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Career pathways: post-16 qualifications held by employees
What are the career pathways statistics?
The statistics in this publication are focused on employees, the industry sectors they work in and their education achievements. They help us to understand:
The distribution of young employees across different industry sectors and regions in England (ages 25-30 in the 2018/19 tax year).
The education levels of employees within each industry sector.
The subject and qualification choices of employees within industry sectors.
The earnings of employees and how these vary by industry sector, education level, qualification choices and region.
The education pathways followed by employees of different industry sector.
The publication uses the Longitudinal Education Outcomes (LEO) study and the Inter-Departmental Business Register (IDBR) to bring together information on the education history of employees with their earnings and industry sector of their employment in the 2018-19 tax year.
Why have we published the career pathways statistics?
The data and dashboard have been produced to support the aims of the Unit for Future Skills (UFS). You can read more about the UFS here.
The publication aims to:
Explore how LEO can be used to understand the education pathways of employees in different industry sectors.
Demonstrate how LEO data could be used to develop a careers information tool via an interactive dashboard.
The interactive dashboard is a first attempt to present LEO data as a tool to aid careers advice. It is designed to showcase the potential of LEO data rather than function as a service for users.
The statistics in the publication are produced using the Longitudinal Education Outcomes (LEO) dataset. The LEO study has been brought together by different government departments and is being used to improve the information available on a range of topics across different policy areas.
The LEO dataset links information about individuals, including:
Personal characteristics such as gender, ethnic group and age.
Education, including schools, colleges and higher education institution attended, courses taken, and qualifications achieved.
Employment and income.
It is created by combining data from the following sources:
The National Pupil Database (NPD) held by the Department for Education (DfE).
Higher Education Statistics Agency (HESA) data on students at UK publicly funded higher education institutions and some Alternative Providers held by DfE.
Individualised Learner Record Data (ILR) on students at further education institutions held by DfE.
Employment data (P45 and P14) held by Her Majesty’s Revenue and Customs (HMRC).
The National Benefit Database, Labour Market System and JUVOS data held by the Department for Work and Pensions (DWP).
Inter-Departmental Business Register (IDBR).
The privacy statement explaining how personal data in this project is shared and used is published here.
Inter-Departmental Business Register
This publication uses the recent link between LEO and the IDBR to look at the industry sector of employment for employees in England.
The Office for National Statistics Inter-departmental Business Register (ONS IDBR): the comprehensive list of UK businesses that is used by Government for statistical purposes and provides the main sampling frame for surveys of businesses carried out by the Office for National Statistics and other Government departments. It is also a key data source for analyses of business activity. The IDBR covers around 2.7 million businesses in all sectors of the UK economy, other than some very small businesses (those without employees, and with turnover below the relevant tax threshold) and some non-profit making organisations. More information on the IDBR is available here.
Standard Industrial Classification
Using the ONS Standard Industrial Classification (SIC) of economic activities, there are over 700 detailed industry codes at the five digit level, which are then grouped hierarchically at the four, three and two digit level before being grouped into 21 broad industry sections. See the data processing section for more information about the SIC grouping used in this publication.
This publication covers employment in England across the 2018-19 tax year. It focuses on young adults and includes details of their education achievements spanning GCSEs and post-16 learning.
The analysis is based on individuals in LEO who turned aged 25-30 in the 2018-19 tax year and schooled in England with education records in the National Pupil Database, who also meet the following criteria:
In sustained PAYE employment.
Not studying in a Higher Education institution in the 2018/19 academic year.
In work that has been matched to a Standard Industrial Classification (SIC) code via the IDBR.
Table 1: impact of the cohort selection criteria
% of starting cohort
LEO starting cohort
+ Sustained employment
+ Not in higher education
+ Matched to a SIC code
There are important difference between the cohort used for this analysis and the wider population employees in England:
The cohort is not representative for employees of all ages. It is focused on young adults born between September 1988 and August 1993.
The cohort is restricted to employees who were schooled England. This means employees who went to school elsewhere in the UK or who came to the UK as migrants are not covered.
The administrative data matching used to generate LEO and the definition of sustained employment will result in some employees being excluded from the cohort.
A complete breakdown of employees by industry sector is published by the Office for National Statistics here.
Figures on subject area and highest level of education are based on the full set of qualification achievements available in LEO, from GCSE attainment through to qualifications achieved in post-16 education and higher education. LEO is a complete record of government funded qualifications achieved in school and in post-16 education.
The figures on top qualifications in each sector are restricted to employees' highest qualifications and exclude:
Qualifications at below level 2.
Qualifications achieved prior to post-16 education (e.g. GCSEs and other qualifications achieved at younger ages).
These additional restrictions ensure a focus on post-16 education when drawing associations between sector and employee qualification achievement.
