Volume 41 - Article 43 | Pages 1235–1268
The impact of the choice of life table statistics when forecasting mortality
By Marie-Pier Bergeron-Boucher, Søren Kjærgaard, James E. Oeppen, James W. Vaupel
References
Aitchison, J. (1986). The statistical analysis of compositional data. London: Chapman and Hall.
Basellini, U. and Camarda, C.G. (2019). Modelling and forecasting adult age-at-death distributions. Population Studies 73(1): 119-138.
Bell, W.R. (1997). Comparing and Assessing Time Series Methods for Forecasting Age-Specific Fertility and Mortality Rates. Journal of Official Statistics 13(3): 279-303.
Bergeron–Boucher, M.–P., Canudas-Romo, V., Oeppen, J., and Vaupel, J.W. (2017). Coherent forecasts of mortality with compositional data analysis. Demographic Research 37(17): 527-568.
Bergeron–Boucher, M.–P., Simonacci, V., Oeppen, J., and Gallo, M. (2018). Coherent Modeling and Forecasting of Mortality Patterns for Subpopulations Using Multiway Analysis of Compositions: An Application to Canadian Provinces and Territories. North American Actuarial Journal 22(1): 92-118.
Bernardi, Mauro and Catania, Leopoldo (2015). The Model Confidence Set package for R.
Bohk–Ewald, C. and Rau, R. (2017). Probabilistic mortality forecasting with varying age-specific survival improvements. Genus 73(1): 1-37.
Bongaarts, J. and Feeney, G. (2002). How Long Do We Live? Population and Development Review 28(1): 13-29.
Booth, H., Hyndman, R., Tickle, L., and de Jong, Pi. (2006). Lee–Carter mortality forecasting: A multi-country comparison of variants and extensions. Demographic Research 15(9): 289-310.
Booth, H., Maindonald, J., and Smith, L. (2002). Applying Lee–Carter under conditions of variable mortality decline. Population Studies 56(3): 325-336.
Booth, H. and Tickle, L. (2008). Mortality Modelling and Forecasting: A Review of Methods. Annals of Actuarial Science 3(1-2): 3-43.
Brass, W. (1971). On the scale of mortality. Taylor and Francis.
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(4): 687-718.
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 and Wales and the United States. North American Actuarial Journal 13(1): 1-35.
Carter, L.R. and Lee, R.D. (1992). Modeling and forecasting US sex differentials in mortality. International Journal of Forecasting 8(3): 393-411.
de Jong, P. and Marshall, C. (2007). Mortality projection based on the Wang transform. ASTIN Bulletin 37(1): 149-161.
Debón, A., Montes, F., and Puig, F. (2008). Modelling and forecasting mortality in Spain. European Journal of Operational Research 189(3): 624-637.
Ediev, D.M. (2008). Extrapolative projections of mortality: Towards a more consistent method part I: the central scenario.
Glei, D.A. and Horiuchi, S. (2007). The narrowing sex differential in life expectancy in high-income populations: Effects of differences in the age pattern of mortality. Population Studies 61(2): 141-159.
Gompertz, B. (1825). On the Nature of the Function Expressive of the Law of Human Mortality, and on a New Mode of Determining the Value of Life Contingencies. Philosophical Transactions of the Royal Society of London 115: pp.-513.
Haberman, S. and Renshaw, A. (2012). Parametric mortality improvement rate modelling and projecting. Insurance: Mathematics and Economics 50(3): 309-333.
Haldrup, Niels and Rosenskjold, Carsten P. T. (2019). A Parametric Factor Model of the Term Structure of Mortality. Econometrics 7(1).
Hansen, P.R., Lunde, A., and Nason, J.M. (2011). The Model Confidence Set. Econometrica 79(2): 453-497.
Hatzopoulos, P. and Haberman, S. (2013). Common mortality modeling and coherent forecasts. An empirical analysis of worldwide mortality data. Insurance: Mathematics and Economics 52(2): 320-337.
HMD. Human mortality database [electronic resource], year=2019, note = Berkeley: University of California; Rostock: Max Planck Institute for Demographic Research \hrefhttp://www.mortality.org/\textcolorbluewww.mortality.org.
Hyndman, R.J., Booth, H., and Yasmeen, F. (2013). Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models. Demography 50(1): 261-283.
Hyndman, R.J. and Ullah, S. (2007). Robust forecasting of mortality and fertility rates: A functional data approach. Computational Statistics and Data Analysis 51(10): 4942-4956.
Janssen, F., van Wissen, L.J.G., and Kunst, A.E. (2013). Including the smoking epidemic in internationally coherent mortality projections. Demography 50(4): 1341-1362.
Kannisto, V., Lauritsen, J., Thatcher, A.R., and Vaupel, J.W. (1994). Reductions in mortality at advanced ages: Several decades of evidence from 27 countries. Population and Development Review 20(4): 793-810.
Keyfitz, N. (1991). Experiments in the projection of mortality. Canadian Studies in Population 18(2): 1-17.
