Category: Economics: Ch 26

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Will AI make the world less equal?

With businesses increasing their use of AI, this is likely to have significant effects on employment. But how will this affect the distribution of income, both within countries and between countries?

In some ways, AI is likely to increase inequality within countries as it displaces low-skilled workers and enhances the productivity of higher-skilled workers. In other ways, it could reduce inequality by allowing lower-skilled workers to increase their productivity, while displacing some higher-skilled workers and managers through the increased adoption of automated processes.

The effect of AI on the distribution of income between countries will depend crucially on its accessibility. If it is widely available to low-income countries, it could significantly enhance the productivity of small businesses and workers in such countries and help to reduce the income gap with the richer world. If the gains in such countries, however, are largely experienced by multinational companies, whether in mines and plantations, or in labour-intensive industries, such as garment production, few of the gains may accrue to workers and global inequality may increase.

Redistribution within a country

The deployment of AI may result in labour displacement. AI is likely to replace both manual and white-collar jobs that involve straightforward and repetitive tasks. These include: routine clerical work, such as data entry, filing and scheduling; paralegal work, contract drafting and legal research; consulting, business research and market analysis; accounting and bookkeeping; financial trading; proofreading, copy mark-up and translation; graphic design; machine operation; warehouse work, where AI-enabled warehouse robots do many receiving, sorting, stacking, retrieval, carrying and loading tasks (e.g. Amazon’s Sequoia robotic system); basic coding or document sifting; market research and advertising design; call-centre work, such as enquiry handling, sales, telemarketing and customer service; hospitality reception; sales cashiers in supermarkets and stores; analysis of health data and diagnosis. Such jobs can all be performed by AI assistants, AI assisted robots or chat bots.

Women are likely to be disproportionately affected because they perform a higher share of the administrative and service roles most exposed to AI.

Workers displaced by AI may find that they can find employment only in lower-paid jobs. Examples include direct customer-facing roles, such as bar staff, shop assistants, hairdressers and nail and beauty consultants.

Such job displacement by AI is likely to redistribute income from relatively low-skilled labour to capital: a redistribution from wages to profits. This will tend to lead to greater inequality.

AI is also likely to lead to a redistribution of income towards certain types of high-skilled labour that are difficult to replace with AI but which could be enhanced by it. Take the case of skilled traders, such as plumbers, electricians and carpenters. They might be able to use AI in their work to enhance their productivity, through diagnosis, planning, problem-solving, measurement, etc. but the AI would not displace them. Instead, it could increase their incomes by allowing them to do their work more efficiently or effectively and thus increase their output per hour and enhance their hourly reward. Another example is architecture, where AI can automate repetitive tasks and open up new design possibilities, allowing architects to focus on creativity, flexibility, aesthetics, empathy with clients and ethical decision-making.

An important distinction is between disembodied and embodied AI investment. Disembodied AI investment could include AI ‘assistants’, such as ChatGPT and other software that can be used in existing jobs to enhance productivity. Such investment can usually be rolled out relatively quickly. Although the extra productivity may allow some reduction in the number of workers, disembodied AI investment is likely to be less disruptive than embodied AI investment. The latter includes robotics and automation, where workers are replaced by machines. This would require more investment and may be slower to be adopted.

Then there are jobs that will be created by AI. These include prompt engineers, who develop questions and prompt techniques to optimise AI output; health tech experts, who help organisations implement new medical AI products; AI educators, who train people in the uses of AI in the workplace; ethics advisors, who help companies ensure that their uses of AI are aligned with their values, responsibilities and goals; and cybersecurity experts who put systems in place to prevent AI stealing sensitive information. Such jobs may be relatively highly paid.

