Category: Essential Economics for Business: Ch 02

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Holy Mackerel! Soaring fish prices


The prices of many species of fish have risen in recent months. Coastal pelagic fish, such as mackerel, herring and sardines have risen especially rapidly. Mackerel, once seen as a cheap source of protein, is no longer quite such a ‘bargain’.

From January 2023 to May 2026, the international price index of pelagic fish rose by 69%. In 2025, UK supermarket fresh, chilled smoked and tinned mackerel prices rose by an average of 25%; and over the first part of 2026, some tinned mackerel product lines have increased by as much 55%. In February 2026, Waitrose announced that it would suspend sales of fresh and chilled mackerel and tinned mackerel once current stocks had been cleared. It cited overfishing and sustainability concerns.

Supply and demand

But why have mackerel prices risen so much? The price of fish is determined by demand and supply. So what has changed? The main changes have been on the supply side.

Supply.  Most of the world’s supply of mackerel comes from the Northeast Atlantic. These waters have been overfished for many years, thereby depleting the stock of the fish and reducing the amount of mackerel caught.

To arrest the decline and allow stocks to rebuild, the International Council for the Exploration of the Sea (ICES) recommended a quota of 174,357 tonnes for 2026. This would represent a 70% cut from 2025. The main fishing countries – Norway, the UK, the Faroe Islands and Iceland – eventually agreed to a quota of 299,010 tonnes: a cut of 48%. After a series of bilateral agreements between the four countries over access to each other’s waters, this resulted in the following quota shares: UK 30.55%, Norway 26.4%, Faroes 12% and Iceland 10.5%. The remaining 20.55% would be for the EU, Greenland and Russia.

Despite these other countries not being part of the deal, in May 2026 the EU agreed to reduce its catch by 48% too. Russia, however, set its own quota of 67,548 tonnes, which is 22.6% of the total 299,010 quota, above the 20.55% set aside for the EU, Russia and Greenland combined and almost almost five times Russia’s historic quota share! The UK, EU and Iceland responded by agreeing to bar Russian vessels carrying mackerel from entering their ports.

The quotas have added to the decline in supply, even though the aim is to increase supply in the future as stocks are rebuilt. In May this year, the Norwegian catch was down nearly 85% – well below the 48% reduction in the quota.

Demand.  Despite higher prices, demand has remained strong. Part of the reason is that demand is relatively inelastic. This is because, despite its increase in price, mackerel remains a relatively cheap fish and thus there is little option to switch to cheaper alternative fish. Indeed, with other fish going up in price, and meat too, some people may even switch to mackerel.

Another reason for strong demand is the growing market outside Europe, especially in southeast Asia, China, South Korea and Japan. In some of these countries, mackerel is seen as a luxury fish and people are prepared to pay higher prices, making demand relatively inelastic but at the other end of the market. In 2025, imports of frozen whole mackerel into the region rose by nearly 9%, despite rising prices.

However, Norwegian exports to the region have been falling, reflecting lower quotas in 2025 and lower still in 2026. This has further exacerbated the rise in price and intensified competition between Asian importers. For example, in July 2026, Korea sent a ‘mackerel envoy’ to Norway and other major exporters to seek to secure additional supplies.

The future

With supply restricted by declining stocks and tighter quotas, and with a price inelastic and growing demand, the high prices of mackerel in all forms look set to last – at least until stocks rebuild and quotas can be relaxed. But, with total quotas well above the level suggested by the ICES, rebuilding could take a long time.

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Data

  • Dashboards

    • European Market Observatory for Fisheries and Aquaculture Products (EUMOFA)

Questions

  1. Draw a supply and demand diagram to illustrate what has happened to mackerel prices.
  2. What is the effective price elasticity of supply of mackerel?
  3. Why is demand for mackerel relatively price inelastic in the UK, except when prices rise above a certain level?
  4. Why is demand for mackerel relatively price inelastic in certain Asian countries, such as Japan and South Korea?
  5. In which country is demand for mackerel likely to be more income elastic: the UK or Japan?
  6. Under what circumstances might the price of mackerel in five years’ time be (a) higher than now; (b) lower than now? What will determine which is more likely?
  7. Should other supermarkets follow Waitrose’s lead in stopping the sale of mackerel?
  8. What is the ‘tragedy of the commons’? Why is a common resource such as fish in the open seas likely to result in the tragedy?
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The global economic impacts of the war with Iran – update

With relentless bombing of Iran by Israel and the USA, and with Iranian counterattacks on Gulf states, the costs of the war are mounting. The most obvious are in terms of human lives, injuries and suffering. But there are significant economic costs too. Some of these are immediate, such as the rising price of oil and hence the costs of fuel, or the fall in stock market prices. Some will be longer term, depending on how the war develops. For example, prices could rise more generally as supply chains are disrupted.

