IDEAS home Printed from https://ideas.repec.org/a/pal/gpprii/v49y2024i2d10.1057_s41288-024-00319-y.html
   My bibliography  Save this article

Frailty-based mortality models and reserving for longevity risk

Author

Listed:
  • Maria Carannante

    (University of Salerno)

  • Valeria D’amato

    (University of Salerno
    Sapienza University of Rome)

  • Steven Haberman

    (University of London)

  • Massimiliano Menzietti

    (University of Salerno)

Abstract

For the life insurance industry and pension schemes, mortality projections are critical for accurately managing exposure to longevity risk in terms of both premium setting and reserving. Frailty has been identified as an important latent factor underpinning the evolution of mortality rates. It represents the comorbidities that drive the deterioration of the human body’s physiological capacity. In this paper, we propose a stochastic mortality model that incorporates the trend in frailty, and we analyse the gap between the actuarial evaluations of premiums and technical provisions calculated under frailty-based and traditional stochastic mortality models. We observe that the frailty-based model leads to higher levels of uncertainty in estimates and projections (compared to a traditional stochastic mortality model), which is attributed to the explicit modelling of the comorbidities. This leads to proposing a potentially important policy-oriented recommendation: the incorporation of frailty in mortality modelling would allow for the profiling of mortality according to the portfolio in force for the insurer (or pension scheme), thereby mitigating the problem of adverse selection.

