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Cited by 369

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Some Practical Issues in the Evaluation of Heterogeneous Labour Market Programmes by Matching Methods

Lechner, Michael·2002·Journal of the Royal Statistical Society Series A: Statistics in Society

Abstract

Summary: Recently several studies have analysed active labour market policies by using a recently proposed matching estimator for multiple programmes. Since there is only very limited practical experience with this estimator, this paper checks its sensitivity with respect to issues that are of practical importance in this kind of evaluation study. The estimator turns out to be fairly robust to several features that concern its implementation. Furthermore, the paper demonstrates that the matching approach per se is no panacea for solving all the problems of evaluation studies, but that its success depends critically on the information that is available in the data. Finally, a comparison with a bootstrap distribution provides some justification for using a simplified approximation of the distribution of the estimator that ignores its sequential nature.

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Metadata

Authors
Lechner, M.
Venue
Journal of the Royal Statistical Society Series A: Statistics in Society
Published
2002-02-01
Volume
165
Issue
1
Pages
59-82
ISSN
  • 0964-1998 (ISSN-L)
  • 1467-985X
OpenAlex
W2104405605
Cited by
369
References
5
FWCI
13.68
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Some Practical Issues in the Evaluation of Heterogeneous Labour Market Programmes by Matching Methods. https://app.cochat.ai/papers/10.1111/1467-985x.0asp2
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Lechner, M. (2002). Some Practical Issues in the Evaluation of Heterogeneous Labour Market Programmes by Matching Methods. Journal of the Royal Statistical Society Series A: Statistics in Society. https://doi.org/10.1111/1467-985x.0asp2

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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.