Volume 25 - Article 5 | Pages 173–214  

Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods

By Han Lin Shang, Heather Booth, Rob Hyndman

References

Alho, J.M. (1998). A stochastic forecast of the population of Finland. Helsinki, Finland: Statistics Finland (Reviews 1998/4).

Download reference:

Alho, J.M. (1997). Scenarios, uncertainty and conditional forecasts of the world population. Journal of the Royal Statistical Society: Series A 160(1): 71-85.

Weblink:
Download reference:

Alho, J.M. and Spencer, B.D. (2005). Statistical Demography and Forecasting. New York: Springer.

Download reference:

Bengtsson, T. (2003). The need for looking far back in time when predicting future mortality trends. In: Bengtsson, T. and Keilman, N. (eds.). Perspectives on mortality forecasting, Vol. 1. Swedish National Social Insurance Agency.

Download reference:

Bongaarts, J. (2005). Long-range trends in adult mortality: Models and projection methods. Demography 42(1): 23-49.

Weblink:
Download reference:

Booth, H. (2006). Demographic forecasting: 1980 to 2005 in review. International Journal of Forecasting 22(3): 547-581.

Weblink:
Download reference:

Booth, H., Hyndman, R.J., Tickle, L., and De Jong, P. (2006). Lee-Carter mortality forecasting: A multi-country comparison of variants and extensions. Demographic Research 15(9): 289-310.

Weblink:
Download reference:

Booth, H., Maindonald, J., and Smith, L. (2002). Applying Lee-Carter under conditions of variable mortality decline. Population Studies 56(3): 325-336.

Weblink:
Download reference:

Booth, H. and Tickle, L. (2008). Mortality modelling and forecasting: A review of methods. Annals of Actuarial Science 3(1-2): 3-43.

Weblink:
Download reference:

Booth, H., Tickle, L., and Smith, L. (2005). Evaluation of the variants of the Lee-Carter method of forecasting mortality: A multi-country comparison. New Zealand Population Review 31(1): 13-34.

Download reference:

Brouhns, N., Denuit, M., and Van Keilegom, I. (2005). Bootstrapping the Poisson log-bilinear model for mortality forecasting. Scandinavian Actuarial Journal 2005(3): 212-224.

Weblink:
Download reference:

Brouhns, N., Denuit, M., and Vermunt, J.K. (2002). A Poission log-bilinear regression approach to the construction of projected lifetables. Insurance: Mathematics and Economics 31(3): 373-393.

Weblink:
Download reference:

Cairns, A.J.G. (2000). A discussion of parameter and model uncertainty in insurance. Insurance: Mathematics and Economics 27(3): 313-330.

Weblink:
Download reference:

Cairns, A.J.G., Blake, D., Dowd, K., Coughlan, G.D., Epstein, D., and Khalaf-Allah, M. (2011). Mortality density forecasts: An analysis of six stochastic mortality models. Insurance: Mathematics and Economics 48(3): 355-367.

Weblink:
Download reference:

Cardot, H., Ferraty, F., and Sarda, P. (2003). Spline estimators for the functional linear model. Statistica Sinica 13(3): 571-591.

Download reference:

Carter, L.R. and Prskawetz, A. (2001). Examining structural shifts in mortality using the Lee-Carter method. Rostock: Max Planck Institute for Demographic Research (Working paper, 2001-007).

Chatfield, C. (1993). Calculating interval forecasts. Journal of Business & Economic Statistics 11(2): 121-135.

Weblink:
Download reference:

Chatfield, C. (2000). Time-Series Forecasting. Boca Raton, Florida: Chapman & Hall/CRC.

Weblink:
Download reference:

Currie, I.D., Durban, M., and Eilers, P.H.C. (2004). Smoothing and forecasting mortality rates. Statistical Modelling 4(4): 279-298.

