Economic inactivity

Published

Last updated 11 December 2023 - see all updates

1. Main facts and figures

  • in 2022, 22% of working age people in England, Scotland and Wales were economically inactive – this means they were out of work and not looking for a job
  • 21% of white people were economically inactive, compared with 26% of people from all other ethnic groups combined
  • the combined Pakistani and Bangladeshi ethnic group had the highest rate of economic inactivity (33%), and the white ‘other’ group had the lowest (15%)
  • in every region, white people had a lower rate of economic inactivity than people from all other ethnic groups combined
  • women were more likely to be economically inactive than men in every ethnic group except for the mixed ethnic group
  • the biggest gap between men and women was in the combined Pakistani and Bangladeshi ethnic group, where 48% of women and 19% of men were economically inactive

Further research:

Recent research by the Equality Hub shows that migration and integration are factors that may affect the disparities that ethnic minorities face in the labour market. The study found generational differences in labour market outcomes within ethnic minority groups. Among certain ethnic groups, second generation ethnic minorities performed better than the first generation for the labour market outcomes of economic inactivity.

Some ethnic minority groups still face disparities in the labour market, such as a higher likelihood of being economically inactive than white British people. For Pakistani women, there is no evidence of a generational effect – first and second generation Pakistani women were more likely to be economically inactive compared to white British women, even after controlling for level of education and health in the fully adjusted regression model.

The reasons for poor labour market outcomes for certain ethnic groups are complex. According to research by the Department for Work and Pensions, some of the disparities might be due to the effects of segregation and cultural attitudes, where women are expected to stay at home and care for younger and older members of the household.

2. Things you need to know

What the data measures

The data measures the percentage of working age people (16 to 64 year olds) who were economically inactive.

A person is economically inactive if they are:

  • out of work
  • not actively looking for work
  • not waiting to start a job
  • not in full-time education
  • caring for their family
  • retired

Percentages are rounded to whole numbers. Population numbers are rounded to the nearest 100 people, but economic inactivity rates have been calculated using unrounded data.

Not included in the data

The data does not include estimates based on fewer than:

  • 30 survey respondents for data covering all ethnic groups together
  • 100 survey respondents for data by ethnicity

This is to protect people’s confidentiality and because the numbers involved are too small to make reliable generalisations.

The ethnic groups used in the data

The data uses the ethnic groups from the 2011 Census.

Data is aggregated for the black, mixed and other ethnic groups, which means estimates are shown for these groups as a whole.

Data is shown separately for white British people and all other white people (the white ‘other’ ethnic group). Separate figures are also shown for 3 different Asian ethnic groups (Indian, Pakistani and Bangladeshi combined, and Asian ‘other’).

Data by ethnicity and area is shown for 2 ethnic groups (white, and all other ethnic groups combined).

People whose ethnicity is not known are included in the figures for ‘All’.

Methodology

Read the detailed methodology document for this data.

The Annual Population Survey updated its ethnicity questions in 2011. This means estimates from before and after 2011 may not be consistent, and data for individual ethnic groups in 2011 is not available.

Local authority names and boundaries change over time. The data for local authorities in the data file does not use the most recent local authority boundaries for England, Scotland and Wales.

There are separate employment and economic inactivity figures in the ethnicity pay gap data published by the Office for National Statistics (ONS) in November 2023. The rates by ethnicity may be different to those shown on this page, because:

  • the ONS data excludes extreme values that differ from most other data points in a dataset (‘outliers’)
  • the datasets use different weighting rules

The figures on this page are based on survey data. Find out more about:

In the data file

See Download the data for:

  • estimates by region, age group and sex over time for detailed ethnic groups
  • estimates by local authority for white and all other ethnic groups combined
  • confidence intervals for each ethnic group – read about how we use confidence intervals
  • sample sizes

3. By ethnicity

Percentage and number of 16 to 64 year olds who were economically inactive, by ethnicity
Ethnicity % Number of people economically inactive
All 22 8,693,500
Asian 26 874,700
Indian 20 259,500
Pakistani, Bangladeshi 33 390,500
Asian other 24 224,800
Black 26 397,200
Mixed 26 183,500
White 21 6,967,200
White British 21 6,509,600
White other 15 457,600
Other 28 258,700
Unknown withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable

