Bristol Centre for Economics and Finance hosted an online event on 28th May 2020: Rules vs. Principles-based Regulation: What can we learn from different professions? Below is a summary and recording of each session.

Session 1: Data regulation 

Lizzie Green at UWE introduced the principles-based approach to data governance. She noted that protecting data is easy: just hide it in a big metal box. More difficult is protecting it while simultaneously extracting value from it. A rules-based approach offers clarity and consistency, but it can run into problems: humans are good at finding interpreting ambiguity for their own benefit, sometimes just for the pleasure of getting round a restriction. A principles-based approach gets round this, but it introduces uncertainty which can be hard to manage. One way to do this is to map principles to accreditation procedures, using frameworks such as the Five Safes. 

Felix Ritchie, also of UWE, described experiences of regulation in the UK and Australia. In the UK, this has been an evolutionary model, from a ‘default-closed’ perspective at the start of the century in a context set by a law from 1948, through two pieces of legislation and a shift in attitudes towards a default-open model. In contrast, the Australian federal government took a conscious decision to bring in the default-open principles-based models that had evolved slowly elsewhere. As public perceptions and discussion of data governance in these countries differ substantially, the contrast between the Australian and UK approach will be informative to a great many countries.  

Martin Hickley, Director of Martin Hickley Data Solutions, discussed private sector models of regulation. Focused on the Data Protection Impact Assessment carried out for the Covid-19 tracking app being trialled on the Isle of Wight. He argued that the DPIA is significantly flawed, and appears to have been completed as a check-box exercise rather than understanding the risk-based context. This is one of the problems of rules-based regulation. In contrast the principles-based approach calls for transparency, active scrutiny and debate – which are hard but necessary for robust solutions. 

Finally, Luk Arbuckle, Chief Methodologist of Privacy Analytics, discussed US health data regulation. He demonstrated that the HIPAA guidance includes both rules-based and principles-based regulation. The safe harbour regulations are rules based: comprehensive and easy to follow, but, most importantly, with a catch-all of “actual knowledge”. This brings in flexibility, but can lead to uncertainty; but overall, it means that the safe harbour rules are easily applied. In contrast, the ‘expert determination’ of the level of protection in the data is explicitly principles-based, relying on trained experts to make informed judgements based on “generally accepted statistical and scientific principles”.  In contrasting the two models, he noted that the safe harbour model demonstrates one of the problems of rules-based regulation – that it is more likely to become out of date as it reflects the context in which it was written. 

The ensuing discussion initially focused on the expertise needed in a principles-based environment: how for example do you enforce the principle “drive safely” without training people to understand what this means? More deeply, do we over-estimate the value of principles-based models because we are all ‘experts’ in this field in some way? Finally, how do we make sure that we have enough experts to do principles-based? Rules are very efficient in making sure a lot of people carry out a lot of activity adequately, and perhaps expertise isn’t needed all the time. Moreover, evidence suggests that a basic level of ‘expert knowledge’ can be instilled quite easily, in many different environments. 

A number of participants also suggested that the implementation matters. Some organisations claimed to be principles-based and but are actually rules-based, and there is always an incentive to turn compliance into a tick-box exercise. Perhaps there is a need to accept that encouraging positive behaviour via checkboxes might be a less-worst option than over-estimating people’s willingness to become experts. Understanding the threat environment is key, because all options are a subjective balance of risks. A mix of rules implementing overarching principles may be the preferred outcome. Conceptual frameworks have an important role to play in   developing the context. 

Finally, the discussion considered whether there is a difference between the public and private sector. There do seem to be different incentives (what is important) as well as different disincentives (what punishments are being avoided), and perhaps also a different way of assessing costs and benefits. However, there wasn’t a consensus as to whether this limits the options for public-private co-operative projects. 

