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Data Provider: Welsh Government National Statistics Out-of-work benefit claimants by Welsh economic region, variable and year
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[Collapse]Statistical GroupStatistical Group typology is to present each person by the main reasons why they are claiming benefit. Each client is classified just once. [Filtered]
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Statistical Group 1[Filter]
Area Code[Filter]
Measure1
VariableLevel/Rate [Filter]
Date(Ascending)[Filtered]
[Collapse]AreaWelsh economic regions, local authorities, Wales and UK[Filter]
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[Collapse]Area 1
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Area 2
[Collapse]LevelThe number of people claiming benefits[Collapse]RateThe number of people claiming benefits as a percentage of the population aged 16-64.
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[Expand]Great Britain4,797,6984,730,2034,412,4084,017,6483,724,3633,481,58812.111.911.110.19.38.7
[Collapse]Wales293,710286,090267,695250,510235,875221,07515.114.813.913.012.311.5
Wales[Collapse]North WalesIsle of Anglesey5,8705,7255,4754,9384,7034,36513.913.713.212.011.510.7
Gwynedd8,4358,1407,5187,0056,7106,29511.210.910.19.59.08.5
Conwy9,5509,4208,9488,2787,7607,30514.114.013.312.411.711.0
Denbighshire8,9158,7208,1787,6357,2386,73015.615.414.513.613.012.1
Flintshire11,05810,5989,8608,9238,1637,64811.411.110.39.48.68.1
Wrexham11,70311,39310,6339,9259,1088,53013.613.312.511.710.810.1
[Collapse]Mid WalesPowys8,2207,9557,3236,8086,5436,16310.310.19.48.88.58.0
Ceredigion4,8254,6604,2904,0053,9083,77010.09.68.98.58.48.1
[Collapse]South West WalesPembrokeshire9,6039,4238,8588,2508,0807,66013.012.912.211.411.210.7
Carmarthenshire17,00316,32815,08014,21313,45012,78015.114.613.512.812.211.6
Swansea23,38322,70821,48320,50519,50818,54515.214.814.013.412.712.0
Neath Port Talbot17,41816,61815,67814,96314,13513,40819.618.817.817.016.115.3
[Collapse]South East WalesBridgend15,24514,89513,93012,94812,01511,22517.116.915.814.713.612.7
The Vale of Glamorgan9,9709,4508,7288,2037,8287,55812.512.011.110.510.09.7
Rhondda, Cynon, Taff29,84529,21327,19825,29023,79522,36319.919.518.217.016.015.0
Merthyr Tydfil8,2638,0757,5106,9486,4135,89021.721.419.918.517.115.7
Caerphilly21,25820,52519,06317,82316,64315,23318.618.116.815.814.813.5
Blaenau Gwent10,24510,0389,2738,4937,9687,33022.922.620.919.318.216.7
Torfaen9,8139,7739,1558,5007,9487,26817.117.116.014.914.012.8
Monmouthshire5,5105,5055,0734,7804,5104,2189.89.99.18.68.27.7
Newport15,02014,89814,30313,57012,63811,65816.216.215.514.713.712.6
Cardiff32,56832,03330,15028,50526,81825,14513.813.512.611.911.110.4

Metadata

Title

Benefit claimants by Welsh economic region and statistical group

Last update

19 May 2017 19 May 2017

Next update

No longer updated

Publishing organisation

Welsh Government

Source 1

Jobcentre Plus Administrative System, Department for Work and Pensions

Contact email

economic.stats@gov.wales

Designation

National Statistics

Lowest level of geographical disaggregation

Local authorities

Geographical coverage

Wales

Languages covered

English and Welsh

Data 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-licence

General description

This dataset provides a quarterly snapshot of benefit claimants at particular points in time and are based on 100% of claimants so is not subject to any sampling error. Data are for the number of people aged 16 to 64 who are claiming one or more key DWP benefits and the combination of benefits they are claiming.
The aim of the Statistical Group typology is to present each person by the main reasons why they are claiming benefit. Each client is classified just once.
Benefits are arranged hierarchically and claimants are assigned to the top most benefit which they receive. Thus a person who is a lone parent and receives Incapacity Benefit would be classified as incapacity benefits.
For this reason the group lone parent, for example, will not contain all lone parents claiming Income Support. Some will be included in the incapacity benefits group instead.
Data are not seasonally adjusted so any comparisons should be made year on year.


Data collection and calculation

Data are for the number of people aged 16 to 64 who are claiming one or more key DWP benefits and the combination of benefits they are claiming.

The aim of the Statistical Group typology is to present each person by the main reasons why they are claiming benefit. Each client is classified just once. Benefits are arranged hierarchically and claimants are assigned to the top most benefit which they receive. Thus a person who is a lone parent and receives Incapacity Benefit would be classified as incapacity benefits.
For this reason the group lone parent, for example, will not contain all lone parents claiming Income Support. Some will be included in the incapacity benefits group instead.
Data are not seasonally adjusted so any comparisons should be made year on year.

Frequency of publication

Quarterly

Data reference periods

1999 to 2016

Rounding applied

Data are rounded to the nearest 10.

Revisions information

From August 2017, the Department for Work and Pensions (DWP) are no longer publishing working age benefits claimants by client group. The full DWP statement is available at https://www.nomisweb.co.uk/articles/1048.aspx. We are in the process of identifying a new appropriate source for this data.

Statistical quality

Difficulties exist in the ability of the WPLS data to identify flows claims of short duration. These short duration cases affect the numbers starting a new claim (on-flow) or ending a benefit claim (off-flow) with reference to a certain time period. Flows are currently reported for Bereavement Benefit/Widows Benefit (6 weekly scan), Incapacity Benefit/Severe Disability Allowance (6 weekly scan), Income Support (weekly scan), Pension Credit (weekly scan), State Pension (6 weekly scan) and Employment and Support Allowance (2 weekly scan). Claims which both start and end between two consecutive extract dates will not be detected. Previously for the 5% sample data, because there is a 3 month gap between extracts, some claims with a duration from one day up to almost 3 months were missed and so the use of WPLS data offers much improvement in this respect.

Keywords

Benefits