A Poisson log-bilinear regression approach to the construction of projected lifetables
By Natacha Brouhns, Michel Denuit, Jeroen K. Vermunt. 2002
752 citations recorded by the source corpus.
Subfields: Demography, General Health Professions, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/f544cf1c14a9882656157490f8e997f78c6c9f9b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Demography
- Andrew J. G. Cairns
- H. Booth
- Kevin Dowd
- Elena Vigna
- David P. Blake
- Johnny Siu-Hang Li
- Mary R. Hardy
- L. Tickle
In General Health Professions
- Andrew J. G. Cairns
- Johnny Siu-Hang Li
- Mary R. Hardy
- Kevin Dowd
- Elena Vigna
- David P. Blake
- Zoltan Butt
- Steven Haberman
In Management Science and Operations Research
- L. Tickle
- H. Booth
- Michel Denuit
- Paul H. C. Eilers
- Kevin Dowd
- Antoine Delwarde
- David P. Blake
- Mary R. Hardy
Citations in the corpus
- Smoothing and forecasting mortality rates (2004, methodology): “We follow Brouhns et al. (2002) and fit the model by maximum likelihood.”
- Mortality Modelling and Forecasting: a Review of Methods (2008, methodology): “He also developed a maximum likelihood estimation solution based on the assumption of a Poisson distribution of deaths; this Poisson log-bilinear model has subsequently been implemented by others (e.g. Brouhns et al., 2002; Czado et al., 2005; Koissi et al., 2006).”
- A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States (2009, methodology): “We will model the number of deaths using the Poisson model commonly employed in the literature on mortality modeling: we assume D(t, x) has a Poisson distribution with mean E(t, x) m(t, x) (or D(t, x) Po(E(t, x)m(t, x))); see, for example, Brouhns et al. (2002).”
- Demographic forecasting: 1980 to 2005 in review (2006, background): “Brouhns, Denuit, and Vermunt (2002) proposed a similar bilinear approach in which the Lee–Carter model forms the systematic component (predictor) in the Poisson error setting (cf Wilmoth, 1993).”
- Longevity risk in portfolios of pension annuities (2008, methodology): “Several extensions and modifications to the methodology originally developed by Lee and Carter (1992) have been proposed, e.g. Renshaw and Haberman (2003) and Brouhns et al. (2002, 2005).”
- Measuring Basis Risk in Longevity Hedges (2011, methodology): “Alternatively the model parameters can be estimated by the method of maximum likelihood (Wilmoth 1993; Brouhns et al. 2002) or by Markov chain Monte Carlo (Czedo et al. 2005).”
- The New Life Market (2013, neutral): “45 Other academic studies of mortality models include Booth et al. (2002a,b), Brouhns et al. (2002, 2004), Biffis (2005), Czado et al. (2005), Koissi et al. (2005), Renshaw and Haberman (2006), Delwarde et al. (2007), Blake et al. (2008b), Bauer et al. (2008, 2010a), Hari et al. (2008), Hatzopoulos…”
- Mortality-Indexed Annuities Managing Longevity Risk Via Product Design (2011, background): “Among numerous proposed extensions (see, e.g., Lee 2000 or Renshaw and Haberman 2003) an approach presented by Brouhns et al. (2002) resorts to the notion that the number of deaths can be regarded as a Poisson counting process.”
- A Two-Factor Model for Stochastic Mortality With Parameter Uncertainty: Theory and Calibration (2006, positive): “Aggregate mortality rates are, at best, measured annually and for this reason Lee and Carter (1992) and later authors who adopted a similar approach (see, for example, Brouhns, Denuit, and Vermunt, 2002; Renshaw and Haberman, 2003; Currie, Durban, and Eilers, 2004) worked in discrete time.”
- Stochastic portfolio specific mortality and the quantification of mortality basis risk (2009, methodology): “JEL classification: G22; G23 Subject classification: IM10; IE43; IB10 Keywords: portfolio specific mortality, stochastic mortality models, mortality basis risk, longevity risk, Solvency 2”
- A comparative study of parametric mortality projection models (2011, methodology): “Similarly, the LC2 predictor, which is also non-linear in the parameters, is fitted using an obvious expansion of the suitably adjusted LC fitting algorithm (Brouhns et al. (2002), Renshaw and Haberman (2003)).”
- Smoothing the Lee–Carter and Poisson log-bilinear models for mortality forecasting (2007, methodology): “…(2003b) and the method proposed by Brouhns et al. (2002a, 2002b): the difference centres on the interpretation of time, which in the Lee–Carter and Brouhns et al. (2002a, 2002b) approach is modelled as a factor and under the approach proposed by Renshaw and Haberman (2003b) is modelled as a…”