Apprenticeship as a stepping stone to beter jobs: Evidence from brazilian matched employer-employee data

Carlos Corseuil, Miguel Foguel and Gustavo Gonzaga

No 651, Textos para discussão from Department of Economics PUC-Rio (Brazil)

Abstract: The objective of this paper is to evaluate the Brazilian Apprenticeship program (Lei do Aprendiz). This program is a youth-targeted ALMP that has been adopted at a large scale since 2000 in Brazil. The program concedes payroll subsidies to firms that hire and train young workers under special temporary contracts aiming to help them successfully complete the transition from school to work. We make use of a very rich longitudinal matched employee-employer dataset covering the universe of formally employed workers in Brazil, including apprentices. Our identification strategy exploits a discontinuity by age in the eligibility to enter the program in the early 2000’s, when 17 was the age limit to take part in the program. We examine the impacts on employability, wage growth and attachment to the formal labor market using other temporary workers as a control group. We find that the program increases the probability of employment in permanent jobs in 2-3- and 4-5-year horizons. We also find a positive impact on real wages that increases over time. These results hold when we isolate the effects of the training dimension of the program by using an alternative control group composed of subsidized temporary workers. We show evidence that the positive effects of the program are much larger for less-educated workers and for workers who had their first jobs in large firms. These results are robust to other choices of methods to address selection into the program based on unobservables.

Pages: 49p
Date: 2016-04
New Economics Papers: this item is included in nep-dev, nep-edu, nep-lam and nep-ltv
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Journal Article: Apprenticeship as a stepping stone to better jobs: Evidence from Brazilian matched employer-employee data (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:rio:texdis:651

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