By Dr Claire Tyler, Professor Lindsey Macmillan, and Dr Catherine Dilnot

Last Thursday we released our Nuffield-funded ‘Inequalities in Access to Professional Occupations’ report, and an accompanying blog post showing that Black undergraduates are well represented in application pools for professional graduate roles but are almost half as likely (45% less likely) to receive to receive job offers than white applicants (Figure 1 – blue dot).

Even when we compare candidates who ‘look the same on paper’, including attending a similar university, studying a similar subject and applying for similar jobs, Black applicants are still a third (34%) less likely to receive a job offer than white applicants (yellow dot).

This  analysis is based on a large sample of 117,043 applicants (of which 9,859 reported being of Black ethnicity) to graduate schemes at 17 large UK employers, across a range of sectors including accounting, law and public sector.

Figure 1: Offer rates to graduate programmes, conditional on observable differences across applicants, by ethnicity

 

Recruitment stages

In this blog post, we delve deeper into the low success rates for Black applicants to explore which stage of the recruitment process appears to be causing the largest barriers for these undergraduates.

For our analysis, we firstly needed to create some alignment in the recruitment data we received from 17 employers, as recruitment stages varied both by employer, and over time for the same employer. For consistent reporting, we grouped recruitment activity into two key stages:

1) Screening and testing, which includes all application sifting, screening based on educational credentials and online testing. Online tests assess skills such as numerical reasoning, verbal reasoning, situational judgement, behaviours, preferences and strengths.

2) Face to Face which includes interviews (video and in person), and assessment centres (case studies, group exercises).

In our sample, only around a quarter of candidates applied to a recruitment process which included screening based on prior educational qualifications (GCSE, A-levels and/or 2:1 degree) as these criteria are becoming less popular with employers. Whereas most participating employers used online tests, interviews and assessment centres as selection methods (80-100% of candidates applied to employers who used these methods).

Screening and testing matters

Exploring success rates for each of the two key stages revealed that Black applicants are 45% less likely to pass the upfront screening and online testing stage than white applicants and 8% less likely to pass the face to face stage (Figure 2 and 3 – blue dots). Even comparing applicants on a ‘like for like’ basis , Black applicants are 37% less likely to pass the screening and online testing stage than their comparable peers of white ethnicity, and 5% less likely to pass the face-to-face stage (Figure 2 and 3 – yellow dots).

Figure 2 – Relative likelihood of passing screening and online tests for the graduate programmes, conditional on observable differences across applicants, by ethnicity

 

Figure 3 – Relative likelihood of passing face to face stages for the graduate programmes, conditional on observable differences across applicants, by ethnicity

A recent report by Black Talent Charter also shows that ethnic minorities are disproportionately rejected in the early stages of recruitment, which further supports our findings. Their analysis of 400 students shows that the representation of Black applicants falls markedly at the ‘screening & testing stage’ in financial services recruitment (Figure 4) from around 16% of the applicant pool to 10% of the candidates invited for job interviews. For professional services the representation drops from 13% to 7% and in law from 10% to 7%. In each case, more Black applicants are rejected from the process at the ‘screening and online testing stage’ than at the following ‘face to face’ stage, both in terms of raw numbers of applicants and percentage point representation. The authors of the report quite rightly highlight the drop in representation at the ‘face to face’ stage between job interview and job offer but do not draw out the implications of the larger barriers at the earlier screening and testing stages.

Figure 4 – Percentage representation of Black talent throughout the candidate journey, from university application to job acceptance, across financial services (FS), law and professional services (PS)

Note: Figure reproduced from the Black Talent Charter 2204 report ‘Why We Need To Fix The Broken Pipeline for Graduate Black Talent in the UK’ (Figure 6, page 12). Red oval added by UCL to highlight figures of interest

Widen the focus?

Our findings suggest that employers may be overlooking racial inequalities at screening and testing stages of the recruitment process. Racial inequalities may still be seen as an ‘in person’ issue, whereas our evidence highlights other significant barriers in the recruitment process. This may explain why limited progress has been made to date in removing these inequalities in access to professional careers.

These findings mirror patterns of prior education and skills inequality via online tests such as numerical and verbal reasoning, situational judgement and critical thinking (we are hoping to be working on a new project about this soon). But the fact that these gaps are still so large after accounting for university attended suggest they may also relate to lack of preparation for such tests if these applicants are less likely to have parents or networks with experience of these types of tests.

This evidence also suggests a potential conflict between outreach activities of employers to widen the diversity of application pools and the initial screening and testing processes which disproportionally reject ethnic minority applicants.

Given the huge increase in graduate job applications and a record high ratio of applications to vacancies (140:1), it is also important to recognise that recruiters are currently dealing with unprecedented volumes of applications in narrower recruitment windows. The screening and online testing stages of recruitment act as a substantial filter for recruiters, with only 15% of candidates in our sample passing this stage, with the remaining 85% being rejected before any face to face interactions with the employer. With the increasing use of AI by job applicants, ‘getting it right’ at the screening and testing stage is becoming ever more important for employers – balancing the need to process huge volumes of applications while ensuring the best talent is recruited.