In other cases, the gains from AI in employment are likely to accrue mainly to the consumer, with probably little change in the incomes of the workers themselves. This is particularly the case in parts of the public sector where wages/salaries are only very loosely related to productivity and where a large part of the work involves providing a personal service. For example, health professionals’ productivity could be enhanced by AI, which could allow faster and more accurate diagnosis, more efficient monitoring and greater accuracy in surgery. The main gainers would be the patients, with probably little change in the incomes of the health professionals themselves. Teachers’ productivity could be improved by allowing more rapid and efficient marking, preparation of materials and record keeping, allowing more time to be spent with students. Again, the main gainers would be the students, with little change in teachers’ incomes. Other jobs in this category include social workers, therapists, solicitors and barristers, HR specialists, senior managers and musicians.

Thus there is likely to be a distribution away from lower-skilled workers to both capital and higher-skilled workers who can use AI, to people who work in new jobs created by AI and to the consumers of certain services.

AI will accelerate productivity growth and, with it, GDP growth, but will probably displace workers faster than new roles emerge. This is likely to increase inequality and be a major challenge for society. Can the labour market adapt? Could the effects be modified if people moved to a four- or three-day week? Will governments introduce statutory limits to weekly working hours? Will training and education adapt to the new demands of employers?

Redistribution between countries

AI threatens to widen the global rich–poor divide. It will give wealthier nations a productivity and innovation edge, which could displace low-skilled jobs in low-income nations. Labour-intensive production could be replaced by automated production, with the capital owned by the multinational companies of just a few countries, such as the USA and China, which between them account for 40% of global corporate AI R&D spending. For some companies, it would make sense to relocate production to rich countries, or certain wealthier developing countries, with better digital infrastructure, advanced data systems and more reliable power supply.

For other companies, however, production might still be based in low-income countries to take advantage of low-cost local materials. But there would still be a redistribution from wages in such countries to the profits of multinationals.

But it is not just in manufacturing where low-income countries are vulnerable to the integration of AI. Several countries, such as India, the Philippines, Mexico and Egypt have seen considerable investment in call centres and IT services for business process outsourcing and customer services. AI now poses a threat to employment in this industry as it has the potential to replace large numbers of workers.

AI-related job losses could exacerbate unemployment and deepen poverty in poorer countries, which, with limited resources, limited training and underdeveloped social protection systems, are less equipped to absorb economic and social shocks. This will further widen the global divide. In the case of embodied AI investment, it may only be possible in low-income countries through multinational investment and could displace many traditional jobs, with much of the benefit going in additional multinational profit.

But it is not all bad news for low-income countries. AI-driven innovations in healthcare, education, and agriculture, if adopted in poor countries, can make a significant contribution to raising living standards and can slow, or even reverse, the widening gap between rich and poor nations. Some of the greatest potential is in small-scale agriculture. Smallholders can boost crop yields though precision farming powered by AI; AI tools can help farmers buy seeds, fertilisers and animals and sell their produce at optimum times and prices; AI-enabled education tools can help farmers learn new techniques.

Articles

Questions

  1. What types of job are most vulnerable to AI?
  2. How will AI change the comparative advantage of low-income countries and what effect will it be likely to have on the pattern of global trade?
  3. Assess alternative policies that governments in high-income countries can adopt to offset the growth in inequality caused by the increasing use of AI.
  4. What policies can governments in low-income countries or aid agencies adopt to offset the growth in inequality within low-income countries and between high- and low-income countries?
  5. How might the growth of AI affect your own approach to career development?
  6. Is AI likely to increase or decrease economic power? Explain.
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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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A single European market in banking

Large European banks call for further integration, but is it in consumers’ interests?

Those of a certain age may remember the fanfare which heralded the introduction of the Single European market (SEM) on 1 January 1993. It promised the removal of internal barriers to the movement of goods, services, capital and people. One sector that was noticeably absent from the single market, however, was banking.

Moves towards banking union only started after the global financial crisis in 2008. However, as a report published on the 2 September 2025 by the Association of Financial Markets in Europe (AFME) highlights, the institutional frameworks of banking in the EU are still deeply fragmented – the promised integration through the European Banking Union (EBU) is still incomplete. This has put European banks at a competitive disadvantage in global markets compared with rivals from the USA and Asia, thereby reducing their profitability and growth prospects. The report called on the European Central Bank (ECB) and national regulatory authorities to remove hurdles to cross-border banking services in the EU. This would enhance the strategic position of European banks.

