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Article: Does specifi cation matter? Experiments with simple multiregional probabilistic population projections

TitleDoes specifi cation matter? Experiments with simple multiregional probabilistic population projections
Authors
KeywordsEngland
Multiregional demography
Probabilistic population forecasting
Vector autoregressive (VAR) time series models
Issue Date2012
Citation
Environment and Planning A, 2012, v. 44, n. 11, p. 2664-2686 How to Cite?
AbstractPopulation projection models that introduce uncertainty are a growing subset of projection models in general. In this paper we focus on the importance of decisions made with regard to the model specifi cations adopted. We compare the forecasts and prediction intervals associated with four simple regional population projection models: an overall growth rate model, a component model with net migration, a component model with in-migration and out-migration rates, and a multiregional model with destinationspecifi c out-migration rates. Vector autoregressive models are used to forecast future rates of growth, birth, death, net migration, in-migration and out-migration, and destinationspecifi c out-migration for the North, Midlands, and South regions in England. They are also used to forecast diff erent international migration measures. The base data represent a time series of annual data provided by the Offi ce for National Statistics from 1976 to 2008. The results illustrate how both the forecasted subpopulation totals and the corresponding prediction intervals diff er for the multiregional model in comparison to other simpler models, as well as for diff erent assumptions about international migration. The paper ends with a discussion of our results and possible directions for future research. © 2012 Pion and its Licensors.
Persistent Identifierhttp://hdl.handle.net/10722/334300
ISSN
2023 Impact Factor: 4.6
2023 SCImago Journal Rankings: 2.084
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorRaymer, James-
dc.contributor.authorAbel, Guy J.-
dc.contributor.authorRogers, Andrei-
dc.date.accessioned2023-10-20T06:47:09Z-
dc.date.available2023-10-20T06:47:09Z-
dc.date.issued2012-
dc.identifier.citationEnvironment and Planning A, 2012, v. 44, n. 11, p. 2664-2686-
dc.identifier.issn0308-518X-
dc.identifier.urihttp://hdl.handle.net/10722/334300-
dc.description.abstractPopulation projection models that introduce uncertainty are a growing subset of projection models in general. In this paper we focus on the importance of decisions made with regard to the model specifi cations adopted. We compare the forecasts and prediction intervals associated with four simple regional population projection models: an overall growth rate model, a component model with net migration, a component model with in-migration and out-migration rates, and a multiregional model with destinationspecifi c out-migration rates. Vector autoregressive models are used to forecast future rates of growth, birth, death, net migration, in-migration and out-migration, and destinationspecifi c out-migration for the North, Midlands, and South regions in England. They are also used to forecast diff erent international migration measures. The base data represent a time series of annual data provided by the Offi ce for National Statistics from 1976 to 2008. The results illustrate how both the forecasted subpopulation totals and the corresponding prediction intervals diff er for the multiregional model in comparison to other simpler models, as well as for diff erent assumptions about international migration. The paper ends with a discussion of our results and possible directions for future research. © 2012 Pion and its Licensors.-
dc.languageeng-
dc.relation.ispartofEnvironment and Planning A-
dc.subjectEngland-
dc.subjectMultiregional demography-
dc.subjectProbabilistic population forecasting-
dc.subjectVector autoregressive (VAR) time series models-
dc.titleDoes specifi cation matter? Experiments with simple multiregional probabilistic population projections-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1068/a4533-
dc.identifier.scopuseid_2-s2.0-84870766431-
dc.identifier.volume44-
dc.identifier.issue11-
dc.identifier.spage2664-
dc.identifier.epage2686-
dc.identifier.eissn1472-3409-
dc.identifier.isiWOS:000313231400011-

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