Permanent and temporary employment
Published
- 1. Navigate toMain facts and figures section
- 2. Navigate toThings you need to know section
- 3. Navigate to By ethnicity section
- 4. Navigate to By ethnicity over time (permanent employment only) section
- 5. Navigate to By ethnicity over time (temporary employment only) section
- 6. Navigate to By ethnicity and gender section
- 7. Navigate toData sources section
- 8. Navigate toDownload the data section
1. Main facts and figures
- 95% of all working age people (16 to 64 year olds) employed in 2022 were in permanent employment, and 5% were in temporary employment
- 95% of white employees were in permanent employment – the highest percentage out of all ethnic groups
- 12% of black employees were in temporary employment – the highest percentage out of all ethnic groups
- in every ethnic group, a higher percentage of women than men were in temporary employment – the biggest difference was in the Asian ‘other’ and ‘other’ ethnic groups
2. Things you need to know
What the data measures
The data shows the number and percentage of working age people (16 to 64 year olds) in employment who were in permanent and temporary work in their main job. The data covers employees in England, Wales and Scotland.
A person of working age is employed if they:
- are in paid work, as an employee or self-employed
- have a job that they are temporarily away from, for example on holiday
- are on a government-supported training or employment programme
- are doing unpaid family work, for example working in a family business
An employee is in temporary employment if they have a fixed-period contract, or are doing one of the following:
- agency temping
- casual work
- seasonal work
- other temporary work
In the Annual Population Survey, respondents decide if they are in permanent or temporary employment.
Percentages are rounded to whole numbers. Population numbers are rounded to the nearest 100 people, but employment 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 which includes 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 this data
The data uses the ethnic categories 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 the white British and white ‘other’ ethnic groups. Separate figures are also shown for 3 different Asian ethnic groups (Indian, Pakistani and Bangladeshi combined, and Asian ‘other’).
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. Estimates from before and after 2011 may not be consistent, and data for individual ethnic groups in 2011 is not available.
Data for 2004 and 2005 cannot be compared with later years. This is because the permanent or temporary employment status was not known for a large percentage of employees.
There are separate employment 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:
- interpreting survey data, including how reliability is affected by the number of people surveyed
- how weighting is used to make survey data more representative of the whole group being studied
In the data file
See Download the data for:
- estimates by region, and by region and sex for all ethnic groups from 2004 onwards
- confidence intervals for each ethnic group – see how we use confidence intervals to demonstrate the reliability of survey estimates
- sample sizes
- estimates rounded to 1 decimal place
- estimates for employees whose employment status was not known
3. By ethnicity
Permanent | Temporary | |||
---|---|---|---|---|
Ethnicity | Permanent % | Permanent Number of people employed | Temporary % | Temporary Number of people employed |
All | 95 | 25,180,700 | 5 | 1,424,900 |
Asian | 92 | 1,913,900 | 8 | 170,300 |
Indian | 93 | 832,900 | 7 | 64,800 |
Pakistani, Bangladeshi | 90 | 528,400 | 10 | 58,700 |
