Probabilistic estimations and projections of life expectancy for Argentina, 2000-2095
Demographic projections contain uncertainty and probabilistic models aim to quantify it. This paper develops probabilistic projections of Life Expectancy at birth for Argentina for the period 2025-2100 based on the Bayesian Hierarchical Model. Raftery et. to the. (2013) develop a model that allows e...
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| Format: | Article |
| Language: | Spanish |
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Universidad Nacional de Asunción
2023-07-01
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| Series: | Población y Desarrollo |
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| Online Access: | https://revistascientificas.una.py/index.php/RE/article/view/3787/3137 |
| _version_ | 1797379002961231872 |
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| author | Lucía Andreozzi |
| author_facet | Lucía Andreozzi |
| author_sort | Lucía Andreozzi |
| collection | DOAJ |
| description | Demographic projections contain uncertainty and probabilistic models aim to quantify it. This paper develops probabilistic projections of Life Expectancy at birth for Argentina for the period 2025-2100 based on the Bayesian Hierarchical Model. Raftery et. to the. (2013) develop a model that allows estimating the rate of increase in life expectancy of a country using previous data from that country, and taking into account past patterns observed in all other countries. Then Raftery (2014) uses the female gap model to develop life expectancy in males. For this purpose, three adjustment periods are evaluated and the results are analyzed based on the selection of the most appropriate one; life expectancy for men and women, its trend and the gap between the two. Finally, the estimated results are compared with the official data from the national statistical agency. The BHM presents plausible results together with a measure of associated un-certainty that allows deciding until when the forecasts would be reliable or reportable, however, the base period includes projections as input data, generating a paradox of using projections to project. The difference that occurs in the projections for men shows the importance in the model of including or not the last point of the data series. Although the probabilistic models represent great advances, details remain to be discussed, such as the base period and its relationship with official sources (whether estimates or projections. |
| first_indexed | 2024-03-08T20:15:52Z |
| format | Article |
| id | doaj.art-3cc0af926d7642b1bd82701440adb518 |
| institution | Directory Open Access Journal |
| issn | 2076-0531 2076-054X |
| language | Spanish |
| last_indexed | 2024-03-08T20:15:52Z |
| publishDate | 2023-07-01 |
| publisher | Universidad Nacional de Asunción |
| record_format | Article |
| series | Población y Desarrollo |
| spelling | doaj.art-3cc0af926d7642b1bd82701440adb5182023-12-22T14:53:52ZspaUniversidad Nacional de AsunciónPoblación y Desarrollo2076-05312076-054X2023-07-012957476010.18004/pdfce/2076-054x/2023.029.57.047Probabilistic estimations and projections of life expectancy for Argentina, 2000-2095Lucía Andreozzi0https://orcid.org/0000-0002-1723-5725Universidad Nacional de Córdoba, Facultad de Ciencias EconómicasDemographic projections contain uncertainty and probabilistic models aim to quantify it. This paper develops probabilistic projections of Life Expectancy at birth for Argentina for the period 2025-2100 based on the Bayesian Hierarchical Model. Raftery et. to the. (2013) develop a model that allows estimating the rate of increase in life expectancy of a country using previous data from that country, and taking into account past patterns observed in all other countries. Then Raftery (2014) uses the female gap model to develop life expectancy in males. For this purpose, three adjustment periods are evaluated and the results are analyzed based on the selection of the most appropriate one; life expectancy for men and women, its trend and the gap between the two. Finally, the estimated results are compared with the official data from the national statistical agency. The BHM presents plausible results together with a measure of associated un-certainty that allows deciding until when the forecasts would be reliable or reportable, however, the base period includes projections as input data, generating a paradox of using projections to project. The difference that occurs in the projections for men shows the importance in the model of including or not the last point of the data series. Although the probabilistic models represent great advances, details remain to be discussed, such as the base period and its relationship with official sources (whether estimates or projections. https://revistascientificas.una.py/index.php/RE/article/view/3787/3137bayesian hierarchical modellife expectancy at birthargentina |
| spellingShingle | Lucía Andreozzi Probabilistic estimations and projections of life expectancy for Argentina, 2000-2095 Población y Desarrollo bayesian hierarchical model life expectancy at birth argentina |
| title | Probabilistic estimations and projections of life expectancy for Argentina, 2000-2095 |
| title_full | Probabilistic estimations and projections of life expectancy for Argentina, 2000-2095 |
| title_fullStr | Probabilistic estimations and projections of life expectancy for Argentina, 2000-2095 |
| title_full_unstemmed | Probabilistic estimations and projections of life expectancy for Argentina, 2000-2095 |
| title_short | Probabilistic estimations and projections of life expectancy for Argentina, 2000-2095 |
| title_sort | probabilistic estimations and projections of life expectancy for argentina 2000 2095 |
| topic | bayesian hierarchical model life expectancy at birth argentina |
| url | https://revistascientificas.una.py/index.php/RE/article/view/3787/3137 |
| work_keys_str_mv | AT luciaandreozzi probabilisticestimationsandprojectionsoflifeexpectancyforargentina20002095 |