The impacts will vary across the world and across markets. The most obvious markets to be affected are those where significant supply comes from the Persian Gulf. Approximately 20% of total global oil consumption passes through the Strait of Hormuz, which connects the Persian Gulf with the Arabian Sea and the Indian Ocean.

Oil prices rose considerably in the days following the start of the war on 28 February, with Brent crude, a key measure of international oil prices, rising from $71.3 on 27 February to a peak of $119.4 per barrel by the morning of 9 March – a rise of 67%. It was possible that they would rise even further in the short term. However, prices fell back substantially later on 9 March after G7 finance ministers declared that the group ‘stands ready’ to release oil from strategic reserves if needed. By late in the day, the price had fallen to below $85. (Click here for a PowerPoint of the chart.)

However, despite the announcement on 11 March that 32 countries had agreed to release 400m barrels of oil reserves, oil prices began rising again and reached $100 on 12 March after three tankers had been struck in the Gulf, two of them close to the Strait of Hormuz. With Iran pledging to keep the Strait closed, there were worries that the release of oil reserves would provide only temporary relief. Just over 20m barrels of oil normally pass through the Strait of Hormuz. The 400m barrels released from storage is the equivalent, therefore, of only 20 days’ worth of lost oil from the Gulf.

Not only did oil prices rise, but the price became much more volatile as markets reacted to the news on a continuous basis. Intra-day fluctuations in oil prices of several percentage points became typical, reflecting shifting expectations. The second chart shows daily fluctuations, with the highest and lowest prices for each day shown, along with the closing price. (Click here for a PowerPoint.)

The biggest fluctuation had been on 9 March when fears of the closing of the Strait of Hormuz saw the price of Brent crude rising to nearly $120 but falling to around $84 later in the day (a fall of around 30%) after the G7 announcement about releasing reserves.

There was another big fluctuation on 23 March. The previous day (Sunday), President Trump threatened to bomb Iran’s power plants if Iran did not allow free passage of ships through the Strait of Hormuz. Iran threatened to retaliate by striking Gulf countries’ energy and water systems. In early trading on Monday 23rd, Brent crude rose to over $115 per barrel. But later that day, Trump said that there had been constructive talks between the USA and Iran. The oil price immediately dropped to around $96 – a fall of 17% – before settling at around $100.

Rising oil prices will drive up inflation. For those countries with a heavy dependence on Gulf oil, particularly countries in Asia, there could be significant supply problems. For oil exporters in the Persian Gulf, with tankers unable to traverse the Strait of Hormuz, the economic impact is huge. Oil exporters outside the Gulf, such as Russia, Norway and Canada, however, will gain from the higher prices. Clearly the size of these effects will depend on how long the conflict continues and how long the Strait of Hormuz remains closed.

And it is not just oil that is affected. Other products, such as liquified natural gas (LNG), petrochemicals, industrial materials, fertilizers for food production, medicines, helium for microchip production, metals and minerals are transported through the Strait of Hormuz. Gulf countries import much of their food through the Strait. On 18 March, Israel struck Iran’s huge South Pars gas field off the Gulf coast. This is the largest gas field in the world and is a major source of export revenue for Iran. Iran responded by striking the Qatari gas hub in Ras Laffan. Donald Trump responded by threatening to ‘blow up’ the entire Iranian South Pars gas field if Iran made further strikes on Qatar. The effect of this escalation was to drive oil and gas prices up further. By the week ending 20 March, the oil price closed at just over $112 per barrel.

Cuts in supplies of oil and other products represent an adverse supply shock. Such shocks push up prices (cost-push inflation), while adversely affecting aggregate output. This can lead to stagflation – a combination of higher inflation and stagnation or even falling output. Central banks with a simple mandate to keep inflation to a target are likely to raise interest rates, or at least delay in reducing them. In the USA, with a dual mandate of controlling inflation but also maximising employment, the response may be less deflationary, depending on the judgement of the Federal Reserve.

Uncertainty

There is great uncertainty about how long the conflict will last. There is also a lack of clarity and consistency from the US administration about its war aims. This uncertainty has affected financial markets, which have seen considerable volatility. Stock markets have seen widespread falls, with airline, travel and AI-heavy stocks being particularly vulnerable.

If the war is concluded relatively swiftly, the economic effects could be relatively small. If the war continues, and especially if the Gulf countries are drawn further into the conflict and if the conflict spreads to other countries, the economic effects could be much more substantial. A prolonged conflict could see oil prices remaining above $100 per barrel, potentially increasing global inflation by 1 percentage point or more. This would slow or halt the move by central banks to cut rates and thereby reduce global economic growth – potentially, as we have seen, leading to stagflation.