King, G. and Soneji, S. (2011). The future of death in America. Demographic Research 25(1): 1-38.
Kjærgaard, S., Ergemen, Y.E., Kallestrup–Lamb, M., Oeppen, J., and Lindahl-Jacobsen, R. (2019). Forecasting causes of death by using compositional data analysis: The case of cancer deaths. Journal of the Royal Statistical Society: Series C (Applied Statistics) 65(5): 1351-1370.
Lee, R. (2000). The Lee–Carter method for forecasting mortality, with various extensions and applications. North American Actuarial Journal 4(1): 80-93.
Lee, R. and Miller, T. (2001). Evaluating the performance of the Lee–Carter method for forecasting mortality. Demography 38(4): 537-549.
Lee, R.D. and Carter, L.R. (1992). Modeling and forecasting US mortality. Journal of the American Statistical Association 87(419): 659-671.
Li, H., O’Hare, C., and Zhang, X. (2015). A semiparametric panel approach to mortality modeling. Insurance: Mathematics and Economics 61(Supplement C): 264-270.
Li, N. and Lee, R. (2005). Coherent mortality forecasts for a group of populations: An extension of the Lee–Carter method. Demography 42(3): 575-594.
Li, N., Lee, R., and Gerland, P. (2013). Extending the Lee–Carter Method to Model the Rotation of Age Patterns of Mortality Decline for Long-Term Projections. Demography 50(6): 2037-2051.
Martín–Fernández, J.A., Barceló–Vidal, C., and Pawlowsky–Glahn, V. (2003). Dealing With Zeros and Missing Values in Compositional Data Sets Using Nonparametric Imputation. Mathematical Geology 35(3): 253-78.
Meslé, F. (2004). Life expectancy: A female advantage under threat. Population and Societies 402(4).
Oeppen, J. (2008). Coherent forecasting of multiple-decrement life tables: A test using Japanese cause of death data. (Paper presented at the European Population Conference, Barcelona, Spain, July 10–July 12, 2008).
Oeppen, J. and Vaupel, J.W. (2002). Broken Limits to Life Expectancy. Science 296(5570): 1029-1031.
Pascariu, M., Canudas–Romo, V., and Vaupel, J.W. (2018). The double-gap life expectancy forecasting model. Insurance: Mathematics and Economics 78: 339-350.
Pawlowsky–Glahn, V. and Buccianti, A. (2011). Compositional data analysis: Theory and applications. Chichester: John Wiley and Sons.
Pollard, J.H. (1987). Projection of age-specific mortality rates. Population Bulletin of the United Nations (21/22): 55-69.
Preston, S., Heuveline, P., and Guillot, M. (2001). Demography: Measuring and modeling population processes. Oxford: Blackwell Publishing.
Raftery, A.E., Chunn, J.L., Gerland, P., and Ševčíková, H. (2013). Bayesian Probabilistic Projections of Life Expectancy for All Countries. Demography 50(3): 777-801.
Raftery, A.E., Lalic, N., and Gerland, P. (2014). Joint probabilistic projection of female and male life expectancy. Demographic Research 30: 795-822.
Renshaw, A.E. and Haberman, S. (2006). A cohort-based extension to the Lee–Carter model for mortality reduction factors. Insurance: Mathematics and Economics 38(3): 556-570.
Russolillo, M., Giordano, G., and Haberman, S. (2011). Extending the Lee–Carter model: A three-way decomposition. Scandinavian Actuarial Journal 2011(2): 96-117.
Scherbov, S. and Ediev, D. (2016). Does selection of mortality model make a difference in projecting population ageing? Demographic Research 34(2): 39-62.
Shang, H.L. and Haberman, S. (2018). Model confidence sets and forecast combination: An application to age-specific mortality. Genus 74(1): 19.
Stoeldraijer, L., van Duin, C., van Wissen, L.J.G., and Janssen, F. (2013). Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands. Demographic Research 29(13): 323-354.
Sweeting, P.J. (2011). A Trend-Change Extension of the Cairns–Blake–Dowd Model. Annals of Actuarial Science 5(2): 143-162.
Thatcher, R.A., Kannisto, V., and Vaupel, J.W. (1998). The force of mortality at ages 80 to 120. Odense, Denmark: Odense University Press.
Torri, T. and Vaupel, J.W. (2012). Forecasting life expectancy in an international context. International Journal of Forecasting 28(2): 519-531.
Vaupel, J.W. and Yashin, A.I. (1987). Repeated resuscitation: How lifesaving alters life tables. Demography 24(1): 123-135.
White, K.M. (2002). Longevity Advances in High-Income Countries, 1955–96. Population and Development Review 28(1): 59-76.
Wilmoth, J.R. (2005). Overview and Discussion of the Social Security Mortality Projections.
Wilmoth, J.R. (1990). Variation in vital rates by age, period, and cohort. Sociological Methodology 20: 295-335.