In this blog we will trace the development of the EBU and analyse the current state of integration. We discuss the AFME proposals for achieving greater integration and highlight their benefits for large banks. We also analyse the barriers which limit full integration and examine the risks that retail customers might see few benefits from the proposed changes.

What is meant by European Banking Union (EBU)?

The 1993 Single European Market (SEM) in goods and services removed internal barriers to the movement of goods, services, capital and people within the EU. As part of this, there were harmonised standards and regulations for goods and services, no capital controls, mutual recognition of professional qualifications and common regulations on consumer protection, product safety, environmental protection and labour rights.

This integration of previously restricted domestic markets was designed to boost economic growth, employment and competitiveness by increasing trade and investment flows. Offering consumers greater choice would expose firms to greater competition. This would drive down prices and encourage greater efficiency and innovation. It has generally achieved these goals across many industries.

However, banking was excluded from integration. The 1985 White Paper, Completing the Internal Market, proposed the liberalisation of financial services, but banking remained regulated at the national level. This was influenced by interrelated economic, political and institutional forces, national sovereignty and political sensitivities, fragmented regulation and concerns about risk.

Even as the EU moved towards economic and monetary union (EMU) during the 1990s, there was no discussion of integration for the banking industry. However, that changed following the 2008 financial crisis and 2011 eurozone crisis. Both episodes exposed vulnerabilities in the EU banking system which required taxpayer support. It was proposed that deeper integration of the banking sector would ensure its stability and resilience. This stimulated moves towards European Banking Union (EBU), starting with the European Council agreeing its creation in 2012. There are three institutional pillars to the Union:

  1. The Single Supervisory Mechanism (2014) for systemically important financial institutions (SIFIs) ensures consistent oversight. SIFIs are banks with over €30 billion of liabilities or 20% of national GDP.
  2. The Single Resolution Mechanism (2016) manages the orderly resolution of failing banks with minimal costs to taxpayers. There is a central board for resolution decisions and a fund financed by the banking industry to support resolution actions.
  3. A European Deposit Insurance Scheme (still under negotiation) is proposed to protect depositors uniformly across the banking union against bank default.


The Union is intended to operate under a harmonised set of EU laws, known as the ‘Single Rulebook’, which includes implementing the BASEL III capital requirements, regulating national deposit insurance and setting rules for managing failing banks.

What is the state of integration at present?

Moves towards European Banking Union (EBU) have contributed to enhancing the resilience of the European banking system. This was one of its major objectives. European banks are much more secure having increased capital and liquidity levels, reduced credit risks and become less reliant on state-aid. They are also less profitable.

The AFME report points to remaining gaps in Banking Union which raise the cost for banks offering cross-border retail banking within the EU and limit the incentive to do so. The report identifies four such gaps.

1. Ring fencing.  Although there is a single supervisory mechanism for large systemically important institutions, since the financial crisis national regulators have implemented ‘ring-fencing’. This aims to protect retail banking activities from riskier investment banking. Ring-fencing retains liquidity, dividends and other bank assets within national borders to protect their retail banking sectors from contagion. The ECB estimates €225 billion of capital and €250 billion of liquidity is trapped by such national restrictions. Further, unharmonized and unpredictable use of capital buffers adds complexity for capital management at a multinational level. This particularly impacts large institutions. Banks’ cross-border activities are impeded since they are restricted in the way they can use capital and liquidity across the bloc.

The report argues that the stringent requirements of the ECB and the multiple layers of macroprudential requirements imposed at national level have led to an unnecessarily high level of capital. This disadvantages large European banks compared to their international competitors.

