关于官方统计及其未来的几点思考(附讨论)

Pub Date : 2022-06-01 DOI:10.2478/jos-2022-0026
Yves Tillé, M. Debusschere, Henri Luomaranta, Martin Axelson, E. Elvers, A. Holmberg, R. Valliant
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引用次数: 0

摘要

在这篇文章中,我们分享了一些关于统计科学的现状及其在官方统计生产系统中的演变的思考。我们首先尝试对统计思维的演变做一个综合。然后,我们研究了官方统计实践的演变,官方统计很早就不得不面对来源多样化的问题:首先是使用人口普查,然后是抽样调查,最后是行政档案。在每个阶段,都需要对方法进行深刻的修改。我们表明,自20世纪中叶以来,统计的主要挑战之一是从各种来源产生估计。为了做到这一点,已经提出了基于非常不同的基础的大量方法。“大数据”一词包含了一系列来源和新的统计方法。我们首先考察了官方统计中大数据价值增值的潜力。一些应用,如农业预测的图像分析是非常古老的,将进一步发展。然而,我们报告我们对网页抓取方法的怀疑。然后我们研究了新的深度学习方法的使用。随着获得越来越多的来源,巨大的挑战将仍然是这些来源的价值和协调。
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Some Thoughts on Official Statistics and its Future (with discussion)
Abstract In this article, we share some reflections on the state of statistical science and its evolution in the production systems of official statistics. We first try to make a synthesis of the evolution of statistical thinking. We then examine the evolution of practices in official statistics, which had to face very early on a diversification of sou rces: first with the use of censuses, then sample surveys and finally administrative files. At each stage, a profound revision of methods was necessary. We show that since the middle of the 20th century, one of the major challenges of statistics has been to produce estimates from a variety of sources. To do this, a large number of methods have been proposed which are based on very different f oundations. The term “big data” encompasses a set of sources and new statistical methods. We first examine the potential of valorization of big data in official statistics. Some applications such as image analysis for agricultural prediction are very old and will be further developed. However, we report our skepticism towards web-scrapping methods. Then we examine the use of new deep learning methods. With access to more and more sources, the great challenge will remain the valorization and harmonization of these sources.
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