Forecasting Changes in Mortality

Gutterman, Sam; Vanderhoof, Irwin T.

doi:10.1080/10920277.1998.10595759

Cited by 29 publications

(2 citation statements)

References 2 publications

(2 reference statements)

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“…Despite being widely used and performing adequately, the Lee-Carter model has several drawbacks (Lee, 2000). Researchers like Gutterman and Vanderhoof (1999) have criticized these shortcomings. Given that the authors might not have anticipated some of these limitations, it seems like a good moment to compare the Lee-Carter strategy with alternative approaches.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Lee Carter and Arch Model in Modelling Female Mortality in Nigeria

Shelleng

Sule²,

Kajuru

et al. 2022

USci

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Using Nigeria mortality data from 2009 to 2020, this study compares and contrasts how well the Lee-Carter and ARCH models performed. Singular value decomposition (SVD) method, Langrage multiplier test, and autoregressive conditional heteroskedasticity (ARCH) effects were examined. Five (5) different ARIMA and ARCH models were fitted together with their criteria, i.e., AIC and BIC in order to determine the best model for Nigeria mortality data. ARIMA (0,1,0) had the lowest AIC and BIC values, and was determined to be the best ARIMA model. The mortality index is then modelled using ARIMA (0,1,0) and plugged back into the Lee-Carter model to predict the future mortality rate. Also ARCH (1) turned out to be the best ARCH model among other candidate models. The performance of Lee-Carter model and ARCH model was compared using error measures. Results obtained revealed that the ARCH model had the minimum RMSE and MAPE when compared with the Lee-carter model, therefore it was concluded that the ARCH model performs better than the Lee-Carter model on Nigeria mortality data.

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Section: Introductionmentioning

confidence: 99%

Comparative Study of Lee Carter and Arch Model in Modelling Female Mortality in Nigeria

Shelleng

Sule²,

Kajuru

et al. 2022

USci

View full text Add to dashboard Cite

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“…An alternative approach that has been considered in the literature is to construct all-cause mortality projections based on cause-specific mortality experience. Though some literature states the merits of mortality forecasts based on cause-of-death mortality data (Tabeau et al 1999), several studies have discussed potential drawbacks of this approach (Wilmoth, 1995;Gutterman and Vanderhoof 1998;Booth and Tickle 2008). The main concerns are inferior data quality and availability, and the complex dependence structure between causes.…”

Section: Introductionmentioning

confidence: 99%

A Multi-population Approach to Forecasting All-Cause Mortality Using Cause-of-Death Mortality Data

Lyu

Waegenaere

Melenberg

2020

North American Actuarial Journal

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All-cause mortality is driven by various types of cause-specific mortality. Projecting all-cause mortality based on cause-ofdeath mortality allows one to understand the drivers of the recent changes in all-cause mortality. However, the existing literature has argued that all-cause mortality projections based on cause-specific mortality experience have a number of serious drawbacks, including the inferior cause-of-death mortality data and the complex dependence structure between causes of death. In this article, we use the recent World Health Organization causes-of-death data to address this issue in a multipopulation context. We construct a new model in the spirit of N. Li and Lee (2005) but in terms of cause-specific mortality. A new two-step beta convergence test is used to capture the cause-specific mortality dynamics between different countries and between different causes. We show that the all-cause mortality estimations produced by the new model perform in the sample similarly to the estimations by the Lee-Carter and Li-Lee all-cause mortality models. However, in contrast to results from earlier studies, we find that the all-cause mortality projections of the new model have better out-of-sample performance in a long forecast horizon. Moreover, for the case of The Netherlands, an approximately 1-year higher remaining life expectancy projection for a 67-year-old Dutch male in a 30-year forecast horizon is obtained by this new model, compared to the all-cause Li-Lee mortality model.

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