2. Impediments to cross-border M&As in banking within the EU.  This is due to cumbersome authorisation processes, involving multiple authorities at both national and supra-national level. Further, national authorities may interfere in the process of M&As in a bid to prevent domestic banks being acquired by ones from other parts of the EU. A recent example is UniCredit’s bid for Germany’s Commerzbank, which the German government opposes. These characteristics restrict opportunities for consolidation and efficiency gains for European banks.

The AFME report estimates that once eurozone banks grow beyond €450 billion in total assets, they suffer from negative synergies putting them at a competitive disadvantage to global competitors. Indeed, US banks are able to leverage scale economies from their domestic market to enter large EU markets. An example is JP Morgan’s entry into multiple EU markets through its Chase brand.

3. Contributions to the Single Resolution Fund (SRF) are complex and lack transparency.  This makes it difficult for banks to predict future commitments. The fund itself and its target level were determined at a time when banks had low buffers. Since then, European banks have raised their loss absorbing capacity and the AFME report proposes that further increases in contributions to the fund need to be carefully considered and reviewed.

4. The Deposit Guarantee Scheme remains unimplemented and there are still differences in national schemes.  This situation creates uncertainty for banks, which would like the European scheme for large systemically important institutions to be implemented fully.

These AFME proposals focus on the aspects of banking union which benefit large European institutions in their strategic competition with global rivals. These aspects would create ‘European’ banks as opposed to ‘national’ ones. This would give them the scale to be ‘champions’ in global competition. In particular, the large banks want lower capital requirements and the relaxation of national ring-fencing for retail banking to allow them greater freedom to achieve scale and scope economies across the bloc.

To what extent this will benefit retail customers, however, is debateable.

Will retail banking customers benefit?

Retail banking across Europe remains deeply fragmented, with significant price differentials from country to country. The following table illustrates pricing differentials for two retail products – loans and mortgages – across a sample of EU countries for July 2025.


The data show a range of average interest rates offered across the countries with a range of 5.03% for loans to households and 0.92% for new mortgages. These price differentials reflect a broad array of factors, not least the different institutional legal and risk characteristics of the national markets. They also reflect varying degrees of competition and the lack of cross-border trade in retail banking products. Retail banking remains a largely domestic industry within the EU. Cross-border banking services remain a marginal activity with non-domestic retail deposits rising by just 0.5% and non-domestic retail loans rising by just 0.3% between 2016 and 2024.

There are both natural and policy-induced barriers, which means that retail banking will remain largely segmented by nation.

On the demand-side, retail banking is largely a relational rather than a transactional service, with consumption taking place over a long time-period with significant financial risks attached. Even with deposit insurance and a lender of last resort (the central bank), consumers exhibit significant loss aversion in their use of retail banking services. Consequently, trust and confidence are important characteristics for consumers and that means they are likely to prefer to use familiar domestic institutions.

Further, perceptions about switching costs mean that consumers are reluctant to change suppliers. Such costs are exacerbated by language, cultural and legal differences between European countries, which can make the perceived costs of banking beyond national boundaries prohibitively expensive and create a preference for local institutions.

Consumer preferences can also create idiosyncratic market structures for retail banking services in particular countries. For instance, in several countries across the EU, notably Germany, mutualised credit unions account for significant shares of retail banking. This may limit the potential for foreign banks to penetrate Europe’s largest market.

There are also policy-induced obstacles to cross-border retail banking which operate on the demand-side. These include discriminatory tax treatment of foreign financial services which deters their purchase by consumers. Further, there are still eight different currencies used in the EU across the 27 member states (Denmark, Poland and Sweden are three significant examples). This creates costs and risks associated with currency exchange for consumers that may deter their use of cross-border deposits and loans. The full adoption of a single currency across the EU seems a long way off, which will limit the potential for a single banking market, particularly in the retail segment.

Retail banking as a public utility

Some argue that retail banking is a public utility and should be regulated as such. It has a simple business model, taking deposits, making payments and making loans. Like other utilities, such as water and energy, retail banking is an essential service for the smooth functioning of the economy and society. Like other utilities, bank failures create severe problems for the economy and society.

