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Modelling and forecasting mortality in Spain

  • Debón, A.
  • Montes, F.
  • Puig, F.
Registered author(s):

    Experience shows that static life tables overestimate death probabilities. As a consequence of this overestimation the premiums for annuities, pensions and life insurance are not what they actually should be, with negative effects for insurance companies or policy-holders. The reason for this overestimation is that static life tables, through being computed for a specific period of time, cannot take into account the decreasing mortality trend over time. Dynamic life tables overcome this problem by incorporating the influence of the calendar when graduating mortality. Recent papers on the topic look for the development of new methods to deal with this dynamism. Most methods used in dynamic tables are parametric, apply traditional mortality laws and then analyse the evolution of estimated parameters with time series techniques. Our contribution consists in extending and applying Lee-Carter methods to Spanish mortality data, exploring residuals and future trends.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(06)01173-8
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    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 189 (2008)
    Issue (Month): 3 (September)
    Pages: 624-637

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    Handle: RePEc:eee:ejores:v:189:y:2008:i:3:p:624-637
    Contact details of provider: Web page: http://www.elsevier.com/locate/eor

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    1. Lawrence R. Carter & Alexia Prskawetz, 2001. "Examining structural shifts in mortality using the Lee-Carter method," MPIDR Working Papers WP-2001-007, Max Planck Institute for Demographic Research, Rostock, Germany.
    2. Arthur Renshaw & Steven Haberman, 2003. "Lee-Carter mortality forecasting: a parallel generalized linear modelling approach for England and Wales mortality projections," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(1), pages 119-137.
    3. Renshaw, A. E. & Haberman, S., 2003. "Lee-Carter mortality forecasting with age-specific enhancement," Insurance: Mathematics and Economics, Elsevier, vol. 33(2), pages 255-272, October.
    4. 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.
    5. Pitacco, Ermanno, 2004. "Survival models in a dynamic context: a survey," Insurance: Mathematics and Economics, Elsevier, vol. 35(2), pages 279-298, October.
    6. Felipe, A. & Guillen, M. & Perez-Marin, A. M., 2002. "Recent Mortality Trends in the Spanish Population," British Actuarial Journal, Cambridge University Press, vol. 8(04), pages 757-786, October.
    7. Sithole, Terry Z. & Haberman, Steven & Verrall, Richard J., 2000. "An investigation into parametric models for mortality projections, with applications to immediate annuitants' and life office pensioners' data," Insurance: Mathematics and Economics, Elsevier, vol. 27(3), pages 285-312, December.
    8. Lee, Ronald & Rofman, Rafael, 1994. "Modelación y proyección de la mortalidad en Chile," Notas de Población, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), June.
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