Recommendations

To improve the success rates of Black and other ethnic minority applicants we therefore recommend:

• Employers broaden the focus of ethnic diversity interventions/strategies to include the screening and online testing stages of recruitment in addition to any existing focus on face to face assessments.
• Employers review the success rates of under-represented groups at each stage of the recruitment process to see where the largest barriers occur.
• University career teams and employers collaborate to share insights about which under-represented groups may need additional information or guidance to be prepared for online recruitment assessments.
• Employers share these findings with your ‘race equality’ leads to ensure these issues are considered when planning new initiatives.
• Employers challenge external providers of recruitment assessments to provide data on success rates of candidates from under-represented groups on each type of test conducted.

What’s next?

We are working on launching a new project soon to delve deeper into the barriers for applicants from ethnic minority and lower socio-economic backgrounds – please get in touch if you would like to hear more about how to participate in our research collaborations. Projects are anonymous, free of charge and full of insights for participating employers.

 

 

By Dr Claire Tyler, Professor Lindsey Macmillan, and Dr Catherine Dilnot

Last Thursday we released our Nuffield-funded ‘Inequalities in Access to Professional Occupations’ report, and an accompanying blog post showing that working class students are well represented in application pools for professional graduate roles but are 32% less likely to receive job offers than applicants from professional backgrounds.

On Friday, our blog post revealed that date of application accounts for 11% of the gap in offer rates between applicants from working class and professional backgrounds in the accounting and professional services sector. This means that even if an applicant from a working class background obtained the same A-level grades, attended a similar university and studied the same undergraduate subject (also with the same gender, ethnicity, UK region of origin and office location and applied to the same employer), they are still less likely to obtain a job offer because they are more likely to apply later.

Our findings suggest that employers who can reduce or remove the delay in applications from working class applicants, will likely see an improvement in the offer rates to working class applicants to their graduate schemes. We therefore argue that improving the ‘application readiness’ of working class applicants may be low hanging fruit amongst the many challenges which exist in improving social mobility into professional careers.

Even applying a few weeks earlier can make a difference to a candidate’s chance of obtaining a job offer. We found that applying one month earlier is associated with around a 6% increased chance of obtaining a job offer (0.4ppt benefit per month, mean offer rate 6.3ppt), even among otherwise similar candidates.

Closing windows

Highlighting the importance of application readiness for working class applicants is particularly timely as data from the Institute of Student Employers (ISE) Recruitment Surveys 2021 to 2024 shows that recruitment windows have been narrowing over recent years. In the last year of available data from the 2023/2024 recruitment cycle collected in July 2024, 38% of employers closed graduate recruitment between October to December (2023), compared to 24% the previous year and 14% in the year before that (Figure 1). In our own data from employers, we show that by the start of an undergraduate’s final year of study (early October), the accountancy firms in our sample have already received 30% of applications and made 50% of job offers for graduate schemes starting the following September.

Figure 1: Recruitment campaign closing date trends

The ISE suggest the decision of graduate employers to close earlier this year may have been a response to being overwhelmed by the recent 59% increase in graduate job applications and the record high ratio of applications to vacancies (140:1), the highest recorded in over 30 years. It is likely this huge increase in application volumes is due to the increasing use of AI by applicants and the ongoing removal of academic attainment criteria . Our findings suggest that if this early closure trend continues it risks further disadvantaging lower SEB candidates.

The work experience ‘treadmill’

Initial feedback from discussing our findings with universities and employers highlighted that lower SEB candidates may apply later to graduate schemes for many reasons including less awareness of application deadlines; being unaware that employers may close recruitment early; less confidence in their application so they may take longer to prepare; and being more likely to be balancing competing priorities of study and graduate job applications with part time employment.

This issue of ‘application readiness’ is also far from confined to graduate scheme applications. Internships, undertaken a year earlier, also face a similar issue as undergraduates must be ready during their second year of university to apply to these programmes. Figure 2 shows that state school applicants ‘under’ apply to internships, whereas private school applicants ‘over’ apply, relative to the graduate talent pool. In other words, applicants to internship routes from independent schools are hugely overrepresented relative to the proportion of graduates from our national benchmarks attending these types of schools, with double the proportion applying to internship routes (27% compared to 13% nationally). State school applicants are therefore underrepresented in applicant pools for internships, but crucially when they do apply, they perform equally as well as independent school students during the recruitment process (Figure 3). So the key here is encouraging undergraduates from state school to be ready to apply for internships during their penultimate year at university – and as early as possible within that year.

Figure 2 : Proportion of interns at various stages of the recruitment process, by school type

Figure 3: Offer rates to internship programmes, conditional on observable differences across applicants, by school type

 

Given the drive for employers to lock in talented undergraduates early, awareness of application deadlines and requirements can also be important for students as early as first year where undergraduates scramble to apply for spring internship opportunities as soon as they enrol in first term. The ‘treadmill’ of work experience schemes is therefore starting earlier in an undergraduate’s journey, with high conversion rates to competitive graduate jobs for the lucky few. As one young person told us this week, “having the right information makes it easier to be lucky”.

