Covid-19 as an Accelerator of Social Inequality – Small-Scale Analyses with German Neighborhood Data

Tasks

In this project funded by the German Research Foundation, we seek to understand the role of disadvantaged neighborhoods with low average socio-economic status of their inhabitants in the context of the Covid-19 pandemic. Rigorous empirical evidence on social inequality and infection rates is still lacking, mainly because small area information below the district level is not comprehensively available. We aim to fill this gap by providing the corresponding empirical evidence and thereby adding to our understanding of the pandemic. Our results from this project can inform policy-makers for targeted interventions to overcome the current and future pandemics.

Methods

Our project involves three steps: First, we collect data on inner-city and inner-district infection rates and combine the data with rich information on housing and socio-economic status at the same regional level. We also collect data on the potential and take-up rate of working from home and on vaccine hesitancy. Second, we analyze these data with state-of-the-art methods to learn about the role of disadvantaged neighborhoods, the changing economic geography of cities, and to draw evidence-based policy recommendations. Third, we make as much as possible small-scale data available for future scientific research upon completion of the project.

We collaborate with researchers from the RWI Leibniz-Institute for Economic Research in Essen and the University of Paderborn as well as industry partners for data collection and provision.