Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-10T16:42:32.815Z Has data issue: false hasContentIssue false
  • English
  • Français

Modelling the reverse select and ultimate mortality experience of UK ill-health retirement occupational pension scheme members

Published online by Cambridge University Press:  22 August 2016

Mary Hall  and
Linda Daly
Mary Hall*
Affiliation:
School of Mathematical Sciences, Dublin City University, Glasnevin, Dublin 9, Ireland
Linda Daly
Affiliation:
School of Mathematical Sciences, University College Cork, Western Road, Cork T12XY86, Ireland
*
*Correspondence to: Mary Hall, School of Mathematical Sciences, Dublin City University, Glasnevin, Dublin 9, DO9Y5NO Ireland. Tel: 01 7007012; Fax: 01 7005786; E-mail: mary.hall@dcu.ie
Get access Rights & Permissions [Opens in a new window]

Abstract

Retirements from the workforce can be split between those who are forced to retire early specifically for health reasons referred to as ill-health retirements and all other retirements referred to as normal-health retirements. Rates of ill-health retirement increase with age and are higher for females than males. Consequently, the mortality experience of ill-health retirement pensioners will become more important in the future as pension schemes increase their normal retirement age in line with increases in life expectancy and the proportion of women in the workforce and therefore in occupational pension schemes increases. This paper seeks to model the mortality of ill-health retirements from occupational pension schemes in the United Kingdom in the period immediately following retirement (reverse select mortality) and over the longer term (ultimate mortality) allowing for age at retirement. Females experience a longer reverse select period than males and for both males and females the improvement in mortality rates over the reverse select period is greatest at younger ages. Post the reverse select period the effect of age at retirement decreases over time with ultimate mortality rates converging by the mid-eighties for males and females.

Keywords

Ill-health retirement pensionersReverse select mortalityUltimate mortalityGeneralised additive models (GAMs)
Type
Papers
Information
Annals of Actuarial Science , Volume 10 , Issue 2 , September 2016 , pp. 222 - 235
Copyright
© Institute and Faculty of Actuaries 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