Weblink:
Download reference:

De Jong, P. and Tickle, L. (2006). Extending Lee-Carter mortality forecasting. Mathematical Population Studies 13(1): 1-18.

Weblink:
Download reference:

Debón, A., Montes, F., and Sala, R. (2006). A comparison of models for dynamic life tables. Application to mortality data from the Valencia Region (Spain). Lifetime Data Analysis 12(2): 223-244.

Weblink:
Download reference:

Ediev, D.M. (2008). Extrapolative projections of mortality: Towards a more consistent method. Vienna Institute of Demography (Working paper, 3/2008).

Erbas, B., Hyndman, R.J., and Gertig, D.M. (2007). Forecasting age-specific breast cancer mortality using functional data models. Statistics in Medicine 26(2): 458-470.

Weblink:
Download reference:

Felipe, A., Guillén, M., and Pérez-Marín, A.M. (2002). Recent mortality trends in the Spanish population. British Actuarial Journal 8(4): 757-786.

Download reference:

Girosi, F. and King, G. (2008). Demographic Forecasting. Princeton: Princeton University Press.

Download reference:

Haberman, S. and Renshaw, A. (2008). Mortality, longevity and experiments with the Lee-Carter model. Lifetime Data Analysis 14(3): 286-315.

Weblink:
Download reference:

Hubert, M., Rousseeuw, P.J., and Verboven, S. (2002). A fast method of robust principal components with applications to chemometrics. Chemometrics and Intelligent Laboratory Systems 60(1-2): 101-111.

Weblink:
Download reference:

Human Mortality Database (2009). University of California, Berkeley (USA), and Max Planck Institute for Demographic Research (Germany).

Weblink:
Download reference:

Hyndman, R.J. (2011). Demography: Forecasting mortality, fertility, migration and population data. (with contributions from Heather Booth and Leonie Tickle and John Maindonald, R package version 1.09-1) [electronic resource].

Weblink:
Download reference:

Hyndman, R.J. and Booth, H. (2008). Stochastic population forecasts using functional data models for mortality, fertility and migration. International Journal of Forecasting 24(3): 323-342.

Weblink:
Download reference:

Hyndman, R.J. and Khandakar, Y. (2008). Automatic time series forecasting: The forecast package for R. Journal of Statistical Software 27(3).

Download reference:

Hyndman, R.J., Koehler, A.B., Ord, J.K., and Snyder, R.D. (2008). Forecasting with Exponential Smoothing: The State Space Approach. Berlin: Springer.

Weblink:
Download reference:

Hyndman, R.J. and Shang, H.L. (2009). Forecasting functional time series (with discussion). Journal of the Korean Statistical Society 38(3): 199-221.

Weblink:
Download reference:

Hyndman, R.J. and Ullah, M.S. (2007). Robust forecasting of mortality and fertility rates: A functional data approach. Computational Statistics & Data Analysis 51(10): 4942-4956.

Weblink:
Download reference:

Keilman, N., Pham, D., and Hetland, A. (2002). Why population forecasts should be probabilistic - illustrated by the case of Norway. Demographic Research 6(15): 409-454.

Weblink:
Download reference:

Koissi, M.-C., Shapiro, A.F., and Högnäs, G. (2006). Evaluating and extending the Lee-Carter model for mortality forecasting: Bootstrap confidence interval. Insurance: Mathematics and Economics 38(1): 1-20.

Weblink:
Download reference:

Lazar, D. and Denuit, M.M. (2009). A multivariate time series approach to projected life tables. Applied Stochastic Models in Business and Industry 25(6): 806-823.

Weblink:
Download reference:

Lee, R.D. and Carter, L.R. (1992). Modeling and forecasting U.S. mortality. Journal of the American Statistical Association 87(419): 659-671.

Weblink:
Download reference:

Lee, R.D. and Miller, T. (2001). Evaluating the performance of the Lee-Carter method for forecasting mortality. Demography 38(4): 537-549.

