State of the Nation 2024

Foreword

Our aim at the Social Mobility Commission is to improve opportunities for all, but particularly for those whose opportunities are most limited.

At this moment of change in the country, we believe it is important to set out the main challenges for social mobility and the steps needed to address these. Decisive and bold action is needed in key areas such as addressing regional inequalities and supporting the most vulnerable. But we believe traditional approaches to social mobility have not always worked, and we want to make sure that initiatives are targeted at the right people and based on evidence-based practice.

There are now 4 overlapping challenges in the UK which frame our social mobility problem: low public confidence; a younger generation doing less well than their parents, particularly in terms of pay, progression and housing; insufficient attention to regional disparities and ‘left behind’ people and places; and the need for more successful and cost effective interventions. Each of these is critical and each needs urgent attention.

Over the past 3 years, the Social Mobility Commission (SMC) has fulfilled its duty to report to Parliament by setting out and implementing a long-term vision for monitoring social mobility outcomes in our annual report. In 2022, we developed and published a new Social Mobility Index for measuring mobility in the UK systematically over time. We reported a range of robust social mobility measures, looking at people’s life outcomes in comparison with their parents’ outcomes. In 2023, we took this a step further, with breakdowns by protected characteristics such as ethnicity, sex and disability, to reveal a more nuanced picture. And we emphasised the important role of geography in shaping opportunity, by publishing our Data Explorer.

In this year’s State of the Nation report, we have taken the analysis a step further, extending our geographic breakdown of the UK, so that we are now looking at 203 Upper Tier Local Authority (LA) areas, instead of 41 regions (as last year). We have done this using 4 summative measures, or composite indices: ‘Promising Prospects’, which covers intermediate outcomes (early-life mobility outcomes); and ‘Conditions of Childhood’, ‘Labour Market Opportunities for Young People’, and ‘Innovation and Growth’, which cover the drivers (or enablers) of social mobility. This is a huge step forward in terms of providing a comprehensive evidence base – a set of measures and targets – that can support place-based approaches to social mobility.

Our previous reports have shown that much of what people say about social mobility in our country can be simplistic and misleading. It’s not true that social mobility is getting worse on all counts, nor does our country compare badly with others. In reality, the picture is complex. But we don’t need a crisis to recognise that opportunity can be improved; the key is how to approach this.

The evidence suggests that a one-size-fits-all national strategy for social mobility is too broad brush to make any real difference. We are keen to see place-based approaches, and a recognition of the close interplay between innovative economies, better opportunities and strong social mobility, rather than exclusively focussing on education in isolation from the need to solve fundamental economic problems.

Our State of the Nation report for 2024 brings this possibility a step nearer. The new composite indices demonstrate how each upper-tier local authority performs on key social mobility indicators. They show the areas which are outliers, either because they perform especially well or particularly poorly. And they support our aim, which is to champion a wider variety of opportunities for a wider variety of people in a wider variety of places.

We hope we can now work with a whole range of stakeholders, including central government, employers, educators and local leaders to ensure that everyone has the opportunity to thrive irrespective of their background or the place they grew up in.

The new framework has 2 types of measure: outcomes (mobility and intermediate) and drivers.

Mobility outcomes

Mobility outcomes compare your starting point in life, based on your parents’ position, to your own eventual position as an adult. For example, we might compare the income of a person’s parents with the person’s own income around the age of 50 years. We look at occupation, income, education, housing and wealth, where the data allows.

Analysis of most mobility outcomes relies on data from panel or birth cohort studies, which aren’t always updated yearly. We have therefore reported the same figures as last year for the mobility outcomes and included them in our online data explorer that complements this report.

Intermediate outcomes

For intermediate outcomes, we look at people’s progress from their parents’ position to their own position at an earlier point in life, such as employment in their 20s or educational attainment at age 16 years. We track this because a person’s early outcomes can be a very good indicator of how their later life will turn out. It also means that we have an early snapshot of mobility without having to wait to assess outcomes much later in life.

We break both mobility and intermediate outcome measures down by people’s socio-economic background (SEB), so that we can see how different starting points might affect progress to later points.^{[footnote 4]}

Drivers

Unlike the outcomes, drivers are forward-looking. They represent the national or local background conditions that make social mobility easier (or more challenging). We include indicators that affect aggregate, not individual, rates of mobility. For example, the availability of good schools or work opportunities are drivers, because they help groups of people who wouldn’t otherwise have the opportunity to be socially mobile. The question of what is or is not a driver is also distinct from the question of what might help an individual achieve upward mobility (like getting a good degree, for example).