The uncertainty was reflected in the decision of the Fed to keep interest rates unchanged at its meeting on 17/18 March. The Fed has the twin targets of keeping inflation close to 2% and maximising employment. Fed Chair, Jay Powell, acknowledged the current tension between the two goals: ‘upward risks for inflation and downward risks for employment, and that puts us in a difficult situation’. He also recognised that the future for inflation and the economy was highly uncertain as the war developed. This made interest rate setting difficult.

Then there is the issue of a potential new international refugee crisis. If the economic and political system in Iran deteriorates rapidly, this could trigger a wave of migration to neighbouring countries, such as Turkey, already hosting large numbers of refugees. Many could seek sanctuary further afield in Europe, with several countries already facing a backlash against immigration. The political and economic effects of this on host countries could be significant – but as yet, highly uncertain.

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Questions

  1. Who are the biggest gainers and losers from disruption to oil supplies from the Persian Gulf?
  2. Illustrate the effect of the current oil price shock on an aggregate demand and supply diagram (either static or dynamic).
  3. Why is the Iranian war likely to be less damaging to the European economy than the Ukrainian war has been?
  4. Why have AI-related stock prices been vulnerable to the uncertainty caused by the Iranian war?
  5. How have the Bank of England and the Federal Reserve Bank responded to higher oil prices and the broader economic effects of the war? Why might their responses be different in the coming months?
  6. What is the likely impact of the Iranian war on global economic recovery?
  7. How might the Iranian war affect global economic alliances?
  8. How is the current oil price shock likely to affect the eurozone? Will it be different from the oil price shock that followed the Russian invasion of Ukraine?
  9. What are the likely economic effects of large-scale migration caused by the war?
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The precious metals roller coaster

Precious metals, such as gold, silver and platinum, are seen as safe havens by investors in uncertain times. With the on-off nature of Donald Trump’s tariffs, with ongoing wars, such as the war in Ukraine, and with threats of US action in Iran, with inflation slow to fall and pressure by the Trump administration on the Federal Reserve to make precipitant cuts in interest rates, investors have flocked to precious metals.

Precious metals peaked in late January 2026. Compared with just four months earlier, gold was up by 48%, platinum by 76% and silver by a massive 162%. Silver and platinum were also boosted by their industrial uses. Silver has excellent conductive properties and is used for electronics, AI, solar energy (photovoltaic cells), chemical catalysts and medical equipment. Over 50% of its consumption is for industrial purposes. Platinum is used as a catalyst in catalytic converters to reduce exhaust emissions, in medical devices, chemical processing, oil refining, electronics and glass manufacturing.

The rise was fuelled by speculation, which gathered momentum in December and January. But then the prices of all three metals fell dramatically on Friday 30 January and a bit more on 2 February. Despite a moderate bounce back on 3 February, the prices then fell again and by the end of 5 February, gold had fallen by 15%, platinum by 30% and silver by a massive 42% from the peak.

Figure 1 illustrates the effect of speculation on the rise in price of a precious metal, such as silver. Assume that demand rises from D0 to D1 for the reasons given above. Equilibrium moves from point a to point b and the price rises from P1 to P2. Seeing the price rising, holders of the metal wait until the price rises further before selling. Supply shifts from S1 to S2. Potential purchasers of the metal, anticipating a further rise in price, buy now before the price does rise. Demand shifts from D1 to D2. As a result, equilibrium moves from point b to point c and price rises to P3.

Figure 2 illustrates the effect of speculation on the subsequent fall in prices triggered by a belief that price will fall. Speculative selling shifts the supply curve from S2 to S3. Potential demanders hold back and the demand curve shifts from D2 to D3. Equilibrium moves to point d and price falls from P3 to P4. (Click here for a PowerPoint of the two figures.)

But why did prices fall so dramatically? The first reason was that analysts were beginning to argue that the exuberance of investors had led the price of all three metals to overshoot the fundamental balance of supply and demand. Once a tipping point arrived, people sold quickly to lock in the gains they had made over previous weeks. This profit taking caused prices to plummet as speculation of further falls drove prices lower.

So what was the tipping point? This was the appointment by Donald Trump of Kevin Warsh as the new Chair of the Federal Reserve to take over from Jerome Powell when his tenure comes to an end in May this year.

It was expected that Trump would appoint someone much more willing to cut interest rates and this worried investors, who feared that inflation would rise again. This uncertainty drove demand for precious metals, which are seen as a safe haven. But Kevin Walsh is viewed as hawkish on monetary policy and less likely to slash interest rates than other possible choices for Chair. This triggered the fall in precious metal prices.

