Uncertainty in population projections: the state of the art

In this paper I critically review the state of the art in population projections, focusing on how uncertainty is handled in three approaches: the classical cohort-component, the frequentist probabilistic model and the Bayesian paradigm. Next, I focus on recent developments on mortality, fertility an...

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Main Author: Raquel Rangel de Meireles Guimarães
Format: Article
Language:English
Published: Associação Brasileira de Estudos Populacionais 2014-12-01
Series:Revista Brasileira de Estudos de População
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-30982014000200003&lng=en&tlng=en
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spelling doaj-9342d3abeda84a93a20ca1b5260f6e5a2021-04-02T05:36:07ZengAssociação Brasileira de Estudos PopulacionaisRevista Brasileira de Estudos de População0102-30982014-12-0131227729010.1590/S0102-30982014000200003S0102-30982014000200003Uncertainty in population projections: the state of the artRaquel Rangel de Meireles Guimarães0Universidade Federal do ParanáIn this paper I critically review the state of the art in population projections, focusing on how uncertainty is handled in three approaches: the classical cohort-component, the frequentist probabilistic model and the Bayesian paradigm. Next, I focus on recent developments on mortality, fertility and migration projections under the Bayesian setting, which have been clearly at the frontier of knowledge in demography. By evaluating the merits and limitations of each framework, I conclude that in the near future the Bayesian paradigm will offer the most promising approach to population projections, since it combines expert opinion, information that demographers have readily available from their empirical analyses and sophisticated statistical and computational methods to deal with uncertainty. Hence, the availability of population forecasts that take uncertainty carefully into account may enhance communication among demographers by allowing for greater flexibility in reflecting demographic beliefs.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-30982014000200003&lng=en&tlng=enProyecciones de poblaciónIncertidumbreModelo de cohorte-componenteEnfoque frecuentistaEnfoque bayesiano
collection DOAJ
language English
format Article
sources DOAJ
author Raquel Rangel de Meireles Guimarães
spellingShingle Raquel Rangel de Meireles Guimarães
Uncertainty in population projections: the state of the art
Revista Brasileira de Estudos de População
Proyecciones de población
Incertidumbre
Modelo de cohorte-componente
Enfoque frecuentista
Enfoque bayesiano
author_facet Raquel Rangel de Meireles Guimarães
author_sort Raquel Rangel de Meireles Guimarães
title Uncertainty in population projections: the state of the art
title_short Uncertainty in population projections: the state of the art
title_full Uncertainty in population projections: the state of the art
title_fullStr Uncertainty in population projections: the state of the art
title_full_unstemmed Uncertainty in population projections: the state of the art
title_sort uncertainty in population projections: the state of the art
publisher Associação Brasileira de Estudos Populacionais
series Revista Brasileira de Estudos de População
issn 0102-3098
publishDate 2014-12-01
description In this paper I critically review the state of the art in population projections, focusing on how uncertainty is handled in three approaches: the classical cohort-component, the frequentist probabilistic model and the Bayesian paradigm. Next, I focus on recent developments on mortality, fertility and migration projections under the Bayesian setting, which have been clearly at the frontier of knowledge in demography. By evaluating the merits and limitations of each framework, I conclude that in the near future the Bayesian paradigm will offer the most promising approach to population projections, since it combines expert opinion, information that demographers have readily available from their empirical analyses and sophisticated statistical and computational methods to deal with uncertainty. Hence, the availability of population forecasts that take uncertainty carefully into account may enhance communication among demographers by allowing for greater flexibility in reflecting demographic beliefs.
topic Proyecciones de población
Incertidumbre
Modelo de cohorte-componente
Enfoque frecuentista
Enfoque bayesiano
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-30982014000200003&lng=en&tlng=en
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