THE STATISTICAL CHALLENGES OF MODELLING COVID-19. (2021)

• Record Type: Journal Article
• Authors: Dolton, Peter
• Is Part Of: National Institute economic review. Volume 257:Number 1(2021)
• Page Start: 46
• Page End: 82
• Publication Date: 2021
• Subjects: COVID-19 -- econometric modelling; C54 -- I18 -- C32 -- C33; Economic history -- 1945- -- Periodicals; Economics -- Great Britain -- Periodicals; Great Britain -- Economic conditions -- 1945-1964 -- Periodicals; 330.941
• DOI: 10.1017/nie.2021.22
• Languages: English
• ISSNs: 0027-9501

Abstract

Abstract : In 2020–2021, the world has been gripped by a pandemic that no living person has ever known. The coronavirus pandemic is undoubtedly the greatest challenge the world has faced in over a generation. The imperative of statistical modelling is not only to manage the short-run crisis for the health services, but also to explain the pandemic's course and establish the effectiveness of different policies, both non-pharmaceutical and with vaccines. This difficult task has been undertaken by the epidemiologists and others in the face of measurement data problems, behavioural complications and endogeneity issues. This paper proposes a simple taxonomy of the alternative different models and suggests how they may be used together to overcome limitations. This perspective may have important implications for how policy-makers cope with future waves or strains in the current pandemic, or future pandemics.