But the main factors that drove the demand for the metals still exist. There is still uncertainty, still an increased demand from central banks for gold, still a growing demand for silver and platinum for industrial uses. The next day, 3 February, it seemed that the prices of all three metals had over-corrected. Investors started buying again at the lower prices and consequently prices rose again – once more fuelled by speculation. Gold rose by 6.1%, platinum by 7.9% and silver by 11.6%.

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Questions

  1. What has happened to the price of silver since this blog was written? Use a demand and supply diagram to illustrate this.
  2. Identify the factors that affect the demand for and supply of (a) silver; (b) gold.
  3. What determines the elasticity of supply of silver (a) in total; (b) to the market?
  4. Choose another commodity other than the three metals considered in this blog. Find out what has happened to their prices over the past 12 months and explain why these price movements have occurred.
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AI stock: still under priced or a speculative bubble?

The share prices of various AI-related companies have soared in this past year. Recently, however, they have fallen – in some cases dramatically. Is this a classic case of a bubble that is bursting, or at least deflating?

Take the case of NVIDIA, the world’s most valuable company, with a market capitalisation of around $4.2 trillion (at current share prices). It designs and produces graphics cards and is a major player in AI. From a low of $86.62 April this year, its share price rose to a peak of $212.19 on 29 October. But then began falling as talk grew of an AI bubble. Despite news on 19 November that its 2025 Q3 earnings were up 62% to $57.0bn, beating estimates by 4%, its share price, after a temporary rise, began falling again. By 21 November, it was trading at around $180.

Other AI-related stocks have seen much bigger rises and falls. One of the biggest requirements for an AI revolution is data processing, which uses huge amounts of electricity. Massive data centres are being set up around the world. Several AI-related companies have been building such data centres. Some were initially focused largely on ‘mining’ bitcoin and other cryptocurrencies (see the blog, Trump and the market for crypto). But many are now changing focus to providing processing power for AI.

Take the case of the Canadian company, Bitfarms Ltd. As it says on its site: ‘With access to multiple energy sources and strategic locations, our U.S. data centers support both mining and high-performance computing growth opportunities’. Bitfarms’ share price was around CAD1.78 in early August this year. By 15 October, it had reached CAD9.27 – a 421% increase. It then began falling and by 24 November was CAD3.42 – a decline of over 63%.

Data centres do have huge profit potential as the demand for AI increases. Many analysts are arguing that the current share price of data centres undervalues their potential. But current profits of such companies are still relatively low, or they are currently loss making. This then raises the question of how much the demand for shares, and hence their price, depends on current profits or future potential. And a lot here depends on sentiment.

If people are optimistic, they will buy and this will lead to speculation that drives up the share price. If sentiment then turns and people believe that the share price is overvalued, with future profits too uncertain or less than previously thought, or if they simply believe that the share price has overshot the value that reflects a realistic profit potential, they will sell and this will lead to speculation that drives down the share price

The dot.com bubble of the late 1990s/early 2000s is a case in point. There was a stock market bubble from roughly 1995 to 2001, where speculative investment in internet-based companies caused their stock values to surge, peaking in late 1999/early 2000. There was then a dramatic crash. But then years later, many of these companies’ share prices had risen well above their peak in 2000.

Take the case of Amazon. In June 1997, its share price was $0.08. By mid-December 1999, it had reached $5.65. It then fell, bottoming out at $0.30 in September 2001. The dot-com bubble had burst.

But the potential foreseen in many of these new internet companies was not wrong. After 2001, Amazon’s share price began rising once more. Today, Amazon’s shares are trading at over $200 – the precise value again being driven largely by the company’s performance and potential and by sentiment.

So is the boom in AI-related stock a bubble? Given that the demand for AI is likely to continue growing rapidly, it is likely that the share price of companies providing components and infrastructure for AI is likely to continue growing in the long term. But just how far their share prices will fall in the short term is hard to call. Sentiment is a fickle thing.

Articles

Questions

  1. Using a supply and demand diagram, illustrate how speculation can drive up the share price of a company and then result in it falling.
  2. What is meant by overshooting in a market? What is the role of speculation in this process?
  3. Does a rapid rise in the price of an asset always indicate a bubble? Explain.
  4. What are the arguments for suggesting that markets are/are not experiencing an AI share price bubble? Does it depend of what part of the AI market is being considered?
  5. What is meant by the market capitalisation of a company? Is it a good basis for deciding whether or not a company’s share price is a true reflection of the company’s worth? What other information would you require?
  6. Find out what has been happening to the price of Bitcoin. What factors determine the price of Bitcoin? Do these factors make the price inherently unstable?
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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.