Abstract
The COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains. We study the association between accuracy of reported COVID-19 data and developmental indicators. We use the Newcomb–Benford law (NBL) to gauge data accuracy. We run an OLS regression of an index constructed from developmental indicators (democracy level, gross domestic product per capita, healthcare expenditures, and universal healthcare coverage) on goodness-of-fit measures to the NBL. We find that countries with higher values of the developmental index are less likely to deviate from the Newcomb-Benford law. The relationship holds for the cumulative number of reported deaths and total cases but is more pronounced for the death toll. The findings are robust for second-digit tests and for a sub-sample of countries with regional data. The NBL provides a first screening for potential data manipulation during pandemics. Our study indicates that data from autocratic regimes and less developed countries should be treated with more caution. The paper further highlights the importance of independent surveillance data verification projects.
Highlights
The COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains
We find that our goodness-of-fit measures are negatively correlated with the developmental index and each of the macroeconomic indicators (Democracy Index, gross domestic product (GDP), healthcare expenditures, and Universal Health Coverage Index (UHC))
Even though the D-statistic is more independent of the sample size, goodness-of-fit measures may still be affected by the sizes of the samples used to estimate them
Summary
The COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains. We study the association between accuracy of reported COVID-19 data and developmental indicators. We use the Newcomb–Benford law (NBL) to gauge data accuracy. With tens of millions of confirmed cases and millions of deaths, this pandemic has spurred a great number of controversies, including many related to the accuracy of the data countries report. We study the association between the accuracy of COVID-19 data reported by countries and their macroeconomic and political indicators. We use compliance with the Newcomb–Benford law (NBL), which is an observation that in many naturally occurring collections of numbers the first digit is not uniformly distributed. We use the regression analysis to find the Scientific Reports | (2021) 11:22914
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have