American Journal of Theoretical and Applied Statistics

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Actuarial Analysis of Single Life Status and Multiple Life Statuses

Received: 12 April 2016    Accepted: 22 April 2016    Published: 10 May 2016
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Abstract

Actuaries frequently employ probability models to analyse situations involving uncertainty. They are also not simply interested in modelling the future states of a subject but also model cash flows associated with future states. This study compared single life status and multiple life statuses using life functions. The expected time until death, annuity payments, insurance payable and premiums were estimated using age as a risk factor. The analysis also employed the De Moirve’s law on mortality in estimating the rate of mortality. The analysis revealed that, the expected time until death for single life status and multiple life statuses are all increasing functions of age. It was realized also that, the premium for single life status was increasing with age and the same with multiple life statuses. But the premium for single life was higher than multiple life statuses. In the case of the multiple life statuses, it was revealed that, premium for joint life was higher than the last survivor and that a change in the interest rate or force of interest and the benefit did not changed the trend in premium payments.

DOI 10.11648/j.ajtas.20160503.17
Published in American Journal of Theoretical and Applied Statistics (Volume 5, Issue 3, May 2016)
Page(s) 123-131
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Single Life Status, Multiple Life Statuses, Annuity, Insurance and Premium

References
[1] Black K. Jr., and Skipper H. D. Jr., (1994). Life Insurance. Prentice-Hall, Inc.
[2] Carriere, J. F., & Chan, (1986). The bounds of bivariate distributions that limit the value of last-survivor annuities. Transactions of the Society of Actuaries, 38: 51-74.
[3] Carriere, J. F., (2000). Bivariate survival models for coupled lives. Scandinavian Actuarial Journal, 5: 17-31.
[4] Denuit, M., and Cornet, A. (1999). Multiple Premium Calculation with Dependent Future Lifetimes. Journal of Actuarial Practice Vol. 7.
[5] Denuit, M., and Teghem, S. (1998). “Measuring the Impact of a Dependence Among Insured Lifelengths”. Bulletin de 1’ Association Royale des Actuaries Belge: to appear.
[6] Denuit, M., Dhaene, J., Le Bailly de Tilleghem, C. & Teghem, S. (2001). Measuring the impact of dependence among insured life lengths. Belgian Actuarial Bulletin 3(1): 18-39.
[7] Dhaene, J., Vanneste, M. and Wolthuis, H. (2000). A note on dependencies in multiple life statuses. Mitteilungen der Schweizerisher Aktuarvereinigung, 4: 19-33.
[8] Frees, E.; Carriere, J.; and Valdez, E., (1996). Annuity Valuation with Dependent Mortality. Journal of Risk and Insurance. 63: 229-261.
[9] Heekyung Y., Arkady S., and Edwin H., (2002). A Re-examination of the Joint Mortality Functions. North American Actuarial Journal. 6(1): 166-170.
[10] Hurliman W., (2009). Actuarial analysis of the multiple life endowment insurance contract. Conference paper (January, 2009), available from Werner Hurliman, retrieved on 19 April 2016.
[11] Jagger C., and Sutton C. J., (1991). “Death After Marital Bereavement-Is the Risk Increased? Statistics in Medicine 10: 395-404.
[12] Norberg, R. (1989). Actuarial analysis of dependent lives. Mitteilungen derSchweiz. Vereinigung der Versicherungsmathematiker, 2: 243-255.
[13] Oakes, D. (1989). Bivariate survival models induced by frailties. J. Americ. Statist. Assoc. 84 (406): 487-493.
[14] Parkes C. M., Benjamin B., and Fitzgerald R. G., (1969). “Broken Heart”: A statistical Study of Increased Mortality among Widows. British Medical Journal 1: 740-743.
[15] Yang J., and Zhou S., (1991). “Joint-life status and Gompertz’s Law”. Mathematical Population Studies 5: 127-138.
[16] Youn, H., Shemyakin, A. & Herman, E. (2002). A re-examination of the joint life mortality functions. North American Actuarial Journal. 6: 166-170.
Author Information
  • Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

  • Department of Statistics, University for Development Studies, Navrongo, Ghana

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  • APA Style

    Abonongo John, Luguterah Albert. (2016). Actuarial Analysis of Single Life Status and Multiple Life Statuses. American Journal of Theoretical and Applied Statistics, 5(3), 123-131. https://doi.org/10.11648/j.ajtas.20160503.17

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    ACS Style

    Abonongo John; Luguterah Albert. Actuarial Analysis of Single Life Status and Multiple Life Statuses. Am. J. Theor. Appl. Stat. 2016, 5(3), 123-131. doi: 10.11648/j.ajtas.20160503.17

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    AMA Style

    Abonongo John, Luguterah Albert. Actuarial Analysis of Single Life Status and Multiple Life Statuses. Am J Theor Appl Stat. 2016;5(3):123-131. doi: 10.11648/j.ajtas.20160503.17

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  • @article{10.11648/j.ajtas.20160503.17,
      author = {Abonongo John and Luguterah Albert},
      title = {Actuarial Analysis of Single Life Status and Multiple Life Statuses},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {5},
      number = {3},
      pages = {123-131},
      doi = {10.11648/j.ajtas.20160503.17},
      url = {https://doi.org/10.11648/j.ajtas.20160503.17},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajtas.20160503.17},
      abstract = {Actuaries frequently employ probability models to analyse situations involving uncertainty. They are also not simply interested in modelling the future states of a subject but also model cash flows associated with future states. This study compared single life status and multiple life statuses using life functions. The expected time until death, annuity payments, insurance payable and premiums were estimated using age as a risk factor. The analysis also employed the De Moirve’s law on mortality in estimating the rate of mortality. The analysis revealed that, the expected time until death for single life status and multiple life statuses are all increasing functions of age. It was realized also that, the premium for single life status was increasing with age and the same with multiple life statuses. But the premium for single life was higher than multiple life statuses. In the case of the multiple life statuses, it was revealed that, premium for joint life was higher than the last survivor and that a change in the interest rate or force of interest and the benefit did not changed the trend in premium payments.},
     year = {2016}
    }
    

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    AB  - Actuaries frequently employ probability models to analyse situations involving uncertainty. They are also not simply interested in modelling the future states of a subject but also model cash flows associated with future states. This study compared single life status and multiple life statuses using life functions. The expected time until death, annuity payments, insurance payable and premiums were estimated using age as a risk factor. The analysis also employed the De Moirve’s law on mortality in estimating the rate of mortality. The analysis revealed that, the expected time until death for single life status and multiple life statuses are all increasing functions of age. It was realized also that, the premium for single life status was increasing with age and the same with multiple life statuses. But the premium for single life was higher than multiple life statuses. In the case of the multiple life statuses, it was revealed that, premium for joint life was higher than the last survivor and that a change in the interest rate or force of interest and the benefit did not changed the trend in premium payments.
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