Mixing Standardized Administrative Data and Survey Data With Qualitative Content Analysis in Longitudinal Designs: Perceptions of Justified Pensions and Related Life Courses

Abstract

Citizens are more likely to accept reforms of welfare state arrangements if they perceive them as just and reasonable. However, the concept of social justice is multidimensional. For instance, in discourses on old-age security, justice is addressed in terms of meritocratic principles, demands, processes, redistribution, gender, or intergenerational equity.

In the study "Lebensverläufe und Altersvorsorge" (LeA) [Life Courses and Old-Age Provision], respondents could express their wishes for retirement and the German statutory pension system in an open-ended question. We draw on this study to illustrate who addresses which social justice dimensions and how. Methodologically, we mixed standardized administrative and survey data with qualitative content analysis.

More generally, we aim to highlight the rich analytical potential and challenges of open-ended questions. We reflect on methodological issues, e.g., the time-consuming preparation and interpretation of an enormous amount of non-standardized data, the interview situation compared to conventional qualitative interviews as well as interpretation difficulties due to missing contextual information. Furthermore, we prepared the open-ended question for quantitative analysis and integrated it into the data set while preserving its qualitative character. Finally, to illustrate options for joint analyses, we combined content analysis results with sequence/cluster analysis for longitudinal quantitative data.