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Does specification matter? Experiments with simple multiregional probabilistic population projections

Raymer, James; Abel, Guy J.; Rogers, Andrei

Description

Population 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...[Show more]

dc.contributor.authorRaymer, James
dc.contributor.authorAbel, Guy J.
dc.contributor.authorRogers, Andrei
dc.date.accessioned2015-12-10T23:02:11Z
dc.identifier.issn0308-518X
dc.identifier.urihttp://hdl.handle.net/1885/61899
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.
dc.publisherPion Ltd
dc.sourceEnvironment and Planning A
dc.subjectKeywords: demographic method; numerical model; prediction; probability; time series analysis; vector autoregression; England; United Kingdom England; Multiregional demography; Probabilistic population forecasting; Vector autoregressive (VAR) time series models
dc.titleDoes specification matter? Experiments with simple multiregional probabilistic population projections
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume44
dc.date.issued2012
local.identifier.absfor140305 - Time-Series Analysis
local.identifier.absfor160399 - Demography not elsewhere classified
local.identifier.absfor160303 - Migration
local.identifier.ariespublicationu9406909xPUB648
local.type.statusPublished Version
local.contributor.affiliationRaymer, James, College of Arts and Social Sciences, ANU
local.contributor.affiliationAbel, Guy J, Vienna Institute of Demography
local.contributor.affiliationRogers, Andrei, University of Colorado
local.description.embargo2037-12-31
local.bibliographicCitation.issue11
local.bibliographicCitation.startpage2664
local.bibliographicCitation.lastpage2686
local.identifier.doi10.1068/a4533
local.identifier.absseo870103 - Regional Planning
local.identifier.absseo910102 - Demography
dc.date.updated2016-02-24T12:00:08Z
local.identifier.scopusID2-s2.0-84870766431
local.identifier.thomsonID000313231400011
CollectionsANU Research Publications

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