Automatic Identification of Faked and Fraudulent Interviews in Surveys by Two Different Methods

This paper presents two new tools for the identification of faking interviewers in surveys. One method is based on Benford's Law, and the other exploits the empirical observation that fakers most often produce answers with less variability than could be expected from the whole survey. We focus on fabricated data, which were taken out of the survey before the data were disseminated in the German Socio-Economic Panel (SOEP). For two samples, the resulting rankings of the interviewers with respect to their cheating behavior are given. For both methods all of the evident fakers are identified.