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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