Education, social mobility and outcomes for students receiving free school meals in England: initial findings on earnings outcomes by demographic and regional factors

• At age 25 years, 23.0% of free school meal (FSM) recipients who attended school in England had recorded earnings above the annualised full-time equivalent of the Living Wage in comparison with 43.5% of those that did not.

• 18.2% of females who received FSM had recorded earnings above the Living Wage compared with 27.8% of males who received FSM; for non-recipients, the proportion was 39.3% and 47.5% respectively.

• The East of England had the greatest proportion of FSM recipients with recorded earnings above the Living Wage (29.5%), the smallest proportion was in the North East, where it was 19.9%.

• The difference in the percentage of FSM recipients and non-recipients earning above the Living Wage was broadly similar in all regions, at around 20 percentage points.

• For both females and males, the difference between FSM recipients and non-recipients earning the living wage was broadly similar in every region.

• In every region, the proportion of males who received FSMs earning above the Living Wage was larger than the proportion of female FSM recipients.

• Earnings distributions by FSM status show that proportionately fewer FSM recipients obtained high earnings than their non-recipient counterparts.

Longitudinal Education Outcomes (LEO) data are used to explore whether people who grew up in low-income households experienced earnings mobility in young adulthood. This is measured by using free school meal (FSM) status, and whether an individual's annual earnings are greater than the Living Wage in the tax year when they turned 25-years-old (more information can be found in the Methodology section). The Living Wage is a voluntary pay standard calculated based on the cost of living using a basket of goods and services, updated annually. Its use in this analysis is to provide a reference point for comparison.

The data are split into four categories:

• matched records that have recorded earnings above the Living Wage at age 25 years

• matched records that have recorded earnings below the Living Wage at age 25 years

• no recorded earnings at age 25 years

• those who were not matched to outcomes records at any age; this group is relatively small

Throughout the publication, individuals in each of these categories are shown as a percentage of the total of the four categories, except for geographical breakdowns where location data are not available for unmatched individuals. By including all groups, we focus on those that had earnings and contextualise them against their peers who were not earning.

This article highlights where there are inequalities relating to earnings and low-income households, in line with the Sustainable Development Goals (SDGs). All UK SDG data can be found on the Office for National Statistics SDG website.

At age 25 years, 23.0% of FSM recipients were matched to an outcome and had recorded earnings above the Living Wage and 42.0% had earnings below the Living Wage. Almost a third (29.2%) of FSM recipients were in the no recorded earnings group, with the remainder unmatched.

In comparison, 43.5% of non-recipients had earnings above the Living Wage. 

There was a 13.8 percentage point difference between the proportion of FSM recipients who had no recorded earnings at age 25 years, compared with non-recipients. As outlined in the Methodology section, this group should be treated with some caution; some of the individuals could have been in full time education, others in receipt of benefits.

A smaller proportion of females who received free school meals (FSM) earned above the Living Wage at age 25 years (18.2%) than males (27.8%). Longitudinal Education Outcomes (LEO) data does not include hours worked and reported earnings have not been annualised. This publication instead focuses on the total amount earned in one year, regardless of whether that is from a full-time job or a series of short-term, low hour contracts. Statistics show that females tend to work fewer hours in employment than males, so this is likely to account for some of the difference particularly for mothers of dependent children.

More than twice the proportion of female non-recipients (39.3%) earned above the minimum wage than their FSM counterparts (18.2%). The gap between recipients and non-recipients was slightly smaller for males, with 27.8% of males who received FSM earning above the Living Wage compared with 47.5% of male non-recipients.

Figure 2: Lower proportions of female free school meals recipients earned above the Living Wage than males

Earnings status at age 25 years by free school meal status and gender, tax year ending 2012 to tax year ending 2019

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There was variation within and between regions in the proportion of individuals earning above the Living Wage. Figure 3 shows the proportion of individuals in each region earning above the Living Wage, split by free school meal (FSM) status. The gap between the proportion of FSM recipients and the proportion of non-recipients earning the Living Wage was similar in all regions, at around 20 percentage points. The largest gap within a region was in the East Midlands, where 23.1% of FSM recipients earned above the Living Wage compared with 45.1% of non-recipients, a gap of 22 percentage points.

Earnings by FSM status also differed between regions. The East of England had the highest proportion of FSM recipients earning at or above the Living Wage (29.5%). This contrasts with the North East which had the lowest proportion (19.9%).

The Other UK category had the smallest difference between FSM recipients and non-recipients. However, as the population being studied is based on attendance in English schools, the numbers living in Northern Ireland, Scotland, and Wales at age 25 years are relatively small and may have specific characteristics (see Methodology section)​.