Overall, the session concluded that while the principles-based models has many advantages (principally, flexibility in context and application, and efficiency), it does pre-suppose an ability to get agreement on /train individuals in those principles. Moreover, a badly-designed principles-based system doesn’t avoid box-ticking, especially for untrained users. In practice, an element of rules within an overall principles-based approach can offer efficiency gains, whilst not sacrificing the gains from a recognition of principles. Ultimately this is a balance-of-risks decision, and so understanding the risk environment (including human behaviour) is central to a well-designed system. 

WATCH RECORDING OF SESSION 1 HERE

Session 2: Regulation in UK financial markets and accounting 

Paul Keenan, of Keenan Regulatory Consulting and visiting Professor at UWE, introduced the two-pronged approach in UK financial markets. Following on from an initial simple principle (‘My word is my bond’) an extensive rulebook has been developed, leading to the current system of higher-level principles backed up by rules. In practice, he explained, when the regulator takes actions against market participants, they look at rule breaches and whether the interpretation of the rule led to a breach of a principle. Essentially, the regulator considers the firm’s understanding and interpretation of the rules to be in breach of the principles. So even if the rules have been broken the action taken, i.e. the fine imposed, is based on the principles. 

Bryan Foss, Digital Non-Executive Director, Risk & Audit Chair, and also visiting Professor at UWE, reflected on the need for, and implementation of, regulation. He argued that regulators should work with stakeholders to develop effective regulation, and that flexibility to change with circumstances over time is a key point for adequate regulation. Principles are therefore generally better suited by allowing scope for differences, innovation, easier revision or withdrawal. Fundamentally, however, both approaches require transparency, accountability, and stakeholder oversight to make them work. He also noted that there tends to be a lot of social pressure at the moment to increase the rules, and the UK regulator looking to bring in aspects of US rules-based elements, despite practitioners recognising the advantages of principles. 

Florian Meier of UWE discussed the self-regulation and enforcement approach used by UK professional accounting bodies. Members are subject to both professional regulations and principles-based codes of ethics, with the key component being the ethical principles. Self-regulation, however, raises a number of challenges which do cast some doubt on the effectiveness of enforcement. Ismail Adelopo, also of UWE, highlighted how corporate governance exhibits a clear split along a geographical line: The UK uses principles and the US uses rules, each having evolved from their historical contexts over time to each address specific situations and needs. The UK approach relies heavily on investors’ active involvement as a key factor in ensuring compliance and enforcement, but this leads to challenges such as: What if investors don’t play along and simply sell non-compliant firms instead of engaging with them? Who enforces compliance if everybody sells, or the market simply doesn’t care? 

The discussion focused largely on questions surrounding enforcement and effectiveness of approaches. Starting with the area of financial market regulations, the initial debate around appropriateness of fines quickly turned to looking at the broader aspect of penalties: As firms seem to increasingly consider fines as cost of doing business, maybe the focus then should be much more on the personal accountability of individuals? In this context the measure of imposing a ‘stop trading’ order on an individual or firm was brought up. Those can be more important than a simple fine since they may even lead to the closing of a firm or ending a career. Given those potentially severe consequences, robust processes to defend yourself or the firm against the regulator (if the regulator is wrong) are therefore seen as essential.  

Another interesting point brought up was that the market regulator’s approach seems to have shifted over the years from being rather heavy-handed and punitive in the past to a much more constructive approach: They are increasingly working with firms and affected individuals to help them improve and change to become better.  

In the area of corporate governance, the discussion touched upon shortcomings of the current UK approach and brought up ideas for improvement. For instance, it questioned the reliance of UK enforcement on investors and pointed to significant shortcomings. For one, the fact that it is essentially being left to the major shareholders to hold the firms to account or take them to the courts was raised as a concern. Unless in line with the majority, the minority shareholders’ interests get disregarded. They lack the resources to fight for their interests, so what recourse do they have other than either accepting this or selling the shares?  

