Search results for "Lee–Carter"

showing 3 items of 3 documents

Do different models induce changes in mortality indicators? That is a key question for extending the Lee-Carter model

2021

[EN] The parametric model introduced by Lee and Carter in 1992 for modeling mortality rates in the USA was a seminal development in forecasting life expectancies and has been widely used since then. Different extensions of this model, using different hypotheses about the data, constraints on the parameters, and appropriate methods have led to improvements in the model's fit to historical data and the model's forecasting of the future. This paper's main objective is to evaluate if differences between models are reflected in different mortality indicators' forecasts. To this end, nine sets of indicator predictions were generated by crossing three models and three block-bootstrap samples with …

Health Toxicology and MutagenesisPopulationESTADISTICA E INVESTIGACION OPERATIVALee–Carter modellcsh:MedicineSample (statistics)forecastingHG01 natural sciencesArticle010104 statistics & probabilityLife ExpectancyMortality indicators0502 economics and businessEconometrics0101 mathematicsMortalityeducationBlock-bootstrapMathematicsProbabilityfunctional ANOVAeducation.field_of_study050208 financeModels StatisticalLee Carter models block-bootstrap functional ANOVA forecasting mortality indicatorsMortality rate05 social scienceslcsh:RPublic Health Environmental and Occupational Healthblock-bootstrapFunctional ANOVAMortality dataParametric modelmortality indicatorsAnalysis of varianceLee-Carter modelsForecasting
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Modelling and forecasting mortality in Spain

2008

[EN] Experience shows that static life tables overestimate death probabilities. As a consequence of this overestimation the premiums for annuities, pensions and life insurance are not what they actually should be, with negative effects for insurance companies or policy-holders. The reason for this overestimation is that static life tables, through being computed for a specific period of time, cannot take into account the decreasing mortality trend over time. Dynamic life tables overcome this problem by incorporating the influence of the calendar when graduating mortality. Recent papers on the topic look for the development of new methods to deal with this dynamism. Most methods used in dyna…

Information Systems and ManagementLee–CarterGeneral Computer ScienceESTADISTICA E INVESTIGACION OPERATIVAManagement Science and Operations ResearchLee carterIndustrial and Manufacturing EngineeringDynamic life tablesMortality dataModeling and SimulationLife insuranceEconomicsEconometricsStatistical analysisDynamismBootstrap confidence intervalParametric statisticsForecastingBootstrap confidence intervals
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Temporal evolution of some mortality indicators: Application to Spanish data

2012

[EN] In Spain, as in other developed countries, significant changes in mortality patterns have occurred during the 20th and 21st centuries. One reflection of these changes is life expectancy, which has improved in this period, although the robustness of this indicator prevents these changes from being of the same order as those for the probability of death. If, moreover, we bear in mind that life expectancy offers no information as to whether this improvement is the same for different age groups, it is important and necessary to turn to other mortality indicators whose past and future evolution in Spain we are going to study. These indicators are applied to Spanish mortality data for the pe…

Statistics and ProbabilityEconomics and EconometricsLee-Carter modelESTADISTICA E INVESTIGACION OPERATIVALee–Carter modelConfidence intervalBootstrapGeographyAge groupsMortality dataMortality indicatorsLife expectancyEconometricsStatistics Probability and UncertaintyDeveloped countryDemography
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