Weblink:
Download reference:

Lee, R.D. and Nault, F. (1993). Modeling and forecasting provincial mortality in Canada. Paper presented at the World Congress of the International Union for the Scientific Study of Population, Montreal, Canada.

Download reference:

Lee, R.D. and Rofman, R. (1994). Modeling and projecting mortality in Chile. Notas de Poblacion 22(59): 183-213.

Download reference:

Lin, J. (1995). Changing kinship structure and its implications for old-age support in urban and rural China. Population Studies 49(1): 127-145.

Weblink:
Download reference:

Lundström, H. and Qvist, J. (2004). Mortality forecasting and trend shifts: An application of the Lee-Carter model to Swedish mortality data. International Statistical Review/Revue Internationale de Statistique 72(1): 37-50.

Weblink:
Download reference:

Lutz, W. and Goldstein, J.R. (2004). Introduction: How to deal with uncertainty in population forecasting? International Statistical Review/Revue Internationale de Statistique 72(1): 1-4.

Weblink:
Download reference:

Oeppen, J. and Vaupel, J.W. (2002). Broken limits to life expectancy. Science 296(5570): 1029-1031.

Weblink:
Download reference:

Ramsay, J.O. (1988). Monotone regression splines in action. Statistical Science 3(4): 425-441.

Weblink:
Download reference:

Ramsay, J.O. and Silverman, B.W. (2005). Functional Data Analysis, 2nd. New York: Springer.

Weblink:
Download reference:

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.

Weblink:
Download reference:

Renshaw, A.E. and Haberman, S. (2003b). Lee-Carter mortality forecasting with age-specific enhancement. Insurance: Mathematics and Economics 33(2): 255-272.

Weblink:
Download reference:

Renshaw, A.E. and Haberman, S. (2003a). Lee-Carter mortality forecasting: A parallel generalized linear modelling approach for England and Wales mortality projections. Journal of the Royal Statistical Society: Series C 52(1): 119-137.

Weblink:
Download reference:

Renshaw, A.E. and Haberman, S. (2008). On simulation-based approaches to risk measurement in mortality with specific reference to Poisson Lee-Carter modelling. Insurance: Mathematics and Economics 42(2): 797-816.

Weblink:
Download reference:

Renshaw, A.E. and Haberman, S. (2003c). On the forecasting of mortality reduction factors. Insurance: Mathematics and Economics 32(3): 379-401.

Weblink:
Download reference:

Swanson, D.A. and Beck, D.M. (1994). A new short-term county population projection method. Journal of Economic and Social Measurement 20(1): 25-50.

Download reference:

Tayman, J., Schafer, E., and Carter, L. (1998). The role of population size in the determination and prediction of population forecast errors: An evaluation using confidence intervals for subcounty areas. Population Research and Policy Review 17(1): 1-20.

Weblink:
Download reference:

Tayman, J., Smith, S.K., and Lin, J. (2007). Precision, bias, and uncertainty for state population forecasts: An exploratory analysis of time series models. Population Research and Policy Review 26(3): 347-369.

Weblink:
Download reference:

Tuljapurkar, S. (2005). Stochastic forecasts of mortality, population, and pension systems. In: Keilman, N. (ed.). Perspectives on Mortality Forecasting. II: Probabilistic Models. Stockholm: Swedish Social Insurance Agency: 65-77.

Download reference:

Tuljapurkar, S., Li, N., and Boe, C. (2000). A universal pattern of mortality decline in the G7 countries. Nature 405(6788): 789-792.

Weblink:
Download reference:

White, K.M. (2002). Longevity advances in high-income countries, 1955-96. Population and Development Review 28(1): 59-76.

Weblink:
Download reference:

Wilmoth, J.R. (1996). Mortality projections for Japan: A comparison of four methods. In: Caselli, G. and Lopez, A.D. (eds.). Health and Mortality among Elderly Populations. Oxford: Clarendon Press: 266-287.

Download reference:

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