Recommendations

To improve the ‘application readiness’ of underrepresented applicants we therefore recommend:

• Employers clearly communicate planned recruitment windows and emphasise to university careers teams and students that you may close early if vacancies are filled or if you’re managing the pipeline due to a high volume of applications.
• University careers teams reach students early (in first or early second year) and where possible embed awareness of recruitment demands into the curriculum as early as possible. For undergraduates from underrepresented groups to be successful they need to know the ‘rules of the game’ they’re playing.
• Universities make clear to disadvantaged students that applying early to graduate and internship schemes is likely to improve their chances of success.
• Employers and university careers teams collaborate to build the confidence of underrepresented groups to apply earlier, factoring in the competing demands these students may be juggling. This includes providing guidance on testing requirements and practice tests. This has the double benefit of giving students who might not have a support network familiar with recruitment processes the chance to overcome a lack of confidence with testing through repeated practice and increasing the chance of their making early applications to graduate schemes.
• Employers consider opening spring week schemes to undergraduate students from all years and internships to finalists (as well as penultimate year students) to enable talented students from underrepresented groups a better chance of participating in these schemes.
• Employers expand outreach efforts to attract state-educated applicants to internships, given their high conversion to graduate roles.

 

 

 

By Dr Claire Tyler, Professor Lindsey Macmillan, and Dr Catherine Dilnot

Yesterday we released our Nuffield-funded ‘Inequalities in Access to Professional Occupations’ report, and an accompanying blog post showing that working class students are well represented in application pools for professional graduate roles but are 32% less likely to receive job offers than applicants from professional backgrounds.

In today’s blog post, we focus in on analysis from the accounting and professional services sector to ask why we see these differences in offer rates for working class applicants. This sector is broadly representative of the full sample of employers we work with but were able to share more detailed data on applicants. Among applicants to the accountancy sector, 7.0% of applicants from professional/managerial backgrounds receive job offers compared to 4.8% of applicants from working class backgrounds (31% less likely). But which specific characteristics explain the socio-economic background (SEB) gap?

Figure 1 decomposes the SEB gap into three elements – unfavourable, favourable and unexplained parts. Unfavourable characteristics (in orange) reduce the chances of working class applicants obtaining a job offer, whereas favourable ones (in green) increase these chances.

Figure 1: Decomposition of the working class disadvantage in graduate offers in the accounting sector

 

Education does not equalise opportunities

Starting first with the unfavourable characteristics, we know from existing research that working class applicants are likely to have lower prior attainment and attend lower ranked universities than their more privileged peers.

Working class applicants in our sample achieved one grade lower at A-level than their peers from professional backgrounds (124 v 132 UCAS tariff points). Each grade lower reduces the chances of being an offered a job by around 10% (0.6ppt penalty, mean offer rate 6.3%) even when applicants are comparable on a range of other characteristics. This accounts for one third (34%) of the difference in offer rates by socio-economic background.

Working class applicants are also more likely to attend lower ranked universities than their peers from professional backgrounds. This accounts for a quarter (27%) of the gap in offers. Degree class also makes a small contribution (2.8%) due to small differences in university attainment which are magnified by the importance of educational attainment for these careers. This indicates that the university attended accounts for a significant part of the SEB gap over and above attainment prior to university.

But yet even if a working class applicant gets the same prior attainment, attends a similar university courses, and performs similarly well as someone from a professional background, the working class applicant is still less likely to get an offer. Education therefore is not equalising opportunities for young people to enter professional careers.

Applications matter

‘Application readiness’ is an important driving factor of the SEB gap as working class applicants apply later on average to graduate schemes than their peers from professional backgrounds. This accounts for 11% of the difference in offer rates. By the start of an undergraduate’s final year of study (early October), the accountancy firms in our sample have already received 30% of applications and made 50% of job offers for graduate schemes starting the following September.

But in contrast, applicants from working class backgrounds made favourable application decisions relating to their choice of employer and line of service. These applicants were more likely to apply to the ‘least competitive’ accountancy firm and service line (although all are very competitive) which improved their chances of obtaining a job offer. For example, applying to audit rather than consulting roles can double an applicant’s chance of obtaining a job offer.

Double disadvantage

Working class applicants are also more likely to be of Asian or Black ethnicity than their peers from professional backgrounds. Barriers for these ethnic minorities, which are not explained by the other characteristics in our data, account for 12% and 3% of the SEB gap respectively. This highlights the importance of intersectional analysis to identify further barriers in the recruitment process for ethnic minorities from working class backgrounds.

Together these elements explain almost two-thirds (62%) of the SEB gap in entry-level access to the accountancy profession.

What’s left?

Over one third (38%) of the SEB gap in entry level access to the accountancy profession remains unexplained by the detailed data, including a range of factors which are not significant drivers of the SEB gap here and therefore do not account for this unexplained gap. These include subject choice, use of networks, postgraduate qualifications, UK region of origin and UK region of office applied to. So this SEB gap remains even when taking all these factors into account. Other potential unexplained barriers may include performance on online tests (only those uncorrelated with educational attainment as those correlated will already be captured by our analysis), quality and duration of work experience, quality of networks used, commercial awareness, cultural capital and private schooling.

The firms in our sample have proactive social mobility strategies, are strong performers in the Social Mobility Employer Index, and are open and generous with their data for research purposes, yet still barriers for working class applicants remain. We suggest these barriers may be even larger for employers who are at the beginning of their social mobility journey.

