Examining the structure of spatial health effects in Germany using Hierarchical Bayes Models

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 g...

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Bibliographic details
Volume:	49
Main Author:	Eibich, Peter Ziebarth, Nicolas R
Format:	Journal Article
Language:	English
Zielgruppe:	Academic
Place of publication:	AMSTERDAM Elsevier B.V 01.11.2014 ELSEVIER DIW
published in:	Regional science and urban economics Vol. 49; pp. 305 - 320
ORCID:	0000-0003-3562-2371
Data of publication:	November 2014
ISSN:	0166-0462 1879-2308
EISSN:	1879-2308
Classification Codes:
Dewey Decimal Classification:	330
Discipline:	Economics Sociology & Social History
Subjects:	Hierarchical Bayes Models SOEP Spatial health effects SF12 Germany Economics Environmental Studies Social Sciences Life Sciences & Biomedicine Urban Studies Business & Economics Environmental Sciences & Ecology Science & Technology Statistische Methode Panel Spatial health effects,Hierarchical Bayes Models,Germany,SOEP,SF12 Gesundheitswesen Gesundheitspolitik Spatial health effects, Hierarchical Bayes Models, Germany, SOEP, SF12 Hierarchical Bayes Models SOEP I18 Spatial health effects SF12 C11 C21 I12 I14 Germany MORTALITY REGIONAL DIFFERENCES RISK-FACTORS PATTERNS EXPENDITURE EAST-GERMANY IMPACT AVOIDABLE CANCER DEATHS NEIGHBORHOOD DEPRIVATION SOCIOECONOMIC-STATUS
Online Access:	available in Bonn?
Database:	Social Sciences Citation Index Web of Science - Social Sciences Citation Index - 2014 Web of Knowledge Web of Science CrossRef Academic OneFile (A&I only) OpenAIRE OpenAIRE (Open Access) Database information Databases - DBIS