Enchev, Vasil; Kleinow, Torsten; Cairns, Andrew J. G. Multi-population mortality models: fitting, forecasting and comparisons. (English) Zbl 1401.62206 Scand. Actuar. J. 2017, No. 4, 319-342 (2017). Summary: We review a number of multi-population mortality models: variations of the Li & Lee model, and the common-age-effect (CAE) model of Kleinow. Model parameters are estimated using maximum likelihood. Although this introduces some challenging identifiability problems and complicates the estimation process it allows a fair comparison of the different models. We propose to solve these identifiability problems by applying two-dimensional constraints over the parameters. Using data from six countries, we compare and rank, both visually and numerically, the models’ fitting qualities and develop forecasting models that produce non-diverging, joint mortality rate scenarios. It is found that the CAE model fits best. But we also find that the Li and Lee model potentially suffers from robustness problems when calibrated using maximum likelihood. Cited in 17 Documents MSC: 62P05 Applications of statistics to actuarial sciences and financial mathematics 62P25 Applications of statistics to social sciences 91B30 Risk theory, insurance (MSC2010) 91D20 Mathematical geography and demography Keywords:stochastic mortality model; multi-population; Li and Lee model; common age effect model PDF BibTeX XML Cite \textit{V. Enchev} et al., Scand. Actuar. J. 2017, No. 4, 319--342 (2017; Zbl 1401.62206) Full Text: DOI OpenURL References: [1] Brouhns, N., Denuit, M. & Vermunt, J. K. (2002). A poisson log-bilinear regression approach to the construction of projected lifetables. Insurance: Mathematics and Economics 31, 373-393. · Zbl 1074.62524 [2] Cairns, A. J. G., Blake, D. & Dowd, K. (2006). A two-factor model for stochastic mortality with parameter uncertainity: theory and calibration. The Journal of Risk and Insurance 73(4), 687-718. [3] Cairns, A. J. G., Blake, D., Dowd, K., Coughlan, G. D., Epstein, D., Ong, A. & Balevich, I. (2009). A quantative comparison of stochastic mortality model using data from england and wales and the united states. North American Actuarial Journal 13(1). [4] Cairns, A. J. G., Blake, D., Dowd, K., Coughlan, G. D. & Khalaf-Allah, M. (2011). Stochastic mortality modelling for two populations. ASTIN Bulletin 41(4), 29-55. · Zbl 1228.91032 [5] Danesi, I. L., Haberman, S. & Millossovich, P. (2015). Forecasting mortality in subpopu- lations using leecarter type models: a comparison. Insurance: Mathematics and Economics 62, 151-161. · Zbl 1318.91109 [6] Haberman, S., Kaishev, V., Millosovich, P., Villegas, A., Baxter, S. & Baxter, S., (2014). Longevity basis risk: a methodology for assessing basis risk. Sessional meeting of the Institute and Faculty of Actuaries. Available online at: https://www.actuaries.org.uk/documents/longevity-basis-risk-methodology-assessing-basis-risk [7] Kleinow, T. (2015). A common age effect model for the mortality of multiple populationsInsurance: Mathematics and Economics 63, 147-152. · Zbl 1348.91233 [8] Lee, R. D. & Carter, L. R. (1992). Modeling and forecasting u.s. mortality. Journal of the American Statistical Association 87, 659-675. · Zbl 1351.62186 [9] Lee, R. & Miller, T. (2001). Evaluating the performance of the Lee-Carter method for forecasting mortality. Demography 38(4), 537-549. [10] Li, J. (2013). A poisson common factor model for projecting mortality and life expectancy jointly for females and males. Population Studies: A Journal of Demography 67(1), 111-126. [11] Li, N. & Lee, R. (2005). Coherent mortality forecasts for a group of populations: an extension of the Lee-Carter method. Demography 42(3), 575-594. [12] Li, J. S.-H., Zhou, R. & Hardy, M. (2015). A step-by-step guide to building two- population stochastic mortality models. Insurance: Mathematics and Economics 63, 121-134. · Zbl 1348.91164 [13] OECD. (2011). Health at a glance 2011: OECD Indicators, OECD Publishing. http://dx.doi.org/10.1787/health_glance-2011-en [14] Oeppen, J. & Vaupel, J. (2002). Broken limits to life expectancy. Science 296, 1029-1031. [15] Olshansky, S. J., Passaro, D. J., Hershow, R. C., Layden, J., Carnes, B. A., Brody, J., Hayflick, L., Butler, R. N., Allison, D. B. & Ludwig, D. S. (2005). A potential decline in life expectancy in the united states in the 21st century. New England Journal of Medicine 352(11), 1138-1145. 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.