Recommendations

Employers from all industries should review the extent to which they are rewarding potential in their recruitment processes and whether prior educational attainment criteria (or tests correlated with these) may be a barrier for high potential working class applicants entering their organisation.

Policy makers should improve the chances of high potential young people from all backgrounds being able to achieve the highest levels of academic success which are required for entry to competitive professional careers.

Greater information, advice and guidance should be provided to working class applicants relating to timelines and requirements of graduate scheme applications to improve their ‘application readiness’. This should include improving readiness for internship applications due to their high conversion rates to graduate roles. Guidance about which sectors, employers and roles are most or least competitive may also be useful for working class students to partly offset their educational disadvantage.

By Professor Lindsey Macmillan, Dr Claire Tyler, and Dr Catherine Dilnot

We know that people from working class backgrounds and ethnic minority groups have worse labour market outcomes than their more affluent and white peers. We also know that they are less likely to work in professional occupations early in their careers. These are the types of roles that offer the first rung of the ladder to careers with higher levels of job security, and better longer term earnings prospects, so this ultimately limits their social mobility. Yet to date we have not been able to distinguish between whether a) working class and ethnic minority groups are not applying to these roles, or whether b) they are applying but are not being hired. Our new Nuffield-funded report provides the first large-scale multi-sector evidence that these disadvantaged groups are applying to these roles but are not being offered positions at the same rate as their more advantaged peers.

Recruitment processes rather than outreach?

Using unique individual-level information on over 250,000 applicants to 17 employers’ entry-level roles across accountancy, law, and the public sector, we can show that most of the socio-economic background (SEB) and ethnic inequalities that we observe in entry to professional roles appear to be driven by employer decisions made during the recruitment process rather than a lack of aspiration or applications from underrepresented groups. .

While there has been a lot of emphasis on outreach from employers to diversify workforces, we find that the applicant pools to graduate programmes are representative of the available pool of talent from linked-administrative data records. While rates of withdrawal from programmes are equally spread across applicants from different backgrounds, final job offer rates are heavily skewed in favour of more advantaged applicants (with parents from professional backgrounds) and white applicants. Working class applicants are 32% less likely to get a job offer than their more advantaged counterparts. Black and Asian applicants are 45% and 29% less likely to get a job offer than their white counterparts respectively.

Figure 1: Proportion of graduates at various stages of the recruitment process, by parental NS-SEC

 

Figure 1 illustrates this point for working class compared to professional background applicants. The first column shows the proportion of all graduates that come from each social class, based on linked-administrative data (National Pupil Database linked to Higher Education Statistics Agency data) breakdowns. The second column shows our total applicant pool to graduate-level entry routes across all employers. As we can see, working class applicants (green part of the bar) are well represented in the pool of applicants. But as we move to the third and fourth bar, the proportion of working class applicants drops while the proportion of professional background applicants increases through the recruitment process.

These translate to offer gaps of over 30% for working class applicants relative to professional background applicants when we model offer rates for those who have not chosen to withdraw from the recruitment process – focusing then on only decisions made by employers rather than individual applicants. Of course, it could be the case that working class applicants have different prior attainment or live in different places to more advantaged applicants, and this could be leading to them being less likely to receive job offers to these programmes. Our analysis allows us to take this into account by looking at offer rates between applicants from different backgrounds with otherwise similar characteristics, comparing like-for-like. When we do this, as shown in Figure 2, we still find that working class applicants are 18% less likely to get a job offer than applicants from professional backgrounds, even comparing applicants who attended similar universities, studied similar subjects, and applied to similar roles.

Figure 2: Offer rates to graduate programmes, conditional on observable differences across applicants, by parental NS-SEC

Note: Raw models contain employer fixed effects only; + Demographics adds controls for region of origin, and visa status; + University adds controls for university category and subject studies; + Application adds controls for networks, region of office, and job role applied to. Points represent % estimates while lines represent 95% confidence intervals.

 

For ethnic minority applicants, we see a similar story – ethnic minority applicants are actually overrepresented in the applicant pools for these graduate training programmes, but are less likely to receive job offers, relative to white applicants. This is true even when we take into account differences in prior attainment and other factors that might lead to differential offer rates. Figure 3 shows that Black applicants are still 33% less likely to receive a job offer than a white applicant, even when comparing applicants that look the same on paper. Asian applicants are 25% less likely to receive a job offer than their similar white counterparts.

When considering the intersection between socio-economic background and ethnicity, we observe a double disadvantage for working class ethnic minority groups, who are 37% less likely to get an offer than otherwise similar white applicants from professional backgrounds.

Figure 3: Offer rates to graduate programmes, conditional on observable differences across applicants, by ethnicity

 

Note: Raw models contain employer fixed effects only; + Demographics adds controls for region of origin, and visa status; + University adds controls for university category and subject studies; + Application adds controls for networks, region of office, and job role applied to. Points represent % estimates while lines represent 95% confidence intervals.

