ABSTRACT
There is a growing consensus among international observers that official statistics in many subSaharan African countries are woefully inadequate and unreliable (Jerven, 2013), what Devarajan (2013) calls a ‘statistical tragedy’. In response to this tragedy, the UN High Level Panel on post-2015 development goals has called for a ‘data revolution’ to improve tracking of economic and social indicators in Africa and the rest of the developing world (United Nations, 2013). The agenda emerging around these discussions has tended to assume that more money and better technology will solve the problem, focusing on an expansion of survey data collection efforts, and a push for national governments to disseminate information under open data protocols (Caeyers, Chalmers, & De Weerdt, 2012; Demombynes, 2012). Do these solutions address the underlying causes of bad statistics? Relatively less attention has been
paid to understanding why national statistics systems became so badly broken in the first place, or to analysing the perverse incentives which any data revolution in sub-Saharan Africa must overcome. We attempt to fill this gap by documenting systematic discrepancies between data sources on key development indicators across a large sample of countries. By necessity, we focus on cases where multiple independent sources report statistics on ostensibly comparable development indicators.1 For this, we draw on cross-national data within Africa on primary school enrolment and vaccination rates taken from the Demographic and Health Surveys (DHS), and contrast it with data from education and health management information systems maintained by line ministries.2
