Examining the structure of spatial health effects using hierarchical Bayes models : conference paper

This paper makes use of Hierarchical Bayes Models to model and estimate spatial health effects. We focus on Germany, combining rich individual-level household panel data with administrative county level information to estimate spatial county-level health dependencies. As dependent variable, we use the generic, continuous, and quasi-objective SF12 health measure. Our findings reveal strong and highly significant spatial dependencies and clusters. The strong and systematic county-level impact is comparable to an age effect on health of up to 31 years. Even 20 years after the peaceful German reunification, we detect a clear spatial East-West health pattern that equals an age impact on health of up to 9 life years.