UK Gross Value Added for Lower Layer Super Output Areas, 1998-2019: Secure Access

DOI

Abstract copyright UK Data Service and data collection copyright owner.

Gross Value Added (GVA) measures the contribution to the economy of each individual producer, industry or sector. It is the value of the amount of goods and services that have been produced, less the cost of all inputs and raw materials that are directly attributable to that production.GVA estimates have been produced as part of the Office for National Statistics' flexible geography project, which aims to produce economic statistics for small geographic areas. These estimates can then be aggregated in a flexible way, allowing users to create their own geographies.The dataset is made by apportioning total GVA at Local Authority level to lower-level geographies [Lower Layer Super Output Areas (LSOAs) in England and Wales, Data Zones in Scotland and Super Output Areas in Northern Ireland] for the period 1998 to 2019. The lower-level geographies data form the small building blocks that can be aggregated flexibly to larger areas including Middle Layer Super Output Areas, Parliamentary Constituencies, Travel-to-Work areas, Health Boards, and towns. The building blocks enable users to build bespoke areas for analysis. The breaking down of GVA to lower-level geographies is the first time such granularity has been achieved and represents a significant improvement which allows the construction of much more detailed geographic areas.

Main Topics:

This dataset includes the following variables:LSOA codes and namesLocal Authority District codes and namesInternational Territorial Level 1 codes and namesGVA for the years 1998 to 2019

No sampling (total universe)

Compilation/Synthesis

Identifier
DOI https://doi.org/10.5255/UKDA-SN-8913-1
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=42e31154731120b7cc6e0a66bc0285f747b0dac9041f33144b821956cb54a0e9
Provenance
Creator Office for National Statistics
Publisher UK Data Service
Publication Year 2022
Funding Reference Office for National Statistics
Rights <a href="https://www.nationalarchives.gov.uk/information-management/re-using-public-sector-information/uk-government-licensing-framework/crown-copyright/" target="_blank">© Crown copyright</a>. The use of these data is subject to the <a href="https://ukdataservice.ac.uk/app/uploads/cd137-enduserlicence.pdf" target="_blank">UK Data Service End User Licence Agreement</a>. Additional restrictions may also apply.; <p>The Data Collection is available to UK Data Service registered users subject to the <a href="https://ukdataservice.ac.uk/app/uploads/cd137-enduserlicence.pdf" target="_blank">End User Licence Agreement</a>.</p><p>Commercial use is not permitted.</p><p>Use of the data requires approval from the data owner or their nominee. Users must apply for access via a Secure Access application.</p><p>Non UK-users must have a UK HE or FE affiliation.</p><p>Registered users must complete the Safe Researcher Training course and gain&nbsp;<a href="https://uksa.statisticsauthority.gov.uk/digitaleconomyact-research-statistics/better-useofdata-for-research-information-for-researchers/" target="_blank">Accredited Researcher Status</a>.</p><p>Users must be based in the UK when accessing data.</p><p>The Data Collection must be accessed via a secure virtual private network in a safe environment approved by the UK Data Service.</p><p>Users should note that researchers are encouraged not to publish individual LSOA data and to combine the LSOA GVA with at least two other LSOAs to meet the standard dominance rules. Users should note in order to assist with the quality assurance process, the ONS business area would like to see any outputs using the study before publication. Once the outputs are checked for disclosure by the UK Data Service these will be forwarded to the data owner for comments/feedback. Please note that due to this process, releasing outputs for this study might take up to ten working days.</p>
OpenAccess true
Representation
Resource Type Numeric
Discipline Economics; Social and Behavioural Sciences
Spatial Coverage United Kingdom