<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

Models for Combining Aggregate-Level Administrative Data in the Absence of a Traditional Census

University of Southampton, Social Statistics and Demography, Social Sciences, Southampton, SO17 1BJ, UK.

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Administrative data sources are an important component of population data collection and they have been used in census data production in the Nordic countries...

Models for Combining Aggregate-Level Administrative Data in the Absence of a Traditional Census

Published Online: Sep 01, 2015

Page range: 431 - 451

Received: Jan 01, 2014

Accepted: Feb 01, 2015

DOI: https://doi.org/10.1515/jos-2015-0026

Keywords
Combining data, log-linear model with offset, administrative data, England and Wales, population estimates

© by Dilek Yildiz

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Models for Combining Aggregate-Level Administrative Data in the Absence of a Traditional Census

Published Online: Sep 01, 2015

Page range: 431 - 451

Received: Jan 01, 2014

Accepted: Feb 01, 2015

DOI: https://doi.org/10.1515/jos-2015-0026

KeywordsCombining data, log-linear model with offset, administrative data, England and Wales, population estimates

© by Dilek Yildiz

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Combining data, log-linear model with offset, administrative data, England and Wales, population estimates