparty institutions to losses from securitised debt instruments. Now, as more and more banks reveal exposures to NBFIs, concerns about the unknown position of other banks may produce a repeat of the credit crunch which occurred then. A seizing up of credit markets will worsen any downturn. However, unlike 2008, the financial resources available to central banks and governments to deal with any consequences are severely limited.

Only time and the path of the US economy will reveal the extent of any contagion related to lending in the shadow-banking sector. However, central banks are already worried about the risks associated with the shadow-banking sector and have been taking steps to identify and ameliorate them. Events in the USA over the past few weeks may accelerate the process and bring more of that lending within the regulatory cordon.

Articles

Academic paper

Data

Questions

  1. Explain why the need to hold more capital raises its cost for banks.
  2. Why does this reduce the lending they undertake?
  3. What is the attraction of ‘off-balance sheet transactions’ for regulated banks?
  4. Analyse the asymmetric information that banks face when providing liquidity to non-bank financial institutions (NBFIs).
  5. Examine the dangers for the financial system associated with regulated banks’ exposure to NBFIs?
  6. Discuss some policy recommendations regarding bank lending to NBFIs.
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What do ticket resellers and parents have in common?

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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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.