Asian other | 92 | 552,600 | 8 | 46,800 |
Black | 88 | 850,300 | 12 | 113,600 |
Mixed | 91 | 398,500 | 9 | 37,800 |
White | 95 | 21,535,800 | 5 | 1,048,000 |
White British | 95 | 19,503,000 | 5 | 924,500 |
White other | 94 | 2,032,700 | 6 | 123,500 |
Other | 89 | 468,800 | 10 | 54,200 |
Download table data for ‘By ethnicity’ (CSV) Source data for ‘By ethnicity’ (CSV)
Summary of Permanent and temporary employment By ethnicity Summary
The data shows that:
- 95% of all working age people (16 to 64 year olds) who were employed in 2022 were in permanent employment, and 5% were in temporary employment
- 95% of white employees were in permanent employment – the highest percentage out of all ethnic groups
- 88% of black employees were in permanent employment – the lowest percentage
- 12% of black employees were in temporary employment – the highest percentage out of all ethnic groups
- 5% of white employees were in temporary employment – the lowest percentage
4. By ethnicity over time (permanent employment only)
All | Asian | Indian | Pakistani, Bangladeshi | Asian other | Black | Mixed | White | White British | White other | Other | Unknown | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ethnicity | All % | All Number of people employed | Asian % | Asian Number of people employed | Indian % | Indian Number of people employed | Pakistani, Bangladeshi % | Pakistani, Bangladeshi Number of people employed | Asian other % | Asian other Number of people employed | Black % | Black Number of people employed | Mixed % | Mixed Number of people employed | White % | White Number of people employed | White British % | White British Number of people employed | White other % | White other Number of people employed | Other % | Other Number of people employed | Unknown % | Unknown Number of people employed |
2004 | 94 | 22,217,100 | 91 | 843,100 | 92 | 426,200 | 91 | 224,800 | 92 | 192,000 | 92 | 408,300 | 91 | 138,000 | 94 | 20,628,300 | 95 | 19,663,400 | 90 | 964,900 | 87 | 184,500 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2005 | 95 | 22,522,100 | 91 | 888,500 | 91 | 444,800 | 92 | 236,100 | 89 | 207,700 | 90 | 439,800 | 93 | 143,700 | 95 | 20,799,800 | 95 | 19,727,800 | 91 | 1,072,000 | 89 | 237,900 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2006 | 94 | 22,655,500 | 91 | 927,600 | 90 | 460,100 | 92 | 250,900 | 91 | 216,600 | 92 | 484,500 | 93 | 151,400 | 95 | 20,816,900 | 95 | 19,547,300 | 91 | 1,269,700 | 89 | 263,000 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2007 | 94 | 22,818,900 | 92 | 1,000,600 | 93 | 492,900 | 91 | 255,300 | 92 | 252,400 | 92 | 510,100 | 90 | 154,500 | 95 | 20,849,800 | 95 | 19,506,800 | 92 | 1,343,000 | 88 | 292,600 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2008 | 95 | 23,048,800 | 92 | 1,084,200 | 93 | 517,300 | 91 | 280,400 | 91 | 286,500 | 92 | 515,100 | 91 | 156,300 | 95 | 20,970,600 | 95 | 19,544,700 | 92 | 1,425,900 | 89 | 310,300 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2009 | 94 | 22,527,200 | 92 | 1,119,500 | 92 | 542,400 | 93 | 302,700 | 89 | 274,400 | 94 | 522,100 | 90 | 166,800 | 95 | 20,422,000 | 95 | 19,009,300 | 92 | 1,412,700 | 88 | 282,600 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2010 | 94 | 22,336,800 | 91 | 1,148,800 | 91 | 556,900 | 90 | 305,100 | 90 | 286,800 | 91 | 538,600 | 91 | 173,900 | 94 | 20,150,000 | 95 | 18,726,400 | 92 | 1,423,600 | 93 | 305,300 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2011 | 94 | 22,328,400 | 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 | 94 | 22,282,500 | 91 | 1,264,000 | 92 | 583,000 | 89 | 340,300 | 91 | 340,700 | 90 | 551,500 | 89 | 190,800 | 94 | 19,975,800 | 94 | 18,667,800 | 91 | 1,308,100 | 90 | 287,400 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2013 | 94 | 22,510,100 | 91 | 1,287,000 | 91 | 577,400 | 92 | 380,800 | 91 | 328,800 | 91 | 570,400 | 87 | 206,700 | 94 | 20,135,000 | 94 | 18,786,600 | 91 | 1,348,400 | 92 | 299,700 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2014 | 94 | 22,901,600 | 92 | 1,402,400 | 92 | 637,300 | 91 | 416,400 | 91 | 348,700 | 89 | 592,100 | 90 | 218,800 | 94 | 20,353,400 | 94 | 18,852,500 | 92 | 1,501,000 | 91 | 296,500 | 96 | 38,400 |
