Data source: Produced by the Institute for Employment Research, University of Warwick
Provision: Detailed estimates based on econometric analysis of Labour Force Survey (LFS) and Annual Survey of Hours and
Earnings (ASHE) data, constrained to match Office for National Statistics (ONS) published headline figures
Questions you can ask of the data:
How many hours do people work in a particular occupation?
Example of visualised data:
Description of the dataset and provenance
Information on average weekly hours is taken from the ASHE conducted by the ONS. ASHE is the most reliable source of information on Pay and Hours.
Details of the owner / curator
Although the ASHE data set is based on a relatively large sample, this is not large enough to produce reliable data at the level of detail ideally required. There are also concerns about information being disclosive. To avoid these problems the raw survey data are not used.
Instead a set of estimates have been prepared on behalf of the Department for Education by the Institute for Employment Research based on the available information and constrained to match published figures. The estimates are based on published ASHE data but the detailed
estimates are predictions based on a simple set of assumptions that differentiates across each of the main dimensions/characteristics. The results are constrained to match the published totals using an iterative RAS process. The characteristics of the groups concerned distinguish:
- Industry (75 almost 2 digit 2007 classification categories)
- Region/ Country (4 UK countries and 9 English regions)
- Occupation (SOC2010 4 digit categories)
As for Pay, estimates are also provided for earlier years but detailed comparisons between years will not yield statistically robust estimates of changes over time.
Known quality issues with data
ASHE provides robust estimates, but these are subject to sampling errors when sample sizes are small.
Quality control processes
The API suppresses sample cells with zero or small sample sizes.
Accuracy of data
Precise confidence intervals are not provided around the point estimates. Based on guidelines produced by ONS for general use of LFS data the following “rules of thumb” have been adopted:
- If the numbers employed in a particular category / cell (defined by the 12 regions, gender, status, occupation, qualification and industry (75 categories)) are below 1,000 then a query about the related average weekly hours will return “no reliable data available” and offer to go up a level of aggregation across one or more of the main dimensions (e.g. UK rather than region, some aggregation of industries rather than the 75 level, or SOC 2 digit rather than 4 digit).
- If the numbers employed in a particular category / cell (defined as in 1.) are between 1,000 and 10,000 then a query on the average weekly hours will return the estimated figure but with a flag to say that this is based on a relatively small sample size and if the user requires more robust estimates they should go up a level of aggregation across one or more of the main dimensions (as in 1).
- Rounding of estimates – in order to avoid false impressions of precision the API rounds up the estimates before delivering the answer to any query. In the case of the average weekly hours estimates they are rounded to the nearest hour.
Frequency of update
Does the data underlying the API change over time?
ASHE is conducted on an annual basis and the data could in principle be updated at that frequency (but this would require the processing of the data described above (under Details of the owner / curator)).
Will the data go out of date?
The data are as accurate as they can be at the time they are produced. As time goes by they become more out of date but they can be updated regularly.
Does the data you capture change on at least a daily basis?
No – see above.
What type of dataset series is this?
Information based on a cross-sectional survey of employers (ASHE).
Is a feed of changes made available?
No, see above.
How frequently do you create a new release?
Every two years.
What is the delay between creating a dataset and publishing it?
Once the data have been processed they can be uploaded to the LMI for All database.
Do you also provide dumps of the dataset?
Will the data be corrected if they contain errors?
Disclosure and confidentiality
The Department for Education complies with all applicable Data Protection laws in the UK.
The average weekly hours data included in this database are non-disclosive.