Economic inactivity by qualification level

Published

1. Main facts and figures

  • in 2018, 19% of 16 to 64 year olds were economically inactive, which broadly means they were out of work and not looking for work
  • in every ethnic group, people with a degree (or other level 4 qualification or above) were less likely to be economically inactive than people with lower level qualifications
  • among people qualified up to level 3 (at least 2 A levels), those from the White ethnic group were the least likely out of all ethnic groups to be economically inactive
  • in every ethnic group, women had higher rates of economic inactivity than men
  • among women, those from the Asian ethnic group had the highest rates of economic inactivity
Things you need to know

The data for this analysis comes from the Annual Population Survey (APS). The APS surveys a random sample of the population to make generalisations about the whole population.

The commentary for this data includes only reliable findings. Findings are reliable ('statistically significant’) when we can be confident they are reflective of the total population. This means we would get similar findings 19 times out of 20 if we carried out the same survey on different random samples of the population.

As with all surveys, the estimates from the APS are subject to a degree of uncertainty as they are based on a sample of the population.

Ethnic minority groups tend to have a smaller number of survey respondents. As a result, their estimates are less reliable than those for White people.

Results taken from a low number of responses are more likely to change from year to year. What appear to be changes over time might not reflect real differences. Please use caution when interpreting short-term trends in the data, especially for small groups.

Values based on fewer than 30 responses have been withheld from results for 'All' groups. Values based on fewer than 100 responses have been withheld from results for specific ethnic groups. This is both:

  • to protect respondents’ confidentiality
  • because the numbers involved are too small to draw any reliable conclusions

This data gives detailed breakdowns such as information by local authority area. Higher-level figures may differ from those published by the Department for Work and Pensions and the Office for National Statistics that use the Labour Force Survey (LFS).

The ethnic groupings used here are broad. There is no breakdown of data for the more specific ethnic groups, whose experiences might be very different to one another. For example, the Black ethnic group could include both:

  • recent migrants from Somalia
  • Black people born in Britain to British parents
What the data measures

This data measures the percentage of people aged 16 to 64 years who are economically inactive and not in full-time education.

This is broken down by their highest level of qualification and ethnicity.

A person of working age is counted as economically inactive if:

  • they are out of work
  • they have not been actively looking for work in the past 4 weeks
  • they are not waiting to start a job

People who are caring for their family or retired are also counted as economically inactive.

Qualification level refers to someone's highest qualification, from the following:

  • level 4 or higher: degree level or equivalent (including HND, Bachelor degree and Master degree)
  • level 3: two or more A levels or equivalent (including advanced GNVQ, NVQ 3 or higher, and Scottish higher or advanced higher)
  • level 2: five or more GCSE passes at grades A* to C (or 9 to 4) or equivalent (including intermediate GNVQ, NVQ 2, and Scottish intermediate 2)
  • below level 2: fewer than 5 GCSE passes at grades A* to C (or 9-4) or equivalent (including foundation GNVQ, NVQ 1, and Scottish intermediate 1)
  • no qualifications

Trade apprenticeships are treated as being 50% NVQ level 2 and 50% NVQ level 3. This is in line with Office for National Statistics guidelines.

In the charts and tables, ‘other qualifications’ include:

  • qualifications from outside the UK
  • some professional qualifications where the level is not clear
The ethnic categories used in this data

For this data, the number of people surveyed was too small to draw any reliable conclusions about specific ethnic categories. Therefore, the data is broken down into the following 5 broad ethnic groups used in the 2011 Census:

  • Asian or Asian British
  • Black or Black British
  • Mixed
  • White (including White ethnic minorities)
  • Other

The data in the download file is also broken down by 2 ethnic groups:

  • White – White ethnic groups (including White British and White ethnic minorities)
  • Other – all other ethnic minorities

