Mario De Oliveira, Ana Carolina Soares Bertho, Bruno Costa, Flávia Sommerlatte Silva, Mariane Branco Alves, Milton Ramos Ramirez, Rafael Brandão de Rezende Borges, R. Marques, Ricardo Martins da Silva Rosa, Rodrigo Lima Peregrino, Viviana das Graças Ribeiro Lobo, Thais C. O. Fonseca
{"title":"BR-EMS 2021 life table for the Brazilian insured population","authors":"Mario De Oliveira, Ana Carolina Soares Bertho, Bruno Costa, Flávia Sommerlatte Silva, Mariane Branco Alves, Milton Ramos Ramirez, Rafael Brandão de Rezende Borges, R. Marques, Ricardo Martins da Silva Rosa, Rodrigo Lima Peregrino, Viviana das Graças Ribeiro Lobo, Thais C. O. Fonseca","doi":"10.20947/s0102-3098a0252","DOIUrl":null,"url":null,"abstract":"This article presents the Brazilian private insurance market’s actuarial life tables, BR- EMS 2021. Using Bayesian inference on the parameters of the Heligman- Pollard law of mortality and data from 23 insurance groups over 15 years, totaling 3.5 billion registers, the data were corrected through a two hidden-layer neural network. The resulting tables show that the insured population exhibits lower mortality rates than the general Brazilian population, even lower than the national populations of well-developed countries such as the USA. Moreover, besides the expected gender gap in mortality rates, there is a clear distance between the death and survivorship insurance coverage groups. Likewise, the insured population characteristics mitigate well-known regional structural discrepancies in the Brazilian population, indicating that being part of the selected population of insured individuals is thus associated with a more effective protection against death than other outstanding factors such as geographic region of residence.","PeriodicalId":503637,"journal":{"name":"Revista Brasileira de Estudos de População","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista Brasileira de Estudos de População","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20947/s0102-3098a0252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article presents the Brazilian private insurance market’s actuarial life tables, BR- EMS 2021. Using Bayesian inference on the parameters of the Heligman- Pollard law of mortality and data from 23 insurance groups over 15 years, totaling 3.5 billion registers, the data were corrected through a two hidden-layer neural network. The resulting tables show that the insured population exhibits lower mortality rates than the general Brazilian population, even lower than the national populations of well-developed countries such as the USA. Moreover, besides the expected gender gap in mortality rates, there is a clear distance between the death and survivorship insurance coverage groups. Likewise, the insured population characteristics mitigate well-known regional structural discrepancies in the Brazilian population, indicating that being part of the selected population of insured individuals is thus associated with a more effective protection against death than other outstanding factors such as geographic region of residence.