Economic inactivity by qualification level

Published 23 January 2018

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Contents

1. Main facts and figures

• at most qualification levels, White people were less likely to be economically inactive than other ethnic groups

• for all ethnic groups, people with lower qualification levels were more likely to be economically inactive than people with higher qualification levels

• the differences in economic inactivity between White and other ethnic groups were larger for women than for men

Things you need to know

The economic inactivity figures are estimates based on the Annual Population Survey (APS).

The APS is a ‘sample survey’. It collects information from a random sample of the population to make generalisations (reach ‘findings’) about the total population.

Unless stated otherwise, 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.

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 16 to 64 year olds who are economically inactive and not in full-time education. This is broken down by the highest level of qualification and ethnicity.

Someone is ‘economically inactive’ if they:

• are currently jobless
• have not actively sought work in the past 4 weeks and/or are not available to start work in the next 2 weeks

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: 2 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: 5 or more GCSEs at grades A to C; intermediate GNVQ; NVQ 2; intermediate 2 national qualification (Scotland), or equivalent
• below level 2: fewer than 5 GCSEs at grades A to C; foundation GNVQ; NVQ 1; intermediate 1 national qualification (Scotland), or equivalent
• no qualifications: no formal qualifications held

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 (including White ethnic minorities)
• Other

2. Economic inactivity by ethnicity and qualification level

• Location: England, Wales and Scotland
• Time period: 2016
• Source: Annual Population Survey

Percentage of 16 to 64 year olds who were economically inactive and not in full-time education, by ethnicity and qualification level

Highest qualification	All	Asian	Black	Mixed	White	Other
All	19	26	20	21	18	27
Level 4 and above	11	14	10	9	11	19
Level 3	15	26	18	17	14	25
Level 2	21	29	24	28	21	32
Below Level 2	26	33	30	35	25	44
Other qualifications	21	31	27		18	27
No qualifications	51	58	51	57	50	52

Data withheld because a small sample size makes it unreliable

Download table data (CSV) Source data (CSV)

Summary of Economic inactivity by qualification level Economic inactivity by ethnicity and qualification level Summary

This data shows that:

• in 2016, at every qualification level except 4 or above, a smaller percentage of White people were economically inactive compared to other ethnic groups

• among people with level 4 qualifications or above, a similar percentage of the Asian, Black, Mixed and White ethnic groups were economically inactive, at 14%, 10%, 9% and 11% respectively

• for all ethnic groups, a smaller percentage of people with level 4 qualifications or above were inactive compared with those with lower-level qualifications

• the largest difference between ethnic groups was found among those with below level 2 qualifications: 25% of White people with these qualifications were inactive, compared with 44% for people from the Other ethnic group

• among those with no qualifications, people from the White, Black and Other ethnic groups had a similar percentage of economically inactive people, at 50%, 51% and 52% respectively

3. Economically inactive men by ethnicity and qualification level

• Location: England, Wales and Scotland
• Time period: 2016
• Source: Annual Population Survey

Percentage of 16 to 64 year old men who were economically inactive and not in full-time education, by ethnicity and qualification level

Highest qualification	All	Asian	Black	Mixed	White	Other
All	13%	12%	14%	16%	13%	16%
Level 4 and above	7%	5%	5%	7%	8%	9%
Level 3	11%	15%	9%	8%	11%	16%
Level 2	15%	16%	16%	17%	15%	23%
Below level 2	16%	13%	21%		16%
Other qualifications	13%	11%	16%		13%	17%
No qualifications	40%	35%	53%		40%	34%

Data withheld because a small sample size makes it unreliable

Download table data (CSV) Source data (CSV)

Summary of Economic inactivity by qualification level Economically inactive men by ethnicity and qualification level Summary

This data shows that:

• men with level 4 qualifications or above from the White and Other groups were most likely to be economically inactive (at 8% and 9% respectively); men with the same level of qualification from the Asian group were least likely to be economically inactive (at 5%)

• overall, 40% of men with no qualifications were economically inactive: Asian men were less likely to be economically inactive (at 35%) and Black men more likely (at 53%)

• although the chart shows differences in economic inactivity between other ethnic groups at these and other qualification levels, small sample sizes mean we can’t draw firm conclusions about these results

4. Economically inactive women by ethnicity and qualification level

• Location: England, Wales and Scotland
• Time period: 2016
• Source: Annual Population Survey

