ILO unemployment rates by Welsh local areas and year
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Year ending 30 Jun 2005Metadata
- High level information
- Summary information
- Keywords
- Statistical quality information
- Weblinks
- Open Data
Title
Annual Population Survey / Local Labour Force Survey: Summary of economic activityLast update
9 October 2024Next update
January 2025Publishing organisation
Welsh GovernmentSource 1
Annual Population Survey, Office for National StatisticsContact email
LabourMarket.Stats@gov.walesDesignation
National StatisticsLowest level of geographical disaggregation
Local authoritiesGeographical coverage
WalesLanguages covered
English and WelshData licensing
You may use and re-use this data free of charge in any format or medium, under the terms of the Open Government License - see http://www.nationalarchives.gov.uk/doc/open-government-licenceGeneral description
These data are taken from the ANNUAL datasets from the Labour Force Survey (LFS) carried out by the Office for National Statistics (ONS), providing labour market data back to 1996 for the NUTS2 areas in Wales, and back to 2001 for the local authorities in Wales. The availability of local authority data is dependent upon on an enhanced sample (around 350 per cent larger) for the annual LFS, which commenced in 2001.For years labelled 1996 to 2004 in this dataset, the actual periods covered are the 12 months running from March in the year given to February in the following year (e.g. 2001 = 1 March 2001 to 28 February 2002).
Since 2004, the annual data have been produced on a rolling annual basis, updated every three months, and the dataset is now referred to as the Annual Population Survey (APS). The rolling annual averages are on a calendar basis with the first rolling annual average presented here covering the period 1 January 2004 to 31 December 2004, followed by data covering the period 1 April 2004 to 31 March 2005, with rolling quarterly updates applied thereafter.
Note therefore that the consecutive rolling annual averages overlap by nine months, and there is also a two-month overlap between the last period presented on the former March to February basis, and the first period on the new basis.
The population can be broken down into economically active and economically inactive populations. The economically active population is made up of persons in employment, and persons unemployed according to the International Labour Organisation (ILO) definition. This report allows the user to access these data.
Although each measure is available for different population bases, there is an official standard population base used for each of the measures, as follows.
Population aged 16 and over: Economic activity level, Employment level, ILO unemployment level
Population aged 16-64: Economic inactivity level
16-64 population is used as the base for economic inactivity. By excluding persons of pensionable age who are generally retired and therefore economically inactive, this gives a more appropriate measure of workforce inactivity.
Rates for each of the above measures are also calculated in a standard manner and are available in the dataset. With the exception of the ILO unemployment rate, each rate is defined in terms of the shares of population that fall into each category. The ILO unemployment rate is defined as ILO unemployed persons as a percentage of the economically active population.
Although each rate is available for the different population bases, there is an official standard population base used for each of the rates, as follows.
Percentage of population aged 16-64: Economic activity, Employment,. Economic inactivity
Percentage of economically active population aged 16 and over: ILO unemployment
Data collection and calculation
The local authority and Wales figures for 2001, 2002 and 2003 in these tables may not be the same as published elsewhere, as the numbers here are estimated using Welsh specific weights. These weights better reflect the population estimates for Welsh local authorities in these years.LFS data is collected throughout the year, and is available from the ONS in a variety of ways. This dataset contains the latest annual results, as referred to in the second bullet below.
. Key data on the labour market is updated every month showing the position for the latest three months, for the UK and each of the UK countries and English regions. Note these data are seasonally adjusted and also that no sub-regional (i.e. local authority) data are published by the ONS to a monthly timetable.
. Annual results covering the periods described earlier are also available from the ONS, providing more detailed data from the LFS, including data for sub-Wales geographies. These annual datasets use results from the samples for the quarterly surveys used for the key series, together with results from additional persons sampled to provide a more robust (boosted) dataset, with estimates subject to much lower sampling variability.
. Quarterly results are also available, again providing more detailed data from the LFS than the key series, including data for sub-Wales geographies. However, although these data are available earlier than the data taken from the annual datasets, data for sub-Wales geographies taken from the quarterly datasets are no longer included on StatsWales as the results are far less robust than those which come from the annual datasets.
Note that as data are taken from the ANNUAL Labour Force Survey datasets they do NOT exactly match annual averages derived from the 4 QUARTERLY datasets in the relevant 12 month period covered due to differences in the sampling structure.
Further note that the data presented here for Wales and the UK are consistent with the sub-Wales level data, and so have not been seasonally adjusted. Further they do not take account of population estimates released since February 2003 in weighting the results (weighting since then is based on projections). They therefore do not tally with the key labour market data for Wales and the UK.
Nomis is the ONS's official portal for labour market statistics. Note that some estimates from Nomis for the APS may differ slightly from those presented here due to differences in how local authority geographies are constructed.
Note finally that the ILO unemployment measure differs from another commonly used measure of unemployment, namely the claimant count. The latter is a count of all those claiming unemployment benefit, and as such it is not subject to sampling variability. However, it excludes those who are unemployed who are not eligible to claim (for example those out of work but whose partner works), and those who do not wish to claim. The ILO measure, which is a count of those who are out of work and want a job, have actively sought work in the last 4 weeks and are available to start work in the next two weeks; plus those who are out of work, have found a job and are waiting to start in the next 2 weeks, is a more encompassing measure of unemployment, which is used around the world.
Frequency of publication
QuarterlyData reference periods
1996 to 2024Rounding applied
Figures are rounded to the nearest hundred and so there may be some apparent slight discrepancies between the sum of constituent items and the totals as shown.Keywords
Labour marketStatistical quality
Annual Population Survey (APS) responses are weighted to official population projections. The projections for 2020 were 2018-based, and, therefore, were based on demographic trends that pre-dated the COVID-19 pandemic.To allow for different trends during the pandemic the responses for the APS have been reweighted on the 9 September 2021 to new populations derived using growth rates from HM Revenue and Customs (HMRC) Real Time Information (RTI). The reweighting has been applied from year ending March 2020 data onwards and gives improved estimates of both rates and levels.
The changes ONS have made to the weighting should reduce the bias of estimates at high levels of aggregation. Some smaller breakdowns may be impacted negatively and more extreme changes could be seen given the reduced size of the underlying sample since the start of the pandemic.
As the data come from a survey, the results are sample-based estimates and therefore subject to differing degrees of sampling variability, i.e. the true value for any measure lies in a differing range about the estimated value. This range or sampling variability increases as the detail in the data increases, for example individual local authority data are subject to higher variability than Wales data.
