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The Administrative Data Research Network is an ESRC-funded project that ran from October 2013 - July 2018. It is currently at the end of its funding cycle and is no longer taking applications. Administrative data research will be taken forward in a new project, to be launched later in 2018.

Linking Individualised Learner Records (ILR) to business outcome indicators (Employer Data Service and Inter Departmental Business Register data)

Research overview

While there is considerable evidence of the benefits of apprenticeships for individuals, there is little which aims to estimate the net economic benefit of vocational education on firms. A better trained labour force will benefit a sector or the economy in general, but the question of benefits to individual firms which offer apprenticeships is a key policy question in the government's agenda to increase apprenticeships.

By linking earnings records with data on graduate apprenticeships and information about individual firms, this project aims to discover new knowledge on the impact of vocational education on firms.


This research will deliver much needed evidence on this key policy, and the impact of apprenticeships on productivity and other outcomes for the companies concerned. It will improve decision making on government policy to help young people into work. It will also benefit colleges and other providers which work with employers to deliver apprenticeships.

Government departments

Department of Work and Pensions, HM Revenue & Customs, Department of Education, ONS

More about the research

In contrast to a significant number of studies estimating individual return to apprenticeships in the UK, as recently reviewed by London Economics for BIS [1] , we know of only one UK study (qualitative) by Hogarth et al. (2012), which aimed to estimate the net economic benefit of apprenticeships on firms. This important study does not provide genuine econometric evidence (e.g. a return to investment of firms like for individual-level return estimates of the Mincer tradition), but presents an accounting framework for costs and benefits to firms (similar to Pfeiffer et al., 2009 for the economic evaluation of the German Dual System). As is the case for Germany, Hogarth et al. (2012) show that there are substantial net costs of apprenticeships for employers, i.e. the apprentice product is not sufficient to recover all costs that employers incur when employing apprentices. This suggests that individual employers would have to recoup some of the cost to the employer from the investment into skills by paying post-apprenticeship employees below their marginal revenue product. If there was no such ‘rent sharing’, employers would have few incentives to take on apprentices because they would not be able to recover net apprenticeship costs. A number of studies (See Dionisius et al., 2009, for a summary) from Germany and Switzerland have been looking at whether employers incur a net cost in offering apprenticeships. The main finding emerging from these studies is that the net costs of training apprentices are substantial in Germany, whereas apprenticeship training is on average profitable during the training period for firms in Switzerland, in spite of relatively similar Vocational Education and Training (VET) systems.

While there are undoubtedly firm level effects of apprentices more generally – for example because of a better trained labour force available to sectors or the wider aggregate – the question of individual benefits to firms delivering apprenticeships is a key policy question in the current Government’s agenda to increase apprenticeships.
This study – funded by the Centre for Vocational Education Research (CVER) – will be looking into the post-apprenticeship benefits of individual apprentices to employers. The purpose of this study is to estimate the magnitude of employer’s returns from apprenticeships by looking at the evolution of earnings among apprenticeship graduates and compare movers to stayers.
The main issue is that mobility decision is not random but depends on a number of factors such as productivity, outside opportunities, etc., making the identification of employers’ returns very challenging. To overcome this issue, we propose to link WPLS / ILR (a dataset which allows for the identification of apprenticeship graduates and their earnings) to the Interdepartmental Business Register (IDBR) and the Annual Business Survey which contains employer (i.e. business/firm) level information. This would allow us model the local labour market structure based on the number of similar employers (in terms of industry, size, etc.) within the local labour market and use this as an instrument for mobility decisions.

Date approved

January 2017

Research team/lead researcher

Dr Stefan Speckesser, National Institute of Economic and Social Research and University of Sussex
Dr Matthew Bursnall, National Institute of Economic and Social Research.
Vahé Nafilyan, King’s College London
Sophie Hedges, University of Sussex
Lucia Barbone, University of Sussex
Prof. Steven McIntosh, University of Sheffield
Prof. Andy Dickerson, University of Sheffield
Dr Damon Morris, University of Sheffield
Konstantina Maragkou, University of Sheffield

Page last updated: 24/10/2017