Smoothing and forecasting mortality rates

By Iain D. Currie, María Durbán, Paul H. C. Eilers. 2004

465 citations recorded by the source corpus.

Subfields: Demography, Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/24fb51942f36ea4e4729715d0fb82b760a59349d

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Citations in the corpus

Twenty years of P-splines (2015, methodology): “Fortunately, by rearranging the calculations, one can avoid the explicit Kronecker products and gain orders of magnitudes in computation speed and memory use (Currie et al., 2006; Eilers et al., 2006). This array algorithm, so-called GLAM, allows arbitrary weights and so is suitable for generalized ”
Smoothing the Lee–Carter and Poisson log-bilinear models for mortality forecasting (2007, methodology): “The final Section 5 concludes with a comparison with other possible approaches, including the P-spline method proposed by Durban et al. (2004) and Bayesian models worked out in Czado et al. (2005) and Girosi and King (in press).”
Mortality Modelling and Forecasting: a Review of Methods (2008, methodology): “In an alternative approach using the GLM framework, Currie et al. (2004) employed p-splines (penalised b-splines) to impose smoothness on the age-period surface of the force of mortality.”
Pricing of Ratchet Equity-Indexed Annuities under Stochastic Interest Rates ? (2007, background): “However, many studies suggest that mortality risk is systematic in the long run and is therefore non-diversifiable; e.g., see Currie et al. (2004).”
Pricing Death: Frameworks for the Valuation and Securitization of Mortality Risk* (2006, methodology): “Figure 1.1: Fitted values using P-splines for the force of mortality ^ „(t;x) for the years t = 1947 to 1999 and for ages x = 11 to 100 from Currie, Durban and Eilers, 2004 .”
Robust forecasting of mortality and fertility rates: A functional data approach (2007, methodology): “Currie et al. (2004) employ bivariate penalized B-splines to smooth the mortality surface in both the time and age direction.”
Understanding, modelling and managing longevity risk: key issues and main challenges (2012, methodology): “Yet, in the periodic approach of mortality modelling (spot mortality rates), some authors (Schrager (2006) and Dahl (2004) or Biffis (2005)) introduce the so-called intensity framework to stochastic mortality modelling, which is very popular both in interest rate and credit risk modelling.”
Modelling function‐valued stochastic processes, with applications to fertility dynamics (2017, methodology): “In related applications such as mortality analysis, the decomposition into age and year has been studied by Eilers and Marx (2003), Currie et al. (2004, 2006) and Eilers et al. (2006), by using P-splines.”
P-spline ANOVA-type interaction models for spatio-temporal smoothing (2011, methodology): “Recent papers outline the use of these methods in several applications for Gaussian and non-Gaussian responses in one or more dimensions (see, e.g., Currie et al., 2004).”
Living with Mortality: Longevity Bonds and Other Mortality-Linked Securities (2006, methodology): “Examples of smoothing techniques can be found in Currie et al. (2004), and Forfar et al. (1988). The use of smoothing techniques exploits the fact that adjacent ages (and also calendar years) are subject to very similar rates of mortality.”
Demographic forecasting: 1980 to 2005 in review (2006, methodology): “Regression models are easily extended to three factors, but (as noted above) ageperiod-cohort (APC) models must accommodate the identification problem (see also Van Hoorn & De Beer, 2001). To address this, Wilmoth (1990) developed a modified model involving additive age and period effects and severa”
The New Life Market (2013, unknown): “44 Finally, there is the P-splines model (Currie et al., 2004) which assumes smoothness across both years and ages.”