The qualification pathways analysis includes all qualifications achieved by employees, not just the highest qualification. The same restrictions apply as above, but we also exclude:
Short qualifications that are taken alongside A Levels or more substantial level 2 or level 3 study (e.g. some small awards and certificates).
This ensures the modelled qualification pathways reflect substantial progression through levels of education.
Earnings estimates are based on information recorded through the Pay As You Earn (PAYE) system used to collect Income Tax and National Insurance from employment by Her Majesty’s Revenue and Customs (HMRC).
Limitations of earnings data
The median earnings in this release are presented as raw figures. They do not seek to control for differences in employee characteristics.
The earnings estimates do not include any income that was recorded though the self-assessment tax system. This means that earnings will be underreported for employees who have self-assessment income in addition to earnings from paid employment collected by the PAYE system. Employees who recorded their income entirely through the self-assessment tax system are not included in the estimates.
The PAYE records from HMRC do not include reliable information on the hours worked in employment so it is not possible to accurately distinguish between employees in full time and part time employment.
Differences in earnings could be a result of factors other than the education, sector and region of employees, such as:
The number of employees in part time employment.
The employment history of employees.
Pay conditions within the local labour market.
Any additional income recorded through the self-assessment tax system.
Employees who are not in sustained employment are excluded from these statistics.
The definition of sustained employment is consistent with the definition used for 16-19 accountability and in the further education outcome based success measures publication. This looks at employment activity in the six month October to March period. For 2018-19 tax year employees to be counted as in sustained employment:
An employee must be in paid PAYE employment in five out of the six months between October 2018 and March 2019.
An employee needs to be in paid PAYE employment for at least one day in a month for that month to be counted.
If an employee is employed in the five months between October 2018 and February 2019, but not in March 2019, then they must also be employed in April 2019.
This report presents the median annualised earnings of employees. The median is calculated by ranking all employees' annualised earnings and taking the value at which half of employees fall above and half fall below.
Annualised earnings are calculated for employees that started or left employment part way through the tax year by adjusting their recorded earnings to the equivalent earnings had they been employed for the entire tax year. The PAYE records from HMRC do not include reliable information on the hours worked in employment so it is not possible to distinguish between employees in full time and part time employment. Part time earnings are not adjusted to the full-time equivalent amount.
Median earnings will be lower for groups of employees with high levels of part time employment. This is the case for sectors such as accommodation and food, retail and education, where many employment opportunities are part time.
Standard industrial classification
This publication includes two aggregations of SIC codes: sector and sub-sector. Sector is an adjustment of the ONS 21 industry sections. The adjustment is based on the approach used in Working Futures and allows a direct link to forecasts of employment published there. Sub-sector is a custom grouping of SIC 2 to 5 digit codes designed to add extra layers of detail to some of the broader sectors.
Where an employee worked in multiple industries across the 2018-19 tax year, SIC code associated with the highest earning employment is assigned.
Table 2: SIC code mapping for sector and sub-sector
Crop and animal production
Fishing and aquaculture
Forestry and logging
Mining & quarrying
Extraction of petroleum and gas
Mining of coal and lignite
Mining of metal ores
Mining support service activities
Other mining and quarrying
Food drink & tobacco
Food, beverages and tobacco
Machinery and electrical equipment
Machinery and electrical equipment
Paper and paper products
Textiles and leather
Electricity & gas
Air conditioning supply
Water & sewerage
Other waste management
Waste collection and treatment
Water treatment and supply
Building completion and finishing
Construction of buildings
Demolition and site preparation
Electrical, plumbing and installation
Other construction activities
Whole. & retail trade
Retail, except of motor vehicles
Trade and repair of motor vehicles
Wholesale, except of motor vehicles
Transport & storage
Postal and courier activities
Warehousing for transportation
Accommodation. & food
Food and beverage services
Restaurants, mobile food service
Information service activities
Programming and broadcasting
Video, TV production, sound recording
Computer programming and consultancy
Finance & insurance
Financial service activities
Insurance and pension funding
Real estate activities
Accounting, auditing, tax consultancy
Advertising and market research
Architectural and engineering services
Other professional activities
Scientific research and development
Employment placement agencies
Office administrative and support
Rental and leasing
Security and investigation
Services to buildings and landscape
Travel agency, tour operators
Public admin. & defence
Public administration and defence
Health & social work
Medical and dental practice
Other human health activities
Residential care activities
Social work activities
Arts & entertainment
Creative, arts and entertainment
Gambling and betting
Libraries, archives, museums
Sports activities and recreation
Region is based on the the home address of the employee as recorded in LEO for the 2018-19 tax year. This reflects the address that The Department for Work and Pensions (DWP) has recorded for each individual on their Customer Information System (CIS). The CIS is primarily updated when an individual notifies DWP or HMRC of a change of address or through the individual interacting with a tax or benefit system.
