{"title":"计算还是估算?关于根据行政数据编制人口估计数的说明","authors":"John Dunne, Francesca Kay, Timothy Linehan","doi":"10.3233/sji-230067","DOIUrl":null,"url":null,"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.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":"6 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"To count or to estimate: A note on compiling population estimates from administrative data\",\"authors\":\"John Dunne, Francesca Kay, Timothy Linehan\",\"doi\":\"10.3233/sji-230067\",\"DOIUrl\":null,\"url\":null,\"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. 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引用次数: 0
摘要
与许多国家一样,爱尔兰一直在研究利用行政数据编制人口估计数的新系统。爱尔兰没有可用于编制估算的中央人口登记册。利用行政数据编制人口估计的主要步骤是首先建立一个人口统计数据集(SPD)。理想情况下,SPD 将为人口中的每个人提供一条包含相关属性的记录。理想的 SPD 只需对记录进行计数即可编制统计数据。实际上,SPD 的编制容易出错。这些错误可分为 4 类:过度覆盖、覆盖不足、领域分类错误和链接错误。迄今为止,爱尔兰已经研究了 2 种不同的方法来编制行政数据中的人口估计值。第一种方法在本文中称为简单计数法,其基础是建立一个 SPD,最大限度地减少单个记录错误的总体数量,从而使 SPD 的简单计数能够提供人口估计值。第二种方法在本文中称为估算方法,其基础是建立一个旨在消除除覆盖不足以外所有误差类型的 SPD,然后使用双系统估算(DSE)方法对覆盖不足的计数进行调整,以获得人口估算值。本文探讨了这两种方法的优缺点,然后考虑了如何整合这两种方法以消除缺点。许多国家统计机构在编制类似人口普查的年度人口估计时都会考虑类似的挑战,本文旨在为这一讨论做出贡献。
To count or to estimate: A note on compiling population estimates from administrative data
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.
期刊介绍:
This is the flagship journal of the International Association for Official Statistics and is expected to be widely circulated and subscribed to by individuals and institutions in all parts of the world. The main aim of the Journal is to support the IAOS mission by publishing articles to promote the understanding and advancement of official statistics and to foster the development of effective and efficient official statistical services on a global basis. Papers are expected to be of wide interest to readers. Such papers may or may not contain strictly original material. All papers are refereed.