200
Views
1
CrossRef citations to date
0
Altmetric
Longevity 13 Articles

A Synthesis Mortality Model for the Elderly

&

REFERENCES

  • Ahcan, A., D. Medved, A. Olivieri, and E. Pitacco. 2014. Forecasting mortality for small populations by mixing mortality data. Insurance: Mathematics and Economics 54:12–27.
  • Akaike, H. 1973. Information theory and an extension of the maximum likelihood principle. In Proceedings of the Second International Symposium on Information Theory, ed. B. N. Petrov and F. Csaki, 267–81. Budapest, Hungary: Akademiai Kiado.
  • Bohk-Ewald, C., and R. Rau. 2017. Probabilistic mortality forecasting with varying age specific survival improvements. Genus 73 (1):1–37.
  • Bőrger, M., and J. Schupp. 2018. Modeling trend processes in parametric mortality models. Insurance: Mathematics and Economics 78:369–80.
  • Brouhns, N., M. Denuit, and J. K. Vermunt. 2002. A Poisson log-bilinear regression approach to the construction of projected lifetables. Insurance: Mathematics and Economics 31:373–93.
  • Brown, R. L. 1993. Introduction to the mathematics of demography, 2nd ed. New Hartford, CT: ACTEX.
  • Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: A practical information-theoretic approach, 2nd ed. New York: Springer-Verlag.
  • Cadena, M., and M. Denuit. 2016. Semi-parametric accelerated hazard relational models with applications to mortality projections. Insurance: Mathematics and Economics 68:1–16.
  • Cairns, A. J. G., D. Blake, and K. Dowd. 2006. A two-factor model for stochastic mortality with parameter uncertainty: Theory and calibration. Journal of Risk and Insurance 73:687–718.
  • Cairns, A. J. G., D. Blake, K. Dowd, G. D. Coughlan, D. Epstein, A. Ong, and I. Balevich. 2009. A quantitative comparison of stochastic mortality models using data from England and Wales and the United States. North American Actuarial Journal 13:1–35.
  • Carnes, B. A., S. J. Olshansky, and D. Grahn. 2003. Discussed biological evidence for limits to the duration of life. Biogeography 4 (1):31–45.
  • Chen, H., and S. H. Cox. 2009. Modeling mortality with jumps: Applications to mortality securitization. Journal of Risk and Insurance 76:727–51.
  • Coale, A., and E. E. Kisker. 1990. Defects in data on old-age mortality in the United States: New procedures for calculating mortality schedules and life tables at the highest ages. Asian and Pacific Population Forum 4 (1):1–31.
  • Cox, S. H., Y. Lin, and H. Pedersen. 2010. Mortality risk modeling: Applications to insurance securitization. Insurance: Mathematics and Economics 46:242–53.
  • Dowd, K., A. J. G. Cairns, D. Blake, G. D. Coughlan, D. Epstein, and M. Khalaf-Allah. 2010. Backtesting stochastic mortality models: An ex post evaluation of multiperiod-ahead density forecasts. North American Actuarial Journal 14:281–98.
  • Haberman, S., and A. Renshaw. 2009. On age-period-cohort parametric mortality rate projections. Insurance: Mathematics and Economics 45:255–270.
  • Kannisto, V. 1994. Development of oldest-old mortality, 1950–1990: Evidence from 28 developed countries. Odense Monographs on Population Aging, vol. 1. Odense, Denmark: Odense University Press.
  • Kannisto, V., J. Lauritsen, A. R. Thatcher, and J. W. Vaupel. 1994. Reductions in mortality at advanced ages: Several decades of evidence from 27 countries. Population and Development Review 20 (4):793–810.
  • Lee, R. D., and L. R. Carter. 1992. Modeling and forecasting U.S. mortality. Journal of the American Statistical Association 87 (419):659–71.
  • Lee, W. 2003. A partial SMR approach to smoothing age-specific rates. Annuals of Epidemiology, 13 (2):89–99.
  • Li, J. S.-H., M. R. Hardy, and K. S. Tan. 2009. Uncertainty in mortality forecasting: An extension to the classical Lee-Carter approach. Astin Bulletin 39:137–64.
  • Li, J. S.-H., W. Chan, and S. Cheung. 2011. Structural changes in the Lee-Carter mortality indexes: Detection and implications. North American Actuarial Journal 15:13–31.
  • Mitchell, D., P. Brockett, R. Mendoza-Arriaga, and K. Muthuraman. 2013. Modeling and forecasting mortality rates. Insurance: Mathematics and Economics 52:275–85.
  • Renshaw, A. E., and S. Haberman. 2006. A cohort-based extension to the Lee-Carter model for mortality reduction factors. Insurance: Mathematics and Economics 38:556–70.
  • Perks, W. 1932. On some experiments in the graduation of mortality statistics. Journal of the Institute of Actuaries 63:12–40.
  • Preston, S. H., and A. Stokes. 2012. Sources of population aging in more and less developed countries. Population and Development Review 38 (2):221–36.
  • Terblanche, W. 2016. Retrospective testing of mortality forecasting methods for the projection of very elderly populations in Australia. Journal of Forecasting 35:703–17.
  • Thatcher, A. R., V. Kannisto, and J. W. Vaupel. 1999. The force of mortality at ages 80 to 120. Odense Monographs on Population Aging, vol. 5. Odense, Denmark: Odense University Press.
  • Thatcher, A. R., V. Kannisto, and K. Andreev. 2002. The survivor ratio method for estimating numbers at high ages. Demographic Research 6 (1):2–15.
  • Tsai, C. C. L., and S. Yang. 2015. A linear regression approach to modeling mortality rates of different forms. North American Actuarial Journal 19:1–23.
  • Tsai, C. C. L., and T. Lin. 2017. Incorporating the Bühlmann credibility into mortality models to improve forecasting performances. Scandinavian Actuarial Journal 2017 (5):419–40.
  • Van Berkum, F., K. Antonio, and M. Vellekoop. 2016. The impact of multiple structural changes on mortality predictions. Scandinavian Actuarial Journal 2016 (7):581–603.
  • Wang, H., C. J. Yue, and Y. Chen. 2016. A study of elderly mortality models. Journal of Population Studies 52:1–42.
  • Wang, H., C. J. Yue, and C. Chong. 2018. Mortality models and longevity risk for small populations. Insurance: Mathematics and Economics 78:351–59
  • Yue, C. J. 2002. Oldest-old mortality rates and the Gompertz law: A theoretical and empirical study based on four countries. Journal of Population Studies 24:33–57.
  • Yue, C. J. 2012. Mortality compression and longevity risk. North American Actuarial Journal 16 (4):434–48.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.