Since the financial crisis, stability in retail banking has been much more highly valued. In the period preceding the crisis, banks had used retail deposits to cross-subsidise their risky investment banking. The bank failures that resulted from this had severe economic consequences. The danger today is that by relaxing capital and liquidity restrictions too much, large banks may once again engage in risky behaviour, subsidised by retail banking – for example, by engaging in cross-border M&As. These may benefit their shareholders but provide little benefit to retail customers.

Further, allowing these large banks freedom to move funds around the bloc may lead to capital being concentrated in the most profitable markets, leaving less profitable markets / countries underserved. Retail banking, as a public utility, should be required to provide services there.

Who ultimately benefits?

The integration of banking services in the EU has progressed since the financial crisis, producing a more resilient system. However, there are features of retail banking which mean that integration which benefits consumers may be difficult to achieve.

Addressing the policy gaps identified by the AFME report may benefit large European banks by facilitating the scale economies to make them competitive internationally. However, until consumers are prepared, or able, to source banking services beyond national borders, they will see little benefit from European Banking Union (EBU) through lower prices and/or better service. The nature of retail banking in the EU suggests that this is unlikely any time soon.

Furthermore, since retail banking exhibits features of a public utility, regulators need to be wary of permitting the type of behaviour by large institutions which creates dangerous systemic risk. The worry is that, in the drive to create ‘European Champions’ in banking, regulators ignore the potential impact on retail customers.

Articles

Book

Report

Data and Information

Questions

  1. Using an average cost (AC) schedule, illustrate the efficiency benefits for large European banks from banking union.
  2. Analyse the sources of efficiency gains that European banks can gain from cross-border M&As.
  3. Explain how European retail banking customers could gain from such efficiency.
  4. Analyse why they may not.
  5. Analyse whether retail banking in Europe needs to be regulated as a public utility.
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Rising global uncertainty and its effects

In a blog in October 2024, we looked at global uncertainty and how it can be captured in a World Uncertainty Index. The blog stated that ‘We continue to live through incredibly turbulent times. In the past decade or so we have experienced a global financial crisis, a global health emergency, seen the UK’s departure from the European Union, and witnessed increasing levels of geopolitical tension and conflict’.

Since then, Donald Trump has been elected for a second term and has introduced sweeping tariffs. What is more, the tariffs announced on so-called ‘Liberation Day‘ have not remained fixed, but have fluctuated with negotiations and threatened retaliation. The resulting uncertainty makes it very hard for businesses to plan and many have been unwilling to commit to investment decisions. The uncertainty has been compounded by geopolitical events, such as the continuing war in Ukraine, the war in Gaza and the June 13 Israeli attack on Iran.

The World Uncertainty Index (WUI) tracks uncertainty around the world by applying a form of text mining known as ‘term frequency’ to the country reports produced by the Economist Intelligence Unit (EIU). The words searched for are ‘uncertain’, ‘uncertainty’ and ‘uncertainties’ and the number of times they occur as percentage of the total words is recorded. To produce the WUI this figure is then multiplied by 1m. A higher WUI number indicates a greater level of uncertainty.

The monthly global average WUI is shown in Chart 1 (click here for a PowerPoint). It is based on 71 countries. Since 2008 the WUI has averaged a little over 23 000: i.e. 2.3 per cent of the text in EIU reports contains the word ‘uncertainty’ or a close variant. In May 2025, it was almost 79 000 – the highest since the index was first complied in 2008. The previous highest was in March 2020, at the start of the COVID-19 outbreak, when the index rose to just over 56 000.

The second chart shows the World Trade Uncertainty Index (WTUI), published on the same site as the WUI (click here for a PowerPoint). The method adopted in its construction therefore mirrors that for the WUI but counts the number of times in EIU country reports ‘uncertainty’ is mentioned within proximity to a word related to trade, such as ‘protectionism’, ‘NAFTA’, ‘tariff’, ‘trade’, ‘UNCTAD’ or ‘WTO.’