2015 | 94 | 23,488,700 | 92 | 1,429,200 | 93 | 641,300 | 91 | 416,600 | 92 | 371,400 | 89 | 672,900 | 90 | 234,600 | 94 | 20,794,800 | 95 | 19,148,100 | 91 | 1,646,700 | 91 | 330,000 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2016 | 94 | 23,624,500 | 93 | 1,513,800 | 94 | 662,400 | 92 | 454,400 | 92 | 397,000 | 90 | 704,300 | 91 | 251,000 | 94 | 20,795,300 | 95 | 19,009,100 | 94 | 2,032,700 | 90 | 342,500 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2017 | 94 | 24,081,400 | 92 | 1,542,400 | 93 | 677,400 | 92 | 455,700 | 92 | 409,300 | 88 | 653,900 | 91 | 282,400 | 95 | 21,225,500 | 95 | 19,326,000 | 91 | 1,786,200 | 91 | 361,600 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2018 | 95 | 24,335,700 | 93 | 1,628,000 | 94 | 702,200 | 93 | 522,300 | 91 | 403,500 | 89 | 740,400 | 92 | 295,500 | 95 | 21,292,600 | 95 | 19,393,800 | 92 | 1,899,600 | 91 | 361,400 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2019 | 95 | 24,605,300 | 94 | 1,653,800 | 95 | 728,000 | 93 | 506,700 | 93 | 419,100 | 91 | 801,500 | 92 | 290,100 | 95 | 21,478,100 | 95 | 19,491,200 | 92 | 1,898,800 | 91 | 372,200 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2020 | 95 | 24,778,300 | 93 | 1,671,300 | 94 | 770,900 | 93 | 458,400 | 93 | 442,100 | 91 | 780,800 | 91 | 349,900 | 95 | 21,580,600 | 95 | 19,598,200 | 93 | 1,986,800 | 92 | 377,000 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2021 | 94 | 24,742,800 | 93 | 1,741,200 | 92 | 776,000 | 91 | 490,100 | 95 | 475,200 | 89 | 774,800 | 91 | 356,500 | 95 | 21,471,200 | 95 | 19,500,200 | 94 | 1,982,400 | 91 | 381,600 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2022 | 95 | 25,180,700 | 92 | 1,913,900 | 93 | 832,900 | 90 | 528,400 | 92 | 552,600 | 88 | 850,300 | 91 | 398,500 | 95 | 21,535,800 | 95 | 19,503,000 | 94 | 1,971,100 | 89 | 468,800 | 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 (permanent employment only)’ (CSV) Source data for ‘By ethnicity over time (permanent employment only)’ (CSV)
Summary of Permanent and temporary employment By ethnicity over time (permanent employment only) Summary
The data shows that, between 2006 and 2022:
- the percentage of all employees in permanent employment was consistently between 94% and 95%
- in every ethnic group except for the black, mixed, and combined Pakistani and Bangladeshi ethnic groups, the percentage of employees in permanent employment was higher in 2022 than in 2006
- the percentage of employees from the white ‘other’ and Indian ethnic groups in permanent employment went up by 3 percentage points, (91% to 94% and 90% to 93% respectively)– the biggest increase out of all ethnic groups
- the percentage of black employees in permanent employment went down from 92% to 88% – the biggest decrease out of all ethnic groups *the percentage of employees in permanent employment from mixed and Pakistani and Bangladeshi ethnic groups went down by 2 percentage points between 2006 and 2022
5. By ethnicity over time (temporary employment only)
