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Factors driving aggregate mortality rates in postwar Germany

  • Katja HanewaldEmail author
Abhandlung

Abstract

Using German data over the period 1956–2006, this study provides a comprehensive empirical analysis of factors driving aggregate mortality rates over time. It differs from previous contributions in this field by simultaneously considering an extensive set of macroeconomic, socioeconomic, and ecological factors as explanatory variables. Our regression analysis shows that sex- and age-specific mortality rates vary substantially in their response to external factors. Strongest associations are found with changes in real GDP, flu epidemics, and the two lifestyle variables—alcohol and cigarette consumption—in both univariate and multivariate setups. Further analysis indicates that these effects are primarily contemporary, whereas other indicators, such as weather conditions, exert lagged effects. We derive optimal multivariate models for every age group that provide a good fit to the observed variation in annual mortality rates, and thereby confirm the relevance of the identified factors.

Keywords

Cigarette Consumption German Federal Statistical Public Health Expenditure Monthly Earning German Reunification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Zusammenfassung

Basierend auf deutschen Daten für den Zeitraum 1956–2006 wird der Einfluss externer Faktoren auf aggregierte Sterberaten untersucht. Dafür wird erstmalig eine umfassende Zusammenstellung von makroökonomischen, sozioökonomischen und ökologischen Faktoren gleichzeitig betrachtet. Die Regressionsergebnisse zeigen, dass geschlechts- und altersspezifische Sterberaten sehr unterschiedlich auf externe Einflussfaktoren reagieren. Als wichtigste Faktoren werden Schwankungen im realen Wirtschaftswachstum, Grippewellen, sowie die beiden “Lifestyle”-Indikatoren Alkohol- und Zigarettenkonsum identifiziert. Diese Effekte treten hauptsächlich im selben Jahr auf, während bei anderen Faktoren, wie zum Beispiel bei extremen Wetterbedingungen, verzögerte Reaktionen der Sterberaten beobachtet werden. Für jede Altersgruppe werden optimale multivariate Modelle bestimmt, die die beobachtete Variation in den Daten gut erklären und somit die Bedeutung der identifizierten Faktoren bestätigen.

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Dr. Wolfgang Schieren-Lehrstuhl für Versicherungs- und RisikomanagementHumboldt-Universität zu BerlinBerlinGermany

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