 

Recommendations

The analysis and discussions with employers and universities has led us to make a number of recommendations. For employers, there’s a clear need for more tracking of diversity data and reviewing of recruitment processes. Employers who performed particularly well at maintaining diverse applicant pools proactively monitored their recruitment processes and their applicant pool. The report goes into more detail about particular stages of the recruitment process that are problematic and close monitoring of both online testing and design of face-to-face assessments could lead to wider recruitment of potential talent. Employers should also look to broaden the group of universities they work with and ensure there is relevant assistance for careers teams to support their students in applying to roles. Universities can also play a key role in ensuring that information is readily passed on to those who need it most, including the benefits of applying early to graduate schemes, and providing more assistance with tests and assessments.

Claire Crawford

The manifestos are out and the general election is looming. We at CEPEO, as the name suggests, are particularly interested in education policy and equalising opportunities. So, what did the manifestos actually tell us about potential plans in these areas? We focus here on plans set out by the Conservative, Labour and Liberal Democrat parties.

While the details differed, there were some agreed areas of importance across the parties: the need to recruit, train and retain high quality teachers; to do more to support children with special educational needs; and to incentivise more adult learning. These issues would probably appear quite high up most lists of pressing issues likely to be facing the Department for Education over the next few years.

There was also an emphasis on support for disadvantaged students. The Conservatives highlighted £3bn of spending via the pupil premium – helpful, of course, but only so high because of the very large proportion of pupils eligible now – 25% as of January 2024. Some of this rise is driven by transitional arrangements for Universal Credit, but I’m sure we could all agree that it would be better for far fewer children to be experiencing low family income, even temporarily.

The Liberal Democrats promised to go further on this front by tripling the early years premium to bring it closer to the amount allocated to school children – and extending the pupil premium it to those aged 16-18 as well – both very welcome ambitions. There were no specific details on this issue in the Labour manifesto, but one of their five missions is to break down barriers to opportunity, so there may be more specific announcements to come if they are the ones in office come 5^th July.

There were also some clear omissions though. There was very little detail on what might be done to shore up HE funding. Labour and the Liberal Democrats were clear that ‘something’ should be done, but unclear what that would look like. Certainly no-one was brave enough to say that tuition fees might need to go up substantially. We can probably expect another independent review in the coming months to spell out the unappealing choices. The Lib Dems did commit to reintroducing maintenance grants, though, while the Conservatives re-emphasised their plan to close down “poor quality” degrees, which of course are challenging to identify and may disproportionately affect those from lower socio-economic backgrounds, as we have discussed previously.

In contrast to the strong focus on the importance of high-quality staff for schools, there was also very little in the way of detail on a potential workforce strategy to help deliver the extended early education entitlements to children in working families from 9 months, which both the Conservatives and Labour have committed to delivering. The Conservatives are presumably relying on the market to deliver the places (and staff), incentivised by the higher funding rates they have committed to over the coming years. Labour are planning to re-use freed-up space in primary schools to deliver more places, but have not provided any specific details of their plans for the workforce.

While it is possible that providers will use some of the higher government funding to pay staff more, the market does not provide a strong incentive to invest in high quality staff – or in quality more generally. It is challenging for parents to identify setting quality (beyond Ofsted ratings) and many also weigh other considerations – such as availability and convenience – more highly when choosing a place for their child, suggesting that more will need to be done if we are serious about delivering high quality early education.

There is also a lot more that could be done to distribute this funding more equitably, as I spell out in this companion piece. And, of course, it would have been great to see consideration of some of our more ambitious policy priorities to equalise opportunities, including reforming school admissions, introducing a post-qualification admissions system and greater commitment to funding for further education (although credit to the Liberal Democrats for making an explicit commitment on this).

Of the three, the Liberal Democrat manifesto was the most ambitious in terms of the number and scope of specific policy ideas to equalise opportunities – but it certainly wasn’t radical. We must therefore hope that the next government is going to over-deliver on its manifesto commitments. For, as my colleagues so eloquently put it in a recent blog post, there can be no economic growth without education and skills. Ensuring that the benefits of this growth are distributed equitably starts with the education system. We here at CEPEO therefore hope that bolder action to equalise opportunities in education is just around the corner, whichever party is in power next month.

By Professor Lindsey Macmillan and Professor Gill Wyness

We were having a discussion in our CEPEO team meeting yesterday about Spring Budget 2024 and the implications for education policy. As we outlined in our Twitter thread, there’s resounding disappointment across the education sector based on the announcements, with very little offered in terms of investment in education and skills. It’s no real surprise of course, given there is no money. Without any real prospect of economic growth this will be the story for the foreseeable future. And yet, and this is the catch-22 of it all, we cannot have growth without a focus on education and skills. In the words of John Maynard Keynes “We do nothing because we have not the money. But it is precisely because we do not do anything that we have not the money”.

Lip service is often paid to the importance of education and skills for growth, and we hear regularly about investments to support the development of skills in particular sectors – AI or green growth, for example. But while these skills are undoubtedly going to be important for future growth, it is the skills of the many, not the few, that are critical for productivity. And, as we know from a wealth of evidence about the effects of the pandemic, the challenge here is a daunting one. We can see from the most recent assessments at the end of primary school that the proportion of pupils reaching expected standards in reading, writing, and maths are down to 60%, levels not seen since 2016. In addition, inequalities have risen. The disadvantage gap is now higher than any point in the past decade.