With the drivers, we look at these conditions across the UK and not by SEB. This is an important distinction from the mobility and intermediate outcomes.

Absolute and relative mobility measures

Absolute measures capture the number of people who have experienced mobility. They are usually expressed as percentages of the population. For example, the absolute occupational mobility rate is the percentage of people who are in a different occupational class from their parents. For income mobility, a common absolute measure is the percentage of people whose income is higher than their parents’ income was, at the same age. We can compare these rates across different regions of the UK.

Relative measures compare the chances that at least 2 groups have of reaching, versus avoiding, a particular outcome. It is this element of comparison that makes such measures relative. A relative mobility measure tells us that one group has better chances than another, rather than telling us the total number of socially mobile people. Low relative mobility means that those who start life in a particular position are more likely than others to be in the same position later in life. For that reason, low relative mobility can be thought of as ‘stickiness’, while high relative mobility can be thought of as ‘fluidity’.

Composite indices

As in last year’s report, we feature composite indices, covering some of our drivers and intermediate outcomes. We call them composite indices, because they summarise multiple drivers, or intermediate outcomes, in one score. They give us a summary of how different geographical areas of the UK compare on the main dimensions of mobility that we have identified from the data.

The composites also allow us to be more confident in drawing conclusions about any differences between geographical areas. Estimates for individual areas in most cases involve sampling errors (since they are based on sample surveys, like the Labour Force Survey (LFS)).^{[footnote 5]} There’s therefore always a risk that differences between areas in respect of a single measure could be due to random sampling errors. To get around this imprecision, we summarise findings across multiple indicators that seem to be related. And, when multiple measures all give a similar picture, we can confidently say that there are real differences between the areas. We can then begin to ask whether these differences are due to the areas themselves or the individuals living within them.

Socio-economic background

We measure SEB using the same 5-part grouping that we introduced last year.^{[footnote 6]} This grouping uses the occupational classes in the Office for National Statistics’ (ONS) National Statistics Socio-economic Classification system (NS-SEC).^{[footnote 7]} There are 8 ‘analytic’ classes in the NS-SEC, and we grouped them into 5 categories: ‘higher professional and managerial’, ‘lower professional and managerial’, ‘intermediate’, ‘higher working class’, and ‘lower working class’.

We use this grouping to look not only at a person’s socio-economic or occupational background – in other words, what job a person’s parents did – but also what jobs people are currently doing. For example, if we say that someone has a ‘higher professional background’, this means that their parents had a higher professional or higher managerial occupation.^{[footnote 8]}

Previous groupings included only 3 categories – ‘professional and managerial’, ‘intermediate’ and ‘working class’. However, these categories were broad and did not provide enough information to understand short-range mobility. Using 3 categories also meant that there was considerable variation within each category.

How do we measure socio-economic background (SEB)?

SEB reflects a person’s starting point. A person’s SEB is measured by looking at their parent’s socio-economic situation when they were growing up. For example, this might be the parents’ occupational class, income or education. So for instance, we might look at whether one or both of a person’s parents had a degree when the person was a child.

Throughout our report, we often report on SEB, as it’s recorded in the Labour Force Survey (LFS) – a representative sample survey to provide information on the UK’s labour market. In this survey, participants are asked about their current jobs and what job the main earner in the household did when they were age 14 years. This enables us to look back at someone’s SEB without having to track the same individual across all the intervening years. The LFS also covers the whole of the UK, in line with the SMC’s statutory obligations.

We can now look at short- and long-range mobility, as well as important differences within the professional and working-class groups with these 5 categories. For example, we can determine if someone from a lower working-class background now works in a higher working-class occupation.

Table 1: Our 5-part grouping of occupational classes based on the NS-SEC.

NS-SEC	Previous 3-part grouping	5-part grouping	Example occupations
1	Professional and managerial	Higher professional, including higher managerial, administrative and professional	Chief executive officer of large firm, doctor, clergy, engineer, senior army officer
2	Professional and managerial	Lower professional, including lower managerial, administrative and professional	Teacher, nurse, office manager, journalist, web designer
3 and 4	Intermediate^{[footnote 9]}	Intermediate, including intermediate occupations, small employers and freelance workers	Clerical worker, driving instructor, graphic designer, IT engineer, shopkeeper, hotel manager, taxi driver, roofer
5 and 6	Working class	Higher working class, including lower supervisory, technical and semi-routine workers	Foreman, mechanic, electrician, train driver, printer, shop assistant, traffic warden, housekeeper, farmworker
7 and 8	Working class	Lower working class and workless families	Cleaner, porter, waiter, labourer, refuse collector, bricklayer

Occupational class versus earnings

Types of jobs are not always tied to how much you earn. Sometimes people in lower occupational classes earn more than those in higher occupational classes. For example, speech and language therapists count as higher professionals, NS-SEC 1, because their job requires a first degree for entry and experience-related training, and the practical application of a body of knowledge to instruct others. Yet their average salary is lower than that of many working-class occupations, including some routine manual occupations.