Suggested Citation

  • Maria Carannante & Valeria D’amato & Steven Haberman & Massimiliano Menzietti, 2024. "Frailty-based mortality models and reserving for longevity risk," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 320-339, April.
    • Handle: RePEc:pal:gpprii:v:49:y:2024:i:2:d:10.1057_s41288-024-00319-y
    DOI: 10.1057/s41288-024-00319-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41288-024-00319-y
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41288-024-00319-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, An & Guillen, Montserrat & Vigna, Elena, 2018. "Solvency Requirement In A Unisex Mortality Model," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1219-1243, September.
    2. Amy Finkelstein & James Poterba, 2004. "Adverse Selection in Insurance Markets: Policyholder Evidence from the U.K. Annuity Market," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 183-208, February.
    3. Franziska Tausch & Jan Potters & Arno Riedl, 2014. "An experimental investigation of risk sharing and adverse selection," Journal of Risk and Uncertainty, Springer, vol. 48(2), pages 167-186, April.
    4. Clemente, Gian Paolo & Della Corte, Francesco & Savelli, Nino, 2022. "A stochastic model for capital requirement assessment for mortality and longevity risk, focusing on idiosyncratic and trend components," Annals of Actuarial Science, Cambridge University Press, vol. 16(3), pages 527-546, November.
    5. Mengyi Xu & Michael Sherris & Ramona Meyricke, 2019. "Systematic Mortality Improvement Trends and Mortality Heterogeneity: Insights from Individual-Level HRS Data," North American Actuarial Journal, Taylor & Francis Journals, vol. 23(2), pages 197-219, April.
    6. Roozbeh Hosseini, 2015. "Adverse Selection in the Annuity Market and the Role for Social Security," Journal of Political Economy, University of Chicago Press, vol. 123(4), pages 941-984.
    7. Jan Walliser, 2000. "Adverse Selection in the Annuities Market and the Impact of Privatizing Social Security," Scandinavian Journal of Economics, Wiley Blackwell, vol. 102(3), pages 373-393, September.
    8. Su, Shu & Sherris, Michael, 2012. "Heterogeneity of Australian population mortality and implications for a viable life annuity market," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 322-332.
    9. Rothschild, Casey G., 2009. "Adverse selection in annuity markets: Evidence from the British Life Annuity Act of 1808," Journal of Public Economics, Elsevier, vol. 93(5-6), pages 776-784, June.
    10. Butt, Zoltan & Haberman, Steven, 2004. "Application of Frailty-Based Mortality Models Using Generalized Linear Models," ASTIN Bulletin, Cambridge University Press, vol. 34(1), pages 175-197, May.
    11. 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.
    12. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    13. Pitacco, Ermanno & Denuit, Michel & Haberman, Steven & Olivieri, Annamaria, 2009. "Modelling Longevity Dynamics for Pensions and Annuity Business," OUP Catalogue, Oxford University Press, number 9780199547272.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Annamaria Olivieri & Ermanno Pitacco, 2016. "Frailty and Risk Classification for Life Annuity Portfolios," Risks, MDPI, vol. 4(4), pages 1-23, October.
    2. Filipe Costa Souza & Wilton Bernardino & Silvio C. Patricio, 2024. "How life-table right-censoring affected the Brazilian social security factor: an application of the gamma-Gompertz-Makeham model," Journal of Population Research, Springer, vol. 41(3), pages 1-38, September.
    3. Cannon, Edmund & Tonks, Ian, 2016. "Cohort mortality risk or adverse selection in annuity markets?," Journal of Public Economics, Elsevier, vol. 141(C), pages 68-81.
    4. Jonas Šiaulys & Rokas Puišys, 2022. "Survival with Random Effect," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    5. Roozbeh Hosseini, 2015. "Adverse Selection in the Annuity Market and the Role for Social Security," Journal of Political Economy, University of Chicago Press, vol. 123(4), pages 941-984.
    6. Andrea Attar & Thomas Mariotti & François Salanié, 2021. "Entry-Proofness and Discriminatory Pricing under Adverse Selection," American Economic Review, American Economic Association, vol. 111(8), pages 2623-2659, August.
    7. Katrien Antonio & Anastasios Bardoutsos & Wilbert Ouburg, 2015. "Bayesian Poisson log-bilinear models for mortality projections with multiple populations," Working Papers Department of Accountancy, Finance and Insurance (AFI), Leuven 485564, KU Leuven, Faculty of Economics and Business (FEB), Department of Accountancy, Finance and Insurance (AFI), Leuven.
    8. Berdin, Elia, 2016. "Interest rate risk, longevity risk and the solvency of life insurers," ICIR Working Paper Series 23/16, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).
    9. D’Amato, Valeria & Haberman, Steven & Piscopo, Gabriella & Russolillo, Maria, 2012. "Modelling dependent data for longevity projections," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 694-701.
    10. David Blake & Marco Morales & Enrico Biffis & Yijia Lin & Andreas Milidonis, 2017. "Special Edition: Longevity 10 – The Tenth International Longevity Risk and Capital Markets Solutions Conference," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 515-532, April.
    11. Erin Cottle Hunt & Frank N. Caliendo, 2022. "Social security and risk sharing: A survey of four decades of economic analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 36(5), pages 1591-1609, December.
    12. Raj Chetty & Amy Finkelstein, 2012. "Social Insurance: Connecting Theory to Data," NBER Working Papers 18433, National Bureau of Economic Research, Inc.
    13. Homa Magdalena, 2020. "Mathematical Reserves vs Longevity Risk in Life Insurances," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(1), pages 23-38, March.
    14. Gastón Illanes & Manisha Padi, 2019. "Retirement Policy and Annuity Market Equilibria: Evidence from Chile," NBER Working Papers 26285, National Bureau of Economic Research, Inc.
    15. Bucher-Koenen, Tabea & Kluth, Sebastian, 2013. "Subjective Life Expectancy and Private Pensions," MEA discussion paper series 201214, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    16. Edwin Wong, 2015. "Marital bargaining in the demand for life insurance: evidence from the Health and Retirement Study," Review of Economics of the Household, Springer, vol. 13(2), pages 243-268, June.
    17. Bütler, Monika & Peijnenburg, Kim & Staubli, Stefan, 2017. "How much do means-tested benefits reduce the demand for annuities?," Journal of Pension Economics and Finance, Cambridge University Press, vol. 16(4), pages 419-449, October.
    18. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2023. "Thirty years on: A review of the Lee–Carter method for forecasting mortality," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1033-1049.
    19. Man Chung Fung & Gareth W. Peters & Pavel V. Shevchenko, 2016. "A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting," Papers 1605.09484, arXiv.org.
    20. Milevsky, Moshe A., 2020. "Swimming with wealthy sharks: longevity, volatility and the value of risk pooling," Journal of Pension Economics and Finance, Cambridge University Press, vol. 19(2), pages 217-246, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:gpprii:v:49:y:2024:i:2:d:10.1057_s41288-024-00319-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.