As outlined in the Times Education Supplement piece this morning, there was a fully-costed education strategy put in place by Sir Kevan Collins, at the request of the government, in 2021 to help children who had missed school during the pandemic. This was based on the idea of three Ts. Teachers, Tutoring, and Time. Invest in the education workforce, invest in tutoring, and invest in extending the school day. Each one supported by rigorous evidence. And each one intertwined with the other to create complementarities to support education recovery. £15 billion was the ask, equivalent to £1,680 per pupil. This might sound like a lot of money but it was against a backdrop of estimates of the economic cost of learning loss reaching as high as £1.5 trillion, because of a lower-skilled workforce. In the end, only one tenth of this £15bn was offered up by the then Chancellor (and current PM), prompting Sir Kevan Collins’ resignation.

This is one example of the short-termism of government policy relating to growth: the reluctance to spend money now for the sake of future benefit. Those incomprehensibly large numbers of the economic costs of learning loss won’t fully hit now, but will instead permeate for decades to come. This means there is little incentive to spend the required money now; government won’t see the immediate benefits and get direct political gain in this election cycle.

Human Capital or Signalling?

A telling part of Sir Kevan Collins’ interview is that there was some kind of idea that the learning lost during the pandemic “would all just come out in the wash”. That children and young people who missed months of school would just catch up with little intervention required.

But this suggests that children can miraculously learn more in a year than they might otherwise have done with no further investment. That somehow teachers could be more productive after the pandemic than before – despite the myriad other challenges the pandemic created or worsened, not least significantly higher school absences. It also suggests that the government didn’t think that investment in the education system would have led to more learning.

But that goes against one of the fundamental theories of economics – human capital theory. The idea is that education increases the stock of human capital – skills – and higher skills fuel productivity and the economy, so investing in education is one of the most effective ways to drive sustainable economic growth. This is backed up by a wealth of evidence establishing a positive return to individuals and the wider economy from investing in education. Furthermore, education has been shown to have wider social benefits as more educated societies have higher levels of civic participation, better birth outcomes and reduced crime. We outline this in more detail in our briefing note “Does education raise people’s productivity or does it just signal their existing ability?”

There was also a lot of discussion at the time that learning loss didn’t matter anyway – because education is just there to act as a signal to employers about the relative abilities of different individuals, rather than something that directly improves their productivity. In other words, if someone has 3 A*s at A level, this tells an employer that they are a better worker than someone with 3 Bs, and it doesn’t matter how much knowledge or skills the person with 3 A*s actually has. But the evidence around this is much weaker as our briefing note describes.

Wasted talent

Linked to this is the belief that learning loss would be equally felt by all pupils. But again, the evidence (including from our own COSMO study) has shown the opposite. Learning loss is felt much more by pupils from disadvantaged backgrounds, and thus failing to invest in catch-up has compounded inequality. This inevitably results in wasted talent, further stifling economic growth, as outlined in our UKRI-funded project exploring the links between diversity, education and productivity. Evidence from the US shows that between 20-40% of economic growth over the last 50 years resulted from a better allocation of talent.

Failing to invest when pupils are young also has knock on effects. Education and skills are like building blocks. It is much easier to build an individuals’ skills if they have an existing foundation of basic skills to build upon. This in turn leads to higher returns on investment, as individuals become more and more skilled.

The catch-22 illusion?

This isn’t the first time education has been side-lined in recent budgets. Even the childcare announcement of 2023 was really about increasing labour force participation, rather than investing in early childhood education.

This short-term outlook is the government catch-22: we need growth to invest, but we can’t invest without growth. We need to break this cycle and understand that human capital is the fundamental underpinning of economic growth.

By Dr Claire Tyler

CEPEO recently launched New Opportunities: our evidence-based policy priorities for equalising opportunities. In this weekly blog, we are highlighting one of our priorities and the reasoning and evidence behind them. This week, we are focusing on socio-economic inequalities in the workplace and how employers can use data to create more socially diverse and inclusive organisations.

Evidence consistently shows that an individual’s social background predicts their chances of accessing a ‘top job’ such as a professional or managerial career – for example, 74% of medical professionals, 64% of journalists and lawyers and 89% of senior financial services professionals originate from professional or managerial backgrounds compared to 33% of the population. Two-fifths of Britain’s ‘leading people’ attended independent schools compared to 7% of the population. Even comparing graduates with similar academic backgrounds, privately educated graduates are still a third more likely to enter top jobs than comparable peers from state school.

But this isn’t just an issue of access: large socioeconomic pay and progression gaps also exist within many occupations. Individuals from working-class backgrounds earn 16% less in top jobs compared to colleagues from more privileged backgrounds. And These issues of access, pay and progression gaps by social background mirror those faced by women and ethnic minorities in the workforce. These gaps could therefore be targeted by a similar data-led policy approach – mandatory gender pay gap reporting was introduced in 2017 in the UK and mandatory ethnicity pay gap reporting is on the horizon after the government released guidance for voluntary reporting last month.

So what do we propose? We suggest the introduction of both entry and pay gap audits by socio-economic background. Employers would report: 1) the proportion of individuals from different socio-economic backgrounds entering occupations (which are easily compared to national benchmarks), and 2) pay inequalities by socio-economic background in a similar way to current gender pay-gap reporting. This policy would shine a light on current disparities in both access and progression of individuals from lower-socioeconomic backgrounds and reveal if career opportunities are being equalised over time.