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

Summary of Economic inactivity By ethnicity Summary

The data shows that:

  • 22% of working age people in England, Scotland and Wales were economically inactive (out of work and not looking for a job) in 2022
  • 33% of people from the combined Pakistani and Bangladeshi ethnic group were economically inactive – the highest percentage out of all ethnic groups, followed by people from ‘other’ ethnic groups, 28%
  • 15% of people from the white ‘other’ ethnic group were economically inactive – the lowest percentage out of all ethnic groups

4. By ethnicity over time (white and other ethnic groups)

Percentage and number of 16 to 64 year olds who were economically inactive, by ethnicity over time (white and other ethnic groups)
All White Other ethnic groups Unknown
time All % All Number of people economically inactive White % White Number of people economically inactive Other ethnic groups % Other ethnic groups Number of people economically inactive Unknown % Unknown Number of people economically inactive
2004 24 8,823,700 23 7,593,100 35 1,220,900 28 9,600
2005 24 8,853,900 22 7,573,000 34 1,270,500 31 10,400
2006 23 8,843,900 22 7,520,100 33 1,314,300 33 9,600
2007 23 8,999,600 22 7,609,800 33 1,378,800 39 11,000
2008 23 9,017,300 22 7,570,400 33 1,437,600 35 9,300
2009 23 9,067,100 22 7,581,400 33 1,475,100 31 10,500
2010 24 9,339,000 23 7,800,000 33 1,527,800 29 11,200
2011 24 9,399,300 not collected not collected not collected not collected not collected not collected
2012 23 9,143,700 22 7,526,600 32 1,603,800 45 13,300
2013 23 8,965,000 22 7,332,400 31 1,621,900 37 10,700
2014 23 8,957,700 21 7,273,100 31 1,664,900 27 19,700
2015 22 8,824,100 21 7,131,300 31 1,673,600 34 19,200
2016 22 8,849,900 21 7,103,700 30 1,734,500 32 11,700
2017 22 8,644,300 20 6,906,300 30 1,725,300 38 12,700
2018 22 8,624,100 20 6,849,300 30 1,763,200 31 11,600
2019 21 8,468,400 20 6,699,800 29 1,759,900 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
2020 21 8,439,300 20 6,861,000 27 1,565,100 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
2021 22 8,666,400 21 7,039,100 27 1,614,900 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
2022 22 8,693,500 21 6,967,200 26 1,714,100 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable

Download table data for ‘By ethnicity over time (white and other ethnic groups)’ (CSV) Source data for ‘By ethnicity over time (white and other ethnic groups)’ (CSV)

Summary of Economic inactivity By ethnicity over time (white and other ethnic groups) Summary

The data shows that:

  • 21% of white people were economically inactive in 2022, compared with 26% of people from all other ethnic groups combined
  • from 2004 to 2022, the economic activity rate went down from 23% to 21% for white people, and from 35% to 26% for people from all other ethnic groups combined

