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The ‘Golden Generations’ in Historical Context

Published online by Cambridge University Press:  10 June 2011

Michael Murphy
Michael Murphy
Affiliation:
Department of Social Policy, London School of Economics, Houghton Street, London WC2A 2AE, U.K. Tel: +44-20-7955-7661; Fax: +44-20-7955-7415; E-mail: [email protected]
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Abstract

Assumptions about future mortality are more important than those for factors such as fertility, migration, disability trends or real interest rates for cost projections of the U.S. Old Age, Survivors, Disability and Health Insurance scheme. Recently, one factor has been assumed to be the key driver of future mortality in both official British population projections and actuarial ones: a ‘cohort effect’ associated with a group who were born in a period centred on the early 1930s who have been identified as having experienced particularly rapid improvements in mortality rates and are often referred to as the ‘golden generations’ or ‘golden cohorts’. The concept of ‘cohort effects’ is discussed; limitations of national-level cohort data considered; and methods for identifying such effects are reviewed. Particular attention is given to the analysis of populations which have been identified as having clear cut cohort effects; those of Britain and Sweden in the later part of the nineteenth century and early twentieth century, as well as the contemporary British population. The likely magnitude of such effects is discussed using a stylised model to assess the extent to which members of the ‘golden generations’ are especially privileged.

Keywords

MortalityCohort PatternsHistorical DemographyGolden Generations
Type
Sessional meetings: papers and abstracts of discussions
Information
British Actuarial Journal , Volume 15 , Issue S1 , 2009 , pp. 151 - 184
Copyright
Copyright © Institute and Faculty of Actuaries 2009

