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To count or to estimate: A note on compiling population estimates from administrative data.
- Source :
-
Statistical Journal of the IAOS . 2023, Vol. 39 Issue 4, p879-885. 7p. - Publication Year :
- 2023
-
Abstract
- Like many countries, Ireland has been researching new systems of population estimates compiled using administrative data. Ireland does not have a Central Population Register from which the estimates can be compiled. The primary step in compiling population estimates from administrative data is to first build a Statistical Population Dataset (SPD). Ideally an SPD will have one record for each person in the population containing the relevant attributes. The ideal SPD then allows compilation of statistics by simply counting over records. In practice, the compilation of SPDs is prone to error. These errors can be classified into 4 types of error; overcoverage, undercoverage, domain misclassification and linkage error. Ireland, to date, has investigated 2 different approaches to the compilation of population estimates from administrative data. The first, labeled in this paper as the simple count method, is based on building an SPD which minimises the overall number of individual record errors such that simple counts from the SPD will provide population estimates. The second, labeled in this paper as the estimation method, is based on building an SPD which aims to eliminate all error types bar that of undercoverage and then adjusts counts for undercoverage using Dual System Estimation (DSE) methods to obtain population estimates. This paper explores the advantages and disadvantages of both methods before considering how they could be integrated to eliminate the disadvantages. Many NSIs will be considering similar challenges when compiling annual Census like population estimates and this paper aims to contribute to that discussion. [ABSTRACT FROM AUTHOR]
- Subjects :
- *CENSUS
*POPULATION statistics
*COUNTING
Subjects
Details
- Language :
- English
- ISSN :
- 18747655
- Volume :
- 39
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Statistical Journal of the IAOS
- Publication Type :
- Academic Journal
- Accession number :
- 174544354
- Full Text :
- https://doi.org/10.3233/SJI-230067