5. By ethnicity over time

Percentage and number of 16 to 64 year olds who were economically inactive, by ethnicity over time
All Asian Indian Pakistani, Bangladeshi Asian other Black Mixed White White British White other Other Unknown
time All % All Number of people economically inactive Asian % Asian Number of people economically inactive Indian % Indian Number of people economically inactive Pakistani, Bangladeshi % Pakistani, Bangladeshi Number of people economically inactive Asian other % Asian other Number of people economically inactive Black % Black Number of people economically inactive Mixed % Mixed Number of people economically inactive White % White Number of people economically inactive White British % White British Number of people economically inactive White other % White other Number of people economically inactive Other % Other Number of people economically inactive Unknown % Unknown Number of people economically inactive
2004 24 8,823,700 37 711,700 27 212,000 49 348,600 36 151,200 31 256,300 29 78,900 23 7,593,100 22 7,150,200 25 442,900 38 174,000 28 9,600
2005 24 8,853,900 37 740,500 26 209,600 49 364,700 36 166,200 30 257,900 30 80,500 22 7,573,000 22 7,134,800 23 438,100 36 191,600 31 10,400
2006 23 8,843,900 36 747,000 25 216,000 48 370,400 34 160,500 28 264,100 27 76,900 22 7,520,100 22 7,051,100 21 469,000 36 226,400 33 9,600
2007 23 8,999,600 36 789,900 26 222,600 48 390,100 33 177,100 28 267,400 28 84,500 22 7,609,800 22 7,118,300 21 491,500 36 237,000 39 11,000
2008 23 9,017,300 35 810,600 26 237,800 46 392,600 31 180,300 28 288,400 31 100,400 22 7,570,400 22 7,080,700 21 489,600 35 238,200 35 9,300
2009 23 9,067,100 34 829,600 25 246,300 44 398,500 32 184,800 29 300,400 30 106,700 22 7,581,400 22 7,070,000 21 511,400 36 238,500 31 10,500
2010 24 9,339,000 34 878,000 24 235,500 44 417,400 36 225,000 28 306,900 28 98,100 23 7,800,000 23 7,270,500 21 529,400 35 244,900 29 11,200
2011 24 9,399,300 not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected
2012 23 9,143,700 33 928,700 23 247,300 42 436,400 34 245,000 27 314,200 29 121,500 22 7,526,600 22 7,061,200 20 465,400 35 239,400 45 13,300
2013 23 8,965,000 33 953,400 24 257,600 41 444,500 36 251,300 26 306,200 26 116,400 22 7,332,400 22 6,873,200 19 459,200 35 246,000 37 10,700
2014 23 8,957,700 32 943,200 24 267,900 40 442,500 33 232,800 27 331,200 28 126,100 21 7,273,100 22 6,797,100 19 476,000 37 264,400 27 19,700
2015 22 8,824,100 32 942,100 24 265,300 40 439,100 32 237,700 26 346,700 28 127,700 21 7,131,300 21 6,669,000 17 462,400 35 257,100 34 19,200
2016 22 8,849,900 32 995,400 23 260,800 39 459,700 34 275,000 25 336,800 28 142,400 21 7,103,700 21 6,607,900 17 495,800 34 259,800 32 11,700
2017 22 8,644,300 31 979,800 22 246,800 39 472,600 32 260,500 26 338,300 27 147,200 20 6,906,300 21 6,402,800 16 503,500 33 260,000 38 12,700
2018 22 8,624,100 30 960,700 21 233,100 38 469,900 32 257,700 27 374,800 28 152,200 20 6,849,300 21 6,383,500 15 465,700 34 275,600 31 11,600
2019 21 8,468,400 31 999,100 21 253,000 39 492,900 31 253,200 25 365,300 26 136,900 20 6,699,800 20 6,255,300 14 444,500 32 258,600 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
2020 21 8,439,300 27 836,600 19 231,900 37 393,100 26 211,700 25 357,100 25 159,000 20 6,861,000 21 6,445,000 14 416,000 30 212,400 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
2021 22 8,666,400 26 833,300 19 224,700 35 392,900 26 215,700 26 372,300 29 204,500 21 7,039,100 21 6,577,300 15 461,800 28 204,700 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
2022 22 8,693,500 26 874,700 20 259,500 33 390,500 24 224,800 26 397,200 26 183,500 21 6,967,200 21 6,509,600 15 457,600 28 258,700 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable

Download table data for ‘By ethnicity over time’ (CSV) Source data for ‘By ethnicity over time’ (CSV)

Summary of Economic inactivity By ethnicity over time Summary

The data shows that:

  • in all ethnic groups, the rate of economic inactivity was lower in 2022 than in 2004
  • the biggest decreases were in the combined Pakistani and Bangladeshi ethnic group (down from 49% to 33%) and the Asian ‘other’ ethnic group (down from 36% to 24%)
  • in every year from 2004 to 2022, the combined Pakistani and Bangladeshi ethnic group had the highest rate of economic inactivity out of all ethnic groups

