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MODELLING SOCIO-ECONOMIC DIFFERENCES IN MORTALITY USING A NEW AFFLUENCE INDEX

  • Andrew J.G. Cairns (a1), Malene Kallestrup-Lamb (a2), Carsten Rosenskjold (a2), David Blake (a3) and Kevin Dowd (a4)...

Abstract

We introduce a new modelling framework to explain socio-economic differences in mortality in terms of an affluence index that combines information on individual wealth and income. The model is illustrated using data on older Danish males over the period 1985–2012 reported in the Statistics Denmark national register database. The model fits the historical mortality data well, captures their key features, generates smoothed death rates that allow us to work with a larger number of sub-groups than has previously been considered feasible, and has plausible projection properties.

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Blake, D., Cairns, A.J.G., Dowd, K. and Kessler, A. R. (2018) Still living with mortality: The longevity risk transfer market after one decade. British Actuarial Journal, 24, e1, 180.
Börger, M., Fleischer, D. and Kuksin, N. (2014) Modelling the mortality trend under modern solvency regimes. ASTIN Bulletin, 44, 138.
Booth, H., Maindonald, J. and Smith, L. (2002) Applying Lee-Carter under conditions of variable mortality decline. Population Studies, 56, 325336.
Bound, J., Geronimus, A.T., Rodriguez, J.M. and Waidmann, T.A. (2015) Measuring recent apparent declines in longevity: The role of increasing educational attainment. Health Affairs, 34, 21672173.
Brønnum-Hansen, H. and Baadsgaard, M. (2012) Widening social inequality in life expectancy in Denmark. A register-based study on social composition and mortality trends for the Danish population. BMC Public Health, 12, 994.
Cairns, A.J.G. (2013) Robust hedging of longevity risk. Journal of Risk and Insurance, 80, 621648.
Cairns, A.J.G., Blake, D. and Dowd, K. (2006) A two-factor model for stochastic mortality with parameter uncertainty: Theory and calibration. Journal of Risk and Insurance, 73, 687718.
Cairns, A.J.G., Blake, D., Dowd, K., Coughlan, G.D., Epstein, D., Ong, A. and Balevich, I. (2009) A quantitative comparison of stochastic mortality models using data from England & Wales and the United States. North American Actuarial Journal, 13, 135.
Cairns, A.J.G., Blake, D., Dowd, K., Coughlan, G.D. and Khalaf-Allah, M. (2011) Bayesian stochastic mortality modelling for two populations. ASTIN Bulletin, 41, 2959.
Cairns, A.J.G., Blake, D., Dowd, K. and Kessler, A. (2016) Phantoms never die: Living with unreliable population data. Journal of the Royal Statistical Society, Series A, 179, 9751005.
Cairns, A.J.G. and El Boukfaoui, G. (2017) Basis risk in index based longevity hedges: A guide for longevity hedgers. North American Actuarial Journal (to appear).
Chen, L., Cairns, A.J.G. and Kleinow, T. (2017) Small population bias and sampling effects in stochastic mortality modelling. European Actuarial Journal, 7, 193230.
Chetty, R., Stepner, M., Abraham, S., Lin, S., Scuderi, B., Turner, N., Bergeron, A. and Cutler, D. (2016) The association between income and life expectancy in the United States, 2001-2014. Journal of the American Medical Association, 315(16), 17501766.
Christensen, K., Davidsen, M., Juel, K., Mortensen, L., Rau, R. and Vaupel, J.W. (2010) The divergent life-expectancy trends in Denmark and Sweden – and some potential explanations. In International Differences in Mortality at Older Ages: Dimensions and Sources (eds. Crimmins, E.M., Preston, S.H., Cohen, B.), pp. 385407. Washington, DC: The National Academies Press.
Coughlan, G.D., Khalaf-Allah, M., Ye, Y., Kumar, S., Cairns, A.J.G., Blake, D. and Dowd, K. (2011) Longevity hedging 101: A framework for longevity basis risk analysis and hedge effectiveness. North American Actuarial Journal, 15, 150176.
Cristia, J.P. (2009) Rising mortality and life expectancy differentials by lifetime earnings in the United States. Journal of Health Economics, 28, 984995.
