The Mannheim Corona Study (MCS) is a project of the German Internet Panel that examines the social changes caused by the Corona pandemic in Germany. The MCS is divided into three stages:
In the data collection phase of the Mannheim Corona Study, approximately 3,600 participants of the German Internet Panel (GIP) were interviewed every week from 20 March to 10 July 2020 about how their lives have changed since the Corona crisis. We examined socio-economic aspects (e.g. childcare, work situations, and disposable income) as well as the influence of political measures on social interactions, fears and the social acceptance of measures to contain the pandemic. The study participants were evenly distributed over the days of the week so that we gained daily insights into the developments of the population.
The data collected during the 16 weeks of the MCS are the basis for the second phase, in which we conduct detailed analyses and draw further conclusions about the effects of the pandemic in Germany. As the Mannheim Corona Study is a panel study that builds on an existing long-term study, this allows us to compare life in Germany before and since the outbreak. The interviewed panel members have regularly participated in our study for at least 18 months; some participants have been part of the GIP for 8 years already.
By integrating the MCS into the ongoing data collection of the GIP, the long-term consequences of the Corona pandemic for Germany can also be investigated in the third phase of the study.
The random sample of the GIP from the registers of the residents' registration offices throughout Germany and our two-stage weighting procedure allows the Mannheim Corona Study to draw conclusions about the general population in Germany. In contrast to many short-term studies that rely on commercial online respondent pools, the representativeness of the Mannheim Corona Study is statistically supported.
On this website you can access the results and publications of the MCS.
The Mannheim Corona Study is based on the methodology and infrastructure of the German Internet Panel (GIP). Like the GIP, the Mannheim Corona Study is led by Prof. Dr. Blom and conducted by the GIP team. The questionnaires are developed together with the researchers at the Collaborative Research Center (SFB) 884 “Political Economy of Reforms”.
The sample of the Mannheim Corona Study was divided into eight random sub-samples. The sub-samples 1-7 were assigned to a specific day of the week, while the eighth sub-sample served as control group and was not surveyed for the Corona Study.
On each day of the week one of the sub-samples received an email invitation to the day’s survey. Contacted panel members had 48 hours to participate. However, they were encouraged to take part on the day of the week that they were assigned to, i.e. within the first 24 hours.
Results for each day are analyzed together, i.e. persons who responded directly on the first day (e.g. Monday) are included in the analysis of that specific day (Monday). Answers of respondents who participated on the day after (Tuesday) are analyzed together with the answers on that day of the next sub-sample. In this way, we minimize biases, because every daily analysis includes both early as well as late respondents.
Within one week, the questionnaire remains exactly the same for all participants. Across weeks, we also aimed to keep the questionnaires constant to allow for a daily continuation of our time series for a long time. However, to conduct in-depth analyses of selected topics and to react to unforeseen events, the questionnaire was evaluated and updated every week.
The Mannheim Corona Study conducts research on the following topics:
Please find all questionnaires here (original version in German).
Weighting and Representativeness
No serious academic study in the field of social and economic research will generally claim to be representative of the population. While commercial research institutes tend to emphasize their representativeness, academia usually tries to avoid the use of this term.
Of course, high-quality academic studies go through great lengths to come as close as possible to ideal of representativeness. To this end, researchers use random samples, elaborate fieldwork procedures, and scientific weighting algorithms to represent the general population as closely as possible across a variety of population statistics. The Mannheim Corona Study in the German Internet Panel is also committed to this professional ethos.
For general information on the GIP sampling strategy and its implementation, please visit our methodology page.
The analyses conducted with the Mannheim Corona Study are weighted with a carefully calculated weight. For this purpose, we carried out a two-stage weighting procedure:
In the first stage, we calculated a response propensity weight, which projects the characteristics of the Corona Study participants to the general GIP study. This included two characteristics: employment and occupational sector.
In the second stage, a raking weight was estimated. This raking weight extrapolated the characteristics of Corona Study participants to those of the general population of Germany (based on the German Mikrozensus). The following characteristics informed the raking procedure: age, gender, marital status, highest level of education, household size, and federal state.
A chained equation algorithm imputed missing values in the weighting variables. The final weight was trimmed for values > 4 and values < 1/4.
More Information on the Methodology of the GIP
can be found here.
The Mannheim Corona Study is conducted within the GIP at the Collaborative Research Center (SFB) 884 “Political Economy of Reforms” and funded by the German Research Foundation (DFG). All researchers involved are part of the SFB 884 and mostly funded by the DFG. Neither the Mannheim Corona Study nor the GIP pursue economic or political interests of any kind.
The Mannheim Corona Study is supported by the Collaborative Research Center (SFB) 884 “Political Economy of Reforms”. The following researchers have particularly contributed to it:
Prof. Dr. Katja Möhring, Project Head at the SFB 884 and Professor for Macrosociology
Dr. Elias Naumann, Postdoc at SFB 884 and JFK Memorial Fellow at Harvard University
Maximiliane Reifenscheid, Doctoral Candidate at SFB 884
Methodology and Implementation:
Tobias Rettig, Doctoral Candidate at SFB 884
Dr. Alexander Wenz, Associate at SFB 884 and Postdoc at the University of Mannheim
Marina Fikel, Researcher at SFB 884
Dr. Carina Cornesse, Postdoc at SFB 884
Sabine Friedel, Researcher at SFB 884
Julian Axenfeld, Doctoral Candidate at MZES
and the student assistants of the GIP Marie-Lou Sohnius, Lisa Wellinghoff, Sabrina Seidl, Elena Madiai, Julia Kozilek, Nourhan Elsayed, Lisa Jäckel, Julia Schwab, and Katja Sonntag
With the Support of the SFB Board:
Prof. Dr. Thomas König, Spokesperson of the SFB 884 and Professor for European Studies
Prof. Dr. Markus Frölich, Deputy Spokesperson of the SFB 884 and Professor for Econometrics
Prof. Dr. Annelies Blom, Director of the GIP und Professor for Data Science
Dr. Christian Bruns, Research Fellow at SFB 884
Prof. Dr. Friedrich Heinemann, Project Head at SFB 884 and Research Manager at ZEW