6. By ethnicity and gender

Percentage and number of 16 to 64 year olds who were economically inactive, by ethnicity and gender
All Men Women
Ethnicity All % All Number of people economically inactive Men % Men Number of people economically inactive Women % Women Number of people economically inactive
All 22 8,693,500 18 3,614,300 25 5,079,200
Asian 26 874,700 17 281,600 34 593,100
Indian 20 259,500 13 87,400 27 172,000
Pakistani, Bangladeshi 33 390,500 19 113,600 48 276,800
Asian other 24 224,800 19 80,500 28 144,300
Black 26 397,200 21 134,600 29 262,600
Mixed 26 183,500 28 91,500 25 92,000
White 21 6,967,200 18 2,999,100 24 3,968,100
White British 21 6,509,600 18 2,837,800 24 3,671,800
White other 15 457,600 11 161,300 18 296,300
Other 28 258,700 22 101,500 35 157,200
Unknown withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable

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

Summary of Economic inactivity By ethnicity and gender Summary

The data shows that:

  • 25% of women and 18% of men were economically inactive in 2022
  • women were more likely to be economically inactive than men in every ethnic group except for the mixed ethnic group
  • the highest rate of economic inactivity for women was in the combined Pakistani and Bangladeshi ethnic group (48%) – the lowest rate was in the white ‘other’ group (18%)
  • the highest rate of economic inactivity among men was in the mixed ethnic group (28%) – the lowest rate was in the white ‘other’ group (11%)
  • the gap between men and women was biggest in the combined Pakistani and Bangladeshi ethnic group, where 48% of women and 19% of men were economically inactive – the gap was smallest in the mixed ethnic group, where 25% of women and 28% of men were economically inactive

7. By ethnicity and age

Percentage and number of 16 to 64 year olds who were economically inactive, by ethnicity and age
16-24 25-49 50-64 All
Ethnicity 16-24 % 16-24 Number of people economically inactive 25-49 % 25-49 Number of people economically inactive 50-64 % 50-64 Number of people economically inactive All % All Number of people economically inactive
All 40 2,645,600 12 2,556,700 27 3,491,200 22 8,693,500
Asian 54 326,400 17 387,700 27 160,500 26 874,700
Indian 52 93,700 12 107,500 25 58,300 20 259,500
Pakistani, Bangladeshi 56 145,300 24 179,500 38 65,700 33 390,500
Asian other 53 87,400 17 100,800 20 36,500 24 224,800
Black 51 171,900 17 143,900 21 81,400 26 397,200
Mixed 43 104,900 15 53,000 24 25,600 26 183,500
White 37 1,943,800 11 1,860,100 28 3,163,300 21 6,967,200
White British 36 1,797,800 11 1,671,600 28 3,040,200 21 6,509,600
White other 44 146,000 9 188,400 20 123,100 15 457,600
Other 62 96,600 18 106,300 32 55,800 28 258,700
Unknown withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable

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

Summary of Economic inactivity By ethnicity and age Summary

The data shows that:

  • 40% of all 16 to 24 year olds were economically inactive, compared with 27% of 50 to 64 year olds, and 12% of 25 to 49 year olds
  • in every ethnic group, 16 to 24 year olds had the highest rate of economic inactivity – this is partly because people in this age group were more likely to be in education
  • for 16 to 24 year olds, people from the ‘other’ ethnic group had the highest rate of economic inactivity (62%) – the lowest rate was in the white British group (36%)
  • for 25 to 49 year olds, people from the combined Pakistani and Bangladeshi ethnic group had the highest rate of economic inactivity (24%) – the lowest rate was in the white ‘other’ group (9%)
  • for 50 to 64 year olds, people from the combined Pakistani and Bangladeshi ethnic group had the highest rate of economic inactivity (38%) – the lowest rate was in the Asian ‘other’ and white ‘other’ groups (20%)