Another concern of growing future significance was raised about pension funds and them increasingly making big investments in private firms. The corporate governance code does not apply to unlisted firms, and as such firms are not easy to divest from, pension funds are therefore probably even more dependent on good corporate governance. The question then becomes: How effective can those investors’ interests be protected, which are ultimately future pensioners? Further, the issue of what constitutes an appropriate penalty was raised and whether the UK has reached an appropriate balance. Especially as firms are often repeat offenders, doubts were expressed whether this can be solved without having a major overhaul to implement a robust regime. On that note, a suggestion was made to maybe learn from other countries, e.g. Australia, where the regulator has powers in regards to corporate governance and can intervene (unlike the UK). 

WATCH RECORDING OF SESSION 2 HERE

Session 3: Legal perspective and non-financial regulation 

Nicholas Ryder of UWE introduced the area of terrorism financing and the successful UK approach to combat it. He first described the current Anti Money Laundering (AML) regulations as fundamentally flawed to deal with terrorism financing, as the legal framework and international banks’ practice (‘soft law recommendations’) target the proceeds of crime, whereas terrorism financing is ‘reverse money laundering’ where no profits are made. By contrast, the more recent UK Joint Money Laundering Intelligence Task Force, a public/private partnership (PPP) with the financial sector, has been quite successful in detecting illegal fund flows and identifying funding patterns. Having been recognised as one of the best international examples of public and private cooperation, other countries have now adopted a similar model. Nicholas suggested that a PPP as opposed to a legal principles-based approach this task force could possibly be the way forward. 

Jaya Chakrabarti, CEO of Semantrica (tiscreport), introduced the TISC report (Transparency In Supply Chains) as a repository for measuring compliance with the UK Modern Slavery Act, along with numerous other financial risk and compliance datasets. She pointed out that, despite the level of compliance required being very low, a lot of companies still don’t provide a statement, and only a fraction of all organisations meet all of the minimum compliance criteria. The frequently observed low quality of data provided by firms poses a challenge to effective reporting. It makes acting on it difficult and thereby enables continued corporate misbehaviour. Further, enforcement seems to be largely non-existent despite potentially severe consequences for non-compliance, thus giving firms no ‘incentive’ to comply. As a way forward, while proper enforcement would be a key pillar for better effectiveness, she also presented some suggestions for modifying corporate behaviour that do not require government regulations and enforcement.  

The discussion mainly centred around enforcement and detection of illegal behaviour. The initial debate on the potential future role of Blockchain applications to certify and trace supply chains to aid transparency quickly turned to the key importance of getting the public sector and the key stakeholders on board to actively pursue enforcement. The public sector was lauded for already actively tracking their suppliers and ensuring compliance, with in particular local governments being very active and frequently working with their suppliers to increase levels of compliance. It was argued that a stumbling block to better enforcement was public bodies’ frequent inaction, even if they have the data, because they don’t know how to deal with it in their enforcement. Further, a general lack of enforcement and disinterest shown by the major stakeholders in various areas of regulation was flagged as a key problem. Using insurers as leverage to enforce better compliance was floated as an idea: that is, refusing professional indemnity insurance for cases of illegal company illegal behaviour, although doubts were also expressed about insurers’ willingness to get involved.  

The discussion then moved on to financial crime and the detection of illegal behaviour. First, the big problem of increasing so-called ‘micro-terrorism’ relying on very simple methods and small amounts which makes identifying individuals and prevent small attacks almost impossible, was pointed out. Regardless of approach (rules or principles), the view was that you can never stop all money laundering or financial crime, comparing it to ‘plugging a hole in a dam with plasticine’. The ‘risk-based approach’, as embodied in international laws and international best practice, to try to identify which businesses are more susceptible to fraud or money laundering, was seen as the best option. On fraud detection, the inability of the current self-reporting nature of verifying compliance with both the slavery act and the bribery act was flagged as a major weakness, with ample evidence from banking regulation showing the approach is not working. Examples from financial services were suggested to introduce accountability as a potential solution to the problem: In some roles, such as money laundering officers, individuals are accountable for self-reporting, so they take it very seriously. Hence non-reporting by the firm puts heavy pressure on that person, which may turn them into ‘whistle-blowers’.  

