Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-24T05:31:07.691Z Has data issue: false hasContentIssue false
  • English
  • Français

Should Projections of Mortality Improvements be Subject to a Minimum Value?

Published online by Cambridge University Press:  10 June 2011

S. D. Baxter
S. D. Baxter
Affiliation:
Hymans Robertson, One London Wall, London EC2Y 5EA, U.K. Tel: +44(0)20 7082 6299; Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Projections of future mortality typically used for funding pension scheme liabilities assume that future year-on-year decreases in mortality rates will slow rapidly, and that there is very limited potential for further decreases at the oldest ages. This paper considers the consistency of such projections with current trends in life expectancy. Particular focus is paid to whether future mortality should be subject to a minimum level of improvement to reflect general advances in medicine. Care is taken to exclude the additional increases in longevity arising from a concentration of positive health factors amongst the generation who are currently experiencing the ‘cohort effect’.

If historic trends continue into the future, then period life expectancy from age 65 in England & Wales will increase at 26 days p.a. for women and 41 days p.a. for men, with additional increases arising from the ‘cohort effect’. This is a faster rate of period increase in life expectancy than embedded in the interim cohort projections. One way to ensure that actuarial projections keep pace with the population trend is to subject projections to a minimum level of (geometric) improvement of at least 11/4% p.a. for men and 3/4% p.a. for women, at all older ages and in all future years.

Consideration is given to the possible impact of differences between the socio-economic profile of England & Wales and the membership of the pension schemes to whom the projections will be applied ultimately. This paper also highlights that the application of a single minimum value, independent of time and age, simplifies a more complex underlying pattern, but that minimum improvements of 11/4% p.a. for males and 3/4% p.a. for females represent an average of historic improvements in mortality seen in England & Wales.

The paper includes a survey of the history of the low levels of mortality seen currently. The survey includes some discussion on the potential for future improvements and considers topical issues, such as the potential impact of obesity on life expectancy projections (and, in turn, the minimum value applied to improvements).

The financial impact of subjecting projections of mortality improvement to a minimum value is quantified.

Keywords

MortalityLongevityAnnuitiesCohort Effect
Type
Sessional meetings: papers and abstracts of discussions
Information
British Actuarial Journal , Volume 13 , Issue 3 , 01 September 2007 , pp. 375 - 464
Copyright
Copyright © Institute and Faculty of Actuaries 2007

