The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.
LONG-RUN EFFECTS OF PUBLIC SECTOR SPONSORED TRAINING IN WEST GERMANY
Open accessAbstract
Between 1991 and 1997 West Germany spent on average about 3.6 bn Euro per year on public sector sponsored training programmes for the unemployed. We base our empirical analysis on a new administrative data base that plausibly allows for selectivity correction by microeconometric matching methods. We identify the effects of different types of training programmes over a horizon of more than seven years. Using bias corrected weighted multiple neighbours matching we find that all programmes have negative effects in the short run and positive effects over a horizon of about four years. However, for substantive training programmes with duration of about two years gains in employment probabilities of more than 10% points appear to be sustainable, but come at the price of large negative lock-in effects.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Estimating causal effects of treatments in randomized and nonrandomized studies
Rubin, D. B. (1974) · Journal of Educational Psychology · doi:10.1037/h0037350 · Cited by 9,436
Fisher, R. A. (1936) · BMJ · doi:10.1136/bmj.1.3923.554-a · Cited by 4,980
Propensity Score-Matching Methods for Nonexperimental Causal Studies
Dehejia, R. H., & Wahba, S. (2002) · Review of Economics and Statistics · doi:10.1162/003465302317331982 · Cited by 4,846
Selection on observed and unobserved variables: Assessing the effectiveness of Catholic schools
Altonji, J. G., Elder, T. E., & Taber, C. R. (2005) · Journal of Political Economy · doi:10.1086/426036 · Cited by 3,706
The Causal Effect of Education on Earnings
Card, D. (1999) · Handbook of Labor Economics · doi:10.1016/s1573-4463(99)03011-4 · Cited by 3,502
The Economics and Econometrics of Active Labor Market Programs
Heckman, J. J., Lalonde, R. J., & Smith, J. A. (1999) · Handbook of Labor Economics · doi:10.1016/s1573-4463(99)03012-6 · Cited by 3,059
Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review
Imbens, G. W. (2004) · Review of Economics and Statistics · doi:10.1162/003465304323023651 · Cited by 2,994
SOME THOUGHTS ON THE DISTRIBUTION OF EARNINGS 1
ROY, A. D. (1951) · Oxford Economic Papers · doi:10.1093/oxfordjournals.oep.a041827 · Cited by 2,958
Large sample properties of matching estimators for average treatment effects
Abadie, A., & Imbens, G. W. (2006) · Econometrica · doi:10.1111/j.1468-0262.2006.00655.x · Cited by 2,908
Cited by
Recent Developments in the Econometrics of Program Evaluation
Imbens, G. W., & Wooldridge, J. M. (2009) · Journal of Economic Literature · doi:10.1257/jel.47.1.5 · Cited by 4,926
Mozart or Pelé? The effects of adolescents' participation in music and sports
Cabane, C., Hille, A., & Lechner, M. (2016) · Labour Economics · doi:10.1016/j.labeco.2016.05.012 · Cited by 51
Self-citation
Metadata
- Authors
- Lechner, M., Miquel, R., & Wunsch, C.
- Venue
- Journal of the European Economic Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-04-28
- Volume
- 9
- Issue
- 4
- Pages
- 742-784
- ISSN
- 1542-4766 (ISSN-L)
- OpenAlex
- W2142076417
- Cited by
- 371
- References
- 72
- FWCI
- 59.57
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: LONG-RUN EFFECTS OF PUBLIC SECTOR SPONSORED TRAINING IN WEST GERMANY. https://app.cochat.ai/papers/10.1111/j.1542-4774.2011.01029.x
- The paper
- Lechner, M., Miquel, R., & Wunsch, C. (2011). LONG-RUN EFFECTS OF PUBLIC SECTOR SPONSORED TRAINING IN WEST GERMANY. Journal of the European Economic Association. https://doi.org/10.1111/j.1542-4774.2011.01029.x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
