BR-EMS 2021 life table for the Brazilian insured population

Authors

DOI:

https://doi.org/10.20947/S0102-3098a0252

Keywords:

Actuarial life tables, Death and survivorship coverages, Mortality graduation, Heligman-Pollard model

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.

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Author Biographies

Mario de Oliveira, Instituto de Matemática, Universidade Federal do Rio de Janeiro (IM/UFRJ), Rio de Janeiro-RJ, Brazil

Mario de Oliveira holds a PhD in Statistics from the Warwick University, is a professor at the Department of Applied Mathematics (UFRJ) and coordinator of the Laboratory of Applied Mathematics at the Institute of Mathematics, Federal University of Rio de Janeiro.

Ana Carolina Soares Bertho, Escola Nacional de Ciências Estatísticas, Instituto Brasileiro de Geografia e Estatística (Ence/IBGE), Rio de Janeiro-RJ, Brazil

Ana Carolina Soares Bertho has doctorate degree in Demography from Universidade Estadual de Campinas (Unicamp). Researcher and professor at Escola Nacional de Ciências Estatísticas (ENCE/IBGE).

Bruno Costa, Instituto de Matemática, Universidade Federal do Rio de Janeiro (IM/UFRJ), Rio de Janeiro-RJ, Brazil

Bruno Costa has a doctorate degree in Applied Mathematics from Indiana Univeristy. Professor of the Applied Mathematics Department of Universidade Federal do Rio de Janeiro (UFRJ).

Flávia Sommerlatte Silva, Mercer, Lisboa, Portugal

Flávia Sommerlatte Silva is Actuary and has a Masters degree in Demography from Universidade Federal de Minas Gerais (UFMG). Actuarial Consultant at Mercer Portugal.

Mariane Branco Alves, Instituto de Matemática, Universidade Federal do Rio de Janeiro (IM/UFRJ), Rio de Janeiro-RJ, Brazil

Mariane Branco Alves holds a PhD in Statistics from the Federal University of Rio de Janeiro (UFRJ), is a professor at the Department of Statistical Methods and a researcher at the Laboratory of Applied Mathematics at the Institute of Mathematics, Federal University of Rio de Janeiro.

Milton Ramos Ramirez, Instituto de Matemática, Universidade Federal do Rio de Janeiro (IM/UFRJ), Rio de Janeiro-RJ, Brazil

Milton Ramos Ramirez has doctorate degree in Systems and Computational Engineer from Universidade Federal do Rio de Janeiro (UFRJ). Professor of the Applied Mathematics Department of Universidade Federal do Rio de Janeiro (UFRJ) and vice-head of the Applied Mathematics Laboratory of UFRJ.

Rafael Brandão de Rezende Borges, Universidade Estadual do Rio de Janeiro (UERJ), Rio de Janeiro-RJ, Brazil

Rafael Brandão de Rezende Borges is Assistant Professor at Departamento de Análise Matemática, Universidade Estadual do Rio de Janeiro (UERJ) and researcher at LabMA/UFRJ.

Reinaldo Marques, Universidade Federal de Alfenas (Unifal-MG), Varginha-MG, Brazil

Reinaldo Marques holds a PhD in Statistics from the University of Oslo, is a professor at the Department of Actuarial Science and a researcher at the Actuarial Risk Lab, Federal University of Alfenas.

Ricardo Martins da Silva Rosa, Instituto de Matemática, Universidade Federal do Rio de Janeiro (IM/UFRJ), Rio de Janeiro-RJ, Brazil

Ricardo Martins da Silva Rosa has a doctorate degree in Applied Mathematics from Indiana Univeristy - USA. Professor of the Applied Mathematics Department of Universidade Federal do Rio de Janeiro (UFRJ) and researcher at LabMA/UFRJ.

Rodrigo Lima Peregrino, Laboratório de Matemática Aplicada, Universidade Federal do Rio de Janeiro (LabMA/UFRJ), Rio de Janeiro-RJ, Brazil

Rodrigo Lima Peregrino is an Applied Mathematician and a researcher at the Laboratory of Applied Mathematics at the Institute of Mathematics, Federal University of Rio de Janeiro.

Viviana das Graças Ribeiro Lobo, Instituto de Matemática, Universidade Federal do Rio de Janeiro (IM/UFRJ), Rio de Janeiro-RJ, Brazil

Viviana das Graças Ribeiro Lobo holds a Ph.D. degree in Statistics from Universidade Federal do Rio de Janeiro (UFRJ). She is a tenured Assistant Professor at the Institute of Mathematics at UFRJ and a researcher at the Applied Mathematics Laboratory at UFRJ.

Thais Cristina Oliveira Fonseca, Instituto de Matemática, Universidade Federal do Rio de Janeiro (IM/UFRJ), Rio de Janeiro-RJ, Brazil

Thais Cristina Oliveira Fonseca holds a PhD in Statistics from the Warwick University, is a professor at the Department of Statistical Methods and a researcher at the Laboratory of Applied Mathematics at the Institute of Mathematics, Federal University of Rio de Janeiro

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Published

2023-12-11

How to Cite

de Oliveira, M., Bertho, A. C. S., Costa, B., Sommerlatte Silva, F., Alves, M. B., Ramos Ramirez, M., Borges, R. B. de R., Marques, R., Rosa, R. M. da S., Peregrino, R. L., Lobo, V. das G. R., & Fonseca, T. C. O. (2023). BR-EMS 2021 life table for the Brazilian insured population. Brazilian Journal of Population Studies, 40, 1–24. https://doi.org/10.20947/S0102-3098a0252

Issue

Vol. 40 (2023)

Section

Original Articles

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