8. By ethnicity over time (16 to 24 year olds only)

Percentage and number of 16 to 24 year olds who were economically inactive, by ethnicity over time
All Asian Indian Pakistani, Bangladeshi Asian other Black Mixed White White British White other Other
Year All % All Number of people economically inactive Asian % Asian Number of people economically inactive Indian % Indian Number of people economically inactive Pakistani, Bangladeshi % Pakistani, Bangladeshi Number of people economically inactive Asian other % Asian other Number of people economically inactive Black % Black Number of people economically inactive Mixed % Mixed Number of people economically inactive White % White Number of people economically inactive White British % White British Number of people economically inactive White other % White other Number of people economically inactive Other % Other Number of people economically inactive
2004 32 2,099,700 53 252,800 46 75,400 56 118,000 57 59,300 47 83,500 39 43,500 29 1,668,500 29 1,574,400 36 94,100 55 49,000
2005 32 2,169,300 54 269,600 49 79,400 55 125,800 60 64,400 50 91,400 41 45,400 29 1,705,400 29 1,616,900 30 88,500 53 54,800
2006 33 2,223,800 51 248,900 44 70,900 52 119,000 60 59,000 48 94,300 38 41,100 30 1,769,400 30 1,671,600 27 97,800 53 65,200
2007 33 2,314,000 54 271,300 45 74,300 56 127,100 62 69,900 49 96,700 39 43,400 31 1,826,000 31 1,705,600 31 120,400 55 73,300
2008 34 2,374,700 52 274,700 48 84,400 52 116,600 59 73,700 53 116,400 45 57,700 31 1,847,600 31 1,728,000 30 119,600 50 73,800
2009 35 2,474,500 55 288,100 51 83,600 54 125,500 65 78,900 52 114,300 47 62,000 32 1,928,600 32 1,792,000 35 136,600 60 77,600
2010 38 2,665,700 58 322,900 51 86,900 56 134,800 70 101,300 55 125,400 45 56,100 34 2,079,500 34 1,947,000 37 132,500 61 76,900
2011 37 2,654,700 not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected not collected
2012 37 2,652,700 56 328,900 46 82,700 56 139,100 68 107,200 53 125,300 42 65,400 34 2,057,300 34 1,921,800 44 135,500 58 70,600
2013 38 2,670,500 57 332,500 54 89,000 52 134,400 69 109,100 53 133,900 38 63,400 35 2,062,700 34 1,936,600 42 126,100 63 76,200
2014 39 2,739,800 60 344,700 58 99,000 55 137,700 69 108,100 54 142,600 43 75,100 35 2,081,300 35 1,941,300 41 140,000 65 85,700
2015 37 2,629,100 57 330,700 54 92,300 53 136,600 67 101,800 56 159,600 46 78,400 34 1,985,200 34 1,862,400 36 122,700 59 70,500
2016 38 2,675,700 60 363,800 59 93,500 56 149,700 68 120,600 50 139,400 48 82,100 35 2,006,400 35 1,871,000 36 135,400 61 79,000
2017 38 2,639,100 58 370,600 49 85,500 58 169,000 65 116,100 56 141,300 45 83,100 35 1,954,900 34 1,789,500 40 165,400 63 83,100
2018 39 2,647,500 56 352,600 52 81,600 53 164,900 65 106,100 57 165,000 46 85,300 35 1,945,900 35 1,798,000 40 147,900 64 95,100
2019 39 2,607,100 58 374,000 56 95,200 56 176,800 64 101,900 53 154,100 48 79,300 35 1,905,600 35 1,772,700 35 132,900 63 92,400
2020 39 2,622,000 56 315,700 54 88,200 59 144,500 55 83,000 55 150,200 46 95,400 36 1,994,500 36 1,873,800 39 120,700 58 63,500
2021 41 2,709,400 55 321,900 59 92,900 53 146,400 53 82,500 56 164,100 53 129,200 38 2,031,400 37 1,892,300 46 139,100 56 61,300
2022 40 2,645,600 54 326,400 52 93,700 56 145,300 53 87,400 51 171,900 43 104,900 37 1,943,800 36 1,797,800 44 146,000 62 96,600

Download table data for ‘By ethnicity over time (16 to 24 year olds only)’ (CSV) Source data for ‘By ethnicity over time (16 to 24 year olds only)’ (CSV)

Summary of Economic inactivity By ethnicity over time (16 to 24 year olds only) Summary

16 to 24 year olds were more likely to be economically inactive than older people. This is partly because people in this age group were more likely to be students.