WATCH RECORDING OF SESSION 3 HERE

by Felix Ritchie and Francesco Tava

A recent working paper discusses the ‘Fives Safes’ framework for confidential data governance and management. This splits planning into a number of separate but related topics:

• safe project: is this an appropriate use of the data? Is there a public benefit, or excessive risk?
• safe people: who will be using the data? What skills do they have?
• safe setting: how will the data be accessed? Are there limits on transferring it?
• safe data: can the detail in the data be reduced without excessively limiting its usefulness?
• safe outputs: is confidentiality protected in products such as tables of statistics?

This framework has been widely adopted, particularly in government, both as a practical guide (eg  this one ) and as a basis for legislation (eg the UK Digital Economy Act or the South Australia data sharing legislation

As a practical guide, there is one obvious limitation. There is no hierarchy among the ‘safes’, and they are all interrelated; so which should you put most emphasis on?

We use the Five Safes to structure courses in confidential data management. One of the exercises asks the attendees to rank them as ‘what should we be most/least concerned with?’ The point of the exercise is not to come up with a definitive ranking, but to get the attendees to think about how different elements might matter in different circumstances.

This exercise generates much discussion. Over the years, we have had participants putting forward good arguments for each of the Five Safes as being the most important. Traditionally, and in the academic literature, Safe Data is seen as the most important: reduce inherent risk in the data, and all your problems go away. In contrast, in the ‘user centred’ planning we now advocate (eg here], Safe People is key: know who your users are, and design ethical processes, IT systems, training and procedures for them.

When training, this is the line we usually take, because we are training people to use systems which have already been designed. The aim of the training is to help people understand the community they are part of. Our views are therefore coloured by the need to work within existing systems.

Our thinking on this has been challenged by the developments in Australia. The Australian federal government is proposing a cross-government data sharing strategy based on the ‘Australian Data Sharing Principles’ (ADSPs). The ADSPs are based on the Five Safes but designed as a detailed practical guide to Australian government departments looking to share data for analysis. As part of the legislative process, the Australian government has engaged in an extensive consultation since 2018, including public user groups, privacy advocates, IT specialists, the security services, lawyers, academic researchers, health services, the Information Commissioner, and the media.

Most of the concerns about data sharing arising in the consultation centre on the ‘safe project’ aspect. Typical questions that cropped up frequently included:

• How do we know the data sharing will be legal/appropriate/ethical?
• Who decides what is in the ‘public interest’?
• How do you prevent shared data, approved for one purpose, being passed on or re-used for another purpose without approval?
• What sort of people will we allow to use the data? Should we trust them?
• What will happen to the data once the sharing is no longer necessary? How is legacy data managed?
• Do we need to lay down detailed rules, or can we allow for flexible adherence to principles?
• Where are the checks and balances for all these processes?

These are all questions which need to be addressed at the design stage: define the project scope, users and duration, and then assess whether the likely benefits outweigh costs and reasonable risks. If this can’t be done… why would you take the project any further?

Similarly, in recent correspondence with a consulting firm, it emerged that a key part of their advice to firms on data sharing is about use: the lawfulness of the data sharing is relatively easy to establish – once you have established the uses to which that shared data will be put. Some organisations have argued that there should be an additional ‘safe’ just to highlight the legal obligations.

This is particularly pertinent for data sharing in the public sector, where organisations face continual scrutiny over the appropriate use of public money. A clear statement of purpose and net benefits at the beginning of any project can make a substantial difference to the acceptability of the project. And whilst well-designed and well-run projects tend to be ignored by people not involved, failures in public data sharing (eg Robodebt or care.data) tend to have negative repercussions far beyond the original problems.

This is not the only concern facing data holders in a digital age of multi-source data. Handling confidential data always involves costs and benefits. Traditional approaches that focus on Safe Data identify the data holder as the relevant metric for these costs and benefit. A recent paper shows how this vision is at odds with the most recent developments in the information society that we live in. Consider the use of social media in research: is any of the actions by the author, the distributor or the researcher sufficient in itself to establish the moral authority of an end use? In this modified context, traditional ethical notions such as individual agency and moral responsibility are gradually substituted by a framework of distributed morality, whereby multiagent systems (multiple human interactions, filtered and possibly extended by technology) are responsible for big morally-loaded actions that take place in today’s society (see on this).

