A Poisson log-bilinear regression approach to the construction of projected lifetables

N. Brouhns, M. Denuit, J.K. Vermunt

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Abstract

This paper implements Wilmoth's [Computational methods for fitting and extrapolating the Lee¿Carter model of mortality change, Technical report, Department of Demography, University of California, Berkeley] and Alho's [North American Actuarial Journal 4 (2000) 91] recommendation for improving the Lee¿Carter approach to the forecasting of demographic components. Specifically, the original method is embedded in a Poisson regression model, which is perfectly suited for age¿sex-specific mortality rates. This model is fitted for each sex to a set of age-specific Belgian death rates. A time-varying index of mortality is forecasted in an ARIMA framework. These forecasts are used to generate projected age-specific mortality rates, life expectancies and life annuities net single premiums. Finally, a Brass-type relational model is proposed to adapt the projections to the annuitants population, allowing for estimating the cost of adverse selection in the Belgian whole life annuity market.
Original languageEnglish
Pages (from-to)373-393
JournalInsurance: Mathematics & Economics
Volume31
Issue number3
Publication statusPublished - 2002

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Life Table
Mortality Rate
Mortality
Siméon Denis Poisson
Regression
Adverse Selection
Demography
ARIMA
Life Expectancy
Poisson Regression
Relational Model
Poisson Model
Computational Methods
Forecast
Forecasting
Recommendations
Regression Model
Time-varying
Projection
Costs

Cite this

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title = "A Poisson log-bilinear regression approach to the construction of projected lifetables",
abstract = "This paper implements Wilmoth's [Computational methods for fitting and extrapolating the Lee¿Carter model of mortality change, Technical report, Department of Demography, University of California, Berkeley] and Alho's [North American Actuarial Journal 4 (2000) 91] recommendation for improving the Lee¿Carter approach to the forecasting of demographic components. Specifically, the original method is embedded in a Poisson regression model, which is perfectly suited for age¿sex-specific mortality rates. This model is fitted for each sex to a set of age-specific Belgian death rates. A time-varying index of mortality is forecasted in an ARIMA framework. These forecasts are used to generate projected age-specific mortality rates, life expectancies and life annuities net single premiums. Finally, a Brass-type relational model is proposed to adapt the projections to the annuitants population, allowing for estimating the cost of adverse selection in the Belgian whole life annuity market.",
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A Poisson log-bilinear regression approach to the construction of projected lifetables. / Brouhns, N.; Denuit, M.; Vermunt, J.K.

In: Insurance: Mathematics & Economics, Vol. 31, No. 3, 2002, p. 373-393.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - A Poisson log-bilinear regression approach to the construction of projected lifetables

AU - Brouhns, N.

AU - Denuit, M.

AU - Vermunt, J.K.

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AB - This paper implements Wilmoth's [Computational methods for fitting and extrapolating the Lee¿Carter model of mortality change, Technical report, Department of Demography, University of California, Berkeley] and Alho's [North American Actuarial Journal 4 (2000) 91] recommendation for improving the Lee¿Carter approach to the forecasting of demographic components. Specifically, the original method is embedded in a Poisson regression model, which is perfectly suited for age¿sex-specific mortality rates. This model is fitted for each sex to a set of age-specific Belgian death rates. A time-varying index of mortality is forecasted in an ARIMA framework. These forecasts are used to generate projected age-specific mortality rates, life expectancies and life annuities net single premiums. Finally, a Brass-type relational model is proposed to adapt the projections to the annuitants population, allowing for estimating the cost of adverse selection in the Belgian whole life annuity market.

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JF - Insurance: Mathematics & Economics

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