Why is this a policy priority? Creating a level-playing field in the workplace is not only the ‘right thing to do’; it is also economically advantageous – a win-win strategy. Recent work shows that reduced workplace discrimination improves the allocation of talent in the labour market and drives economic growth. The growing ‘business case’ for diversity argues that more inclusive workforces drive profitability, innovation and better decision making.

It is also the right time for such a policy – the growth of EDI (equality, diversity and inclusion) agendas alongside more responsible and sustainable business practices (such as ESG reporting) has raised the profile of socio-economic diversity in recruitment, promotion and retention. Young people increasingly aspire to work for companies with a strong commitment to diversity – 72% of workers aged 18- 34 recently said they would consider turning down a job offer or leaving a company if they did not think that their manager (or potential manager) supported EDI initiatives. The policy would also crucially provide employers with a baseline for monitoring the impact of their own diversity initiatives and identify ‘what works’ for creating more diverse organisations –particularly vital insight at time when early talent teams are dropping academic credentials, navigating hybrid working for new recruits and designing alternative pathways into careers to widen and diversify their talent pools.

The policy is also likely to have a substantial impact – recent evidence on the effectiveness of UK gender pay gap legislation shows that pay transparency increases the probability of women working in above-median-wage occupations by 5% and closes the gender pay gap by 18%. Evidence on social background shows that firms returning year-on-year to the Social Mobility Employer Index are more likely to demonstrate progress on social mobility – they are four times more likely to be collecting at least three socioeconomic background data points than new entrants to the index, suggesting that transparency and focus can facilitate change.

While most policy levers available to government to equalise opportunities occur before labour market entry, this policy priority highlights one way in which government can hold employers to account for their role in equalising opportunities. If the government is committed to collecting and using data differently to improve social mobility (as stated here), introducing entry and pay gap audits by social background is a cost-effective place to start with benefits for employees, firms and society.

 

 

 

 

 

 

 

 

 

Jake Anders is the Principal Investigator of the COVID Social Mobility & Opportunities study (COSMO), and Associate Professor and Deputy Director of the UCL Centre for Education Policy & Equalising Opportunities (CEPEO)

Today marks an important landmark in the COVID Social Mobility & Opportunities study (COSMO) and, with it, our understanding of the unequal impacts of the COVID-19 pandemic on young people’s life chances. After more than 18 months of development and fieldwork, we are releasing initial findings and data from the first wave of this planned cohort study.

Unlike much other research from the pandemic, COSMO comes as close as possible to recruiting a representative group of young people from across the country. This is because it is based on invitations to a random sample of all young people in schools across England, rather than a convenient sample collected for some other purpose who are not, therefore, necessarily similar to the population of young people as a whole. Why does this matter? Having a representative sample gives us increased confidence that our findings paint an accurate picture of the extent and variation in the experiences of this group.

As a result, we are extremely grateful to the more than 13,000 young people across England who responded to our invitation to take part in this study, providing us with details of their experiences to help us build up a picture of the lives of this generation and how it has been disrupted. Through this, COSMO is providing vital new evidence on the effects of the pandemic on the lives of young people, with strong signs that it has severely widened existing educational inequalities: 80% of participants told us their academic progress suffered because of the pandemic’s disruption — a figure that is even higher among those from less advantaged backgrounds. Moreover, there are worrying signs that initial impacts have not been fully addressed by the policy response in this country: only about a third of young people told us they have been able to catch up with their lost learning.

Participants’ views on whether their academic progress has suffered

We are documenting aspects of young people’s experiences during and beyond the pandemic in a series of briefing notes authored by members of the COSMO research team, with the first three of these on ‘lockdown learning’, ‘education recovery and catch up’, and ‘future plans and aspirations’ released today and more to come. These shine a light on important details of young people’s experiences.

Changes to educational plans by COVID-19 status

They highlight, for example, that well over half of young people report some change to their education and career plans because of the pandemic, and that this is particularly the case among those who report more acute direct experiences of COVID-19 itself, raising important questions about the consequences of such shifts if they are realised in the years to come.

They also increase our understanding of barriers to learning in lockdown, helping us to break down the factors that seemed to limit home learning, notably the lack of suitable electronic devices to engage in remote lessons or other online educational activities — this is particularly concerning given that over half of those who lacked such a suitable device told us this need had still not been met at the end of the second period of national school closures.

The extremely rich data from COSMO covering the circumstances and experiences of this representative sample of young people, are now available for other researchers to use to address other vital research questions. COSMO is not just a standalone effort to set out the findings as we see them, but also a resource to support others carrying out research to understand this generation.

But, importantly, COSMO’s ability to tell us about these short-term effects is just the start. COSMO is designed as a cohort study, which means that we aim to continue following the lives of its members over the coming years. Just as we are publishing findings from our first survey, we are just getting started in the process of inviting members of the cohort to take part in the first follow-up. Establishing this link through time will be vital to understanding whether conditions during the pandemic have lasting consequences for decisions that young people make about their wellbeing, education, careers and more. Cohort studies for previous generations, such as the British Cohort Study that continues to follow a group of people born in 1970, have been vital to illuminating our understanding of social mobility in society – extending such understanding to the current generation with their unique experiences completing their education will only become more vital.