Employees will have achieve a range of qualifications across over the course of their education. This analysis identifies the highest qualification achievement of employees at the start of the 2018-19 tax year. This qualification is used to summarise the education pathway of employees. Level of education, subject and qualification title groupings are based on the the highest qualification. The hierarchy used to select between qualifications is below:
Most recently achieved qualification (if achieving more than one at the same level).
If the same record appears in the ILR and HESA collections, the HESA record is selected over the ILR record.
The hierarchy used to determine highest qualification is:
Other level 8
Other level 7
Higher apprenticeship level 6
Other level 6
Higher apprenticeship level 5
Other level 5
Higher apprenticeship level 4
Other level 4
Full Level 3 (including academic qualifications, e.g. A-Levels)
Other Level 3
Full Level 2 (including academic qualifications, e.g. GCSEs)
Level 2 English and Maths
Other Level 2
Entry or Level 1 English and Maths
Other Entry or Level 1
Defining subject area
The subject area of qualifications has been categorised using the sector subject area tier 1 classification system, which is owned by OFQUAL.
Qualifications reported in the HESA data collection do not use the SSA categorisation. HESA subjects are recorded using Joint Academic Coding System (JACs). We have mapped HESA records to SSA tier 1 using the mapping in table 3
Qualifications contained in the ILR and NPD data collections are recorded using the SSA classification system.
The mapping between JACS and SSA is published as an ancillary file to the main statistics release.
Qualification titles are derived differently depending on the data source.
For post-16 education in schools and colleges, we use the Learning Aim Reference Service (LARS) database to source titles for qualifications. We have applied extra cleaning to group titles together where there are small differences in naming conventions.
For qualifications achieved in higher education institutions, the title is a combination of the type of qualification and the JACs principle subject area description. This means that titles for HE qualifications may not match similar qualifications in the LARS database, and may be different to those used in other publications.
The interactive dashboard provides a summary of common qualification pathways followed by top earning employees of each industry sector and in each region. This analysis is designed to show potential qualification pathways that could lead to employment in an industry sector of interest.
The pathways analysis is based on modelled achievements data for each employee. The following sections explain this process in detail.
Qualification pathways are constructed from regulated qualifications achieved by employees in post-16 education at level 2 and above. Basic skills qualifications, unregulated provision and qualifications achieved at school, such as GCSEs, are excluded. We also exclude AS Levels and smaller qualifications that are taken alongside A Levels or larger level 2 and 3 qualifications.
The process involves pairing qualifications from the achievements of each employee. Qualification pairs are created where:
The employee holds more than one qualification.
The starting qualification is a lower level than the subsequent qualification.
The subsequent qualification is achieved after the starting qualification.
Pairs of qualifications must include one of the following criteria for progression between levels of education:
Level 2 to level 3.
Level 3 to level 4/5.
Level 3 to level 6 (where the employee does not have a level 4/5).
Level 3 to level 7+ (where the employee does not have a level 4/5 or a level 6).
Level 4/5 to either level 6.
Level 4/5 to level 7+ (where the employee does not have a level 6).
Level 6 to level 7+.
Once constructed, these pairs are then aggregated across all employees in each region and sector to show the most common qualification pathways to higher levels of education. This dataset of qualification pairs is published as part of the underlying data included in this release.
Interactive qualification pathways
The interactive dashboard builds on the qualification pairs data to produce pathways showing progression between more than two qualifications, from level 2 or 3 up to level 7+. These pathways are modelled; the data do not show the same cohort of employees moving through the entire pathway.
Each qualification pair is based on the numbers of students who move between them. The analysis then takes the end qualification of a pair as the starting qualification of a new pair. The combining of qualification pairs in this way builds the full collapsible tree chart in the dashboard.
There are too many qualification pairs to visualise in a single chart. The collapsible tree chart shows pathways based on the most common qualifications held by employees in the top third of earners in each sector and region group.
This is achieved by taking qualifications that meet the following criteria, which are applied for each region, sector and starting level selection:
The first qualification in the pair is in the top ten qualifications by number of employees.
The first qualification in the pair is in one of the top 5 subject areas by number of employees.
The first qualification in the pair is held by at least 30 employees.
At least 3 employees progressed and achieved the second qualification of the pair.
At least 2% employees who hold the first qualification of the pair progressed to achieve the second qualification.
Employee numbers are rounded to the nearest 10, annual median earnings are rounded to the nearest 100 and percentages are provided to the nearest one decimal place. Figures have been suppressed with the value ‘u’ for annual earnings based on fewer than 10 employees and ‘c’ for percentages where the numerator is less than 3 or the denominator is less than 6. Employee numbers below 5 are replaced with ‘low.’