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Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models

SOEPpapers 620, 44 S.

Peter Eibich, Nicolas R. Ziebarth


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Published in: Regional Science and Urban Economics 49 (2014), 305-320


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 the generic, continuous, and quasi-objective SF12 health measure. We find strong and highly significant spatial dependencies and clusters. The strong and systematic county-level impact is equivalent to 0.35 standard deviations in health. Even 20 years after German reunification, we detect a clear spatial East-West health pattern that equals an age impact on health of up to 5 life years for a 40-year old.

JEL-Classification: C21;C11;I12;I14;I18
Keywords: Spatial health effects, Hierarchical Bayes Models, Germany, SOEP, SF12
Frei zugängliche Version: (econstor)