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Vouchers and caseworkers in training programs for the unemployed

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Abstract

This paper studies the role of vouchers and caseworkers in training programs for the unemployed. We explore the unique features of the Hartz reform in Germany which simultaneously introduced training vouchers and imposed more selective criteria on participants. This allows us to go beyond the standard approach when we estimate the treatment effects for the most important type of training. Next to assessing the overall impact of the reform on the training’s effectiveness, we isolate the impact induced by changes in the composition of program participants (selection effect) from the impact based on the introduction of vouchers and related institutional changes (institutional effect). Our results show a small positive overall impact of the reform. The decomposition suggests that the selection effect is, if at all, slightly negative, and that the introduction of the voucher and related institutional changes increased both employment and earnings of participants. It furthermore appears that our findings are driven by skilled participants.

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Notes

  1. The international literature on the evaluation of ALMP is summarized by LaLonde (2003) and Kluve (2010), among others.

  2. The discussion about vouchers in the field of education started with Friedman (1962).

  3. Görlitz (2010) evaluates the impact of training vouchers for employed workers at the establishment level. This voucher program was implemented in one German federal state in 2006.

  4. The approval of providers and courses is subject to a new quality management system which adopts a two-level approach. For details see, e.g., Bruttel (2005).

  5. The official transitional arrangement was as follows: “Individuals who were counseled before January 1, 2003 and participation in a public training program was agreed upon do not receive a training voucher if they enter the program before March 1, 2003.”

  6. When there are many covariates, it is impractical to match directly on covariates because of the curse of dimensionality. See, e.g., Zhao (2008) for some comments on this problem.

  7. We have additionally run simple OLS for the pooled sample. The results (available on request) suggest that participants in 2003 have a significantly higher probability of being employed than participants in 2002. This is in line with our results.

  8. This is precisely the reason why we perform the decomposition exercise in the presented way, namely that we take the post-reform participants and look for similar individuals among the pre-reform participants. The results of the decomposition might change if we would match participants in 2003 to participants in 2002, i.e., if we would hold the composition of the pre-reform constant. Therefore, the institutional effect has to be interpreted with respect to the group of participants in 2003. This issue is conceptually related to the “omitted group” problem in the Oaxaca-Blinder decomposition framework, see Fortin et al. (2011) for a discussion.

  9. The matching algorithms are implemented using the PSMATCH2 Stata ado-package by Leuven and Sianesi (2003).

  10. See Table 1 for descriptive statistics on selected variables and the notes below Table 1 for additional variables that we use to estimate the propensity scores. We include information on the characteristics which have been shown to be particularly important for selection correction in matching estimation, see Lechner and Wunsch (2011).

  11. Ham et al. (2011) experiment with both the standard bootstrap and “\(m\) out of \(n\)” bootstrap in their matching estimators, and they find that both yield similar results. However, “\(m\) out of \(n\)” bootstrap requires much weaker conditions.

  12. Occupation-related or general training is the most important type of training programs, which is also often referred to as further training (Fitzenberger et al. 2010). The two other broad categories of training programs are retraining and short-term training.

  13. It is in general possible to drop-out early from the program as well as to prolong participation. The actual duration of training is thus endogenously determined (Fitzenberger et al. 2010).

  14. The take-up rate is 86 % from 2003 to 2006 (Kruppe 2009). A simple correction would be to weight the treatment effect by the inverse take-up rate, see Bloom (1984). Assuming a positive impact of voucher Footnote 4 continued

    receipt, our results can, therefore, be seen as a lower bound of the institutional effect (which includes the voucher effect).

  15. We implement an imputation procedure for the educational and vocational attainment variables that is similar to the imputation procedure “IP1” in Fitzenberger et al. (2006). However, we only apply this procedure in case of missing information at the (fictitious) program entry.

  16. We include annual GDP growth rates for the 16 federal states since more disaggregated data is not available.

  17. Note that the potential number of matched pairs in the two-step matching approach is determined by the sample size of participants in 2003, which is 1,319 individuals.

  18. Additionally, we test whether our matching procedure generates comparable samples following the framework of Heckman and Hotz (1989). Mueser et al. (2007) apply a similar approach in the context of binary treatment. Focusing on the pre-training employment status, we see that both one-step and two-step matching procedures generate comparison groups with employment probabilities prior to participation which are very close to those of the treatment groups.

  19. Of course excluding participants who entered public training programs in the first quarter of 2003 implies that we also exclude participants who entered public training programs in the first quarter of 2002 as well as corresponding non-participants based on our matching algorithm.

  20. While participating—or being ”locked-in” in the program—individuals probably reduce their search activities for new jobs (van Ours 2004).

  21. When considering realized earnings, i.e., earnings conditional on being employed, we find that the introduction of the voucher and related institutional changes—next to an increased employment probability—also lead to better job matches for the participants, measured by on average higher monthly earnings in the new job.

  22. We consider completed in-plant training and off-the-job training as well as degrees from a vocational school, a technical school, a university, or a university of applied sciences as vocational degrees.

  23. For a broader and more general overview about the German system of secondary school tracks, the apprenticeship system, and vocational degrees which can be obtained, see for example Winkelmann (1996) and Dustmann (2004).

  24. The business cycle might affect the composition of the unemployed who are eligible for training. While our sensitivity analysis explicitly accounts for differences in the business cycle in different regions of Germany, it may not be able to control for changes in the global trend.

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Acknowledgments

We would like to thank the anonymous referees, Marton Csillag, Bernd Fitzenberger, Steffen Künn, Peter R. Mueser, Núria Rodríguez-Planas, Jeffrey A. Smith, Hilmar Schneider, Marc Schneider, and conference participants in Bonn, Kiel, London, Mannheim, Munich, Nuremberg, and Oslo for valuable discussions and helpful comments. We also thank infas and especially Doris Hess and Helmut Schröder for providing supplementary information about the reform under study. Arne Uhlendorff thanks DIW DC where part of this research was pursued. Zhong Zhao acknowledges financial support from the Capacity Building Project for the Economics Discipline Group at Beijing Municipal Universities (2010–2012). All remaining errors are our own.

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Authors and Affiliations

  1. Institute for the Study of Labor (IZA), Schaumburg-Lippe-Straße 5-9, 53113 , Bonn, Germany

    Ulf Rinne, Arne Uhlendorff & Zhong Zhao

  2. University of Mannheim, Mannheim, Germany

    Arne Uhlendorff

  3. IAB, Nuremberg, Germany

    Arne Uhlendorff

  4. DIW, Berlin, Germany

    Arne Uhlendorff

  5. Renmin University of China, Beijing, China

    Zhong Zhao

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  1. Ulf Rinne
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  2. Arne Uhlendorff
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  3. Zhong Zhao
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Correspondence to Ulf Rinne.

Additional information

The data used in this paper originate from the evaluation of public training programs as part of the evaluation of the proposals of the Hartz Commission. Schneider et al. (2007) contains details.

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Rinne, U., Uhlendorff, A. & Zhao, Z. Vouchers and caseworkers in training programs for the unemployed. Empir Econ 45, 1089–1127 (2013). https://doi.org/10.1007/s00181-012-0662-5

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