Some Thoughts on Official Statistics and its Future (with discussion)

Tillé Yves (), Debusschere Marc (), Luomaranta Henri (), Axelson Martin (), Elvers Eva (), Holmberg Anders () and Valliant Richard ()
Additional contact information
Tillé Yves: University of Neuchâtel, Institut de Statistique, Pierre à Mazel 7, 2000 Neuchâtel, Switzerland
Debusschere Marc: Statistics Belgium, Koning Albert II laan 16, B-1000 Brussels, Belgium.
Luomaranta Henri: Statistics Finland. Työpajankatu 13, 00580 Helsinki, Finland.
Axelson Martin: Statistics Sweden, Klostergatan 23, SE-701 89,Örebro, Sweden.
Elvers Eva: Statistics Sweden, Solna strandväg 86, SE-171 54, Solna, Sweden.
Holmberg Anders: Australian Bureau of Statistics, Methodology Division, Locked bag 10, 2617, Belconnen, Australia.
Valliant Richard: University of Michigan, Institute for Social Research, 4620 North Park Avenue Apt 1406W Chevy Chase, Maryland, 20815, U.S.A.

Journal of Official Statistics, 2022, vol. 38, issue 2, 557-598

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.

Keywords: Deduction; foundations; induction; Lasso; p-value; registers; sampling; statistical learning (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:38:y:2022:i:2:p:557-598:n:2

DOI: 10.2478/jos-2022-0026

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