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References

Almond, D.V. (2006). Is the 1918 Influenza Pandemic over? Long-term effects of in utero influenza exposure in the post-1940 U.S. population. Journal of Political Economy, 114, 672–712.CrossRefGoogle Scholar
Alwyn, D.F. & McCammon, R.J. (2006). Generations, cohorts and social change. In: Mortimer, J.T. and Shanahan, M.J. (eds.). Handbook of the Life Course. Springer, New York, 23–49.Google Scholar
Antolin, P. (2007). Longevity risk and private pensions: OECD working paper on insurance and private pensions No. 3. Financial Affairs Division, Directorate for Financial and Enterprise Affairs Organisation for Economic Co-operation and Development, January 2007. Available at www.oecd.org/daf/finGoogle Scholar
Arias, E., Rostron, B.L. & Tejada-Vera, B. (2010). United States life tables, 2005. National vital statistics reports; vol. 58 no. 10., MD: National Center for Health Statistics, Hyattsville, MD:. Available at http://www.cdc.gov/nchs/products/nvsr.htmGoogle Scholar
Aylin, P., Dunnell, K. & Drever, F. (1999). Trends in mortality of young adults aged 15 to 44 in England and Wales. Health Statistics Quarterly, 1, 34–39.Google Scholar
Barker, D.J.P. (1994). Mothers, babies and disease in later life. British Medical Journal Publishing Group, London.Google Scholar
Barker, D.J.P., Osmond, C. & Law, C.M. (1989). The intrauterine and early postnatal origins of cardiovascular disease and chronic bronchitis. Journal of Epidemiology and Community Health, 43, 237–240.CrossRefGoogle ScholarPubMed
Bianchi, M., Boyle, M. & Hollingsworth, D. (1999). A comparison of methods for trend estimation. Applied Economics Letters, 6, 103–109.Google Scholar
Blake, D. & Pickles, J. (2008). Apocalyptic demography? Putting longevity risk in perspective. The Chartered Institute of Management Accountants. Available at www.cimaglobal.comGoogle Scholar
Blake, D., Cairns, A. & Dowd, K. (2007). Longevity risk and the Grim Reaper's toxic tail: The survivor fan charts, Pensions Institute Discussion Paper PI-0705. City University: The Pensions Institute.Google Scholar
Cairns, A.J.G., Blake, D. & Dowd, K. (2006). A two-factor model for stochastic mortality with parameter uncertainty: theory and calibration. The Journal of Risk and Insurance, 73(4), 687–718.CrossRefGoogle Scholar
Carstensen, B. (2007). Age-period-cohort models for the Lexis diagram. Statistics in Medicine, 26, 3018–3045.Google Scholar
Charlton, J. & Murphy, M. (eds.) (1997). The health of adult Britain 1841–1994. Office of population censuses and surveys, Decennial Supplement 12. HMSO, London.Google Scholar
Coale, A.J. & Kisker, E.E. (1986). Mortality crossovers: reality or bad data? Population studies, 40, 389–401.CrossRefGoogle Scholar
Coleman, D. & Salt, J. (1992). The British population: patterns, trends, and processes. Oxford University Press, Oxford.Google Scholar
Continuous Mortality Investigation (2007). Continuous mortality investigation working paper 30. The CMI library of mortality projections, November 2007 (and associated libraries). Available at http://www.actuaries.org.uk/knowledge/cmi/cmi_wp/wp30.Google Scholar
Crimmins, E.M. & Finch, C.E. (2006). Infection, inflammation, height and longevity. Proceedings of the National Academy of Science USA, 103, 498–503.CrossRefGoogle ScholarPubMed
Davey Smith, G. & Kuh, D. (2001). Commentary: William Ogilvy Kermack and the childhood origins of adult health and disease. International Journal of Epidemiology, 30, 696–703.Google Scholar
Davey Smith, G. & Lynch, D.J. (2004). Commentary: social capital, social epidemiology, and disease aetiology. International Journal of Epidemiology, 33, 691–700.Google Scholar
Derrick, V.P.A. (1927). Observation on (1) error on age on the population statistics of England and Wales and (2) the changes of mortality indicated by the national records (with discussion). Journal of the Institute of Actuaries, 58, 117–159.Google Scholar
Di Cesare, M. & Murphy, M. (2009). Forecasting mortality, different approaches for different cause of deaths? The cases of lung cancer; influenza, pneumonia, and bronchitis; and motor vehicle accidents. British Actuarial Journal, 15(Supplement), 185–211.CrossRefGoogle Scholar
Doll, R. & Cook, P. (1967). Summarizing indices for comparison of cancer incidence data. International Journal of Cancer, 2, 269–279.Google Scholar
Dunnell, K. (2008). Ageing and mortality in the UK — National Statistician's Annual Article on the population. Population Trends, 134, 6–23.Google Scholar
Euromoney (2008). Longevity risk debate: How pension schemes cope with an ageing population. Euromoney 7, October 2008, 137–144. Available at http://www.euromoney.com/Print.aspx?ArticleID=2024974Google Scholar
Finch, C.E. & Crimmins, E.M. (2004). Inflammatory exposure and historical changes in human life-spans. Science, 305, 1736–1739.CrossRefGoogle ScholarPubMed
Floud, R., Wachter, K. & Gregory, A. (1990). Height, health and history: nutritional status in the United Kingdom, 1750–1980. Cambridge University Press, Cambridge.Google Scholar
Gray, L., Harding, S. & Reid, A. (2007). Evidence of divergence with duration of residence in circulatory disease mortality in migrants to Australia. European Journal of Public Health, 1–5.Google Scholar