In this complex scenario, taking the data holder as the only arbiter of data governance might be counterproductive, insofar as practices that are morally neutral for the data holder (for example, refusing to consider data sharing) could damage the multiagent infrastructure which that data holder is part of (eg limiting incentives to participate). On the other hand, practices that can cause a minor damage to one of the agents (such as reputational risk for the data holder) could lead to major collective advantages, whose attainment would justify that minor damage, and make acceptable on a societal basis.

In order to minimise the risks, an innovative data management approach should look at the web of collective and societal bonds that links together data owners and users. In practice, this means that decision-making regarding confidential data management will not be grounded on the individual agency and responsibility of individual agents, but will rather correspond to a balance of subjective probabilities. On these premises, focusing on the Safe Project makes pre-eminent the notion that data should be made available for research purposes if the expected benefit to society outweighs the potential loss of privacy for the individual. The most challenging question is, of course, how to calculate this benefit, when so many of the costs and benefits are unmeasurable.

And this is the difference between Safe Projects and the others. ‘Safe projects’ addresses the big conceptual questions. Safe people, safe settings and safe outputs are about the systems and procedure to implement those concepts, whilst Safe Data is the residual (select an appropriate level of detail once the context is defined). So rather than Five Safes perhaps there should be One Plus Four Safes…

About the authors

Felix Ritchie is Professor of Applied Economics in the department of Accounting Economics and Finance

Francesco Tava is Senior Lecturer in Philosophy in the Department of Health and Applied Social Sciences

Timothy Hinks paper has just been accepted for publication

The focus on bribery and corruption and its impact on life satisfaction is relatively new in the economics and development studies literature. This paper contributes to this emerging field by asking whether reasons for making informal payments are correlated with life satisfaction. We find that paying bribes negatively correlates with life satisfaction and that those who were extorted by public officials or made an informal payment since they thought it was expected of them reported lower life satisfaction levels. We also find that those who made an informal payment to speed things up or who thought of the payment as a gift reported higher life satisfaction. Reasons for bribery differ in their associated significance with life satisfaction by public service that is used and by income group. For example people who instigated informal payments to public officials in the civil courts report higher life satisfaction bringing into question the integrity of judicial systems in transitional countries.

The paper is paper is published in World Development Perspectives and available online at here.

By Professor Felix Ritchie and Anthea Springbett

UWE Bristol has recently been commissioned by the Office for National Statistics (ONS) to develop a course in ‘output checking’ for research data centres. This is where researchers working on confidential data have their statistical outputs checked before publication, to ensure that they don’t break the law by inadvertently releasing information about individuals; for example, without proper checks a table of earnings in a small village could reveal the income of the highest earner. This checking process is called ‘statistical disclosure control’, or SDC.

Output checking is a well-established field, and there are experienced trainers and automatic tools to help those producing statistics. Why then does ONS need a new course? The reason is that new forms of data, new ways of working, and new types of users have all created a need for a different kind of output checking.

SDC training is largely focused on the tables produced by national statistical institutes (NSIs) such as ONS. NSI outputs have particular demands: similar tables are produced year after year, multiple tables are produced from the same data so consistency across tables is important, and NSIs publish a lot of information about their tables, including sampling methods.

Research outputs are quite different. Researchers aim to find new and interesting ways to extract meaning from data. Researchers choose data based on the hypotheses they want to explore and sub-samples of the population they are interested in, including or excluding data according to their own criteria. Finally, and most importantly, researchers don’t tend to produce detailed tables of the type NSIs generate; they are interested in multivariate analysis, non-linear models, heat maps, survival functions… For researchers, tables are often just used to describe the data before they get on to the interesting stuff. As a result, the forty-odd years of SDC designed for NSIs is of limited practical use in this environment.

