Examining the Structure of Spatial Health Effects using Hierarchical Bayes Models

Peter Eibich and Nicolas Ziebarth ()

VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order from Verein für Socialpolitik / German Economic Association

Abstract: 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.

JEL-codes: C11 C21 I18 (search for similar items in EconPapers)
Date: 2013
New Economics Papers: this item is included in nep-geo and nep-hea
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:vfsc13:79844

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