Explaining political participation: A comparison of real and falsified survey data

Abstract

This paper examines differences between real survey data and data falsified by interviewers. Previous studies show that there are only small differences between real and falsified data which implies that falsifying interviewers are able to (re-)produce realistic frequency distributions. The question this paper aims to answer is whether they are also able to produce multivariate results in accordance with the assumptions of established social science approaches. As an example for a realistic theory-driven data analysis, real and falsified data are compared in terms of the identified determinants of political participation. I use an experimental data set with data partly collected in real interviews and partly by interviewers being instructed to falsify; that is, to fill in the questionnaire based on little information about the respondent. The questionnaire measures twelve political activities, based on which I calculate an index for political participation. There are differences in the models between the real and the falsified data: The explained variances are higher in the regression models of the falsified data. There are some variables significant in both data sets and some that are significant only in the real or in the falsified data. These differences can be explained by our theoretical assumptions.