When is there enough data to create a global statistic?

Q3 Decision Sciences
Daniel Gerszon Mahler, Umar Serajuddin, Hiroko Maeda
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引用次数: 0

Abstract

To monitor progress towards global goals such as the Sustainable Development Goals, global statistics are needed. Yet cross-country datasets are rarely truly global, creating a trade-off for producers of global statistics: the lower the data coverage threshold for disseminating global statistics, the more can be made available, but the lower accuracy they will have. We quantify this availability-accuracy trade-off by running more than 10 million simulations on the World Development Indicators. We show that if the fraction of the world’s population on which one lacks data is x, then one should expect to be 0.37 *x standard deviations off the true global value, and risk being as much as x standard deviations off. We show the robustness of this result to various assumptions and give recommendations on when there is enough data to create global statistics. Though the decision will be context specific, in a baseline scenario we suggest not to create global statistics when there is data for less than half of the world’s population.
什么时候有足够的数据来创建一个全球统计?
为了监测可持续发展目标等全球目标的进展,需要全球统计数据。然而,跨国数据集很少是真正全球性的,这给全球统计数据的生产者带来了一种权衡:传播全球统计数据的数据覆盖阈值越低,可以获得的数据就越多,但它们的准确性就越低。我们通过对世界发展指标进行1000多万次模拟,量化了这种可用性与准确性之间的权衡。我们表明,如果缺乏数据的世界人口比例为x,那么人们应该期望与真实全球值相差0.37 *x个标准差,并且风险与x个标准差相差。我们展示了该结果对各种假设的稳健性,并就何时有足够的数据来创建全局统计提供了建议。虽然决定将根据具体情况而定,但在基线情景中,我们建议在有不到世界人口一半的数据时不要创建全球统计数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Statistical Journal of the IAOS
Statistical Journal of the IAOS Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
1.30
自引率
0.00%
发文量
116
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.
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