Figure 3: Across regions, the percentage of free school meal recipients earning above the Living Wage was consistently smaller than the percentage of non-recipients

Earnings status at age 25 years by free school meal status and region, tax year ending 2012 to tax year ending 2019

Notes:

1. Individuals who do not have a region recorded are not included in this chart.

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Proportions of females earning above the Living Wage were consistently lower across all regions than males for both free school meal (FSM) recipients and non-recipients. The exception to this was in London, where the proportion of female non-recipients earning above the Living Wage was slightly larger then males (1 percentage point).

The difference between genders among FSM recipients was widest in the North East where 13.1% of female FSM recipients earned above the Living Wage, compared with 26.6% of males. The gap for FSM recipients was smallest in London (2.4 percentage points).

The earnings differences between FSM recipients and non-recipients within each region were generally larger for females. The difference was largest in the South East where less than half as many female FSM recipients (23.0%) had earnings above the Living Wage, compared with female non-recipients (47.2%).

Figure 4: Across regions, the proportion of female free school meal recipients earning above the Living Wage was smaller than that of their male counterparts

Earnings status at age 25 by free school meals status, region, and gender, tax year ending 2012 to tax year ending 2019

Notes:

1. Individuals who do not have a region recorded are not included in this chart.

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Across the earning distribution, the proportion of free school meal (FSM) recipients was lower than the proportion of non-recipients. The proportion of FSM recipients decreased at a faster rate than non-recipients until earnings reached 1.5 times the Living Wage. After this point, the rate of decrease for FSM recipients slowed down until the proportion reached close to zero at a lower level of earnings than non-recipients. Where earnings were at least double the Living Wage the proportion of FSM recipients was 2.0% compared with 6.4% of non-recipients. 

Across the earning distribution, the proportion of males who received free school meals (FSM) was greater than females. The proportion of both groups decreased at a similar rate as earnings increased, however the proportion of female FSM recipients reached close to zero at a lower level of earnings.

Non-recipients follow a different pattern. The proportion of female and male non-recipients was almost equal to just above the Living Wage threshold, until earnings reached around 1.5 times the Living Wage. From this point, as earnings went up the proportion of female non-recipients decreased at a faster rate towards zero than the proportion of male non-recipients.

The total proportion of each group earning at least double the Living Wage was lowest for female FSM recipients at 1.0% compared with 3.0% of male FSM recipients. The group with the greatest proportion of individuals earning at least double the Living Wage was male non-recipients (8.7%).

Combined earnings

Combined earnings are an individual's total recorded annual earnings from employment and self-employment.

Earnings from employment in Longitudinal Education Outcomes (LEO) come from HM Revenue and Customs' (HMRC) pay as you earn (PAYE) system. This value is reflective of the rate of pay, and the number of hours and/or days worked.

The earnings from self-employment sole trader and partnership earnings data comes from self-assessment tax returns submitted to HMRC.

Free school meals

Free school meals (FSM) are a statutory benefit available to school-aged children whose families receive other qualifying means-tested benefits from the Department for Work and Pensions (DWP). Families need to register for them and not all families entitled to FSM go on to claim them. School Census data record only where learners are both eligible and register a claim. In England, universal FSM are provided for all infants in primary school.

FSM is a commonly used proxy measure for socio-economic disadvantage (including household income deprivation) during childhood. We use FSM eligibility in the academic year an individual started at age 15 years.

Gender

"Male" or "Female" as reported in the learner's Key Stage 4 (KS4) record.

Key Stage 4

KS4 is the period of education where qualifications such as GCSEs and equivalents are typically taken, usually covering ages 14 to 16 years in school years 10 and 11.

Living Wage

Also known as the real Living Wage or the voluntary Living Wage.

The Living Wage is calculated independently by the Resolution Foundation and overseen by the Living Wage Commission. It estimates the cost of living using a basket of household goods and services. There is a separate rate for London and the rest of the UK.

This is different to the government's National Living Wage, which was introduced in 2016 for employees aged 25 years and over.

Matched record

Matched records are those in LEO where an individual's education records have successfully been matched to their earnings or benefits outcomes records. Unmatched records are those that appear in the education data but could not be matched with earnings or benefits. Approximately 95% of records in LEO have been successfully linked.

The match rate varies by ethnicity, first language and geographical region. In some cases, a lack of match will be because of administrative reasons, for example names being changed or spelt inconsistently across data sources. In other cases, it will reflect a learner's activities: they may have moved out of the UK before ever working, have died, or not engaged with formal employment nor the benefits system at any point in their life.

No earnings record

This is where education records are matched to earnings and benefits information but there is no record of employment and subsequent earnings in the tax year they turn 25 years.

