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Apprenticeships and firm performance an empirical investigation using “big data” for all English businesses

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posted on 2025-10-29, 16:33 authored by Stefan Speckesser, LEI XuLEI Xu
<p dir="ltr">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.</p><p><br></p>

Funding

Centre for Vocational Education (CVER) work programme, Department for Education, UK Central Government [RE140182BIS]

History

School

  • Loughborough Business School

Published in

Industrial Relations Journal

Publisher

Wiley

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This is an open access article under the terms of the Creative Commons Attribution License - https://creativecommons.org/licenses/by/4.0/, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Acceptance date

2025-10-14

Publication date

2025-10-26

Copyright date

2025

ISSN

0019-8692

eISSN

1468-2338

Language

  • en

Depositor

Dr LEI Xu. Deposit date: 27 October 2025

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