Establishing infrastructure for the use of big data to understand total survey error

Abstract

"In the past couple of years, the demand for administrative data, commercial data, and other large data sources in social sciences has increased tremendously. Especially in survey operations, administrative data are considered a highly valuable resource to mitigate errors in the survey process and empirical analyses. The Institute for Employment Research (IAB) of the German Federal Employment Agency (BA), for instance, conducts large-scale national surveys of individuals, households, and establishments - often in combination with interviewer observations and other paradata. In addition, the IAB holds labor market data collected from administrative records, which consist of employer notifications to social security and information about unemployment benefits or welfare receipts claimed at agencies of the BA. These data comprise about 86% of the German labor force and can be linked to the survey data if respondents provide informed consent to data linkage." (Text excerpt, IAB-Doku) ((en))

Cite article

Kirchner, A., Hochfellner, D. & Bender, S. (2017): Establishing infrastructure for the use of big data to understand total survey error. Examples from four survey research organizations. Part 1: Big data infrastructure at the Institute for Employment Research. In: P. P. Biemer, E. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L. E. Lyberg, N. C. Tucker & B. T. West (Hrsg.) (2017): Total survey error in practice, p. 458-466.