Economic inactivity by qualification level

The main facts and figures show that:

  • overall, 12% of people aged 16 to 64 years with a level 4 qualification (like a degree) or above were economically inactive (out of work and not looking for a job) and not in full-time education in 2017; this figure increased to 14% for people with a level 3 qualification, 21% for those with a level 2 qualification, and 49% for those with no qualifications
  • White people were less likely to be economically inactive compared with the Asian ethnic group at every qualification level, and compared with the Other ethnic group at every qualification level apart from no qualifications; results for other ethnic groups are less reliable and it's not possible to draw firm conclusions about differences
  • in the White and Asian ethnic groups, people with lower qualification levels were more likely to be economically inactive than people with higher qualification levels; results for other ethnic groups are less reliable and it's not possible to draw firm conclusions about differences
  • the differences in economic inactivity between White and other ethnic groups were larger for women than for men
Things you need to know

This analysis is based on the Annual Population Survey (APS), which is a ‘sample survey’. It collects information from a random sample of the population to make generalisations (reach 'findings') about the total population.

The commentary for this data includes only reliable, or ‘statistically significant’, findings. Findings are statistically significant when we can be confident that they can be repeated, and are reflective of the total population rather than just the survey sample.

Specifically, the statistical tests used mean we can be confident that if we carried out the same survey on different random samples of the population, 19 times out of 20 we would get similar findings.

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. The degree of uncertainty is greater when the number of respondents is small, so it will be highest for ethnic minority groups.

Smaller numbers of survey respondents from ethnic minority backgrounds mean that estimates for these ethnic groups are more unreliable than estimates for White people (which includes White British and White ethnic minorities).

Results taken from a low number of responses are more likely to be affected by statistical variation, so observed changes might not reflect real differences. As such, caution is needed when interpreting short-term trends in the data, especially for sub groups (for example, a specific ethnic group, age group and gender).

When looking at data for ‘All’ groups, any values based on fewer than 30 responses have been withheld, and when further breaking down the data by ethnicity, any values based on fewer than 100 responses have been withheld. This is to protect confidentiality or because the numbers involved are too small to draw any reliable conclusions.

Data is sourced from the APS to get additional detail such as information by local authority area. Some figures may differ slightly from reports published by the Department for Work and Pensions and the Office for National Statistics that also use the Labour Force Survey (LFS).

Changes were made to the LFS (and therefore the APS) ethnicity questions in January to March 2011, to bring them more in line with Census data collection on these topics. In April to June 2011 further changes were made to the ethnicity questions to bring them in line with Scottish Census data collection. As a result, there may be some inconsistencies with estimates from earlier than 2011.

The ethnic groupings used here are broad; there is no breakdown of data for the more specific ethnic groups each contains. Some of the specific ethnic groups have very different experiences to one another. For example, the Black ethnic group could include both recent migrants from Somalia and 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 the highest qualification gained by an individual. It is broken down into 5 broad categories:

  • level 4 or higher: higher national diploma (HND); degree; higher degree-level qualifications, or equivalent
  • level 3: two or more A levels; advanced general national vocational qualification (GNVQ); national vocational qualification (NVQ) 2, 3 or higher; higher or advanced higher national qualifications (Scotland), or equivalent
  • level 2: five or more GCSEs at grades A to C/9-4; intermediate GNVQ; NVQ 2; intermediate 2 national qualification (Scotland), or equivalent
  • below level 2: fewer than 5 GCSEs at grades A to C/9-4; foundation GNVQ; NVQ 1; intermediate 1 national qualification (Scotland), or equivalent
  • 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:

  • foreign qualifications
  • some professional qualifications where the level of qualification is not clear
The ethnic categories used in this data

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

  • Asian
  • Black
  • Mixed
  • White
  • Other

Ethnic groups and how data on ethnicity is collected

Economic inactivity 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% 26% 20% 21% 18% 27%
Level 4 and above 12% 14% 10% 13% 11% 17%
Level 3 14% 21% 17% 13% 14% 27%
Level 2 21% 33% 27% 25% 20% 35%
Below Level 2 25% 37% 27% 33% 24% 41%
Other qualifications 21% 29% 29% withheld because a small sample size makes it unreliable 18% 29%
No qualifications 49% 56% 54% 53% 48% 52%

Download table data (CSV) Source data (CSV)

Summary

This data shows that:

  • overall, 12% of people aged 16 to 64 years with a level 4 qualification (such as a degree) or above were economically inactive (out of work and not looking for a job) and not in full-time education in 2017; this figure increased to 14% for people with a level 3 qualification, 21% for those with a level 2 qualification, and 49% for those with no qualifications
  • among people with level 4 qualifications or above, a smaller percentage of the White ethnic group (11%) was economically inactive than the Asian (14%) and Other (17%) ethnic groups
  • in the White and Asian ethnic groups, a smaller percentage of people with level 4 qualifications or above were economically inactive compared with those with lower-level qualifications; results for other ethnic groups are less reliable and it's not possible to draw firm conclusions about differences
  • the largest difference between ethnic groups was found among those with below level 2 qualifications – 24% of White people were economically inactive, compared with 41% of people from the Other ethnic group and 37% from the Asian group
  • among those with no qualifications, only people in the Asian group were significantly more likely than the White group to be economically inactive

