The health risks of the current COVID-19 pandemic, together with the drastic mitigation measures taken in many affected nations, pose an obvious threat to public mental health. The social science literature has already established a clear link between mental health and sociodemographic as well...

The health risks of the current COVID-19 pandemic, together with the drastic mitigation measures taken in many affected nations, pose an obvious threat to public mental health. The social science literature has already established a clear link between mental health and sociodemographic as well...

This paper exploits rich SOEP microdata to analyze state-level variation in health care utilization in Germany. Unlike most studies in the field of the Small Area Variation (SAV) literature, our approach allows us to net out a large array of individual-level and state-level factors that may...

This paper uses Hierarchical Bayes Models to model and estimate spatial health effects in Germany. We combine rich individual-level household panel data from the German SOEP with administrative county-level data to estimate spatial county-level health dependencies. As dependent variable we use...

This paper exploits rich SOEP microdata to analyze state-level variation in health care utilization in Germany. Unlike most studies in the field of the Small Area Variation (SAV) literature, our approach allows us to net out a large array of individual-level and state-level factors that may...

This paper exploits rich SOEP microdata to analyze state-level variation in health care utilization in Germany. Unlike most studies in the field of the Small Area Variation (SAV) literature,our approach allows us to net out a large array of individual-level and state-level factors that may...

This paper uses Hierarchical Bayes Models to model and estimate spatial health effects in Germany. We combine rich individual-level household panel data from the German SOEP with administrative county-level data to estimate spatial county-level health dependencies. As dependent variable we use...

This paper exploits rich SOEP microdata to analyze state-level variation in health care utilization in Germany. Unlike most studies in the field of the Small Area Variation (SAV) literature, our approach allows us to net out a large array of individual-level and state-level factors that may...

This paper exploits rich SOEP microdata to analyze state-level variation in health care utilization in Germany. Unlike most studies in the field of the Small Area Variation (SAV) literature, our approach allows us to net out a large array of individual-level and state-level factors that may...

This paper uses Hierarchical Bayes Models to model and estimate spatial health effects in Germany. We combine rich individual-level household panel data from the German SOEP with administrative county-level data to estimate spatial county-level health dependencies. As dependent variable we use...