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Mortality modeling: Lee-Carter and the macroeconomy

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  • Katja Hanewald

Abstract

Using data for six OECD countries, this paper studies the effect of macroeconomic conditions on the mortality index kt in the well-known Lee-Carter model. Significant correlations are found with real GDP growth rates in Australia, Canada, and the United States, and with unemployment rate changes in Japan, for the period 1950–2005. In recent years, the relationship between the state of the economy and mortality is found to change from procyclical to countercyclical in all six countries. Based on these findings, variants of the Lee-Carter model are proposed that capture a substantial fraction of the variation in the mortality index.

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Bibliographic Info

Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2009-008.

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Length: 24 pages
Date of creation: Jan 2009
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2009-008

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Keywords: Demography; Lee-Carter; business cycle; time series model;

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References

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  1. Ronald Lee & Timothy Miller, 2001. "Evaluating the performance of the lee-carter method for forecasting mortality," Demography, Springer, vol. 38(4), pages 537-549, November.
  2. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
  3. Debón, A. & Montes, F. & Puig, F., 2008. "Modelling and forecasting mortality in Spain," European Journal of Operational Research, Elsevier, vol. 189(3), pages 624-637, September.
  4. Heather Booth & Rob J Hyndman & Leonie Tickle & Piet de Jong, 2006. "Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions," Monash Econometrics and Business Statistics Working Papers 13/06, Monash University, Department of Econometrics and Business Statistics.
  5. Gerdtham, Ulf-G. & Ruhm, Christopher J., 2002. "Deaths Rise in Good Economic Times: Evidence From the OECD," IZA Discussion Papers 654, Institute for the Study of Labor (IZA).
  6. Wolfgang Reichmuth & Samad Sarferaz, 2008. "Modeling and Forecasting Age-Specific Mortality: A Bayesian Approach," SFB 649 Discussion Papers SFB649DP2008-052a, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  7. Hári, Norbert & De Waegenaere, Anja & Melenberg, Bertrand & Nijman, Theo E., 2008. "Estimating the term structure of mortality," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 492-504, April.
  8. José Tapia granados, 2008. "Macroeconomic fluctuations and mortality in postwar Japan," Demography, Springer, vol. 45(2), pages 323-343, May.
  9. Katja Hanewald, 2008. "Beyond the business cycle - factors driving aggregate mortality rates," SFB 649 Discussion Papers SFB649DP2008-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  10. Neumayer, Eric, 2004. "Recessions lower (some) mortality rates:: evidence from Germany," Social Science & Medicine, Elsevier, vol. 58(6), pages 1037-1047, March.
  11. Christopher J. Ruhm, 2000. "Are Recessions Good For Your Health?," The Quarterly Journal of Economics, MIT Press, vol. 115(2), pages 617-650, May.
  12. Renshaw, A.E. & Haberman, S., 2006. "A cohort-based extension to the Lee-Carter model for mortality reduction factors," Insurance: Mathematics and Economics, Elsevier, vol. 38(3), pages 556-570, June.
  13. Brouhns, Natacha & Denuit, Michel & Vermunt, Jeroen K., 2002. "A Poisson log-bilinear regression approach to the construction of projected lifetables," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 373-393, December.
  14. Tapia Granados, José A. & Ionides, Edward L., 2008. "The reversal of the relation between economic growth and health progress: Sweden in the 19th and 20th centuries," Journal of Health Economics, Elsevier, vol. 27(3), pages 544-563, May.
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Citations

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Cited by:
  1. Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  2. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  3. T. Paul Schultz, 2009. "Population and Health Policies," Working Papers 974, Economic Growth Center, Yale University.
  4. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  5. Dowd, Kevin & Cairns, Andrew J.G. & Blake, David & Coughlan, Guy D. & Epstein, David & Khalaf-Allah, Marwa, 2010. "Evaluating the goodness of fit of stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 47(3), pages 255-265, December.
  6. Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.

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