2. By ethnicity and qualification level

Percentage of people aged 16 to 64 years who were economically inactive and not in full-time education, by ethnicity and qualification level
Highest qualification held All Asian Black Mixed White Other
All 19% 25% 21% 23% 18% 27%
Level 4 and above 11% 13% 11% 11% 11% 17%
Level 3 15% 22% 19% 21% 14% 29%
Level 2 22% 34% 30% 35% 21% 32%
Below Level 2 25% 36% 30% 34% 24% 37%
Other qualifications 21% 30% 22% withheld because a small sample size makes it unreliable 18% 29%
No qualifications 48% 56% 45% 57% 47% 52%

Download table data for ‘By ethnicity and qualification level’ (CSV) Source data for ‘By ethnicity and qualification level’ (CSV)

Summary

This data shows that:

  • in 2018, 19% of 16 to 64 year olds were economically inactive, which broadly means they were out of work and not looking for work
  • among people qualified up to level 3 (at least 2 A levels) and people with other qualifications, those from the White ethnic group were the least likely out of all ethnic groups to be economically inactive
  • among people with a degree (or other level 4 qualification or above), those from the White, Mixed and Black ethnic groups were the least likely to be economically active
  • 17% of 16 to 64 year olds from the Other ethnic group with a degree (or other level 4 qualification or above) were economically inactive, the highest rate out of all ethnic groups
  • in every ethnic group, a lower percentage of people with a degree (or other level 4 qualification or above) were economically inactive compared with those with lower level qualifications
  • among people with no qualifications, those with Mixed ethnicity had the highest rate of economic inactivity (at 57%), and Black people had the lowest (at 45%)
  • although the table and chart show other differences, some of the results are based on small numbers of people so caution should be taken when making generalisations

3. By ethnicity and qualification level (men only)

Percentage of men aged 16 to 64 years who were economically inactive and not in full-time education, by ethnicity and qualification level
Highest qualification held All Asian Black Mixed White Other
All 13% 12% 15% 17% 13% 16%
Level 4 and above 8% 5% 7% 8% 8% 9%
Level 3 10% 8% 16% 15% 10% withheld because a small sample size makes it unreliable
Level 2 16% 22% 24% 27% 15% withheld because a small sample size makes it unreliable
Below Level 2 17% 19% 19% withheld because a small sample size makes it unreliable 17% withheld because a small sample size makes it unreliable
Other qualifications 12% 12% 12% withheld because a small sample size makes it unreliable 12% 12%
No qualifications 38% 32% 32% withheld because a small sample size makes it unreliable 39% 38%

Download table data for ‘By ethnicity and qualification level (men only)’ (CSV) Source data for ‘By ethnicity and qualification level (men only)’ (CSV)

Summary

This data shows that:

  • in 2018, 13% of men aged 16 to 64 were economically inactive, which broadly means they were out of work and not looking for work
  • among men with a degree (or other level 4 qualification or above), those from the Asian ethnic group had the lowest economic inactivity rate out of all ethnic groups (at 5%)
  • among men with no qualifications, those from the White ethnic group were the most likely out of all ethnic groups to be economically inactive (at 39%), while Black and Asian men were least likely to be (both at 32%)
  • although the table and chart show other differences, some of the results are based on small numbers of people so caution should be taken when making generalisations

4. By ethnicity and qualification level (women only)

Percentage of women aged 16 to 64 years who were economically inactive and not in full-time education, by ethnicity and qualification level
Highest qualification held All Asian Black Mixed White Other
All 24% 38% 26% 28% 22% 36%
Level 4 and above 14% 21% 14% 14% 14% 24%
Level 3 19% 35% 22% 29% 18% 42%
Level 2 27% 45% 37% 43% 26% 39%
Below Level 2 33% 52% 39% withheld because a small sample size makes it unreliable 32% withheld because a small sample size makes it unreliable
Other qualifications 32% 50% 35% withheld because a small sample size makes it unreliable 27% 47%
No qualifications 59% 79% 56% withheld because a small sample size makes it unreliable 56% 65%

Download table data for ‘By ethnicity and qualification level (women only)’ (CSV) Source data for ‘By ethnicity and qualification level (women only)’ (CSV)

Summary

This data shows that:

