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© 2014 Elsevier B.V. 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.

Original publication

DOI

10.1016/j.regsciurbeco.2014.06.005

Type

Journal article

Journal

Regional Science and Urban Economics

Publication Date

01/11/2014

Volume

49

Pages

305 - 320