Hajnal, J. (1955). The prospects of population forecasts. Journal of the American Statistical Association, 50, 309–322.CrossRefGoogle Scholar
Harris, B. (2001). ‘The child is father of the man’. The relationship between child health and adult mortality in the 19th and 20th centuries. International Journal of Epidemiology, 30, 688–696.CrossRefGoogle ScholarPubMed
Hobcraft, J., Menken, J. & Preston, S.H. (1982). Age, period, and cohort analysis in demography: a review. Population Index, 48(1), 4–43.Google Scholar
Human Mortality Database (2009). University of California, Berkeley (U.S.A.), and Max Planck Institute for Demographic Research (Germany). Available at HMD, http://www.mortality.org/Google Scholar
Kannisto, V., Christensen, K. & Vaupel, J.W. (1997). No increased mortality in later life for cohorts born during famine. American Journal of Epidemiology, 145(11), 987–994.CrossRefGoogle ScholarPubMed
Kenny, P.B. & Durbin, J. (1982). Local trend estimation and seasonal adjustment of economic and social time series. Journal of the Royal Statistical Society. Series A (General), 145(1), 1–41.Google Scholar
Kermack, W.O., McKendrick, A.G. & McKinlay, P.L. (1934). Death-rates in Great Britain and Sweden. Some general regularities and their significance. Lancet, 223(5770), 698–703.Google Scholar
Kuh, D. & Davey Smith, G. (1993). When is mortality risk determined? Historical insights into a current debate. Social History of Medicine, 6, 101–123.Google Scholar
Kuh, D. & Ben-Schlomo, Y. (1997). A life course approach to chronic disease epidemiology. Oxford University Press, Oxford.Google Scholar
Kyd, J.G. (1953). Discussion. Transactions of the Faculty of Actuaries, 21, 45–49.Google Scholar
Lumey, L.H. & Van Poppel, F.W. (1994). The Dutch famine of 1944–45: mortality and morbidity in past and present generations. Social History of Medicine, 7, 229–246.Google Scholar
Lumey, L.H., Stein, A.D., Kahn, H.S., van der Pal-de Bruin, K.M., Blauw, G.J., Zybert, P.A. & Susser, E.S. (2007). Cohort profile: the Dutch hunger winter families study. International Journal of Epidemiology, 36(6), 1196–1204.CrossRefGoogle ScholarPubMed
MacMinn, R. & Weber, F. (2009). Select birth cohorts. Discussion Paper 2009—03. Munich School of Management University of Munich Fakultät für Betriebswirtschaft Ludwig-Maximilians-Universitat Munchen. Available at http://epub.ub.uni-muenchen.de/Google Scholar
McKeown, T. (1976). The modern rise of population. Edward Arnold, London.Google Scholar
McKeown, T. (1988). The origins of human disease, Blackwell Publishers, Oxford.Google Scholar
Mazumder, B., Almond, D., Park, K., Crimmins, E.M. & Finch, C.E. (2009). Lingering prenatal effects of the 1918 influenza pandemic on cardiovascular disease. Journal of Developmental Origins of Health and Disease. eprint ahead of publication DOI: 10.1017/S2040174409990031.CrossRefGoogle Scholar
Ministry of Health, Labour and Welfare (2009). Abridged life tables for Japan 2008. Statistics and Information Department Minister's Secretariat Ministry of Health, Labour and Welfare Japanese Government. Available at http://www.mhlw.go.jp/Google Scholar
Murphy, M. (1995). The prospect of mortality: England and Wales and the United States of America 1962–1989. British Actuarial Journal, 1(2), 331–350.Google Scholar
Murphy, M. (2009). Where have all the children gone? Reports of increasing childlessness in a large-scale continuous household survey. Population Studies, 63(2), 115–133.CrossRefGoogle Scholar
Murphy, M. (2010a). Correspondence: detecting year-of-birth mortality patterns with limited data. Journal of the Royal Statistical Society Part A, 173(4): 915–920.CrossRefGoogle Scholar
Murphy, M. (2010b). Reexamining the dominance of birth cohort effects on mortality. Population and Development Review, 36(2), 365–390.Google Scholar
Newman, S.C. (2001). Biostatistical methods in epidemiology. Wiley-Interscience, New York.Google Scholar
OECD (2007). Pensions at a glance: public policies across OECD countries: 2007 Edition. Paris: OECD Publications.Google Scholar
Office for National Statistics (2008a). Occupational pension schemes Annual Report No. 15. 2007 edition. Available at http://www.statistics.gov.uk/statbase/Product.asp?vlnk=1721Google Scholar
Office for National Statistics (2008b). National population projections 2006-based. Series pp2 No 26. Palgrave Macmillan, Basingstoke.Google Scholar
Office for National Statistics (2008c). Mortality statistics. Deaths registered in 2007. Review of the National Statistician on deaths in England and Wales, 2007. Series DR DR_07. Available at http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15096Google Scholar
Office for National Statistics (2009a). Statistical bulletin. National population projections, 2008-based 21 October 2009, Available at http://www.statistics.gov.uk/StatBase/Product.asp?vlnk=8519Google Scholar
Office for National Statistics (2009b). Population by country of birth & nationality, Jan 2008 to Dec 2008. Available at http://www.statistics.gov.uk/statbase/Product.asp?vlnk=15147Google Scholar
