Who Manipulates Data During Pandemics? Evidence from Newcomb-Benford Law

TL;DR

This study applies the Newcomb-Benford law to assess data manipulation during COVID-19, revealing that democratic and wealthier countries with better healthcare are less likely to manipulate reported pandemic data.

Contribution

It introduces a novel application of the Newcomb-Benford law to evaluate pandemic data integrity across countries, highlighting the role of political and economic factors.

Findings

Democratic countries show less deviation from the law.

Higher GDP per capita correlates with less data manipulation.

Robust results across different tests and previous pandemics.

Abstract

We use the Newcomb-Benford law to test if countries have manipulated reported data during the COVID-19 pandemic. We find that democratic countries, countries with the higher gross domestic product (GDP) per capita, higher healthcare expenditures, and better universal healthcare coverage 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, for a sub-sample of countries with regional data, and in relation to the previous swine flu (H1N1) 2009-2010 pandemic. The paper further highlights the importance of independent surveillance data verification projects.