Renshaw, A. E.; Haberman, S. A cohort-based extension to the Lee-Carter model for mortality reduction factors. (English) Zbl 1168.91418 Insur. Math. Econ. 38, No. 3, 556-570 (2006). Summary: The Lee-Carter modelling framework is extended through the introduction of a wider class of generalized, parametric, nonlinear models. This permits the modelling and extrapolation of age-specific cohort effects as well as the more familiar age-specific period effects. The choice of error distribution is generalized. Cited in 186 Documents MSC: 91B30 Risk theory, insurance (MSC2010) 62P05 Applications of statistics to actuarial sciences and financial mathematics Keywords:cohort effects; mortality reduction factors; generalized nonlinear models; time series; mortality projections Software:GLIM PDF BibTeX XML Cite \textit{A. E. Renshaw} and \textit{S. Haberman}, Insur. Math. Econ. 38, No. 3, 556--570 (2006; Zbl 1168.91418) Full Text: DOI References: [1] Alho, J. M., Discussion, North American Actuarial Journal, 4, 91-93 (2000) [2] Booth, P.; Chadburn, R.; Haberman, S.; James, D.; Khorasanee, Z.; Plumb, R.; Rickayzen, B., Modern Actuarial Theory and Practice (2005), CRC Press: CRC Press Boca Raton · Zbl 1076.62107 [3] Brouhns, N.; Denuit, M.; Vermunt, J. K., A Poisson log-bilinear regression approach to the construction of projected life-tables, Insurance: Mathematics and Economics, 31, 373-393 (2002) · Zbl 1074.62524 [4] Brouhns, N.; Denuit, M.; Vermunt, J. K., Measuring the longevity risk in mortality projections, Bulletin of the Swiss Association of Actuaries, 105-130 (2002) · Zbl 1187.62158 [5] CMI Committee, Standard Tables of Mortality Based on the 1991-1994 Experiences. Continuous Mortality Reports, vol. 17 (1999), Institute and Faculty of Actuaries, pp. 1-227 [6] Francis, B.; Green, M.; Payne, C., The Glim System: Release 4 Manual (1993), Clarendon: Clarendon Oxford · Zbl 0835.62005 [7] Goodman, L. A., Simple models for the analysis of association in cross-classifications having ordered categories, Journal of the American Statistics Association, 74, 537-552 (1979) [8] James, I. R.; Segal, M. R., On a method of mortality analysis incorporating age-year interaction, with application to prostate cancer mortality, Biometrics, 38, 433-443 (1982) [9] Lee, R. D.; Carter, L., Modelling and forecasting the time series of US mortality, Journal of the American Statistics Association, 87, 659-671 (1992) [10] Lee, R. D., The Lee-Carter method of forecasting mortality, with various extensions and applications (with discussion), North American Actuarial Journal, 4, 80-93 (2000) · Zbl 1083.62535 [11] Renshaw, A. E.; Haberman, S., Lee-Carter mortality forecasting: a parallel generalised linear modelling approach for England and Wales mortality projections, Applied Statistics, 52, 119-137 (2003) · Zbl 1111.62359 [12] Renshaw, A. E.; Haberman, S., On the forecasting of mortality reduction factors, Insurance: Mathematics and Economics, 32, 379-401 (2003) · Zbl 1025.62041 [13] Tuljapurkar, S.; Li, N.; Boe, C., A universal pattern of mortality decline in the G7 countries, Nature, 405, 789-792 (2000) [14] Willets, R. C., The cohort effect: insights and explanations, British Actuarial Journal, 10, 833-877 (2004) This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.