The Research Data Centre of the German Federal Employment Agency at the Institute for Employment Research (RDC-IAB)

Abstract

"Since 2004, the Research Data Centre of the German Federal Employment Agency at the Institute for Employment Research (RDC-IAB) has been offering comprehensive individual data on employees, unemployed persons, job seekers and participants in active labour market programmes for scientific labour market research. For this purpose, data from employer notifications and from different administrative processes in the labour market administration are linked. These administrative data are also combined with survey data. In addition, linked employer-employee data allow simultaneous analyses of the supply and demand sides of the labour market.<br> The data can be linked using unique identifiers, such as social insurance number, client number of the local employment agency, or establishment number. Since the foundation of the German Record Linkage Center (GRLC) in 2011, the RDC-IAB also applies methods for linking with non-unique and error-prone linkage identifiers like names, addresses and birth dates.<br> German data protection law classifies the data offered by the RDC-IAB as highly sensitive and strictly regulates their use by external researchers. The RDC-IAB has therefore established various data access modes. Although the data can be transferred directly to research institutions in anonymised form, this procedure is generally not effective for linked data, as the loss of information due to the necessary anonymisation would be too great. For this reason, the RDC-IAB focuses on the access modes on-site use and remote data execution. In cooperation with other data centres, RDC-IAB has therefore established on-site data access at currently 16 locations worldwide." (Author's abstract, IAB-Doku) ((en))

Cite article

Antoni, M. & Schmucker, A. (2019): The Research Data Centre of the German Federal Employment Agency at the Institute for Employment Research (RDC-IAB). Linked Microdata for Labour Market Research. In: International Journal of Population Data Science, Vol. 4, No. 2, p. 1-10. DOI:10.23889/ijpds.v4i2.1141