SOEP Research: Survey Methodology and Data Science

Publishing Fine-Grained Standardized Metadata: Lessons Learned from Three Research Data Centers

FAIRness of research data, meaning that data are managed according to the principles of being Findable, Accessible, Interoperable, and Reusable, has become a ubiquitous requirement in research data policies as well as in general guidelines for research data management. Meeting this requirement largely depends on the availability of rich and standardized DDI metadata—based on the Data Documentation ...

Measurement error models on anonymized georeferenced data

Georeferenced data are often anonymized for data protection reasons. This is done either by aggregating the data into larger spatial units (e.g., higher-level administrative units or grids with larger cell sizes) or by using stochastic methods to deliberately overlay the original coordinates. These methods significantly distort the data and associated variables, making further modeling steps...

Methodological Challenges in Cross-Cohort Comparisons of Educational Achievement

Comparisons of educational achievement across cohorts are frequently used to examine changes in educational performance and to evaluate the impact of societal or educational events, such as the COVID-19 pandemic. However, drawing causal inferences from observational data without strong experimental control remains challenging, as often no single clear methodological approach is universally...

Filling in the Blanks: Augmenting Survey Data Imputation with an External Prior

Multiple imputation of missing values in survey data analysis is a state-of-the-art technique. Typically, methods like multivariate imputation by chained equations (mice, van Buuren 2018) are employed, replacing missing values on a variable-by-variable basis. Generally, the information used for imputation comes from the survey dataset being analysed. Valid analysis results are achieved when the...

Intragenerational Mobility in Wealth in Germany, Norway, and Britain: Descriptive Evidence

We study intragenerational wealth rank mobility, investigating three dimensions: (i) wealth mobility over the life cycle, (ii) heterogeneity in mobility among subgroups and wealth components, and (iii) commonalities and differences across divergent country contexts. We use data from Germany (SOEP, N= 12,380 individuals), Norway (administrative register data, N=3,460,602), and Britain (BHPS, N=7,910; ...

Register now for the online workshop series SOEPcampus: Learn to use the SOEP over lunch

In November our online over lunch seminar series returns with one last workshop this year. The workshop provides a comprehensive, practical introduction to the data of the Socio-economic Panel (SOEP) on three Wednesdays during lunchtime. Participants will learn about the study's content, data structure, sample selection, and weighting strategy, along with an overview of the study documentation. To ...

The Bias in Pseudo-Event Studies

Pseudo-event studies promise to overcome the limited availability of panel data by estimating event-study effects from widely available cross-sectional data. Originally developed and increasingly used for child penalty estimation, the approach has been proposed for broader applications. We show that pseudo-event study estimates are systematically biased for both pre-trends and treatment effects...

Reproducible workflows in scholarly communication with CODECHECK

CODECHECK (https://codecheck.org.uk/) provides an approach for independent execution of computations underlying research articles. At one point during the publication process, one reviewer - the codechecker - certifies that they were able to execute relevant parts of a computational workflow. This certificate becomes part of the public record. With over 130 certificates contributed by over 60...

SOEP Annual Report 2025

Learn to use the SOEP over lunch

The German Socio-Economic Panel Study is a representative panel study for the German population, collecting data on a broad variety of topics of everyday life, including general well-being, household composition, educational aspirations and educational status, income and occupational biographies, leisure time activities, housing, health, political orientation and more. With its long-running panel...