The economic downturn due to lockdown measures at the beginning of the COVID-19 crisis raised the question whether any adaptations to the short-term statistics (STS) were needed to ensure accurate and relevant output. We limit ourselves to STS on turnover and related variables like volume of production. We looked into the different stages of the production process – from data collection to output – and anticipated a number of potential lockdown effects. With respect to output relevance, there was an increased interest in faster and specific output. With respect to the output accuracy, we took measures to check whether the anticipated effects really occurred and measures to mitigate the consequences. Examples of such measures are the calculation of an additional editing score function, alternative imputations and extensions of the regular analysis step. In this paper we give an overview of the anticipated effects, the subsequent measures that we took, we evaluate to what extent the anticipated effects occurred in practice and we mention some unforeseen effects. We end this paper by discussing to what extent the developed measures are also useful to keep after the economy has recovered.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.