Percentage of 16 to 64 year old women 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	25%	41%	24%	26%	24%	38%
Level 4 and above	15%	24%	13%	10%	14%	28%
Level 3	19%	36%	25%	25%	18%	34%
Level 2	27%	42%	29%	38%	26%	42%
Below level 2	35%	53%	39%		34%	55%
Other qualifications	32%	54%	39%		26%	39%
No qualifications	61%	78%	49%		59%	70%

Data withheld because a small sample size makes it unreliable

Download table data (CSV) Source data (CSV)

Summary of Economic inactivity by qualification level Economically inactive women by ethnicity and qualification level Summary

This data shows that:

• at every qualification level except 4 and above, White women were less likely to be economically inactive than women from other ethnic groups

• among women with level 4 qualifications, women from the Other ethnic group were most likely to be economically inactive, at 28%, followed by Asian women, at 24%; White, Black and Mixed ethnic women had similar levels of inactivity, at 14%, 13% and 10% respectively

• among women with no qualifications,Asian women were most likely to be economically inactive, at 78%, and Black women were least likely to be, at 49%

• although the chart shows differences in economic inactivity between other ethnic groups at these and other qualification levels, small sample sizes mean we can’t draw firm conclusions about these results

5. Methodology

The APS is a continuous household survey. Most cases are first interviewed face to face, then 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, which are in the sample for 4 waves, spread one year apart

The main source for contacting participants is the Royal Mail postcode address file. However, the NHS communal accommodation list and (in the case of remote parts of Scotland) telephone directories are also used.

All eligible individuals found at a selected address may be interviewed. This analysis only uses data based on responses from the individual concerned or a response on their behalf from a family member.

The complex survey design has been taken into account when calculating confidence intervals.

Confidence intervals

Confidence intervals for each ethnic group are available in the ‘download the data’ section.

Based on the APS results, it’s estimated that 50% of of White 16 to 64 year olds with no qualifications who are not in full-time education were economically inactive in 2016.

The APS is based on a sample of 16 to 64 year olds, rather than all 16 to 64 year olds in Great Britain. This measure makes reliable estimates of the percentage of people in this age bracket in Great Britain who were economically inactive, but it’s impossible to be 100% certain of the true percentage.

It’s 95% certain, however, that somewhere between 48.7% and 50.4% of all White 16 to 64 year olds with no educational qualifications in Great Britain who were not in full-time education were economically inactive in 2016. 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 53.9% and 62.3% for Asians aged 16 to 64 in 2016.

Statistically significant findings have been determined where the 95% confidence intervals of an ethnic group do not overlap with the value for all ethnicities in Great Britain.

Weighting

Surveys seek information about a particular group of people – we call this the target population.

Every target population will have a particular age and gender profile – for example, teachers are predominantly female and under 50. Some target populations will also have a regional profile – for example, they might be clustered in a particular part of the country.

Surveys collect information from a random sample of the target population to make generalisations (reach ‘findings’) about everyone within that population.

For those findings to be reliable, the sample of people should ideally contain the same mix of age, gender and regional location as the target population.

Where this isn’t the case (because some people haven’t responded, for example) analysts use statistical tools to ‘weight’ the data. Weighting rebalances the survey responses so they represent the target population more accurately. They can then be used to reach meaningful conclusions.

For the data presented here, the Office for National Statistics population estimates and projections are used as the basis for this weighting process.

The sample of approximately 275,000 is weighted to make it more representative of the spread of ages and the male/female mix in the whole population of 16 to 64 year olds.

Suppression rules and disclosure control

In data covering all ethnic groups combined, estimates based on sample sizes of fewer than 30 people have been suppressed.

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

For data broken down by ethnic groups, estimates based on sample sizes under 100 have been suppressed (shown by a question mark instead of data in the tables and graphs on this page).

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.

Figures have been suppressed at some qualification levels for the Mixed and Other groups because of the very small numbers. N/A

Rounding

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

Further technical information

Annual Population Survey quality and methodology information

6. Data sources

Source

Annual Population Survey

Type of data

Survey data

Type of statistic

National Statistics

Publisher

Office for National Statistics

Note on corrections or updates

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.

Publication frequency

Yearly

Purpose of data source

The Annual Population Survey (APS) is the largest ongoing household survey in the UK and covers a range of topics, including:

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

The purpose of the APS is to provide information on important social and socio-economic variables at local levels, such as labour market estimates.

The published statistics also allow the government to monitor estimates on a range of issues between censuses.

7. Download the data

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

Publication release date: 23 January 2018

full page history

1. 23 January 2018 First published

From: Office for National Statistics

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