Resumen
Introducción: en este trabajo se implementa un método probabilístico para estimar la esperanza de vida de hombres y mujeres por edad; el método de Double GAP o Doble Brecha. La aplicación al caso de Argentina intenta aportar información al fenómeno del envejecimiento poblacional y su relación con el sistema previsional.
Objetivo: presentar estimaciones y proyecciones de la esperanza de vida de hombres y mujeres por edad obtenidas a través de un método probabilístico que contempla el deferencial por sexo, hasta el año 2025.
Material y métodos: se estima el método de Double GAP o Doble Brecha, y luego se seleccionan las esperanzas de vida a los 60 y a los 65 años (para mujeres y varones respectivamente), dado que se trata de las edades jubilatorias de Argentina y se presentan los pronósticos y sus correspondientes intervalos de confianza.
Resultados: los pronósticos del modelo Doble Brecha indican que las esperanzas de vida en Argentina tanto a los 60 como a los 65 años, crecerán levemente hasta 2025. Para las mujeres se incrementa medio año, mientras que en los varones el crecimiento de la esperanza es levemente superior. Esto último, muestra también una tendencia lenta hacia una convergencia entre las esperanzas de vida masculina y femenina.
Conclusiones: se pone en evidencia cómo Argentina está lejos de registrar un récord de esperanza de vida a nivel mundial para estas edades, debido a que los pronósticos de esperanza de vida que genera el modelo de Doble Brecha para el país están muy lejos de la tendencia de las buenas prácticas (serie de máximos en la esperanza de vida).
Abstract
Background: In this work, a probabilistic method is implemented to estimate the life expectancy of men and women by age; the Double GAP or Double Gap method. The application to the case of Argentina attempts to provide information on the phenomenon of population aging and its relationship with the pension system.
Objective: Present estimates and projections of the life expectancy of men and women by age obtained through a probabilistic method that considers the differential by sex.
Material and methods: The Double GAP or Double Gap method is estimated, and then the life expectancies at 60 and 65 years are selected (for women and men respectively), given that these are the retirement ages in Argentina and are present the forecasts and their corresponding confidence intervals.
Results: The forecasts of the Double Gap model indicate that life expectancy in Argentina at both 60 and 65 years of age will grow slightly until 2025. For women it increases by half a year, while for men the growth in hope is slightly higher. The latter also shows a slow trend towards a convergence between male and female life expectancies.
Conclusions: It is evident that Argentina is far from registering a record in life expectancy worldwide for these ages, because the life expectancy forecasts generated by the Double Gap model for the country are very far from the trend of good practices (series of maximums in life expectancy).
Pascariu MD, Canudas-Romo V, Vaupel JW. The double-gap life expectancy forecasting model. Insur Math Econ. 2018;78: 339-50. doi: 10.1016/j.insmatheco.2017.09.011.
Thesis MD. Modelling and forecasting mortality [Internet]. Scor.com. 2018 [citado el 30 de enero de 2024]. Disponible en: https://www.scor.com/sites/default/files/pascariu_-_2018_-_ modelling_and_forecasting_mortality.pdf.
Martinez-Illanes LR, Pinto-Ortiz, EN Ruiz-Zalazar TR. La sostenibilidad del sistema integrado previsional argentino, SIPA. 50° Jornadas Internacionales de Finanzas Publicas. 2017.
17. van Raalte AA, Sasson I, Martikainen P. The case for monitoring life-span inequality. Science [Internet]. 2018;362 (6418):1002-4. doi:10.1126/science.aau581.
Naran K, Nundalall T, Chetty S, et. al. Principles of immunotherapy: Implications for treatment strategies in cancer and infectious diseases. Front Microbiol 2018 doi: /10.3389/ fmicb.2018.03158.
Olshansky SJ, Carnes BA. Inconvenient truths about human longevity. J Gerontol A Biol Sci Med Sci 2019;74 (Supplement_1):S7-12. doi:10.1093/gerona/glz098.
Gameiro GR, Sinkunas V, Liguori GR, et. al. Precision Medicine: Changing the way we think about healthcare. Clinics (Sao Paulo) 2018 doi:10.6061/clinics/2017/e723.
University of California, Berkeley; Max Planck Institute for Demographic Research, Rostock, Human Mortality Database (HMD). Disponible en: https://www.mortality.org/. Accessed 27 March 2020.
Aburto JM, Villavicencio F, Basellini U, et. al. Dynamics of life expectancy and life span equality. Proc Natl Acad Sci USA 2020;117(10):5250–9. doi:10.1073/pnas.1915884117.
Medford A, Vaupel JW. Human lifespan records are not remarkable but their durations are. PLoS One 2019;14(3) doi:10.1371/ journal.pone.0212345.
Alvarez JA, Aburto JM, Canudas-Romo V. Latin American convergence and divergence towards the mortality profiles of developed countries. Popul Stud (Camb) 2020 74(1):75-92.
Aburto JM, Beltrán-Sánchez H. Upsurge of homicides and its impact on life expectancy and life span inequality in Mexico, 2005-2015. Am J Public Health 2019 doi:10.2105/ ajph.2018.304878.
García J, Aburto JM. The impact of violence on Venezuelan life expectancy and lifespan inequality. Int J Epidemiol 2019 [;48 (5):1593-601.
Maier H, Jeune B, Vaupel JW, editores. Exceptional Lifespans. Cham: Springer International Publishing; 2021.
Oeppen J. Life expectancy convergence among nations since 1820: Separating the effects of technology and income. En: Demographic Research Monographs. Cham: Springer International Publishing; 2019. p. 197-219.
Population.un.org. [citado el 30 de enero de 2024]. Disponible en: https://population.un.org/wpp/publications/Files/WPP2019 _10KeyFindings.pdf.
Bengtsson T, Keilman N. Old and new perspectives on mortality forecasting. Bengtsson T, Keilman N, editores. Cham: Springer International Publishing; 2019.
Bergeron-Boucher M-P, Kjærgaard S, et. al. The impact of the choice of life table statistics when forecasting mortality. Demogr Res 2019;41(43):1235-68.
Lee R. Mortality forecasts and linear life expectancy trends. En: Demographic Research Monographs. Cham: Springer International Publishing; 2019. p. 167-83.
Torri T, Vaupel JW. Forecasting life expectancy in an international context. Int J Forecast 2012;28(2):519-31.
Zarulli V, Barthold-Jones JA, Oksuzyan A, et.al. Women live longer than men even during severe famines and epidemics. Proc Natl Acad Sci US A 2018;115(4). Disponible doi:10.1073/ pnas.170153511.
Dormont B, Samson AL, Fleurbaey M, et. al. Individual uncertainty about longevity. Demography 2018;55(5):1829-54. doi:10.1007/s13524-018-0713-4.
Foreman KJ, Marquez N, Dolgert A, et. al. Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016-40 for 195 countries and territories. Lancet. 2018;392(10159):2052-90.
Zuo W, Jiang S, Guo Z, et. al. Advancing front of old-age human survival. Proc Natl AcadSci USA 2018;115(44):11209-14. doi:10.1073/pnas.1812337115.
Aburto JM, Alvarez-Martínez JA, Villavicencio F, et. al. The threshold age of the lifetable entropy. Demogr Res 2019;41(4): 83-102.