NEET Rates for International Territorial Level 3 Areas, 2022-2024

Houston, Donald (2026). NEET Rates for International Territorial Level 3 Areas, 2022-2024. [Data Collection]. Colchester, Essex: UK Data Service. 10.5255/UKDA-SN-858684

The number of young people not in employment, education or training (NEET) has risen sharply since 2020 and is of rising concern among policy makers. This project examines the geography of NEETS across ITL3 areas and what this can reveal about the underlying causes, in particular the relative importance of the buoyancy of local labour markets versus the traits of young people (specifically qualifications and health).

Data description (abstract)

This dataset contains data for 179 International Territorial Level (ITL3) regions (formerly NUTS3 regions) covering the UK. The ITL3 data have been calculated using ONS's Three-Year Pooled Annual Population Survey Dataset 2022-24 microdata. The novelty of the constructed dataset is that it contains sub-national data on the proportion of 16-24 year olds who are not in employment, education or training (NEET), which is not published by the Office for National Statistics (ONS). Another novel aspect of the dataset is that NEET rates have also been calculated for ages 25-49 and 50-64. Although the NEET concept is normally applied only to young adults, rates for older groups have been included in order to provide benchmarks for comparative analysis. The proportions of different age groups with limiting health conditions and no qualifications are also included.

Data creators:

Creator Name	Affiliation	ORCID (as URL)
Houston Donald		https://orcid.org/0000-0002-7178-9630

Sponsors:

N/A

Topic classification:

Health
Demography (population, vital statistics and censuses)
Labour and employment

Keywords:

YOUTH UNEMPLOYMENT, ILL HEALTH, QUALIFICATIONS, REGIONAL ECONOMY

Project title:

The geography of NEETs

Grant holders:

Donald Houston

Date published:

19 Aug 2026 10:14

Last modified:

19 Aug 2026 10:14

Coverage and Methodology

Collection period:

Date from:	Date to:
1 January 2022	31 December 2024

Geographical area:

ITL3 regions

Country:

United Kingdom

Spatial unit:

European Union Geographies > NUTS-III Areas

Data collection method:

The underlying microdata used to produce the ITL3 dataset is ONS's Three-Year Pooled Annual Population Survey Dataset 2022-24. The Annual Population Survey (APS) is based on a random sample of residential addresses across the UK, aggregating quarterly Labour Force Survey (LFS) data plus APS sample boosts. The APS is designed to produce labour market indicators for local areas. Information is collected on all household members. Weights developed by ONS calibrate the sample (in this case a three-year pooled sample) to local authority population totals (excluding communal establishments), regional population totals by five-year age band and sex, national single-year population totals for 16-24 year olds and national occupational and industrial composition. For more information on the APS/LFS methodology, including weighting, see: Labour Force Survey user guidance, Vol.1 Background and Methodology, 2024 update, Office for National Statistics.

Observation unit:

Geographic unit

Kind of data:

Numeric

Type of data:

UK survey data

Resource language:

English

Access and Administration

Data sourcing, processing and preparation:

NEETs were identified in the underlying APS microdata by deriving a new variable to identify those not in education or training (NET) using the same definition as used by ONS in the quarterly Labour Force Survey, on which the Annual Population Survey is based. ONS’s definition of education or training in deriving NET includes current apprenticeships, government training schemes and part-time courses, any other form of education or training in the previous four weeks (except for leisure interest), plus those currently enrolled on a course but waiting for term to start. NEET was then derived from a combination of NET and employment status, removing those in employment from NET. For details of the derivation of NET and NEET, see: Labour Force Survey user guidance, Vol.4 Standard Derived Variables, 2020 update, Office for National Statistics.

Rights owners: