Modelling residuals dependence in dynamic life tables: A geostatistical approach

2008 ◽  
Vol 52 (6) ◽  
pp. 3128-3147 ◽  
Author(s):  
A. Debón ◽  
F. Montes ◽  
J. Mateu ◽  
E. Porcu ◽  
M. Bevilacqua
Keyword(s):  
Life Tables ◽  
Geostatistical Approach ◽  
Dynamic Life Tables

Constructing dynamic life tables with a single-factor model

2020 ◽  
Vol 43 (2) ◽  
pp. 787-825
Author(s):  
David Atance ◽  
Alejandro Balbás ◽  
Eliseo Navarro
Keyword(s):  
Factor Model ◽  
Life Tables ◽  
Single Factor ◽  
Dynamic Life Tables ◽  
Single Factor Model

scholarly journals A Comparison of Forecasting Mortality Models Using Resampling Methods

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1550
Author(s):  
David Atance ◽  
Ana Debón ◽  
Eliseo Navarro
Keyword(s):  
Insurance Industry ◽  
Geographical Area ◽  
Real Data ◽  
Life Tables ◽  
Insurance Companies ◽  
Prediction Ability ◽  
Resampling Methods ◽  
Proactive Approach ◽  
Mortality Models ◽  
Dynamic Life Tables

The accuracy of the predictions of age-specific probabilities of death is an essential objective for the insurance industry since it dramatically affects the proper valuation of their products. Currently, it is crucial to be able to accurately calculate the age-specific probabilities of death over time since insurance companies’ profits and the social security of citizens depend on human survival; therefore, forecasting dynamic life tables could have significant economic and social implications. Quantitative tools such as resampling methods are required to assess the current and future states of mortality behavior. The insurance companies that manage these life tables are attempting to establish models for evaluating the risk of insurance products to develop a proactive approach instead of using traditional reactive schemes. The main objective of this paper is to compare three mortality models to predict dynamic life tables. By using the real data of European countries from the Human Mortality Database, this study has identified the best model in terms of the prediction ability for each sex and each European country. A comparison that uses cobweb graphs leads us to the conclusion that the best model is, in general, the Lee–Carter model. Additionally, we propose a procedure that can be applied to a life table database that allows us to choose the most appropriate model for any geographical area.

scholarly journals Construcción de tablas de vida dinámicas para uno o dos sexos = Construction of unisex or sex-distinct dynamic life tables

2012 ◽  
pp. 165
Author(s):  
Ewa Dylewska ◽  
María Purificación Galindo Villardón
Keyword(s):  
Life Tables ◽  
Mortality Reduction ◽  
Age And Gender ◽  
Mortality Projection ◽  
Dynamic Life Tables ◽  
And Gender ◽  
Third Dimension ◽  
Carter Model ◽  
Sobre Todo

<p>Mientras que las tablas de vida tradicionales describen la mortalidad actual en un determinado periodo de tiempo, las tablas de vida dinámicas permiten una proyección de mortalidad futura. Además de la edad y el sexo, las tablas de vida dinámicas tienen también una tercera dimensión, que es el tiempo. Por lo tanto, permiten observar cambios en la mortalidad que resultan no solamente de cambios en la edad sino también de cambios que aparecen a lo largo del tiempo. Esto se refiere sobre todo a la tendencia de disminución de riesgo de mortalidad. Las tablas de vida dinámicas son, por lo tanto, muy útiles en la construcción de seguros de vida de larga duración y planes de pensiones. También pueden ser aplicadas en la construcción de tablas unisex (relacionado con el dictamen C-236/09 – Test -Achats). <br />El objetivo del estudio es comprobar la diferencia en la esperanza de vida a la edad <em>x</em> en España calculada utilizando las tablas de vida estáticas (tradicionales) y dinámicas, para uno o ambos sexos. Este fin se realiza aplicando el modelo de Lee-Carter para pronosticar la mortalidad futura.</p><p>Traditional life tables describe a level of mortality at one and defined period of time whereas dynamic life tables allow for projection of future mortality. Apart from age and gender, dynamic life tables also have a third dimension, which is time. In that way, it is possible to observe changes of mortality over the years. This is especially reflected in a mortality reduction trend. Dynamic life tables are therefore very useful in pricing long-term life contracts and especially in pricing annuities. Moreover, dynamic life tables can also be used in constructing unisex life tables (in relation with decision C-236/09 – Test-Achats).</p> The purpose of this paper is to demonstrate differences in life expectancy at age <em>x</em> in Spain calculated by using static (traditional) and dynamic life tables, both unisex and sex-distinct. Mortality projection is done through the application of the Lee-Carter model<p> </p>

Projecting Dynamic Life Tables Using Data Cloning

2017 ◽  
pp. 43-57
Author(s):  
Andrés Benchimol ◽  
Irene Albarrán ◽  
Juan Miguel Marín ◽  
Pablo Alonso-González
Keyword(s):  
Life Tables ◽  
Data Cloning ◽  
Dynamic Life Tables ◽  
Using Data

scholarly journals Dynamic Life Tables for India and Some of Its Major States

2017 ◽  
Vol 25 (4) ◽  
pp. 343-357
Author(s):  
Mompi Sharma ◽  
◽  
Labananda Choudhury ◽  
Rajan Sarma ◽  
◽  
...  
Keyword(s):  
Life Tables ◽  
Dynamic Life Tables

scholarly journals Construcción de tablas de vida dinámicas para uno o dos sexos = Construction of unisex or sex-distinct dynamic life tables

2012 ◽  
pp. 165
Author(s):  
Ewa Dylewska ◽  
María Purificación Galindo Villardón
Keyword(s):  
Life Tables ◽  
Mortality Reduction ◽  
Age And Gender ◽  
Mortality Projection ◽  
Dynamic Life Tables ◽  
And Gender ◽  
Third Dimension ◽  
Carter Model ◽  
Sobre Todo

<p>Mientras que las tablas de vida tradicionales describen la mortalidad actual en un determinado periodo de tiempo, las tablas de vida dinámicas permiten una proyección de mortalidad futura. Además de la edad y el sexo, las tablas de vida dinámicas tienen también una tercera dimensión, que es el tiempo. Por lo tanto, permiten observar cambios en la mortalidad que resultan no solamente de cambios en la edad sino también de cambios que aparecen a lo largo del tiempo. Esto se refiere sobre todo a la tendencia de disminución de riesgo de mortalidad. Las tablas de vida dinámicas son, por lo tanto, muy útiles en la construcción de seguros de vida de larga duración y planes de pensiones. También pueden ser aplicadas en la construcción de tablas unisex (relacionado con el dictamen C-236/09 – Test -Achats). <br />El objetivo del estudio es comprobar la diferencia en la esperanza de vida a la edad <em>x</em> en España calculada utilizando las tablas de vida estáticas (tradicionales) y dinámicas, para uno o ambos sexos. Este fin se realiza aplicando el modelo de Lee-Carter para pronosticar la mortalidad futura.</p><p>Traditional life tables describe a level of mortality at one and defined period of time whereas dynamic life tables allow for projection of future mortality. Apart from age and gender, dynamic life tables also have a third dimension, which is time. In that way, it is possible to observe changes of mortality over the years. This is especially reflected in a mortality reduction trend. Dynamic life tables are therefore very useful in pricing long-term life contracts and especially in pricing annuities. Moreover, dynamic life tables can also be used in constructing unisex life tables (in relation with decision C-236/09 – Test-Achats).</p> The purpose of this paper is to demonstrate differences in life expectancy at age <em>x</em> in Spain calculated by using static (traditional) and dynamic life tables, both unisex and sex-distinct. Mortality projection is done through the application of the Lee-Carter model<p> </p>

Life Tables for the Black Flour Beetle, Tribolium madens Charp.

1945 ◽  
Vol 79 (784) ◽  
pp. 436-444 ◽  
Author(s):  
Thomas Park
Keyword(s):  
Life Tables ◽  
Flour Beetle
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