Models for combining aggregate-level administrative data in the absence of a traditional census
Models for combining aggregate-level administrative data in the absence of a traditional census
Administrative data sources are an important component of population data collection and they have been used in census data production in the Nordic countries since the 1960s. A large amount of information about the population is already collected in administrative data sources by governments. However, there are some challenges to using administrative data sources to estimate population counts by age, sex, and geographical area as well as population characteristics. The main limitation with the administrative data sources is that they only collect information from a subset of the population about specific events, and this may result in either undercoverage or overcoverage of the population. Another issue with the administrative data sources is that the information may not have the same quality for all population groups. This research aims to correct an inaccurate administrative data source by combining aggregate-level administrative data with more accurate marginal distributions or two-way marginal information from an auxiliary data source and produce accurate population estimates in the absence of a traditional census. The methodology developed is applied to estimate population counts by age, sex, and local authority area in England and Wales. The administrative data source used is the Patient Register which suffers from overcoverage, particularly for people between the ages of 20 and 50.
combining data, log-linear model with offset, administrative data, england and wales, population estimates
431-451
Yildiz, Dilek
71798192-b121-4cd0-9025-7ad5131ac6d5
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
September 2015
Yildiz, Dilek
71798192-b121-4cd0-9025-7ad5131ac6d5
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Yildiz, Dilek and Smith, Peter W.F.
(2015)
Models for combining aggregate-level administrative data in the absence of a traditional census.
Journal of Official Statistics, 31 (3), .
(doi:10.1515/jos-2015-0026).
Abstract
Administrative data sources are an important component of population data collection and they have been used in census data production in the Nordic countries since the 1960s. A large amount of information about the population is already collected in administrative data sources by governments. However, there are some challenges to using administrative data sources to estimate population counts by age, sex, and geographical area as well as population characteristics. The main limitation with the administrative data sources is that they only collect information from a subset of the population about specific events, and this may result in either undercoverage or overcoverage of the population. Another issue with the administrative data sources is that the information may not have the same quality for all population groups. This research aims to correct an inaccurate administrative data source by combining aggregate-level administrative data with more accurate marginal distributions or two-way marginal information from an auxiliary data source and produce accurate population estimates in the absence of a traditional census. The methodology developed is applied to estimate population counts by age, sex, and local authority area in England and Wales. The administrative data source used is the Patient Register which suffers from overcoverage, particularly for people between the ages of 20 and 50.
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More information
Accepted/In Press date: 1 February 2015
e-pub ahead of print date: 1 September 2015
Published date: September 2015
Keywords:
combining data, log-linear model with offset, administrative data, england and wales, population estimates
Organisations:
Statistical Sciences Research Institute
Identifiers
Local EPrints ID: 385212
URI: http://eprints.soton.ac.uk/id/eprint/385212
ISSN: 0282-423X
PURE UUID: cbd14b88-d853-4ea7-894e-17dec38f5db9
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Date deposited: 18 Jan 2016 11:59
Last modified: 15 Mar 2024 02:43
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Author:
Dilek Yildiz
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