Office of Population Censuses and Surveys (1995). National population projections 1992-based. Series PP2 no. 18. HMSO, London.Google Scholar
Omran, A.R. (1971). The epidemiologic transition: a theory of the epidemiology of population change. The Milbank Memorial Fund Quarterly, 49(4), 509–538.CrossRefGoogle ScholarPubMed
Omran, A.R. (1998). The epidemiological transition theory revisited thirty years later. World Health Statistics Quarterly, 51, 99–119.Google Scholar
Preston, S.H. (1976). Mortality patterns in national populations: with special reference to recorded causes of death. Academic Press, New York.Google Scholar
Preston, S.H. (1996). American longevity: past, present, and future distinguished lecturer in aging, Series. No. 7/1996. Maxwell School of Citizenship and Public Affairs, Center for Policy Research, Syracuse University. Available at http://www-cpr.maxwell.syr.edu/pbriefs/pblist.htmGoogle Scholar
Preston, S.H., Keyfitz, N. & Schoen, R. (1972). Causes of death: life tables for national populations. Academic Press, New York.Google Scholar
Preston, S.H. & Wang, H. (2006). Sex mortality differences in the United States: the role of cohort smoking patterns. Demography, 43(4), 631–646.CrossRefGoogle ScholarPubMed
R Development Core Team (2009). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Available at www.r-project.orgGoogle Scholar
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, III, 479–555.Google Scholar
Richards, S.J., Kirkby, J.G. & Currie, I.D. (2006). The importance of year of birth in two-dimensional mortality data. British Actuarial Journal, 12, I, 5–61.CrossRefGoogle Scholar
Singer, B.H. & Manton, K.G. (1998). The effects of health changes on projections of health service needs for the elderly population of the United States. Proceedings of the National Academy of Sciences, 95(26), 15618–15622.Google Scholar
Singh, G.K. & Miller, B.A. (2004). Health, life expectancy, and mortality patterns among immigrant populations in the United States. Canadian Journal of Public Health, 95(3), I–14–21.Google Scholar
Social Security Administration (2008). The 2008 Annual Report of the Board of Trustees of the Federal Old-Age and Survivors Insurance and Federal Disability Insurance Trust Funds. Available at https://www.socialsecurity.gov/OACT/TR/TR08/VI_LRsensitivity.html#100512Google Scholar
Stein, Z.A., Susser, M., Saenger, G. & Marolla, F. (1975). Famine and Human Development: The Dutch Hunger Winter of 1944–1945. Oxford University Press, New York.Google Scholar
Steventon, A. (2008). An assessment of the Government's reforms to public sector pensions: a Research Report by Adam Steventon. Pensions Policy Institute ISBN 978–1–906284–06–0. Available at www.pensionspolicyinstitute.org.ukGoogle Scholar
Susser, M. (2001). The longitudinal perspective and cohort analysis. International Journal of Epidemiology, 30, 684–687.CrossRefGoogle ScholarPubMed
SWISSRE (2007). Annuities: a private solution to longevity risk No. 3/2007. Available at http://www.swissre.com/pws/research%20publications/sigma%20ins.%20research/annuities%20%20a%20private%20solution%20to%20longevity%20risk%20no%203%202007.htmlGoogle Scholar
SWISSRE (2008). Innovative ways of financing retirement. sigma No. 4/2008. Available at http://www.swissre.com/pws/research%20publications/sigma%20ins.%20research/sigma_no_4_2008.htmlGoogle Scholar
Szreter, S. (1988). The importance of social interventions in Britain's mortality decline c. 1850–1914: a re-interpretation of the role of public health. Social History of Medicine, 1, 1–37.Google Scholar
The Pensions Regulator (2008). Good practice when choosing assumptions for defined benefit pension schemes with a special focus on mortality. Consultation document February 2008, Available at www.thepensionsregulator.gov.ukGoogle Scholar
Van der Zee, H.A. (1998). The hunger winter: occupied Holland 1944–1945. University of Nebraska Press, Nebraska.Google Scholar
Vaupel, J.W., Manton, K.G. & Stallard, E. (1979). The impact of heterogeneity in individual frailty on the dynamics of mortality. Demography, 16, 439–454.Google Scholar
Vaupel, J.W. & Yashin, A.I. (1985). Heterogeneity's ruses: some surprising effects of selection on population dynamics. The American Statistician, 39, 176–185.Google Scholar
Willets, R.C. (1999). Mortality in the next millennium. SIAS. Available at http://www.sias.org.uk/siaspapers/listofpapers/view_ paper?id=MortalityMillenniumGoogle Scholar
Willets, R.C. (2004). The cohort effect: insights and explanations. British Actuarial Journal, 10(4), 833–877.Google 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 (with discussion). British Actuarial Journal, 10(4), 685-832, 878–898.Google Scholar
Williams, G.C. (1957). Pleitropy, natural selection and the evolution of senescence. Evolution, 11, 398–411.CrossRefGoogle Scholar
Woods, R.I. (2000). The demography of Victorian England and Wales. Cambridge University Press, Cambridge.Google Scholar
Yang, Y., Fu, W.J. & Land, K.C. (2004). A methodological comparison of age-period cohort models: intrinsic estimator and conventional generalized linear models, with response of H.L. Smith. In: Stolzenberg, R.M. (ed.). Sociological Methodology. Blackwell Publishing, Boston, MA, 75–110.Google Scholar