For fifteen years, we have been developing an approach designed specifically for the research environment; we call it ‘output SDC’ (OSDC) to emphasise that this is a general approach to outputs, not just tables and not just for NSIs. There are two strands to this approach, one statistical and one operational.

The statistical strand comes from the ‘evidence-based, default-open, risk-managed, user-centred’ approach that we apply across our work in confidential data management. The way that researchers use data, and the confidentiality risks that they generate, require the output checker to be familiar with a wide range of statistics, which we address through classifying outputs into types, with a higher or lower inherent risk; this allows the checker to spend more time on the more ‘risky’ outputs. For these ‘risky’ outputs, context is everything. The traditional approach has been to apply simple yes/no rules (are there enough observations? Are there any outliers?) but this can be a very blunt instrument. Our approach emphasises the use of evidence in decision-making, which places more of a burden on the output-checker but increases the range of allowable outputs.

The operational strand reflects the fact that researchers are initially, on the whole, resistant to what they see as restrictions on output. A key part of the training will be helping output checkers build relationships with researchers; for example, emphasising that this is not about restricting output, but about keeping the researcher out of jail…

This is, we believe, the first formal course targeted specifically at (a) research outputs, and (b) those checking the outputs of the researchers, rather than the producers of statistics themselves. ONS is sponsoring the development of this training for all interested UK organisations. Many overseas organisations also run facilities that vet researcher outputs. We hope therefore that this will be of interest to a wide range of organisations, and may prompt a sea of change in the adoption of more general OSDC principles.

By Professor Felix Ritchie and Anthea Springbett

UWE Bristol has recently been commissioned by the Office for National Statistics (ONS) to develop a course in ‘output checking’ for research data centres. This is where researchers working on confidential data have their statistical outputs checked before publication, to ensure that they don’t break the law by inadvertently releasing information about individuals; for example, without proper checks a table of earnings in a small village could reveal the income of the highest earner. This checking process is called ‘statistical disclosure control’, or SDC.

Output checking is a well-established field, and there are experienced trainers and automatic tools to help those producing statistics. Why then does ONS need a new course? The reason is that new forms of data, new ways of working, and new types of users have all created a need for a different kind of output checking.

SDC training is largely focused on the tables produced by national statistical institutes (NSIs) such as ONS. NSI outputs have particular demands: similar tables are produced year after year, multiple tables are produced from the same data so consistency across tables is important, and NSIs publish a lot of information about their tables, including sampling methods.

Research outputs are quite different. Researchers aim to find new and interesting ways to extract meaning from data. Researchers choose data based on the hypotheses they want to explore and sub-samples of the population they are interested in, including or excluding data according to their own criteria. Finally, and most importantly, researchers don’t tend to produce detailed tables of the type NSIs generate; they are interested in multivariate analysis, non-linear models, heat maps, survival functions… For researchers, tables are often just used to describe the data before they get on to the interesting stuff. As a result, the forty-odd years of SDC designed for NSIs is of limited practical use in this environment.

For fifteen years, we have been developing an approach designed specifically for the research environment; we call it ‘output SDC’ (OSDC) to emphasise that this is a general approach to outputs, not just tables and not just for NSIs. There are two strands to this approach, one statistical and one operational.

The statistical strand comes from the ‘evidence-based, default-open, risk-managed, user-centred’ approach that we apply across our work in confidential data management. The way that researchers use data, and the confidentiality risks that they generate, require the output checker to be familiar with a wide range of statistics, which we address through classifying outputs into types, with a higher or lower inherent risk; this allows the checker to spend more time on the more ‘risky’ outputs. For these ‘risky’ outputs, context is everything. The traditional approach has been to apply simple yes/no rules (are there enough observations? Are there any outliers?) but this can be a very blunt instrument. Our approach emphasises the use of evidence in decision-making, which places more of a burden on the output-checker but increases the range of allowable outputs.

