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Martin Biewen, University of Mainz, IZA, DIW

Employment Effects of Short and Medium Term Further Training Programs in Germany in the Early 2000s. Martin Biewen, University of Mainz, IZA, DIW Bernd Fitzenberger, University of Frankfurt, ZEW, IZA, IFS Aderonke Osikominu, University of Frankfurt

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Martin Biewen, University of Mainz, IZA, DIW

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  1. Employment Effects of Short and Medium Term Further Training Programs in Germany in the Early 2000s Martin Biewen, University of Mainz, IZA, DIW Bernd Fitzenberger, University of Frankfurt, ZEW, IZA, IFS Aderonke Osikominu, University of Frankfurt Marie Waller, University of Frankfurt, CDSEM, ZEW

  2. Motivation • Training programs still major part of active labor market programs in Germany (e.g. expenditures 2000: 6,793 bill. EUR, 2004: 3,616 bill.) • Traditionally, focus on long, expensive programs • Recently, shift towards cheaper short-term training measures • Research questions: • To what extend have programs positive effects? • To what extend can cheaper short-term programs substitute the traditional long-term programs?

  3. Literature • Older studies • Hübler (1998), Lechner (1999), Hujer/Wellner (2000), Fitzenberger/Prey (2000), u.a. • Survey data: SOEP, Arbeitsmarktmonitor Ost • More recent studies • 1) Lechner et al. (2005a,b), Fitzenberger/Speck-esser (2005), Fitzenberger et al. (2006) • 2) Lechner/Wunsch (2006), Schneider et al (2006) • Administrative data from 1) 80s/90s 2) 2000s

  4. Contribution of our study • New, informative data make possible, for the first time, serious evaluations of recent programs • Use of up-to-date econometric methods that address possibility of multiple treatments and dynamic selection into treatment • New evidence on effectiveness and comparative effectiveness of short and medium-term programs

  5. Program types • Short-Term Training (STT) • 2 – 12 weeks • E.g. computer course, application training • Further Training (CFT, PFT) • Several months to one year • Classroom Training (CFT), Practical Training (PFT) • E.g. accounting training in practice firm • Retraining (RT) • 2 to 3 years • Leads to formal professional degree

  6. Data (1) • Integrated Employment Biographies (IEB 2.05) • Administrative Data • 2,2% random sample drawn from 4 sources • Employment History (BeH), 01/90-12/03 • Benefit Recipient Hist. (LeH), 01/90-06/04 • Supply of Applicants (BewA), 01/00-07/04 • Program Participation (MTG), 01/00-07/04 • 1,4 million individuals, 17 million spells • Validation of data set was part of the project

  7. Data (2) • Example employed BeH subsistence allowance unempl. benefit unempl. assistance LeH registered as unemployed searching BewA PFT STT MTG Time

  8. Evaluation strategy (1) • Evaluation Problem: • Effect of program is difference of actual employ-ment outcome and employment outcome in case of counterfactual non-participation • Problem: only one outcome observable • Possible solution: use outcomes of comparable control group of non-participants

  9. Evaluation strategy (2) • Who is a potential participant? • Inflow-sample in non-employment conditioning on previous employment • Advantages • Wide definition of unemployment • Avoid problem of endogenous unemployment • Our inflow-sample • Inflow in non-employment 02/2000 - 01/2002 • At least 3 months of previous employment • 25-53 years old at beginning of non-employment

  10. Evaluation strategy (3) • Multiple Treatments (e.g. Lechner (2001)) • Different Treatments • Here: STT, CFT, PFT or „no treatment“ • Potential outcomes • Average Treatment Effect on the Treated

  11. Evaluation strategy (4) • Dynamic selection into treatment • Program may start at different points of time during unemployment spell • Unemployed individuals who don‘t participate now may participate later • Static approach implicitly conditions on future outcomes (Fredriksson/Johanson (2003)) • Treatment effect may vary with previous unemployment duration (Sianesi (2003, 2004)) • → Distinguish different starting points

  12. Evaluation strategy (5) • Aggregation of potential starting points STT Example: 4-6 months unemployed CFT STT PFT CFT STT PFT UN CFT PFT UN UN Time 0-3 months unemployed 4-6 months unemployed 7-12 months unemployed

  13. Evaluation strategy (6) • Interpretation of treatment effect • Treatment effect reflects decision problem of the case worker: participation now vs. participation later (waiting), or participation in program vs. participation in program

  14. Evaluation strategy (7) • Propensity-score matching • In an experimental sense, individuals are com-parable if they had the same propensity to par-ticipate in the program • Among all -individuals, estimate propensity to participate in program vs. in program • Estimate the counterfactual employment outcome of participants in if they instead had participated in by a local linear kernel regression on the propensity score and the calendar month of the beginning of the unemployment spell

  15. Evaluation strategy (8) • Estimated treatment effect Actual employment outcome of a parti- cular participant Counterfactual employment outcome of the participant is given by weighted average of the employment outcomes of the control group

  16. Evaluation strategy (9) • Cross-validated bandwidth choice (Bergemann et al. (2004)) Choose bandwidth so that the employment outcome of a particular member of the control group is pre- dicted as good as possible by the employment outcomes of the other members of the control group. Here, the particular member of the control group stands for a particular member of the treatment group whose employment status is to be predicted as good as possible.

  17. Evaluation strategy (10) • Determinants of the propensity score • Individual characteristics: age, qualifications, marital status, nationality, health … • Characteristics of the last job: occupation, industry, wage … • Labor market and transfer receipt history • Assessments of case worker: lack of motivation, lack of cooperation, penalties … • Regional information: regional unemployment rate, federal state …

  18. Evaluation strategy (11) • Validity of Cond. Independence Assumption • Rich set of covariates, typically 20 to 35 statis-tically significant regressors in propensity score • Even information on typically unobserved factors • Further unobserved factors proxied by labor and transfer receipt history • Assignment to programs contains strong random element due to local availability of courses • „Pre-Program Test“/Balancing-Tests

  19. Evaluation strategy (12) • Further details of estimation procedure • Smith/Todd (2005)-Balancing-Test • Extensive specification searches for each PS (program £ East/West £ men/women £ strata) • Graphical check of common support assumption • Fully bootstrapped standard errors

  20. Results (1): West GermanyShort Term Training (STT) 5 % 7 % M. 7-12 months unempl. 0-3 months unempl. 4-6 months unempl. 10 % 9 % F.

  21. Results (2): West GermanyClassroom Further Training (CFT) 8 % M. Lock-in Effect 7-12 months unempl. 0-3 months unempl. 4-6 months unempl. 5 % 10 % 16 % F.

  22. Results (3): West GermanyPractical Further Training (PFT) 10 % F. M. 0-12 months unempl. 0-12 months unempl.

  23. Results (4): East GermanyShort Term Training (STT) 7 % M. 7-12 months unempl. 0-3 months unempl. 4-6 months unempl. F.

  24. Results (5): West GermanyClassroom Further Training (CFT) 9 % M. 7-12 months unempl. 0-3 months unempl. 4-6 months unempl. F.

  25. Results (6): West GermanyPractical Further Training (PFT) 7 % F. M. 0-12 months unempl. 0-12 months unempl.

  26. Conclusions • West Germany: both STT and CFT/PFT have sizable positive employment effects (5-10%) • The employment effects of STT are in many cases comparable to those of the longer CFT/PFT • Effects for women generally larger than for men • Effects larger for the long-term unemployed • PFT effective for West German women • Almost no positive effects in East Germany • To do: 1) cross-evaluate programs, 2) incorporate new data, 3) evaluate RT

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