More and more novel data sources are becoming available for researchers. One example are images of the night sky. “Petabytes of satellite imagery have become publicly accessible at increasing resolution, many algorithms for extracting meaningful social science information from these images are now routine, and modern cloud- based processing power allows these algorithms to be run at global scale.” 
Measuring the Real Gross Domestic Product (GDP) “is at the heart of macroeconomic analysis”, but it can be inaccurate due to lack of statistical capacity or mis-measurement of the economy. In this research paper Yingyao Hu und Jiaxiong Yao  analyse how to improve GDP measurement using satellite recorded nighttime lights. Using public available Data from the National Oceanic and Atmospheric Administration and the Visible Infrared Imaging Radiometer Suite they show that a light predicted GDP measure does improve on the official measure of GDP in middle and low income countries, but not in high and very low income countries, for different reasons. In high income countries “nighttime lights are bright enough to reach the saturation level of satellite sensors and hence may not adequately reflect variations in economic activity“. In very low income countries for example in Malawi the light intensity is almost zero at night because of a “paltry access to electricity in the country”. However, in middle and low income countries their approach can play a big role.
They also show that that it is be optimal to use a weighted average of the light-measured GDP and the official measure with the weight of the light-measured GDP being between 20 and 35 percent. This means also “that the relationship between nighttime lights and real GDP may be nonlinear”.
As described in  other granular measures of income, electricity use and development are possible to construct from the night sky images. It allows to provide novel indicators for economic policy and answer important economic question in new ways.