Lee-Carter method for forecasting mortality for Peruvian Population

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In this article, we have modeled mortality rates of Peruvian female and male populations during the period of 1950-2017 using the two-factor Lee-Carter (LC) model. The stochastic mortality model was introduced by Lee and Carter (1992) and has been used by many authors for fitting a...

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Detalles Bibliográficos
Autores: Cerda-Hernández, J., Sikov, A.
Formato: artículo
Fecha de Publicación:2021
Institución:Universidad Nacional de Trujillo
Repositorio:Revistas - Universidad Nacional de Trujillo
Lenguaje:inglés
OAI Identifier:oai:ojs.revistas.unitru.edu.pe:article/3702
Enlace del recurso:https://revistas.unitru.edu.pe/index.php/SSMM/article/view/3702
Nivel de acceso:acceso abierto
Materia:Lee-Carter (LC) model
Mortality modeling
Forecasting
Life expectancy
Singular value decomposition (SVD)
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spelling Lee-Carter method for forecasting mortality for Peruvian PopulationLee-Carter method for forecasting mortality for Peruvian PopulationCerda-Hernández, J.Sikov, A.Lee-Carter (LC) modelMortality modelingForecastingLife expectancySingular value decomposition (SVD)Lee-Carter (LC) modelMortality modelingForecastingLife expectancySingular value decomposition (SVD)In this article, we have modeled mortality rates of Peruvian female and male populations during the period of 1950-2017 using the two-factor Lee-Carter (LC) model. The stochastic mortality model was introduced by Lee and Carter (1992) and has been used by many authors for fitting and forecasting the human mortality rates. The Singular Value Decomposition (SVD) approach is used for estimation of the parameters of the LC model. Utilizing the best fitted auto regressive integrated moving average (ARIMA) model we forecast the values of the time dependent parameter of the LC model for the next thirty years. The forecasted values of life expectancy at different age group with 95% confidence intervals are also reported for the next thirty  years. In this research we use the data, obtained from the Peruvian National Institute of Statistics (INEI).  In this article, we have modeled mortality rates of Peruvian female and male populations during the period of 1950-2017 using the two-factor Lee-Carter (LC) model. The stochastic mortality model was introduced by Lee and Carter (1992) and has been used by many authors for fitting and forecasting the human mortality rates. The Singular Value Decomposition (SVD) approach is used for estimation of the parameters of the LC model. Utilizing the best fitted auto regressive integrated moving average (ARIMA) model we forecast the values of the time dependent parameter of the LC model for the next thirty years. The forecasted values of life expectancy at different age group with 95% confidence intervals are also reported for the next thirty  years. In this research we use the data, obtained from the Peruvian National Institute of Statistics (INEI).  National University of Trujillo - Academic Department of Mathematics2021-07-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.unitru.edu.pe/index.php/SSMM/article/view/3702Selecciones Matemáticas; Vol. 8 No. 01 (2021): January-July; 52 - 65Selecciones Matemáticas; Vol. 8 Núm. 01 (2021): Enero-Julio; 52 - 65Selecciones Matemáticas; v. 8 n. 01 (2021): Janeiro-julho; 52 - 652411-1783reponame:Revistas - Universidad Nacional de Trujilloinstname:Universidad Nacional de Trujilloinstacron:UNITRUenghttps://revistas.unitru.edu.pe/index.php/SSMM/article/view/3702/4371Derechos de autor 2021 J. Cerda-Hernández, A. Sikovhttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:ojs.revistas.unitru.edu.pe:article/37022021-07-29T15:56:48Z
dc.title.none.fl_str_mv Lee-Carter method for forecasting mortality for Peruvian Population
Lee-Carter method for forecasting mortality for Peruvian Population
title Lee-Carter method for forecasting mortality for Peruvian Population
spellingShingle Lee-Carter method for forecasting mortality for Peruvian Population
Cerda-Hernández, J.
Lee-Carter (LC) model
Mortality modeling
Forecasting
Life expectancy
Singular value decomposition (SVD)
Lee-Carter (LC) model
Mortality modeling
Forecasting
Life expectancy
Singular value decomposition (SVD)
title_short Lee-Carter method for forecasting mortality for Peruvian Population
title_full Lee-Carter method for forecasting mortality for Peruvian Population
title_fullStr Lee-Carter method for forecasting mortality for Peruvian Population
title_full_unstemmed Lee-Carter method for forecasting mortality for Peruvian Population
title_sort Lee-Carter method for forecasting mortality for Peruvian Population
dc.creator.none.fl_str_mv Cerda-Hernández, J.
Sikov, A.
author Cerda-Hernández, J.
author_facet Cerda-Hernández, J.
Sikov, A.
author_role author
author2 Sikov, A.
author2_role author
dc.subject.none.fl_str_mv Lee-Carter (LC) model
Mortality modeling
Forecasting
Life expectancy
Singular value decomposition (SVD)
Lee-Carter (LC) model
Mortality modeling
Forecasting
Life expectancy
Singular value decomposition (SVD)
topic Lee-Carter (LC) model
Mortality modeling
Forecasting
Life expectancy
Singular value decomposition (SVD)
Lee-Carter (LC) model
Mortality modeling
Forecasting
Life expectancy
Singular value decomposition (SVD)
description In this article, we have modeled mortality rates of Peruvian female and male populations during the period of 1950-2017 using the two-factor Lee-Carter (LC) model. The stochastic mortality model was introduced by Lee and Carter (1992) and has been used by many authors for fitting and forecasting the human mortality rates. The Singular Value Decomposition (SVD) approach is used for estimation of the parameters of the LC model. Utilizing the best fitted auto regressive integrated moving average (ARIMA) model we forecast the values of the time dependent parameter of the LC model for the next thirty years. The forecasted values of life expectancy at different age group with 95% confidence intervals are also reported for the next thirty  years. In this research we use the data, obtained from the Peruvian National Institute of Statistics (INEI).  
publishDate 2021
dc.date.none.fl_str_mv 2021-07-29
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.unitru.edu.pe/index.php/SSMM/article/view/3702
url https://revistas.unitru.edu.pe/index.php/SSMM/article/view/3702
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistas.unitru.edu.pe/index.php/SSMM/article/view/3702/4371
dc.rights.none.fl_str_mv Derechos de autor 2021 J. Cerda-Hernández, A. Sikov
https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2021 J. Cerda-Hernández, A. Sikov
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv National University of Trujillo - Academic Department of Mathematics
publisher.none.fl_str_mv National University of Trujillo - Academic Department of Mathematics
dc.source.none.fl_str_mv Selecciones Matemáticas; Vol. 8 No. 01 (2021): January-July; 52 - 65
Selecciones Matemáticas; Vol. 8 Núm. 01 (2021): Enero-Julio; 52 - 65
Selecciones Matemáticas; v. 8 n. 01 (2021): Janeiro-julho; 52 - 65
2411-1783
reponame:Revistas - Universidad Nacional de Trujillo
instname:Universidad Nacional de Trujillo
instacron:UNITRU
instname_str Universidad Nacional de Trujillo
instacron_str UNITRU
institution UNITRU
reponame_str Revistas - Universidad Nacional de Trujillo
collection Revistas - Universidad Nacional de Trujillo
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repository.mail.fl_str_mv
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