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
Englisch

Bibliographic citation
Journal: Journal for Labour Market Research ; ISSN: 2510-5027 ; Volume: 57 ; Year: 2023 ; Issue: 1 ; Pages: 1-19

Classification
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
Unemployment benefts
Beneft sanction
Labor market policies

Event
Geistige Schöpfung
(who)
Schmidtke, Julia
Event
Veröffentlichung
(who)
Springer
(where)
Heidelberg
(when)
2023

DOI
doi:10.1186/s12651-023-00347-6
Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

This object is provided by:
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

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