Does specification matter? Experiments with simple multiregional probabilistic population projections
Does specification matter? Experiments with simple multiregional probabilistic population projections
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 specifications 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 destination-specific out-migration rates. Vector autoregressive models are used to forecast future rates of growth, birth, death, net migration, in-migration and out-migration, and destination-specific out-migration for the North, Midlands, and South regions in England. They are also used to forecast different international migration measures. The base data represent a time series of annual data provided by the Office for National Statistics from 1976 to 2008. The results illustrate how both the forecasted subpopulation totals and the corresponding prediction intervals differ for the multiregional model in comparison to other simpler models, as well as for different assumptions about international migration. The paper ends with a discussion of our results and possible directions for future research.
multiregional demography, probabilistic population forecasting, vector autoregressive (var) time series models, england
2664-2686
Raymer, James
ed2973c1-b78d-4166-baf3-4e18f1b24070
Abel, Guy J.
d35b5069-3c52-4d13-a678-1684ae1fce1e
Rogers, Andrei
ed63d88a-6d71-4284-8d18-a0cd4a802371
2012
Raymer, James
ed2973c1-b78d-4166-baf3-4e18f1b24070
Abel, Guy J.
d35b5069-3c52-4d13-a678-1684ae1fce1e
Rogers, Andrei
ed63d88a-6d71-4284-8d18-a0cd4a802371
Raymer, James, Abel, Guy J. and Rogers, Andrei
(2012)
Does specification matter? Experiments with simple multiregional probabilistic population projections.
Environment and Planning A, 44 (11), .
(doi:10.1068/a4533).
Abstract
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 specifications 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 destination-specific out-migration rates. Vector autoregressive models are used to forecast future rates of growth, birth, death, net migration, in-migration and out-migration, and destination-specific out-migration for the North, Midlands, and South regions in England. They are also used to forecast different international migration measures. The base data represent a time series of annual data provided by the Office for National Statistics from 1976 to 2008. The results illustrate how both the forecasted subpopulation totals and the corresponding prediction intervals differ for the multiregional model in comparison to other simpler models, as well as for different assumptions about international migration. The paper ends with a discussion of our results and possible directions for future research.
This record has no associated files available for download.
More information
Published date: 2012
Keywords:
multiregional demography, probabilistic population forecasting, vector autoregressive (var) time series models, england
Organisations:
Social Statistics & Demography, Statistical Sciences Research Institute
Identifiers
Local EPrints ID: 337955
URI: http://eprints.soton.ac.uk/id/eprint/337955
ISSN: 0308-518X
PURE UUID: 3cc84852-674f-42db-9bee-330c363cba3e
Catalogue record
Date deposited: 04 May 2012 12:40
Last modified: 14 Mar 2024 11:00
Export record
Altmetrics
Contributors
Author:
James Raymer
Author:
Guy J. Abel
Author:
Andrei Rogers
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics