Apprenticeships and Firm Performance an Empirical Investigation Using “Big Data” for All English Businesses

Bibliographic Data

ID21334554
AuthorsStefan Speckesser (0000-0002-2442-7194, University of Brighton Brighton East Sussex UK), Lei Xu (0009-0000-3744-0753, Loughborough University Loughborough Leicestershire UK, corresponding author)
Year2026
Volume57
Issue1
Pages87-101
Publication date2026-01-01
Open AccessYes
TypeARTICLE
VenueIndustrial Relations Journal (JOURNAL)
Journal identifiersISSN: 0019-8692 • E-ISSN: 1468-2338
PublisherWiley (PUBLISHER • GB)
DOI10.1111/irj.70016
OpenAlexW4415566941
LanguageEN
References cited25

There are quite a few robust estimates of the earnings effects of successful apprenticeships for individuals, but there is a shortage of research concerning the relationship between apprentices and firm performance, and most of this study is qualitative or based on surveys. This paper aims for an empirical investigation of this relationship using quantitative data available from large government registers. We analyse data for all English businesses, which—linked to Individual Learner Record data (ILR) for participants in apprenticeship programmes—provide structural information on apprenticeship firms and other firms for the years 2010 to 2015. The descriptions show that around 10%–15% of all eligible firms undertook apprenticeships and that apprenticeship firms are larger both in terms of turnover and employment than other firms. Regression analysis is used to explore the nature of the relationship between apprenticeships and the firms' turnover. In models employing a range of observable characteristics and using Inverse Probability Weighting to alleviate the selection into apprenticeships, our findings point towards a positive relationship between engaging in apprenticeships and firm growth, but not to a change in business productivity

Apprenticeship · Earnings · Economic shortage · Empirical research · Government (linguistics) · Identification (biology) · Ordinary least squares · Panel data · Point (geometry) · Education Systems and Policy · Firm Innovation and Growth · Labor market dynamics and wage inequality