Professor Stephan Klasen, Head of Ibero-America Institute for Economic Research at the University of Göttingen presents his paper on the impact of SENAI vocational training in Brazil and its implications for African countries. Read the full research at www.brazil4africa.org/publications

1. What lessons can the Brazil’s SENAI
offer to Africa?
(Draft)
PEGNet Conference
Lusaka
September 19, 2014
Carlos Villalobos and Stephan Klasen
University of Göttingen
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2. Introduction: Africa’s Problematic
School-Work Transitions
• Massive (youth) unemployment rates
• Strong demographic expansion (Youth bulge)
• Accelerated and dysfunctional urbanization (Garcia
and fares 2008, Hove et al. 2013, UNFP 2007);
• What lessons can Brazil’s SENAI system of vocational
training offer for Africa?
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4. SENAI: Origins
• The origins of the SENAI (now larger S-System)
– Deficient schooling system
• basic education universalized in the 1990s (quality?)
• Lack of skills
– WWII and the big effort to industrialize the economy
• to reduce the dependence on imports from the north
• Import substitution policies
– Polarized Pro and anti labour positions
• It was all about politics and ideology
– The need of a new institution devoted to
encourage the supply of skills that would be
acceptable for all parts (financing as key factor)
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5. SENAI-Financing
• Financing model (cost benefit analysis)
• Levy-based (tax of one percent on all payrolls)
• Training based on fee for service
Disadvantages Advantages
Neglect the informal sector Political acceptance
Discourage employers’ training
Financial stability
(dual system)
Lack of competition in the supply
of training / standardization of
training programs
Decoupling of supply and demand
for skills
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6. SENAI-Financing
Training agreements
– supervision
– sell of services
Changing financing structure of the SENAI
– 98% levy in 1965
– 80% levy, 11 % sale of services in 1995
– 71% levy, 20% sale of services in 2000
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7. Literature
Previous evaluations of the SENAI
• Failure of the dual system (lack of apprenticeships vacancies
already in the 1960s)
• Wage premium between 10 and 37% (De Moura Castro 1979,
Arriagada and Ziderman (1992), Vasconcellos et al. (2010),
Fresneda (2012)
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8. Multi-model Approach
• Use PNAD 2007 (with detailed information on
prior training, but only S-System);
• Probit model for current enrolment in vocational
training
• Inverse probability weighting (IPW) estimators to
isolate the average treatment effect (ATE) of
SENAI training (and training made by other
institutions) on monthly labour earnings, monthly
hours of work, hourly labour earnings, formality,
employment, and employment in the same area.
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9. Multi-model Approach
• Heckit approach (control for unobservables +
strong distributional assumptions)
– impact of SENAI training on employability and labour
earnings
• Quintile regressions on monthly earnings to
assess how heterogeneous the wage premium is
distributed by gender and area (urban and rural)
• Switching regression model to study the
geographic mobility of workers (SENAI graduates)
after controlling for wage differentials
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10. Findings
• 4 Samples:
– 1: All population 10+
– 2: Restricted to 15-29
– 3: Restricted to urban areas
– 4: Restricted to women
• Descriptives
– 18% graduates of training, mostly non-SENAI
– S-System graduates more formal, more unionized,
more migrants, more educated, fewer female
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12. (Current) Participation Results
• Higher likelihood:
– Education levels
– Formal sector employed
– Industrial occupations
• No difference: Race and region (only S-System)
• Lower likelihood:
– Female (more likely to do other training);
– (And maybe better served by general school
system?
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15. Results Impact
• Higher earnings, higher likelhood of
employment, and formality;
• Women benefit less from S-System;
• Quantile regressions: Reduces rural-urban gap
at lower quantiles;
• Promotes inter-regional migration;
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16. 16

17. SENAI wage earnings premium by areas as of 2007
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18. Table 3: Probit model: determinants of inter-state Migration (Reduced form and structural)
Survey: Probit regression
Dependent variable: recent inter-state migration
(Five years time span)
Aged 30-40
Variables / Model Reduced Structural
Earnings differential - 0.074
- (0.109)
Earnings differential - squared - -0.136
- (0.155)
Training in S-system 0.142* 0.144*
(0.076) (0.077)
Training in other institutions 0.066 0.061
(0.049) (0.049)
Age -0.010* -0.010*
(0.006) (0.006)
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19. What are the lessons to date?
• Structure:
– SENAI System underwent significant evolutions over
time;
– Continued political struggle over it;
– Struggle over costs and administration;
• Outcomes:
– Broad-based participation (race, region);
– Positive outcomes;
– Does not help the least educated;
– Does not help women much;
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20. What are the lessons to date?
• A mixed financing model seems to be preferred.
(levy + sale of services)
• Federal structure of the system seems to contribute
to geographic and ethnic/racial neutrality (long term
sustainability)
• The potential and limitations of the SENAI (and S-system
as well) originate from its market orientation,
its decentralised and self-governing federal
organization
– We argue that the SENAI can be just as good as the local
employers associations are.
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21. Lessons for Africa?
• Only useful for non-agricultural employment:
relevant only for larger more industrialized Sub-
Saharan African economies?
• Need strong industrial associations to drive the
program;
• Substantial share of formality important (levy-based
system);
• Next step:
– Evaluate SENAI transplants in Africa (Mozambique,
Angola);
– Compare to other training approaches;
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