Adults (16-64 years) with low or no qualifications
Low or no qualification is SCQF level 4 or below
Data
Adults (16-64 years) with low or no qualifications
Description
Note: Labour Force Survey (LFS) and Annual Population Survey (APS) responses are weighted to official 2018-based population projections on demographic trends that pre-date the COVID-19 pandemic. In the Coronavirus and the impact on payroll employment article, ONS analyse the population totals used in the LFS weighting process and state their intention to make adjustments. Rates published from the LFS remain robust; however, levels and changes in levels should be used with caution. This will particularly affect estimates for country of birth, nationality, ethnicity and disability.
The new weighting LFS methodology was published on 17 May 2021 and it will be applied to Labour Force Survey results in July 2021 and Annual Population Survey results in August/September 2021.
People are classed as having low or no qualifications if they have SCQF level 4 or below. The ratio is the number of people who reported having low or no qualification divided by the number of people in employment (16-64 years). A small number with unknown qualifications are excluded from this calculation.
The data used for this indicator are taken from the Annual Population Survey (APS). The APS was introduced in January 2004 and it has replaced the Annual Local Area Labour Force Survey. The APS combines results from the Labour Force Survey (LFS) and the English, Welsh and Scottish Labour Force Survey boosts. The boosts increase the sample size which means the APS can provide more robust labour market estimates for local areas compared to the main LFS. Thus the APS is the primary source for information on local labour markets providing headline estimates on employment, unemployment and economic activity. The APS is the largest annual household survey in Scotland and provides a wealth of information about individuals' personal circumstances and their work. The LFS surveys individuals living at private households in the UK and is designed to be representative of the national population.
The Scottish Government funds the boost to the LFS sample in Scotland, taking the sample size from approximately 8,000 households for the each year to 17,000 households.
Metadata
| Theme | Labour Force |
|---|---|
| Organisation | Scottish Government |
| License | UK Open Government Licence (OGL) |
| Published | |
| Last updated | |
| Next update | 1 Nov 2022 |
| Update frequency | annual |
| Reference period | 2004 to 2019 |
| Geographic coverage | Council Areas, Country |
| Contact | lmstats@gov.scot |
Data quality
Completeness
Statistics from the APS are presented in reports and spreadsheets available on the Scottish Government's website.
Uniqueness
Not assessed
Consistency
The Scottish Government publishes reports which present analysis on the labour market at Scotland and sub-Scotland levels. Note that these data are not seasonally adjusted and comparisons should only be made with the same quarter across years.
Timeliness
This dataset is updated quarterly. However it is updated on statistics.gov.scot annually.
Validity
The APS combines results from the 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 LFS, for local areas and smaller groups of the population.
Accuracy
Where the estimate is unreliable (i.e. the group sample size or estimate is small) or the group sample size is zero or disclosive (0-2), the data has been removed.
Quality management
Details on the methodology and quality assurance of APS data can be found on the ONS website.
Estimates are not shown where the estimate is not sufficiently robust due to being based on a small sample size.
Additional details
Revisions
In April 2019, APS data for Scotland was reweighted to 2016 population estimates. Consequently estimates for previous years (from 2012 through to 2018) may differ from previously released results.
Confidentiality policy
This dataset does not contain any sensitive or personal information.