Artikel
Linking information on unemployment benefit sanctions from different datasets about welfare receipt: Proceedings and research potential
Most studies on benefit sanctions within the German welfare system rely on established datasets about welfare receipt. This paper analyzes how using a dataset from the operational system of the German Federal Employment Agency for processing welfare claims can contribute to further research on benefit sanctions. For this purpose, I use a random sample of welfare recipients with at least one sanction between 2016 and 2018. First, this allows the detailed analysis of time lags between different steps in the sanction process. Second, linking this dataset with established datasets allows the identification of imposed sanctions for which sanction periods could not be (fully) implemented. This is largely explained by individuals leaving the welfare system between sanction events and sanction periods, e.g., by taking up employment. Third, the paper shows differences in benefit cuts across subgroups. This opens up paths for future research.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal for Labour Market Research ; ISSN: 2510-5027 ; Volume: 57 ; Year: 2023 ; Issue: 1 ; Pages: 1-19
- Classification
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Wirtschaft
Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
Unemployment Insurance; Severance Pay; Plant Closings
Welfare, Well-Being, and Poverty: Government Programs; Provision and Effects of Welfare Programs
Mobility, Unemployment, and Vacancies: Public Policy
- Subject
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Unemployment benefts
Beneft sanction
Labor market policies
- Event
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Geistige Schöpfung
- (who)
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Schmidtke, Julia
- Event
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Veröffentlichung
- (who)
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Springer
- (where)
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Heidelberg
- (when)
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2023
- DOI
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doi:10.1186/s12651-023-00347-6
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Schmidtke, Julia
- Springer
Time of origin
- 2023