Truth or Dare? Detecting Systematic Manipulation of COVID-19 Statistics

Abstract

Which countries manipulate COVID-19 statistics? Does the party ideology of local governors affect the probability of data manipulation at subnational levels? How does democratic quality affect statistical transparency during the pandemic? In this article, we apply election fraud detection methods — various digit-based tests that exploit human biases in generating random numbers — to the daily announced official numbers of new and cumulative coronavirus infections. First, we use digit-based tests to identify countries that likely manipulated their pandemic statistics. We then move on to examine the empirical relationship between democratic quality and data transparency. We find suggestive evidence that data manipulation occurred in China, the United States, Russia, and Turkey. Second, we show that non-democracies, as well as countries without free and fair elections, are more likely to release data that display signs of statistical malpractice.