Modeling and forecasting mortality rates

Mitchell, Daniel; Brockett, Patrick L.; Mendoza-Arriaga, Rafael; Muthuraman, Kumar

doi:10.1016/j.insmatheco.2013.01.002

Cited by 85 publications

(91 citation statements)

References 19 publications

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“…The general population mortality rate gradually decreases over time, reflecting the projected mortality (life expectancy) using birth cohorts and the Lee-Carter model as estimated by Statistics Canada. 26 This means that the projected mortality for people with MS decreased at the same rate as for Canadians living without MS, largely consistent with observations in British Columbia. 27 Using the BC administrative data prevalence cohort, we examined the number of deaths among individuals with MS, and compared it to the death rate among individuals without a neurological condition.…”

Section: Ms Status: Incidencesupporting

confidence: 81%

Multiple sclerosis in Canada 2011 to 2031: results of a microsimulation modelling study of epidemiological and economic impacts

Amankwah

Marrie

Bancej

et al. 2017

Health Promot Chronic Dis Prev Can

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Section: Ms Status: Incidencesupporting

confidence: 81%

Multiple sclerosis in Canada 2011 to 2031: results of a microsimulation modelling study of epidemiological and economic impacts

Amankwah

Marrie

Bancej

et al. 2017

Health Promot Chronic Dis Prev Can

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“…Tuljapurkar, Li, and Boe (2000) use the observed long-term linear mortality decline in the G7 countries on the logarithmic scale to justify the modeling of log-linear mortality forecasts. If we found support for our hypothesis of (almost) linear variance to mean relationships for death rates and their rates of change, TL might also justify linear assumptions for forecasting models relying on the change of mortality (Mitchell et al 2013;Haberman and Renshaw 2012;Bohk and Rau 2014).…”

Section: Hypothesismentioning

confidence: 56%

Taylor's power law in human mortality

Bohk¹,

Rau²,

Cohen³

2015

DemRes

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“…As these strong constraints are implausible, large errors in the forecasts generated are likely, especially in the long run. Mitchell (2013) and Haberman and Renshaw (2012) tried to overcome this inflexibility by taking (and extending) the predictor structure of the original Lee-Carter model in order to forecast the rates of mortality improvement instead of the death rates. This procedure allowed them to capture relative mortality changes more flexibly and to model dynamic age shifts, which is one reason why we also have chosen to use the rates of mortality improvement in our mortality forecasting model.…”

Section: Russiamentioning

confidence: 99%

“…Recently developed approaches have attempted to overcome these shortcomings. For instance, Mitchell (2013) and Haberman and Renshaw (2012) suggested forecasting the rates of mortality improvement (rather than the death rates) in order to model flexible changes in survival over age and time. Li and Lee (2005) and Cairns et al (2011) recommended jointly forecasting the mortality of multiple (sub)populations in so-called coherent mortality forecasts, which allows the user to adjust the mortality trend in each country using mortality information of other countries.…”

Section: Summary and Concluding Remarksmentioning

confidence: 99%

Impact of Economic Conditions and Crises on Mortality and its Predictability

Bohk

Rau

2016

Social Demography Forschung an Der Schnittstelle Von Soziologie Und Demografie

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To investigate how economic conditions and crises affect mortality and its predictability in industrialized countries, we review the related literature, and we forecast mortality developments in Spain, Hungary, and Russia-three countries which have recently undergone major transformation processes following the introduction of radical economic and political reforms. The results of our retrospective mortality forecasts from 1991 to 2009 suggest that our model can capture major changes in long-term mortality trends, and that the forecast errors it generates are usually smaller than those of other well-accepted models, like the Lee-Carter model and its coherent variant. This is because our approach is capable of modeling (1) dynamic shifts in survival improvements from younger to older ages over time, as well as (2) substantial changes in long-term trends by optionally complementing the extrapolated mortality trends in a country of interest with those of selected reference countries. However, the forecasting performance of our model is limited (like that of every model): e.g., if mortality becomes extremely volatile-as was the case in Russia after the dissolution of the Soviet Union-generating a precise forecast will depend more on luck than on methodology and expert judgment. In general, we conclude that, on their own, recent economic changes appear to have minor effects on life expectancy in industrialized countries, but that the effects of these changes are greater if they occur in conjunction with other major social and political changes. Keywords

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Modeling and forecasting mortality rates

Cited by 85 publications

References 19 publications

Multiple sclerosis in Canada 2011 to 2031: results of a microsimulation modelling study of epidemiological and economic impacts

Multiple sclerosis in Canada 2011 to 2031: results of a microsimulation modelling study of epidemiological and economic impacts

Taylor's power law in human mortality

Impact of Economic Conditions and Crises on Mortality and its Predictability

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