Tag: behavioural economics

Posted on

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?
Posted on

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.
Posted on

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

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

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

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

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

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

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

Benefits of hybrid working

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

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

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

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

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

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

Problems of hybrid working

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

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

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

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

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

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

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

Improving hybrid working

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

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

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

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

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

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

Articles

Data

Questions

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

Artificial intelligence in pricing: a double-edged sword?

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

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

How AI pricing tools can enhance competition

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

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

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

How AI pricing tools can undermine competition

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

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

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

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

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

What does this mean for competition policy?

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

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

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

Articles

Questions

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

Subscription traps: policy responses to a market failure

Policy makers have become increasingly concerned about what the US Federal Trade Commission (FTC) describe as ‘negative option marketing’. These are marketing deals that contain the following feature:

a term or condition that allows a seller to interpret a customer’s silence, or failure to take affirmative action, as an acceptance of an offer.

For example, companies such as Amazon, Apple, Spotify and Netflix may offer students a 3-month free trial or 3-month introductory offer (at a special lower price) for movie and music streaming services. However, many of these subscription contracts contain an example of negative option marketing – auto renewal clauses.

Problems with auto-renewal contracts

The inclusion of an auto-renewal clause means that if a customer fails to cancel the subscription at the end of the three-month period, the subscription automatically reverts to its full price. The full-price contract then continues to roll-over indefinitely unless the customer takes a pre-specified action to terminate the deal. Inattentive consumers could end up paying subscription prices that far exceed their willingness to pay.

Auto-renewal contracts are not just an issue with free trials/introductory offers. Some people may purchase subscription contracts at the full price and then forget about them. These consumers could end up paying fees for months after they have effectively stopped using the service.

Another potential problem with the use of auto-renewal contracts, is businesses deliberately making the cancellation process more complex than it needs to be. In many cases it takes just one click to sign up for the subscription, but multiple clicks through a series of menus to cancel. Some businesses do not provide consumers with the option to cancel online and, instead, they are forced to phone a number that is often very busy.

Effects on consumer welfare

To what extent do these problems caused by auto-renewal reduce consumer welfare? What evidence do we have?

Research by Citizens Advice found that just over one in four people (26 per cent) had signed up to a subscription by accident. 58 per cent of this group forgot to cancel a free trial, while 21 per cent did not realise that the free trial would automatically roll-over to a full-price subscription. This seems to be a particular issue for those on low incomes with 46 per cent of people on Universal Credit signing up to a subscription by accident.

Analysis by the Department for Business and Trade (DBT) has tried to estimate the value of these unwanted subscriptions. The study found that consumers spent £602 million on unwanted subscriptions where a free or reduced-price trial had been rolled over to the full price. The same study also found that £573 million was spent on subscriptions that people had forgotten about.

One in five people in the Citizens Advice study who tried to cancel a subscription found the process difficult. The DBT estimates that cancellation difficulties led to £382 million being spent on unwanted subscriptions.

UK Government response

In response to these findings, the government introduced the Digital Markets, Competition and Consumers Bill into Parliament in April 2023.

Provisions in the Bill seek to standardise the information that businesses must provide consumers before they sign up for subscription contracts. For example, in the future, firms will have to display prominently (a) any auto-renewal provisions, (b) whether the price increases after a specified period, (c) details about how consumers can terminate the contract and (d) cooling-off periods.

The Bill also stipulates that businesses will have to provide consumers with reminders when a free/reduced-price trial period is about to end and/or a subscription is about to renew automatically. They must also make it easy to exit contracts and remove any unnecessary steps.

The government initially considered an additional measure that would force businesses to provide consumers with the option to take out any subscription without auto-renewal.

Citizens Advice strongly supported this policy. They argued that not only should consumers be given the choice, but that auto-renewal should not be the default i.e. people would have to opt-in to auto-renewal subscriptions.

However, after the consultation process for the Bill, the government decided against introducing this additional measure. Businesses have also argued that the other elements of the policy are too prescriptive.

Articles

Government documents

Questions

  1. Outline some theories from behavioural economics that might help to explain why people sometimes end up with unwanted subscriptions.
  2. Discuss some of the potential benefits of auto-renewal subscriptions for both consumers and firms.
  3. Using behavioural economic theory, explain some of the potential disadvantages for businesses of using auto-renewal subscriptions.
  4. When businesses deliberately make the cancellation process more complex than it needs to be, it is referred to as an example of ‘sludge’. Explain the meaning of ‘sludge’ in more detail, referring to some different examples in your answer.
  5. What difference do you think it would make to the number of people signing up for auto-renewal subscriptions if you had to opt-in as opposed to opting out? Explain your answer.
  6. Another policy would be to force firms to cancel subscription contracts if there is evidence that consumers have not used the service for a long period of time. Discuss some of the advantages and disadvantages of this measure.
  7. Explain what are meant by ‘dark patterns’. How may the choice architecture on some sites actually hinder consumer choice?