The data shows that:

  • between 2004 and 2022, the overall rate of economic inactivity for 16 to 24 year olds went up from 32% to 40%
  • the biggest increase was in the white ‘other’ ethnic group (up from 26% to 44%)
  • for the Asian ‘other’ ethnic group, the rate of economic inactivity for 16 to 24 year olds went down from 57% to 53%

9. By ethnicity and area

Percentage and number of 16 to 64 year olds who were economically inactive, by ethnicity and area
All Asian Indian Pakistani, Bangladeshi Asian other Black Mixed White White British White other Other Unknown
Region All % All Number of people economically inactive Asian % Asian Number of people economically inactive Indian % Indian Number of people economically inactive Pakistani, Bangladeshi % Pakistani, Bangladeshi Number of people economically inactive Asian other % Asian other Number of people economically inactive Black % Black Number of people economically inactive Mixed % Mixed Number of people economically inactive White % White Number of people economically inactive White British % White British Number of people economically inactive White other % White other Number of people economically inactive Other % Other Number of people economically inactive Unknown % Unknown Number of people economically inactive
All 22 8,693,500 26 874,700 20 259,500 33 390,500 24 224,800 26 397,200 26 183,500 21 6,967,200 21 6,509,600 15 457,600 28 258,700 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
East Midlands 23 667,400 27 63,900 25 36,000 35 14,000 28 13,800 24 21,100 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 22 557,900 23 529,400 14 28,400 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
East of England 19 737,800 24 55,700 16 13,800 35 26,400 22 15,500 19 22,900 19 14,800 19 633,400 20 584,600 15 48,800 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
London 20 1,244,100 24 281,300 18 81,600 31 121,100 23 78,600 25 190,700 27 54,800 17 609,500 18 445,900 15 163,600 27 105,700 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
North East 26 423,200 29 13,600 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 26 392,300 26 382,700 22 9,600 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
North West 23 1,046,000 33 108,800 23 22,300 41 68,700 26 17,800 29 32,400 33 21,900 22 855,200 22 828,500 15 26,700 39 27,300 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
Scotland 23 788,500 28 36,900 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 26 13,800 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 23 718,000 23 685,300 13 32,800 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
South East 19 1,083,800 19 77,200 19 32,800 22 17,400 19 27,100 28 33,000 22 17,600 19 934,100 20 877,800 13 56,300 21 19,500 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
South West 20 652,800 25 25,800 18 6,400 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 29 14,800 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 15 7,000 19 607,600 20 580,500 15 27,100 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
Wales 24 466,200 24 10,300 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 24 439,900 24 429,100 19 10,800 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
West Midlands 23 818,800 28 130,300 22 40,800 37 75,000 19 14,500 30 53,600 39 25,900 21 575,400 21 547,200 16 28,200 31 31,400 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable
Yorkshire and The Humber 23 765,000 31 70,800 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 30 39,400 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable 26 20,600 26 16,600 22 643,800 22 618,600 16 25,300 withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable withheld because a small sample size makes it unreliable

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

Summary of Economic inactivity By ethnicity and area Summary

Where data is available and not withheld due to small sample sizes, the data shows that:

  • people from the white ‘other’ ethnic group had a lower rate of economic inactivity among 16 to 64 year olds in every region
  • in particular, people from the white ‘other’ ethnic group had the lowest rate of economic inactivity in Scotland and the South East (both 13%)
  • the combined Pakistani and Bangladeshi ethnic group had the highest rate of economic inactivity among 16 to 64 year olds in the East Midlands, East of England, London, and the North West
  • in particular, the highest rate of economic inactivity was for people from the combined Pakistani and Bangladeshi ethnic group in the North West (41%)

10. Data sources

Source

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.

11. Download the data

Economic Inactivity By Local Authority - Spreadsheet (csv) 3 MB

This file contains the following: Measure, Ethnicity, Ethnicity_type, Time, Time_type, Geography, Geography_type, Age, Value, Confidence_interval, Numerator, Denominator, Sample_size

Economic Inactivity By Region - Spreadsheet (csv) 4 MB

This file contains the following: Measure, Ethnicity, Ethnicity_type, Time, Time_type, Geography, Geography_type, Age, Age_type, Sex, Value, Confidence_interval, Numerator, Denominator, Sample_size