Dowd, K., Cairns, A.J.G., Blake, D., Coughlan, G.D. and Khalaf-Allah, M. (2010) Backtesting stochastic mortality models: An ex-post evaluation of multi-period-ahead density forecasts. North American Actuarial Journal, 14, 281298.
Dowd, K., Cairns, A.J.G., Blake, D., Coughlan, G.D., and Khalaf-Allah, M. (2011) A gravity model of mortality rates for two related populations. North American Actuarial Journal, 15, 334356.
Gavrilov, L.A. and Gavrilova, N.S. (1991) The Biology of Life Span: A Quantitative Approach. New York, NY: Harwood Academic Publisher.
Gilks, W.R., Richardson, S. and Spiegelhalter, D.J. (1996) Markov Chain Monte Carlo in Practice. London: Chapman and Hall.
Hyndman, R., Booth, H. and Yasmeen, F. (2013) Coherent mortality forecasting: The product-ratio method with functional time series models. Demography, 50, 261283.
Juel, K. (2008) Middellevetid og dødelighed i Danmark sammenlignet med i Sverige. Hvad betyder rygning og alkohol? [Life expectancy and mortality in Denmark compared to Sweden. What is the effect of smoking and alcohol?]. Ugeskrift Laeger, 170(33), 24232427. (In Danish).
Kallestrup-Lamb, M. and Rosenskjold, C. (2017) Insight into the female longevity puzzle: Using register data to analyse mortality and cause of death behaviour across socioeconomic groups. CREATES Research Paper 2017-08, Department of Economics and Business Economics, Aarhus University.
Kitagawa, E.M. and Hauser, P.M. (1968) Education differentials in mortality by cause of death: United States, 1960. Demography, 5, 318353.
Kwon, H.-S. and Jones, B. L. (2008) Applications of a multi-state risk factor/mortality model in life insurance. Insurance: Mathematics and Economics, 43, 394402.
Lee, R.D. and Carter, L.R. (1992) Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87, 659675.
Lee, R. and Miller, T. (2001) Evaluating the performance of the Lee-Carter method for forecasting mortality. Demography, 38, 537549.
Li, N. and Lee, R. (2005) Coherent mortality forecasts for a group of populations: An extension of the Lee-Carter method. Demography, 42, 575594.
Mackenbach, J.P., Bos, V., Andersen, O., Cardano, M., Costa, G., Harding, S., Reid, A., Hemström, Ö., Valkonen, T. and Kunst, A.E. (2003) Widening socioeconomic inequalities in mortality in six Western European countries. International Journal of Epidemiology, 32, 830837.
Michaelson, A. and Mulholland, J. (2015) Strategy for increasing the global capacity for longevity risk transfer: Developing transactions that attract capital markets investors. Pension and Longevity Risk Transfer for Institutional Investors, 2015(1), 2837.
Office for National Statistics (2011) Trends in life expectancy by National Statistics Socio-economic Classification 1982-2006. Available at: https://www.ons.gov.uk/.
Olshansky, S.J., Antonucci, T., Berkman, L., Binstock, R.H., Boersch-Supan, A., Cacioppo, J.T., Carnes, B.A., Carstensen, L.L., Fried, L.P., Goldman, D.P., Jackson, J., Kohli, M., Rother, J., Zheng, Y. and Rowe, J. (2012). Differences in life expectancy due to race and educational differences are widening, and many may not catch up. Health Affairs, 31(8), 18031813.
Plat, R. (2009) On stochastic mortality modelling. Insurance: Mathematics and Economics, 45, 393404.
Van Berkum, F., Antonio, K. and Vellekoop, M. (2016) The impact of multiple structural changes on mortality predictions. Scandinavian Actuarial Journal, 2016, 581603.
Villegas, A. and Haberman, S. (2014) On the modeling and forecasting of socio-economic mortality differentials: An application to deprivation and mortality in England. North American Actuarial Journal, 18, 168193.
Villegas, A., Haberman, S., Kaishev, V. and Millossovich, P. (2017) A comparative study of two-population models for the assessment of basis risk in longevity hedges. ASTIN Bulletin, 47, 631679.
Waldron, H. (2013) Mortality differentials by lifetime earnings decile: Implications for evaluations of proposed social security law changes. Social Security Bulletin, 73(1), 137.

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