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A functional data analysis approach for forecasting population: a case study for the United Kingdom

A functional data analysis approach for forecasting population: a case study for the United Kingdom
A functional data analysis approach for forecasting population: a case study for the United Kingdom
Cohort component models are often used to model the evolution of an age-specific population, and are particularly useful to highlight which demographic component contributes the most to population change. Many methods have been proposed to forecast four demographic components, namely mortality, fertility, emigration and immigration. These existing methods are sometimes considered from a deterministic viewpoint, which in practice can be quite restrictive. The statistical method we propose is a multilevel functional data analytic approach, where the mortality and migration for females and males are modelled and forecasted jointly. The forecast uncertainty associated with each component is incorporated through bootstrapping. Using the historical data for the United Kingdom from 1975 to 2009, we found that the proposed method shows good in-sample forecast accuracy for the holdout data between years 2000 and 2009. Moreover, we produce out-of-sample population forecasts from 2010 to 2030, and compare our forecasts with those produced by the Office for National Statistics
41
ESRC Centre for Population Change
Shang, Han Lin
1625ecc8-1ab1-4ef8-b87e-e5a2382d34c5
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Wisniowski, Arkadiusz
ec9da054-45f0-4393-ad91-87e8f9750ae9
McGowan, Teresa
4524e894-04de-4822-8508-f4b966e12ae2
Shang, Han Lin
1625ecc8-1ab1-4ef8-b87e-e5a2382d34c5
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Wisniowski, Arkadiusz
ec9da054-45f0-4393-ad91-87e8f9750ae9
McGowan, Teresa
4524e894-04de-4822-8508-f4b966e12ae2

Shang, Han Lin, Smith, Peter W.F., Bijak, Jakub and Wisniowski, Arkadiusz , McGowan, Teresa (ed.) (2013) A functional data analysis approach for forecasting population: a case study for the United Kingdom Southampton, GB. ESRC Centre for Population Change 42pp. (ESRC Centre for Population Change Working Paper Series, 41)

Record type: Monograph (Working Paper)

Abstract

Cohort component models are often used to model the evolution of an age-specific population, and are particularly useful to highlight which demographic component contributes the most to population change. Many methods have been proposed to forecast four demographic components, namely mortality, fertility, emigration and immigration. These existing methods are sometimes considered from a deterministic viewpoint, which in practice can be quite restrictive. The statistical method we propose is a multilevel functional data analytic approach, where the mortality and migration for females and males are modelled and forecasted jointly. The forecast uncertainty associated with each component is incorporated through bootstrapping. Using the historical data for the United Kingdom from 1975 to 2009, we found that the proposed method shows good in-sample forecast accuracy for the holdout data between years 2000 and 2009. Moreover, we produce out-of-sample population forecasts from 2010 to 2030, and compare our forecasts with those produced by the Office for National Statistics

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More information

Published date: 19 December 2013
Organisations: Social Statistics & Demography, Centre for Population Change

Identifiers

Local EPrints ID: 360721
URI: https://eprints.soton.ac.uk/id/eprint/360721
PURE UUID: de6c8ca7-69c0-4758-b455-23071f476c7a
ORCID for Peter W.F. Smith: ORCID iD orcid.org/0000-0003-4423-5410
ORCID for Jakub Bijak: ORCID iD orcid.org/0000-0002-2563-5040

Catalogue record

Date deposited: 06 Jan 2014 13:50
Last modified: 06 Jun 2018 13:11

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