Abstract

Falsified Interviews can have a substantial impact on survey data quality and can lead to population estimates that are seriously biased. Especially in the context of policy research, unidentified falsification can be problematic since the falsified data might produce results that lead to a misallocation of public funds. Within different projects, we were able to develop new and evaluate known statistical identification approaches. These efficient and cost-effective quality control strategies will now be implemented for the Panel Study "Labour Market and Social Security" (PASS).