Example occupations, their NS-SEC classes and median salaries

Speech and language therapists: NS-SEC 1 – higher professional. Median salary: £31,932.
Train and tram drivers: NS-SEC 5 – higher working class. Median salary: £63,807.
Air conditioning and refrigeration installers and repairers: NS-SEC 6 – higher working class. Median salary: £39,818.
Large goods vehicle drivers: NS-SEC 7 – lower working class. Average salary: £36,847.^{[footnote 10]}

There can also be great variation in earnings within a class. For example, teaching assistants earn an average of £19,033, and rail travel assistants earn an average of £36,080, yet both occupations are classified as ‘intermediate’.^{[footnote 11]} Apart from different salaries, these jobs may also have very different working conditions.

And, finally, 2 people doing the same type of work can be in different classes if one is an employee and the other is self-employed since the self-employed tend to be classed as intermediate. For example, a bricklayer who is an employee would be in NS-SEC 7, lower working class, while a self-employed bricklayer would be in NS-SEC 4, intermediate class. The salaries in these 2 cases may also be very different.

Improvements this year

We have made significant improvements since last year’s report, providing richer detail and greater insights. We outline these changes below.

New composite indices

Our Index remains comparable with the one we published last year. However, we keep our list of indicators under review to make sure that we are capturing what matters. We have updated some indicators and improved our summary measures, which we call composite indices.

We now have a single composite index for intermediate outcomes at the upper-tier LA level. This gives us 203 geographical regions across the UK, instead of the 41 regions that we had last year. This index, called Promising Prospects, covers highest qualifications, hourly earnings, and also the professional and working-class occupations of young people.

Similarly, we have developed 3 new composite indices of drivers at upper-tier LA level, giving the same 203 geographical regions. The first index based on drivers is called Conditions of Childhood. This covers childhood poverty, parental education, parental working-class occupation, and parental professional occupation. The second index based on drivers is Labour Market Opportunities for Young People. This covers unemployment, professional employment, and working-class employment. Finally, we have retained our composite index that looks at research and development, but improved it so that it also gives us 203 regions. This index is now called Innovation and Growth. A more detailed explanation of our methodology can be found in the technical annex.

New geographical breakdowns

In 2023, we provided new geographical breakdowns for some of our indicators. To do so, we used regions defined by the ONS’ International Territorial Level (ITL) classification framework.^{[footnote 12]} We focused on breakdowns at the level known as ITL2, which divides the UK into 41 regions. Each region had between 800,000 and 3,000,000 inhabitants and contained about 4 upper-tier LAs.

This year, we improve upon this analysis and provide more detailed geographical breakdowns. We have divided the UK into 203 upper- or single-tier LAs.^{[footnote 13]} LA areas vary greatly in terms of the numbers of inhabitants, but they are more recognisable as geographical divisions, and they have policy responsibility for education and transport (among other things). In doing this, we have made significant progress on our policy framework objective of developing the data and methods for place-based approaches.

We provide this analysis by combining indicators into summary formulas (in other words, composited indices) and pooling together more years of the LFS data and wider age bands. Doing this allows us to increase the sample sizes so that we can publish separate figures for each upper- or single-tier LA.

Differences between International Territorial Level 2 (ITL2) and local authority (LA) breakdowns

In some areas of the UK, local government is divided between a county council (upper-tier LA) and a district council (lower-tier LA), which are responsible for different services. In other areas, there is a single-tier (unitary) LA instead. This year’s analysis breaks the UK down by upper-tier and single-tier LAs. There are 203 such LA areas across the UK in our analysis. In Northern Ireland, data limitations have meant that we cannot provide further geographical breakdowns, so instead we present Northern Ireland as a single geographical unit.

Last year, we provided breakdowns at ITL2, which included areas comprising roughly 4 upper-tier LAs for a total of 41 regions. At ITL2, for example, Herefordshire, Worcestershire and Warwickshire were grouped as one region. This year, they are considered separately.

Executive Summary

Chapter 1

A person experiences social mobility when they have different life outcomes from their parents, for example, in income, occupation, housing, education or wealth.

Our long-term vision is to report a consistent set of social-mobility statistics over time – our Social Mobility Index. In line with this, we have created a new website to host it, and we have also updated most of the statistics reported there since last year’s report.

