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| Nomis (official labour market statistics) | |
|---|---|
| Name | Nomis (official labour market statistics) |
| Established | 2001 |
| Type | Statistical service |
| Headquarters | Newcastle upon Tyne |
| Jurisdiction | United Kingdom |
| Parent agency | Office for National Statistics |
Nomis (official labour market statistics) is an online service providing detailed United Kingdom labour market data, microdata extracts, and bespoke statistical tables. It compiles and disseminates statistics from multiple official sources to support research by academics, analysts at Bank of England, policymakers at Cabinet Office, commentators at Financial Times, and local authorities such as Greater London Authority. Nomis presents data for small geographies and demographic subgroups to aid users including researchers at University of Oxford, analysts at Institute for Fiscal Studies, and NGOs like Resolution Foundation.
Nomis aggregates official labour market outputs from principal producers including the Office for National Statistics, the Department for Work and Pensions, and the HM Revenue and Customs to create harmonised tables for public use. The service exposes microdata from surveys such as the Labour Force Survey and administrative counts like Monthly Labour Force Survey outputs, enabling disaggregation by geography (for example County Durham, Greater Manchester, West Midlands), industry classifications referencing Standard Industrial Classification 2007, and occupational codes aligned with the Standard Occupational Classification 2010. Users can retrieve time series compatible with national indicators produced by organisations such as Organisation for Economic Co-operation and Development, Eurostat, and International Labour Organization.
Nomis originated from a collaboration between the Office for National Statistics and predecessors to central statistical services in the early 2000s, building on earlier dissemination projects at Newcastle University and administrative data initiatives linked to Department for Work and Pensions registers. Key milestones include expansion to include administrative earnings records from HM Revenue and Customs and integration of enhanced geographies following the 2011 United Kingdom census. Subsequent development phases aligned Nomis with digital dissemination standards used by institutions like data.gov.uk and interoperability frameworks referenced by United Nations Statistics Division guidance. Investment rounds and governance changes reflect engagement with bodies such as UK Statistics Authority and advisory input from research centres like Social Policy Research Unit.
Nomis combines survey datasets—most notably the Labour Force Survey and the Annual Population Survey—with administrative sources including Pay As You Earn records from HM Revenue and Customs, benefit caseload information from the Department for Work and Pensions, and vacancy statistics derived from Business Register and Employment Survey. Coverage spans employment, unemployment, inactivity, earnings, vacancies, and workplace characteristics across UK nations: England, Scotland, Wales, and Northern Ireland. Geographic granularity reaches local tiers such as Upper Tier Local Authority and Middle Layer Super Output Area, facilitating comparisons with territorial units used by Eurostat and regional analysis employed by Northern Powerhouse Partnership.
Nomis implements harmonisation rules consistent with standards from the Office for National Statistics and quality frameworks articulated by the UK Statistics Authority. Survey weighting procedures reflect design features of the Labour Force Survey sample; imputation methods and disclosure control routines follow best practice exemplified by the Census 2011 processing and statistical disclosure control used by ONS Data Science Campus. Accuracy statements align with internationally accepted measures promulgated by the International Labour Organization and error estimation techniques used by the OECD. Quality assurance includes automated validation pipelines, peer review by domain experts at University College London and London School of Economics, and user feedback mechanisms modelled on platforms such as data.gov.uk.
Nomis delivers bespoke table building, microdata extracts, and API access to support automated retrieval by research teams at University of Manchester, think tanks like Institute for Government, and software developers at private firms. Interactive mapping and time-series plotting utilities support visualisation tasks similar to those offered by Office for National Statistics online content, while documentation and metadata conform to standards promoted by the UK Data Service and Data Documentation Initiative. Training materials and case studies have been used in courses at University of Leeds and workshops run with partners such as Economic and Social Research Council.
Primary users include academics at University of Cambridge, policy analysts at Scottish Government, local planners at Birmingham City Council, journalists at The Guardian, and consultants at PricewaterhouseCoopers. Applications span labour market monitoring, evaluation of welfare reforms introduced by Welfare Reform Act 2012, regional economic planning aligned with Northern Powerhouse ambitions, and academic research published in journals like Economica and Journal of Labour Economics. Nomis data underpin evidence for public inquiries, parliamentary briefings at House of Commons Library, and forecasting models built by Bank of England staff.
Governance arrangements for Nomis involve stewardship by the Office for National Statistics under oversight frameworks associated with the UK Statistics Authority and partnerships with data providers such as HM Revenue and Customs and the Department for Work and Pensions. Funding has historically come from departmental budgets and centrally allocated resources, with programme support influenced by initiatives tied to Government Digital Service modernization and collaborative research funding from bodies like the Economic and Social Research Council. Ongoing governance balances data access, privacy safeguards informed by precedents like the Data Protection Act 2018, and commitments to transparency advocated by organisations such as Open Knowledge Foundation.
Category:Labour statistics