The chart shows that in May 2025, the WTUI had risen to just over 23 000 – the second highest since December 2019, when President Trump imposed a new round of tariffs on Chinese imports and announced that he would restore steel tariffs on Brazil and Argentina. Since 2008, the WTUI has averaged just 2228.

It remains to be seen whether more stability in trade relations and geopolitics will allow WUI and WUTI to decline once more, or whether greater instability will simply lead to greater uncertainty, with damaging consequences for investment and also for consumption and employment.

Articles

Uncertainty Indices

Questions

  1. Explain what is meant by ‘text mining’. What are its strengths and weaknesses in assessing business, consumer and trade uncertainty?
  2. Explain how the UK Monthly EPU Index is derived.
  3. Why has uncertainty increased so dramatically since the start of 2025?
  4. Compare indices based on text mining with confidence indices.
  5. Plot consumer and business/industry confidence indicators for the past 24 months, using EC data. Do they correspond with the WUI?
  6. How may uncertainty affect consumers’ decisions?
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‘Liberation day’: or start of a Trump slump?

On April 2nd, Donald Trump announced sweeping new ‘reciprocal’ tariffs. These would be in addition to 25% tariffs on imports of cars, steel and aluminium already announced and any other tariffs in place on individual countries, such as China. The new tariffs would apply to US imports from every country, except for Canada and Mexico where tariffs had already been imposed.

The new tariffs would depend on the size of the country’s trade in goods surplus with the USA (i.e. the USA’s trade in goods deficit with that country). The bigger the percentage surplus, the bigger the tariff. But, no matter how small a country’s surplus or even if it runs a deficit (i.e. imports more goods from the USA than it sells), it would still face a minimum 10% ‘baseline’ tariff.

President Trump stated that these tariffs are to counter what he claims as unfair trade practices inflicted on the USA. People had been expecting that these tariffs would reflect the tariffs applied by other countries on US goods and possibly also non-tariff barriers, such as the ban on chlorine-washed chicken or hormone-injected beef in the EU and UK. But, by basing them on the size of a country’s trade surplus, this meant imposing them on many countries with which the USA has a free-trade deal with no tariffs at all.

The table gives some examples of the new tariff rates. The largest rates would apply to China and south-east Asian countries, which supply low-priced products, such as clothing, footwear and electronics to the US market. In China’s case, it would a reciprocal tariff rate of 34% plus the previously imposed tariff rate of 20%, giving a massive 54%.

What is more, the ‘de minimis’ exemption will be scrapped for packages sent by private couriers. This had exempted goods of $800 or less sent direct to consumers from China and other countries from companies such as Temu and Alibaba. It is also intended to cut back on packages of synthetic opioids sent from these countries.

Since ‘liberation day’, President Trump has made several changes to these tariff rates. On 9 April he ‘paused’ the implementation of the tariffs above the 10% rate pending trade discussions with individual countries. However, in the case of China, there have been tit-for-tat tariff increases, so that by the end of April, the US tariff rate on Chinese imports was a massive 145% and the Chinese rate on US imports was 125%. The two countries seemed locked in a high-stakes game of chicken.

The US formula for reciprocal tariffs

As we have seen, the proposed (and then paused) reciprocal tariffs do not reflect countries’ tariff rates on the USA. Instead, rates for countries running a trade in goods surplus with the USA (a US trade deficit with these countries) are designed to reflect the size of that surplus as a percentage of their total imports from the USA. The White House has published the following formula.


where:

When the two elasticities are multiplied together this gives 1 and so can be ignored. As there was no previous ‘reciprocal’ tariff, the rise in the reciprocal tariff rate is the actual reciprocal tariff rate. The formula for the reciprocal tariff rate thus becomes the percentage trade surplus of that country with the USA: (exports – imports) / imports, expressed as a percentage. This is then rounded up to the nearest whole number.

President Trump also stated that countries would be given a discount to show US goodwill. This involves halving the rate from the above formula and then rounding up to the nearest whole number.

