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Unemployment Model Based Estimates: a data cube spreadsheet

Unemployment Model Based Estimates (level and rate)

Count (People), Ratio (Percentage Of Population), 95% Upper Confidence Limit (Percentage Of Population), 95% Lower Confidence Limit (Percentage Of Population) for values of measure type
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Filter Areas by type:
Measure Type
  1. 95% Lower Confidence Limit
  2. 95% Upper Confidence Limit
  3. Count
  4. Ratio
Reference Period
  1. 2004-Q4
  2. 2005-Q1
  3. 2005-Q2
  4. 2005-Q3
  5. 2005-Q4
  6. 2006-Q1
  7. 2006-Q2
  8. 2006-Q3
  9. 2006-Q4
  10. 2007-Q1
  11. 2007-Q2
  12. 2007-Q3
  13. 2007-Q4
  14. 2008-Q1
  15. 2008-Q2
  16. 2008-Q3
  17. 2008-Q4
  18. 2009-Q1
  19. 2009-Q2
  20. 2009-Q3
  21. 2009-Q4
  22. 2010-Q1
  23. 2010-Q2
  24. 2010-Q3
  25. 2010-Q4
  26. 2011-Q1
  27. 2011-Q2
  28. 2011-Q3
  29. 2011-Q4
  30. 2012-Q1
  31. 2012-Q2
  32. 2012-Q3
  33. 2012-Q4
  34. 2013-Q1
  35. 2013-Q2
  36. 2013-Q3
  37. 2013-Q4
  38. 2014-Q1
  39. 2014-Q2
  40. 2014-Q3
  41. 2014-Q4
  42. 2015-Q1
  43. 2015-Q2
  44. 2015-Q3
  45. 2015-Q4
  46. 2016-Q1
  47. 2016-Q2
  48. 2016-Q3
  49. 2016-Q4
  50. 2017-Q1
  51. 2017-Q2
  52. 2017-Q3
  53. 2017-Q4
  54. 2018-Q1
  55. 2018-Q2
  56. 2018-Q3
  57. 2018-Q4
  58. 2019-Q1
  59. 2019-Q2
  60. 2019-Q3
  61. 2019-Q4
  62. 2020-Q1
  63. 2020-Q2
  64. 2020-Q3
  65. 2020-Q4
  66. 2021-Q1
  67. 2021-Q2
  68. 2021-Q3
Reference Area
(showing types of area available in these data)
  1. Countries
  2. Council Areas
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About the Dataset
Not supplied
Not supplied
In dataset
Next update due
April 2022

The model-based estimate produces a single-best estimate for total unemployment for the local area.

The Annual Population Survey (APS), on which these estimates are based is published quarterly, but with each publication including data for one year. The four publications per year cover the periods January to December; April to March of the following year; July to June of the following year; and October to September of the following year. Three quarters of the survey observations included in one publication will therefore be included in the following publication. The model-based unemployment estimates (and the direct APS survey estimates) represent valid estimates for the period to which they refer but because, as explained above, estimates from consecutive quarters are based on common observations they are not independent, and should not be used for comparisons over time.

Comparisons over time for say the latest annual estimate should only be made using estimates for the same period a year earlier, as the data for these two periods will not include any common observations. Estimates of economic activity status are usually taken from surveys of individuals (nationally from the Labour Force Survey, and from the annual Labour Force Survey or Annual Population Survey for smaller areas). However for most local areas, even the Annual Population Survey does not have a sufficiently large sample to provide precise estimates of unemployment. For this reason a statistical model has been developed to improve the annual LFS/APS estimates of unemployment, for small areas, by using supplementary information, mainly the numbers of claimants of Jobseekers' Allowance (the claimant count). The claimant count is not a measure of unemployment as not all unemployed people are eligible for the benefit (and some legitimate claimants would be considered to be employed under the International Labour Organization definition of employment). However, the claimant count does have a high positive correlation with the number of unemployed people in an area, and it is an administrative count so it is known without sampling error.

The model considers unemployment from the annual LFS/APS and claimant count for six age and sex groups, and also includes a socio-economic area indicator and a random area effect. The relationship between claimant count and the number of unemployed may be different in two areas in spite of them sharing the same factors in the model and this last term is included in order to model these random local differences. The inclusion of the random effect term gives the model-based estimates the property that, for sufficiently large samples, they will coincide with the direct survey estimates.

Confidentiality Policy

This dataset does not contain any sensitive or personal information.

Quality Management

Details on the methodology and quality assurance of Annual Population Survey data can be found on the ONS website.

Accuracy and Reliability

Where the estimate is unreliable (i.e. the group sample size is 3-9 or estimate is less than 500) or the group sample size is zero or disclosive (0-2), the data has been removed.

Coherence and Comparability

Note that this data is not seasonally adjusted and comparisons should only be made with the same quarter across years.

The Scottish Government publishes reports which present analysis on the labour market at Scotland and sub-Scotland levels.

Accessibility and Clarity

Statistics from the APS are presented in reports and spreadsheets available on the Scottish Goverment's website.


The Annual Population Survey (APS) combines results from the Labour Force Survey (LFS) and the English, Welsh and Scottish Labour Force Survey boosts increasing the sample size in Scotland, which means the APS can provide more robust labour market estimates compared to the main Labour Force Survey, for local areas and smaller groups of the population.

Timeliness and Punctuality

This dataset is updated quarterly.


Note relating to Q1 2020 estimates onwards: Annual Population Survey (APS) responses for periods April 2019-March 2020 to January-December 2020 were reweighted on 18 August 2021 to new populations derived using growth rates from HM Revenue and Customs (HMRC) Real Time Information (RTI), to allow for different trends during the coronavirus (COVID-19) pandemic. The reweighting gives improved estimates of both rates and levels. This weighting methodology has also been used for subsequent time periods. Further information on the reweighting process and its impact on labour market statistics can be found in an ONS article at:


This slice of multidimensional data is not a Linked Data resource in the database: it's a virtual resource (i.e. you can't query it by SPARQL). But does have a permanent unique URL which can be bookmarked.
Dimensions Linked Data

A linked data-orientated view of dimensions and values

Dimension Locked Value
Reference Period
Reference Area
(not locked to a value)
Measure Type
(not locked to a value)