Subnational probabilistic projections of fertility: rethinking from Latin America

Autores
Andreozzi, Lucía
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
General trends in fertility, mortality, and migration can be discerned and projected into the future with reasonable results, however, there is considerable uncertainty attached to each specific trend from a particular country or region. Then, subnational projections then represent a special chapter within the demographic projections. After introducing subnational projections and its close relationship with the fertility, this work proposes as the main objective to project fertility rates at the subnational level for Argentina using a probabilistic method; the bayesian hierarchical model (BHM), and then compare the results with the point estimates of deterministic projections published by the national organism of statistics. Forecasts were obtained from two models, one including all the countries available in World Population Prospects (WPP) and a second model based only in a subgroup of countries; Argentina, Colombia, Chile, Cuba and Uruguay, both based on data from 1980 to 2010. This set of countries where selected using the transitional to identify a subset of countries with similar patterns among them, that includes Argentina, but show different patterns compared to the rest region. Time period is selected to include years for which these countries reach an adequate data quality. BHM for subnational projections is an extremely useful and flexible method. It presents many advantages over the classical methods. Bayesian framework is a powerful scheme to generate national and subnational projections for mortality, fertility and finally population. This paper reinforces the use of probabilistic models, moreover BHM, that respects data not forcing it to get caught into a mathematical assumption.
Fil: Andreozzi, Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
Materia
Argentina
Bayesian Models
Demographic Projections
Fertility
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/230978
Acceder
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spelling Subnational probabilistic projections of fertility: rethinking from Latin AmericaAndreozzi, LucíaArgentinaBayesian ModelsDemographic ProjectionsFertilityhttps://purl.org/becyt/ford/5.9https://purl.org/becyt/ford/5General trends in fertility, mortality, and migration can be discerned and projected into the future with reasonable results, however, there is considerable uncertainty attached to each specific trend from a particular country or region. Then, subnational projections then represent a special chapter within the demographic projections. After introducing subnational projections and its close relationship with the fertility, this work proposes as the main objective to project fertility rates at the subnational level for Argentina using a probabilistic method; the bayesian hierarchical model (BHM), and then compare the results with the point estimates of deterministic projections published by the national organism of statistics. Forecasts were obtained from two models, one including all the countries available in World Population Prospects (WPP) and a second model based only in a subgroup of countries; Argentina, Colombia, Chile, Cuba and Uruguay, both based on data from 1980 to 2010. This set of countries where selected using the transitional to identify a subset of countries with similar patterns among them, that includes Argentina, but show different patterns compared to the rest region. Time period is selected to include years for which these countries reach an adequate data quality. BHM for subnational projections is an extremely useful and flexible method. It presents many advantages over the classical methods. Bayesian framework is a powerful scheme to generate national and subnational projections for mortality, fertility and finally population. This paper reinforces the use of probabilistic models, moreover BHM, that respects data not forcing it to get caught into a mathematical assumption.Fil: Andreozzi, Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaChulalongkorn University2024-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/230978Andreozzi, Lucía; Subnational probabilistic projections of fertility: rethinking from Latin America; Chulalongkorn University; Journal of Demography; 39; 2; 1-2024; 1-232730-39340857-2143CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://digital.car.chula.ac.th/jdm/vol39/iss2/1/info:eu-repo/semantics/altIdentifier/doi/10.56808/2730-3934.1358info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T15:05:02Zoai:ri.conicet.gov.ar:11336/230978instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-08-25 15:05:03.092CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Subnational probabilistic projections of fertility: rethinking from Latin America
title Subnational probabilistic projections of fertility: rethinking from Latin America
spellingShingle Subnational probabilistic projections of fertility: rethinking from Latin America
Andreozzi, Lucía
Argentina
Bayesian Models
Demographic Projections
Fertility
title_short Subnational probabilistic projections of fertility: rethinking from Latin America