All | Asian | Indian | Pakistani, Bangladeshi | Asian other | Black | Mixed | White | White British | White other | Other | Unknown | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ethnicity | All % | All Number of people employed | Asian % | Asian Number of people employed | Indian % | Indian Number of people employed | Pakistani, Bangladeshi % | Pakistani, Bangladeshi Number of people employed | Asian other % | Asian other Number of people employed | Black % | Black Number of people employed | Mixed % | Mixed Number of people employed | White % | White Number of people employed | White British % | White British Number of people employed | White other % | White other Number of people employed | Other % | Other Number of people employed | Unknown % | Unknown Number of people employed |
2004 | 6 | 1,368,900 | 9 | 78,100 | 8 | 37,600 | 9 | 23,100 | 8 | 17,400 | 9 | 37,800 | 9 | 13,400 | 6 | 1,211,200 | 5 | 1,105,000 | 10 | 106,200 | 13 | 27,800 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2005 | 6 | 1,302,500 | 9 | 90,800 | 9 | 43,300 | 8 | 21,300 | 11 | 26,200 | 10 | 46,800 | 7 | 10,400 | 5 | 1,124,000 | 5 | 1,016,100 | 9 | 107,900 | 11 | 29,100 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2006 | 6 | 1,346,800 | 9 | 93,100 | 10 | 49,000 | 9 | 23,300 | 9 | 20,800 | 8 | 44,800 | 7 | 11,400 | 5 | 1,163,500 | 5 | 1,035,100 | 9 | 128,400 | 11 | 33,400 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2007 | 6 | 1,359,000 | 8 | 84,600 | 7 | 37,400 | 9 | 24,300 | 8 | 22,900 | 8 | 46,000 | 10 | 16,400 | 5 | 1,173,300 | 5 | 1,050,000 | 8 | 123,200 | 11 | 37,500 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2008 | 5 | 1,268,300 | 8 | 94,800 | 7 | 39,200 | 9 | 27,900 | 9 | 27,800 | 8 | 43,900 | 9 | 15,300 | 5 | 1,076,900 | 5 | 959,300 | 8 | 117,600 | 11 | 36,600 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2009 | 6 | 1,313,500 | 8 | 102,300 | 8 | 45,600 | 7 | 23,700 | 11 | 32,900 | 6 | 35,900 | 10 | 18,400 | 5 | 1,119,700 | 5 | 999,200 | 8 | 120,500 | 11 | 36,100 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2010 | 6 | 1,401,600 | 9 | 116,900 | 9 | 53,700 | 10 | 32,500 | 10 | 30,700 | 9 | 51,100 | 9 | 17,100 | 6 | 1,190,500 | 5 | 1,065,500 | 8 | 125,000 | 7 | 24,300 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2011 | 6 | 1,425,100 | not collected | not collected | not collected | not collected | not collected | not collected | not collected | not collected | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable | 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 | 6 | 1,484,200 | 9 | 126,200 | 8 | 53,100 | 10 | 39,500 | 9 | 33,600 | 10 | 57,900 | 11 | 23,400 | 6 | 1,245,700 | 6 | 1,122,000 | 9 | 123,700 | 10 | 30,300 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2013 | 6 | 1,487,300 | 9 | 119,400 | 9 | 56,400 | 8 | 32,500 | 8 | 30,400 | 9 | 54,000 | 13 | 29,800 | 6 | 1,255,800 | 6 | 1,122,100 | 9 | 133,600 | 8 | 27,000 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2014 | 6 | 1,514,700 | 8 | 120,300 | 7 | 51,000 | 8 | 36,300 | 9 | 33,000 | 10 | 68,900 | 10 | 23,600 | 6 | 1,271,400 | 6 | 1,134,300 | 8 | 137,200 | 9 | 29,200 | 3 | 1,400 |
2015 | 6 | 1,496,400 | 8 | 121,800 | 7 | 47,500 | 9 | 41,100 | 8 | 33,200 | 11 | 83,900 | 10 | 26,700 | 6 | 1,230,800 | 5 | 1,074,200 | 9 | 156,600 | 9 | 32,100 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2016 | 6 | 1,487,400 | 7 | 116,100 | 6 | 43,800 | 8 | 37,900 | 8 | 34,300 | 10 | 80,500 | 9 | 25,400 | 6 | 1,225,600 | 5 | 1,058,200 | 6 | 123,500 | 10 | 37,600 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2017 | 6 | 1,472,100 | 8 | 125,400 | 7 | 50,800 | 8 | 39,900 | 8 | 34,700 | 12 | 88,900 | 10 | 29,500 | 5 | 1,192,700 | 5 | 1,033,400 | 9 | 167,400 | 9 | 34,800 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2018 | 5 | 1,399,700 | 7 | 121,100 | 6 | 42,700 | 8 | 42,200 | 8 | 36,200 | 11 | 90,600 | 8 | 26,400 | 5 | 1,126,900 | 5 | 969,500 | 8 | 159,300 | 8 | 33,100 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2019 | 5 | 1,321,400 | 6 | 109,400 | 5 | 39,100 | 7 | 38,800 | 