Take the case of China. China’s exports of goods to the USA in 2024 were $439bn, while its imports of goods from the USA were $144bn, giving China a trade surplus with the USA of $295bn. Expressing this as a percentage of exports gives ($295/$439 × 100)/2 = 33.6%, rounded up to 34%. For the EU, the formula gives ($227bn/$584bn × 100)/2 = 19.4%, rounded up to 20%.

Questioning the value of φ. Even if you accept the formula itself as the basis for imposing tariffs, the value of the second term in the denominator, φ, is likely to be seriously undervalued. The term represents the elasticity of import prices with respect to tariff changes. It shows the proportion of a tariff rise that is passed on to consumers, which is assumed to be just one quarter, with producers bearing the remaining three quarters. In reality, it is highly likely that most of the tariff will get passed on, as it was with the tariffs applied in Donald Trump’s first presidency.

If the value for φ were 1 (i.e. all the tariff passed on to the consumer), the formula would give a ‘reciprocal tariff’ of just one quarter of that with a value of φ of 0.25. The figures in the table above would look very different. If the rates were then still halved, all countries with a tariff below 40% (such as the EU, Japan or India) would instead face just the baseline tariff of 10%. What is more, China’s rate would be reduced from 54% to 30% (the original 20% plus the baseline of 10%). Cambodia’s would be reduced to 13%. Even if the halving discount were no longer applied, the rates would still be only half of those shown in the table (and 37% for China).

Are the tariffs justified?

Even if a correct value of φ were used, a percentage trade surplus is a poor way of measuring the protection used by a country. Many countries running a trade surplus with the USA are low-income countries with low labour costs. They have a comparative advantage in labour-intensive goods. That allows such goods to be purchased at low cost by Americans. Their trade surplus may not be a reflection of protection at all.

Also, if protection is to be used to reflect the trade imbalance with each country, then why impose a 10% baseline on countries, like the UK, with which the USA has a trade surplus? By the Trump administration’s logic, it ought to be subsidising UK imports or accepting of UK tariffs on imports of US goods.

But President Trump also wants to address the USA’s overall trade deficit. The US balance of trade in goods deficit was $1063bn in 2023 (the latest year for a full set of figures). But the overall balance of payments must balance. There were thus surpluses elsewhere on the balance of payments account (and some other deficits). There was a surplus on the services account of $278bn and on the financial account of $924bn. In other words, inward investment to the USA (both direct and portfolio) and the acquisition of dollars by other countries as a reserve asset were very large and helped to drive up the exchange rate. This made US goods less competitive and imports relatively cheaper.

The USA has a large national debt of some $36 trillion of which some $9 trillion is owed to foreign investors (people, institutions or countries). Servicing the debt pushes up US interest rates. This helps to maintain a high exchange rate, thereby making imports cheaper and worsening the trade deficit. The fiscal burden of servicing the debt also crowds out US government expenditure on items such as defence, education, law and order and infrastructure. President Trump hopes that tariffs will bring in additional revenue to help finance the deficit.

Effects on the USA

If the tariffs reduce spending on imports and if other countries do not retaliate, then the US balance of trade should improve. However, a tariff is effectively a tax on imported goods. It is charged to the importing company not to the manufacturer abroad. As we saw in the context of the false value for φ, most of the tariff will be passed on to American consumers. Theoretically the incidence of the tariff is shared between the supplier and the purchaser, but in practice, most of the higher cost to the importer will be passed on to the consumer. As with other taxes, the effect is to transfer money from the consumer to the government, making people poorer but giving the government extra revenue. This revenue will be dollars, not foreign currency.

As some of the biggest price rises will be for cheap manufactured products, such as imports from China, and various staple foodstuffs, the effects could be felt disproportionately by the poor. Higher import prices will allow domestic producers competing with these imports to raise their prices too. The tariffs are thus likely to be inflationary. But because the inflation would be the result of higher costs, not higher demand, this could lead to recession as real incomes fell.

