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Beyond the business cycle - factors driving aggregate mortality rates

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  • Katja Hanewald

Abstract

This article provides a comprehensive econometric analysis of factors driving aggregate mortality rates over time. It differs from previous studies in this field by simultaneously considering an extensive set of macroeconomic, socio-economic and ecological factors as explanatory variables. Germany is chosen as an indicative example for other industrialized countries due to its advanced demographic transition process. Our regression analysis, which covers the time interval 1956-2004, indicates 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 life style variables alcohol and cigarette consumption in both univariate and multivariate setups. Further analysis shows that these effects are primarily contemporary, while other indicators such as weather conditions exert lagged effects. By combining variables in a multivariate model the share of explained data volatility can be substantially increased.

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Bibliographic Info

Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2008-031.

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Length: 34 pages
Date of creation: Apr 2008
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2008-031

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Keywords: Aggregate mortality; business cycle; socio-economic factors; multivariate model;

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References

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  1. Christopher J. Ruhm, 2000. "Are Recessions Good For Your Health?," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 115(2), pages 617-650, May.
  2. Gerard J. van den Berg & Maarten Lindeboom & France Portrait, 2006. "Economic Conditions Early in Life and Individual Mortality," American Economic Review, American Economic Association, vol. 96(1), pages 290-302, March.
  3. Neumayer, Eric, 2004. "Recessions lower (some) mortality rates:: evidence from Germany," Social Science & Medicine, Elsevier, vol. 58(6), pages 1037-1047, March.
  4. Hugh Gravelle & John Wildman & Matthew Sutton, . "Income, Income Inequality and Health: What can we Learn from Aggregate Data?," Discussion Papers 00/26, Department of Economics, University of York.
  5. Olivier Desch�nes & Enrico Moretti, 2009. "Extreme Weather Events, Mortality, and Migration," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 659-681, November.
  6. Eric Stallard, 2006. "Demographic Issues in Longevity Risk Analysis," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(4), pages 575-609.
  7. Leigh, Andrew & Jencks, Christopher, 2006. "Inequality and Mortality: Long-Run Evidence from a Panel of Countries," Working Paper Series rwp06-032, Harvard University, John F. Kennedy School of Government.
  8. Ulf-G. Gerdtham & Christopher J. Ruhm, 2002. "Deaths Rise in Good Economic Times: Evidence From the OECD," NBER Working Papers 9357, National Bureau of Economic Research, Inc.
  9. Axel H. Boersch-Supan & Joachim K. Winter, 2001. "Population Aging, Savings Behavior and Capital Markets," NBER Working Papers 8561, National Bureau of Economic Research, Inc.
  10. Yan, Yuk Yee, 2000. "The influence of weather on human mortality in Hong Kong," Social Science & Medicine, Elsevier, vol. 50(3), pages 419-427, February.
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Cited by:
  1. Katja Hanewald & Thomas Post & Helmut Gründl, 2009. "Stochastic Mortality, Macroeconomic Risks, and Life Insurer Solvency," SFB 649 Discussion Papers SFB649DP2009-015, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  2. Wolfgang H. Reichmuth & Samad Sarferaz, 2008. "The Influence of the Business Cycle on Mortality," SFB 649 Discussion Papers SFB649DP2008-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  3. Katja Hanewald, 2009. "Mortality modeling: Lee-Carter and the macroeconomy," SFB 649 Discussion Papers SFB649DP2009-008, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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