Abstract
Official statistics has not properly researched and understood how its methods and models behave at times of downturns (and potentially in the corresponding situation of similarly paced (unpredictable and fast) growths). There is generally a wish to make methods robust to unusual changes, but these are often tackled situation by situation. Production of official statistics during COVID-19 has necessitated some radical changes in both data collection and statistical methods; these have been introduced with admirable speed and dedication, but this process would have been made easier with a body of research already in place to draw from. We discuss the issues with the robustness of statistical methods during downturns, and highlight the opportunity to gather data which can be analysed to give evidence for the most robust methods to use as protection against poor measurement during future downturns.
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