The operational strand reflects the fact that researchers are initially, on the whole, resistant to what they see as restrictions on output. A key part of the training will be helping output checkers build relationships with researchers; for example, emphasising that this is not about restricting output, but about keeping the researcher out of jail…

This is, we believe, the first formal course targeted specifically at (a) research outputs, and (b) those checking the outputs of the researchers, rather than the producers of statistics themselves. ONS is sponsoring the development of this training for all interested UK organisations. Many overseas organisations also run facilities that vet researcher outputs. We hope therefore that this will be of interest to a wide range of organisations, and may prompt a sea of change in the adoption of more general OSDC principles.

By Artjoms Ivlevs

On June 23, 2016, the United Kingdom (UK) held a historic referendum in which citizens voted, 52% to 48%, to leave the European Union (EU). The outcome of this vote has sent shockwaves around the world and is likely to change the course of British and European politics for years to come. It is widely recognized that immigration played a major role in the decision of the UK to leave the EU: immigration was a dominant theme in the pre-referendum debate and remains a key issue as the UK prepares its exit from the bloc. Specifically, the proponents of Brexit argued that the levels of immigration to the UK from other EU countries have become too high; exiting the EU would enable the country to control immigration from the EU. Slogans such as ‘immigrants take our jobs’ and ‘take back control of our borders’ have resonated well with the UK general public, for whom immigration has indeed become one of the biggest worries.

However, for some time scholars have been pointing that immigration has few, if any, adverse effects on the labour markets of migrant-receiving countries (Constant, 2014; Peri, 2014). Such findings, coupled with mounting worries over immigration levels, raise a question: in what ways does immigration affect the well-being of people in migrant-receiving countries – beyond the realm of the labour markets? In a study “Local-level immigration and life satisfaction: The EU enlargement experience in England and Wales”, published in 2018 in Environment and Planning A (Ivlevs and Veliziotis, 2018), we explored the effects of immigration on the subjective well-being, and in particular life satisfaction, of local residents – a relationship that has so far received little attention in both the literature and public debate.

To answer our research question – whether immigration affects the life satisfaction of residents in a host country – we focused on a recent immigration wave to the UK. Following the 2004 enlargement of the European Union, the UK opened its labour market to citizens of the new EU member states (Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia and Slovenia – also known as the accession or A8 countries). As a result, 1.5 million East Europeans started working in the UK between 2004 and 2011. In 2015, Poles – the largest group among the A8 migrants – became the largest foreign-born group in the UK, overtaking Indians, the Irish, Pakistani and Bangladeshi.

Besides being fast and unexpectedly large, the A8 migration to the UK was also geographically unevenly distributed (see the map below). The demand for jobs in the geographically-concentrated, ‘migrant-intensive’ industries, such as agriculture, food processing and manufacturing, meant that that some UK communities were affected by the East European migration much more than others. We related the local-level intensity of A8 migration to the changes in people’s life satisfaction over time. To capture the local-level migration intensity, we used data from the Worker Registration Scheme (WRS), which documented, between 2004 and 2011, the number of A8 workers starting a job in the UK at the local authority level. To capture changes in individual life satisfaction, we used the British Household Panel Survey (BHPS), which followed the same people over time.

Geographical distribution of A8 migration in England and Wales, 2004-2008, % of local population

Source: Worker Registration Scheme and authors’ calculations.

Our results showed that immigration from the A8 countries in the UK on average was not related to the life satisfaction of UK nationals. However, important sub-group differences emerged and are presented in the graphs below. More intense local-level immigration was associated with lower life satisfaction among older people, as well as the unemployed and the economically inactive, while the life satisfaction of younger people and those in employment went up with local-level immigration. We have also obtained somewhat weaker evidence that the life satisfaction of better educated UK nationals and those with higher incomes increased with immigration, while the life satisfaction of people with low incomes decreased with it. All these associations were pronounced in the ‘migration shock’ period – the first two years after the UK opened its labour market to the new Europeans – and became statistically insignificant in the longer term.