Economic inactivity among men by ethnicity and qualification level

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% 13% 14% 17% 13% 16%
Level 4 and above 8% 6% 5% 9% 8% 8%
Level 3 11% 11% 10% 10% 10% 19%
Level 2 15% 23% 25% 19% 14% 32%
Below Level 2 16% 18% 20% withheld because a small sample size makes it unreliable 16% withheld because a small sample size makes it unreliable
Other qualifications 13% 13% 15% withheld because a small sample size makes it unreliable 13% 16%
No qualifications 39% 31% 45% withheld because a small sample size makes it unreliable 40% 31%

Download table data (CSV) Source data (CSV)

Summary

This data shows that:

  • overall, 8% of men aged 16 to 64 years with a level 4 qualification (such as a degree) or above were economically inactive and not in full-time education in 2017; this figure increased to 11% for men with a level 3 qualification, 15% for those with a level 2 qualification, and 39% for those with no qualifications
  • among men with level 4 qualifications, those from the Black and Asian ethnic groups were less likely to be economically inactive (at 5% and 6% respectively) than those from the White group (at 8%)
  • among men with no qualifications, those from the Asian ethnic group were less likely to be economically inactive (at 31%) than those from the White ethnic group (at 40%)
  • although the chart shows differences in economic inactivity between other ethnic groups at these and other qualification levels, sample sizes for these groups are small and any generalisations based on these results are unreliable

Economic inactivity among women by ethnicity and qualification level

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% 39% 26% 24% 23% 37%
Level 4 and above 15% 22% 14% 15% 14% 25%
Level 3 19% 30% 22% 17% 18% 35%
Level 2 26% 43% 28% 29% 25% 38%
Below Level 2 33% 53% 33% withheld because a small sample size makes it unreliable 32% withheld because a small sample size makes it unreliable
Other qualifications 31% 48% 41% withheld because a small sample size makes it unreliable 26% 44%
No qualifications 60% 78% 61% withheld because a small sample size makes it unreliable 57% 70%

Download table data (CSV) Source data (CSV)

Summary

This data shows that:

  • overall, 15% of women aged 16 to 64 years with a level 4 qualification (such as a degree) or above were economically inactive and not in full-time education in 2017; this figure increased to 19% for women with a level 3 qualification, 26% for those with a level 2 qualification, and 60% for those with no qualifications
  • at every qualification level, White women were less likely to be economically inactive than women from the Asian ethnic group
  • at almost every qualification level, White women were also less likely to be economically inactive than women from the Other ethnic group where data was available; the only exception was among those with a level 2 qualification, where both ethnic groups were similarly likely
  • although the chart shows differences in economic inactivity between other ethnic groups at these and other qualification levels, sample sizes for these groups are small and any generalisations based on these results are very unreliable

Methodology

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 partly from waves 1 and 5 of the Labour Force Survey (in which selected addresses are contacted every 3 months) and partly from 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 (PAF). 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. Individuals 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 achieved sample of approximately 275,000 undergoes weighting which is structured at local authority level and uses age and sex dimensions.

Weighting is used to adjust the results of a survey to make them representative of the population and improve their accuracy.

For example, a survey which contains 25% females and 75% males will not accurately reflect the views of the general population, which we know is around 50% male and 50% female.

Statisticians rebalance or ‘weight’ the survey results to more accurately represent the general population. This helps to make them more reliable.

Survey weights are usually applied to make sure the survey sample has broadly the same gender, age, ethnic and geographic make up as the general population.

The Office for National Statistics population estimates and projections are used as the basis for this weighting process.

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 measure makes reliable estimates of the percentage of people in this age bracket who were employed, but it’s impossible to be 100% certain of the true percentage.

Based on the APS results, it’s estimated that 48% of of White 16 to 64 year olds with no qualifications who are not in full-time education were economically inactive in 2017.

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 measure makes reliable estimates of the percentage of people in this age bracket in England, Wales and Scotland who were economically inactive, but it’s impossible to be 100% certain of the true percentage.

It’s 95% certain, however, that somewhere between 47.2% and 49.0% of all White 16 to 64 year olds with no educational qualifications in England, Wales and Scotland who were not in full-time education were economically inactive in 2017. 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 (that is, between the upper and lower confidence interval). 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 16 to 64 year olds from the Asian ethnic group responded to the survey than their White counterparts, so we can be less certain about the estimate for the smaller group. This greater uncertainty is expressed by a wider confidence interval, for example of between 52.0% and 60.5% for Asians aged 16 to 64 in 2017.

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 to which they are being compared.

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 and the relatively smaller overall population of those who are unemployed reduces sample sizes further and makes the figures less reliable.

Data 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

Data sources

Source

Type of data

Survey data

Type of statistic

Official statistics

Publisher

Department for Education

Publication frequency

Yearly

Purpose of data source

The Annual Population Survey (APS) is the largest ongoing household survey in the UK. It is based on interviews with members of randomly selected households.

The APS covers a range of topics, including:

  • personal characteristics
  • labour market status
  • work characteristics
  • education
  • health

The APS provides information on important social and socio-economic variables at local levels, such as labour market estimates.

The data also allows government to monitor estimates on a range of issues between censuses.

The survey data presented here has been collected to allow analysis of the labour market and related topics at a lower level than is possible in the Labour Force Survey.

Download the data

Economic inactivity by qualification level - Spreadsheet (csv) 186 KB

This file contains: ethnicity, year, highest qualification level, gender, value, denominator, numerator and sample size