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...

Using SOEP panel data and difference-in-differences methods, this study is the first to empirically evaluate the effectiveness of four different health care cost containment measures within an integrated framework. The four measures investigated were introduced in Germany in 1997 to reduce moral...