Predicted life satisfaction as a function of the local immigration rate for respondents of different age, employment status, income and education

How can one explain these results? A positive association between immigration and life satisfaction for the young could be because young people are in favor of diversity brought about by immigration. In contrast, older people might be particularly opposed to diversity and change, as well as be concerned with the (perceived) pressure immigrants put on local health services; this could explain why the elderly become less life-satisfied when larger immigrant inflows take place. The negative association between the local immigration rate and life satisfaction among the unemployed could mean that people in this group feel that their chances of getting back to work and their labour market bargaining power get weaker with higher levels of immigration – a form of labour market competition. At the same time, those in employment do not seem to be threatened by labour market competition, as their life satisfaction increases with the levels of local immigration.

The finding that life satisfaction increases with local-level immigration among those with high incomes and relatively high levels of education could indicate that these groups do not perceive Eastern European migrants as labour market competitors (which is consistent with the fact that the A8 migrants are concentrated in low-skilled sectors/occupations). Instead, the wealthier and better educated could be gaining in life satisfaction through, for example, enhanced social life (many A8 migrants are employed in the hospitality industry, keeping its product prices low) or satisfaction with house or family life (A8 migrants increased the supply of cheap household services).

Overall, our results suggest that immigration does not affect the well-being of different groups of people in the same way and that labour market considerations are unlikely to be a dominant factor in explaining the links between immigration and natives’ well-being. In addition, the fact that the life satisfaction of particular groups, such as the elderly, decreases with immigration has implications for the formation of immigration policy in most developed immigration-receiving countries, where populations are aging and older people are generally more likely to vote. From this perspective, the recent decision of the UK to leave the EU could well be explained by the negative association between A8 immigration and the life satisfaction of older people in the UK. This contention, however, hinges on the assumptions that 1) the Brexit referendum vote was indeed largely about restricting immigration, and 2) life satisfaction affects people’s immigration policy preferences.

Reference to the full paper:

Ivlevs, A. and Veliziotis, M. (2018). “Local-level immigration and life satisfaction: The EU enlargement experience in England and Wales”, Environment and Planning A 50(1): 175-193.

The article is also available on the UWE Research Repository.

By Professor Felix Ritchie and Dr Hilary Drew

Apprentices are amongst the lowest paid workers in the UK. Their statutory minimum wage is lower than for any other worker aged 16 or over. Despite this, our research, along with Michail Veliziotis at Southampton University, showed that up to a quarter of all apprentices still seem to be paid below their legal minimum hourly rate. In comparison, the rate of non-compliance amongst the whole work force is less than 5%.

We argued that this was partly due to the minimum wage for apprentices being more complicated than for other workers. However, in this segment of the economy there are weak mechanisms for checking that the correct wage is being paid. Apprentices are often unaware or incurious about pay rates, while employers showed a confidence that they could work out pay rates which wasn’t strongly supported by statistics. Apprentices had a high degree of trust in employers to pay the right wage, which meant that mistakes were unlikely to be uncovered. Finally, all this was set in a low-pay culture, where it was accepted that “rubbish pay” (to quote one apprentice) at the early stage of your career was one of the rites of passage.

We advised that more targeted information could help to resolve this problem; in particular, we proposed an ‘app app’ (a wage calculator designed for young people fresh out of school or college), and working with trainers at FE colleges who were best placed to help apprentices check their pay.

Our recommendations have now been taken forward in the South West. Earlier this month we presented our findings at the “Great Apprenticeships – Treated Well – Treated Right” event organised by the South West TUC at the City of Bristol College.  Union representatives, training providers, local government and apprentices attended the event.

One of the aims was to showcase the South West TUC’s new wage calculator,  developed specifically for apprentices. The meeting also presented an opportunity for interested parties to examine a regional approach.

The event indicated that there was a clear common interest in taking action to improve pay awareness amongst apprentices and to better promote the TUC’s wage calculator. We are excited to remain involved with the work taking this forward in 2019 and plan to support the City of Bristol College in targeting their apprentices as part of the South West TUC’s campaign. We hope as a result of this we can demonstrate how a simple intervention, allied to a targeted information programme, can make a material difference to some of the lowest paid employees.