Statistical methods to compare mortality for a group with non-divergent populations: an application to Spanish regions

Debón, Ana; Montes, Francisco; Martínez-Ruiz, Francisco

doi:10.1007/s13385-011-0043-z

Cited by 21 publications

(14 citation statements)

References 15 publications

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“…In spite of that, these models may still be applied successfully in situations where there are data limitations and more parsimonious models are preferred, or in the study of mortality differentials in populations of a different nature. An example of the later is the application of the stratified Lee-Carter in the modelling of mortality in Spanish regions discussed in Debón et al (2011).…”

Section: Discussionmentioning

confidence: 99%

“…There are two restricted versions of the joint-κ model which are worth exploring as alternatives for modelling mortality differentials: the "common factor" model introduced by Li and Lee (2005) and the stratified or additive Lee-Carter model considered in Butt and Haberman (2009) and in Debón et al (2011). The common factor model, obtained by setting β xg = 0, can be expressed as…”

Section: The Joint K-modelmentioning

confidence: 99%

“…This later model has especially been designed taking into consideration the characteristics of socio-economic subpopulations as well as some of the typical issues of mortality data disaggregated by socio-economic circumstances. Although previous studies have investigated the use of multipopulation mortality models in the assessment of mortality differentials among two countries (Li and Hardy, 2011) and regions within a country (Debón et al, 2011), this is the first study to apply such models to socio-economic mortality differentials in particular. More specifically, we use multipopulation mortality models to analysis the extent of mortality differentials across deprivation subgroups in England.…”

Section: Introductionmentioning

confidence: 99%

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On the Modeling and Forecasting of Socioeconomic Mortality Differentials: An Application to Deprivation and Mortality in England

Villegas

Haberman

2014

North American Actuarial Journal

107

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This is the submitted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractIn any country, mortality rates and indices such as life expectancy usually differ across subpopulations, for example, defined by gender, geographic area or socio-economic variables (e.g. occupation, level of education, income). These differentials, and in particular those related to socio-economic circumstances, pose important challenges for the design of public policies for tackling social inequalities, as well as for the design of pension systems and the management of longevity risk in pension funds and annuity portfolios. We discuss the suitability for the modelling and forecasting of socio-economic differences in mortality of several multiple population extensions of the Lee-Carter model, including a newly introduced relative model based on the modelling of the mortality in socio-economic subpopulations alongside the mortality of a reference population. Using England mortality data for socioeconomic subpopulations defined using a deprivation index, we show that this new relative model exhibits the best results in terms of goodness of fit and ex-post forecasting performance. We then use this model to derive projections of deprivation specific mortality rates and life expectancies at pensioner ages and analyse the impact of socio-economic differences in mortality on the valuation of annuities.

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Section: Discussionmentioning

confidence: 99%

Section: The Joint K-modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On the Modeling and Forecasting of Socioeconomic Mortality Differentials: An Application to Deprivation and Mortality in England

Villegas

Haberman

2014

North American Actuarial Journal

107

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“…Butt and Haberman (2009), Debón et al (2011) Augmented Common Factor and Lee (2005), Li andHardy (2011) Hyndman et al (2013), Li (2012) Augmented Common Factor + Cohorts…”

Section: Russolillo Et Al (2011)mentioning

confidence: 99%

A Comparative Study of Two-Population Models for the Assessment of Basis Risk in Longevity Hedges

Villegas¹,

Haberman²,

Kaishev³

et al. 2017

ASTIN Bull.

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link ABSTRACTLongevity swaps have been one of the major success stories of pension scheme derisking in recent years. However, with some few exceptions, all of the transactions to date have been bespoke longevity swaps based upon the mortality experience of a portfolio of named lives. In order for this market to start to meet its true potential, solutions will ultimately be needed that provide protection for all types of members, are cost effective for large and smaller schemes, are tradable, and enable access to the wider capital markets. Index-based solutions have the potential to meet this need; however concerns remain with these solutions. In particular, the basis risk emerging from the potential mismatch between the underlying forces of mortality for the index reference portfolio and the pension fund/annuity book being hedged is the principal issue that has, to date, prevented many schemes progressing their consideration of index-based solutions. Two-population stochastic mortality models offer an alternative to overcome this obstacle as they allow market participants to compare and project the mortality experience for the reference and target populations and thus assess the amount of demographic basis risk involved in an index-based longevity hedge. In this paper, we systematically assess the suitability of several multi-population stochastic mortality models for assessing basis risks and provide guidelines on how to use these models in practical situations paying particular attention to the data requirements for the appropriate calibration and forecasting of such models.

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“…Modifications are also proposed in Booth et al (2002), Li and Lee (2005) and Debón et al (2011), these proposing modifications to the Lee-Carter method to forecast mortality for a group of countries, taking into account their membership of a group instead of considering them individually. More recently, Czado et al (2005) and Pedroza (2006) introduced a Bayesian estimation of the parameters, the latter by means of state-space models.…”

Section: Lee-carter's Modelmentioning

confidence: 99%

Pricing reverse mortgages in Spain

2013

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In Spain, as in other European countries, the continuous ageing of the population creates a need for long-term care services and their financing. However, in Spain the development of this kind of services is still embryonic. The aim of this article is to obtain a calculation method for reverse mortgages in Spain based on the fit and projection of dynamic tables for Spanish mortality, using the Lee and Carter model. Mortality and life expectancy for the next 20 years are predicted using the fitted model, and confidence intervals are obtained from the prediction errors of parameters for the mortality index of the model. The last part of the article illustrates an application of the results to calculate the reverse mortgage model promoted by the Spanish Instituto de Crédito Oficial (ICO) (Spanish State Financial Agency), for which the authors have developed a computer application.

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Statistical methods to compare mortality for a group with non-divergent populations: an application to Spanish regions

Cited by 21 publications

References 15 publications

On the Modeling and Forecasting of Socioeconomic Mortality Differentials: An Application to Deprivation and Mortality in England

On the Modeling and Forecasting of Socioeconomic Mortality Differentials: An Application to Deprivation and Mortality in England

A Comparative Study of Two-Population Models for the Assessment of Basis Risk in Longevity Hedges

Pricing reverse mortgages in Spain

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