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Measuring output quality for multisource statistics in official statistics: Some directions

机译:在官方统计中测量多源统计的输出质量:一些方向

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摘要

Many statistical offices have been moving towards an increased use of administrative data sources for statistical purposes, both as a substitute and as a complement to survey data. Moreover, the emergence of big data constitutes a further increase in available sources. As a result, statistical output in official statistics is increasingly based on complex combinations of sources. The quality of such statistics depends on the quality of the primary sources and on the ways they are combined. This paper analyses the appropriateness of the current set of output quality measures for multiple source statistics, it explains the need for improvement and outlines directions for further work. The usual approach for measuring the quality of the statistical output is to assess quality through the measurement of the input and process quality. The paper argues that in multisource production environment this approach is not sufficient. It advocates measuring quality on the basis of the output itself - without analysing the details of the inputs and the production process - and proposes directions for further development.
机译:许多统计局一直在为统计目的增加使用行政数据源,以替代和补充调查数据。此外,大数据的出现构成了可用资源的进一步增加。结果,官方统计中的统计输出越来越多地基于复杂的来源组合。此类统计数据的质量取决于主要来源的质量及其组合方式。本文分析了针对多源统计数据的当前一组输出质量度量的适用性,解释了改进的必要性并概述了进一步工作的方向。测量统计输出质量的常用方法是通过测量输入和过程质量来评估质量。本文认为,在多源生产环境中,这种方法是不够的。它主张在不分析投入和生产过程细节的基础上,根据产出本身来衡量质量,并提出进一步发展的方向。

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