National statistical systems are the enterprises tasked with collecting, validating and reporting societal attributes. These data serve many purposesthey allow governments to improve services, economic actors to traverse markets, and academics to assess social theories. National statistical systems vary in quality, especially in developing countries. This study examines determinants of national statistical capacity in developing countries, focusing on the impact of general purpose technologies (GPTs). Just as technological progress helps to explain differences in economic growth, states with markets with greater technological attainment (specifically, general purpose technologies) arguably have greater capacity for gathering and processing quality data. Analysis using panel methods shows a strong, statistically significant positive linear relationship between GPTs and national statistical capacity. There is no evidence to support a non-linear function in this relationship. Which is to say, there does not appear to be a marginal depreciating National Statistical Capacity benefit associated with increases in GPTs. example, in 2010, the national statistical system of one developing country, Ghana, erroneously estimated their GDP and issued a revision that raised the statistic by some 60% (Jerven 2013, Devarajan 2013), the effect of which being an overnight reclassification of Ghana from a lowincome to middle-income country (Jerven 2013); the implications of these issues are profound for foreign aid, lending, commerce, development and foreign investment. The response from the international economic development community was a call for serious reflection on Africa's socalled "statistical tragedy" (Devarajan 2013) and reinforced support for international efforts to evaluate and improve national statistical systems (e.g., Willoughby 2008). Thus, serious