Tracking the development of cities in emerging economies is difficult with conventional data. This paper shows that nighttime lights can be used as a reliable proxy for economic activity at the city level, provided they are first corrected for top-coding. The commonly-used satellite images of nighttime light intensity fail to capture the true brightness of larger cities. We present a stylized model of urban luminosity and empirical evidence which both suggest that these ‘top lights’ can be characterized by a Pareto distribution or similarly heavy-tailed distributions. We then propose a correction procedure that recovers the full distribution of city lights. Our results show that the brightest cities account for nearly a third of global light output. Applying this approach to cities in Sub-Saharan Africa, we find that primate cities are outgrowing secondary cities. Contrary to the top-coded data, our data show that differences at the intensive margin drive the differential in relative growth rates across city types.