The main activities for this group could include:

• full-time education
• unemployed
• economic inactivity
• voluntary work
• imprisonment
• deceased
• living overseas

This group is different from the unmatched group.

Region

An individual's Government Office Region at age 25 years is taken from the government's Customer Information System (CIS). The CIS is updated when an individual notifies DWP or HMRC of a change of address or through interacting with a tax or benefit system, for example the address held by their employer's payroll. This means some geographies could be out of date.

This publication also uses "Other UK". It refers to individuals in Northern Ireland, Scotland, and Wales, plus those with an unknown UK address. The data are based on individuals who attended school in England. There are small numbers in the Other UK groups and findings should be treated with caution. 

A small number of records have region recorded as "Abroad". These have been excluded from the regional analysis.

Social mobility

The Social Mobility Commission broadly defines social mobility as the link between an individual's occupation, income, or circumstances and those of their parents. This publication estimates intergenerational social mobility by exploring whether an individual in a low-income household at age 15 years was still economically disadvantaged through low earnings by age 25 years.

Sustainable Development Goals

The Sustainable Development Goals (SDGs) are the United Nations' (UN) radical and ambitious Agenda for a more inclusive, sustainable and prosperous world that leaves no one and nowhere behind by 2030. There are 17 Goals, 169 targets and 247 indicators grouped under five pillars: People, Planet, Prosperity, Peace and Partnerships. Together, they give the world a focus. They aim to reduce poverty and hunger. They highlight important topics like health and education, economic growth, equal rights, justice for all and environmental balance. They promote the idea that sustainable development requires partnerships at local, national and global level to make progress.

This work was produced using statistical data from the Office for National Statistics (ONS). The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical data. This work uses research datasets which may not exactly reproduce National Statistics aggregates. These outputs must not be used without this disclaimer and warning note. 

Longitudinal Education Outcomes database

The Longitudinal Educational Outcomes (LEO) is a major database constructed by the Department for Education (DfE). As of 2021, LEO comprised 38 million individuals. It links administrative education data from Early Years through to Higher Education from DfE and the Higher Education Statistics Agency (HESA) with employment, benefits and earnings data from the Department for Work and Pensions (DWP) and Her Majesty's Revenue and Customs (HMRC).

However, some information is not available. HMRC pay as you earn (PAYE) records do not contain earnings information for "cash in hand" payment and the School Census does not include students who were home schooled. Qualification's data are available from each stage of education for learners who were registered for Key Stage 4 assessments from the 2001/2002 academic year to the 2017/2018 academic year and labour market outcome data are available from 2003/2004 until the 2018/2019 tax year. To be included in the LEO database with school level education and outcomes data, individuals must have been in the English school education system for a least one academic year.

As outcomes in this publication are focused on early adulthood, we studied individuals who turned 25-years-old in available tax years (2011/2012 to 2018/2019).

This analysis uses the LEO data asset available to researchers in the Secure Research Service (SRS), also referred to as the "standard release". Further information about LEO is available from DfE or the SRS.

Coverage and context

This publication looks at young people who meet both of the following criteria:

• were in the English education system at Key Stage 4 (KS4), including pupils from both the state and independent school systems

• turned 25-years-old between the start of the 2011/2012 tax year and the end of the 2018/2019 tax year

In total, 5,154,457 individuals are included in the analysis.

The population of interest is outlined in Figure 7 to Figure 11.

Measuring disadvantage during childhood

As details of family income and background are not yet available in the Longitudinal Education Outcomes (LEO) dataset, free school meals (FSM) eligibility is used as a proxy measure for individual level socio-economic disadvantage (including household income deprivation) during childhood. This is a common approach to identifying whether an individual grew up in a household with a low income. Pupils are classified as FSM eligible according to their status during the academic year they started at age 15 years. For most learners, this was the year they took formal KS4 assessments.

FSM status alone does not represent socio-economic disadvantage. Households close to or at the threshold of FSM eligibility criteria may be categorised differently but are likely to have had similar access to resources.

Measuring earnings deprivation in early adulthood

We calculated annual "combined earnings" at age 25 years using earnings from employment (pay as you earn (PAYE) records) and self-employment (self-assessment records). We focus on age 25 years as most people have completed formal full-time education and entered the labour market by this age. This definition is also consistent with Organisation for Economic Co-operation and Development (OECD) labour market statistics which consider ages ranging from 25 to 54 years to be "prime working life".

An individual's combined earnings are compared with the Living Wage for the tax year they turned 25-years-old.

Earnings from employment are distinct from full-time equivalent salary so will be affected by reduced participation in the labour market for reasons such as caring responsibilities or part-time study. Full-time equivalent salary currently cannot be derived using LEO because of a lack of data on hours worked.