7 | 31,600 | 9 | 76,900 | 8 | 25,000 | 5 | 1,073,700 | 5 | 934,700 | 8 | 157,400 | 9 | 35,300 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2020 | 5 | 1,367,400 | 7 | 118,800 | 6 | 52,700 | 7 | 32,900 | 7 | 33,200 | 9 | 77,600 | 9 | 33,700 | 5 | 1,105,900 | 5 | 971,600 | 7 | 138,900 | 7 | 30,500 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2021 | 6 | 1,438,900 | 7 | 139,300 | 8 | 63,200 | 9 | 49,200 | 5 | 27,000 | 11 | 96,600 | 9 | 35,300 | 5 | 1,132,300 | 5 | 1,003,700 | 6 | 134,300 | 8 | 34,100 | withheld because a small sample size makes it unreliable | withheld because a small sample size makes it unreliable |
2022 | 5 | 1,424,900 | 8 | 170,300 | 7 | 64,800 | 10 | 58,700 | 8 | 46,800 | 12 | 113,600 | 9 | 37,800 | 5 | 1,048,000 | 5 | 924,500 | 6 | 128,500 | 10 | 54,200 | 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 (temporary employment only)’ (CSV) Source data for ‘By ethnicity over time (temporary employment only)’ (CSV)
Summary of Permanent and temporary employment By ethnicity over time (temporary employment only) Summary
The data shows that, between 2006 and 2022:
- the percentage of employees in temporary employment was consistently between 5% and 6% in every year
- the percentage of people in the white ‘other’ and Indian ethnic groups who were in temporary employment went down from 9% to 6% and 10% to 7% respectively
- the percentage of black employees in temporary employment went up from 8% to 12% – the biggest increase out of all ethnic groups
6. By ethnicity and gender
Men | Women | |||||||
---|---|---|---|---|---|---|---|---|
Ethnicity | Men % Permanent employees | Men Number Permanent employees | Men % Temporary employees | Men Number Temporary employees | Women % Permanent employees | Women Number Permanent employees | Women % Temporary employees | Women Number Temporary employees |
All | 95 | 12,738,700 | 5 | 637,900 | 94 | 12,442,000 | 6 | 787,100 |
Asian | 92 | 1,031,900 | 7 | 83,300 | 91 | 882,000 | 9 | 87,000 |
Indian | 93 | 457,200 | 7 | 33,400 | 92 | 375,700 | 8 | 31,400 |
Pakistani, Bangladeshi | 90 | 310,900 | 10 | 32,800 | 89 | 217,500 | 11 | 25,900 |
Asian other | 94 | 263,800 | 6 | 17,100 | 90 | 288,800 | 9 | 29,700 |
Black | 88 | 352,000 | 11 | 44,500 | 88 | 498,300 | 12 | 69,100 |
Mixed | 91 | 177,800 | 8 | 15,300 | 90 | 220,700 | 9 | 22,600 |
White | 96 | 10,911,100 | 4 | 469,400 | 95 | 10,624,600 | 5 | 578,600 |
White British | 96 | 9,973,300 | 4 | 419,000 | 95 | 9,529,700 | 5 | 505,500 |
White other | 95 | 937,800 | 5 | 50,400 | 94 | 1,094,900 | 6 | 73,100 |
Other | 91 | 258,700 | 9 | 25,400 | 88 | 210,100 | 12 | 28,800 |
Download table data for ‘By ethnicity and gender’ (CSV) Source data for ‘By ethnicity and gender’ (CSV)
Summary of Permanent and temporary employment By ethnicity and gender Summary
The data shows that, among working age people in employment:
- 6% of women and 5% of men were in temporary employment in 2022
- in every ethnic group, a higher percentage of women than men were in temporary employment – out of all ethnic groups, the largest difference was in the Asian ‘other’, and ‘other’ ethnic groups (both 3 percentage points)
- in every ethnic group except the black group, a higher percentage of men than women were in permanent employment
- in the Asian ‘other’ ethnic group, 94% of men and 90% of women were in permanent employment – the largest difference between men and women out of all ethnic groups
7. 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.
8. Download the data
This file contains the following variables: Measure, Employment_type (temporary, permanent), Ethnicity, Ethnicity_type, Time, Time_type, geography, geography_type, sex, value, value_type, confidence_interval, Numerator, Denominator, Sample_size