Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Night lights data are increasingly used in applied economics, almost always from the Defense Meteorological Satellite Program (DMSP). These data are old, with production ending in 2013, and are flawed by blurring, lack of calibration and top‐coding. These inaccuracies in DMSP data cause mean‐reverting errors. This paper shows newer and better VIIRS night lights data have 80% higher predictive power for real GDP in a cross‐section of 269 European NUTS2 regions. Spatial inequality is greatly understated with DMSP data, especially for the most densely populated regions. A Pareto correction for top‐coding of DMSP data has a modest effect.