We have made further improvements to our geographical reporting by creating a composite index of intermediate (early-life) outcomes at the upper-tier local authority (LA) level.^{[footnote 1]} This has allowed us to split the UK into 203 geographical areas, instead of 41, as we had last year.

Chapter 2

The attainment gap between pupils eligible for free school meals (FSM) and those not eligible remains largely unchanged from last year. For example, at age 5 years, there is a consistent gap of around 20 percentage points in the attainment of a ‘good level of development.’ However, in some cases it has widened, such as key stage 4 (KS4).

Among disadvantaged children, girls still do better than boys. For example, at age 11 years, 47% of disadvantaged girls reach the expected standard in reading, writing and maths, compared with 41% of boys.

FSM-eligible children from some ethnic backgrounds achieve very well. For example, FSM children of Chinese background perform better than the national average for non-FSM children at KS2 and KS4 (11 and 16 years). At age 11 years, 71% of FSM-eligible children of Chinese background reach the required standards.

All the areas of London continue to do well in terms of educational attainment for FSM-eligible pupils at 5, 11 and 16 years.

The percentage of children living in relative poverty in the UK (after accounting for housing costs) has risen since 2012 and is at about 30%. It is still below the levels reached in the 1990s (when the percentage was closer to the mid-30s), but is much higher than historical levels from the 1960s and 70s.

The availability of high-quality education in the UK remains good. The UK has performed at or above the Organisation for Economic Co-operation and Development (OECD) average in the Programme for International Student Assessment (PISA) for mathematics, reading and science, but 2022 scores show decreases across the world.

We see that unemployment levels among young people are now the lowest they have been since 2014, at 11% in 2022. This means that far fewer young people are suffering the negative effects of unemployment.

However, for those young people who are unemployed, finding a job could be more difficult, as job vacancy rates have fallen from 0.9 to 0.7 vacancies for every unemployed person between 2022 to 2023.

There appears to be a narrowing of the socio-economic background (SEB) gap in university enrolment between 2014 and 2022. In 2014, young people from higher professional backgrounds were 3.9 times more likely to be studying for a degree than those from lower working-class backgrounds. In 2022 they were only 2.2 times more likely. Data from the Department for Education (DfE), which goes back to 2006, suggests that this is an even longer-term trend.

Young people with low qualifications may have closed the earnings gap with their more qualified peers. For example, there has been a 16% increase in real hourly earnings for people with lower-level qualifications between 2014 to 2016, and 2020 to 2022. This is higher than the increases for all groups with higher-level qualifications.

Civic engagement – participating in democratic processes, such as signing a petition or attending a public rally – has decreased from 40% to 34%.

The percentage of premises with gigabit internet availability has increased sharply across the UK since 2020, potentially fostering better technical infrastructure for innovation and growth.

We have not included a full range of breakdowns by protected characteristics in this document. These breakdowns are instead published in full on our website, social-mobility.data.gov.uk.

Chapter 3

We have developed new composite indices of intermediate outcomes (mobility outcomes earlier in life), and drivers (the enablers of mobility), at the local authority (LA) level.

We now have a single index for intermediate outcomes at the upper-tier LA level. This gives us 203 geographical regions across the UK, instead of the 41 regions that we had last year. This index, called Promising Prospects, covers highest qualifications, hourly earnings, and also professional and working-class occupations of young people.

In common with other work on the topic, we have found that most LAs have similar levels of mobility, with a few at the top and bottom ends. The most favourable areas tend to be either in London or in the adjoining Home Counties.

Similarly, we have developed 3 new composite indices of drivers (the background conditions that help or hinder mobility) at upper-tier LA level, giving the same 203 geographical regions.

The first index based on drivers is called Conditions of Childhood. This covers childhood poverty, parental education, parental working-class occupation and parental professional occupation. The most favourable conditions of childhood tend to be found in affluent areas, mainly Greater London and the Home Counties but also parts of the North and Scotland.

The second composite index based on drivers is Labour Market Opportunities for young people. This covers youth unemployment, youth professional employment, and youth working-class employment. Results are similar, although the LAs with the less favourable opportunities for young people tend to be in the North East and North West, as well as older industrial and port areas.

We have retained our composite index that looks at research and development (R&D), but improved it so that it also gives us 203 regions. This index is now called Innovation and Growth. The most favourable areas are clustered around London, mainly in the South of England, but a few other areas score well on this index.

In some areas of the UK, local government is divided between a county council (upper-tier LA) and a district council (lower-tier LA), which are responsible for different services. In other areas, there is a single-tier (or ‘unitary’) LA instead.

State of the Nation 2024