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Why Firms Do and Don’t Offer Apprenticeships

  • Robert I. LermanEmail author
Chapter
Part of the Technical and Vocational Education and Training: Issues, Concerns and Prospects book series (TVET, volume 24)

Abstract

The workforce strategy of firms is increasingly important for competitiveness and for producing at high quality and low costs. Firms must decide on the mix of skills and wages for current and future operations and on whether to train skilled workers or hire them from the open labour market. While traditional human capital theory states that firms will not finance training for general skills, modifications of the theory show training for general skills can be profitable. The modifications are compelling, since employer training for occupational skills varies widely across countries. Employers in the U.S. and France provide little occupational training while the extent of employer occupational training in Germany and Switzerland is enough to reach 55–70 % of a youth cohort. This chapter examines the factors influencing firm choices about providing one type of general training-apprenticeships. Offers of apprenticeships are common in countries where knowledge about apprenticeships is widespread, occupational standards are well developed, and the government finances related, off-the-job training. One reason is that firms in these countries recoup most or all of their investments during the apprenticeship itself, mainly because of the productive contributions to output by the apprentices. But in other contexts, such as the U.S., firms are far less likely to offer apprenticeships. South Carolina’s Apprenticeship Carolina demonstrates how marketing to individual firms and simplifying the process of hiring apprentices can lead large numbers of employers to provide occupational skills training.

Keywords

Human Capital Skilled Worker Occupational Training General Training German Firm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Urban InstituteWashington, DCUSA

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