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

Employment Effects of Short and Medium Term Further Training Programs in Germany in the Early 2000s

Martin Biewen, University of Mainz, IZA, DIWBernd Fitzenberger, University of Frankfurt, ZEW, IZA,

IFSAderonke Osikominu, University of Frankfurt

Marie Waller, University of Frankfurt, CDSEM, ZEW

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?

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

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

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

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

Data (2) Example

BeH

LeH

BewA

MTG

Time

employed

unempl. benefit

searching registered as unemployed

unempl. assistance

STT

subsistence allowance

PFT

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

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

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

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

Evaluation strategy (5) Aggregation of potential starting points

Time

STT

CFT

UN

STT

CFT

UN

STT

CFT

UN

0-3 months unemployed4-6 months unemployed7-12 months unemployed

PFT

PFT

PFT

Example: 4-6 months unemployed

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

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

Evaluation strategy (8)

Estimated treatment effect

Counterfactual employment outcome of the participant isgiven by weighted average of the employment outcomesof the control group

Actual employmentoutcome of a parti-cular participant

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 groupwhose employment status is to be predicted as good as possible.

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 …

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

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

Results (1): West GermanyShort Term Training (STT)

M.

F.

0-3 months unempl. 4-6 months unempl. 7-12 months unempl.

7 %5 %

9 % 10 %

Results (2): West GermanyClassroom Further Training (CFT)

M.

F.

Lock-in Effect

8 %

5 %16 %

10 %

0-3 months unempl. 4-6 months unempl. 7-12 months unempl.

Results (3): West GermanyPractical Further Training (PFT)

M. F.

0-12 months unempl. 0-12 months unempl.

10 %

Results (4): East GermanyShort Term Training (STT)

M.

F.

7 %

0-3 months unempl. 4-6 months unempl. 7-12 months unempl.

Results (5): West GermanyClassroom Further Training (CFT)

M.

F.

9 %

0-3 months unempl. 4-6 months unempl. 7-12 months unempl.

Results (6): West GermanyPractical Further Training (PFT)

M. F.

7 %

0-12 months unempl. 0-12 months unempl.

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