American Academy of Actuaries (2011). Selecting and documenting mortality assumptions for pensions. American Academy of Actuaries Pensions Committee, Washington.Google Scholar
Bloemen, H., Hochguertel, S. & Zweerink, J. (2013). The causal effect of retirement on mortality: evidence from targeted incentives to retire early. Discussion Paper No. 7570, IZA – Institute for the Study of Labour, Germany.Google Scholar
Booth, P., Chadburn, R., Cooper, D., Haberman, S. & James, D. (1998). Modern Actuarial Theory and Practice. CRC Press, Florida.Google Scholar
Brown, R.L. & Mc Daid, J. (2003). Factors affecting retirement mortality. North American Actuarial Journal, 7(2), 24–43.Google Scholar
Butt, Z. & Haberman, S. (2004). Application of frailty-based mortality models using generalized linear models. ASTIN Bulletin, 34(1), 175–197.Google Scholar
Claussen, B. & Dalgard, O. (2009). Disability pensioning: the gender divide can be explained by occupation, income, mental distress and health. Scandinavian Journal of Public Health, 37(6), 590–597.Google Scholar
Continuous Mortality Investigation (CMI) (2001). Continuous Mortality Investigation, Report No. 20, Institute and Faculty of Actuaries, UK.Google Scholar
Continuous Mortality Investigation (CMI) (2008 a). Continuous Mortality Investigation, Working Paper No. 34, Institute and Faculty of Actuaries, UK.Google Scholar
Continuous Mortality Investigation (CMI) (2008 b). Continuous Mortality Investigation, Working Paper No. 35, Institute and Faculty of Actuaries, UK.Google Scholar
Continuous Mortality Investigation (CMI) (2009). Continuous Mortality Investigation, Report No. 23, Institute and Faculty of Actuaries, UK.Google Scholar
Continuous Mortality Investigation (CMI) (2013 a). Continuous Mortality Investigation, Working Paper No. 65, Institute and Faculty of Actuaries, UK.Google Scholar
Continuous Mortality Investigation (CMI) (2013 b). Continuous Mortality Investigation, Working Paper No. 66, Institute and Faculty of Actuaries, UK.Google Scholar
Continuous Mortality Investigation (CMI) (2014). Continuous Mortality Investigation, Working Paper No. 71, Institute and Faculty of Actuaries, UK.Google Scholar
Dave, D., Rashad, I. & Spasojevic, J. (2008). The effects of retirement in physical and mental health outcomes. Southern Economic Journal, 75, 497–523.CrossRefGoogle Scholar
Ellingsen, T. (2010). Mortality among disability pensioners. International Congress of Actuaries, 8th–12th March 2010, Cape Town, South Africa.Google Scholar
Haberman, S. & Renshaw, A.E. (1996). Generalized linear models and actuarial science. Journal of the Royal Statistical Society. Series D, 45(4), 407–436.Google Scholar
Hall, M. & Friel, N. (2011). Mortality projections using generalized additive models. Annals of Actuarial Science, 5, 19–32.Google Scholar
Haukenes, I., Gjesdal, S., Rortveit, G., Riise, T. & Maelan, J. (2012). Women’s higher likelihood of disability pension: the role of health, family and work. A 5-7 years follow-up of the Hordaland Health Study. BMC Public Health, 12, 720.Google Scholar
Hernaes, E., Markussen, S., Piggott, J. & Vestad, O.L. (2013). Does retirement age impact mortality. Journal of Health Economics, 32, 586–598.Google Scholar
Jong, P. & Heller, G.Z. (2008). Generalized Linear Models for Insurance Data. Cambridge University Press, Cambridge.Google Scholar
Madrigal, A.M., Matthews, F.E., Patel, D.D., Gaches, A.T. & Baxter, S.D. (2011). What longevity predictors should be allows for when valuing pension scheme liabilities? British Actuarial Journal, 16(1), 1–38.Google Scholar
Malmusi, D., Artazcoz, L., Benach, J. & Borrell, C. (2012). Perception or real illness? How chronic conditions contribute to gender inequalities in self-rated health. The European Journal of Public Health, 22(6), 781–786.Google Scholar
Marra, G. & Wood, S. (2012). Coverage properties of confidence intervals for generalized additive model components. Scandinavian Journal of Statistics, 39, 53–74.Google Scholar
Nelder, J.A. & Wedderburn, R.W.N. (1972). Generalized linear models. Journal of the Royal Statistical Society, A, 135, 370–384.CrossRefGoogle Scholar
Olivieri, A. (2006). Heterogeneity in survival models. Applications to pensions and life annuities. Belgian Actuarial Bulletin, 6, 23–39.Google Scholar
Pitacco, E. (2012). Mortality of disabled people. Available online at the address www.actuaries.org/ CTTEES_TFM/Documents/Mortality_Disabled.pdf.Google Scholar
R Development Core Team (2014). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available online at the address http://www.R-project.org.Google Scholar
Silverman, B.W. (1985). Some aspects of the spline smoothing approach to non-parametric regression curve fitting. Journal of the Royal Statistical Society, Series B, 47(1), 1–53.Google Scholar
Wahba, G. (1983). Bayesian confidence intervals for the cross validated smoothing spline. Journal of the Royal Statistical Society, Series B, 45, 133–150.Google Scholar
Wood, S.N. (2001). mgcv: GAMs and generalized ridge regression for R. R News, 1, 20–25.Google Scholar
Wood, S.N. (2003). Thin plate regression splines. Journal of the Royal Statistical Society B, 65(1), 95–114.Google Scholar
Wood, S.N. (2006). Generalized Additive Models, an Introduction With R. Chapman & Hall.Google Scholar
Zayatz, T. (2005). Social security disability insurance program worker experience. Actuarial Study No. 118. Available online at the address www.ssa.gov/OACT/NOTES/as118/DI-WrkerExper_Body.html.Google Scholar
Zweerink, J. (2013). The causal effect of retirement on mortality: evidence from targeted incentives to retire early, Discussion Paper No. 7570, IZA – Institute for the Study of Labour, Germany.Google Scholar