  • in 2018, 24% of women aged 16 to 64 were economically inactive, which broadly means they were out of work and not looking for work
  • at every qualification level, White women were the least likely out of all ethnic groups to be economically inactive (jointly with other ethnic groups in for those with level 4 qualifications and no qualifications)
  • among women with a degree (or another level 4 qualification or above), those from the Other (24%) and Asian (21%) ethnic groups were the most likely to be economically inactive
  • among women with no qualifications, Asian women were the most likely to be economically inactive (at 79%), and Black and White women were the least likely to be economically inactive (both at 56%)
  • although the table and chart show other differences, some of the results are based on small numbers of people so caution should be taken when making generalisations

5. Methodology

The Annual Population Survey is a continuous household survey. Most people are interviewed in person first, and later by telephone.

The sample is formed from:

  • waves 1 and 5 of the Labour Force Survey (in which selected addresses are contacted every 3 months)
  • boost cases that are in the sample for 4 waves, spread one year apart

Participants are randomly selected from the Royal Mail postcode address file. The NHS communal accommodation list is also used and (in the case of remote parts of Scotland) telephone directories. All eligible individuals found at the selected address may be interviewed.

People are included in the dataset for this analysis if they respond themselves or if a family member responds on their behalf. The complex survey design has been taken into account when calculating confidence intervals.

Weighting:

The sample of approximately 275,000 people undergoes weighting at local authority level, using age and sex dimensions.

Weighting adjusts the results of a survey to make them representative of the population and make them more reliable.

For example, a survey of 25 women and 75 men will not accurately reflect the views of the general population, which is around 50% male and 50% female.

The weighting for this data is based on Office for National Statistics population statistics.

Confidence intervals:

Confidence intervals for each ethnic group are available if you download the data.

The APS is based on a sample of 16 to 64 year olds, rather than all 16 to 64 year olds in England, Wales and Scotland.

This page includes only reliable estimates ('statistically significant’) of the percentage of 16 to 64 year olds who were economically inactive. However, it’s impossible to be 100% certain of the true percentage.

For example, based on the APS results, it’s estimated that 34% of White 16 to 64 year olds who had no educational qualifications were economically inactive in 2018.

It is 95% certain that between 28.1% and 39.2% of White 16 to 64 year olds with no educational qualifications were economically inactive in 2018. In statistical terms, this is a 95% confidence interval. This means that if 100 random samples were taken, then 95 times out of 100, the estimate would fall in this range. But 5 times out of 100 it would fall outside this range.

The smaller the survey sample, the more uncertain the estimate and the wider the confidence interval. For example, fewer Asian 16 to 64 year olds responded to the survey, so we can be less certain about the estimate for the smaller group.

Statistically significant findings have been determined where the 95% confidence intervals of an ethnic group do not overlap with the confidence interval for the group they're being compared with.

Suppression rules and disclosure control

In data covering all ethnic groups together, estimates based on sample sizes of less than 30 have been suppressed. For data broken down by ethnic groups, estimates based on sample sizes under 100 have been suppressed.

‘Suppression’ means these figures have not been included in the data, to protect confidentiality and because the numbers involved are too small to draw any reliable conclusions.

Breaking the figures down by gender reduces sample sizes further and makes the figures less reliable.

Data has been suppressed at some qualification levels for the Mixed and Other groups because of the very small numbers.

Rounding

Estimates in the charts and tables are rounded to whole percentages. Estimates in the download file are rounded to 1 decimal place.

Quality and methodology information

6. Data sources

Source

Type of data

Survey data

Type of statistic

National Statistics

Publisher

Office for National Statistics

Publication frequency

Yearly

Purpose of data source

The main purpose of the Annual Population Survey (APS) is to provide good quality estimates about the UK workforce. It’s the largest household study in the UK in terms of how many people it’s sent to and how in depth the questions are. It provides the official measures of employment and unemployment.

The survey measures all elements of people's work, including:

  • the education and training needed to equip them for work
  • features of their jobs
  • unemployment and job seeking
  • income from work and benefits

7. Download the data