American resources will be diverted by the tariffs from sectors in which the USA has a comparative advantage, such as advanced manufactured goods and services, to more basic products. Tariffs on cheap imports will make domestic versions of these products more profitable: even though they are more costly to produce, they will be sold at a higher price.

The tariffs will also directly affect goods produced by US companies. The reason is that many use complex supply chains involving parts produced abroad. Take the case of Apple. Even though it is an American company which designs its products in California, the company sources parts from several Asian countries and has factories in Vietnam, China, India, and Thailand. These components will face tariffs and thus directly affect the price of iPhones, iPads, MacBooks, etc. Similarly affected are other US tech hardware manufacturers, US car manufactures, clothing and footwear producers, such as The Gap and Nike, and home goods producers.

Monetary policy response. How the Fed would respond is not clear. Higher inflation and lower growth, or even a recession, produces what is known as ‘stagflation’: inflation combined with stagnation. Many countries experienced stagflation following the Russian invasion of Ukraine, when higher commodity prices led to soaring inflation and economic slowdown. There was a cost-of-living crisis.

If a central bank has a simple mandate of keeping inflation to a target, higher inflation would be likely to lead to higher interest rates, making recession even more likely. It is the inflation of the two elements of stagflation (inflation and stagnation) that is addressed. The recession is thus likely to be deepened by monetary policy. But as the Fed has a dual mandate of controlling inflation but also of maximising employment, it may choose not to raise interest rates, or even to lower them, to get the optimum balance between these two targets.

If other countries retaliate by themselves raising tariffs on US exports and/or if consumers boycott American goods and services, this will further reduce incomes in the USA. Just two days after ‘liberation day’, China retaliated against America’s 34% additional tariff on Chinese imports by imposing its own 34% tariff on US imports to China.

A trade war will make the world poorer, especially the USA. Investors know this. In the two days following ‘liberation day’, stock markets around the world fell sharply and especially in the USA. The Dow Jones was down 9.3% and the tech-heavy Nasdaq Composite was down 11.4%.

Effects on the rest of the world

The effects of the tariffs on other countries will obviously depend on the tariff rate. The countries facing the largest tariffs are some of the poorest countries which supply the USA with simple labour-intensive products, such as garments, footwear, food and minerals. This could have a severe effect on their economies and cause rapidly increasing poverty and hardship.

If countries retaliate, then this will raise prices of their imports from the USA and hurt their own domestic consumers. This will fuel inflation and push the more seriously affected countries into recession.

If the USA retaliates to this retaliation, thereby further escalating the trade war, the effects could be very serious. The world could be pushed into a deep recession. The benefits of trade, where all countries can gain by specialising in producing goods with low opportunity costs and importing those with high domestic opportunity costs, would be seriously eroded.

What President Trump hopes is that the tariffs will put him in a strong negotiating position. He could offer to reduce or scrap the tariffs on a particular country in exchange for something he wants. An example would be the offer to scrap or reduce the baseline 10% tariff on UK exports and/or the 25% tariff on UK exports of cars, steel and aluminium. This could be in exchange for the UK allowing the importation of US chlorinated chicken or abolishing the digital services tax. This was introduced in 2020 and is a 2% levy on tech firms, including big US firms such as Amazon, Alphabet (Google), Meta and X.

It will be fascinating but worrying to see how the politics of the trade war play out.

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Questions

  1. What is the law of comparative advantage? Does this imply that free trade is always the best alternative for countries?
  2. From a US perspective, what are the arguments for and against the tariffs announced by President Trump on 2 April 2025?
  3. What response to the tariffs is in the UK’s best interests and why?
  4. Should the UK align with the EU in responding to the tariffs?
  5. What is meant by a negative sum game? Explain whether a trade war is a negative sum game. Can a specific ‘player’ gain in a negative sum game?
  6. What happened to stock markets directly following President Trump’s announcement and what has happened since? Explain you findings.