Abstract: 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 almost 300 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.
Persistent link: https://EconPapers.repec.org/RePEc:csa:wpaper:2020-08