- 1. Main facts and figures
- 2. By ethnicity
- 3. By ethnicity (2 ethnic groups)
- 4. By ethnicity over time
- 5. By ethnicity and gender
- 6. By ethnicity and age group
- 7. By ethnicity and age group over time (16 to 24 year olds only)
- 8. By ethnicity and area
- 9. Methodology
- 10. Data sources
- 11. Download the data
1. Main facts and figures
- in 2017, the total working age population (people aged 16 to 64 years) in England, Wales and Scotland was just under 40 million – of those, just over 34 million people were White, and nearly 6 million people were from all other ethnic groups combined
- the main definition of economic inactivity is if a person is out of work and not looking for a job – in 2017, there were 8.6 million economically inactive people in England, with 6.9 million coming from White ethnic groups, and 1.7 million from all other ethnic groups combined
- the economic inactivity rate in 2017 was 20% for White people and 30% for people from all other ethnic groups combined, a difference of 9 percentage points – the economic inactivity rate is the number of economically inactive people as a percentage of the total working age population
- in 2017, 56% of Pakistani/Bangladeshi women were economically inactive, compared with 23% of Pakistani/Bangladeshi Men (a gap of 33 percentage points), and 25% of White British women (a gap of 31 percentage points)
The ethnic categories used in this data
Data is shown for the following ethnic groups:
- Pakistani or Bangladeshi
- Any other Asian ethnicity (including Chinese)
- White British
- White other
Any other ethnic group
Where data is broken down by gender, age group, and area, the number of people surveyed (the ‘sample size’) was too small to draw any firm conclusions about specific ethnic categories, so data is shown for the following 2 categories:
- White – White ethnic groups (including White British and White ethnic minorities)
- Other – all other ethnic minorities
People whose ethnicity is 'Unknown' (because their ethnicity was not recorded or they chose not to state their ethnicity) are counted when calculating the total number of people in employment (shown as the ‘All’ group in the data).
2. By ethnicity
|Ethnicity||%||Total economically inactive|
|Pakistani and Bangladeshi||39||474,000|
|Asian other inc Chinese||32||262,000|
3. By ethnicity (2 ethnic groups)
|Ethnicity||%||Total economically inactive|
|Other than White||30||1,732,000|
4. By ethnicity over time
|Pakistani and Bangladeshi||49||49||48||48||46||44||44||N/A*||42||41||40||40||39||39|
|Asian other inc Chinese||36||36||34||33||31||32||36||N/A*||34||36||33||32||34||32|
5. By ethnicity and gender
|Ethnicity||%||Total economically inactive||%||Total economically inactive||%||Total economically inactive|
|Pakistani and Bangladeshi||39||474,000||23||141,000||56||333,000|
|Asian other inc Chinese||32||262,000||24||89,000||39||173,000|
6. By ethnicity and age group
|Ethnicity||%||Total economically inactive||%||Total economically inactive||%||Total economically inactive||%||Total economically inactive|
|Pakistani and Bangladeshi||57||169,000||32||242,000||43||63,000||39||474,000|
|Asian other inc Chinese||65||116,000||22||106,000||27||39,000||32||262,000|
|Mixed||45||83,000||15||42,000||withheld because a small sample size makes it unreliable||withheld because a small sample size makes it unreliable||27||147,000|
7. By ethnicity and age group over time (16 to 24 year olds only)
|Pakistani and Bangladeshi||56||55||52||56||52||54||56||N/A*||56||52||55||53||56||57|
|Asian other inc Chinese||57||60||60||62||59||65||70||N/A*||68||69||69||67||68||65|
8. By ethnicity and area
|All||White||Other than White|
|region||%||Total economically active||%||Total economically active||%||Total economically active|
|East of England||19||721,000||19||628,000||24||93,000|
|Yorkshire and The Humber||23||766,000||21||620,000||37||144,000|
The Annual Population Survey (APS) 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 makeup 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.
Based on the APS, it is estimated that 20.2% of White people of working age were economically inactive in 2017.
The data from the APS is based on a sample of the population in England, Wales and Scotland, rather than the whole population. The estimate obtained from this sample is a reliable estimate of the percentage of individuals in working age that were economically inactive, but it’s impossible to be 100% certain of the true percentage for the whole population of working age.
It’s 95% certain, however, that somewhere between 19.5% (lower bound of the confidence interval) and 20.9% (upper bound of the confidence interval) of White individuals of working age 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 between the lower and upper bounds of the 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, the sample has less data for individuals from the Black ethnic group than from the White ethnic group, so we can be less certain about the estimate for the smaller group. This greater uncertainty is expressed by a wider confidence interval, of between 22.3% and 30.5% for the Black ethnic group compared to 19.5% and 20.9% for the White ethnic group in 2017.
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.
Percentages are rounded to whole numbers in charts and tables. Download the data to see the percentages rounded to 1 decimal place. Calculations have been made using the unrounded figures.
10. Data sources
Type of data
Type of statistic
Department for Work and Pensions
Purpose of data source
Survey data, collected to allow analysis of labour market and related topics at a more detailed level than is possible in the Labour Force Survey.
11. Download the data
This file contains the following variables: measure, year, region, ethnicity, ethnicity_type, sex, age_band, value, confidence_interval, numerator, denominator, samp_size
This file contains the following variables: measure, age_band, year, local_authority, ethnicity, ethnicity_type, value, confidence_interval, numerator, denominator, samp_size