Many shades of wrong: what governments do when they manipulate statistics

A considerable number of recent analyses report statistical evidence indicating that governments manipulate official macroeconomic indicators. Employing creative strategies to identify systematic biases in statistical outputs, these studies have shown that political manipulation of economic statistics does occur. But they have paid less attention to the question how official statistics are being manipulated. To shed light on the processes behind data manipulation, this article examines three recent high-profile cases in depth: Greece’s public deficit figures, controversies about Argentina’s inflation statistics, and the Brazilian “fiscal pedaling” scandal. We make two main contributions: first, macroeconomic indicators are much more ambiguous than it is commonly realized. Therefore, the line between accurate and manipulated data is more blurry than typical narratives about manipulation acknowledge. Second, in recognition of this ambiguity we introduce a typology distinguishing four types of manipulation: outright manipulation (type 1), politically motivated guesstimating (type 2), the opportunistic use of methodology space (type 3), and indicators-management through indirect means (type 4). The findings from our cases highlight that the politics of statistics do not revolve around “right” and “wrong” numbers. They are better understood as contestations about different shades of wrong.