title_full Subnational probabilistic projections of fertility: rethinking from Latin America
title_fullStr Subnational probabilistic projections of fertility: rethinking from Latin America
title_full_unstemmed Subnational probabilistic projections of fertility: rethinking from Latin America
title_sort Subnational probabilistic projections of fertility: rethinking from Latin America
dc.creator.none.fl_str_mv Andreozzi, Lucía
author Andreozzi, Lucía
author_facet Andreozzi, Lucía
author_role author
dc.subject.none.fl_str_mv Argentina
Bayesian Models
Demographic Projections
Fertility
topic Argentina
Bayesian Models
Demographic Projections
Fertility
purl_subject.fl_str_mv https://purl.org/becyt/ford/5.9
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv General trends in fertility, mortality, and migration can be discerned and projected into the future with reasonable results, however, there is considerable uncertainty attached to each specific trend from a particular country or region. Then, subnational projections then represent a special chapter within the demographic projections. After introducing subnational projections and its close relationship with the fertility, this work proposes as the main objective to project fertility rates at the subnational level for Argentina using a probabilistic method; the bayesian hierarchical model (BHM), and then compare the results with the point estimates of deterministic projections published by the national organism of statistics. Forecasts were obtained from two models, one including all the countries available in World Population Prospects (WPP) and a second model based only in a subgroup of countries; Argentina, Colombia, Chile, Cuba and Uruguay, both based on data from 1980 to 2010. This set of countries where selected using the transitional to identify a subset of countries with similar patterns among them, that includes Argentina, but show different patterns compared to the rest region. Time period is selected to include years for which these countries reach an adequate data quality. BHM for subnational projections is an extremely useful and flexible method. It presents many advantages over the classical methods. Bayesian framework is a powerful scheme to generate national and subnational projections for mortality, fertility and finally population. This paper reinforces the use of probabilistic models, moreover BHM, that respects data not forcing it to get caught into a mathematical assumption.
Fil: Andreozzi, Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
description General trends in fertility, mortality, and migration can be discerned and projected into the future with reasonable results, however, there is considerable uncertainty attached to each specific trend from a particular country or region. Then, subnational projections then represent a special chapter within the demographic projections. After introducing subnational projections and its close relationship with the fertility, this work proposes as the main objective to project fertility rates at the subnational level for Argentina using a probabilistic method; the bayesian hierarchical model (BHM), and then compare the results with the point estimates of deterministic projections published by the national organism of statistics. Forecasts were obtained from two models, one including all the countries available in World Population Prospects (WPP) and a second model based only in a subgroup of countries; Argentina, Colombia, Chile, Cuba and Uruguay, both based on data from 1980 to 2010. This set of countries where selected using the transitional to identify a subset of countries with similar patterns among them, that includes Argentina, but show different patterns compared to the rest region. Time period is selected to include years for which these countries reach an adequate data quality. BHM for subnational projections is an extremely useful and flexible method. It presents many advantages over the classical methods. Bayesian framework is a powerful scheme to generate national and subnational projections for mortality, fertility and finally population. This paper reinforces the use of probabilistic models, moreover BHM, that respects data not forcing it to get caught into a mathematical assumption.
publishDate 2024
dc.date.none.fl_str_mv 2024-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/230978
Andreozzi, Lucía; Subnational probabilistic projections of fertility: rethinking from Latin America; Chulalongkorn University; Journal of Demography; 39; 2; 1-2024; 1-23
2730-3934
0857-2143
CONICET Digital
CONICET
url http://hdl.handle.net/11336/230978
identifier_str_mv Andreozzi, Lucía; Subnational probabilistic projections of fertility: rethinking from Latin America; Chulalongkorn University; Journal of Demography; 39; 2; 1-2024; 1-23
2730-3934
0857-2143
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://digital.car.chula.ac.th/jdm/vol39/iss2/1/
info:eu-repo/semantics/altIdentifier/doi/10.56808/2730-3934.1358
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Chulalongkorn University
publisher.none.fl_str_mv Chulalongkorn University
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.24418

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