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

BBC (2004). Heart death ‘may be eradicated’. http://news.bbc.co.uk/1/hi/health/3560671.stmGoogle Scholar
Cancer Research U.K. Lung cancer and smoking statistics. Available from: http://info.cancerresarchuk.org/cancerstats/types/ling/smokingGoogle Scholar
CMI Bureau (1990). Continuous Mortality Investigation Reports Number 10.Google Scholar
CMI Bureau (1998). Continuous Mortality Investigation Reports Number 16.Google Scholar
CMI Bureau (1999). Continuous Mortality Investigation Reports Number 17.Google Scholar
CMI Bureau Mortality Sub-Committee (2002a). Working paper 1: An interim basis for adjusting the ‘92’ series mortality projections for cohort effects.Google Scholar
CMI Bureau Mortality Sub-Committee (2002b). Working paper 2: Responses to the draft report entitles a proposed interim basis for adjusting the ‘92’ series mortality projections for cohort effects and further commentary thereon.Google Scholar
CMI Bureau Technical Support and Research Committee of the Pensions Board (2004a). Working paper 4: Report on the preliminary analysis into the mortality experience of self-administered pension schemes for the period 2000 to 2002.Google Scholar
CMI Bureau Technical Support and Research Committee of the Pensions Board (2004b). Working paper 9: An analysis of the preliminary results of the mortality of male pensioners of self-administered pension schemes for the period 2000 to 2002 as reported in working paper 4.Google Scholar
CMI Bureau Technical Support and Research Committee of the Pensions Board (2005). Working paper 17: Report on the preliminary results of the mortality experience of pensioners of self-administered pension schemes for the period 2000 to 2003.Google Scholar
CMI Mortality Committee (2005). Working paper 15: Projecting future mortality: towards a proposal for a stochastic methodology. CMI Mortality Committee (2006). Working paper 22: The graduation of the CMI 1999-2002 mortality experience: final ‘00’ series mortality tables — annuitants and pensioners.Google Scholar
CMI Mortality Committee (2007a). Revised working paper 20: Stochastic projection methodologies: Further progress and P-spline model features, example results and implications.Google Scholar
CMI Mortality Committee (2007b). Working paper 27: The “library” of mortality projections.Google Scholar
Cummings, J.H. & Bingham, S.A. (1998). Diet and the prevention of cancer. British Medical Journal, 317, 1636–1640.CrossRefGoogle ScholarPubMed
Currie, I.D., Durban, M. & Eilers, P.H.C. (2004). Smoothing and forecasting mortality rates. Statistical Modelling, 4, 279–298.CrossRefGoogle Scholar
Doll, R. & Hill, A.B. (1950). Smoking and carcinoma of the lung: preliminary report. British MedicalJournal, 02, 739–748.CrossRefGoogle Scholar
Department of Health (2004). Technical note for the Spending Review 2004: Public Service Agreement 2005-2008. Available from www.dh.gov.ukGoogle Scholar
Eilers, P.H.C. & Marx, B.D. (1996). Flexible smoothing with B-splines and penalties. Statistical Science, 11, 89–102.CrossRefGoogle Scholar
Friedman, J.M. (2000). Obesity in the new millennium. Nature, 404, 632–634.CrossRefGoogle ScholarPubMed
Friedman, J.M. & Halaas, J.L. (1998). Leptin and the regulation of body weight in mammals. Nature, 395, 763–770.CrossRefGoogle ScholarPubMed
Government Actuary's Department (2001). National population projections: review of methodology for projecting mortality. NSQR Series, 8. 438Google Scholar
Government Actuary's Department (2004). National population projections (2004-based). Series PP2, 25.Google Scholar
Hicks, J. & Allen, G. (1999). A century of change: trends in U.K. statistics since 1900. House of Commons research paper 99/111.Google Scholar
Hubert, H.B., Feinleib, M., McNamara, P.M. & Castelli, W.P. (1983). Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the Framingham Heart Study. Circulation, 67, 968–977.CrossRefGoogle ScholarPubMed
Human Mortality Database (2006). Human mortality database. University of California, Berkeley (USA), and Max Planck Institute for Demographic Research (Germany). Available at www.mortality.org or www.humanmortality.de. England & Wales data downloaded on 30 November 2006, U.S.A. data downloaded 11 December 2006, data for rest of the world downloaded on 29 May 2007.Google Scholar
Kalben, B.B. (2002). Why men die younger: causes of mortality differences by sex. Society of Actuaries monograph M-LI01-1.Google Scholar
Kopelman, P.G. & Grace, C. (2004). New thoughts on managing obesity. Gut, 53, 1044–1053.CrossRefGoogle ScholarPubMed
Lee, R.D. & Carter, L. (1992). Modelling and forecasting the time series of U.S. mortality. Journal of the American Statistical Association, 87, 659–671.Google Scholar
Lu-Yao, G., Albertsen, P.C., Stanford, J.L., Stukel, T.A., Walker-Corkery, E.S. & Barry, M.J. (2002). Natural experiment examining impact of aggressive screening and treatment on prostate cancer mortality in two fixed cohorts from Seattle area and Conneticut. British Medical Journal, 325, 740.CrossRefGoogle Scholar
National Health Service (2000a). National Service framework for coronary heart disease: modern standards and service models. Available from http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_4094275Google Scholar
National Health Service (2000b). The NHS cancer plan: a plan for investment: a plan for reform. Available from http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_4009609Google Scholar
National Health Service (2006). The coronary heart disease national service framework: shaping the future: progress report for 2006. Available from http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_063168Google Scholar
NTC Publications in Association with Hewitt (2007). Pensions pocket book 2007.Google Scholar
Oeppen, J. & Vaupel, J. (2002). Broken limits to life expectancy. Science, 296, 1029–1031.CrossRefGoogle ScholarPubMed
Office for National Statistics (2003a). Twentieth century mortality trends in England & Wales. Health Statistics Quarterly, 18, 5–17.Google Scholar
Office for National Statistics (2003b). Twentieth century mortality.Google Scholar
Office for National Statistics (2006). Focus on health: 2006 edition.Google Scholar
Olshansky, S.J. & Carnes, B.A. (2001). The quest for immortality. Norton.Google Scholar
Olshansky, S.J., Passaro, D.J., Hershow, R.C., Layden, J., Carnes, B.A., Brody, J., Hayflick, L., Butler, R.N., Allison, D.B. & Ludwig, D.S. (2005). A potential decline in life expectancy in the United States in the 21st century. New England Journal of Medicine, 352(11), 1138–1145.CrossRefGoogle Scholar
Peeters, A., Barendregt, J.J., Willekens, F., MacKenbach, J.P., Al Mamun, A. & Bonneux, L. (2003). Obesity in adulthood and its consequences for life expectancy: a life-table analysis. Annals of International Medicine, 138, 24–32.CrossRefGoogle ScholarPubMed
Richards, S.J., Ellam, J.R., Hubbard, J., Lu, J.L.C., Makin, S.J. & Miller, K.A. (2007). Two dimensional mortality data: patterns and projections. British Actuarial Journal, 13, 479–554.CrossRefGoogle Scholar
Richards, S. & Jones, G. (2004). Financial aspects of longevity risk. Paper presented to the Staple Inn Actuarial Society.Google Scholar
Riley, J.C. (2001). Rising life expectancy: a global history. Cambridge University Press.CrossRefGoogle Scholar
Rose, D. (1995). Official social classifications in the U.K. Social Research Update 9, Published by the Department of Sociology, University of Surrey. http://sru.soc.surry.ac.uk/SRU9.htmlGoogle Scholar
Thatcher, A.R., Kannisto, V. & Vaupel, J.W. (1998). The force of mortality at ages 80 to 120. Odense University Press.Google Scholar
The Pensions Regulator (2007). The purple book.Google Scholar
Unal, B., Critchley, J.A. & Capewell, S. (2004). Explaining the decline in coronary heart disease mortality in England & Wales between 1981 and 2000. Circulation, 109, 1101–1107.CrossRefGoogle ScholarPubMed
Willets, R.C. (1999). Mortality in the next millenium. Paper presented to the Staple Inn Actuarial Society.Google Scholar
Willets, R.C. (2004). The cohort effect: insights and explanations. British Actuarial Journal, 10, 833–877.CrossRefGoogle Scholar
Willets, R.C., Gallop, A.P., Leandro, P.A., Lu, J.L.C., MacDonald, A.S., Miller, K.A., Richards, S.J., Robjohns, N., Ryan, J.P. & Waters, H.R. (2004). Longevity in the 21st century. British Actuarial Journal, 10, 685–832.CrossRefGoogle Scholar
Wilmoth, J.R. (1997). In Search of Limits. Published within Between Zeus and the salmon: the biodemography of longevity (edited by Watcher, Kenneth & Finch, Caleb. National Academic Press.Google Scholar
World Health Organization (2006). Cancer. Fact sheet no 297.Google Scholar