Unlike some similar publications using LEO, the outcomes of females (who typically have lower labour participation rates and higher rates of part-time working) have been included in this analysis. This is because we want to capture individual earnings deprivation across the tax year regardless of the cause (low hourly pay or low hours worked).

The Living Wage Foundation sets an hourly wage rather than an annual salary. As LEO does not contain data on hours worked, "annual equivalent" values have been calculated based on full-time employment (37.5 hours per week) at the relevant hourly rate of pay. For example, in the 2018/2019 tax year, the hourly Living Wage had an hourly rate of £9.00 for the UK and £10.55 for London. The annual equivalent for that year was £17,550 (UK) and £20,572.50 (London).

The government's National Living Wage is a legal minimum hourly rate for people classed as "workers". The majority of people earning below the National Living Wage will be part time workers, or exempt, although some will be due to employers not complying with the law.

Based on matching criteria, employment status and combined annual earnings, individuals are categorised as follows.

• "Below Living Wage" - matched records that have recorded earnings at age 25 years below the annual equivalent of the Living Wage.

• "Above Living Wage" - matched records that have recorded earnings at age 25 years above the annual equivalent of the Living Wage.

• "No earnings record" - matched records that do not have earnings records at age 25 years but do appear elsewhere in the outcomes data.

• "Unmatched" - those whose education records were not matched to outcomes records at any age.

A small number of individuals have recorded earnings of £0. It is possible that they are still on a payroll system but not actively working for a company, for example because they recently left a job, are taking unpaid leave, or are employed on a zero hour contract. These individuals have been assigned to the "no earnings record" group.

Strengths of Longitudinal Education Outcomes data

LEO data come from population administrative records rather than labour market surveys such as the Office for National Statistics (ONS) Labour Force Survey (LFS). This means it can provide greater population coverage, greater accuracy, and longer reporting periods than other approaches to understanding labour market outcomes. LEO also provides detailed data on the educational attainment of individuals from Early Years to Higher Education which cannot be easily collected on a survey.

Limitations of Longitudinal Education Outcomes data

Missing data - LEO does not have complete coverage of every variable, with a small number of records missing values for FSM status or geography. When this is the case, a rules-based approach has been taken; for example, by assigning a region based on where someone lived in the tax year before or after the year in which they turned 25 years. Data may not necessarily be missing at random, and imputation may lead to measurement error.

Non-matches - match rates across LEO are generally high and vary between data sources and cohorts but are around 95% accurate on average. However, the probability of a successful match is not equal for all observations and varies according to characteristics such as ethnicity, location and first-language.

Coverage - LEO does not contain full data on people who were not in the English secondary school system. Regional estimates outside of England generally represent those who have moved to other countries within the United Kingdom and may have different characteristics to the rest of the local population.

Data availability - self-assessment data are only available from the 2014/2015 tax year onwards. Estimates of combined earnings are therefore missing sources of income for the 2011/2012 to 2013/2014 tax cohorts used in this publication.

An increase in the number of PAYE records is seen from April 2013, when HM Revenue and Customs (HMRC) changed their reporting policy. Prior to this date, employers were not required to report earnings for employees under the lower earning limit, although some larger employers would include them because of data transfer methods.

The authors welcome feedback and the opportunity to learn from best practices. This section details the planned developments to this analysis.

A series of publications will investigate additional educational and demographic factors associated with earnings including:

• highest level of qualification achieved
• qualification type
• route through education
• educational attainment at each stage of qualification
• type(s) of educational establishment attended
• apprenticeships
• subject(s) of study
• ethnicity
• special educational needs and disability
• English as a first language
• outcomes at age 30 years

We will examine how earnings outcomes are affected by the interactions of these factors. For example, whether the same routes through education tend to have similar outcomes for young people who received free school meals (FSM) but are from different ethnic groups.

Analysis developments

The Department for Education have calculated the main activity of individuals, including employment, full-time education, or claiming out of work benefits. Future work will use a similar approach to understand activity other than employment or reasons why earnings might be low. For example, someone who is both studying full-time and working.

Self-employment earnings were introduced to the Longitudinal Education Outcomes database for the 2014/2015 tax year. They provide evidence for another source of earnings for individuals turning 25-years-old after that tax year. We will use this to assess which groups are more likely to be self-employed and how this effects outcomes.

We will add a second outcome measure based on the deprivation level (measured using the index of multiple deprivation) of where individuals are living in their 25th tax year. This will investigate the rate at which people who are FSM eligible live (move into or stay) in the most deprived areas as young adults. Data will be broken down by the different demographic and educational factors to see where the differences between groups are. This will also be compared with those not eligible for FSM.

A FSM earnings gap will also be modelled; this will explore how average earnings in early adulthood differ according to FSM eligibility for equivalently educated people.