Post-secondary vocational training courses: are they effective for Italian unemployed youth with a high school diploma? COMPIE 2014 Conference Rome, 27th.

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Post-secondary vocational training courses: are they effective for Italian unemployed youth with a high school diploma? COMPIE 2014 Conference Rome, 27th November 2014 Paolo Severati Scientific Coordinator of the Project and Head of Training Policies Evaluation Unit ISFOL – Institute for the Development of Vocational Training for Workers Roma, Corso d’Italia, 33

A national project Ministry of Labour and Social Policies (applicant and provider of the co-financing of the project) ISFOL - Institute for the Development of Vocational Training for Workers ASVAPP & IRVAPP Coordinamento delle Regioni (National Coordination Committee of the Italian Regions)

Outline Evaluation design and methodology Average impact estimates Subgroup analysis Conclusions and policy implications References

EVALUATION DESIGN AND METHODOLOGY

Policy intervention and target population  The study is focused on ‘post-diploma’ (PD) training courses targeted mainly to year old unemployed individuals with a high school diploma  Within the whole spectrum of the training programmes co-financed by ESF in Italy, the features of PD interventions are quite homogenous across the country  PD training courses are very intensive and have a strong focus on the acquisition specific job skills  So, they should reasonably have a positive effect on individual employability

Geographical scope Piedmont Trento Veneto Lazio

Time coverage Different from Region to Region, according to the programming choices and availability of data. For example, in Piedmont PD courses started between 2007 and 2011 were chosen (from 2-6 year coverage, outcome data being available until the end of 2013) PD courses last from less than one to two years Lock-in effect (generally absorbed after maximum 2 years)

Methodology Propensity score matching Kernel matching estimator Blocking with regression adjustment estimator (Imbens [2014])

Data requirement Propensity score matching is data hungry in terms of the number of variables to estimate participation and outcomes Three archives were used and merged for the analysis : 1.Regional archives on training policies (co-funded by ESF or not); 2.Public Employment Service Archives; 3.COB (Comunicazioni Obbligatorie) Archives, containing information that every private employer or agent is legally bound to communicate on- line to the COB archive in order to initiate, modify or terminate any work- related contract

Accurate description of the pre-intervention labour market history is crucial to derive a credible comparison group Pre-programme (un)employment is an important predictor of programme entry and employment outcomes (un)employment history can capture unobservable characteristics (as, for instance, motivation) which could influence participation and outcomes

Design of evaluation

AVERAGE IMPACT ESTIMATES

Average impact estimates Evidence from our analysis shows: 1.Significant and positive effects on individual employability 2.Lock-in effect (months after the beginning of the course the treatment group exhibits a lower probability of employment, but a positive effect on the probability of employment is evident in subsequent months)

Piedmont - Trainees employment rate and counterfactual estimate, months -24 to 48 since the beginning of the training courses, years

Trento - Probability to be at work for participants and controls after matching, months -36 to 27 since the beginning of the training courses, years 2010 and 2011 Trento - Probability to be at work for participants and controls after matching, months -36 to 27 since the beginning of the training courses, years 2010 and 2011

Veneto - Probability to be at work for participants and controls after matching, months -60 to 36 since the beginning of the training course, years 2008 and 2009

Effects on other outcomes and matching procedure It seems that participation to courses reduces the probability of finding an open-ended contract Positive effect on number of weeks spent working in a year Impact estimates do not depend on the matching procedure used

Piedmont – Average impact estimates

Piedmont - Sensitivity analysis

Trento - ATT on the probability to be at work estimating using kernel matching (KM) and blocking with regression adjustment (BRA)

Trento - ATT on the probability to get an open – ended contract and on the number of weeks at work estimating using kernel matching (KM) and blocking with regression adjustment (BRA)

Veneto - ATT on the probability to be at work estimating using kernel matching (KM) and blocking with regression adjustment (BRA)

Veneto - ATT on the probability to get an open – ended contract and on the number of weeks at work estimating using kernel matching (KM) and blocking with regression adjustment (BRA)

Lazio - ATT on the probability to be at work at 12, 24, 36 months after the beginning of the treatment

Lazio - ATT on the probability to get an open-ended contract at 12, 24, 36 months after the beginning of the treatment

SUBGROUP ANALYSIS

Effects on subgroups are different in each Region Age. In Piedmont, the impact seems to be higher for younger people (18-20) who just got a diploma. In Veneto the impact is larger for older participants. Gender. In Piedmont, few differences between women and men. In Veneto the effect is larger for females Length: in Piedmont some evidence on the existence of positive correlation between course length and employability. In Veneto slight evidence of a positive correlation between (short) length and the (short) size of the lock-in effect

Piedmont – Average impact estimates, by age

Piedmont - Average impact estimates, by gender and nationality

Trento - Average impact estimates, by age and gender

Veneto - Average impact estimates, by age and gender

Conclusions and policy implications Training courses have a positive effect on individual employability (and on number or weeks worked in a year) Effects on different target groups are different from Region to Region Length of courses and lock-in: interesting but slight evidence. More analysis is needed

References Ashenfelter,O. (1978), Estimating the effects of training programs on earnings, The Review of Economics and Statistics, Vol.60: Crépon, B., Ferracci, M. and Fougère, D. (2007). Training the unemployed in France: how does it affect unemployment duration and recurrence? Bonn: IZA discussion paper n Heckman, J.J., LaLonde, R.J. and Smith, J.A. (1999). The economics and econometrics of active labor market programs. In Ashenfelter, A. and Card, D. (Edited by) Handbook of Labour Economics, Volume 3: Elsevier Imbens G. (2014), ‘Matching Methods in Practice: Three Examples’, IZA Discussion Paper n Lechner, M. (1999). Earnings and employment effects of continuous off-the-job training in East Germany after reunification. Journal of Business & Economic Statistics, 17(1): 74-90

References Lechner, M., Miquel, R. and Wunsch, C. (2007). The curse and blessing of training the unemployed in changing economy: the case of East Germany after unification. German Economic Review, 8(4): van Ours, J.C. (2004). The locking-in effect of subsidized jobs. Journal of Comparative Economics, 32(1): Sianesi, B. (2004). An evaluation of the Swedish system of active labor market programs in the 1990s. Review of Economics and Statistics, 86(1):

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