Whether or not we think of the pandemic as over, its effects will continue to cast a long shadow, and COSMO will continue to help us to understand this in the years to come.

Arun Advani and Claire Crawford

Today marks the launch of the Department for Education’s new Unit for Future Skills (UFS). Its remit is to use existing data – and champion the creation of new data – to better understand the skills businesses want and whether the education and training system is delivering them.

A focus of the UFS is to improve understanding of ‘skills mismatches’ – the gaps between the demand for and supply of different skills. The idea is that by learning more about skills mismatches and, crucially, their sources, we can design more effective policies to close these gaps, and hence raise productivity.

The UFS was the brainchild of the current Secretary of State for Education, Nadhim Zahawi. Its origins, though, lie at least in part in the Skills and Productivity Board (SPB), set up by the former Secretary of State for Education, Gavin Williamson, to investigate both skills mismatches and how skills contribute to productivity. The SPB comes to an end as the UFS launches.

This apparent change in remit between the UFS and its predecessor is an important one. While the focus of the new unit on collating and sharing data is undoubtedly welcome, the loss of the explicit link to productivity risks losing the ‘bigger picture’ rationale for such a unit.

Part of our work on the SPB – on which we sat alongside four other academic experts – was to provide some initial insights into the skills which seemed to have significant mismatches between demand and supply, or for which demand was likely to grow over time.

Unfortunately, the data at our disposal were not well suited to identifying skills mismatches, and we made a series of recommendations to the Secretary of State about the ways in which the UFS could improve upon this. For example, information about the demand for skills is collected either using relatively small-scale national surveys or in different ways across different local areas, for example as part of the new Local Skills Information Plans, making granular information that is comparable across areas difficult to obtain. Instead, we had to infer the demand for skills by combining information on the number of jobs in different occupations in the economy with the importance of each skill in those occupations.

The difficulties in identifying the supply of skills were even greater: while the Longitudinal Education Outcomes (LEO) data provides excellent information about the qualifications of younger cohorts in England, there is no straightforward way of identifying which skills – rather than knowledge – different qualifications develop, and no way to reflect the skills that workers acquire – or indeed lose – through on-the-job training rather than in formal education.

Despite these challenges, our analysis highlighted some skills which seemed to be particularly important and potentially worthy of further investment by the government:

• We identified a set of ‘core transferable skills’ that are important across a large number of jobs in the economy now, and are expected to remain so in future. These skills included communication skills, people skills and ‘information skills’ – including decision-making, problem solving and critical thinking. Ensuring people have these skills means they should be equipped to perform a range of jobs well, and should also help them to transfer between jobs as needed.
• We also identified a set of skills that, despite being important for only a small number of jobs, seem to be in shortage now, and are valuable in occupations that contribute disproportionately to productivity. These include Science, Technology, Engineering and Maths (STEM) knowledge and the application of this knowledge, including scientific and mathematical reasoning.

The appropriate policy responses to these findings are not straightforward. While encouraging more people to study STEM subjects may be sensible for many reasons, it may not help fill STEM job vacancies: not if the main challenge is that these occupations pay a lot less – or have other less attractive job characteristics – than occupations in which those skills can be equally effectively applied and are rewarded more highly.

In bringing together richer skills and labour market data, the work of the UFS should enable us to better understand these issues and support the development of policies to eliminate these gaps. But an important question is how far eliminating skills mismatches – and indeed increasing skills more generally – can get us in terms of boosting productivity, especially in ‘left behind’ areas.

One potential risk of relying heavily on skills investments as a route to ‘levelling up’ is that higher skilled or more educated individuals may move away, meaning the areas in which the investments are made do not benefit fully from those investments. We already know this is the case for many graduates.

But our work suggests that, unlike graduates, those with lower level qualifications are highly likely to remain in or close to the areas in which they grew up. While around half of both graduates and non-graduates have moved at least locally by age 27, only one in six non-graduates moves to a different commuting area, compared to a one in three graduates. Amongst those who move, a majority of non-graduates move less than 5km, compared to more than 20km for graduates. This suggests that poorer performing areas would benefit from investments in skills, at least up to degree level.

Our work also suggests that while a substantial proportion (two-thirds) of the difference in wages (a proxy for productivity) across areas can be explained by the qualifications and skills of the individuals living in those areas, a significant minority (one-third) cannot. This highlights that investments in human capital (skills) on their own will not be enough to ‘level up’. Such investments will need to be supplemented with investments in other types of capital – the type and extent of which will differ from place to place – to ensure that the benefits of investments in education and skills can be fully realised.

Better data will help shed light on the extent of and reasons for skills mismatches, and hopefully lead to policies aimed at addressing these mismatches. However, reducing mismatches alone is unlikely to be sufficient to deliver the necessary boost to productivity if we are to eliminate differences across areas, or between the UK and its international competitors.

Without greater demand for skills, particularly in poorer performing areas of the country, we risk levelling down rather than levelling up. It is crucial that the UFS works closely with colleagues across government and in local areas to ensure that they support the ‘productivity’ as well as the ‘skills’ part of the board they are replacing.