Economic inactivity by qualification level
Last updated 4 March 2018 - see all updates
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- 1. Navigate to Main facts and figures section
- 2. Navigate toEconomic inactivity by ethnicity and qualification level section
- 3. Navigate toEconomically inactive men by ethnicity and qualification level section
- 4. Navigate toEconomically inactive women by ethnicity and qualification level section
- 5. Navigate to Methodology section
- 6. Navigate to Data sources section
- 7. Navigate to Download the data section
1. Main facts and figures
in 2016, at most qualification levels, White people were less likely to be economically inactive compared with 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
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:
- White (including White ethnic minorities)
2. Economic inactivity by ethnicity and qualification level
|Level 4 and above||11||14||10||9||11||19|
|Below Level 2||26||33||30||35||25||44|
|Other qualifications||21||31||27||withheld because a small sample size makes it unreliable||18||27|
Summary of Economic inactivity by qualification level Economic inactivity by ethnicity and qualification level Summary
3. Economically inactive men by ethnicity and qualification level
|Level 4 and above||7%||5%||5%||7%||8%||9%|
|Below level 2||16%||13%||21%||withheld because a small sample size makes it unreliable||16%||withheld because a small sample size makes it unreliable|
|Other qualifications||13%||11%||16%||withheld because a small sample size makes it unreliable||13%||17%|
|No qualifications||40%||35%||53%||withheld because a small sample size makes it unreliable||40%||34%|
Summary of Economic inactivity by qualification level Economically inactive men by ethnicity and qualification level Summary
4. Economically inactive women by ethnicity and qualification level
|Highest qualification held||All||Asian||Black||Mixed||White||Other|
|Level 4 and above||15%||24%||13%||10%||14%||28%|
|Below level 2||35%||53%||39%||withheld because a small sample size makes it unreliable||34%||55%|
|Other qualifications||32%||54%||39%||withheld because a small sample size makes it unreliable||26%||39%|
|No qualifications||61%||78%||49%||withheld because a small sample size makes it unreliable||59%||70%|
Summary of Economic inactivity by qualification level Economically inactive women by ethnicity and qualification level Summary
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.
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 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 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 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 48.7% and 50.4% 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 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 England, Wales and Scotland.
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.
Estimates in the charts and tables are rounded to whole percentages. Estimates in the download file are rounded to 1 decimal place.
6. Data sources
Type of data
Type of statistic
Office for National Statistics
Purpose of data source
The Annual Population Survey (APS) is the largest household survey in the UK and covers topics, including:
- personal characteristics
- labour market status
- work characteristics
The purpose of the APS is to provide information on social and socio-economic variables at local levels, such as labour market estimates.
The published statistics also allow the government to monitor estimates between Censuses.